Examination of Genome Homogeneity in Prokaryotes Using Genomic Signatures

Background

DNA word frequencies, normalized for genomic AT content, are remarkably stable within prokaryotic genomes and are therefore said to reflect a “genomic signature.” The genomic signatures can be used to phylogenetically classify organisms from arbitrary sampled DNA. Genomic signatures can also be used to search for horizontally transferred DNA or DNA regions subjected to special selection forces. Thus, the stability of the genomic signature can be used as a measure of genomic homogeneity. The factors associated with the stability of the genomic signatures are not known, and this motivated us to investigate further. We analyzed the intra-genomic variance of genomic signatures based on AT content normalization (0^th order Markov model) as well as genomic signatures normalized by smaller DNA words (1^st and 2^nd order Markov models) for 636 sequenced prokaryotic genomes. Regression models were fitted, with intra-genomic signature variance as the response variable, to a set of factors representing genomic properties such as genomic AT content, genome size, habitat, phylum, oxygen requirement, optimal growth temperature and oligonucleotide usage variance (OUV, a measure of oligonucleotide usage bias), measured as the variance between genomic tetranucleotide frequencies and Markov chain approximated tetranucleotide frequencies, as predictors.

Principal Findings

Regression analysis revealed that OUV was the most important factor (p<0.001) determining intra-genomic homogeneity as measured using genomic signatures. This means that the less random the oligonucleotide usage is in the sense of higher OUV, the more homogeneous the genome is in terms of the genomic signature. The other factors influencing variance in the genomic signature (p<0.001) were genomic AT content, phylum and oxygen requirement.

Conclusions

Genomic homogeneity in prokaryotes is intimately linked to genomic GC content, oligonucleotide usage bias (OUV) and aerobiosis, while oligonucleotide usage bias (OUV) is associated with genomic GC content, aerobiosis and habitat.     

Resolving Prokaryotic Taxonomy without rRNA: Longer Oligonucleotide Word Lengths Improve Genome and Metagenome Taxonomic Classification

Oligonucleotide signatures, especially tetranucleotide signatures, have been used as method for homology binning by exploiting an organism’s inherent biases towards the use of specific oligonucleotide words. Tetranucleotide signatures have been especially useful in environmental metagenomics samples as many of these samples contain organisms from poorly classified phyla which cannot be easily identified using traditional homology methods, including NCBI BLAST. This study examines oligonucleotide signatures across 1,424 completed genomes from across the tree of life, substantially expanding upon previous work. A comprehensive analysis of mononucleotide through nonanucleotide word lengths suggests that longer word lengths substantially improve the classification of DNA fragments across a range of sizes of relevance to high throughput sequencing. We find that, at present, heptanucleotide signatures represent an optimal balance between prediction accuracy and computational time for resolving taxonomy using both genomic and metagenomic fragments. We directly compare the ability of tetranucleotide and heptanucleotide world lengths (tetranucleotide signatures are the current standard for oligonucleotide word usage analyses) for taxonomic binning of metagenome reads. We present evidence that heptanucleotide word lengths consistently provide more taxonomic resolving power, particularly in distinguishing between closely related organisms that are often present in metagenomic samples. This implies that longer oligonucleotide word lengths should replace tetranucleotide signatures for most analyses. Finally, we show that the application of longer word lengths to metagenomic datasets leads to more accurate taxonomic binning of DNA scaffolds and have the potential to substantially improve taxonomic assignment and assembly of metagenomic data.     

Investigations of oligonucleotide usage variance within and between prokaryotes

Oligonucleotide usage in archaeal and bacterial genomes can be linked to a number of properties, including codon usage (trinucleotides), DNA base-stacking energy (dinucleotides), and DNA structural conformation (di- to tetranucleotides). We wanted to assess the statistical information potential of different DNA ‘word-sizes’ and explore how oligonucleotide frequencies differ in coding and non-coding regions. In addition, we used oligonucleotide frequencies to investigate DNA composition and how DNA sequence patterns change within and between prokaryotic organisms. Among the results found was that prokaryotic chromosomes can be described by hexanucleotide frequencies, suggesting that prokaryotic DNA is predominantly short range correlated, i.e., information in prokaryotic genomes is encoded in short oligonucleotides. Oligonucleotide usage varied more within AT-rich and host-associated genomes than in GC-rich and free-living genomes, and this variation was mainly located in non-coding regions. Bias (selectional pressure) in tetranucleotide usage correlated with GC content, and coding regions were more biased than non-coding regions. Non-coding regions were also found to be approximately 5.5% more AT-rich than coding regions, on average, in the 402 chromosomes examined. Pronounced DNA compositional differences were found both within and between AT-rich and GC-rich genomes. GC-rich genomes were more similar and biased in terms of tetranucleotide usage in non-coding regions than AT-rich genomes. The differences found between AT-rich and GC-rich genomes may possibly be attributed to lifestyle, since tetranucleotide usage within host-associated bacteria was, on average, more dissimilar and less biased than free-living archaea and bacteria.     

A genomic schism in birds revealed by phylogenetic analysis of DNA strings

The molecular systematics of vertebrates has been based entirely on alignments of primary structures of macromolecules; however, higher order features of DNA sequences not used in traditional studies also contain valuable phylogenetic information. Recent molecular data sets conflict over the phylogenetic placement of flightless birds (ratites - paleognaths), but placement of this clade critically influences interpretation of character change in birds. To help resolve this issue, we applied a new bioinformatics approach to the largest molecular data set currently available. We distilled nearly one megabase (1 million base pairs) of heterogeneous avian genomic DNA from 20 birds and an alligator into genomic signatures, defined as the complete set of frequencies of short sequence motifs (strings), thereby providing a way to directly compare higher order features of nonhomologous DNA sequences. Phylogenetic analysis and principal component analysis of the signatures strongly support the traditional hypothesis of basal ratites and monophyly of the nonratite birds (neognaths) and imply that ratite genomes are linguistically primitive within birds, despite their base compositional similarity to neognath genomes. Our analyses show further that the phylogenetic signal of genomic signatures are strongest among deep splits within vertebrates. Despite clear problems with phylogenetic analysis of genomic signatures, our study raises intriguing issues about the biological and genomic differences that fundamentally differentiate paleognaths and neognaths.     

Ecogenomics and genome landscapes of marine Pseudoalteromonas phage H105/1

Marine phages have an astounding global abundance and ecological impact. However, little knowledge is derived from phage genomes, as most of the open reading frames in their small genomes are unknown, novel proteins. To infer potential functional and ecological relevance of sequenced marine Pseudoalteromonas phage H105/1, two strategies were used. First, similarity searches were extended to include six viral and bacterial metagenomes paired with their respective environmental contextual data. This approach revealed ‘ecogenomic'' patterns of Pseudoalteromonas phage H105/1, such as its estuarine origin. Second, intrinsic genome signatures (phylogenetic, codon adaptation and tetranucleotide (tetra) frequencies) were evaluated on a resolved intra-genomic level to shed light on the evolution of phage functional modules. On the basis of differential codon adaptation of Phage H105/1 proteins to the sequenced Pseudoalteromonas spp., regions of the phage genome with the most ‘host''-adapted proteins also have the strongest bacterial tetra signature, whereas the least ‘host''-adapted proteins have the strongest phage tetra signature. Such a pattern may reflect the evolutionary history of the respective phage proteins and functional modules. Finally, analysis of the structural proteome identified seven proteins that make up the mature virion, four of which were previously unknown. This integrated approach combines both novel and classical strategies and serves as a model to elucidate ecological inferences and evolutionary relationships from phage genomes that typically abound with unknown gene content.     

Genetic structure of three fosmid-fragments encoding 16S rRNA genes of the Miscellaneous Crenarchaeotic Group (MCG): implications for physiology and evolution of marine sedimentary archaea

Archaea of the Miscellaneous Crenarchaeotic Group (MCG) exist widely in soil, freshwater and marine sediments of both surface and subsurface. However, current knowledge about this group is limited to its phylogenetic diversity. An archaeal 16S library was constructed from a sediment sample from the South China Sea, which was dominated by MCG and Marine Group I (MG-I). A metagenomic library was constructed from the same sediment sample, and three MCG fosmids (E6-3G, E37-7F and E48-1C) containing 16S rRNA genes were screened. Annotation showed that the three genomic fragments encode a variety of open reading frames (ORFs) that are potentially homologous to important functional genes related to lipid biosynthesis, energy metabolism, and resistance to oxidants. No colinear regions were found between MCG fosmids and reported archaeal genomic fragments or genomes, suggesting that the MCG archaea are quite different from the sequenced archaea in gene arrangement. Analyses of both the phylogenies of 16S rRNA genes and several informational processing genes and nucleotide frequencies showed that MCG archaea are distinct from MG-I plus relatives. In addition, tetranucleotide frequency analysis in combination with phylogenetic analysis suggested that some fragments in the MCG fosmids are probably derived from non-MCG or non-archaeal genomes.     

Whole Genome Sequence Analysis Using JSpecies Tool Establishes Clonal Relationships between Listeria monocytogenes Strains from Epidemiologically Unrelated Listeriosis Outbreaks

In an effort to build a comprehensive genomic approach to food safety challenges, the FDA has implemented a whole genome sequencing effort, GenomeTrakr, which involves the sequencing and analysis of genomes of foodborne pathogens. As a part of this effort, we routinely sequence whole genomes of Listeria monocytogenes (Lm) isolates associated with human listeriosis outbreaks, as well as those isolated through other sources. To rapidly establish genetic relatedness of these genomes, we evaluated tetranucleotide frequency analysis via the JSpecies program to provide a cursory analysis of strain relatedness. The JSpecies tetranucleotide (tetra) analysis plots standardized (z-score) tetramer word frequencies of two strains against each other and uses linear regression analysis to determine similarity (r²). This tool was able to validate the close relationships between outbreak related strains from four different outbreaks. Included in this study was the analysis of Lm strains isolated during the recent caramel apple outbreak and stone fruit incident in 2014. We identified that many of the isolates from these two outbreaks shared a common 4b variant (4bV) serotype, also designated as IVb-v1, using a qPCR protocol developed in our laboratory. The 4bV serotype is characterized by the presence of a 6.3 Kb DNA segment normally found in serotype 1/2a, 3a, 1/2c and 3c strains but not in serotype 4b or 1/2b strains. We decided to compare these strains at a genomic level using the JSpecies Tetra tool. Specifically, we compared several 4bV and 4b isolates and identified a high level of similarity between the stone fruit and apple 4bV strains, but not the 4b strains co-identified in the caramel apple outbreak or other 4b or 4bV strains in our collection. This finding was further substantiated by a SNP-based analysis. Additionally, we were able to identify close relatedness between isolates from clinical cases from 1993–1994 and a single case from 2011 as well as links between two isolates from over 30 years ago. The identification of these potential links shows that JSpecies Tetra analysis can be a useful tool in rapidly assessing genetic relatedness of Lm isolates during outbreak investigations and for comparing historical isolates. Our analyses led to the identification of a highly related clonal group involved in two separate outbreaks, stone fruit and caramel apple, and suggests the possibility of a new genotype that may be better adapted for certain foods and/or environment.     

Visualization of Pseudomonas genomic structure by abundant 8–14mer oligonucleotides

Under- and over-represented mono- to hexanucleotides are signatures of bacterial genomes, but the compositional biases of octa- to tetradecanucleotides have not yet been explored. Thirteen completely sequenced genomes of the Pseudomonas genus were searched for highly overrepresented 8–14mers. Between 59–989 overrepresented 8–14mers were found to exceed the applied threshold value. All genomic data sets of the 13 strains showed a consistent pattern, with individual oligomers clustering in either non-coding or coding regions. Non-coding oligonucleotides were typically part of longer repeats. Coding oligonucleotides were evenly distributed in the core genome, preferred one reading frame and matched with the local tetranucleotide usage patterns. Genomic islands were recognized by the depletion of overrepresented oligonucleotides. Several mainly coding 8–14mers occurred in genomes on average every 10 000 bp or less. Such frequently occurring 8–14mers could become useful markers for species identification. In the future of next-generation ultra-high throughput DNA sequencing, the composition of bacterial metagenomes may be quantified by scanning the primary sequence reads for these 8–14mer markers.     

Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes

Introduction

Genomic base composition ranges from less than 25% AT to more than 85% AT in prokaryotes. Since only a small fraction of prokaryotic genomes is not protein coding even a minor change in genomic base composition will induce profound protein changes. We examined how amino acid and codon frequencies were distributed in over 2000 microbial genomes and how these distributions were affected by base compositional changes. In addition, we wanted to know how genome-wide amino acid usage was biased in the different genomes and how changes to base composition and mutations affected this bias. To carry this out, we used a Generalized Additive Mixed-effects Model (GAMM) to explore non-linear associations and strong data dependences in closely related microbes; principal component analysis (PCA) was used to examine genomic amino acid- and codon frequencies, while the concept of relative entropy was used to analyze genomic mutation rates.

Results

We found that genomic amino acid frequencies carried a stronger phylogenetic signal than codon frequencies, but that this signal was weak compared to that of genomic %AT. Further, in contrast to codon usage bias (CUB), amino acid usage bias (AAUB) was differently distributed in AT- and GC-rich genomes in the sense that AT-rich genomes did not prefer specific amino acids over others to the same extent as GC-rich genomes. AAUB was also associated with relative entropy; genomes with low AAUB contained more random mutations as a consequence of relaxed purifying selection than genomes with higher AAUB.

Conclusion

Genomic base composition has a substantial effect on both amino acid- and codon frequencies in bacterial genomes. While phylogeny influenced amino acid usage more in GC-rich genomes, AT-content was driving amino acid usage in AT-rich genomes. We found the GAMM model to be an excellent tool to analyze the genomic data used in this study.     

Human and mouse switch-like genes share common transcriptional regulatory mechanisms for bimodality

Background

The increasing number of sequenced prokaryotic genomes contains a wealth of genomic data that needs to be effectively analysed. A set of statistical tools exists for such analysis, but their strengths and weaknesses have not been fully explored. The statistical methods we are concerned with here are mainly used to examine similarities between archaeal and bacterial DNA from different genomes. These methods compare observed genomic frequencies of fixed-sized oligonucleotides with expected values, which can be determined by genomic nucleotide content, smaller oligonucleotide frequencies, or be based on specific statistical distributions. Advantages with these statistical methods include measurements of phylogenetic relationship with relatively small pieces of DNA sampled from almost anywhere within genomes, detection of foreign/conserved DNA, and homology searches. Our aim was to explore the reliability and best suited applications for some popular methods, which include relative oligonucleotide frequencies (ROF), di- to hexanucleotide zero'th order Markov methods (ZOM) and 2.order Markov chain Method (MCM). Tests were performed on distant homology searches with large DNA sequences, detection of foreign/conserved DNA, and plasmid-host similarity comparisons. Additionally, the reliability of the methods was tested by comparing both real and random genomic DNA.

Results

Our findings show that the optimal method is context dependent. ROFs were best suited for distant homology searches, whilst the hexanucleotide ZOM and MCM measures were more reliable measures in terms of phylogeny. The dinucleotide ZOM method produced high correlation values when used to compare real genomes to an artificially constructed random genome with similar %GC, and should therefore be used with care. The tetranucleotide ZOM measure was a good measure to detect horizontally transferred regions, and when used to compare the phylogenetic relationships between plasmids and hosts, significant correlation (R ² = 0.4) was found with genomic GC content and intra-chromosomal homogeneity.

Conclusion

The statistical methods examined are fast, easy to implement, and powerful for a number of different applications involving genomic sequence comparisons. However, none of the measures examined were superior in all tests, and therefore the choice of the statistical method should depend on the task at hand.     

Genomic comparisons of <Emphasis Type="Italic">Brucella</Emphasis> spp. and closely related bacteria using base compositional and proteome based methods

Background  

Classification of bacteria within the genus Brucella has been difficult due in part to considerable genomic homogeneity between the different species and biovars, in spite of clear differences in phenotypes. Therefore, many different methods have been used to assess Brucella taxonomy. In the current work, we examine 32 sequenced genomes from genus Brucella representing the six classical species, as well as more recently described species, using bioinformatical methods. Comparisons were made at the level of genomic DNA using oligonucleotide based methods (Markov chain based genomic signatures, genomic codon and amino acid frequencies based comparisons) and proteomes (all-against-all BLAST protein comparisons and pan-genomic analyses).     

Multiple variants of the archaeal DNA rudivirus SIRV1 in a single host and a novel mechanism of genomic variation

The DNA rudivirus SIRV1 of the hyperthermophilic archaeon Sulfolobus shows exceptional properties. Viral isolates invariably contain a population of variants with different but closely related genomes. Upon propagation in a given host strain, one or more genomes dominate in the viral population. However, upon passage into a new host strain the viral population undergoes changes and other dominant variants are selected. Sequencing and analysis of the variant genomes revealed that major differences occur in gene order, gene size and gene content at localized genomic sites. A previously unknown mechanism of genomic rearrangement involving putative 12 bp archaeal introns appears to facilitate alteration of the variant genomes. Inter-genomic recombination between the different variants also occurs. The variant genomes exhibit signature tetranucleotide sequences near their putative sites for replication initiation.     

Comprehensive DNA signature discovery and validation

DNA signatures are nucleotide sequences that can be used to detect the presence of an organism and to distinguish that organism from all other species. Here we describe Insignia, a new, comprehensive system for the rapid identification of signatures in the genomes of bacteria and viruses. With the availability of hundreds of complete bacterial and viral genome sequences, it is now possible to use computational methods to identify signature sequences in all of these species, and to use these signatures as the basis for diagnostic assays to detect and genotype microbes in both environmental and clinical samples. The success of such assays critically depends on the methods used to identify signatures that properly differentiate between the target genomes and the sample background. We have used Insignia to compute accurate signatures for most bacterial genomes and made them available through our Web site. A sample of these signatures has been successfully tested on a set of 46 Vibrio cholerae strains, and the results indicate that the signatures are highly sensitive for detection as well as specific for discrimination between these strains and their near relatives. Our approach, whereby the entire genomic complement of organisms are compared to identify probe targets, is a promising method for diagnostic assay development, and it provides assay designers with the flexibility to choose probes from the most relevant genes or genomic regions. The Insignia system is freely accessible via a Web interface and has been released as open source software at: http://insignia.cbcb.umd.edu.     

Chromatin accessibility of primary human cancers ties regional mutational processes and signatures with tissues of origin

Somatic mutations in cancer genomes are associated with DNA replication timing (RT) and chromatin accessibility (CA), however these observations are based on normal tissues and cell lines while primary cancer epigenomes remain uncharacterised. Here we use machine learning to model megabase-scale mutation burden in 2,500 whole cancer genomes and 17 cancer types via a compendium of 900 CA and RT profiles covering primary cancers, normal tissues, and cell lines. CA profiles of primary cancers, rather than those of normal tissues, are most predictive of regional mutagenesis in most cancer types. Feature prioritisation shows that the epigenomes of matching cancer types and organ systems are often the strongest predictors of regional mutation burden, highlighting disease-specific associations of mutational processes. The genomic distributions of mutational signatures are also shaped by the epigenomes of matched cancer and tissue types, with SBS5/40, carcinogenic and unknown signatures most accurately predicted by our models. In contrast, fewer associations of RT and regional mutagenesis are found. Lastly, the models highlight genomic regions with overrepresented mutations that dramatically exceed epigenome-derived expectations and show a pan-cancer convergence to genes and pathways involved in development and oncogenesis, indicating the potential of this approach for coding and non-coding driver discovery. The association of regional mutational processes with the epigenomes of primary cancers suggests that the landscape of passenger mutations is predominantly shaped by the epigenomes of cancer cells after oncogenic transformation.     

Phylogenetic and metagenomic analysis of Verrucomicrobia in former agricultural grassland soil

The bacterial phylum Verrucomicrobia has a widespread distribution, and is known to be one of the most common and diverse phyla in soil habitats. However, members of this phylum have typically been recalcitrant to cultivation methods, hampering the study of this presumably important bacterial group. In this study, we examine the phylogenetic diversity of the Verrucomicrobia in a former agricultural field and gain access to genomic information via a metagenomic approach. We examined Verrucomicrobia -like 16S rRNA gene sequences recovered from general bacterial and phylum-specific libraries, revealing a dominance of subdivisions 1 and 2. A PCR-based screening method was developed to identify inserts containing verrucomicrobial 16S rRNA genes within a large-insert metagenomic library, and on screening of 28 800 clones, four fosmids were identified as containing verrucomicrobial genomic DNA. Full-length sequencing of fosmid inserts and gene annotation identified a total of 98 ORFs, representing a range of functions. No conservation of gene order was observed adjacent to the ribosomal operons. Fosmid inserts were further analyzed for tetranucleotide frequencies to identify remnants of past horizontal gene transfer events. The metagenomic approach utilized proved to be suitable for the recovery of verrucomicrobial genomic DNA, thereby providing a window into the genomes of members of this important, yet poorly characterized, bacterial phylum.     

Detection and characterization of horizontal transfers in prokaryotes using genomic signature

Horizontal DNA transfer is an important factor of evolution and participates in biological diversity. Unfortunately, the location and length of horizontal transfers (HTs) are known for very few species. The usage of short oligonucleotides in a sequence (the so-called genomic signature) has been shown to be species-specific even in DNA fragments as short as 1 kb. The genomic signature is therefore proposed as a tool to detect HTs. Since DNA transfers originate from species with a signature different from those of the recipient species, the analysis of local variations of signature along recipient genome may allow for detecting exogenous DNA. The strategy consists in (i) scanning the genome with a sliding window, and calculating the corresponding local signature (ii) evaluating its deviation from the signature of the whole genome and (iii) looking for similar signatures in a database of genomic signatures. A total of 22 prokaryote genomes are analyzed in this way. It has been observed that atypical regions make up ~6% of each genome on the average. Most of the claimed HTs as well as new ones are detected. The origin of putative DNA transfers is looked for among ~12000 species. Donor species are proposed and sometimes strongly suggested, considering similarity of signatures. Among the species studied, Bacillus subtilis, Haemophilus Influenzae and Escherichia coli are investigated by many authors and give the opportunity to perform a thorough comparison of most of the bioinformatics methods used to detect HTs.     

Prokaryotic gene finding based on physicochemical characteristics of codons calculated from molecular dynamics simulations

An ab initio model for gene prediction in prokaryotic genomes is proposed based on physicochemical characteristics of codons calculated from molecular dynamics (MD) simulations. The model requires a specification of three calculated quantities for each codon: the double-helical trinucleotide base pairing energy, the base pair stacking energy, and an index of the propensity of a codon for protein-nucleic acid interactions. The base pairing and stacking energies for each codon are obtained from recently reported MD simulations on all unique tetranucleotide steps, and the third parameter is assigned based on the conjugate rule previously proposed to account for the wobble hypothesis with respect to degeneracies in the genetic code. The third interaction propensity parameter values correlate well with ab initio MD calculated solvation energies and flexibility of codon sequences as well as codon usage in genes and amino acid composition frequencies in ∼175,000 protein sequences in the Swissprot database. Assignment of these three parameters for each codon enables the calculation of the magnitude and orientation of a cumulative three-dimensional vector for a DNA sequence of any length in each of the six genomic reading frames. Analysis of 372 genomes comprising ∼350,000 genes shows that the orientations of the gene and nongene vectors are well differentiated and make a clear distinction feasible between genic and nongenic sequences at a level equivalent to or better than currently available knowledge-based models trained on the basis of empirical data, presenting a strong support for the possibility of a unique and useful physicochemical characterization of DNA sequences from codons to genomes.