Genomic island identification in Vibrio vulnificus reveals significant genome plasticity in this human pathogen

Genomic islands (GIs) are large chromosomal regions present in a subset of bacterial strains that increase the fitness of the organism under specific conditions. We compared the complete genome sequences of two Vibrio vulnificus strains YJ016 and CMCP6 and identified 14 regions (ranging in size from 14 to 117 kb), which had the characteristics of GIs. Bioinformatic analysis of these 14 GI regions identified the presence of phage-like integrase genes, aberrant GC content and genome signature (dinucleotide frequency) within each GI compared with the core genome indicating that these regions were acquired from an anomalous source. We examined the distribution of the nine GIs from strain YJ016 among 27 V. vulnificus isolates and found that most GIs were absent from the majority of these isolates. The chromosomal insertion sites of three GIs were adjacent to tRNA sites, which contained novel horizontally acquired DNA in all six available sequenced Vibrionaceae genomes. Supplementary information: Supplementary data are available at Bioinformatics online.     

A general system for studying protein-protein interactions in Gram-negative bacteria

One of the most promising methods for large-scale studies of protein interactions is isolation of an affinity-tagged protein with its in vivo interaction partners, followed by mass spectrometric identification of the copurified proteins. Previous studies have generated affinity-tagged proteins using genetic tools or cloning systems that are specific to a particular organism. To enable protein-protein interaction studies across a wider range of Gram-negative bacteria, we have developed a methodology based on expression of affinity-tagged "bait" proteins from a medium copy-number plasmid. This construct is based on a broad-host-range vector backbone (pBBR1MCS5). The vector has been modified to incorporate the Gateway DEST vector recombination region, to facilitate cloning and expression of fusion proteins bearing a variety of affinity, fluorescent, or other tags. We demonstrate this methodology by characterizing interactions among subunits of the DNA-dependent RNA polymerase complex in two metabolically versatile Gram-negative microbial species of environmental interest, Rhodopseudomonas palustris CGA010 and Shewanella oneidensis MR-1. Results compared favorably with those for both plasmid and chromosomally encoded affinity-tagged fusion proteins expressed in a model organism, Escherichia coli.     

Homogeneous versus heterogeneous probes for microbial ecological microarrays

Microbial ecological microarrays have been developed for investigating the composition and functions of microorganism communities in environmental niches. These arrays include microbial identification microarrays, which use oligonucleotides, gene fragments or microbial genomes as probes. In this article, the advantages and disadvantages of each type of probe are reviewed. Oligonucleotide probes are currently useful for probing uncultivated bacteria that are not amenable to gene fragment probing, whereas the functional gene fragments amplified randomly from microbial genomes require phylogenetic and hierarchical categorization before use as microbial identification probes, despite their high resolution for both specificity and sensitivity. Until more bacteria are sequenced and gene fragment probes are thoroughly validated, heterogeneous bacterial genome probes will provide a simple, sensitive and quantitative tool for exploring the ecosystem structure.     

Freshwater bacterial lifestyles inferred from comparative genomics

While micro‐organisms actively mediate and participate in freshwater ecosystem services, we know little about freshwater microbial genetic diversity. Genome sequences are available for many bacteria from the human microbiome and the ocean (over 800 and 200, respectively), but only two freshwater genomes are currently available: the streamlined genomes of Polynucleobacter necessarius ssp. asymbioticus and the Actinobacterium AcI‐B1. Here, we sequenced and analysed draft genomes of eight phylogentically diverse freshwater bacteria exhibiting a range of lifestyle characteristics. Comparative genomics of these bacteria reveals putative freshwater bacterial lifestyles based on differences in predicted growth rate, capability to respond to environmental stimuli and diversity of useable carbon substrates. Our conceptual model based on these genomic characteristics provides a foundation on which further ecophysiological and genomic studies can be built. In addition, these genomes greatly expand the diversity of existing genomic context for future studies on the ecology and genetics of freshwater bacteria.     

Use of competitive DNA hybridization to identify differences in the genomes of bacteria

Although recent technological advances in DNA sequencing and computational biology now allow scientists to compare entire microbial genomes, comparisons of closely related bacterial species and individual isolates by whole-genome sequencing approaches remains prohibitively expensive for most laboratories. Here we report the development and testing of a biochemical approach for targeted sequencing of only those chromosomal regions that differ between two DNA preparations. The method, designated GFE (genome fragment enrichment) uses competitive solution hybridization and positive selection to obtain genomic DNA fragments that are present in one pool of fragments but not another. Repeated comparisons of the genomes of Enterococcus faecalis and E. faecium led to the identification of 225 putative genome-specific DNA fragments. Species and strain variations within these fragments were confirmed by both experimental and bioinformatic analyses. The E. faecalis genome-specific sequences identified included both a preponderance of those predicted to encode surface-exposed proteins, as well as several previously described unique marker regions embedded within highly conserved rrn operons. The GFE strategy we describe efficiently identified genomic differences between two enterococcal genomes, and will be widely applicable for studying genetic variation among closely related bacterial species.     

Genetic comparison of Bacillus anthracis and its close relatives using amplified fragment length polymorphism and polymerase chain reaction analysis

Amplified fragment length polymorphism (AFLP) analysis allows a rapid, relatively simple analysis of a large portion of a microbial genome, providing information about the species and its phylogenetic relationship to other microbes (Vos et al. 1995). The method simply surveys the genome for length and sequence polymorphisms. The AFLP pattern identified can be used for comparison to the genomes of other species. Unlike other methods, it does not rely on analysis of a single genetic locus that may bias the interpretation of results and does not require any prior knowledge of the targeted organism. Moreover, a standard set of reagents can be applied to any species without using species-specific information or molecular probes. We are using AFLP analysis to rapidly identify different bacterial species. A comparison of AFLP profiles generated from a large battery of Bacillus anthracis strains shows very little variability among different isolates (Keim et al. 1997). By contrast, there is a significant difference between AFLP profiles generated for any B. anthracis strain and even the most closely related Bacillus species. Sufficient variability is apparent among all known microbial species to allow phylogenetic analysis based on large numbers of genetically unlinked loci. These striking differences among AFLP profiles allow unambiguous identification of previously identified species and phylogenetic placement of newly characterized isolates relative to known species based on a large number of independent genetic loci. Data generated thus far show that the method provides phylogenetic analyses that are consistent with other widely accepted phylogenetic methods. However, AFLP analysis provides a more detailed analysis of the targets and samples a much larger portion of the genome. Consequently, it provides an inexpensive, rapid means of characterizing microbial isolates to further differentiate among strains and closely related microbial species. Such information cannot be rapidly generated by other means. AFLP sample analysis quickly generates a very large amount of molecular information about microbial genomes. However, this information cannot be analysed rapidly using manual methods. We are developing a large archive of electronic AFLP signatures that is being used to identify isolates collected from medical, veterinary, forensic and environmental samples. We are also developing the computational packages necessary to rapidly and unambiguously analyse the AFLP profiles and conduct a phylogenetic comparison of these data relative to information already in our database. We will use this archive and the associated algorithms to determine the species identity of previously uncharacterized isolates and place them phylogenetically relative to other microbes based on their AFLP signatures. This study provides significant new information about microbes with environmental, veterinary and medical significance. This information can be used in further studies to understand the relationships among these species and the factors that distinguish them from one another. It should also allow the identification of unique factors that contribute to important microbial traits, including pathogenicity and virulence. We are also using AFLP data to identify, isolate and sequence DNA fragments that are unique to particular microbial species and strains. The fragment patterns and sequence information provide insights into the complexity and organization of bacterial genomes relative to one another. They also provide the information necessary for the development of species-specific polymerase chain reaction primers that can be used to interrogate complex samples for the presence of B. anthracis, other microbial pathogens or their remnants.     

Implications of strain- and species-level sequence divergence for community and isolate shotgun proteomic analysis

The recent surge in microbial genomic sequencing, combined with the development of high-throughput liquid chromatography-mass-spectrometry-based (LC/LC-MS/MS) proteomics, has raised the question of the extent to which genomic information of one strain or environmental sample can be used to profile proteomes of related strains or samples. Even with decreasing sequencing costs, it remains impractical to obtain genomic sequence for every strain or sample analyzed. Here, we evaluate how shotgun proteomics is affected by amino acid divergence between the sample and the genomic database using a probability-based model and a random mutation simulation model constrained by experimental data. To assess the effects of nonrandom distribution of mutations, we also evaluated identification levels using in silico peptide data from sequenced isolates with average amino acid identities (AAI) varying between 76 and 98%. We compared the predictions to experimental protein identification levels for a sample that was evaluated using a database that included genomic information for the dominant organism and for a closely related variant (95% AAI). The range of models set the boundaries at which half of the proteins in a proteomic experiment can be identified to be 77-92% AAI between orthologs in the sample and database. Consistent with this prediction, experimental data indicated loss of half the identifiable proteins at 90% AAI. Additional analysis indicated a 6.4% reduction of the initial protein coverage per 1% amino acid divergence and total identification loss at 86% AAI. Consequently, shotgun proteomics is capable of cross-strain identifications but avoids most cross-species false positives.     

Multiple Rieske proteins in prokaryotes: Where and why?

Many microbial genomes have been sequenced in the recent years. Multiple genes encoding Rieske iron-sulfur proteins, which are subunits of cytochrome bc-type complexes or oxygenases, have been detected in many pro- and eukaryotic genomes. The diversity of substrates, co-substrates and reactions offers obvious explanations for the diversity of the low potential Rieske proteins associated with oxygenases, but the physiological significance of the multiple genes encoding high potential Rieske proteins associated with the cytochrome bc-type complexes remains elusive. For some organisms, investigations into the function of the later group of genes have been initiated. Here, we summarize recent finding on the characteristics and physiological functions of multiple high potential Rieske proteins in prokaryotes. We suggest that the existence of multiple high potential Rieske proteins in prokaryotes could be one way of allowing an organism to adapt their electron transfer chains to changing environmental conditions.     

Universal activity-based labeling method for ammonia- and alkane-oxidizing bacteria

The advance of metagenomics in combination with intricate cultivation approaches has facilitated the discovery of novel ammonia-, methane-, and other short-chain alkane-oxidizing microorganisms, indicating that our understanding of the microbial biodiversity within the biogeochemical nitrogen and carbon cycles still is incomplete. The in situ detection and phylogenetic identification of novel ammonia- and alkane-oxidizing bacteria remain challenging due to their naturally low abundances and difficulties in obtaining new isolates from complex samples. Here, we describe an activity-based protein profiling protocol allowing cultivation-independent unveiling of ammonia- and alkane-oxidizing bacteria. In this protocol, 1,7-octadiyne is used as a bifunctional enzyme probe that, in combination with a highly specific alkyne-azide cycloaddition reaction, enables the fluorescent or biotin labeling of cells harboring active ammonia and alkane monooxygenases. Biotinylation of these enzymes in combination with immunogold labeling revealed the subcellular localization of the tagged proteins, which corroborated expected enzyme targets in model strains. In addition, fluorescent labeling of cells harboring active ammonia or alkane monooxygenases provided a direct link of these functional lifestyles to phylogenetic identification when combined with fluorescence in situ hybridization. Furthermore, we show that this activity-based labeling protocol can be successfully coupled with fluorescence-activated cell sorting for the enrichment of nitrifiers and alkane-oxidizing bacteria from complex environmental samples, enabling the recovery of high-quality metagenome-assembled genomes. In conclusion, this study demonstrates a novel, functional tagging technique for the reliable detection, identification, and enrichment of ammonia- and alkane-oxidizing bacteria present in complex microbial communities.Subject terms: Environmental microbiology, Sequencing, Microbiology     

Global detection and characterization of hypothetical proteins in Shewanella oneidensis MR-1 using LC-MS based proteomics

The availability of whole genome sequences has enabled the application of powerful tools for assaying global expression patterns in environmentally relevant bacteria such as Shewanella oneidensis MR-1. A large number of genes in prokaryote genomes, including MR-1, have been annotated as hypothetical, indicating that no similar protein has yet been identified in other organisms. Using high-sensitivity MS coupled with accurate mass and time (AMT) tag methodology, 1078 tryptic peptides were collectively detected in MR-1 cultures, 671 of which were unique to their parent protein. Using only these unique tryptic peptides and a minimum of two peptides per protein, we identified, with high confidence, the expression of 258 hypothetical proteins. These proteins ranged from 3.5 to 139 kDa, with 47 being 100 amino acid residues or less. Using a combination of information including detection in cells grown under specific culture conditions, presence within a specific cell fraction, and predictive algorithms such as PSORT and PSORT-B, possible/plausible functions are proposed for some hypothetical proteins. Further, by applying this approach a number of proteins were found not only to be expressed, but only expressed under certain culturing conditions, thereby suggesting function while at the same time isolating several proteins to distinct locales of the cell. These results demonstrate the utility of the AMT tag methodology for comprehensive profiling of the microbial proteome while confirming the expression of a large number of hypothetical genes.     

Strain/species identification in metagenomes using genome-specific markers

Shotgun metagenome sequencing has become a fast, cheap and high-throughput technology for characterizing microbial communities in complex environments and human body sites. However, accurate identification of microorganisms at the strain/species level remains extremely challenging. We present a novel k-mer-based approach, termed GSMer, that identifies genome-specific markers (GSMs) from currently sequenced microbial genomes, which were then used for strain/species-level identification in metagenomes. Using 5390 sequenced microbial genomes, 8 770 321 50-mer strain-specific and 11 736 360 species-specific GSMs were identified for 4088 strains and 2005 species (4933 strains), respectively. The GSMs were first evaluated against mock community metagenomes, recently sequenced genomes and real metagenomes from different body sites, suggesting that the identified GSMs were specific to their targeting genomes. Sensitivity evaluation against synthetic metagenomes with different coverage suggested that 50 GSMs per strain were sufficient to identify most microbial strains with ≥0.25× coverage, and 10% of selected GSMs in a database should be detected for confident positive callings. Application of GSMs identified 45 and 74 microbial strains/species significantly associated with type 2 diabetes patients and obese/lean individuals from corresponding gastrointestinal tract metagenomes, respectively. Our result agreed with previous studies but provided strain-level information. The approach can be directly applied to identify microbial strains/species from raw metagenomes, without the effort of complex data pre-processing.     

Genome sequencing of five Shewanella baltica strains recovered from the oxic-anoxic interface of the Baltic Sea

Here we describe five Shewanella baltica genomes recovered from the same sample, as well as 12 years apart from the same sampling station. These genomes expand the collection of previously sequenced S. baltica strains and represent a valuable resource for assessing the role of environmental settings on genome adaptation.     

An environmental signature for 323 microbial genomes based on codon adaptation indices

Background

Codon adaptation indices (CAIs) represent an evolutionary strategy to modulate gene expression and have widely been used to predict potentially highly expressed genes within microbial genomes. Here, we evaluate and compare two very different methods for estimating CAI values, one corresponding to translational codon usage bias and the second obtained mathematically by searching for the most dominant codon bias.

Results

The level of correlation between these two CAI methods is a simple and intuitive measure of the degree of translational bias in an organism, and from this we confirm that fast replicating bacteria are more likely to have a dominant translational codon usage bias than are slow replicating bacteria, and that this translational codon usage bias may be used for prediction of highly expressed genes. By analyzing more than 300 bacterial genomes, as well as five fungal genomes, we show that codon usage preference provides an environmental signature by which it is possible to group bacteria according to their lifestyle, for instance soil bacteria and soil symbionts, spore formers, enteric bacteria, aquatic bacteria, and intercellular and extracellular pathogens.

Conclusion

The results and the approach described here may be used to acquire new knowledge regarding species lifestyle and to elucidate relationships between organisms that are far apart evolutionarily.     

Optimizing SNP microarray probe design for high accuracy microbial genotyping

Microarrays to characterize single nucleotide polymorphisms (SNPs) provide a cost-effective and rapid method (under 24 h) to genotype microbes as an alternative to sequencing. We developed a pipeline for SNP discovery and microarray design that scales to 100's of microbial genomes. Here we tested various SNP probe design strategies against 8 sequenced isolates of Bacillus anthracis to compare sequence and microarray data. The best strategy allowed probe length to vary within 32–40 bp to equalize hybridization free energy. This strategy resulted in a call rate of 99.52% and concordance rate of 99.86% for finished genomes. Other probe design strategies averaged substantially lower call rates (94.65–96.41%) and slightly lower concordance rates (99.64–99.80%). These rates were lower for draft than finished genomes, consistent with higher incidence of sequencing errors and gaps. Highly accurate SNP calls were possible in complex soil and blood backgrounds down to 1000 copies, and moderately accurate SNP calls down to 100 spiked copies. The closest genome to the spiked strain was correctly identified at only 10 spiked copies. Discrepancies between sequence and array data did not alter the SNP-based phylogeny, regardless of the probe design strategy, indicating that SNP arrays can accurately place unsequenced isolates on a phylogeny.     

Overcoming species boundaries in peptide identification with Bayesian information criterion-driven error-tolerant peptide search (BICEPS)

Currently, the reliable identification of peptides and proteins is only feasible when thoroughly annotated sequence databases are available. Although sequencing capacities continue to grow, many organisms remain without reliable, fully annotated reference genomes required for proteomic analyses. Standard database search algorithms fail to identify peptides that are not exactly contained in a protein database. De novo searches are generally hindered by their restricted reliability, and current error-tolerant search strategies are limited by global, heuristic tradeoffs between database and spectral information. We propose a Bayesian information criterion-driven error-tolerant peptide search (BICEPS) and offer an open source implementation based on this statistical criterion to automatically balance the information of each single spectrum and the database, while limiting the run time. We show that BICEPS performs as well as current database search algorithms when such algorithms are applied to sequenced organisms, whereas BICEPS only uses a remotely related organism database. For instance, we use a chicken instead of a human database corresponding to an evolutionary distance of more than 300 million years (International Chicken Genome Sequencing Consortium (2004) Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution. Nature 432, 695-716). We demonstrate the successful application to cross-species proteomics with a 33% increase in the number of identified proteins for a filarial nematode sample of Litomosoides sigmodontis.     

SENTRA, a database of signal transduction proteins

SENTRA, available via URL http://wit.mcs.anl.gov/WIT2/Sentra/, is a database of proteins associated with microbial signal transduction. The database currently includes the classical two-component signal transduction pathway proteins and methyl-accepting chemotaxis proteins, but will be expanded to also include other classes of signal transduction systems that are modulated by phosphorylation or methylation reactions. Although the majority of database entries are from prokaryotic systems, eukaroytic proteins with bacterial-like signal transduction domains are also included. Currently SENTRA contains signal transduction proteins in 34 complete and almost completely sequenced prokaryotic genomes, as well as sequences from 243 organisms available in public databases (SWISS-PROT and EMBL). The analysis was carried out within the framework of the WIT2 system, which is designed and implemented to support genetic sequence analysis and comparative analysis of sequenced genomes.     

Microbial ecology in the age of genomics and metagenomics: concepts, tools, and recent advances

Microbial ecology examines the diversity and activity of micro-organisms in Earth's biosphere. In the last 20 years, the application of genomics tools have revolutionized microbial ecological studies and drastically expanded our view on the previously underappreciated microbial world. This review first introduces the basic concepts in microbial ecology and the main genomics methods that have been used to examine natural microbial populations and communities. In the ensuing three specific sections, the applications of the genomics in microbial ecological research are highlighted. The first describes the widespread application of multilocus sequence typing and representational difference analysis in studying genetic variation within microbial species. Such investigations have identified that migration, horizontal gene transfer and recombination are common in natural microbial populations and that microbial strains can be highly variable in genome size and gene content. The second section highlights and summarizes the use of four specific genomics methods (phylogenetic analysis of ribosomal RNA, DNA-DNA re-association kinetics, metagenomics, and micro-arrays) in analysing the diversity and potential activity of microbial populations and communities from a variety of terrestrial and aquatic environments. Such analyses have identified many unexpected phylogenetic lineages in viruses, bacteria, archaea, and microbial eukaryotes. Functional analyses of environmental DNA also revealed highly prevalent, but previously unknown, metabolic processes in natural microbial communities. In the third section, the ecological implications of sequenced microbial genomes are briefly discussed. Comparative analyses of prokaryotic genomic sequences suggest the importance of ecology in determining microbial genome size and gene content. The significant variability in genome size and gene content among strains and species of prokaryotes indicate the highly fluid nature of prokaryotic genomes, a result consistent with those from multilocus sequence typing and representational difference analyses. The integration of various levels of ecological analyses coupled to the application and further development of high throughput technologies are accelerating the pace of discovery in microbial ecology.