PseudoMLSA: a database for multigenic sequence analysis of <Emphasis Type="Italic">Pseudomonas</Emphasis> species

Background  

The genus Pseudomonas comprises more than 100 species of environmental, clinical, agricultural, and biotechnological interest. Although, the recommended method for discriminating bacterial species is DNA-DNA hybridisation, alternative techniques based on multigenic sequence analysis are becoming a common practice in bacterial species discrimination studies. Since there is not a general criterion for determining which genes are more useful for species resolution; the number of strains and genes analysed is increasing continuously. As a result, sequences of different genes are dispersed throughout several databases. This sequence information needs to be collected in a common database, in order to be useful for future identification-based projects.     

Comparative genomic assessment of Multi-Locus Sequence Typing: rapid accumulation of genomic heterogeneity among clonal isolates of <Emphasis Type="Italic">Campylobacter jejuni</Emphasis>

Background  

Multi-Locus Sequence Typing (MLST) has emerged as a leading molecular typing method owing to its high ability to discriminate among bacterial isolates, the relative ease with which data acquisition and analysis can be standardized, and the high portability of the resulting sequence data. While MLST has been successfully applied to the study of the population structure for a number of different bacterial species, it has also provided compelling evidence for high rates of recombination in some species. We have analyzed a set of Campylobacter jejuni strains using MLST and Comparative Genomic Hybridization (CGH) on a full-genome microarray in order to determine whether recombination and high levels of genomic mosaicism adversely affect the inference of strain relationships based on the analysis of a restricted number of genetic loci.     

Classification and identification of bacteria by mass spectrometry and computational analysis

Background

In general, the definite determination of bacterial species is a tedious process and requires extensive manual labour. Novel technologies for bacterial detection and analysis can therefore help microbiologists in minimising their efforts in developing a number of microbiological applications.

Methodology

We present a robust, standardized procedure for automated bacterial analysis that is based on the detection of patterns of protein masses by MALDI mass spectrometry. We particularly applied the approach for classifying and identifying strains in species of the genus Erwinia. Many species of this genus are associated with disastrous plant diseases such as fire blight. Using our experimental procedure, we created a general bacterial mass spectra database that currently contains 2800 entries of bacteria of different genera. This database will be steadily expanded. To support users with a feasible analytical method, we developed and tested comprehensive software tools that are demonstrated herein. Furthermore, to gain additional analytical accuracy and reliability in the analysis we used genotyping of single nucleotide polymorphisms by mass spectrometry to unambiguously determine closely related strains that are difficult to distinguish by only relying on protein mass pattern detection.

Conclusions

With the method for bacterial analysis, we could identify fire blight pathogens from a variety of biological sources. The method can be used for a number of additional bacterial genera. Moreover, the mass spectrometry approach presented allows the integration of data from different biological levels such as the genome and the proteome.     

A new experimental approach for studying bacterial genomic island evolution identifies island genes with bacterial host-specific expression patterns

Background  

Genomic islands are regions of bacterial genomes that have been acquired by horizontal transfer and often contain blocks of genes that function together for specific processes. Recently, it has become clear that the impact of genomic islands on the evolution of different bacterial species is significant and represents a major force in establishing bacterial genomic variation. However, the study of genomic island evolution has been mostly performed at the sequence level using computer software or hybridization analysis to compare different bacterial genomic sequences. We describe here a novel experimental approach to study the evolution of species-specific bacterial genomic islands that identifies island genes that have evolved in such a way that they are differentially-expressed depending on the bacterial host background into which they are transferred.     

Assessing the reliability of eBURST using simulated populations with known ancestry

Background  

The program eBURST uses multilocus sequence typing data to divide bacterial populations into groups of closely related strains (clonal complexes), predicts the founding genotype of each group, and displays the patterns of recent evolutionary descent of all other strains in the group from the founder. The reliability of eBURST was evaluated using populations simulated with different levels of recombination in which the ancestry of all strains was known.     

Pan-genome sequence analysis using Panseq: an online tool for the rapid analysis of core and accessory genomic regions

Background  

The pan-genome of a bacterial species consists of a core and an accessory gene pool. The accessory genome is thought to be an important source of genetic variability in bacterial populations and is gained through lateral gene transfer, allowing subpopulations of bacteria to better adapt to specific niches. Low-cost and high-throughput sequencing platforms have created an exponential increase in genome sequence data and an opportunity to study the pan-genomes of many bacterial species. In this study, we describe a new online pan-genome sequence analysis program, Panseq.     

Azithromycin effectiveness against intracellular infections of <Emphasis Type="Italic">Francisella</Emphasis>

Background  

Macrolide antibiotics are commonly administered for bacterial respiratory illnesses. Azithromycin (Az) is especially noted for extremely high intracellular concentrations achieved within macrophages which is far greater than the serum concentration. Clinical strains of Type B Francisella (F.) tularensis have been reported to be resistant to Az, however our laboratory Francisella strains were found to be sensitive. We hypothesized that different strains/species of Francisella (including Type A) may have different susceptibilities to Az, a widely used and well-tolerated antibiotic.     

Multilocus sequence typing supports the hypothesis that Ochrobactrum anthropi displays a human-associated subpopulation

Background  

Ochrobactrum anthropi is a versatile bacterial species with strains living in very diverse habitats. It is increasingly recognized as opportunistic pathogen in hospitalized patients. The population biology of the species particularly with regard to the characteristics of the human isolates is being investigated. To address this issue, we proposed a polyphasic approach consisting in Multi-Locus Sequence Typing (MLST), multi-locus phylogeny, genomic-based fingerprinting by pulsed-field gel electrophoresis (PFGE) and antibiotyping.     

From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification

Background  

Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification.     

TaxMan: a taxonomic database manager

Background  

Phylogenetic analysis of large, multiple-gene datasets, assembled from public sequence databases, is rapidly becoming a popular way to approach difficult phylogenetic problems. Supermatrices (concatenated multiple sequence alignments of multiple genes) can yield more phylogenetic signal than individual genes. However, manually assembling such datasets for a large taxonomic group is time-consuming and error-prone. Additionally, sequence curation, alignment and assessment of the results of phylogenetic analysis are made particularly difficult by the potential for a given gene in a given species to be unrepresented, or to be represented by multiple or partial sequences. We have developed a software package, TaxMan, that largely automates the processes of sequence acquisition, consensus building, alignment and taxon selection to facilitate this type of phylogenetic study.     

Use of a multilocus variable-number tandem repeat analysis method for molecular subtyping and phylogenetic analysis of Neisseria meningitidis isolates

Background  

The multilocus variable-number tandem repeat (VNTR) analysis (MLVA) technique has been developed for fine typing of many bacterial species. The genomic sequences of Neisseria meningitidis strains Z2491, MC58 and FAM18 have been available for searching potential VNTR loci by computer software. In this study, we developed and evaluated a MLVA method for molecular subtyping and phylogenetic analysis of N. meningitidis strains.     

Automated group assignment in large phylogenetic trees using GRUNT: GRouping,Ungrouping, Naming Tool

Background  

Accurate taxonomy is best maintained if species are arranged as hierarchical groups in phylogenetic trees. This is especially important as trees grow larger as a consequence of a rapidly expanding sequence database. Hierarchical group names are typically manually assigned in trees, an approach that becomes unfeasible for very large topologies.     

Identification of polymorphic tandem repeats by direct comparison of genome sequence from different bacterial strains : a web-based resource

Background

Polymorphic tandem repeat typing is a new generic technology which has been proved to be very efficient for bacterial pathogens such as B. anthracis, M. tuberculosis, P. aeruginosa, L. pneumophila, Y. pestis. The previously developed tandem repeats database takes advantage of the release of genome sequence data for a growing number of bacteria to facilitate the identification of tandem repeats. The development of an assay then requires the evaluation of tandem repeat polymorphism on well-selected sets of isolates. In the case of major human pathogens, such as S. aureus, more than one strain is being sequenced, so that tandem repeats most likely to be polymorphic can now be selected in silico based on genome sequence comparison.

Results

In addition to the previously described general Tandem Repeats Database, we have developed a tool to automatically identify tandem repeats of a different length in the genome sequence of two (or more) closely related bacterial strains. Genome comparisons are pre-computed. The results of the comparisons are parsed in a database, which can be conveniently queried over the internet according to criteria of practical value, including repeat unit length, predicted size difference, etc. Comparisons are available for 16 bacterial species, and the orthopox viruses, including the variola virus and three of its close neighbors.

Conclusions

We are presenting an internet-based resource to help develop and perform tandem repeats based bacterial strain typing. The tools accessible at http://minisatellites.u-psud.fr now comprise four parts. The Tandem Repeats Database enables the identification of tandem repeats across entire genomes. The Strain Comparison Page identifies tandem repeats differing between different genome sequences from the same species. The "Blast in the Tandem Repeats Database" facilitates the search for a known tandem repeat and the prediction of amplification product sizes. The "Bacterial Genotyping Page" is a service for strain identification at the subspecies level.

     

Assessment of urban microbiome assemblies with the help of targeted in silico gold standards

Background

Microbial communities play a crucial role in our environment and may influence human health tremendously. Despite being the place where human interaction is most abundant we still know little about the urban microbiome. This is highlighted by the large amount of unclassified DNA reads found in urban metagenome samples. The only in silico approach that allows us to find unknown species, is the assembly and classification of draft genomes from a metagenomic dataset. In this study we (1) investigate the applicability of an assembly and binning approach for urban metagenome datasets, and (2) develop a new method for the generation of in silico gold standards to better understand the specific challenges of such datasets and provide a guide in the selection of available software.

Results

We applied combinations of three assembly (Megahit, SPAdes and MetaSPAdes) and three binning tools (MaxBin, MetaBAT and CONCOCT) to whole genome shotgun datasets from the CAMDA 2017 Challenge. Complex in silico gold standards with a simulated bacterial fraction were generated for representative samples of each surface type and city. Using these gold standards, we found the combination of SPAdes and MetaBAT to be optimal for urban metagenome datasets by providing the best trade-off between the number of high-quality genome draft bins (MIMAG standards) retrieved, the least amount of misassemblies and contamination. The assembled draft genomes included known species like Propionibacterium acnes but also novel species according to respective ANI values.

Conclusions

In our work, we showed that, even for datasets with high diversity and low sequencing depth from urban environments, assembly and binning-based methods can provide high-quality genome drafts. Of vital importance to retrieve high-quality genome drafts is sequence depth but even more so a high proportion of the bacterial sequence fraction too achieve high coverage for bacterial genomes. In contrast to read-based methods relying on database knowledge, genome-centric methods as applied in this study can provide valuable information about unknown species and strains as well as functional contributions of single community members within a sample. Furthermore, we present a method for the generation of sample-specific highly complex in silico gold standards.

Reviewers

This article was reviewed by Craig Herbold, Serghei Mangul and Yana Bromberg.

     

Evolutionary,structural and functional relationships revealed by comparative analysis of syntenic genes in Rhizobiales

Background  

Comparative genomics has provided valuable insights into the nature of gene sequence variation and chromosomal organization of closely related bacterial species. However, questions about the biological significance of gene order conservation, or synteny, remain open. Moreover, few comprehensive studies have been reported for rhizobial genomes.     

Improved analysis of bacterial CGH data beyond the log-ratio paradigm

Background  

Existing methods for analyzing bacterial CGH data from two-color arrays are based on log-ratios only, a paradigm inherited from expression studies. We propose an alternative approach, where microarray signals are used in a different way and sequence identity is predicted using a supervised learning approach.     

Identification of amino acid residues involved in substrate specificity of plant acyl-ACP thioesterases using a bioinformatics-guided approach

Background  

The large amount of available sequence information for the plant acyl-ACP thioesterases (TEs) made it possible to use a bioinformatics-guided approach to identify amino acid residues involved in substrate specificity. The Conserved Property Difference Locator (CPDL) program allowed the identification of putative specificity-determining residues that differ between the FatA and FatB TE classes. Six of the FatA residue differences identified by CPDL were incorporated into the FatB-like parent via site-directed mutagenesis and the effect of each on TE activity was determined. Variants were expressed in E. coli strain K27 that allows determination of enzyme activity by GCMS analysis of fatty acids released into the medium.     

Evolutionary sequence analysis of complete eukaryote genomes

Background  

Gene duplication and gene loss during the evolution of eukaryotes have hindered attempts to estimate phylogenies and divergence times of species. Although current methods that identify clusters of orthologous genes in complete genomes have helped to investigate gene function and gene content, they have not been optimized for evolutionary sequence analyses requiring strict orthology and complete gene matrices. Here we adopt a relatively simple and fast genome comparison approach designed to assemble orthologs for evolutionary analysis. Our approach identifies single-copy genes representing only species divergences (panorthologs) in order to minimize potential errors caused by gene duplication. We apply this approach to complete sets of proteins from published eukaryote genomes specifically for phylogeny and time estimation.     

Introduction of a novel 18S rDNA gene arrangement along with distinct ITS region in the saline water microalga Dunaliella

Background

Sundarban is the world's largest coastal sediment comprising of mangrove forest which covers about one million hectares in the south-eastern parts of India and southern parts of Bangladesh. The microbial diversity in this sediment is largely unknown till date. In the present study an attempt has been made to understand the microbial diversity in this sediment using a cultivation-independent molecular approach.

Results

Two 16 S rRNA gene libraries were constructed and partial sequencing of the selected clones was carried out to identify bacterial strains present in the sediment. Phylogenetic analysis of partially sequenced 16 S rRNA gene sequences revealed the diversity of bacterial strains in the Sundarban sediment. At least 8 different bacterial phyla were detected. The major divisions of detected bacterial phyla were Proteobacteria (alpha, beta, gamma, and delta), Flexibacteria (CFB group), Actinobacteria, Acidobacteria, Chloroflexi, Firmicutes, Planctomycetes and Gammatimonadates.

Conclusion

The gammaproteobacteria were found to be the most abundant bacterial group in Sundarban sediment. Many clones showed similarity with previously reported bacterial lineages recovered from various marine sediments. The present study indicates a probable hydrocarbon and oil contamination in this sediment. In the present study, a number of clones were identified that have shown similarity with bacterial clones or isolates responsible for the maintenance of the S-cycle in the saline environment.     

Similarity-based gene detection: using COGs to find evolutionarily-conserved ORFs

Background  

Experimental verification of gene products has not kept pace with the rapid growth of microbial sequence information. However, existing annotations of gene locations contain sufficient information to screen for probable errors. Furthermore, comparisons among genomes become more informative as more genomes are examined. We studied all open reading frames (ORFs) of at least 30 codons from the genomes of 27 sequenced bacterial strains. We grouped the potential peptide sequences encoded from the ORFs by forming Clusters of Orthologous Groups (COGs). We used this grouping in order to find homologous relationships that would not be distinguishable from noise when using simple BLAST searches. Although COG analysis was initially developed to group annotated genes, we applied it to the task of grouping anonymous DNA sequences that may encode proteins.