PanCGHweb: a web tool for genotype calling in pangenome CGH data

Interest of bacterial pangenome analyses in clinical microbiology

Thanks to the progress and decreasing costs in genome sequencing technologies, more than 250,000 bacterial genomes are currently available in public databases, covering most, if not all, of the major human-associated phylogenetic groups of these microorganisms, pathogenic or not. In addition, for many of them, sequences from several strains of a given species are available, thus enabling to evaluate their genetic diversity and study their evolution. In addition, the significant cost reduction of bacterial whole genome sequencing as well as the rapid increase in the number of available bacterial genomes have prompted the development of pangenomic software tools. The study of bacterial pangenome has many applications in clinical microbiology. It can unveil the pathogenic potential and ability of bacteria to resist antimicrobials as well identify specific sequences and predict antigenic epitopes that allow molecular or serologic assays and vaccines to be designed. Bacterial pangenome constitutes a powerful method for understanding the history of human bacteria and relating these findings to diagnosis in clinical microbiology laboratories in order to optimize patient management.

Comparative Genome Analysis of Lactococcus lactis Indicates Niche Adaptation and Resolves Genotype/Phenotype Disparity

Lactococcus lactis is one of the most important micro-organisms in the dairy industry for the fermentation of cheese and buttermilk. Besides the conversion of lactose to lactate it is responsible for product properties such as flavor and texture, which are determined by volatile metabolites, proteolytic activity and exopolysaccharide production. While the species Lactococcus lactis consists of the two subspecies lactis and cremoris their taxonomic position is confused by a group of strains that, despite of a cremoris genotype, display a lactis phenotype. Here we compared and analyzed the (draft) genomes of 43 L. lactis strains, of which 19 are of dairy and 24 are of non-dairy origin. Machine-learning algorithms facilitated the identification of orthologous groups of protein sequences (OGs) that are predictors for either the taxonomic position or the source of isolation. This allowed the unambiguous categorization of the genotype/phenotype disparity of ssp. lactis and ssp. cremoris strains. A detailed analysis of phenotypic properties including plasmid-encoded genes indicates evolutionary changes during niche adaptations. The results are consistent with the hypothesis that dairy isolates evolved from plant isolates. The analysis further suggests that genomes of cremoris phenotype strains are so eroded that they are restricted to a dairy environment. Overall the genome comparison of a diverse set of strains allowed the identification of niche and subspecies specific genes. This explains evolutionary relationships and will aid the identification and selection of industrial starter cultures.

PGAweb: A Web Server for Bacterial Pan-Genome Analysis

An astronomical increase in microbial genome data in recent years has led to strong demand for bioinformatic tools for pan-genome analysis within and across species. Here, we present PGAweb, a user-friendly, web-based tool for bacterial pan-genome analysis, which is composed of two main pan-genome analysis modules, PGAP and PGAP-X. PGAweb provides key interactive and customizable functions that include orthologous clustering, pan-genome profiling, sequence variation and evolution analysis, and functional classification. PGAweb presents features of genomic structural dynamics and sequence diversity with different visualization methods that are helpful for intuitively understanding the dynamics and evolution of bacterial genomes. PGAweb has an intuitive interface with one-click setting of parameters and is freely available at http://PGAweb.vlcc.cn/.

PGAP-X: extension on pan-genome analysis pipeline

Background

Since PGAP (pan-genome analysis pipeline) was published in 2012, it has been widely employed in bacterial genomics research. Though PGAP has integrated several modules for pan-genomics analysis, how to properly and effectively interpret and visualize the results data is still a challenge.

Result

To well present bacterial genomic characteristics, a novel cross-platform software was developed, named PGAP-X. Four kinds of data analysis modules were developed and integrated: whole genome sequences alignment, orthologous genes clustering, pan-genome profile analysis, and genetic variants analysis. The results from these analyses can be directly visualized in PGAP-X. The modules for data visualization in PGAP-X include: comparison of genome structure, gene distribution by conservation, pan-genome profile curve and variation on genic and genomic region. Meanwhile, result data produced by other programs with similar function can be imported to be further analyzed and visualized in PGAP-X. To test the performance of PGAP-X, we comprehensively analyzed 14 Streptococcus pneumonia strains and 14 Chlamydia trachomatis. The results show that, S. pneumonia strains have higher diversity on genome structure and gene contents than C. trachomatis strains. In addition, S. pneumonia strains might have suffered many evolutionary events, such genomic rearrangements, frequent horizontal gene transfer, homologous recombination, and other evolutionary process.

Conclusion

Briefly, PGAP-X directly presents the characteristics of bacterial genomic diversity with different visualization methods, which could help us to intuitively understand dynamics and evolution in bacterial genomes. The source code and the pre-complied executable programs are freely available from http://pgapx.ybzhao.com.

Electronic supplementary material

The online version of this article (doi: 10.1186/s12864-017-4337-7) contains supplementary material, which is available to authorized users.

The bacterial pangenome as a new tool for analysing pathogenic bacteria

The bacterial pangenome was introduced in 2005 and, in recent years, has been the subject of many studies. Thanks to progress in next-generation sequencing methods, the pangenome can be divided into two parts, the core (common to the studied strains) and the accessory genome, offering a large panel of uses. In this review, we have presented the analysis methods, the pangenome composition and its application as a study of lifestyle. We have also shown that the pangenome may be used as a new tool for redefining the pathogenic species. We applied this to the Escherichia coli and Shigella species, which have been a subject of controversy regarding their taxonomic and pathogenic position.

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Pangenome is a new way of studying pathogenic bacteria.

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Pangenome can be used as a taxonomic tool.

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This review describes pangenome in the world of pathogenic bacteria.

A brief review of software tools for pangenomics

Since the proposal for pangenomic study, there have been a dozen software tools actively in use for pangenomic analysis. By the end of 2014, Panseq and the pan-genomes analysis pipeline (PGAP) ranked as the top two most popular packages according to cumulative citations of peer-reviewed scientific publications. The functions of the software packages and tools, albeit variable among them, include categorizing orthologous genes, calculating pangenomic profiles, integrating gene annotations, and constructing phylogenies. As epigenomic elements are being gradually revealed in prokaryotes, it is expected that pangenomic databases and toolkits have to be extended to handle information of detailed functional annotations for genes and non-protein-coding sequences including non-coding RNAs, insertion elements, and conserved structural elements. To develop better bioinformatic tools, user feedback and integration of novel features are both of essence.

Production of aroma compounds in lactic fermentations

This review describes recent scientific research on the production of aroma compounds by lactic acid bacteria (LAB) in fermented food products. We discuss the various precursor molecules for the formation of aroma compounds in connection with the metabolic pathways involved. The roles of nonmetabolic properties such as cell lysis are also described in relation to aroma formation. Finally, we provide an overview of the literature on methods to steer and control aroma formation by LAB in mixed culture fermentations. We demonstrate that the technological progress made recently in high-throughput analysis methods has been driving the development of new approaches to understand, control, and steer aroma formation in (dairy) fermentation processes. This currently entails proposing new rules for designing stable, high-performance mixed cultures constituting a selection of strains, which in concert and on the basis of their individual predicted gene contents deliver the required functionalities.

Genotype-phenotype matching analysis of 38 Lactococcus lactis strains using random forest methods

Background

Lactococcus lactis is used in dairy food fermentation and for the efficient production of industrially relevant enzymes. The genome content and different phenotypes have been determined for multiple L. lactis strains in order to understand intra-species genotype and phenotype diversity and annotate gene functions. In this study, we identified relations between gene presence and a collection of 207 phenotypes across 38 L. lactis strains of dairy and plant origin. Gene occurrence and phenotype data were used in an iterative gene selection procedure, based on the Random Forest algorithm, to identify genotype-phenotype relations.

Results

A total of 1388 gene-phenotype relations were found, of which some confirmed known gene-phenotype relations, such as the importance of arabinose utilization genes only for strains of plant origin. We also identified a gene cluster related to growth on melibiose, a plant disaccharide; this cluster is present only in melibiose-positive strains and can be used as a genetic marker in trait improvement. Additionally, several novel gene-phenotype relations were uncovered, for instance, genes related to arsenite resistance or arginine metabolism.

Conclusions

Our results indicate that genotype-phenotype matching by integrating large data sets provides the possibility to identify gene-phenotype relations, possibly improve gene function annotation and identified relations can be used for screening bacterial culture collections for desired phenotypes. In addition to all gene-phenotype relations, we also provide coherent phenotype data for 38 Lactococcus strains assessed in 207 different phenotyping experiments, which to our knowledge is the largest to date for the Lactococcus lactis species.

PGAP: pan-genomes analysis pipeline

Summary: With the rapid development of DNA sequencing technology, increasing bacteria genome data enable the biologists to dig the evolutionary and genetic information of prokaryotic species from pan-genome sight. Therefore, the high-efficiency pipelines for pan-genome analysis are mostly needed. We have developed a new pan-genome analysis pipeline (PGAP), which can perform five analytic functions with only one command, including cluster analysis of functional genes, pan-genome profile analysis, genetic variation analysis of functional genes, species evolution analysis and function enrichment analysis of gene clusters. PGAP's performance has been evaluated on 11 Streptococcus pyogenes strains.

Availability:PGAP is developed with Perl script on the Linux Platform and the package is freely available from http://pgap.sf.net.

Contact:junyu@big.ac.cn; xiaojingfa@big.ac.cn

Supplementary information:Supplementary data are available at Bioinformatics online.

Systems solutions by lactic acid bacteria: from paradigms to practice

Lactic acid bacteria are among the powerhouses of the food industry, colonize the surfaces of plants and animals, and contribute to our health and well-being. The genomic characterization of LAB has rocketed and presently over 100 complete or nearly complete genomes are available, many of which serve as scientific paradigms. Moreover, functional and comparative metagenomic studies are taking off and provide a wealth of insight in the activity of lactic acid bacteria used in a variety of applications, ranging from starters in complex fermentations to their marketing as probiotics. In this new era of high throughput analysis, biology has become big science. Hence, there is a need to systematically store the generated information, apply this in an intelligent way, and provide modalities for constructing self-learning systems that can be used for future improvements. This review addresses these systems solutions with a state of the art overview of the present paradigms that relate to the use of lactic acid bacteria in industrial applications. Moreover, an outlook is presented of the future developments that include the transition into practice as well as the use of lactic acid bacteria in synthetic biology and other next generation applications.

Genome-scale diversity and niche adaptation analysis of Lactococcus lactis by comparative genome hybridization using multi-strain arrays

Lactococcus lactis produces lactic acid and is widely used in the manufacturing of various fermented dairy products. However, the species is also frequently isolated from non-dairy niches, such as fermented plant material. Recently, these non-dairy strains have gained increasing interest, as they have been described to possess flavour-forming activities that are rarely found in dairy isolates and have diverse metabolic properties. We performed an extensive whole-genome diversity analysis on 39 L. lactis strains, isolated from dairy and plant sources. Comparative genome hybridization analysis with multi-strain microarrays was used to assess presence or absence of genes and gene clusters in these strains, relative to all L. lactis sequences in public databases, whereby chromosomal and plasmid-encoded genes were computationally analysed separately. Nearly 3900 chromosomal orthologous groups (chrOGs) were defined on basis of four sequenced chromosomes of L. lactis strains (IL1403, KF147, SK11, MG1363). Of these, 1268 chrOGs are present in at least 35 strains and represent the presently known core genome of L. lactis, and 72 chrOGs appear to be unique for L. lactis. Nearly 600 and 400 chrOGs were found to be specific for either the subspecies lactis or subspecies cremoris respectively. Strain variability was found in presence or absence of gene clusters related to growth on plant substrates, such as genes involved in the consumption of arabinose, xylan, α-galactosides and galacturonate. Further niche-specific differences were found in gene clusters for exopolysaccharides biosynthesis, stress response (iron transport, osmotolerance) and bacterial defence mechanisms (nisin biosynthesis). Strain variability of functions encoded on known plasmids included proteolysis, lactose fermentation, citrate uptake, metal ion resistance and exopolysaccharides biosynthesis. The present study supports the view of L. lactis as a species with a very flexible genome.