PanCGH: a genotype-calling algorithm for pangenome CGH data

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.

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.

The complex microbiota of raw milk

Here, we review what is known about the microorganisms present in raw milk, including milk from cows, sheep, goats and humans. Milk, due to its high nutritional content, can support a rich microbiota. These microorganisms enter milk from a variety of sources and, once in milk, can play a number of roles, such as facilitating dairy fermentations (e.g. Lactococcus, Lactobacillus, Streptococcus, Propionibacterium and fungal populations), causing spoilage (e.g. Pseudomonas, Clostridium, Bacillus and other spore-forming or thermoduric microorganisms), promoting health (e.g. lactobacilli and bifidobacteria) or causing disease (e.g. Listeria, Salmonella, Escherichia coli, Campylobacter and mycotoxin-producing fungi). There is also concern that the presence of antibiotic residues in milk leads to the development of resistance, particularly among pathogenic bacteria. Here, we comprehensively review these topics, while comparing the approaches, both culture-dependent and culture-independent, which can be taken to investigate the microbial composition of milk.

Genotypic and phenotypic analysis of dairy Lactococcus lactis biodiversity in milk: volatile organic compounds as discriminating markers

The diversity of nine dairy strains of Lactococcus lactis subsp. lactis in fermented milk was investigated by both genotypic and phenotypic analyses. Pulsed-field gel electrophoresis and multilocus sequence typing were used to establish an integrated genotypic classification. This classification was coherent with discrimination of the L. lactis subsp. lactis bv. diacetylactis lineage and reflected clonal complex phylogeny and the uniqueness of the genomes of these strains. To assess phenotypic diversity, 82 variables were selected as important dairy features; they included physiological descriptors and the production of metabolites and volatile organic compounds (VOCs). Principal-component analysis (PCA) demonstrated the phenotypic uniqueness of each of these genetically closely related strains, allowing strain discrimination. A method of variable selection was developed to reduce the time-consuming experimentation. We therefore identified 20 variables, all associated with VOCs, as phenotypic markers allowing discrimination between strain groups. These markers are representative of the three metabolic pathways involved in flavor: lipolysis, proteolysis, and glycolysis. Despite great phenotypic diversity, the strains could be divided into four robust phenotypic clusters based on their metabolic orientations. Inclusion of genotypic diversity in addition to phenotypic characters in the classification led to five clusters rather than four being defined. However, genotypic characters make a smaller contribution than phenotypic variables (no genetic distances selected among the most contributory variables). This work proposes an original method for the phenotypic differentiation of closely related strains in milk and may be the first step toward a predictive classification for the manufacture of starters.

Explaining microbial phenotypes on a genomic scale: GWAS for microbes

There is an increasing availability of complete or draft genome sequences for microbial organisms. These data form a potentially valuable resource for genotype-phenotype association and gene function prediction, provided that phenotypes are consistently annotated for all the sequenced strains. In this review, we address the requirements for successful gene-trait matching. We outline a basic protocol for microbial functional genomics, including genome assembly, annotation of genotypes (including single nucleotide polymorphisms, orthologous groups and prophages), data pre-processing, genotype-phenotype association, visualization and interpretation of results. The methodologies for association described herein can be applied to other data types, opening up possibilities to analyze transcriptome-phenotype associations, and correlate microbial population structure or activity, as measured by metagenomics, to environmental parameters.

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.

Volatile compound fingerprinting of mixed-culture fermentations

With the advent of the -omics era, classical technology platforms, such as hyphenated mass spectrometry, are currently undergoing a transformation toward high-throughput application. These novel platforms yield highly detailed metabolite profiles in large numbers of samples. Such profiles can be used as fingerprints for the accurate identification and classification of samples as well as for the study of effects of experimental conditions on the concentrations of specific metabolites. Challenges for the application of these methods lie in the acquisition of high-quality data, data normalization, and data mining. Here, a high-throughput fingerprinting approach based on analysis of headspace volatiles using ultrafast gas chromatography coupled to time of flight mass spectrometry (ultrafast GC/TOF-MS) was developed and evaluated for classification and screening purposes in food fermentation. GC-MS mass spectra of headspace samples of milk fermented by different mixed cultures of lactic acid bacteria (LAB) were collected and preprocessed in MetAlign, a dedicated software package for the preprocessing and comparison of liquid chromatography (LC)-MS and GC-MS data. The Random Forest algorithm was used to detect mass peaks that discriminated combinations of species or strains used in fermentations. Many of these mass peaks originated from key flavor compounds, indicating that the presence or absence of individual strains or combinations of strains significantly influenced the concentrations of these components. We demonstrate that the approach can be used for purposes like the selection of strains from collections based on flavor characteristics and the screening of (mixed) cultures for the presence or absence of strains. In addition, we show that strain-specific flavor characteristics can be traced back to genetic markers when comparative genome hybridization (CGH) data are available.

Comparative phenotypic and molecular genetic profiling of wild Lactococcus lactis subsp. lactis strains of the L. lactis subsp. lactis and L. lactis subsp. cremoris genotypes, isolated from starter-free cheeses made of raw milk

Twenty Lactococcus lactis strains with an L. lactis subsp. lactis phenotype isolated from five traditional cheeses made of raw milk with no added starters belonging to the L. lactis subsp. lactis and L. lactis subsp. cremoris genotypes (lactis and cremoris genotypes, respectively; 10 strains each) were subjected to a series of phenotypic and genetic typing methods, with the aims of determining their phylogenetic relationships and suitability as starters. Pulsed-field gel electrophoresis (PFGE) analysis of intact genomes digested with SalI and SmaI proved that all strains were different except for three isolates of the cremoris genotype, which showed identical PFGE profiles. Multilocus sequence typing (MLST) analysis using internal sequences of seven loci (namely, atpA, rpoA, pheS, pepN, bcaT, pepX, and 16S rRNA gene) revealed considerable intergenotype nucleotide polymorphism, although deduced amino acid changes were scarce. Analysis of the MLST data for the present strains and others from other dairy and nondairy sources showed that all of them clustered into the cremoris or lactis genotype group, by using both independent and combined gene sequences. These two groups of strains also showed distinctive carbohydrate fermentation and enzyme activity profiles, with the strains in the cremoris group showing broader profiles. However, the profiles of resistance/susceptibility to 16 antibiotics were very similar, showing no atypical resistance, except for tetracycline resistance in three identical cremoris genotype isolates. The numbers and concentrations of volatile compounds produced in milk by the strains belonging to these two groups were clearly different, with the cremoris genotype strains producing higher concentrations of more branched-chain, derived compounds. Together, the present results support the idea that the lactis and cremoris genotypes of phenotypic Lactococcus lactis subsp. lactis actually represent true subspecies. Some strains of the two subspecies in this study appear to be good starter candidates.

Comparative transcriptome analysis of Lactococcus lactis subsp. cremoris strains under conditions simulating Cheddar cheese manufacture

Gene expression in response to technological variations can influence fermentation and flavor generation in Cheddar cheese, and can vary from one lactococcal strain to another, perceived as differences in starter performance. The aim of this study was to determine the influence of cheese cooking temperature at 38 °C and salting on the transcriptional profiles of four closely related strains of L. lactis subsp. cremoris under simulated conditions of Cheddar cheese manufacture. Two responses could be distinguished, a core gene expression, corresponding to the common response of all strains and strain-specific response during the Cheddar simulating process. For the core gene expression after heating of inoculated milk at 38 °C, two groups of differentially expressed genes were identified: i) stress response and ii) carbohydrate and amino acid metabolism. The response to combined stresses of heat, acid and salt resulted in: i) general decrease of functions linked to cell division and metabolism, ii) specific responses related to stress such as the induction of genes coding for chaperones and proteases and iii) expression of prophage lytic systems for certain strains. Strain-specific responses were mainly observed in three of the four tested strains. These responses were the induction of genes related to osmotic stress or the release of CodY repression leading to the activation of oligopeptide transporters as well as the bcaT gene, related to amino acid degradation for the production of flavor. Comparing transcriptomes provides a core expression profile that contributes to understanding gene expression responses to environmental variations. The strain-specific responses identify predictive markers for the transcriptional state of starter strains before they enter the cheese ripening phase.

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.

Probing the pan-genome of Listeria monocytogenes: new insights into intraspecific niche expansion and genomic diversification

Background

Bacterial pathogens often show significant intraspecific variations in ecological fitness, host preference and pathogenic potential to cause infectious disease. The species of Listeria monocytogenes, a facultative intracellular pathogen and the causative agent of human listeriosis, consists of at least three distinct genetic lineages. Two of these lineages predominantly cause human sporadic and epidemic infections, whereas the third lineage has never been implicated in human disease outbreaks despite its overall conservation of many known virulence factors.

Results

Here we compare the genomes of 26 L. monocytogenes strains representing the three lineages based on both in silico comparative genomic analysis and high-density, pan-genomic DNA array hybridizations. We uncover 86 genes and 8 small regulatory RNAs that likely make L. monocytogenes lineages differ in carbohydrate utilization and stress resistance during their residence in natural habitats and passage through the host gastrointestinal tract. We also identify 2,330 to 2,456 core genes that define this species along with an open pan-genome pool that contains more than 4,052 genes. Phylogenomic reconstructions based on 3,560 homologous groups allowed robust estimation of phylogenetic relatedness among L. monocytogenes strains.

Conclusions

Our pan-genome approach enables accurate co-analysis of DNA sequence and hybridization array data for both core gene estimation and phylogenomics. Application of our method to the pan-genome of L. monocytogenes sheds new insights into the intraspecific niche expansion and evolution of this important foodborne pathogen.

Chromosomal diversity in Lactococcus lactis and the origin of dairy starter cultures

A large collection of Lactococcus lactis strains, including wild-type isolates and dairy starter cultures, were screened on the basis of their phenotype and the macrorestriction patterns produced from pulsed-field gel electrophoresis (PFGE) analysis of SmaI digests of genomic DNA. Three groups of dairy starter cultures, used for different purposes in the dairy industry, and a fourth group made up of strains isolated from the environment were selected for analysis of their chromosomal diversity using the endonuclease I-CeuI. Chromosome architecture was largely conserved with each strain having six copies of the rRNA genes, and the chromosome size of individual strains ranged between 2,240 and 2,688 kb. The origin of L. lactis strains showed the greatest correlation with chromosome size, and dairy strains, particularly those with the cremoris phenotype, had smaller chromosomes than wild-type strains. Overall, this study, coupled with analysis of the sequenced L. lactis genomes, provides evidence that defined strain dairy starter cultures have arisen from plant L. lactis strains. Adaptation of these strains to the dairy environment has involved loss of functions resulting in smaller chromosomes and acquisition of genes (usually plasmid associated) that facilitate growth in milk. We conclude that dairy starter cultures generally and the industrially used cremoris and diacetylactis phenotype strains in particular comprise a specialized group of L. lactis strains that have been selected to become an essential component of industrial processes and have evolved accordingly, so that they are no longer fit to survive outside the dairy environment.

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

Summary: A pangenome is the total of genes present in strains of the same species. Pangenome microarrays allow determining the genomic content of bacterial strains more accurately than conventional comparative genome hybridization microarrays. PanCGHweb is the first tool that effectively calls genotype based on pangenome microarray data.

Availability: PanCGHweb, the web tool is accessible from: http://bamics2.cmbi.ru.nl/websoftware/pancgh/

Contact:sacha.vanhijum@nizo.nl

The proteolytic system of lactic acid bacteria revisited: a genomic comparison

Background

Lactic acid bacteria (LAB) are a group of gram-positive, lactic acid producing Firmicutes. They have been extensively used in food fermentations, including the production of various dairy products. The proteolytic system of LAB converts proteins to peptides and then to amino acids, which is essential for bacterial growth and also contributes significantly to flavor compounds as end-products. Recent developments in high-throughput genome sequencing and comparative genomics hybridization arrays provide us with opportunities to explore the diversity of the proteolytic system in various LAB strains.

Results

We performed a genome-wide comparative genomics analysis of proteolytic system components, including cell-wall bound proteinase, peptide transporters and peptidases, in 22 sequenced LAB strains. The peptidase families PepP/PepQ/PepM, PepD and PepI/PepR/PepL are described as examples of our in silico approach to refine the distinction of subfamilies with different enzymatic activities. Comparison of protein 3D structures of proline peptidases PepI/PepR/PepL and esterase A allowed identification of a conserved core structure, which was then used to improve phylogenetic analysis and functional annotation within this protein superfamily.

The diversity of proteolytic system components in 39 Lactococcus lactis strains was explored using pangenome comparative genome hybridization analysis. Variations were observed in the proteinase PrtP and its maturation protein PrtM, in one of the Opp transport systems and in several peptidases between strains from different Lactococcus subspecies or from different origin.

Conclusions

The improved functional annotation of the proteolytic system components provides an excellent framework for future experimental validations of predicted enzymatic activities. The genome sequence data can be coupled to other "omics" data e.g. transcriptomics and metabolomics for prediction of proteolytic and flavor-forming potential of LAB strains. Such an integrated approach can be used to tune the strain selection process in food fermentations.