Taxonomic position, antibiotic resistance and virulence factor production by Stenotrophomonas isolates from patients with cystic fibrosis and other chronic respiratory infections.

BACKGROUND: The potential pathogenic role of Stenotrophomonas maltophilia in lung disease and in particular in cystic fibrosis is unclear. To develop further understanding of the biology of this taxa, the taxonomic position, antibiotic resistance and virulence factors of S. maltophilia isolates from patients with chronic lung disease were studied. RESULTS: A total of 111 isolates recovered between 2003 and 2016 from respiratory samples from patients in five different countries were included. Based on a cut-off of 95%, analysis of average nucleotide identity by BLAST (ANIb) showed that the 111 isolates identified as S. maltophilia by Matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF/MS) belonged to S. maltophilia (n = 65), S. pavanii (n = 6) and 13 putative novel species (n = 40), which each included 1-5 isolates; these groupings coincided with the results of the 16S rDNA analysis, and the L1 and L2 ß-lactamase Neighbor-Joining phylogeny. Chromosomally encoded aminoglycoside resistance was identified in all S. maltophilia and S. pavani isolates, while acquired antibiotic resistance genes were present in only a few isolates. Nevertheless, phenotypic resistance levels against commonly used antibiotics, determined by standard broth microbroth dilution, were high. Although putative virulence genes were present in all isolates, the percentage of positive isolates varied. The Xps II secretion system responsible for the secretion of the StmPr1-3 proteases was mainly limited to isolates identified as S. maltophilia based on ANIb, but no correlation with phenotypic expression of protease activity was found. The RPF two-component quorum sensing system involved in virulence and antibiotic resistance expression has two main variants with one variant lacking 190 amino acids in the sensing region. CONCLUSIONS: The putative novel Stenotrophomonas species recovered from patient samples and identified by MALDI-TOF/MS as S. maltophilia, differed from S. maltophilia in resistance and virulence genes, and therefore possibly in pathogenicity. Revision of the Stenotrophomonas taxonomy is needed in order to reliably identify strains within the genus and elucidate the role of the different species in disease.

Characterization of clinical Ralstonia strains and their taxonomic position.

To improve understanding of the role of Ralstonia in cystic fibrosis (CF), whole genomes of 18 strains from clinical samples were sequenced using Illumina technology. Sequences were analysed by core genome Multi-Locus Sequence Typing, Average Nucleotide Identity based on BLAST (ANIb), RAST annotation, and by ResFinder. Phylogenetic analysis was performed for the 16S rRNA gene, and the OXA-22 and OXA-60 ß-lactamase families. The minimal inhibitory concentrations (MICs) were determined using broth microdilution. ANIb data for the 18 isolates and 54 strains from GenBank, supported by phylogenetic analysis, showed that 8 groups of clusters (A-H), as well as subgroups that should be considered as species or subspecies. Groups A-C contain strains previously identified as Ralstonia solanacearum and Ralstonia pseudosolanacearum. We propose that group A is a novel species. Group B and C are Ralstonia syzygii, Ralstonia solanacearum, respectively. Group D is composed of Ralstonia mannitolilytica and Group E of Ralstonia pickettii. Group F and G should be considered novel species. Group H strains belong to R. insidiosa. OXA-22 and OXA-60 family ß-lactamases were encoded by all strains. Co-trimoxazole generally showed high activity with low MICs (≤1 mg/l) as did ciprofloxacin (≤0.12 mg/l). MICs against the other antibiotics were more variable, but generally high. RAST annotation revealed limited differences between the strains, and virulence factors were not identified. The taxonomy of the genus Ralstonia is in need of revision, but sequencing additional isolates is needed. Antibiotic resistance levels are high. Annotation did not identify potential virulence factors.

Susceptibility of Pseudomonas aeruginosa Recovered from Cystic Fibrosis Patients to Murepavadin and 13 Comparator Antibiotics.

The objective was to determine the in vitro antimicrobial susceptibility of Pseudomonas aeruginosa isolates cultured from cystic fibrosis (CF) patients and explore associations between strain sequence type and susceptibility. Fourteen antibiotics and antibiotic combinations, including the novel antibacterial peptide murepavadin, were tested for activity against 414 Pseudomonas aeruginosa isolates cultured from respiratory samples of CF patients. The complete genomes of the isolates were sequenced, and minimum spanning trees were constructed based on the sequence types (STs). Percentages of resistance according to CLSI 2019 breakpoints were as follows: cefepime, 14%; ceftazidime, 11%; ceftazidime-avibactam, 7%; ceftolozane-tazobactam, 3%; piperacillin-tazobactam, 12%; meropenem, 18%; imipenem, 32%; aztreonam, 23%; ciprofloxacin, 30%; gentamicin, 30%; tobramycin, 12%; amikacin, 18%; and colistin, 4%. Murepavadin MIC50 and MIC90 were 0.12 mg/liter and 2 mg/liter, respectively. There were no apparent clonal clusters associated with resistance, but higher MICs did appear to occur more often in STs with multiple isolates than in single ST isolates. In general, the CF isolates showed a wide genetic distribution. P. aeruginosa CF isolates exhibited the lowest resistance rates against ceftolozane-tazobactam, ceftazidime-avibactam, and colistin. Murepavadin demonstrated the highest activity on a per-weight basis and may therefore become a valuable addition to the currently available antibiotics for treatment of respiratory infection in people with CF.

Increased risk of acquisition and transmission of ESBL-producing Enterobacteriaceae in malnourished children exposed to amoxicillin.

OBJECTIVES: Routine amoxicillin for children with uncomplicated severe acute malnutrition raises concerns of increasing antibiotic resistance. We performed an ancillary study nested within a double-blind, placebo-controlled trial in Niger testing the role of routine 7 day amoxicillin therapy in nutritional recovery of children 6 to 59 months of age with uncomplicated severe acute malnutrition. METHODS: We screened 472 children for rectal carriage of ESBL-producing Enterobacteriaceae (ESBL-E) as well as their household siblings under 5 years old, at baseline and Week 1 (W1) and Week 4 (W4) after start of therapy, and characterized strains by WGS. ClinicalTrials.gov: NCT01613547. RESULTS: Carriage in index children at baseline was similar in the amoxicillin and the placebo groups (33.8% versus 27.9%, P = 0.17). However, acquisition of ESBL-E in index children at W1 was higher in the amoxicillin group than in the placebo group (53.7% versus 32.2%, adjusted risk ratio = 2.29, P = 0.001). Among 209 index and sibling households possibly exposed to ESBL-E transmission, 16 (7.7%) had paired strains differing by ≤10 SNPs, suggesting a high probability of transmission. This was more frequent in households from the amoxicillin group than from the placebo group [11.5% (12/104) versus 3.8% (4/105), P = 0.04]. CONCLUSIONS: Among children exposed to amoxicillin, ESBL-E colonization was more frequent and the risk of transmission to siblings higher. Routine amoxicillin should be carefully balanced with the risks associated with ESBL-E colonization.

Therapy and Outcome of Staphylococcus aureus Infections of Intracorporeal Ventricular Assist Devices.

Infection of the driveline or pump pocket is a common complication in patients with ventricular assist devices (VADs) and Staphylococcus aureus is the main pathogen causing such infections. Limited evidence is currently available to guide the choice of antibiotic therapy and the duration of treatment in these patients. Patients at the University Medical Center Utrecht who developed a VAD-related S. aureus infection between 2007 and 2016 were retrospectively assessed. Blood culture isolates were typed by whole genome sequencing to differentiate between relapses and reinfections, and to determine whether antibiotic therapy had led to acquisition of resistance mutations. Twenty-eight patients had S. aureus VAD infections. Ten of these patients also suffered S. aureus bacteremia. Discontinuation of antibiotic therapy was followed by relapse in 50% of the patients without prior S. aureus bacteremia and in 80% of patients with bacteremia. Oral cephalexin could ultimately suppress the infection for the duration of follow-up in 8/8 patients without S. aureus bacteremia and in 3/6 patients with S. aureus bacteremia. Clindamycin failed as suppressive therapy in 4/4 patients. Cephalexin appears an adequate choice for antibiotic suppression of VAD infections with methicillin-susceptible S. aureus. In patients without systemic symptoms, it may be justified to attempt to stop therapy after treatment of the acute infection, but antibiotic suppression until heart transplant seems indicated in patients with S. aureus bacteremia.

RNA-seq and Tn-seq reveal fitness determinants of vancomycin-resistant Enterococcus faecium during growth in human serum.

BACKGROUND: The Gram-positive bacterium Enterococcus faecium is a commensal of the human gastrointestinal tract and a frequent cause of bloodstream infections in hospitalized patients. The mechanisms by which E. faecium can survive and grow in blood during an infection have not yet been characterized. Here, we identify genes that contribute to growth of E. faecium in human serum through transcriptome profiling (RNA-seq) and a high-throughput transposon mutant library sequencing approach (Tn-seq). RESULTS: We first sequenced the genome of E. faecium E745, a vancomycin-resistant clinical isolate, using a combination of short- and long read sequencing, revealing a 2,765,010 nt chromosome and 6 plasmids, with sizes ranging between 9.3 kbp and 223.7 kbp. We then compared the transcriptome of E. faecium E745 during exponential growth in rich medium and in human serum by RNA-seq. This analysis revealed that 27.8% of genes on the E. faecium E745 genome were differentially expressed in these two conditions. A gene cluster with a role in purine biosynthesis was among the most upregulated genes in E. faecium E745 upon growth in serum. The E. faecium E745 transposon mutant library was then used to identify genes that were specifically required for growth of E. faecium in serum. Genes involved in de novo nucleotide biosynthesis (including pyrK_2, pyrF, purD, purH) and a gene encoding a phosphotransferase system subunit (manY_2) were thus identified to be contributing to E. faecium growth in human serum. Transposon mutants in pyrK_2, pyrF, purD, purH and manY_2 were isolated from the library and their impaired growth in human serum was confirmed. In addition, the pyrK_2 and manY_2 mutants were tested for their virulence in an intravenous zebrafish infection model and exhibited significantly attenuated virulence compared to E. faecium E745. CONCLUSIONS: Genes involved in carbohydrate metabolism and nucleotide biosynthesis of E. faecium are essential for growth in human serum and contribute to the pathogenesis of this organism. These genes may serve as targets for the development of novel anti-infectives for the treatment of E. faecium bloodstream infections.

The Two-Component System ChtRS Contributes to Chlorhexidine Tolerance in Enterococcus faecium.

Enterococcus faecium is one of the primary causes of nosocomial infections. Disinfectants are commonly used to prevent infections with multidrug-resistant E. faecium in hospitals. Worryingly, E. faecium strains that exhibit tolerance to disinfectants have already been described. We aimed to identify and characterize E. faecium genes that contribute to tolerance to the disinfectant chlorhexidine (CHX). We used a transposon mutant library, constructed in a multidrug-resistant E. faecium bloodstream isolate, to perform a genome-wide screen to identify genetic determinants involved in tolerance to CHX. We identified a putative two-component system (2CS), composed of a putative sensor histidine kinase (ChtS) and a cognate DNA-binding response regulator (ChtR), which contributed to CHX tolerance in E. faecium Targeted chtR and chtS deletion mutants exhibited compromised growth in the presence of CHX. Growth of the chtR and chtS mutants was also affected in the presence of the antibiotic bacitracin. The CHX- and bacitracin-tolerant phenotype of E. faecium E1162 was linked to a unique, nonsynonymous single nucleotide polymorphism in chtR Transmission electron microscopy showed that upon challenge with CHX, the ΔchtR and ΔchtS mutants failed to divide properly and formed long chains. Normal growth and cell morphology were restored when the mutations were complemented in trans Morphological abnormalities were also observed upon exposure of the ΔchtR and ΔchtS mutants to bacitracin. The tolerance to both chlorhexidine and bacitracin provided by ChtRS in E. faecium highlights the overlap between responses to disinfectants and antibiotics and the potential for the development of cross-tolerance for these classes of antimicrobials.

Nomadic lifestyle of Lactobacillus plantarum revealed by comparative genomics of 54 strains isolated from different habitats.

The ability of bacteria to adapt to diverse environmental conditions is well-known. The process of bacterial adaptation to a niche has been linked to large changes in the genome content, showing that many bacterial genomes reflect the constraints imposed by their habitat. However, some highly versatile bacteria are found in diverse habitats that almost share nothing in common. Lactobacillus plantarum is a lactic acid bacterium that is found in a large variety of habitat. With the aim of unravelling the link between evolution and ecological versatility of L. plantarum, we analysed the genomes of 54 L. plantarum strains isolated from different environments. Comparative genome analysis identified a high level of genomic diversity and plasticity among the strains analysed. Phylogenomic and functional divergence studies coupled with gene-trait matching analyses revealed a mixed distribution of the strains, which was uncoupled from their environmental origin. Our findings revealed the absence of specific genomic signatures marking adaptations of L. plantarum towards the diverse habitats it is associated with. This suggests fundamentally similar trends of genome evolution in L. plantarum, which occur in a manner that is apparently uncoupled from ecological constraint and reflects the nomadic lifestyle of this species.

Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?

In the Life Sciences 'omics' data is increasingly generated by different high-throughput technologies. Often only the integration of these data allows uncovering biological insights that can be experimentally validated or mechanistically modelled, i.e. sophisticated computational approaches are required to extract the complex non-linear trends present in omics data. Classification techniques allow training a model based on variables (e.g. SNPs in genetic association studies) to separate different classes (e.g. healthy subjects versus patients). Random Forest (RF) is a versatile classification algorithm suited for the analysis of these large data sets. In the Life Sciences, RF is popular because RF classification models have a high-prediction accuracy and provide information on importance of variables for classification. For omics data, variables or conditional relations between variables are typically important for a subset of samples of the same class. For example: within a class of cancer patients certain SNP combinations may be important for a subset of patients that have a specific subtype of cancer, but not important for a different subset of patients. These conditional relationships can in principle be uncovered from the data with RF as these are implicitly taken into account by the algorithm during the creation of the classification model. This review details some of the to the best of our knowledge rarely or never used RF properties that allow maximizing the biological insights that can be extracted from complex omics data sets using RF.

Diversity in robustness of Lactococcus lactis strains during heat stress, oxidative stress, and spray drying stress.

In this study we tested 39 Lactococcus lactis strains isolated from diverse habitats for their robustness under heat and oxidative stress, demonstrating high diversity in survival (up to 4 log units). Strains with an L. lactis subsp. lactis phenotype generally displayed more-robust phenotypes than strains with an L. lactis subsp. cremoris phenotype, whereas the habitat from which the strains had been isolated did not appear to influence stress survival. Comparison of the stress survival phenotypes with already available comparative genomic data sets revealed that the absence or presence of specific genes, including genes encoding a GntR family transcriptional regulator, a manganese ABC transporter permease, a cellobiose phosphotransferase system (PTS) component, the FtsY protein, and hypothetical proteins, was associated with heat or oxidative stress survival. Finally, 14 selected strains also displayed diversity in survival after spray drying, ranging from 20% survival for the most robust strains, which appears acceptable for industrial application, to 0.1% survival for the least-tolerant strains. The high and low levels of survival upon spray drying correlated clearly with the combined robustness under heat and oxidative stress. These results demonstrate the relevance of screening culture collections for robustness under heat and oxidative stress on top of the typical screening for acidifying and flavor-forming properties.

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.

PhenoLink--a web-tool for linking phenotype to ~omics data for bacteria: application to gene-trait matching for Lactobacillus plantarum strains.

BACKGROUND: Linking phenotypes to high-throughput molecular biology information generated by ~omics technologies allows revealing cellular mechanisms underlying an organism's phenotype. ~Omics datasets are often very large and noisy with many features (e.g., genes, metabolite abundances). Thus, associating phenotypes to ~omics data requires an approach that is robust to noise and can handle large and diverse data sets. RESULTS: We developed a web-tool PhenoLink (http://bamics2.cmbi.ru.nl/websoftware/phenolink/) that links phenotype to ~omics data sets using well-established as well new techniques. PhenoLink imputes missing values and preprocesses input data (i) to decrease inherent noise in the data and (ii) to counterbalance pitfalls of the Random Forest algorithm, on which feature (e.g., gene) selection is based. Preprocessed data is used in feature (e.g., gene) selection to identify relations to phenotypes. We applied PhenoLink to identify gene-phenotype relations based on the presence/absence of 2847 genes in 42 Lactobacillus plantarum strains and phenotypic measurements of these strains in several experimental conditions, including growth on sugars and nitrogen-dioxide production. Genes were ranked based on their importance (predictive value) to correctly predict the phenotype of a given strain. In addition to known gene to phenotype relations we also found novel relations. CONCLUSIONS: PhenoLink is an easily accessible web-tool to facilitate identifying relations from large and often noisy phenotype and ~omics datasets. Visualization of links to phenotypes offered in PhenoLink allows prioritizing links, finding relations between features, finding relations between phenotypes, and identifying outliers in phenotype data. PhenoLink can be used to uncover phenotype links to a multitude of ~omics data, e.g., gene presence/absence (determined by e.g.: CGH or next-generation sequencing), gene expression (determined by e.g.: microarrays or RNA-seq), or metabolite abundance (determined by e.g.: GC-MS).

Computational approaches for network-based integrative multi-omics analysis.

Advances in omics technologies allow for holistic studies into biological systems. These studies rely on integrative data analysis techniques to obtain a comprehensive view of the dynamics of cellular processes, and molecular mechanisms. Network-based integrative approaches have revolutionized multi-omics analysis by providing the framework to represent interactions between multiple different omics-layers in a graph, which may faithfully reflect the molecular wiring in a cell. Here we review network-based multi-omics/multi-modal integrative analytical approaches. We classify these approaches according to the type of omics data supported, the methods and/or algorithms implemented, their node and/or edge weighting components, and their ability to identify key nodes and subnetworks. We show how these approaches can be used to identify biomarkers, disease subtypes, crosstalk, causality, and molecular drivers of physiological and pathological mechanisms. We provide insight into the most appropriate methods and tools for research questions as showcased around the aetiology and treatment of COVID-19 that can be informed by multi-omics data integration. We conclude with an overview of challenges associated with multi-omics network-based analysis, such as reproducibility, heterogeneity, (biological) interpretability of the results, and we highlight some future directions for network-based integration.

Whole-genome analysis of Haemophilus influenzae strains isolated from persons with cystic fibrosis.

Introduction. Haemophilus influenzae is a commensal of the respiratory tract that is frequently present in cystic fibrosis (CF) patients and may cause infection. Antibiotic resistance is well described for CF strains, and virulence factors have been proposed.Hypothesis/Gap. The genetic diversity of H. influenzae strains present in the lungs of persons with CF is largely unknown despite the fact that this organism is considered to be a pathogen in this condition. The aim was to establish the genetic diversity and susceptibility of H. influenzae strains from persons with CF, and to screen the whole genomes of these strains for the presence of antibiotic resistance determinants and proposed virulence factors.Methods. A total of 67 strains, recovered from respiratory samples from persons with CF from the UK (n=1), Poland (n=2), Spain (n=24) and the Netherlands (n=40), were subjected to whole-genome sequencing using Illumina technology and tested for antibiotic susceptibility. Forty-nine of these strains (one per different sequence type) were analysed for encoded virulence factors and resistance determinants.Results. The 67 strains represented 49 different sequence types. Susceptibility testing showed that all strains were susceptible to aztreonam, ciprofloxacin, imipenem and tetracycline. Susceptibility to ampicillin, ampicillin/sulbactam, amoxicillin/clavulanic acid, cefuroxime, cefixime, ceftriaxone, cefepime, meropenem, clarithromycin, co-trimoxazole and levofloxacin ranged from 70.2-98.5%. Only 6/49 strains (12.2%) harboured acquired resistance genes. Mutations associated with a ß-lactamase-negative ampicillin-resistant phenotype were present in four strains (8.2 %). The potential virulence factors, urease, haemoglobin- and haptoglobin-binding protein/carbamate kinase, and OmpP5 (OmpA), were encoded in more than half of the strains. The genes for HMW1, HMW2, H. influenzae adhesin, a IgA-specific serine endopeptidase autotransporter precursor, a TonB-dependent siderophore, an ABC-transporter ATP-binding protein, a methyltransferase, a BolA-family transcriptional regulator, glycosyltransferase Lic2B, a helix-turn-helix protein, an aspartate semialdehyde dehydrogenase and another glycosyltransferase were present in less than half of the strains.Conclusion. The H. influenzae strains showed limited levels of resistance, with the highest being against co-trimoxazole. Sequences encoding a carbamate kinase and a haemoglobin- and haemoglobin-haptoglobin-binding-like protein, a glycosyl transferase and an urease may aid the colonization of the CF lung. The adhesins and other identified putative virulence factors did not seem to be necessary for colonization.

Taxonomic position, antibiotic resistance and virulence factors of clinical Achromobacter isolates.

The role of Achromobacter species in lung disease remains unclear. The aim of this study was to characterize Achromobacter isolated from persons with cystic fibrosis and from other clinical samples. Whole genome sequences from 101 Achromobacter isolates were determined (81 from patients with cystic fibrosis and 20 from other patients) and analysed. Taxonomic analysis showed nine species including two putative novel species. Thirty-five novel sequence types were present. The most active agent was co-trimoxazole followed by imipenem, but Minimal Inhibitory Concentrations (MICs) were high. Acquired antibiotic resistance genes were rare. Their presence did not correlate with minimal inhibitory concentrations suggesting that other mechanisms are involved. Genes for proposed virulence factors were present in only some isolates. Two putative novel species were identified. The putative virulence properties of Achromobacter involved in infections are variable. Despite the high MICs, acquired resistance genes are uncommon.

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

UNLABELLED: 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/.

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.

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.

PanCGH: a genotype-calling algorithm for pangenome CGH data.

MOTIVATION: Pangenome arrays contain DNA oligomers targeting several sequenced reference genomes from the same species. In microbiology, these can be employed to investigate the often high genetic variability within a species by comparative genome hybridization (CGH). The biological interpretation of pangenome CGH data depends on the ability to compare strains at a functional level, particularly by comparing the presence or absence of orthologous genes. Due to the high genetic variability, available genotype-calling algorithms can not be applied to pangenome CGH data. RESULTS: We have developed the algorithm PanCGH that incorporates orthology information about genes to predict the presence or absence of orthologous genes in a query organism using CGH arrays that target the genomes of sequenced representatives of a group of microorganisms. PanCGH was tested and applied in the analysis of genetic diversity among 39 Lactococcus lactis strains from three different subspecies (lactis.cremoris, hordniae) and isolated from two different niches (dairy and plant). Clustering of these strains using the presence/absence data of gene orthologs revealed a clear separation between different subspecies and reflected the niche of the strains.

Draft Genome Sequence of a Haemophilus parainfluenzae Strain Isolated from a Patient with Chronic Obstructive Pulmonary Disease.

Haemophilus parainfluenzae is considered part of the normal oropharyngeal flora but is known to occasionally cause infections. It is closely related to Haemophilus influenzae Here, we report the genome sequence of H. parainfluenzae COPD-014-E1 O, which was cultured from the sputum of a patient with chronic obstructive pulmonary disease.