Ethylene glycol is metabolized to ethanol and acetate and induces expression of bacterial microcompartments in Propionibacterium freudenreichii.

Ethylene glycol (EG, 1,2-ethanediol) is a two-carbon dihydroxy alcohol that can be derived from fermentation of plant-derived xylose and arabinose and which can be formed during food fermentations. Here we show that Propionibacterium freudenreichii DSM 20271 is able to convert EG in anaerobic conditions to ethanol and acetate in almost equimolar amounts. The metabolism of EG led to a moderate increase of biomass, indicating its metabolism is energetically favourable. A proteomic analysis revealed EG induced expression of the pdu-cluster, which encodes a functional bacterial microcompartment (BMC) involved in the degradation of 1,2-propanediol, with the presence of BMCs confirmed using transmission electron microscopy. Cross-examination of the proteomes of 1,2-propanediol and EG grown cells revealed PDU BMC-expressing cells have elevated levels of DNA repair proteins and cysteine biosynthesis proteins. Cells grown in 1,2-propanediol and EG also showed enhanced resistance against acid and bile salt-induced stresses compared to lactate-grown cells. Our analysis of whole genome sequences of selected genomes of BMC-encoding microorganisms able to metabolize EG with acetaldehyde as intermediate indicate a potentially broad-distributed role of the pdu operon in metabolism of EG. Based on our results we conclude EG is metabolized to acetate and ethanol with acetaldehyde as intermediate within BMCs in P. freudenreichii.

Genome-scale metabolic model for Lactococcus lactis MG1363 and its application to the analysis of flavor formation.

Lactococcus lactis subsp. cremoris MG1363 is a paradigm strain for lactococci used in industrial dairy fermentations. However, despite of its importance for process development, no genome-scale metabolic model has been reported thus far. Moreover, current models for other lactococci only focus on growth and sugar degradation. A metabolic model that includes nitrogen metabolism and flavor-forming pathways is instrumental for the understanding and designing new industrial applications of these lactic acid bacteria. A genome-scale, constraint-based model of the metabolism and transport in L. lactis MG1363, accounting for 518 genes, 754 reactions, and 650 metabolites, was developed and experimentally validated. Fifty-nine reactions are directly or indirectly involved in flavor formation. Flux Balance Analysis and Flux Variability Analysis were used to investigate flux distributions within the whole metabolic network. Anaerobic carbon-limited continuous cultures were used for estimating the energetic parameters. A thorough model-driven analysis showing a highly flexible nitrogen metabolism, e.g., branched-chain amino acid catabolism which coupled with the redox balance, is pivotal for the prediction of the formation of different flavor compounds. Furthermore, the model predicted the formation of volatile sulfur compounds as a result of the fermentation. These products were subsequently identified in the experimental fermentations carried out. Thus, the genome-scale metabolic model couples the carbon and nitrogen metabolism in L. lactis MG1363 with complete known catabolic pathways leading to flavor formation. The model provided valuable insights into the metabolic networks underlying flavor formation and has the potential to contribute to new developments in dairy industries and cheese-flavor research.

Interobserver variability and the effect of education in the histopathological diagnosis of differentiated vulvar intraepithelial neoplasia.

No published data concerning intraobserver and interobserver variability in the histopathological diagnosis of differentiated vulvar intraepithelial neoplasia (DVIN) are available, although it is widely accepted to be a subtle and difficult histopathological diagnosis. In this study, the reproducibility of the histopathological diagnosis of DVIN is evaluated. Furthermore, we investigated the possible improvement of the reproducibility after providing guidelines with histological characteristics and tried to identify histological characteristics that are most important in the recognition of DVIN. A total number of 34 hematoxylin and eosin-stained slides were included in this study and were analyzed by six pathologists each with a different level of education. Slides were reviewed before and after studying a guideline with histological characteristics of DVIN. Kappa statistics were used to compare the interobserver variability. Pathologists with a substantial agreement were asked to rank items by usefulness in the recognition of DVIN. The interobserver agreement during the first session varied between 0.08 and 0.54, which slightly increased during the second session toward an agreement between -0.01 and 0.75. Pathologists specialized in gynecopathology reached a substantial agreement (kappa 0.75). The top five of criteria indicated to be the most useful in the diagnosis of DVIN included: atypical mitosis in the basal layer, basal cellular atypia, dyskeratosis, prominent nucleoli and elongation and anastomosis of rete ridges. In conclusion, the histopathological diagnosis of DVIN is difficult, which is expressed by low interobserver agreement. Only in experienced pathologists with training in gynecopathology, kappa values reached a substantial agreement after providing strict guidelines. Therefore, it should be considered that specimens with an unclear diagnosis and/or clinical suspicion for DVIN should be revised by a pathologist specialized in gynecopathology. When adhering to suggested criteria the diagnosis of DVIN can be made easier.

Correlation of immunohistochemical staining p63 and TTF-1 with EGFR and K-ras mutational spectrum and diagnostic reproducibility in non small cell lung carcinoma.

For treatment purposes, distinction between squamous cell carcinoma and adenocarcinoma is important. The aim of this study is to examine the diagnostic accuracy on lung cancer small biopsies for the distinction between adenocarcinoma and squamous cell carcinoma and relate these to immunohistochemical and KRAS and EGFR mutation analysis. An interobserver study was performed on 110 prospectively collected biopsies obtained by bronchoscopy or transthoracic needle biopsy of patients with non-small cell lung cancer. The diagnosis was correlated with immunohistochemical (IHC) analysis for markers of adeno- (TTF1 and/or mucin positivity) and squamous cell differentiation (P63 and CK5/6) as well as KRAS and EGFR mutation analysis. Eleven observers independently read H&E-stained slides of 110 cases, resulting in a kappa value of 0.55 ± 0.10. The diagnosis non-small cell lung cancer not otherwise specified was given on average on 29.5 % of the biopsies. A high concordance was observed between hematoxylin-eosin-based consensus diagnosis (≥8/11 readings concordant) and IHC markers. In all cases with EGFR (n = 1) and KRAS (n = 20) mutations, adenodifferentiation as determined by IHC was present and p63 staining was absent. In 2 of 25 cases with a consensus diagnosis of squamous cell carcinoma, additional stainings favored adenodifferentation, and a KRAS mutation was present. P63 is most useful for distinction between EGFR/KRAS mutation positive and negative patients. In the diagnostic work-up of non-small cell lung carcinoma the limited reproducibility on small biopsies is optimized with immunohistochemical analysis, resulting in reliable delineation for predictive analysis.

Transcriptomes reveal genetic signatures underlying physiological variations imposed by different fermentation conditions in Lactobacillus plantarum.

Lactic acid bacteria (LAB) are utilized widely for the fermentation of foods. In the current post-genomic era, tools have been developed that explore genetic diversity among LAB strains aiming to link these variations to differential phenotypes observed in the strains investigated. However, these genotype-phenotype matching approaches fail to assess the role of conserved genes in the determination of physiological characteristics of cultures by environmental conditions. This manuscript describes a complementary approach in which Lactobacillus plantarum WCFS1 was fermented under a variety of conditions that differ in temperature, pH, as well as NaCl, amino acid, and O(2) levels. Samples derived from these fermentations were analyzed by full-genome transcriptomics, paralleled by the assessment of physiological characteristics, e.g., maximum growth rate, yield, and organic acid profiles. A data-storage and -mining suite designated FermDB was constructed and exploited to identify correlations between fermentation conditions and industrially relevant physiological characteristics of L. plantarum, as well as the associated transcriptome signatures. Finally, integration of the specific fermentation variables with the transcriptomes enabled the reconstruction of the gene-regulatory networks involved. The fermentation-genomics platform presented here is a valuable complementary approach to earlier described genotype-phenotype matching strategies which allows the identification of transcriptome signatures underlying physiological variations imposed by different fermentation conditions.

Understanding the adaptive growth strategy of Lactobacillus plantarum by in silico optimisation.

In the study of metabolic networks, optimization techniques are often used to predict flux distributions, and hence, metabolic phenotype. Flux balance analysis in particular has been successful in predicting metabolic phenotypes. However, an inherent limitation of a stoichiometric approach such as flux balance analysis is that it can predict only flux distributions that result in maximal yields. Hence, previous attempts to use FBA to predict metabolic fluxes in Lactobacillus plantarum failed, as this lactic acid bacterium produces lactate, even under glucose-limited chemostat conditions, where FBA predicted mixed acid fermentation as an alternative pathway leading to a higher yield. In this study we tested, however, whether long-term adaptation on an unusual and poor carbon source (for this bacterium) would select for mutants with optimal biomass yields. We have therefore adapted Lactobacillus plantarum to grow well on glycerol as its main growth substrate. After prolonged serial dilutions, the growth yield and corresponding fluxes were compared to in silico predictions. Surprisingly, the organism still produced mainly lactate, which was corroborated by FBA to indeed be optimal. To understand these results, constraint-based elementary flux mode analysis was developed that predicted 3 out of 2669 possible flux modes to be optimal under the experimental conditions. These optimal pathways corresponded very closely to the experimentally observed fluxes and explained lactate formation as the result of competition for oxygen by the other flux modes. Hence, these results provide thorough understanding of adaptive evolution, allowing in silico predictions of the resulting flux states, provided that the selective growth conditions favor yield optimization as the winning strategy.

Improvement of Lactobacillus plantarum aerobic growth as directed by comprehensive transcriptome analysis.

An aerobic Lactobacillus plantarum culture displayed growth stagnation during early growth. Transcriptome analysis revealed that resumption of growth after stagnation correlated with activation of CO(2)-producing pathways, suggesting that a limiting CO(2) concentration induced the stagnation. Analogously, increasing the CO(2) gas partial pressure during aerobic fermentation prevented the temporal growth stagnation.

High-level production of the low-calorie sugar sorbitol by Lactobacillus plantarum through metabolic engineering.

Sorbitol is a low-calorie sugar alcohol that is largely used as an ingredient in the food industry, based on its sweetness and its high solubility. Here, we investigated the capacity of Lactobacillus plantarum, a lactic acid bacterium found in many fermented food products and in the gastrointestinal tract of mammals, to produce sorbitol from fructose-6-phosphate by reverting the sorbitol catabolic pathway in a mutant strain deficient for both l- and d-lactate dehydrogenase activities. The two sorbitol-6-phosphate dehydrogenase (Stl6PDH) genes (srlD1 and srlD2) identified in the genome sequence were constitutively expressed at a high level in this mutant strain. Both Stl6PDH enzymes were shown to be active, and high specific activity could be detected in the overexpressing strains. Using resting cells under pH control with glucose as a substrate, both Stl6PDHs were capable of rerouting the glycolytic flux from fructose-6-phosphate toward sorbitol production with a remarkably high efficiency (61 to 65% glucose conversion), which is close to the maximal theoretical value of 67%. Mannitol production was also detected, albeit at a lower level than the control strain (9 to 13% glucose conversion), indicating competition for fructose-6-phosphate rerouting by natively expressed mannitol-1-phosphate dehydrogenase. By analogy, low levels of this enzyme were detected in both the wild-type and the lactate dehydrogenase-deficient strain backgrounds. After optimization, 25% of sugar conversion into sorbitol was achieved with cells grown under pH control. The role of intracellular NADH pools in the determination of the maximal sorbitol production is discussed.

Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model.

A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for interpretation of complex fermentation data, as L. plantarum is adapted to nutrient-rich environments and only grows in media supplemented with vitamins and amino acids. (i) Based on experimental input and output fluxes, maximal ATP production was estimated and related to growth rate. (ii) Optimization of ATP production further identified amino acid catabolic pathways that were not previously associated with free-energy metabolism. (iii) Genome-scale elementary flux mode analysis identified 28 potential futile cycles. (iv) Flux variability analysis supplemented the elementary mode analysis in identifying parallel pathways, e.g. pathways with identical end products but different co-factor usage. Strongly increased flexibility in the metabolic network was observed when strict coupling between catabolic ATP production and anabolic consumption was relaxed. These results illustrate how a genome-scale metabolic model and associated constraint-based modeling techniques can be used to analyze the physiology of growth on a complex medium rather than a minimal salts medium. However, optimization of biomass formation using the Flux Balance Analysis approach, reported to successfully predict growth rate and by product formation in Escherichia coli and Saccharomyces cerevisiae, predicted too high biomass yields that were incompatible with the observed lactate production. The reason is that this approach assumes optimal efficiency of substrate to biomass conversion, and can therefore not predict the metabolically inefficient lactate formation.

In silico reconstruction of the metabolic pathways of Lactobacillus plantarum: comparing predictions of nutrient requirements with those from growth experiments.

On the basis of the annotated genome we reconstructed the metabolic pathways of the lactic acid bacterium Lactobacillus plantarum WCFS1. After automatic reconstruction by the Pathologic tool of Pathway Tools (http://bioinformatics.ai.sri.com/ptools/), the resulting pathway-genome database, LacplantCyc, was manually curated extensively. The current database contains refinements to existing routes and new gram-positive bacterium-specific reactions that were not present in the MetaCyc database. These reactions include, for example, reactions related to cell wall biosynthesis, molybdopterin biosynthesis, and transport. At present, LacplantCyc includes 129 pathways and 704 predicted reactions involving some 670 chemical species and 710 enzymes. We tested vitamin and amino acid requirements of L. plantarum experimentally and compared the results with the pathways present in LacplantCyc. In the majority of cases (32 of 37 cases) the experimental results agreed with the final reconstruction. LacplantCyc is the most extensively curated pathway-genome database for gram-positive bacteria and is open to the microbiology community via the World Wide Web (www.lacplantcyc.nl). It can be used as a reference pathway-genome database for gram-positive microbes in general and lactic acid bacteria in particular.

Biodiversity-based identification and functional characterization of the mannose-specific adhesin of Lactobacillus plantarum.

Lactobacillus plantarum is a frequently encountered inhabitant of the human intestinal tract, and some strains are marketed as probiotics. Their ability to adhere to mannose residues is a potentially interesting characteristic with regard to proposed probiotic features such as colonization of the intestinal surface and competitive exclusion of pathogens. In this study, the variable capacity of 14 L. plantarum strains to agglutinate Saccharomyces cerevisiae in a mannose-specific manner was determined and subsequently correlated with an L. plantarum WCFS1-based genome-wide genotype database. This led to the identification of four candidate mannose adhesin-encoding genes. Two genes primarily predicted to code for sortase-dependent cell surface proteins displayed a complete gene-trait match. Their involvement in mannose adhesion was corroborated by the finding that a sortase (srtA) mutant of L. plantarum WCFS1 lost the capacity to agglutinate S. cerevisiae. The postulated role of these two candidate genes was investigated by gene-specific deletion and overexpression in L. plantarum WCFS1. Subsequent evaluation of the mannose adhesion capacity of the resulting mutant strains showed that inactivation of one candidate gene (lp_0373) did not affect mannose adhesion properties. In contrast, deletion of the other gene (lp_1229) resulted in a complete loss of yeast agglutination ability, while its overexpression quantitatively enhanced this phenotype. Therefore, this gene was designated to encode the mannose-specific adhesin (Msa; gene name, msa) of L. plantarum. Domain homology analysis of the predicted 1,000-residue Msa protein identified known carbohydrate-binding domains, further supporting its role as a mannose adhesin that is likely to be involved in the interaction of L. plantarum with its host in the intestinal tract.