Multivariate analysis of microarray data by principal component discriminant analysis: prioritizing relevant transcripts linked to the degradation of different carbohydrates in Pseudomonas putida S12

Non-Invasive microRNA Profiling in Saliva can Serve as a Biomarker of Alcohol Exposure and Its Effects in Humans

Alcohol Use Disorder (AUD) is one of the most prevalent mental disorders worldwide. Considering the widespread occurrence of AUD, a reliable, cheap, non-invasive biomarker of alcohol consumption is desired by healthcare providers, clinicians, researchers, public health and criminal justice officials. microRNAs could serve as such biomarkers. They are easily detectable in saliva, which can be sampled from individuals in a non-invasive manner. Moreover, microRNAs expression is dynamically regulated by environmental factors, including alcohol. Since excessive alcohol consumption is a hallmark of alcohol abuse, we have profiled microRNA expression in the saliva of chronic, heavy alcohol abusers using microRNA microarrays. We observed significant changes in salivary microRNA expression caused by excessive alcohol consumption. These changes fell into three categories: downregulated microRNAs, upregulated microRNAs, and microRNAs upregulated de novo. Analysis of these combinatorial changes in microRNA expression suggests dysregulation of specific biological pathways leading to impairment of the immune system and development of several types of epithelial cancer. Moreover, some of the altered microRNAs are also modulators of inflammation, suggesting their contribution to pro-inflammatory mechanisms of alcohol actions. Establishment of the cellular source of microRNAs in saliva corroborated these results. We determined that most of the microRNAs in saliva come from two types of cells: leukocytes involved in immune responses and inflammation, and buccal cells, involved in development of epithelial, oral cancers. In summary, we propose that microRNA profiling in saliva can be a useful, non-invasive biomarker allowing the monitoring of alcohol abuse, as well as alcohol-related inflammation and early detection of cancer.

Biofilm formation and antibiotic susceptibility in dispersed cells versus planktonic cells from clinical, industry and environmental origins

We examined the cell-surface physicochemical properties, the biofilm formation capability and the antibiotic susceptibility in dispersed cells (from an artificial biofilm of alginate beads) and compared with their planktonic (free-swimming) counterparts. The strains used were from different origins, such as clinical (Acinetobacter baumannii AB4), cosmetic industry (Klebsiella oxytoca EU213, Pseudomonas aeruginosa EU190), and environmental (Halomonas venusta MAT28). In general, dispersed cells adhered better to surfaces (measured as the "biofilm index") and had a greater hydrophobicity [measured as the microbial affinity to solvents (MATS)] than planktonic cells. The susceptibility to two antibiotics (ciprofloxacin and tetracycline) of dispersed cells was higher compared with that of their planktonic counterparts (tested by the "bactericidal index"). Dispersed and planktonic cells exhibited differences in cell permeability, especially in efflux pump activity, which could be related to the differences observed in susceptibility to antibiotics. At 1 h of biofilm formation in microtiter plates, dispersed cells treated with therapeutic concentration of ciprofloxacin yielded a lower biofilm index than the control dispersed cells without ciprofloxacin. With respect to the planktonic cells, the biofilm index was similar with and without the ciprofloxacin treatment. In both cases there were a reduction of the number of bacteria measured as viable count of the supernatant. The lower biofilm formation in dispersed cells with ciprofloxacin treatment may be due to a significant increase of biofilm disruption with respect to the biofilm from planktonic cells. From a clinical point of view, biofilms formed on medical devices such as catheters, cells that can be related to an infection were the dispersed cells. Our results showed that early treatment with ciprofloxacin of dispersed cells could diminishe bacterial dispersion and facilitate the partial elimination of the new biofilm formed.

Redox processes inform multivariate transdifferentiation trajectories associated with TGFβ-induced epithelial-mesenchymal transition

Phenotype reprogramming during transforming growth factor β (TGFβ)-induced epithelial-mesenchymal transition (EMT) is an extensive and dynamic process, orchestrated by the integration of biological signaling across multiple time scales. As part of the numerous transcriptional changes necessary for EMT, TGFβ-initiated Smad3 signaling results in remodeling of the redox environment and decreased nucleophilic tone. Because Smad3 itself is susceptible to attenuated activity through antioxidants, the possibility of a positive feedback loop exists, albeit the time scales on which these mechanisms operate are quite different. We hypothesized that the decreased nucleophilic tone acquired during EMT promotes Smad3 signaling, enhancing acquisition and stabilization of the mesenchymal phenotype. Previous findings supporting such a mechanism were characterized independent of each other; we sought to investigate these relationships within a singular experimental context. In this study, we characterized multivariate representations of phenotype as they evolved over time, specifically measuring expression of epithelial/mesenchymal differentiation, redox regulators, and Smad transcription factors. In-cell Western (ICW) assays were developed to evaluate multivariate phenotype states as they developed during EMT. Principal component analysis (PCA) extracted anticorrelations between phospho-Smad3 (pSmad3) and Smad2/Smad4, which reflected a compensatory up-regulation of Smad2 and Smad4 following cessation of TGFβ signaling. Measuring transcript expression following EMT, we identified down-regulation of numerous antioxidant genes concomitant with up-regulation of NADPH oxidase 4 (NOX4) and multiple mesenchymal phenotype markers. TGFβ treatment increased CM-H2DCF-DA oxidation, decreased H2O2 degradation rates, and increased glutathione redox potential. Our findings suggest that the decreased nucleophilic tone during EMT coincides with the acquisition of a mesenchymal phenotype over too long a time scale to enable enhanced Smad3 phosphorylation during initiation of EMT. We further challenged the mesenchymal phenotype following EMT through antioxidant and TGFβ inhibitor treatments, which failed to induce a mesenchymal-epithelial transition (MET). Our characterization of multivariate phenotype dynamics during EMT indicates that the decrease in nucleophilic tone occurs alongside EMT; however, maintenance of the mesenchymal phenotype following EMT is independent of both the nascent redox state and the continuous TGFβ signaling.

Poly(N-isopropylacrylamide)-stabilized gold nanoparticles in combination with tricationic branched phenylene-ethynylene fluorophore for protein identification

Gold nanoparticles stabilized by thermoresponsive polymer, poly(N-isopropylacrylamide) (PNIPAM-AuNPs) were prepared by surface grafting of thiol-terminated PNIPAM onto citrate-stabilized AuNPs. The color change of the PNIPAM-AuNPs solution from red to blue-purple without precipitation when the solution was heated to 40 °C, above the lower critical solution temperature (LCST) of PNIPAM, indicated the thermoresponsive property of the synthesized AuNPs. PNIPAM-AuNPs were used to detect proteins by chemical nose approach based on fluorescence quenching of fluorophore by AuNPs. An array-based sensing platform for detection of six proteins, namely bovine serum albumin, lysozyme, fibrinogen, concanavalin A, hemoglobin, holo-transferrin human can be successfully developed from the PNIPAM-AuNPs having different molecular weights (4 and 8 kDa) and conformation (varied heat treatment from 25 to 40 °C) in combination with a tricationic branched phenylene-ethynylene fluorophore. From principal component analysis (PCA) followed by linear discriminant analysis (LDA), 100% accuracy of protein classification using a leave-one-out (LOO) approach can be achieved by using only two types of PNIPAM-AuNPs.

Looking back into the future: 30 years of metabolomics at TNO

Metabolites have played an essential role in our understanding of life, health, and disease for thousands of years. This domain became much more important after the concept of metabolism was discovered. In the 1950s, mass spectrometry was coupled to chromatography and made the technique more application-oriented and allowed the development of new profiling technologies. Since 1980, TNO has performed system-based metabolic profiling of body fluids, and combined with pattern recognition has led to many discoveries and contributed to the field known as metabolomics and systems biology. This review describes the development of related concepts and applications at TNO in the biomedical, pharmaceutical, nutritional, and microbiological fields, and provides an outlook for the future.

Identification of biomarkers for intake of protein from meat, dairy products and grains: a controlled dietary intervention study

In the present controlled, randomised, multiple cross-over dietary intervention study, we aimed to identify potential biomarkers for dietary protein from dairy products, meat and grain, which could be useful to estimate intake of these protein types in epidemiological studies. After 9 d run-in, thirty men and seventeen women (22 (sd4) years) received three high-protein diets (aimed at approximately 18 % of energy (en%)) in random order for 1 week each, with approximately 14 en% originating from either meat, dairy products or grain. We used a two-step approach to identify biomarkers in urine and plasma. With principal component discriminant analysis, we identified amino acids (AA) from the plasma or urinary AA profile that were distinctive between diets. Subsequently, after pooling total study data, we applied mixed models to estimate the predictive value of those AA for intake of protein types. A very good prediction could be made for the intake of meat protein by a regression model that included urinary carnosine, 1-methylhistidine and 3-methylhistidine (98 % of variation in intake explained). Furthermore, for dietary grain protein, a model that included seven AA (plasma lysine, valine, threonine, α-aminobutyric acid, proline, ornithine and arginine) made a good prediction (75 % of variation explained). We could not identify biomarkers for dairy protein intake. In conclusion, specific combinations of urinary and plasma AA may be potentially useful biomarkers for meat and grain protein intake, respectively. These findings need to be cross-validated in other dietary intervention studies.

Conserved and specific responses to hypoxia in Aspergillus oryzae and Aspergillus nidulans determined by comparative transcriptomics

Hypoxia imposes stress on filamentous fungi that require oxygen to proliferate. Global transcription analysis of Aspergillus oryzae grown under hypoxic conditions found that the expression of about 50% of 4,244 affected genes was either induced or repressed more than 2-fold. A comparison of these genes with the hypoxically regulated genes of Aspergillus nidulans based on their predicted amino acid sequences classified them as bi-directional best hit (BBH), one-way best hit (extra homolog, EH), and no-hit (non-syntenic genes, NSG) genes. Clustering analysis of the BBH genes indicated that A. oryzae and A. nidulans down-regulated global translation and transcription under hypoxic conditions, respectively. Under hypoxic conditions, both fungi up-regulated genes for alcohol fermentation and the γ-aminobutyrate shunt of the tricarboxylate cycle, whereas A. oryzae up-regulated the glyoxylate pathway, indicating that both fungi eliminate NADH accumulation under hypoxic conditions. The A. oryzae NS genes included specific genes for secondary and nitric oxide metabolism under hypoxic conditions. This comparative transcriptomic analysis discovered common and strain-specific responses to hypoxia in hypoxic Aspergillus species.

Global gene expression analysis of Aspergillus nidulans reveals metabolic shift and transcription suppression under hypoxia

Hypoxia imposes a challenge upon most filamentous fungi that require oxygen for proliferation. Here, we used whole genome DNA microarrays to investigate global transcriptional changes in Aspergillus nidulans gene expression after exposure to hypoxia followed by normoxia. Aeration affected the expression of 2,864 genes (27% of the total number of genes in the fungus), of which 50% were either induced or repressed under hypoxic conditions. Up-regulated genes included those for glycolysis, ethanol production, the tricarboxylic acid (TCA) cycle, and for the γ-aminobutyrate (GABA) shunt that bypasses two steps of the TCA cycle. Ethanol and lactate production under hypoxic conditions indicated that glucose was fermented to these compounds via the glycolytic pathway. Since the GABA shunt bypasses the NADH-generating reaction of the TCA cycle catalyzed by oxoglutarate dehydrogenase, hypoxic A. nidulans cells eliminated excess NADH. Hypoxia down-regulated some genes involved in transcription initiation by RNA polymerase II, and lowered the cellular mRNA content. These functions were resumed by re-oxygenation, indicating that A. nidulans controls global transcription to adapt to a hypoxic environment. This study is the first to show that hypoxia elicits systematic transcriptional responses in A. nidulans.

Global gene expression analysis during sporulation of the aquatic fungus Blastocladiella emersonii

The Blastocladiella emersonii life cycle presents a number of drastic biochemical and morphological changes, mainly during two cell differentiation stages: germination and sporulation. To investigate the transcriptional changes taking place during the sporulation phase, which culminates with the production of the zoospores, motile cells responsible for the dispersal of the fungus, microarray experiments were performed. Among the 3,773 distinct genes investigated, a total of 1,207 were classified as differentially expressed, relative to time zero of sporulation, at at least one of the time points analyzed. These results indicate that accurate transcriptional control takes place during sporulation, as well as indicating the necessity for distinct molecular functions throughout this differentiation process. The main functional categories overrepresented among upregulated genes were those involving the microtubule, the cytoskeleton, signal transduction involving Ca(2+), and chromosome organization. On the other hand, protein biosynthesis, central carbon metabolism, and protein degradation were the most represented functional categories among downregulated genes. Gene expression changes were also analyzed in cells sporulating in the presence of subinhibitory concentrations of glucose or tryptophan. Data obtained revealed overexpression of microtubule and cytoskeleton transcripts in the presence of glucose, probably causing the shape and motility problems observed in the zoospores produced under this condition. In contrast, the presence of tryptophan during sporulation led to upregulation of genes involved in oxidative stress, proteolysis, and protein folding. These results indicate that distinct physiological pathways are involved in the inhibition of sporulation due to these two classes of nutrient sources.

Transcriptomic-based bioassays for the detection of type A trichothecenes

The type A trichothecenes T-2 toxin (T-2) and HT-2 toxin (HT-2) are hazardous Fusarium products that contaminate many field crops growing in cold to temperate regions across the world. Toxicity studies in laboratory and farm animals have been used to derive a temporary tolerable daily intake (t-TDI) for the sum of T-2 and HT-2 of no more than 60 ng/kg body weight. To protect the consumers, it is now necessary to screen a large number of food samples for the presence of these poisonous fungal metabolites. Towards that goal, we discovered that the transcriptional apparatus of a human carcinoma cell line (MCF7) provides a sensitive biological sensor of type A trichothecenes. In fact, exposure of this easy-to-culture cell line to T-2 or HT-2 results in the regulation of >2,000 different transcripts with expression changes ranging from >5,000-fold gene inductions to >40-fold gene repressions. These transcriptional responses have been exploited to develop practical microchip and reverse transcription-polymerase chain reaction (RT-PCR) assays for the detection of type A trichothecenes at parts per billion levels.

Salmonella Sofia differs from other poultry-associated Salmonella serovars with respect to cell surface hydrophobicity

Salmonella enterica is one of the most important foodborne pathogens. Salmonella enterica subsp. II 4,12:b:- (Salmonella Sofia) is commonly found in Australian poultry. It has been suggested that physicochemical properties such as surface charge and hydrophobicity may affect bacterial attachment to surfaces and their ability to persist in food systems. A possible link between hydrophobicity cell surface charge and persistence of Salmonella from the poultry system was examined. Hydrophobicity of Salmonella Sofia (n = 14), Salmonella Typhimurium (n = 6), Salmonella Infantis (n = 3), and Salmonella Virchow (n = 2) was assayed using hydrophobic interaction chromatography, bacterial adherence to hydrocarbons (BATH), using xylene or hexadecane, and the contact angle method (CAM). Cellular surface charge (CSC) of the isolates was determined using zeta potential measurements. The majority (12 of 14) of Salmonella Sofia isolates were found to be hydrophobic when assayed using BATH with xylene, except isolates S1635 and S1636, and the other serovars were found to be hydrophilic. Salmonella Sofia isolates were not significantly different (P > 0.05) from isolates of other serovars as measured by hydrophobic interaction, BATH with hexadecane, or the CAM. No significant differences (P > 0.05) in zeta potential measurements were observed between isolates. Principal component analysis using results from all four measures of hydrophobicity allowed clear differentiation between isolates of the serovar Salmonella Sofia (except S1635 and S1636) and those of other Salmonella serovars. Differences in physicochemical properties may be a contributing factor to the Salmonella Sofia serovar's ability to attach to surfaces and persist in a food system.

Transmission of Vibrio cholerae is antagonized by lytic phage and entry into the aquatic environment

Cholera outbreaks are proposed to propagate in explosive cycles powered by hyperinfectious Vibrio cholerae and quenched by lytic vibriophage. However, studies to elucidate how these factors affect transmission are lacking because the field experiments are almost intractable. One reason for this is that V. cholerae loses the ability to culture upon transfer to pond water. This phenotype is called the active but non-culturable state (ABNC; an alternative term is viable but non-culturable) because these cells maintain the capacity for metabolic activity. ABNC bacteria may serve as the environmental reservoir for outbreaks but rigorous animal studies to test this hypothesis have not been conducted. In this project, we wanted to determine the relevance of ABNC cells to transmission as well as the impact lytic phage have on V. cholerae as the bacteria enter the ABNC state. Rice-water stool that naturally harbored lytic phage or in vitro derived V. cholerae were incubated in a pond microcosm, and the culturability, infectious dose, and transcriptome were assayed over 24 h. The data show that the major contributors to infection are culturable V. cholerae and not ABNC cells. Phage did not affect colonization immediately after shedding from the patients because the phage titer was too low. However, V. cholerae failed to colonize the small intestine after 24 h of incubation in pond water—the point when the phage and ABNC cell titers were highest. The transcriptional analysis traced the transformation into the non-infectious ABNC state and supports models for the adaptation to nutrient poor aquatic environments. Phage had an undetectable impact on this adaptation. Taken together, the rise of ABNC cells and lytic phage blocked transmission. Thus, there is a fitness advantage if V. cholerae can make a rapid transfer to the next host before these negative selective pressures compound in the aquatic environment.

The biological factors that control the transmission of water-borne pathogens like Vibrio cholerae during outbreaks are ill defined. In this study, a molecular analysis of the active but non-culturable (ABNC) state of V. cholerae provides insights into the physiology of environmental adaptation. The ABNC state, lytic phage, and hyperinfectivity were concurrently followed as V. cholerae passaged from cholera patients to an aquatic reservoir. The relevance to transmission of each factor was weighed against the others. As the bacteria transitioned from the patient to pond water, there was a rapid decay into the ABNC state and a rise of lytic phage that compounded to block transmission in a mouse model. These two factors give reason for V. cholerae to make a quick transit through the environment and onto the next human host. Thus, in over-crowded locations with failed water infrastructure, the opportunity for fast transmission coupled with the increased infectivity and culturability of recently shed V. cholerae creates a charged setting for explosive cholera outbreaks.

Comprehensive analysis of the metabolome of Pseudomonas putida S12 grown on different carbon sources

Metabolomics is an emerging, powerful, functional genomics technology that involves the comparative non-targeted analysis of the complete set of metabolites in an organism. We have set-up a robust quantitative metabolomics platform that allows the analysis of 'snapshot' metabolomes. In this study, we have applied this platform for the comprehensive analysis of the metabolite composition of Pseudomonas putida S12 grown on four different carbon sources, i.e. fructose, glucose, gluconate and succinate. This paper focuses on the microbial aspects of analyzing comprehensive metabolomes, and demonstrates that metabolomes can be analyzed reliably. The technical (i.e. sample work-up and analytical) reproducibility was on average 10%, while the biological reproducibility was approximately 40%. Moreover, the energy charge values of the microbial samples generated were determined, and indicated that no biotic or abiotic changes had occurred during sample work-up and analysis. In general, the metabolites present and their concentrations were very similar after growth on the different carbon sources. However, specific metabolites showed large differences in concentration, especially the intermediates involved in the degradation of the carbon sources studied. Principal component discriminant analysis was applied to identify metabolites that are specific for, i.e. not necessarily the metabolites that show those largest differences in concentration, cells grown on either of these four carbon sources. For selected enzymatic reactions, i.e. the glucose-6-phosphate isomerase, triosephosphate isomerase and phosphoglyceromutase reactions, the apparent equilibrium constants (K(app)) were calculated. In several instances a carbon source-dependent deviation between the apparent equilibrium constant (K(app)) and the thermodynamic equilibrium constant (K(eq)) was observed, hinting towards a potential point of metabolic regulation or towards bottlenecks in biosynthesis routes. For glucose-6-phosphate isomerase and phosphoglyceromutase, the K(app) was larger than K(eq), and the results suggested that the specific enzymatic activities of these two enzymes were too low to reach the thermodynamic equilibrium in growing cells. In contrast, with triosephosphate isomerase the K(app) was smaller than K(eq), and the results suggested that this enzyme is kinetically controlled.

Microbial metabolomics: Toward a platform with full metabolome coverage

Achieving metabolome data with satisfactory coverage is a formidable challenge in metabolomics because metabolites are a chemically highly diverse group of compounds. Here we present a strategy for the development of an advanced analytical platform that allows the comprehensive analysis of microbial metabolomes. Our approach started with in silico metabolome information from three microorganisms-Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae-and resulted in a list of 905 different metabolites. Subsequently, these metabolites were classified based on their physicochemical properties, followed by the development of complementary gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry methods, each of which analyzes different metabolite classes. This metabolomics platform, consisting of six different analytical methods, was applied for the analysis of the metabolites for which commercial standards could be purchased (399 compounds). Of these 399 metabolites, 380 could be analyzed with the platform. To demonstrate the potential of this metabolomics platform, we report on its application to the analysis of the metabolome composition of mid-logarithmic E. coli cells grown on a mineral salts medium using glucose as the carbon source. Of the 431 peaks detected, 235 (=176 unique metabolites) could be identified. These include 61 metabolites that were not previously identified or annotated in existing E. coli databases.

Expression profile of human cells in culture exposed to glycidamide, a reactive metabolite of the heat-induced food carcinogen acrylamide

Recent findings of acrylamide in many common foods have sparked renewed interest in assessing human health hazards and the long-term risk associated with exposure to vinyl compounds. Acrylamide is tumorigenic at high doses in rodents and has been classified as a probable human carcinogen. However, cancer risk projections in the population remain problematic because the molecular pathogenesis of acrylamide at the low level of dietary uptake is not understood. In particular, the question of whether specific transcriptional responses may amplify or mitigate the known genotoxicity of acrylamide has never been examined. Here, we used high-density DNA microarrays and PCR validations to assess genome-wide messenger profiles induced by glycidamide, the more reactive metabolite of acrylamide. The expression changes resulting from glycidamide treatment of human epithelial cells are characterized by the induction of detoxification enzymes, several members of the glutathione system and antioxidant factors. Low-dose experiments indicate that the up-regulation of epoxide hydrolase 1 represents the most sensitive transcriptional biomarker of glycidamide exposure. At higher concentrations, glycidamide induces typical markers of tumor progression such as steroid hormone activators, positive regulators of nuclear factor-kappaB, growth stimulators and apoptosis inhibitors. Concomitantly, growth suppressors and cell adhesion molecules are down-regulated. The main implication of these findings for risk assessment is that low concentrations of glycidamide elicit cytoprotective reactions whereas transcriptional signatures associated with tumor progression may be expected only at doses that exceed the range of ordinary dietary exposures.

Multivariate analysis of low-dose radiation-associated changes in cytokine gene expression profiles using microarray technology

OBJECTIVE

The availability of microarray technology, which permits evaluation of the entire cellular transcriptome in a single experiment, has provided new insights on the function of the genome under normal and pathological conditions, as well as in response to genotoxic stimuli, including ionizing radiation. The aims of this study were to: 1) determine whether specific cytokine gene expression profiles can be delineated in individuals exposed to chronic, low-dose radiation; and 2) compare analyses from three multivariate analytic methodologies, hierarchical clustering analysis (HCA), principal component analysis (PCA), and projection pursuit (PP), in evaluating transcriptional responses in human mononuclear cells to low doses of ionizing radiation (IR), as determined by cDNA microarrays.

MATERIALS AND METHODS

Total RNA isolated from mononuclear cells of 19 apparently healthy adult individuals exposed to low doses of IR ranging from 0.18 mSv to 49 mSv over a period of 11 to 13 years, as a result of the Chernobyl Nuclear Power Plant catastrophe, was reverse transcribed in the presence of radioactive dATP to generate radiolabeled complementary cDNA. Target cDNA was hybridized to human cytokine and receptor arrays and mRNA transcriptional patterns were evaluated using HCA, PCA, and PP.

RESULTS

Statistical analyses of the data generated from 19 microarrays revealed distinct gene expression patterns in mononuclear cells of individuals exposed to radiation doses of greater than 10 mSv or less than 10 mSv. Genes encompassed within clusters discerned by HCA, PCA, and PP varied depending on the methodology used to analyze the microarray data. The most frequently expressed genes across all radiation doses were serine/threonine protein kinase receptor (11/19), transforming growth factor (TGF) receptor (11/19), EB13 (10/19), and CD40 ligand.

CONCLUSIONS

Although our findings suggest that it may be possible to assign gene expression profiles to low-dose-irradiated individuals, we show that gene expression profiles vary, depending on the statistical method used to analyze the data. Since there is, as of yet, no consensus regarding the best method to analyze a multivariate dataset, and since discarding the raw data and repeating the experiment at a later date constitutes an unwarranted expenditure, it is important to submit microarray data to public databases where these data can be reevaluated and interpreted by investigators holding expertise in various fields within the scientific community, including radiation biology, statistics, and bioinformatics.

Convergent peripheral pathways catalyze initial glucose catabolism in Pseudomonas putida: genomic and flux analysis

In this study, we show that glucose catabolism in Pseudomonas putida occurs through the simultaneous operation of three pathways that converge at the level of 6-phosphogluconate, which is metabolized by the Edd and Eda Entner/Doudoroff enzymes to central metabolites. When glucose enters the periplasmic space through specific OprB porins, it can either be internalized into the cytoplasm or be oxidized to gluconate. Glucose is transported to the cytoplasm in a process mediated by an ABC uptake system encoded by open reading frames PP1015 to PP1018 and is then phosphorylated by glucokinase (encoded by the glk gene) and converted by glucose-6-phosphate dehydrogenase (encoded by the zwf genes) to 6-phosphogluconate. Gluconate in the periplasm can be transported into the cytoplasm and subsequently phosphorylated by gluconokinase to 6-phosphogluconate or oxidized to 2-ketogluconate, which is transported to the cytoplasm, and subsequently phosphorylated and reduced to 6-phosphogluconate. In the wild-type strain, glucose was consumed at a rate of around 6 mmol g(-1) h(-1), which allowed a growth rate of 0.58 h(-1) and a biomass yield of 0.44 g/g carbon used. Flux analysis of (13)C-labeled glucose revealed that, in the Krebs cycle, most of the oxalacetate fraction was produced by the pyruvate shunt rather than by the direct oxidation of malate by malate dehydrogenase. Enzymatic and microarray assays revealed that the enzymes, regulators, and transport systems of the three peripheral glucose pathways were induced in response to glucose in the outer medium. We generated a series of isogenic mutants in one or more of the steps of all three pathways and found that, although all three functioned simultaneously, the glucokinase pathway and the 2-ketogluconate loop were quantitatively more important than the direct phosphorylation of gluconate. In physical terms, glucose catabolism genes were organized in a series of clusters scattered along the chromosome. Within each of the clusters, genes encoding porins, transporters, enzymes, and regulators formed operons, suggesting that genes in each cluster coevolved. The glk gene encoding glucokinase was located in an operon with the edd gene, whereas the zwf-1 gene, encoding glucose-6-phosphate dehydrogenase, formed an operon with the eda gene. Therefore, the enzymes of the glucokinase pathway and those of the Entner-Doudoroff pathway are physically linked and induced simultaneously. It can therefore be concluded that the glucokinase pathway is a sine qua non condition for P. putida to grow with glucose.

Global gene expression analysis of the heat shock response in the phytopathogen Xylella fastidiosa

Xylella fastidiosa is a phytopathogenic bacterium that is responsible for diseases in many economically important crops. Although different strains have been studied, little is known about X. fastidiosa stress responses. One of the better characterized stress responses in bacteria is the heat shock response, which induces the expression of specific genes to prevent protein misfolding and aggregation and to promote degradation of the irreversibly denatured polypeptides. To investigate X. fastidiosa genes involved in the heat shock response, we performed a whole-genome microarray analysis in a time course experiment. Globally, 261 genes were induced (9.7%) and 222 genes were repressed (8.3%). The expression profiles of the differentially expressed genes were grouped, and their expression patterns were validated by quantitative reverse transcription-PCR experiments. We determined the transcription start sites of six heat shock-inducible genes and analyzed their promoter regions, which allowed us to propose a putative consensus for sigma(32) promoters in Xylella and to suggest additional genes as putative members of this regulon. Besides the induction of classical heat shock protein genes, we observed the up-regulation of virulence-associated genes such as vapD and of genes for hemagglutinins, hemolysin, and xylan-degrading enzymes, which may indicate the importance of heat stress to bacterial pathogenesis. In addition, we observed the repression of genes related to fimbriae, aerobic respiration, and protein biosynthesis and the induction of genes related to the extracytoplasmic stress response and some phage-related genes, revealing the complex network of genes that work together in response to heat shock.

Centering, scaling, and transformations: improving the biological information content of metabolomics data

BACKGROUND

Extracting relevant biological information from large data sets is a major challenge in functional genomics research. Different aspects of the data hamper their biological interpretation. For instance, 5000-fold differences in concentration for different metabolites are present in a metabolomics data set, while these differences are not proportional to the biological relevance of these metabolites. However, data analysis methods are not able to make this distinction. Data pretreatment methods can correct for aspects that hinder the biological interpretation of metabolomics data sets by emphasizing the biological information in the data set and thus improving their biological interpretability.

RESULTS

Different data pretreatment methods, i.e. centering, autoscaling, pareto scaling, range scaling, vast scaling, log transformation, and power transformation, were tested on a real-life metabolomics data set. They were found to greatly affect the outcome of the data analysis and thus the rank of the, from a biological point of view, most important metabolites. Furthermore, the stability of the rank, the influence of technical errors on data analysis, and the preference of data analysis methods for selecting highly abundant metabolites were affected by the data pretreatment method used prior to data analysis.

CONCLUSION

Different pretreatment methods emphasize different aspects of the data and each pretreatment method has its own merits and drawbacks. The choice for a pretreatment method depends on the biological question to be answered, the properties of the data set and the data analysis method selected. For the explorative analysis of the validation data set used in this study, autoscaling and range scaling performed better than the other pretreatment methods. That is, range scaling and autoscaling were able to remove the dependence of the rank of the metabolites on the average concentration and the magnitude of the fold changes and showed biologically sensible results after PCA (principal component analysis).In conclusion, selecting a proper data pretreatment method is an essential step in the analysis of metabolomics data and greatly affects the metabolites that are identified to be the most important.