Gestational diabetes mellitus and the risk of metabolic syndrome: a population-based study in Lausanne, Switzerland.

AIMS: To investigate the relationships between gestational diabetes mellitus (GDM) and the metabolic syndrome (MS), as it was suggested that insulin resistance was the hallmark of both conditions. To analyse post-partum screening in order to identify risk factors for the subsequent development of type 2 diabetes mellitus (DM). METHODS: A retrospective analysis of all singleton pregnancies diagnosed with GDM at the Lausanne University Hospital for 3 consecutive years. Pre-pregnancy obesity, hypertension and dyslipidaemia were recorded as constituents of the MS. RESULTS: For 5788 deliveries, 159 women (2.7%) with GDM were identified. Constituents of the MS were present before GDM pregnancy in 26% (n = 37/144): 84% (n = 31/37) were obese, 38% (n = 14/37) had hypertension and 22% (n = 8/37) had dyslipidaemia. Gestational hypertension was associated with obesity (OR = 3.2, P = 0.02) and dyslipidaemia (OR = 5.4, P=0.002). Seventy-four women (47%) returned for post-partum OGTT, which was abnormal in 20 women (27%): 11% (n = 8) had type 2 diabetes and 16% (n = 12) had impaired glucose tolerance. Independent predictors of abnormal glucose tolerance in the post-partum were: having > 2 abnormal values on the diagnostic OGTT during pregnancy and presenting MS constituents (OR = 5.2, CI 1.8-23.2 and OR = 5.3, CI 1.3-22.2). CONCLUSIONS: In one fourth of GDM pregnancies, metabolic abnormalities precede the appearance of glucose intolerance. These women have a high risk of developing the MS and type 2 diabetes in later years. Where GDM screening is not universal, practitioners should be aware of those metabolic risks in every pregnant woman presenting with obesity, hypertension or dyslipidaemia, in order to achieve better diagnosis and especially better post-partum follow-up and treatment.

Measurements of glial metabolic fluxes with C-11-acetate using positron emission and an adapted NMR-based metabolic modeling approach

Objectives: Acetate brain metabolism has the particularity to occur specifically in glial cells. Labeling studies, using acetate labeled either with 13C (NMR) or 11C (PET), are governed by the same biochemical reactions and thus follow the same mathematical principles. In this study, the objective was to adapt an NMR acetate brain metabolism model to analyse [1-11C]acetate infusion in rats. Methods: Brain acetate infusion experiments were modeled using a two-compartment model approach used in NMR.1-3 The [1-11C]acetate labeling study was done using a beta scintillator.4 The measured radioactive signal represents the time evolution of the sum of all labeled metabolites in the brain. Using a coincidence counter in parallel, an arterial input curve was measured. The 11C at position C-1 of acetate is metabolized in the first turn of the TCA cycle to the position 5 of glutamate (Figure 1A). Through the neurotransmission process, it is further transported to the position 5 of glutamine and the position 5 of neuronal glutamate. After the second turn of the TCA cycle, tracer from [1-11C]acetate (and also a part from glial [5-11C]glutamate) is transferred to glial [1-11C]glutamate and further to [1-11C]glutamine and neuronal glutamate through the neurotransmission cycle. Brain poster session: oxidative mechanisms S460 Journal of Cerebral Blood Flow & Metabolism (2009) 29, S455-S466 Results: The standard acetate two-pool PET model describes the system by a plasma pool and a tissue pool linked by rate constants. Experimental data are not fully described with only one tissue compartment (Figure 1B). The modified NMR model was fitted successfully to tissue time-activity curves from 6 single animals, by varying the glial mitochondrial fluxes and the neurotransmission flux Vnt. A glial composite rate constant Kgtg=Vgtg/[Ace]plasma was extracted. Considering an average acetate concentration in plasma of 1 mmol/g5 and the negligible additional amount injected, we found an average Vgtg = 0.08±0.02 (n = 6), in agreement with previous NMR measurements.1 The tissue time-activity curve is dominated by glial glutamate and later by glutamine (Figure 1B). Labeling of neuronal pools has a low influence, at least for the 20 mins of beta-probe acquisition. Based on the high diffusivity of CO2 across the blood-brain barrier; 11CO2 is not predominant in the total tissue curve, even if the brain CO2 pool is big compared with other metabolites, due to its strong dilution through unlabeled CO2 from neuronal metabolism and diffusion from plasma. Conclusion: The two-compartment model presented here is also able to fit data of positron emission experiments and to extract specific glial metabolic fluxes. 11C-labeled acetate presents an alternative for faster measurements of glial oxidative metabolism compared to NMR, potentially applicable to human PET imaging. However, to quantify the relative value of the TCA cycle flux compared to the transmitochondrial flux, the chemical sensitivity of NMR is required. PET and NMR are thus complementary.

Alcohol drinking, the metabolic syndrome and diabetes in a population with high mean alcohol consumption.

AIMS: To investigate the relationship of alcohol consumption with the metabolic syndrome and diabetes in a population-based study with high mean alcohol consumption. Few data exist on these conditions in high-risk drinkers. METHODS: In 6172 adults aged 35-75 years, alcohol consumption was categorized as 0, 1-6, 7-13, 14-20, 21-27, 28-34 and ≥ 35 drinks/week or as non-drinkers (0), low-risk (1-13), medium-to-high-risk (14-34) and very-high-risk (≥ 35) drinkers. Alcohol consumption was objectively confirmed by biochemical tests. In multivariate analysis, we assessed the relationship of alcohol consumption with adjusted prevalence of the metabolic syndrome, diabetes and insulin resistance, determined with the homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS: Seventy-three per cent of participants consumed alcohol, 16% were medium-to-high-risk drinkers and 2% very-high-risk drinkers. In multivariate analysis, the prevalence of the metabolic syndrome, diabetes and mean HOMA-IR decreased with low-risk drinking and increased with high-risk drinking. Adjusted prevalence of the metabolic syndrome was 24% in non-drinkers, 19% in low-risk (P<0.001 vs. non-drinkers), 20% in medium-to-high-risk and 29% in very-high-risk drinkers (P=0.005 vs. low-risk). Adjusted prevalence of diabetes was 6.0% in non-drinkers, 3.6% in low-risk (P<0.001 vs. non-drinkers), 3.8% in medium-to-high-risk and 6.7% in very-high-risk drinkers (P=0.046 vs. low-risk). Adjusted HOMA-IR was 2.47 in non-drinkers, 2.14 in low-risk (P<0.001 vs. non-drinkers), 2.27 in medium-to-high-risk and 2.53 in very-high-risk drinkers (P=0.04 vs. low-risk). These relationships did not differ according to beverage types. CONCLUSIONS: Alcohol has a U-shaped relationship with the metabolic syndrome, diabetes and HOMA-IR, without differences between beverage types.

Analyse critique des résultats de biopsies musculaires et de la méthodologie utilisée dans 889 cas d'affections neuromusculaires [Critical analysis of the results of muscle biopsies and of the methods used in 889 cases of neuromuscular disorders]

The contribution of muscle biopsies to the diagnosis of neuromuscular disorders and the indications of various methods of examination are investigated by analysis of 889 biopsies from patients suffering from myopathic and/or neurogenic disorders. Histo-enzymatic studies performed on frozen material as well as immunohistochemistry and electron microscopy allowed to provide specific diagnoses in all the neurogenic disorders (polyneuropathies and motor neuron diseases), whereas one third of myopathies remained uncertain. Confrontation of neuropathological data with the clinical indications for histological investigations shows that muscle biopsies reveal the diagnosis in 25% of the cases (mainly in congenital and metabolic myopathies) and confirm and/or complete the clinical diagnosis in 50%. In the remaining cases with non specific abnormalities neuropathological investigations may help the clinician by excluding well defined neuromuscular disorders. Analysis of performed studies and results of investigations show the contribution and specificity of each method for the diagnosis. Statistical evaluation of this series indicates that cryostat sectioning for histo- and immunochemical and electron microscopy increases the rate of diagnoses of neuromuscular diseases: full investigation was necessary for the diagnosis in 30% of the cases. The interpretation of the wide range of pathological reactions in muscles requires a close cooperation with the clinician.

In vivo 13C NMR spectroscopy and metabolic modeling in the brain: a practical perspective.

In vivo 13C NMR spectroscopy has the unique capability to measure metabolic fluxes noninvasively in the brain. Quantitative measurements of metabolic fluxes require analysis of the 13C labeling time courses obtained experimentally with a metabolic model. The present work reviews the ingredients necessary for a dynamic metabolic modeling study, with particular emphasis on practical issues.

The effect of obesity, age, puberty and gender on resting metabolic rate in children and adolescents.

During puberty fat-free mass (FFM) and fat mass (FM) change quickly and these changes are influenced by sex and obesity. Since it is not completely known how these changes affect resting metabolic rate (RMR), the aim of the present study was to investigate the effect of body composition, age, sex and pubertal development of postabsorptive RMR in 9.5- to 16.5- year-old obese and non-obese children. Postabsorptive RMR was measured in a sample of 371 pre- and postpubertal children comprising 193 males (116 non-obese and 77 obese) and 178 females (119 non-obese and 59 obese). RMR was assessed by indirect calorimetry using a ventilated hood system for 45 min after an overnight fast. Body composition (FFM and FM) was estimated from skinfold measurements. The mean (+/- SD) RMR was significantly (P < 0.001) lower in non-obese (males: 5600 +/- 972 kJ/24 h; females: 5112 +/- 632 kJ/24 h) than in obese (males: 7223 +/- 1220 kJ/24 h; females: 6665 +/- 1106 kJ/24 h) children. This difference became non-significant when RMR was adjusted for body composition (FFM+FM). However, the difference between the genders still remained significant (control male: 6118 +/- 507, control female: 5652 +/- 507, P < 0.001; obese male: 6256 +/- 507, obese female: 5818 +/- 507 kJ/24 h, P < 0.001). The main determinant of RMR was FFM. In the whole cohort. FFM explained 79.8% of the variation in RMR, followed by age, gender and FM adding further 3.8%, 1.1% and 0.8% to the predictability of RMR, respectively. No significant contribution for study group (obese, non-obese), pubertal stage, or fat distribution was found in the regression for RMR. The adjusted value of RMR (for FFM and FM) slightly, but significantly (P < 0.01) decreased between the age of 10-16 years, demonstrating the important effect of age on RMR. CONCLUSIONS: The resting metabolic rate of obese and control children is not different when adjusted for body composition. The main determinant of RMR is the fat-free mass, however, age, gender and fat mass are also significant factors. Pubertal development and fat distribution do not influence RMR independently from the changes in body composition.

Hierarchical modeling gave plausible estimates of associations between metabolic syndrome and components of antiretroviral therapy.

OBJECTIVE: Hierarchical modeling has been proposed as a solution to the multiple exposure problem. We estimate associations between metabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. STUDY DESIGN AND SETTING: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes. We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. RESULTS: One thousand two hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate for exposure to atazanavir increased from hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). CONCLUSION: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model.

Increased fat oxidation in prepubertal obese children: a metabolic defense against further weight gain?

The purpose of this study was to measure postabsorptive fat oxidation at rest and to assess the association between fat mass and fat oxidation rate in prepubertal children, who were assigned to two groups: 35 obese children (weight, 44.5 +/- 9.7 kg; fat mass; 31.7 +/- 5.4%) and 37 nonobese children (weight, 30.8 +/- 6.8 kg; fat mass, 17.5 +/- 6.7%). Postabsorptive fat oxidation expressed in absolute value was significantly higher in obese than in nonobese children (31.4 +/- 9.7 mg/min vs 21.9 +/- 10.2 mg/min; p < 0.001) but not when adjusted for fat-free mass by analysis of covariance with fat-free mass as the covariate (28.2 +/- 10.6 mg/min vs 24.9 +/- 10.5 mg/min). In obese children and in the total group, fat mass and fat oxidation were significantly correlated (r = 0.65; p < 0.001). The slope of the relationship indicated that for each 10 kg additional fat mass, resting fat oxidation increased by 18 gm/day. We conclude that obese prepubertal children have a higher postabsorptive rate of fat oxidation than nonobese children. This metabolic process may favor the achievement of a new equilibrium in fat balance, opposing further adipose tissue gain.

Metabolic alterations in the cortex of a mouse model with glutathione deficit - relevance to schizophrenia

Background: Glutathione (GSH) is a major redox regulator and antioxidant and is decreased in cerebrospinal fluid and prefrontal cortex of schizophrenia patients [Do et al. (2000) Eur J Neurosci 12:3721]. The genes of the key GSH-synthesizing enzyme, glutamate- cysteine ligase catalytic (GCLC) and modifier (GCLM) subunits, are associated with schizophrenia, suggesting that the deficit in GSH synthesis is of genetic origin [Gysin et al. (2007) PNAS 104:16621]. GCLM knock-out (KO) mice, which display an 80% decrease in brain GSH levels, have abnormal brain morphology and function [Do et al. (2009) Curr Opin Neurobiol 19:220]. Developmental redox deregulation by impaired GSH synthesis and environmental risk factors generating oxidative stress may have a central role in schizophrenia. Here, we used GCLM KO mice to investigate the impact of a genetically dysregulated redox system on the neurochemical profile of the developing brain. Methods: The neurochemical profile of the anterior and posterior cortical areas of male and female GCLM KO and wild-type mice was determined by in vivo 1H NMR spectroscopy on postnatal days 10, 20, 30, 60 and 90, under 1 to 1.5% isoflurane anaesthesia. Localised 1H NMR spectroscopy was performed on a 14.1 T, 26 cm VNMRS spectrometer (Varian, Magnex) using a home-built 8 mm diameter quadrature surface coil (used both for RF excitation and signal reception). Spectra were acquired using SPECIAL with TE of 2.8 ms and TR of 4 s from VOIs placed in anterior or posterior regions of the cortex [Mlynárik et al. (2006) MRM 56:965]. LCModel analysis allowed in vivo quantification of a neurochemical profile composed of 18 metabolites. Results: GCLM KO mice displayed nearly undetectable GSH levels as compared to WT mice, demonstrating their drastic redox deregulation. Depletion of GSH triggered alteration of metabolites related to its synthesis, namely increase of glycine and glutamate levels during development (P20 and P30). Concentrations of glutamine and aspartate that are produced from glutamate were also increased in GCLM KO animals relative to WT. In addition, GCLM KO mice also showed higher levels of N-acetylaspartate that originates from the acetylation of aspartate. These metabolites are particularly implicated in neurotransmission processes and in mitochondrial oxidative metabolism. Their increase may indicate impaired mitochondrial metabolism with concomitant accumulation of lactate in the adult mice (P60 and P90). In addition, the GSH depletion triggers reduction of GABA concentration in anterior cortex of the P60 mice, which is in accordance with known impairment of GABAergic interneurons in that area. Changes were generally more pronounced in males than in females at P60, which is consistent with earlier disease onset in male patients. Discussion: In conclusion, the observed metabolic alterations in the cortex of a mouse model of redox deregulation suggest impaired mitochondrial metabolism and altered neurotransmission. The results also highlight the age between P20 and P30 as a sensitive period during the development for these alterations.

Increased male offspring's risk of metabolic-neuroendocrine dysfunction and overweight after fructose-rich diet intake by the lactating mother.

An adverse endogenous environment during early life predisposes the organism to develop metabolic disorders. We evaluated the impact of intake of an iso-caloric fructose rich diet (FRD) by lactating mothers (LM) on several metabolic functions of their male offspring. On postnatal d 1, ad libitum eating, lactating Sprague-Dawley rats received either 10% F (wt/vol; FRD-LM) or tap water (controls, CTR-LM) to drink throughout lactation. Weaned male offspring were fed ad libitum a normal diet, and body weight (BW) and food intake were registered until experimentation (60 d of age). Basal circulating levels of metabolic markers were evaluated. Both iv glucose tolerance and hypothalamic leptin sensitivity tests were performed. The hypothalamus was dissected for isolation of total RNA and Western blot analysis. Retroperitoneal (RP) adipose tissue was dissected and either kept frozen for gene analysis or digested to isolate adipocytes or for histological studies. FRD rats showed increased BW and decreased hypothalamic sensitivity to exogenous leptin, enhanced food intake (between 49-60 d), and decreased hypothalamic expression of several anorexigenic signals. FRD rats developed increased insulin and leptin peripheral levels and decreased adiponectinemia; although FRD rats normally tolerated glucose excess, it was associated with enhanced insulin secretion. FRD RP adipocytes were enlarged and spontaneously released high leptin, although they were less sensitive to insulin-induced leptin release. Accordingly, RP fat leptin gene expression was high in FRD rats. Excessive fructose consumption by lactating mothers resulted in deep neuroendocrine-metabolic disorders of their male offspring, probably enhancing the susceptibility to develop overweight/obesity during adult life.

An overview of the metabolic differences between Bradyrhizobium japonicum 110 bacteria and differentiated bacteroids from soybean (Glycine max) root nodules: an in vitro 13C- and 31P-nuclear magnetic resonance spectroscopy study.

Bradyrhizobium japonicum is a symbiotic nitrogen-fixing soil bacteria that induce root nodules formation in legume soybean (Glycine max.). Using (13)C- and (31)P-nuclear magnetic resonance (NMR) spectroscopy, we have analysed the metabolite profiles of cultivated B. japonicum cells and bacteroids isolated from soybean nodules. Our results revealed some quantitative and qualitative differences between the metabolite profiles of bacteroids and their vegetative state. This includes in bacteroids a huge accumulation of soluble carbohydrates such as trehalose, glutamate, myo-inositol and homospermidine as well as Pi, nucleotide pools and intermediates of the primary carbon metabolism. Using this novel approach, these data show that most of the compounds detected in bacteroids reflect the metabolic adaptation of rhizobia to the surrounding microenvironment with its host plant cells.

Comparative genome analysis of Pseudomonas knackmussii B13, the first bacterium known to degrade chloroaromatic compounds.

Pseudomonas knackmussii B13 was the first strain to be isolated in 1974 that could degrade chlorinated aromatic hydrocarbons. This discovery was the prologue for subsequent characterization of numerous bacterial metabolic pathways, for genetic and biochemical studies, and which spurred ideas for pollutant bioremediation. In this study, we determined the complete genome sequence of B13 using next generation sequencing technologies and optical mapping. Genome annotation indicated that B13 has a variety of metabolic pathways for degrading monoaromatic hydrocarbons including chlorobenzoate, aminophenol, anthranilate and hydroxyquinol, but not polyaromatic compounds. Comparative genome analysis revealed that B13 is closest to Pseudomonas denitrificans and Pseudomonas aeruginosa. The B13 genome contains at least eight genomic islands [prophages and integrative conjugative elements (ICEs)], which were absent in closely related pseudomonads. We confirm that two ICEs are identical copies of the 103 kb self-transmissible element ICEclc that carries the genes for chlorocatechol metabolism. Comparison of ICEclc showed that it is composed of a variable and a 'core' region, which is very conserved among proteobacterial genomes, suggesting a widely distributed family of so far uncharacterized ICE. Resequencing of two spontaneous B13 mutants revealed a number of single nucleotide substitutions, as well as excision of a large 220 kb region and a prophage that drastically change the host metabolic capacity and survivability.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

Developmental and metabolic brain alterations in rats exposed to bisphenol A during gestation and lactation.

In recent years, considerable research has focused on the biological effect of endocrine-disrupting chemicals. Bisphenol A (BPA) has been implicated as an endocrine-disrupting chemical (EDC) due to its ability to mimic the action of endogenous estrogenic hormones. The aim of this study was to assess the effect of perinatal exposure to BPA on cerebral structural development and metabolism after birth. BPA (1mg/l) was administered in the drinking water of pregnant dams from day 6 of gestation until pup weaning. At postnatal day 20, in vivo metabolite concentrations in the rat pup hippocampus were measured using high field proton magnetic resonance spectroscopy. Further, brain was assessed histologically for growth, gross morphology, glial and neuronal development and extent of myelination. Localized proton magnetic resonance spectroscopy ((1)H MRS) showed in the BPA-exposed rat a significant increase in glutamate concentration in the hippocampus as well as in the Glu/Asp ratio. Interestingly these two metabolites are metabolically linked together in the malate-aspartate metabolic shuttle. Quantitative histological analysis revealed that the density of NeuN-positive neurons in the hippocampus was decreased in the BPA-treated offspring when compared to controls. Conversely, the density of GFAP-positive astrocytes in the cingulum was increased in BPA-treated offspring. In conclusion, exposure to low-dose BPA during gestation and lactation leads to significant changes in the Glu/Asp ratio in the hippocampus, which may reflect impaired mitochondrial function and also result in neuronal and glial developmental alterations.

Comparative genome analysis of Pseudomonas knackmussii B13, the first bacterium known to degrade chloroaromatic compounds.

Pseudomonas knackmussii B13 was the first strain to be isolated in 1974 that could degrade chlorinated aromatic hydrocarbons. This discovery was the prologue for subsequent characterization of numerous bacterial metabolic pathways, for genetic and biochemical studies, and which spurred ideas for pollutant bioremediation. In this study, we determined the complete genome sequence of B13 using next generation sequencing technologies and optical mapping. Genome annotation indicated that B13 has a variety of metabolic pathways for degrading monoaromatic hydrocarbons including chlorobenzoate, aminophenol, anthranilate and hydroxyquinol, but not polyaromatic compounds. Comparative genome analysis revealed that B13 is closest to Pseudomonas denitrificans and Pseudomonas aeruginosa. The B13 genome contains at least eight genomic islands [prophages and integrative conjugative elements (ICEs)], which were absent in closely related pseudomonads. We confirm that two ICEs are identical copies of the 103 kb self-transmissible element ICEclc that carries the genes for chlorocatechol metabolism. Comparison of ICEclc showed that it is composed of a variable and a 'core' region, which is very conserved among proteobacterial genomes, suggesting a widely distributed family of so far uncharacterized ICE. Resequencing of two spontaneous B13 mutants revealed a number of single nucleotide substitutions, as well as excision of a large 220 kb region and a prophage that drastically change the host metabolic capacity and survivability.