Flux, toxicity, and expression costs generate complex genetic interactions in a metabolic pathway.

Our ability to predict the impact of mutations on traits relevant for disease and evolution remains severely limited by the dependence of their effects on the genetic background and environment. Even when molecular interactions between genes are known, it is unclear how these translate to organism-level interactions between alleles. We therefore characterized the interplay of genetic and environmental dependencies in determining fitness by quantifying ~4000 fitness interactions between expression variants of two metabolic genes, starting from various environmentally modulated expression levels. We detect a remarkable variety of interactions dependent on initial expression levels and demonstrate that they can be quantitatively explained by a mechanistic model accounting for catabolic flux, metabolite toxicity, and expression costs. Complex fitness interactions between mutations can therefore be predicted simply from their simultaneous impact on a few connected molecular phenotypes.

Advantage of the F2:A1:B- IncF Pandemic Plasmid over IncC Plasmids in In Vitro Acquisition and Evolution of blaCTX-M Gene-Bearing Plasmids in Escherichia coli.

Despite a fitness cost imposed on bacterial hosts, large conjugative plasmids play a key role in the diffusion of resistance determinants, such as CTX-M extended-spectrum ß-lactamases. Among the large conjugative plasmids, IncF plasmids are the most predominant group, and an F2:A1:B- IncF-type plasmid encoding a CTX-M-15 variant was recently described as being strongly associated with the emerging worldwide Escherichia coli sequence type 131 (ST131)-O25b:H4 H30Rx/C2 sublineage. In this context, we investigated the fitness cost of narrow-range F-type plasmids, including the F2:A1:B- IncF-type CTX-M-15 plasmid, and of broad-range C-type plasmids in the K-12-like J53-2 E. coli strain. Although all plasmids imposed a significant fitness cost to the bacterial host immediately after conjugation, we show, using an experimental-evolution approach, that a negative impact on the fitness of the host strain was maintained throughout 1,120 generations with the IncC-IncR plasmid, regardless of the presence or absence of cefotaxime, in contrast to the F2:A1:B- IncF plasmid, whose cost was alleviated. Many chromosomal and plasmid rearrangements were detected after conjugation in transconjugants carrying the IncC plasmids but not in transconjugants carrying the F2:A1:B- IncF plasmid, except for insertion sequence (IS) mobilization from the fliM gene leading to the restoration of motility of the recipient strains. Only a few mutations occurred on the chromosome of each transconjugant throughout the experimental-evolution assay. Our findings indicate that the F2:A1:B- IncF CTX-M-15 plasmid is well adapted to the E. coli strain studied, contrary to the IncC-IncR CTX-M-15 plasmid, and that such plasmid-host adaptation could participate in the evolutionary success of the CTX-M-15-producing pandemic E. coli ST131-O25b:H4 lineage.

ClermonTyping: an easy-to-use and accurate in silico method for Escherichia genus strain phylotyping.

The genus Escherichia is composed of Escherichia albertii, E. fergusonii, five cryptic Escherichia clades and E. coli sensu stricto. Furthermore, the E. coli species can be divided into seven main phylogroups termed A, B1, B2, C, D, E and F. As specific lifestyles and/or hosts can be attributed to these species/phylogroups, their identification is meaningful for epidemiological studies. Classical phenotypic tests fail to identify non-sensu stricto E. coli as well as phylogroups. Clermont and colleagues have developed PCR assays that allow the identification of most of these species/phylogroups, the triplex/quadruplex PCR for E. coli phylogroup determination being the most popular. With the growing availability of whole genome sequences, we have developed the ClermonTyping method and its associated web-interface, the ClermonTyper, that allows a given strain sequence to be assigned to E. albertii, E. fergusonii, Escherichia clades I-V, E. coli sensu stricto as well as to the seven main E. coli phylogroups. The ClermonTyping is based on the concept of in vitro PCR assays and maintains the principles of ease of use and speed that prevailed during the development of the in vitro assays. This in silico approach shows 99.4 % concordance with the in vitro PCR assays and 98.8 % with the Mash genome-clustering tool. The very few discrepancies result from various errors occurring mainly from horizontal gene transfers or SNPs in the primers. We propose the ClermonTyper as a freely available resource to the scientific community at: http://clermontyping.iame-research.center/.

PFIM 4.0, an extended R program for design evaluation and optimization in nonlinear mixed-effect models.

BACKGROUND AND OBJECTIVE: Nonlinear mixed-effect models (NLMEMs) are increasingly used for the analysis of longitudinal studies during drug development. When designing these studies, the expected Fisher information matrix (FIM) can be used instead of performing time-consuming clinical trial simulations. The function PFIM is the first tool for design evaluation and optimization that has been developed in R. In this article, we present an extended version, PFIM 4.0, which includes several new features. METHODS: Compared with version 3.0, PFIM 4.0 includes a more complete pharmacokinetic/pharmacodynamic library of models and accommodates models including additional random effects for inter-occasion variability as well as discrete covariates. A new input method has been added to specify user-defined models through an R function. Optimization can be performed assuming some fixed parameters or some fixed sampling times. New outputs have been added regarding the FIM such as eigenvalues, conditional numbers, and the option of saving the matrix obtained after evaluation or optimization. Previously obtained results, which are summarized in a FIM, can be taken into account in evaluation or optimization of one-group protocols. This feature enables the use of PFIM for adaptive designs. The Bayesian individual FIM has been implemented, taking into account a priori distribution of random effects. Designs for maximum a posteriori Bayesian estimation of individual parameters can now be evaluated or optimized and the predicted shrinkage is also reported. It is also possible to visualize the graphs of the model and the sensitivity functions without performing evaluation or optimization. RESULTS: The usefulness of these approaches and the simplicity of use of PFIM 4.0 are illustrated by two examples: (i) an example of designing a population pharmacokinetic study accounting for previous results, which highlights the advantage of adaptive designs; (ii) an example of Bayesian individual design optimization for a pharmacodynamic study, showing that the Bayesian individual FIM can be a useful tool in therapeutic drug monitoring, allowing efficient prediction of estimation precision and shrinkage for individual parameters. CONCLUSION: PFIM 4.0 is a useful tool for design evaluation and optimization of longitudinal studies in pharmacometrics and is freely available at http://www.pfim.biostat.fr.

Glutathione peroxidase-1 gene (GPX1) variants, oxidative stress and risk of kidney complications in people with type 1 diabetes.

BACKGROUND AND AIM: Glutathione peroxidase (GPX) is a class of antioxidant enzymes that catalyze the reduction of hydrogen peroxide to water. GPX1 is the most abundant isoform and is expressed in all kidney cells. Isoprostane and advanced oxidation protein products (AOPP) were identified as markers of oxidative stress in patients with kidney disease. We investigated associations of GPX1 genotypes with kidney complications, and with plasma concentrations of isoprostane and AOPP in type 1 diabetic patients. METHODS: Four SNPs in the GPX1 gene region were genotyped in SURGENE (n=340; 10-year follow-up); GENEDIAB (n=461) and GENESIS (n=584) cohorts of type 1 diabetic patients. Subsets of GENEDIAB (n=237) and GENESIS (n=466) participants were followed up for 9 and 5years, respectively. Plasma concentrations of isoprostane and AOPP were measured at baseline in GENEDIAB. Hazard ratios (HR) were estimated for incidence of kidney complications. RESULTS: In SURGENE, 98 renal events (new cases of microalbuminuria or progression to more severe stage of diabetic nephropathy) occurred during follow-up. The minor T-allele of rs3448 was associated with the incidence of renal events (HR 1.81, 95% CI 1.16-2.84, p=0.008). In GENESIS/GENEDIAB pooled study, end stage renal disease (ESRD) occurred during follow-up in 52 individuals. The same variant was associated with the incidence of ESRD (HR 3.34, 95% CI, 1.69-6.98, p=0.0004). The variant was also associated with higher plasma isoprostane concentration in GENEDIAB cohort: 2.02±0.12 (TT+CT) vs 1.75±0.13 (CC) ng/mL (p=0.009), and with higher plasma AOPP in the subset of participants with the baseline history of ESRD (TT+CT 67±6 vs CC 48±6µmol/L, p=0.006). CONCLUSIONS: The minor T-allele of rs3448 was associated with kidney complications (incidences of microalbuminuria, renal events and ESRD) in patients with type 1 diabetes. The risk allele was associated with higher plasma concentrations of isoprostane and AOPP. Our results are consistent with the implication of GPX1 in the mechanism of renal protection against oxidative stress in type 1 diabetic patients.

Plasma extracellular superoxide dismutase concentration, allelic variations in the SOD3 gene and risk of myocardial infarction and all-cause mortality in people with type 1 and type 2 diabetes.

BACKGROUND: Oxidative stress is involved in development of diabetes complications. Extracellular superoxide dismutase (EC-SOD, SOD3) is a major extracellular antioxidant enzyme and is highly expressed in arterial walls. Advanced oxidation protein products (AOPP) and 8-iso-prostaglandin (isoprostane) are markers of oxidative stress. We investigated association of SOD3 gene variants, plasma concentrations of EC-SOD, AOPP and isoprostane with myocardial infarction and mortality in diabetic patients. METHODS: We studied three cohorts designed to evaluate the vascular complications of diabetes: the GENEDIAB study (469 participants with type 1 diabetes at baseline; follow-up data for 259 participants), the GENESIS study (603 participants with type 1 diabetes at baseline; follow-up data for 525 participants) and the DIABHYCAR study (3137 participants with type 2 diabetes at baseline and follow-up). Duration of follow-up was 9, 5, and 5 years, respectively. Main outcome measures were incidence of myocardial infarction, and cardiovascular and total mortality during follow-up. Six single nucleotide polymorphisms in the SOD3 locus were genotyped in the three cohorts. Plasma concentrations of EC-SOD, AOPP, and isoprostane were measured in baseline samples of GENEDIAB participants. RESULTS: In GENEDIAB/GENESIS pooled cohorts, the minor T-allele of rs2284659 variant was inversely associated with the prevalence at baseline (Odds Ratio 0.48, 95% CI 0.29-0.78, p = 0.004) and the incidence during follow-up of myocardial infarction (Hazard Ratio 0.58, 95% CI 0.40-0.83, p = 0.003) and with cardiovascular (HR 0.33, 95% CI 0.08-0.74, p = 0.004) and all-cause mortality (HR 0.44, 95% CI 0.21-0.73, p = 0.0006). The protective allele was associated with higher plasma EC-SOD and lower plasma AOPP concentrations in GENEDIAB. It was also inversely associated with incidence of myocardial infarction (HR 0.75, 95% CI 0.59-0.94, p = 0.01) and all-cause mortality (HR 0.87, 95% CI 0.79-0.97, p = 0.008) in DIABHYCAR. CONCLUSIONS: The T-allele of rs2284659 in the promoter of SOD3 was associated with a more favorable plasma redox status and with better cardiovascular outcomes in diabetic patients. Our results suggest that EC-SOD plays an important role in the mechanisms of vascular protection against diabetes-related oxidative stress.

Benefits of a new Metropolis-Hasting based algorithm, in non-linear regression for estimation of ex vivo antimalarial sensitivity in patients infected with two strains.

Malaria is one of the world׳s most widespread parasitic diseases. The parasitic protozoans of the genus Plasmodium have developed resistance to several antimalarial drugs. Some patients are therefore infected by two or more strains with different levels of antimalarial drug sensitivity. We previously developed a model to estimate the drug concentration (IC50) that inhibits 50% of the growth of the parasite isolated from a patient infected with one strain. We propose here a new Two-Slopes model for patients infected by two strains. This model involves four parameters: the proportion of each strain and their IC50, and the sigmoidicity parameter. To estimate the parameters of this model, we have developed a new algorithm called PGBO (Population Genetics-Based Optimizer). It is based on the Metropolis-Hasting algorithm and is implemented in the statistical software R. We performed a simulation study and defined three evaluation criteria to evaluate its properties and compare it with three other algorithms (Gauss-Newton, Levenberg-Marquardt, and a simulated annealing). We also evaluated it using in vitro data and three ex vivo datasets from the French Malaria Reference Center. Our evaluation criteria in the simulation show that PGBO gives good estimates of the parameters even if the concentration design is poor. Moreover, our algorithm is less sensitive than Gauss-Newton algorithms to initial values. Although parameter estimation is good, interpretation of the results can be difficult if the proportion of the second strain is close to 0 or 1. For these reasons, this approach cannot yet be implemented routinely.

Capturing the mutational landscape of the beta-lactamase TEM-1.

Adaptation proceeds through the selection of mutations. The distribution of mutant fitness effect and the forces shaping this distribution are therefore keys to predict the evolutionary fate of organisms and their constituents such as enzymes. Here, by producing and sequencing a comprehensive collection of 10,000 mutants, we explore the mutational landscape of one enzyme involved in the spread of antibiotic resistance, the beta-lactamase TEM-1. We measured mutation impact on the enzyme activity through the estimation of amoxicillin minimum inhibitory concentration on a subset of 990 mutants carrying a unique missense mutation, representing 64% of possible amino acid changes in that protein reachable by point mutation. We established that mutation type, solvent accessibility of residues, and the predicted effect of mutations on protein stability primarily determined alone or in combination changes in minimum inhibitory concentration of mutants. Moreover, we were able to capture the drastic modification of the mutational landscape induced by a single stabilizing point mutation (M182T) by a simple model of protein stability. This work thereby provides an integrated framework to study mutation effects and a tool to understand/define better the epistatic interactions.

Fitness, stress resistance, and extraintestinal virulence in Escherichia coli.

The extraintestinal virulence of Escherichia coli is dependent on numerous virulence genes. However, there is growing evidence for a role of the metabolic properties and stress responses of strains in pathogenesis. We assessed the respective roles of these factors in strain virulence by developing phenotypic assays for measuring in vitro individual and competitive fitness and the general stress response, which we applied to 82 commensal and extraintestinal pathogenic E. coli strains previously tested in a mouse model of sepsis. Individual fitness properties, in terms of maximum growth rates in various media (Luria-Bertani broth with and without iron chelator, minimal medium supplemented with gluconate, and human urine) and competitive fitness properties, estimated as the mean relative growth rate per generation in mixed cultures with a reference fluorescent E. coli strain, were highly diverse between strains. The activity of the main general stress response regulator, RpoS, as determined by iodine staining of the colonies, H2O2 resistance, and rpoS sequencing, was also highly variable. No correlation between strain fitness and stress resistance and virulence in the mouse model was found, except that the maximum growth rate in urine was higher for virulent strains. Multivariate analysis showed that the number of virulence factors was the only independent factor explaining the virulence in mice. At the species level, growth capacity and stress resistance are heterogeneous properties that do not contribute significantly to the intrinsic virulence of the strains.

High-throughput analysis of antimalarial susceptibility data by the WorldWide Antimalarial Resistance Network (WWARN) in vitro analysis and reporting tool.

Assessment of in vitro susceptibility is a fundamental component of antimalarial surveillance studies, but wide variations in the measurement of parasite growth and the calculation of inhibitory constants make comparisons of data from different laboratories difficult. Here we describe a Web-based, high-throughput in vitro analysis and reporting tool (IVART) generating inhibitory constants for large data sets. Fourteen primary data sets examining laboratory-determined susceptibility to artemisinin derivatives and artemisinin combination therapy partner drugs were collated from 11 laboratories. Drug concentrations associated with half-maximal inhibition of growth (IC50s) were determined by a modified sigmoid Emax model-fitting algorithm, allowing standardized analysis of 7,350 concentration-inhibition assays involving 1,592 isolates. Examination of concentration-inhibition data revealed evidence of apparent paradoxical growth at high concentrations of nonartemisinin drugs, supporting amendment of the method for calculating the maximal drug effect in each assay. Criteria for defining more-reliable IC50s based on estimated confidence intervals and growth ratios improved correlation coefficients for the drug pairs mefloquine-quinine and chloroquine-desethylamodiaquine in 9 of 11 and 8 of 8 data sets, respectively. Further analysis showed that maximal drug inhibition was higher for artemisinins than for other drugs, particularly in ELISA (enzyme-linked immunosorbent assay)-based assays, a finding consistent with the earlier onset of action of these drugs in the parasite life cycle. This is the first high-throughput analytical approach to apply consistent constraints and reliability criteria to large, diverse antimalarial susceptibility data sets. The data also illustrate the distinct biological properties of artemisinins and underline the need to apply more sensitive approaches to assessing in vitro susceptibility to these drugs.

The emergence of complexity and restricted pleiotropy in adapting networks.

BACKGROUND: The emergence of organismal complexity has been a difficult subject for researchers because it is not readily amenable to investigation by experimental approaches. Complexity has a myriad of untested definitions and our understanding of its evolution comes primarily from static snapshots gleaned from organisms ranked on an intuitive scale. Fisher's geometric model of adaptation, which defines complexity as the number of phenotypes an organism exposes to natural selection, provides a theoretical framework to study complexity. Yet investigations of this model reveal phenotypic complexity as costly and therefore unlikely to emerge. RESULTS: We have developed a computational approach to study the emergence of complexity by subjecting neural networks to adaptive evolution in environments exacting different levels of demands. We monitored complexity by a variety of metrics. Top down metrics derived from Fisher's geometric model correlated better with the environmental demands than bottom up ones such as network size. Phenotypic complexity was found to increase towards an environment-dependent level through the emergence of restricted pleiotropy. Such pleiotropy, which confined the action of mutations to only a subset of traits, better tuned phenotypes in challenging environments. However, restricted pleiotropy also came at a cost in the form of a higher genetic load, as it required the maintenance by natural selection of more independent traits. Consequently, networks of different sizes converged in complexity when facing similar environment. CONCLUSIONS: Phenotypic complexity evolved as a function of the demands of the selective pressures, rather than the physical properties of the network architecture, such as functional size. Our results show that complexity may be more predictable, and understandable, if analyzed from the perspective of the integrated task the organism performs, rather than the physical architecture used to accomplish such tasks. Thus, top down metrics emphasizing selection may be better for describing biological complexity than bottom up ones representing size and other physical attributes.

Complete nucleotide sequence of plasmid pTN48, encoding the CTX-M-14 extended-spectrum ß-lactamase from an Escherichia coli O102-ST405 strain.

The sequence of pTN48, a plasmid of the FII-FIB replicon type that encodes a CTX-M-14 enzyme in an Escherichia coli strain of the phylogenetic group D2 O102-ST405 clone, was determined. pTN48 is, for the most part, a mosaic of virulence, antibiotic resistance, and addiction system modules found in various other plasmids. The presence of multiple addiction systems indicates that the plasmid should be stably maintained in the E. coli clone, favoring dissemination of the CTX-M-14 enzyme.

Online analysis of in vitro resistance to antimalarial drugs through nonlinear regression.

Malaria remains one of the leading causes of morbidity and mortality worldwide which is partly due to the emergence of the parasite resistance to antimalarial drugs. In vitro testing of drugs allows an early detection of resistance. The common parameter used for the monitoring of resistance is the concentration that inhibits 50% of the parasite's activity (IC(50)). Various methods of calculation are already used but none of them consider new available tools nor display the precision of IC(50) estimation. We proposed an approach based on the inhibitory sigmoid E(max) model, which is often used in pharmacology, with estimation of IC(50) through nonlinear regression using a standard function of the R software. To facilitate the usage of that tool we have developed an online version available on the website ICEstimator (ICEstimator website http://www.antimalarial-icestimator.net/, 2009) [1]. This website is used by various teams in the world and the user can do the analysis without knowing R using the GUI. This article describes version 2.1 of this website and shows illustration on five different real examples.

Molecular and evolutionary bases of within-patient genotypic and phenotypic diversity in Escherichia coli extraintestinal infections.

Although polymicrobial infections, caused by combinations of viruses, bacteria, fungi and parasites, are being recognised with increasing frequency, little is known about the occurrence of within-species diversity in bacterial infections and the molecular and evolutionary bases of this diversity. We used multiple approaches to study the genomic and phenotypic diversity among 226 Escherichia coli isolates from deep and closed visceral infections occurring in 19 patients. We observed genomic variability among isolates from the same site within 11 patients. This diversity was of two types, as patients were infected either by several distinct E. coli clones (4 patients) or by members of a single clone that exhibit micro-heterogeneity (11 patients); both types of diversity were present in 4 patients. A surprisingly wide continuum of antibiotic resistance, outer membrane permeability, growth rate, stress resistance, red dry and rough morphotype characteristics and virulence properties were present within the isolates of single clones in 8 of the 11 patients showing genomic micro-heterogeneity. Many of the observed phenotypic differences within clones affected the trade-off between self-preservation and nutritional competence (SPANC). We showed in 3 patients that this phenotypic variability was associated with distinct levels of RpoS in co-existing isolates. Genome mutational analysis and global proteomic comparisons in isolates from a patient revealed a star-like relationship of changes amongst clonally diverging isolates. A mathematical model demonstrated that multiple genotypes with distinct RpoS levels can co-exist as a result of the SPANC trade-off. In the cases involving infection by a single clone, we present several lines of evidence to suggest diversification during the infectious process rather than an infection by multiple isolates exhibiting a micro-heterogeneity. Our results suggest that bacteria are subject to trade-offs during an infectious process and that the observed diversity resembled results obtained in experimental evolution studies. Whatever the mechanisms leading to diversity, our results have strong medical implications in terms of the need for more extensive isolate testing before deciding on antibiotic therapies.

Genotype-phenotype correlations in fetuses and neonates with autosomal recessive polycystic kidney disease.

The prognosis of autosomal recessive polycystic kidney disease is known to correlate with genotype. The presence of two truncating mutations in the PKHD1 gene encoding the fibrocystin protein is associated with neonatal death while patients who survive have at least one missense mutation. To determine relationships between genotype and renal and hepatic abnormalities we correlated the severity of renal and hepatic histological lesions to the type of PKHD1 mutations in 54 fetuses (medical pregnancy termination) and 20 neonates who died shortly after birth. Within this cohort, 55.5% of the mutations truncated fibrocystin. The severity of cortical collecting duct dilatations, cortical tubule and glomerular lesions, and renal cortical and hepatic portal fibrosis increased with gestational age. Severe genotypes, defined by two truncating mutations, were more frequent in patients of less than 30 weeks gestation compared to older fetuses and neonates. When adjusted to gestational age, the extension of collecting duct dilatation into the cortex and cortical tubule lesions, but not portal fibrosis, was more prevalent in patients with severe than in those with a non-severe genotype. Our results show the presence of two truncating mutations of the PKHD1 gene is associated with the most severe renal forms of prenatally detected autosomal recessive polycystic kidney disease. Their absence, however, does not guarantee survival to the neonatal period.

The evolution of epistasis and its links with genetic robustness, complexity and drift in a phenotypic model of adaptation.

The epistatic interactions among mutations have a large effect on the evolution of populations. In this article we provide a formalism under which epistatic interactions among pairs of mutations have a distribution whose mean can be modulated. We find that the mean epistasis is correlated to the effect of mutations or genetic robustness, which suggests that such formalism is in good agreement with most in silico models of evolution where the same pattern is observed. We further show that the evolution of epistasis is highly dependant on the intensity of drift and of how complex the organisms are, and that either positive or negative epistasis could be selected for, depending on the balance between the efficiency of selection and the intensity of drift.