Migraine is a common and debilitating neurovascular disorder with a complex envirogenomic aetiology. Numerous studies have demonstrated a preponderance of women affected with migraine and previous pedigree linkage studies in our laboratory have identified susceptibility loci on chromosome Xq24-Xq28. In this study we have used the genetic isolate of Norfolk Island to further analyse the X chromosome for migraine susceptibility loci.−5) ranking by P-value revealed two primary clusters of SNPs in the top 25. A 10 SNP cluster represents a novel migraine susceptibility locus at Xq12 whilst a 11 SNP cluster represents a previously identified migraine susceptibility locus at Xq27. The strongest association at Xq12 was seen for rs599958 , whilst at Xq27 the strongest association was for rs6525667 . Further analysis of SNPs at these loci was performed in 5,122 migraineurs from the Women’s Genome Health Study and provided additional evidence for association at the novel Xq12 locus (P<0.05).An association approach was employed to analyse 14,124 SNPs spanning the entire X chromosome. Genotype data from 288 individuals comprising a large core-pedigree, of which 76 were affected with migraine, were analysed. Although no SNP reached chromosome-wide significance  is located within the 5′UTR of the HEPH gene, which is involved in iron homeostasis in the brain and may represent a novel pathway for involvement in migraine pathogenesis.Overall, this study provides evidence for a novel migraine susceptibility locus on Xq12. The strongest effect SNP (rs102834, joint P = 1.63×10 Migraine is a complex neurovascular disorder that affects an estimated 18% of adult women and 6% of adult men Inheritance studies have shown migraine to run in families with heritability estimates ranging between 0.34–0.57 The Norfolk Island population is a genetic isolate that is descendant from 11 British ‘Bounty’ mutineers and 6 Tahitian women and family histories can be traced through detailed genealogical databases to the original founders. Geographical isolation as well as strict quarantine and immigration laws have also resulted in a more homogenous lifestyle then are seen in an outbred population 2 = 0.54) and consistent with other populations The prevalence of migraine in the Norfolk Island population is estimated at 25.5%, which is substantially higher then is seen in outbred populations. The heritability of the disorder is also substantial . From the 15,668 SNPs genotyped 14,124 were used for analysis, with the remainder discarded due to low genotyping call rates or low minor allele frequency.P-values from this analysis is depicted in A first pass X chromosome scan was undertaken using a logistic regression analysis that adjusted for age and gender. This approach did not incorporate any adjustment for kinship/relatedness in the cohort to allow for a computationally rapid first pass assessment of SNP rankings. A Manhattan plot of P = 1.65×10−4) and Xq28 (strongest association at rs6627483 P = 3.87×10−3). Interestingly 10 of the 25 top ranked SNPs also mapped to a new 377 Kb locus at Xq12, with the strongest association seen at rs599958 (P = 8.92×10−4) in this novel implicated region.The SNPs were then prioritised according to the approximate P value and the top 25 SNPs were re-analysed in SOLAR using a linkage-based probit regression model to account exactly for the relatedness of the pedigree cohort. The 25 top ranked SNPs see  clearly P = 7×10−3), which is located within the 5′UTR of the hephaestin (HEPH) gene. No association was observed at markers analysed in the Xq27 or Xq28 loci  cohort. Thirty-one SNPs across the three loci were analysed consisting of 21 of the top 25 prioritised SNPs in the Norfolk population and 10 additional SNPs that ranked within the top 100 that also map to these loci. In these regions evidence of validation was observed for the Xq12 locus at three SNPs with the strongest association observed at rs1028348 (OR = 4.479 q28 loci  in the tP = 1.1×10−4). Similarly block 2 included 5 genotyped SNPs representing 5 haplotypes. Of these, haplotype 1 was significantly over-represented in migraineurs (OR = 4.48 P = 1.6×10−4). The effect of this haplotype block appears to be due to the presence of the minor allele at rs1028348, located within the 5′UTR of the HEPH gene. The novel Xq12 SNP cluster was considered for further haplotype analysis. The 377 kb Xq12 locus included 21 SNPs incorporating 10 of the top 25 ranked SNPs from the study. A linkage disequilibrium plot of the region was generated in Haploview and 2 major haplotype blocks were identified . Block 1nd SNP cluster identified includes 10 the top 25 ranked SNPs that localise to a previously identified Xq27 migraine locus. Haplotype analysis in the Xq27 region revealed 2 haplotype blocks (P = 1.3×10−4), while haplotype 5 was significantly overrepresented (OR = 2.3 P = 4×10−4). Similarly the second block also consisted of 6 SNPs with 4 different haplotypes recognised. Haplotype 1 was again underrepresented in cases (OR = 2.22 P = 6.9×10−4) and haplotype 3 significantly overrepresented in migraineurs (OR = 2.06 P = 1.6×10−3). The 2e blocks . Block 1For this study we decided not to pursue haplotypic follow-up in the WGHS because of the substantially different LD structure likely to exist between NI and WGHS cohorts as well as the differences in SNP typed.The female preponderance of migraine suggests the disease is partly influenced by X-linked genomic factors. To date migraine susceptibility loci have been convincingly mapped to Xq24–28 and suggestively mapped to Xp22, mainly via pedigree linkage studies We analysed the X chromosomal data from a recent genome-wide association study P = 8.92×10−4). This statistic, whilst suggestive of association with migraine, fell slightly short of meeting our empirical threshold of statistical significance for the X chromosome (1×10−5). Failure to achieve greater effect sizes and statistical significance probably reflects the complex genetics of migraine and the limited size of the Norfolk population.It is well known that the common forms of migraine are influenced by multiple small to moderate effect loci. Recent GWAS analyses were able to detect some of these loci as statistically significant at the genome-wide level, but only with much larger sample sizes HEPH) and V-set and immunoglobin domain containing 4 (VSIG4) as well as 4 pseudogenes and 1 microRNA - mir223. VSIG4 is coded in the middle of the first LD region identified in our haplotype analysis. This gene is part of the complement receptor family and appears to play an important role in regulating innate and adaptive immune response through clearance of autologous and pathogenic cells The 377 kb Xq12 locus identified by SNP prioritization contains 2 genes, hephaestin , is in the 5′UTR of the HEPH gene. Further sequencing of this locus is required to identify any additional SNPs that may be relevant to migraine. Hephaestin is an iron transport protein involved in cellular iron export through oxidising ferrous to ferric iron for uptake by transferrin or other iron carriers. Hephaestin expression has been identified throughout the human gastrointestinal tract as well as in pancreatic islets and the enteric nerves HEPH gene. Furthermore, it has been shown in mice that hephaestin is required for iron homeostasis in the CNS Similarly the 5′ end of We have provided compelling evidence for a new migraine susceptibility locus at Xq12 in a pedigree from the genetic isolate of Norfolk Island and shown some evidence that the association extends to the general migraine population. Furthermore analysis in the Norfolk Island cohort provides additional evidence to support an existing migraine locus at Xq27.The study protocol was approved by the Griffith University Human Research Ethics Committee and all participants provided signed informed consent. 600 participants were included based on permanent resident status to ensure sampling from a shared genealogical background. A comprehensive medical questionnaire was used to obtain phenotypic data including migraine information regarding family history, symptoms, triggers and medication. Migraineurs were diagnosed in accordance with ICHD-II guidelines Venous blood samples were obtained from the 600 participants  with a mean age of 50.8 years (standard deviation 16.4 years). Blood samples were collected in EDTA tubes and DNA extracted from 10–20 mls using a standard salting out procedure th century N = 1,078) using a peeling algorithm in the pedigree database management system PEDSYS. This 1,078 member pedigree has been previously employed in genome-wide screens of cardiovascular risk traits Genealogical data was obtained via questionnaire, and municipal and historical records. These records indicate Pitcairn Island was settled by 9 Isle of man ‘Bounty’ mutineers, 12 Tahitian women and 6 Tahitian men in 1790 The mode of inheritance of migraine in this extended pedigree does not follow a clear Mendelian pattern ie. is complex. However, there is only a single observable case of male-to-male transmission which is consistent with a predominantly X chromosomal inheritance of migraine in this pedigree.HWE<1×10−5) c) the a minor allele frequency (MAF) was less than 1% d) there were male heterozygosity scores observed A subset of 288 related individuals consisting of 136 males and 152 females were genotyped for this study including 76 migraine cases consisting of 22 males and 54 females. 15,668 X chromosome wide SNPs were genotyped on the Illumina Infinium High Density (HD) Human 610-Quad DNA analysis BeadChip version 1 using 200 ng of DNA per sample, as part of a GWAS. Samples were scanned on the Illumina BeadArray 500GX Reader and the Illumina BeadScan image data acquisition software (version 2.3.0.13) was used to collect raw data. Preliminary analysis of raw data was undertaken in Illumina GenomeStudio software (V2010.1) with the recommended parameters for the Infinium assay. Genotype cluster files were generated based on clustering of genotypes within the Norfolk Island population. Five individuals had a call rate below 95% and were not included in the analysis. SNPs were excluded from the analysis if a) the call rate fell below 99% b) genotype frequencies deviating from Hardy-Weinberg Equilibrium  software package For computational efficiency a logistic regression approach implemented in the PLINK software Haplotype analysis was carried out firstly using Haploview P-value were carried through for assessment in the follow-up cohort from the WGHS. Ascertainment and ethical approval of this cohort are described elsewhere SNPs identified in the haplotype blocks at the Xq12 and Xq27 locus as well as significant SNPs in the Xq28 locus were investigated in an independent follow-up cohort from the Women’s Genome Health Study (WGHS). All SNPs that were present in the top 25 SNPs ranked by


We have previously demonstrated that Bac8c appears to interfere with multiple targets, at least in part through the disruption of cytoplasmic membrane related functions, and that resistance to this peptide does not easily develop using standard laboratory methods. Here, we applied a genomics approach, SCalar Analysis of Library Enrichement (SCALEs), to map the effect of gene overexpression onto Bac8c resistance in parallel for all genes and gene combinations (up to ∼ 10 adjacent genes) in the E. coli genome . Our efforts identified an elaborate network of genes for which overexpression leads to low-level resistance to Bac8c . This data was analyzed to provide insights into the complex relationships between mechanisms of action and potential routes by which resistance to this synthetic AMP can develop.A fundamental issue in the design and development of antimicrobials is the lack of understanding of complex modes of action and how this complexity affects potential pathways for resistance evolution. Bac8c (RIWVIWRR-NH A major barrier to the development of antimicrobial peptide-based therapies is the lack of a complete understanding of the complex modes of killing by antimicrobial peptides (AMPs) 2) is an 8 amino acid peptide derived through a complete substitution analysis of Bac2A (RLARIVVIRVAR-NH2) Bac8c  approach employs gene-chip technology and precisely designed extra-chromosomal libraries to map the effect of gene over-expression on overall cell fitness (in this case resistance to Bac8c) E. coli strain Mach1-T1R  wild-type W strain  Mach1-T1R F− φ80(lacZ)ΔM15 ΔlacX74 hsdR(rK−mK+) ΔrecA1398 endA1 tonA containing the pSMART LC KAN empty vector were used for all control studies. Overnight cultures were grown in Luria Bertani (LB) medium. Growth curves were carried out in 3-(N-morpholino)propanesulfonic acid (MOPS) minimal medium E. coli K12 were grown overnight in 500 ml of LB at 37°C to an optical density at 600 nm (OD600) of 1. DNA was extracted using a Genomic DNA Purification kit (Qiagen) according to the manufacturer’s instructions. Five samples containing 50 µg of purified genomic DNA were digested using two blunt-end cutting restriction enzymes: AluI and RsaI (Invitrogen). Both enzymes have four base pair recognition sequences and are used in tandem to ensure the random digestion of the genomic DNA. The partially digested DNA was immediately mixed and separated based on size using agarose gel electrophoresis. DNA fragments of 0.5, 1, 2, 4, and greater than 8 kb were excised from the gel and purified with a Gel Extraction Kit (Qiagen).Drs. Tanya Warnecke and Michael D. Lynch constructed the genomic library, as described previously E. coli , plated on LB+KAN, and incubated at 37°C for 24 hours. Dilution cultures with one thousandth of the original transformation volume were plated on LB+KAN in triplicate to determine accurate transformation efficiency and to confirm that greater than 105 transformants per library were obtained, corresponding to greater than 99% probability of complete library coverage.Ligation of the purified, fragmented DNA with the pSMART LC KAN vectors was performed with the CloneSmart Kit (Lucigen) according to the manufacturer’s instructions. The ligation product was then electroporated into 11cells/ml 6). The original cultures were combined and diluted to 100 ml with MOPS minimal medium+KAN and incubated at 37°C for 6 hours or until reaching an OD600 of 0.20.Purified plasmid DNA from each library was introduced into MACH-1™-T1® (Invitrogen) by electroporation. MACH-1™-T1® cultures were made electrocompetent by a standard glycerol wash procedure on ice to a final concentration of 10E. coli was determined to be 3 µg/ml while the MBC was 6 µg/ml 600 of 0.1. An aliquot of cells (1 ml of 107 cells/ml) was plated at time zero. Two separate selections were preformed one starting at a Bac8c concentration of 7 µg/ml (above the control MBC), and another starting at . The first selection (batch one) continued until cells reached mid log (OD600 = 0.5), which required 12 h for both AMP concentrations. An aliquot of these cells was diluted and plated on LB+KAN plates , and the cultures were then diluted to an OD600 of 0.1 and supplemented with 6 µg/ml and 5 µg/ml Bac8c respectively added to the separate selections (batch two). This batch was again grown to mid-log phase, which in this round required 6 h of growth. An aliquot of these cells was then plated and the cultures were again diluted and supplemented with 5 and 4 µg/ml Bac8c respectively to the separate selections. Selected populations were plated onto LB+KAN plates, and colonies were harvested after 24 h by gently scraping the plates into TB medium. The cultures were immediately resuspended by vortexing, and aliquoted into 15×1 mL freezerstock cultures with a final glycerol concentration of 15% (v/v) 5′-CAGTCCAGTTACGCTGGAGTC-3′) and SR2 (5′-GGTCAGGTATGATTTAAATGGTCAGT) or by restriction digestion.The MIC of Bac8c for For each array, 3 µg of sample plasmid DNA was mixed with the following control plasmid DNA: 1000 ng pGIBS-DAP (ATCC#87486), 100 ng pGIBS-THR (ATCC# 87484), 10 ng pGIBS-TRP (ATCC# 87485) and 1 ng pGIBS-PHE (ATCC# 87483). The plasmid mixture was digested at 37°C overnight with 1 unit each of AluI and RsaI (Invitrogen) in a reaction containing 50 mM Tris-HCl (pH 8.0), and 10 mM MgCl2. Reactions were heat inactivated at 70°C for 15 min. 10X One Phor All Buffer  was added to the digestions to a final 1X concentration. 1 µL RQDNAse I (Fisher) was added to the reactions and incubated at 37°C for 2 min followed by heat inactivation at 98°C for 20 min.E. Coli Antisense GeneChip® arrays  were handled at the University of Colorado DNA Microarray Facility according to manufacturer’s specifications using a GeneChip® Hybridization oven,GeneChip® Fluidics Station, GeneArray® scanner and GeneChip® Operating Software 1.1 (Affymetrix).One µl of Exonuclease III (Fisher) was added to the reactions and incubated at 37°C for 15 min followed by heat inactivation at 98°C for 20 min. The resulting fragmented single stranded DNA was then labeled with biotinylated ddUTP using the Enzo BioArray™ Terminal Labeling Kit  following the manufacturers’ protocol. Affymetrix et al. Data analysis was completed by utilizing SCALEs software developed by Lynch et al. according to author’s instructions 600 of 0.4 before and then sub-cultured, inoculating conical tubes with 1–10% (v/v) inoculum (starting OD600 = 0.1). Conical tubes (15 ml) were incubated at 37°C with shaking, and OD600 was monitored regularly. Triplicate vector control flasks were run in parallel for all growth experiments. For multiple clone experiments, a 96 well polypropylene plate was used and 100 µl samples were measured in triplicate every 30 minutes for 8 hours. Specific growth rate was calculated by determining the optimal fit of linear trend lines by analyzing the R2-value.For growth rate determination, each clone was inoculated from an −80°C stock, cultured in 5 ml LB with KAN and incubated overnight in a 15 ml conical tube at 37°C with shaking. Each overnight culture was diluted into MOPS minimal medium (containing KAN and 0.1% glucose) to an OD600 of 0.5. The cells were further diluted 1∶1000 and a 90 µl aliquot was used to inoculate each well of a 96 well plate . The plate was arranged to measure the growth of variable strains or growth conditions in increasing Bac8c concentrations, 0 to 60 µg/ml, in 2-fold increments The MIC was determined aerobically in a 96 well-microtitre plate format as described previously E. coli of defined insert size  and employed the SCALEs method to identify E. coli genes for which overexpression improved growth in the presence of sub-lethal levels of Bac8c. We employed a decreasing gradient serial-transfer selection strategy, which we have shown previously improves both sensitivity  and selectivity (true positives) relative to alternative strategies (such as an increasing or flat concentration gradients) We constructed plasmid-based genomic libraries of E. coli genome for which overexpression confers low-level Bac8c resistance is provided in A genome-wide plot of all genes in the It is interesting to note that the major differences in fitness among evaluated clones happened in the later stages of the selection, where the Bac8c concentration was reduced. This is consistent with our prior efforts where starting at a higher concentration selects first for the smaller set of clones that survive the initial shock and then allows for enrichment and separation of such true-positive clones by reducing the selective concentration. While not investigated here, in prior efforts we have shown how this approach improves enrichment for the most tolerant clones that might not grow as well at lower concentrations but are able to survive and/or grow at more selective concentrations. Our data suggests a similar pattern here, a relatively smooth fitness landscapes  in fusA-tufA, yicJ, and putA) actually showed increased growth rate in the presence of the peptide relative to the absence of peptide.We picked twenty-one clones for further analysis that were identified as substantially enriched in the SCALEs analysis and obtained from plates of samples taken at the end of the enrichment studies. For each clone, we first confirmed an increase in resistance to Bac8c either through an increase in specific growth in the presence of the peptide or through an increase in minimum inhibitory concentration (MIC). We found that, in the presence of 3 µg/ml Bac8c, which caused an approximately 50% growth inhibition of the control, 9 of the 21 clones had a relative increase in growth rate compared to the control  confirming the SCALEs predictions of Bac8c resistance . Of the yajO clone that only showed an increase in specific growth in the presence of the peptide, and the pqiAB clone that only showed an increase in MIC. Many of the clones that were not subsequently found to be resistant, showed a slower growth phenotype then the control, in the presence or absence of peptide, providing a possible explanation for their persistence despite lack of resistance  We also tested each clone for an increase in MIC. Similar to the growth rate studies, 14 of the 21 clones demonstrated an increased MIC. These clones were identical with the exception of the Cross-resistance studies were performed both to provide further confirmation of the relevance of the genes that when overexpressed led to Bac8c resistance, as well as to gain further insights into the potential modes of Bac8c action. We tested cross-resistance for seven of our Bac8c resistant clones towards the parental peptide of Bac8c, antimicrobials targeting membrane permeability, cell-wall synthesis, or protein synthesis, conditions triggering a general stress response, and agents influencing electron trafficking.treB clone was observed to demonstrate increased resistance to vancomycin and gramicidin. However, treB was not more resistant to carbenicillin . These data suggest that collectively these clones conferred Bac8c resistance through relief of a mechanism of action separate from or more complex than the mechanisms employed by these antibiotics.We first tested each of the clones against a panel of antibiotics that are known to: alter membrane permeability (polymyxin B and gramicidin), inhibit cell wall synthesis (vancomycin and carbenicillin), or inhibit protein synthesis (streptomycin) . Most Ba2), and Sub3 is a 12-mer with a +6 charge (RRWRIVVIRVRR-NH2). Several clones were cross-resistant to either or both Sub3 and K24. Clones lpd, treB, yajO, rpsLG-fusA, and yicJ were resistant to Sub3, and clones appBC, lpd, treB, yajO, and rpsLG-fusA were resistant to K24. Surprisingly, however, most of the clones that were resistant to Bac8c were not resistant to the parent peptide Bac2A. We found that only the treB and rpsLG-fusA clones exhibited cross-resistance to the parent peptide. These results further support the complexity of mechanism of action of antimicrobial peptides, wherein 1–2 amino acid changes in peptide sequence led to varying levels of susceptibility across a range of resistant clones. This data supports previous work done by Hilpert et. al. We next wanted to know if the resistance to Bac8c extended to the parental peptide of Bac8c (Bac2A), and two additional peptides that were synthesized from Bac2A  . These pyicJ, and rpsLG-fusA demonstrated improved growth under heat shock conditions. Interestingly, of all clones tested these two clones were the only ones that had insert genes that are controlled by σ24, the heat shock sigma factor.One possible explanation for how these clones confer resistance is that each elicits a cellular state that is generally more stress tolerance. To explore this possibility, we next tested resistance of the clones to heat shock. Only clones E. coli such as NAD+/NADH and the various components of electron transport chain (as has been shown for other antibiotics previously 2 and an electron source must be present for paraquat to elicit deleterious effects through generation of reactive oxygen species (ROS). It has also been shown that paraquat can inhibit NAD+ biosynthesis treBC and rpsLG-fusA were consistently between 1.7 and 20 fold more susceptible to paraquat, which could be explained if they had either increased levels of NADH (or another relevant electron donor) or an increased level of baseline or induced ROS. To discriminate between these possibilities; we tested the sensitivity of these clones to H202, an oxidizing agent, which should have the same effect as paraquat if these clones had elevated ROS. None of the clones were statistically more sensitive or resistant to H202. These results were consistent with the hypothesis that increased paraquat sensitivity was related to NAD+/NADH modulation rather than an increase in basal ROS levels, thus suggesting that most of our identified clones were conferring resistance through such modulation.In previous studies, we showed that Bac8c interferes with electron trafficking +/NADH modulation in the resistance of our clones, several clones were tested for resistance to carbonyl cyanide m-chlorophenyl hydrazone (CCCP), an ionophore that disrupts the proton gradient by shuttling protons across the cytoplasmic membrane; this then uncouples electron transport chain based proton pumping from ATP synthesis. An increase in CCCP resistance has previously been correlated with an ability to uncouple substrate metabolism from oxidative phosphorylation +/NADH related electron trafficking in the various Bac8c resistant clones identified here.To further link any role of NADOur study used the SCALEs methodology to better understand the ability of the Bac8c antimicrobial peptide to avoid high-level resistance evolution in laboratory settings. Overexpression from the cloned gene as a method of resistance does not usually occur in the clinic; however it mimics both plasmid mediated resistance and regulatory mutations leading, for example, to increased expression of β-lactamases, efflux pumps, aminoglycoside modifying enzymes and LPS modifications 202 was observed). Conversely bacteria that are resistant to uncouplers like CCCP either exclude these uncouplers or are still sensitive to the effects yet have altered properties that allow metabolism to proceed in the presence of a low membrane potential (ΔΨ) It has often been observed that bacteria that become resistant to a specific antibiotic may develop new properties, including changes in susceptibility to other agents +/NADH, or NADP+/NADPH  might similarly lead to modulation of electron trafficking, and thus resistance, are of interest.We propose that clones fall into two resistance classes that are distinguished by their level of sensitivity to paraquat. Paraquat is a substrate that promotes electron relay and can be reduced by cellular NADPH and NADH. Both di-oxygen and electrons must be present for paraquat to elicit deleterious effects. Thus we speculate that there were two classes of Bac8c resistance: Class one (paraquat sensitive) included clones that were involved in processes that used NADP+/NADPH , namely E.coli likely involving energy metabolism related electron trafficking. Specifically, we observed that many of the genes conferring Bac8c resistance also conferred increased paraquat sensitivity, as well as CCCP resistance; thus reinforcing the mechanistic similarities underlying the resistance of each of these clone. Since each of these clones overexpresses a distinct genetic loci, this outcome serves to illustrate the relationships that exist between the complex modes of action and associated modes of resistance of this synthetic AMP.In conclusion, we sought here to connect two important concepts, namely that Bac8c disturbs energy metabolism when not fully disrupting the membrane, and that resistance to Bac8c does not develop with ease. These concepts were explored by a high-resolution, genome-scale selection and analysis utilizing the SCALEs method. The resultant clones supported a multimodal mechanism of action for Bac8c as suggested by our prior studies Table S1Additional information for important clones.(DOCX)Click here for additional data file.Table S2Raw fitness data for Bac8c selections.(XLSX)Click here for additional data file.


Although energy metabolism and metabolic syndrome are the most intensively studied domain of PPARs, it has not been addressed specifically in any issue of PPAR Research ever since its launch. Here, we gathered 3 reviews and 5 research articles that encompass metabolic syndrome and its complications.Peroxisome proliferator-activated receptors (PPARs) exert versatile biological effects, notably in energy metabolism. During the last two decades, numerous studies have demonstrated that PPARs act as pivotal regulators of metabolic syndrome, a series of disorders in energy utilization and storage that are implicated with type 2 diabetes, diabetic nephropathy, and cardiovascular diseases, to mention a few. PPARγ and human adipogenesis in their research article. Rather than focusing on canonical PPARγ transcripts, authors largely emphasized on the critical contribution of PPARγ dominant negative isoforms to adipogenesis and their implied potential role in pathological conditions. In addition, a novel of PPARγ dominant negative transcript, γ1ORF4, was first identified in this study. In regard to nonalcoholic fatty liver diseases, the hepatic expression of the metabolic syndrome, M. Sharif et al. conducted a thorough analysis of previously published data about the steatogenic role of PPARγ and summarized two probable PPARγ ligand-dependent toxicological modes of action: (i) activation of PPARγ in hepatocytes and (ii) inhibition in adipocytes.M. Aprile et al. tackled the subject of PPARγ in diabetic nephropathy (DN). Their comprehensive review summarized the limitations of traditional PPARγ agonists, addressed the advantages of newly developed PPARγ agonists, and rendered new insights into the therapeutic potential of PPARγ agonists in the treatment of DN, while the research article suggested that a combination of PPARγ agonists with COX-2/PGE2 inhibitors may be an alternative way of dealing with DN. In another research article, J. Jin et al. analyzed the correlation between PPAR gene polymorphisms and pediatric primary nephrotic syndrome (PNS) by comparing children with PNS against healthy subjects. They found that PPARγ (Pro12Ala) and PGC-1α (Gly482Ser) polymorphisms are associated with abnormal insulin and triglyceride metabolism in pediatric PNS patients, suggesting that these polymorphisms may be relevant to the prognosis of this chronic disease.Two papers, one review and a research article, by Z. Jia and Y. Sun et al., appraised the role of PPARα in metabolic disorder-associated cardiovascular diseases was well recognized in this special issue. Z. Jia et al.'s research article asserted the involvement of HMGB1 (high mobility group box 1) in the protective effect of PPARα in cardiac hypertrophy and provided a novel approach to study the pathogenesis of cardiac hypertrophy. Although most studies showed that PPARα activation confers protection against atherogenesis, the intriguing possibility that PPARα might foster atherogenesis is also considered. In this current issue, M. Vechoropoulos et al. found that PPARα mediates the proatherogenic effect of chronic nitric oxide synthesis inhibition and this effect is independent of blood pressure and serum lipids alterations. These data further shaped the view that the role of PPARα in atherosclerosis needs to be reevaluated.The knowledge of the role of PPARPPARs Integrate the Mammalian Clock and Energy Metabolism,” we collected recent findings about the role of PPARs in biological clocks. This brand new function of PPARs bridges energy metabolism with circadian rhythm whose relationship has been known for long time, but not well understood. We summarized the circadian function of three PPAR subtypes one by one and concluded that the abnormality of PPARs and circadian rhythm could impinge on each other and thus leads to metabolic disorders. Further investigation of PPARs in this field will give us a new perspective on the therapeutic advances in the treatment of metabolic ailments.Lastly, in the review article “In conclusion, this special issue is packed with intriguing novel breakthroughs and insights into PPARs and metabolic syndrome. We hope that these advances will generate more interest from the scientific community in better understanding of the role of PPARs in metabolic syndrome and associated complications.Lihong  ChenLihong  ChenZhanjun  JiaZhanjun  JiaGuangrui  YangGuangrui  Yang


Urinary mercury concentrations are used in research exploring mercury exposure. Some theorists have proposed that autism is caused by mercury toxicity. We set out to test whether mercury concentrations in the urine of children with autism were significantly increased or decreased compared to controls or siblings.n = 42) and a control sample of children without ASD in mainstream (n = 121) and special schools (n = 34).Blinded cohort analyses were carried out on the urine of 56 children with autism spectrum disorders (ASD) compared to their siblings (There were no statistically significant differences in creatinine levels, in uncorrected urinary mercury levels or in levels of mercury corrected for creatinine, whether or not the analysis is controlled for age, gender and amalgam fillings.This study lends no support for the hypothesis of differences in urinary mercury excretion in children with autism compared to other groups. Some of the results, however, do suggest further research in the area may be warranted to replicate this in a larger group and with clear measurement of potential confounding factors. Some authors have been concerned that mercury-based preservatives in certain vaccinations Developmental problems associated with environmental mercury exposure are well documented. In a study of 63 infants in Japan with congenital mercury poisoning a range of reported problems were observed, including significant learning disabilities, limb deformities, cerebellar ataxia It is well established that environmental mercury in high doses is very toxic Much lower exposure to mercury than seen in these studies occurs in most societies, with one route being the use of mercury in amalgam fillings. In a study in Portugal over 500 children aged 8–10 were randomised to receive either amalgam fillings or composite fillings The fear that mercury causes autism came from speculation that the use of thimerosal in certain vaccinations may have caused rates of autism diagnoses to rise Despite this, some authors have continued to posit mercury-related abnormalities in the development of autism. It has been hypothesised that children with autism may have a problem excreting mercury from the body Another excretion route is urine; if mercury excretion were impaired in ASD children, this should also be evident in their urinary levels of mercury. Whilst urine studies exploring foetal exposure in mothers who eat large amounts of mercury in fish have found no neurocognitive risk to the children of mothers eating on average 12 fish meals per week Studies that have looked specifically at the urine of children with autism have produced mixed results. Bradstreet and colleagues n = 18, 14 & 5 respectively), perhaps because of the use of chelation, which is potentially harmful for children None of the above studies directly measured urinary levels of mercury in children who had no form of chelation treatment. Furthermore, the Geier/Bradstreet group has only used very small control samples (n = 115), children from special schools (n = 28) and ASD siblings (n = 40). To account for differing levels of mercury exposure across groups, the number of current amalgam fillings was recorded. Urine concentration was controlled for by correcting for creatinine. Given some authors views that heavy metals more broadly might be implicated or face excretion difficulties We set out to do a blinded study to compare urine concentrations of mercury between groups of children with autism spectrum disorders and controls. Unlike other studies of urinary mercury in autism we examined ordinary, non-treatment levels of mercury and compared them to three different control groups; mainstream schoolchildren (Samples of urine were collected from children with autism spectrum disorders (ASDs), ASD siblings, mainstream control children and special school control children. A special school mainly educates children with learning disabilities in the first percentile range. The sample were subsequently frozen at −80°C. Diagnoses of Childhood Autism, Atypical Autism or Asperger Syndrome were made using Research Diagnostic Criteria (RDC) from the World Health Organisation International Classification of Diseases system version 10 Ethical and governance approval was granted by local health ethics and R&D Committees in York. Exclusion criteria included any known metabolic or neurological disorder. Children were excluded from the control group if they had received an assessment for an autism spectrum disorder or where concerns had been raised by the teacher that the child might be on the autism spectrum. Where capacity to provide written consent was reduced then those with parental responsibility provided written consent on their child's behalf with the child or young person also giving their assent.Morning samples were collected in sterile plastic pots, sealed and then placed in a sealed plastic wrapper until collection. No sulfamic acid or surfactant was used. The urine samples were blinded with code numbers and delivered via one of several points of collection to a local Department of Clinical Biochemistry within 24 hours. Creatinine concentrations were determined and aliquots were separated and frozen at −20°C. Analysis of urine was calculated at the Food and Environment Agency at Sand Hutton and the Health and Safety Laboratory in Sheffield, as described below.The analytical laboratories remained blinded to identity or diagnosis throughout.Fer's role in the project was to provide multi-element data. A random subsample  was selected by a laboratory technician blinded to diagnosis or any identifying information using randomised numbers. These urines were additionally tested for other heavy metals. Fer performed an initial screen of 25 elements which, after QA/QC assessment, was reduced to 10, i.e., lithium, vanadium, manganese, cobalt, copper, cadmium, antimony, barium, mercury and lead. Using this, the Limits of Distinction (LOD) were calculated and were all satisfactory except the LOD achievable for mercury, which was 0.9 µg/l, and so all samples were then sent to the Health and Safety Laboratory (HSL) for analysis of this specific element given lower available LODs. The Limit of Detection (LOD) describes the lowest level a target substance can be reliably detected.Measurement of the other nine elements was by Inductively Coupled Plasma Mass Spectrometry*. All aspects of the method were performed to UKAS acceptable criteria. Fer is a regular successful participant in the relevant Series of FAPAS (proficiency testing scheme).Mercury was determined in urine samples using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) Thermo Fisher Scientific X7, Series 1 . The urine samples were defrosted at room temperature and rolled to mix. The urine samples were then diluted 1 in 10  with 5% nitric acid solution, containing 10 µg/L platinum as an internal standard and 1 mg/L gold as a stabiliser for the mercury. External quality control (EQC) samples (Bio-Rad Level 1 Lypocheck Urine) and a 5 µg/L calibration standard check were analysed at the start and end of analysis and after every ten samples. The aqueous calibration standards were in the range 0–100 µg/L. Any sample outside the calibration range would be repeated. The ICP-MS was operated in normal mode with direct nebulisation and a dedicated mercury rinse solution was aspirated containing 1 mg/L gold and 5% nitric acid.The results for the EQC for 53 samples was 40.5±4.6 µg/L (expected range for BR 69091 38–58 µg/L). The stability of the 5 µg/L check standard was 5±0.5 µg/L. The method is UKAS accredited and acquires successful participation in both the UK TEQAS and German G-EQUAS quality assurance schemes.In this study the LOD for mercury using a volume of 1 millilitre was 0.35 nmol/L (0.07 µg/l). The LODs for elements other than mercury were all well below the levels being found.Analysis was performed to see if there was any relationship between mercury levels and diagnostic group. This test was performed twice: i) without creatinine correction and ii) with creatinine correction. Creatinine ratios were calculated to correct for variations in urinary mercury caused by body mass and urine concentration.Some levels of mercury (28) in urine were below the limit of detection (LOD). In order not to lose valuable information in the analysis, we have analysed the data treating values below the LOD in two ways, firstly treating it as zero and secondly using the mercury LOD threshold value (0.35 nmol/L). This covers the spread of possible values below the limit of detection (i.e. the amount could be anything (from zero to 0.35 nmol/L). The statistical analysis therefore covers this range of possible options. In addition, data about the number of current in situ amalgam fillings was collected systematically from all participants' dental records.The power calculation was based on the study by Holmes and colleagues The four groups were compared using Kruskall Wallis tests for continuous data and Chi-Square for categorical data. A p-value of <0.05 was considered to indicate statistical significance. To adjust of the effects of age, gender and number of fillings multiple regression was undertaken. All analyses were performed on SPSS (version 18). Kruskal-Wallis tests were utilised instead of parametric equivalents due to skew in the raw data.Included in the study were 251 children: 54 children on the autism spectrum, 155 children without autism , and 42 children who were the siblings of those with ASD.KW (3) = 3.907, p = 0.272), even after grouping participants into those with or without fillings (Chi(3) = 3.893, p = 0.273).There was a significant difference between the groups for age (F(3) = 20.726, p<0.001), and gender (Chi(3) = 15.900, p = 0.001). The number of fillings was slightly lower in ASD children , althougThere were no significant differences between the four groups in uncorrected mercury level regardless of how the values below the LODs were treated . There was no difference between the groups and creatinine levels (KW(3) = 1.734, p = 0.630).After adjusting for age, gender and number of fillings, there was still no statistically significant difference between the groups (mercury level with blanks given zero: F (3) = 2.587, p = 0.056; mercury level with blanks given 0.35: F (3) = 2.570, p = 0.056), even after removing extreme values (mercury level with blanks given zero: F (3) = 0.897, p = 0.444; mercury level with blanks given 0.35: F (3) = 0.867, p = 0.459).Tests of other heavy metals find no differences between groups. This includes lithium (p = 0.344), vanadium (p = 0.951), manganese (p = 0.613),cobalt , cadmium (p = 0.586), antinomy (p = 0.216), barium (p = 0.328) and lead (p = 0.203)*.The hypothesis that mercury poisoning (either through increased exposure or reduced excretion) may cause autism is a cause of anxiety to many parents. It may prompt them to change vaccination behaviour and in some rare cases to use oral chelating agents, both of which pose a risk to the child The widespread but much lower dose exposure of children to ethylmercury in some vaccinations containing thimerosal has been studied epidemiologically We found no statistically significant differences in urinary mercury corrected for creatinine, between the groups compared to the control groups, mainstream children and siblings. The other heavy metals showed no differences that would have encouraged us to test the whole group for these elements, or to suggest broader heavy metal metabolism problems.We interpret our findings with caution. The results appear to be influenced strongly by a small number of extreme values in the ASD and special school group but not the other two groups see . There iThis study makes no comparisons of brain mercury levels between the two groups. The finding by Holmes and colleagues The present study has limitations that must be considered. The sample size is relatively small. Given the KW and P scores there is a possibility that there is a type II error with inadequate power. Our data can be used to calculate numbers needed for a future adequately powered study. Whilst collection of 24-hour urines may have improved accuracy, such samples are very difficult to collect in children with learning disability and autism and research shows good correlations between spot urines and 24-hour collections This study does not lend support for widespread mercury metabolism problems in autism, but given small numbers of outliers it does suggest further research is warranted to better understand whether a subgroup with autism or learning disabilities have mercury poisoning or excretion difficulties. Recent research has however found no association between autism and genes polymorphisms responsible for controlling the transport and response to body mercury *Further details are available from the corresponding author.


In contrast to rhACE2, rm ACE2 is substantially less potent in transformation of Ang 1–10 to Ang 1–9.Angiotensin-converting enzyme 2 (ACE2) is a monocarboxypeptidase of the renin-angiotensin-system (RAS) which is known to cleave several substrates among vasoactive peptides. Its preferred substrate is Angiotensin II, which is tightly involved in the regulation of important physiological functions including fluid homeostasis and blood pressure. Ang 1–7, the main enzymatic product of ACE2, became increasingly important in the literature in recent years, as it was reported to counteract hypertensive and fibrotic actions of Angiotensin II via the MAS receptor. The functional connection of ACE2, Ang 1–7, and the MAS receptor is also referred to as the alternative axis of the RAS. In the present paper, we describe the recombinant expression and purification of human and murine ACE2 (rhACE2 and rmACE2). Furthermore, we determined the conversion rates of rhACE2 and rmACE2 for different natural peptide substrates in plasma samples and discovered species-specific differences in substrate specificities, probably leading to functional differences in the alternative axis of the RAS. In particular, conversion rates of Ang 1–10 to Ang 1–9 were found to be substantially different when applying rhACE2 or rmACE2  The classical renin-angiotensin-system (RAS) is a proteolytic cascade which is constituted by multiple enzymes and effector peptides. The cascade starts when Angiotensin I Ang 1–10) is released from the propeptide angiotensinogen by kidney-secreted renin. The peptide metabolites produced from Ang 1–10 by a variety of proteases act as ligands for angiotensin receptors in different tissues leading to a diversified panel of physiological functions mediated by angiotensin peptides [–10 is reAngiotensin II (Ang 1–8) is one of the most extensively studied angiotensin peptides. It is mainly produced by the proteolytic action of angiotensin-converting enzyme (ACE) by removal of the two C-terminal amino acids from Ang 1–10. Ang 1–8 is able to bind to several cellular receptors leading to a variety of physiologic effects among different tissues and cell types . ImportaThe disease-promoting functions of Ang 1–8 convert it to a favorable therapeutic target in the treatment of many diseases mainly by preventing its formation by low-molecular-weight compounds inhibiting appropriate enzymes of the RAS cascade. An alternative way of decreasing Ang 1–8 levels became available over the recent years and uses recombinant angiotensin-converting enzyme 2 (ACE2) to lower Ang 1–8 levels. ACE2 inactivates Ang 1–8 by clipping off one C-terminal phenylalanine , while ATherefore, the monocarboxypeptidase ACE2 is a key activator of the alternative RAS and is critically involved in the regulation of the classical RAS, which is known to be functionally important in the vascular system and in a variety of organs , 10, 11.in vitro [Throughout all these studies the loss of ACE2 activity in knock-out variants induced pathologies which could be restored by systemic administration of the recombinant enzyme. ACE2 therefore can be regarded as one of the key players of the renin-angiotensin-system (RAS) being responsible for fluid homeostasis, blood pressure regulation, inflammatory processes, and cell proliferation. ACE2 is a membrane anchored glycoprotein which is expressed in most organs and blood vessels and recognizes multiple peptide substrates within the RAS and other peptide hormone systems. Among its substrates beside Ang 1–8, Ang 1–10, and des-Arg-bradykinin, Apelins and Dynorphins have been reported to be cleaved by ACE2 in vitro  with Angin vitro .in vitro and in blood plasma which represents the natural compartment of enzyme action. In previously mentioned murine knock-out models, rhACE2 was frequently used to restore ACE2 activity. Despite the fact that sequence coverage between murine and human ACE2 is only 83% [We recombinantly expressed both human ACE2 (rhACE2) and murine ACE2 (rmACE2) and compared their substrate conversion rates only 83% , it has 280: rhACE2: ε = 1621 L∗mol−1∗cm−1, rmACE2: ε = 1750 L∗mol−1∗cm−1).The extracellular domains of human or murine ACE2  were recμg of rmACE2 and rhACE2 were applied on a precast native 3–12% gradient gel (Invitrogen). Anode buffer  and cathode buffer  were used to run the gel. 40% glycerol, 200 mM Bis/Tris, and 200 mM Tricine were used as a loading buffer. NativeMark Unstained Protein Standard (Thermo Scientific) was used for estimation of molecular weights in Coomassie Blue-stained gels. The gel was run at 150 V for 80 min. Proteins were stained in gel using NOVEX Colloidal Blue Staining Kit according to manufacturers' recommendations.2 Samples were analyzed by SDS-PAGE using a 4–12% precast gradient gel (NuPage) following reductive denaturation for 5 min at 95°C. BenchMark Protein Ladder was run on the same gel to allow molecular weight estimations. The gel was run in NuPage MES SDS Running Buffer (Invitrogen) at 150 V for 80 min. In gel protein staining was performed using a NOVEX Colloidal Blue Staining Kit according to manufacturer's protocol.in vitro kinetic analysis of Ang 1–8 and Ang 1–10 cleavage followed by HPLC-based quantification of substrate and product concentrations. Enzyme reactions were started by adding a defined amount of enzyme to substrate dilutions in MES-buffer  which were previously equilibrated at 37°C. Aliquots of the reaction mixes were taken every 10 minutes and stopped by addition of 0.5 M EDTA to a final concentration of 100 mM before HPLC-based quantification of peptides.Substrate specific turnover rates for rhACE2 and rmACE2 were determined by μm) with 0.08% H3PO4 in water as mobile phase A and 40% acetonitrile in water and 0.08% H3PO4 as mobile phase B. The optical density at 280 nM was recorded inline for all eluting peaks, and peptide concentrations were calculated via calibration curves for each individual peptide.The concentration of peptides in enzymatic reactions was quantified by detection of peaks eluted from the HPLC column using an in-line diode array detector. Chromatography was performed by running a gradient on a reversed-phase matrix  to isolated blood plasma, rmACE2 or rhACE2 was added to the samples. After 10 minutes of incubation at 37°C, in the presence or absence of Lisinopril (Sigma), samples were chilled on ice and immediately subjected to LC-MS/MS analysis.μL 50% acetonitrile/0.1% formic acid and subjected to LC-MS/MS analysis using a reversed-phase analytical column  using a gradient ranging from 10% acetonitrile/0.1% formic acid to 70% acetonitrile/0.1% formic acid in 9 minutes. The eluate was analyzed in line with a QTRAP-4000 mass spectrometer (AB Sciex) operated in the MRM mode using dwell times of 25 msec at a cone voltage of 4000 volts and a source temperature of 300°C. For each peptide and corresponding internal standards, two different mass transitions were measured. Angiotensin peptide concentrations were calculated by relating endogenous peptide signals to internal standard signals provided that integrated signals achieved a signal-to-noise ratio above 10. The quantification limits for individual peptides were found to range between 1 pg/mL and 5 pg/mL undiluted plasma.Plasma samples were spiked with 100 pg/mL stable-isotope-labeled internal standards and subjected to solid-phase extraction using Sep-Pak cartridges (Waters) according to manufacturers protocol. Following elution and solvent evaporation, samples were reconstituted in 50 The quality of the frozen enzyme batches used for later functional analysis was analyzed regarding enzyme purity and characteristics. The investigation of rmACE2 and rhACE2 by size-exclusion chromatography revealed that no detectable contaminations were present in the enzyme preparations. The protein concentration in the enzyme batches was determined by measuring the peak absorbance inline at 280 nm, peak integration, and subsequent calculation based on the corresponding extinction coefficients. Both ACE2 variants appeared as baseline separated sharp peaks. rhACE2 and rmACE2 were found to slightly differ in retention times, pointing to a difference in their hydrodynamic molecular diameter which was found to be lower for rmACE2 . In ordein vitro system. Therefore, we coincubated defined amounts of purified enzymes with an excess of Ang 1–8 and Ang 1–10, respectively, which represent natural substrates for ACE2. We found that rhACE2 as well as rmACE2 converted Ang 1–8 to Ang 1–7 at comparable rates . Furthermore, the comparison of turnover numbers for different substrates revealed that Ang 1–8 is the preferred substrate for both enzymes in vitro with a 42-fold higher turnover number for rhACE2 (0.77 s−1) and a 492-fold higher turnover number for rmACE2 (0.62 s−1) compared to Ang 1–10  rhACE2 was found to efficiently convert Ang 1–10 to Ang 1–9, as indicated by the peptide levels depicted in the RAS-Fingerprints  . Although ex vivo incubations are very reproducible and reflect an integrated picture of soluble enzyme activities throughout the RAS in undiluted plasma, the angiotensin peptide concentrations are clearly higher in ex vivo incubated plasma samples, which might be caused by a lack of the peptide flow towards organs or endothelial surfaces ex vivo.Therefore, we developed an We investigated the RAS in these samples by means of a newly developed LC-MS/MS method, which allows the quantification of multiple angiotensin metabolites simultaneously in one single sample of blood plasma. The obtained RAS-Fingerprints revealed that, in contrast to rmACE2, rhACE2 is capable to generate Ang 1–9 from Ang 1–10 at physiologic peptide concentrations . This acin vivo [in vivo conditions very well. However, plasma lacks all blood cells which might carry receptors and angiotensin peptide converting enzymes being able to affect angiotensin peptide concentrations in vivo. Comparison of plasma and whole blood samples revealed that Lisinopril-induced Ang 1–7 accumulation is strictly dependent on blood cell-associated angiotensin peptide converting enzymes, as it was exclusively observed in whole blood ex vivo incubations (in vitro [in vivo, especially in the presence of ACE inhibitors which block the formation of Ang 1–8 which is an important precursor for Ang 1–7.Although significant amounts of Ang 1–10 and Ang 1–9 were present in samples treated with Lisinopril alone or in combination with rhACE2, no Ang 1–7 could be detected in these samples. These findings were in contrast to previously published reports on Ang 1–7 accumulating effects of ACE inhibitors in vivo , 21. In in vitro , NEP is in vivo, when ACE inhibitors are used for antihypertensive treatment. As ACE2 is primarily expressed as a membrane-attached enzyme in several organs [in vivo in humans. In addition to Ang 1–7, also Ang 1–9 has been reported to possess protective effects in cardiovascular disease models [In human plasma, the ACE2-mediated formation of Ang 1–9 from Ang 1–10 represents a significant route of establishment of the alternative RAS. This may be, for example, of particular importance l organs , the loce models . These mAltogether, our findings describe important species-specific differences in the fine specificity of ACE2. Thus, the murine RAS is likely to function differently when compared to its human counterpart. Furthermore, our data point to the importance of further investigations and improved understanding of the human RAS, while data generated in murine model systems might be partially reconsidered in respect to different enzyme properties. Deciphering the functional characteristics of the human RAS using new analytical possibilities reveals previously invisible features of the system. The future generation of human-derived data describing RAS function in health and disease will pave the way for new concepts of therapeutic manipulations of the system which are more specifically designed for application in humans.


Any manipulation to the library is an operator acting on n. Selection, amplification, or sequencing could be described as a product of a N × N matrix and a stochastic sampling operator (Sa). The latter is a random diagonal matrix that describes sampling of a library. In this paper, we focus on the properties of Sa and use them to define the sequencing operator (Seq). Sequencing without any bias and errors is Seq = Sa IN, where IN is a N × N unity matrix. Any bias in sequencing changes IN to a nonunity matrix. We identified a diagonal censorship matrix (CEN), which describes elimination or statistically significant downsampling, of specific reads during the sequencing process.Next-generation sequencing techniques empower selection of ligands from phage-display libraries because they can detect low abundant clones and quantify changes in the copy numbers of clones without excessive selection rounds. Identification of errors in deep sequencing data is the most critical step in this process because these techniques have error rates >1%. Mechanisms that yield errors in Illumina and other techniques have been proposed, but no reports to date describe error analysis in phage libraries. Our paper focuses on error analysis of 7-mer peptide libraries sequenced by Illumina method. Low theoretical complexity of this phage library, as compared to complexity of long genetic reads and genomes, allowed us to describe this library using convenient linear vector and operator framework. We describe a phage library as N × 1 frequency vector In vitro selection experiments—such as phage display  is a sampling fraction. fSa operator has the following properties, which emanate from physical properties of the sampling procedure:(I)(II)fSa is a diagonal operator with diagonal scalar functions ||Sa11  Sa22 ⋯ SaNN||, Sai(0) = 0.(III)B = fSa A, B is a vector of positive integers, Bi ≥ 0 and sum(B) = f*sum(A). Integer values ensure that the observable values of the operator have physical meaning. The clone could be observed once (1), multiple times , or not observed at all (0).In (IV)Sa is nondeterministic operator. When applied to the same vector, the operator does not yield the same result but one of the possible vectors that satisfy rules (I–III). The majority of the solutions of the operator, however, reside within a deterministic confidence interval fSa A ∈ [loC hiC].(V)Sa is nonlinear, noncommutative, and nondistributive.As a consequence from (IV), operator (VI)N unity matrixLarge sum of sampling operators with same f should “average out” to yield IThe Sa operator is simple to implement as a random array indexing function in any programming language . It might be possible to express fSa analytically for any f as a diagonal matrix Saif0=0.We evaluated the behaviors of  Figures . The mos Figures . Graphic0.5Sa{A(1)  B(2)  C(3)  D(4)} operation yields large number of solutions with equal probability, termed as redundant solutions . On the other hand, calculation of the confidence interval of each element Bi of the vector B converges rapidly. A multiset {A1000} = {A1(1)  A2(2) ⋯ A1000(1000)} with 1000 unique elements and 1 + 2 + 3 + ⋯+1000 = 500,500 total elements is similar to an average deep sequencing data set   B(2)  C(3)  D(4)} made of four unique and 10 total elements, data set . Calculaments Bi .loKa and hiKa are diagonal matrices of the upper and lower confidence intervals for the association constants. A simulation of the behavior of the Sa operator . The necessary practical steps towards solving (Multiple sampling events of the e vector . Fitting solving  or 10)  Sa operreal sequence abundance in any phage library , hence, has to be derived from the observed sequence abundance (obsn) by solving this equation:fSa describes sampling at that step, and f1–f5 describe the sampling fractions. The bias in growth (Gr), isolation (Is), PCR amplification (PCR), and sequencing (Seq) could be related to the nucleotide sequences. The An analysis operator is a matrix that describes retaining, discarding, or correcting the sequence .Many of the error analyses in the area of deep sequencing are designed for genetic reads, which have variable lengths and unknown sequence throughout the whole read. Analysis of the reads in a phage-display library is a simpler problem because phage-derived constant adapter regions flank the variable reads. Identification of the adapter region is a necessary first step in the analysis. Reads, in which the adapters cannot be mapped, cannot be used. We designed algorithms to recover reads, even if adapters were hampered by truncation, deletion, or mutation  frequency vector on linear and log scale.Figure S5. Distribution of errors in censored reads.13n → 30n process.Table S1. Top 30 sequences censored during the 1n → 13n process.Table S2. Top 30 sequences censored during the Click here for additional data file.


Chlamydiaceae strains in pigeons, different from the established Chlamydiaceae, requires the development of a specific and rapid detection tool to investigate their prevalence and significance. Here is described a new real-time PCR assay that allows specific detection of atypical Chlamydiaceae from pigeons. The assay has been used to assess the dissemination of these strains in field samples collected from Parisian pigeon populations in 2009. The results suggest a limited dissemination compared to the usually higher prevalence of Chlamydia psittaci that is the main species associated with avian chlamydiosis.Recent evidence of the occurrence of atypical  Chlamydia psittaci, an obligatory intracellular bacterium and member of the family ChlamydiaceaeC. psittaci from birds to humans is reported regularly, particularly in high-risk individuals such as breeders or slaughterhouse workers C. psittaci as the causative agent of avian chlamydiosis in birds has been known for decades C. abortusC. suis and C. muridarumC. pecorum and C. trachomatisChlamydiaceae were recently detected in chickens Avian chlamydiosis is a zoonotic disease caused by Chlamydiaceae and the availability of fast, sensitive and specific detection tools are needed in order to better understand their epidemiological importance. A specific 16S rDNA-based real-time PCR was developed recently for the specific detection of atypical Chlamydiaceae from chickens (hereafter named ACC) A better characterisation of these atypical enoA) gene target for the specific detection of atypical Chlamydiaceae from pigeons (hereafter named ACP). This assay has been used to investigate the dissemination of this agent in Parisian pigeon populations.The work reported in this paper deals with the development and validation for routine diagnostic purposes of a real-time PCR based on the enolase A  and the Anses strain collection  were used for specificity testing. These included: Escherichia coli, Proteus mirabilis, Proteus vulgaris, Klebsiella pneumoniae, Salmonella enteritidis, Salmonella enteritidis serovar Gallinarum, Salmonella enteritidis serovar Typhi, Serratia marcescens, Morganella morganii, Citrobacter freundii, Yersinia enterocolitica, Yersinia pseudotuberculosis, Acinetobacter baumannii, Pasteurella haemolytica, Bordetella bronchiseptica, Staphylococcus aureus, Streptococcus pyogenes, Enterococcus faecalis, Mycobacterium avium subsp. avium, Aspergillus fumigatus, Aspergillus niger and Candida albicans.Chlamydial strains and isolates used for determination of specificity, sensitivity and detection limit of the new ACP-specific real-time PCR assay are listed in Chlamydial strains cultivated onto vitellus membranes as well as biological samples were subjected to DNA extraction using the QIAamp DNA Mini Kit . DNA extracts were stored at −20°C before analysis.DNA of non-chlamydial samples was extracted using the Instagen Matrix DNA Kit  according to the manufacturer's instructions. DNA concentration and purity of non-chlamydial extracts were spectrophotometrically assessed by reading A260 and A280 and confirmed by visualization on 0.5% (w/v) agarose gels. Finally, DNAs with a mean concentration of 400 µg/ml were stored at −20°C until required for analysis.enoA gene were previously published by Pannekoek and colleagues enoA were sequenced by Eurofins MWG Operon . Sequence alignments were conducted using the Bionumerics software package version 4.6 . A dendrogram including one representative of each enoA sequence type for established Chlamydiaceae strains YP_enoA5 and YP_enoA6 used for amplification of an approximately 400-bp segment of the 5′- CCTTGATATGTACGTGTTTTCTCG -3′) as well as a specific probe ACP_Pr (5′-FAM- CACCCCTGGTGAAGATATTTCCTTAGCAT -TAMRA 3′) were designed based on enoA and synthesised by Eurofins MWG Operon. Amplification was performed using the 2× TaqMan Universal PCR Master Mix . The final volume of the reaction mixture amounted to 20 µl including 10 µl of master mix, 2 µl of DNA sample, 0.6 µM of each primer, 0.1 µM of the probe and sterile PCR water added to reach the final volume. Amplification was carried out at an ABI Prism 7000 thermocycler (Applied Biosystems) using the following cycling parameters: heating at 95 °C for 10 min, 50 cycles of 95°C for 15 s and 60°C for 1 min. For all PCR reactions, DNA of the isolate 10–743/SC13 arbitrarily defined as reference strain for ACP was used as a positive control while sterile water was used as negative control.Specific primers ACP_Fw (5‘-CATGCAAGCTATTGAGAAAAGTGGT -3’) and ACP_Rv (−1 to 3×105 inclusion-forming units (IFUs) per PCR reaction. The concentration of this DNA was previously determined by comparison to a DNA purified from cell culture containing defined numbers of IFUs of C. psittaci. The standard curve and the number of IFUs were automatically determined by the software using manually entered IFU standard concentrations. The standard curve was generated by plotting Ct against the logarithm of IFU per PCR reaction mix. The Ct, at which the fluorescence crosses the threshold value, and the lower limit of detection of the assay were calculated automatically.The detection limit of the real-time PCR was determined in triplicate (independent runs) using decimal serial dilutions of purified genomic DNA from 10–743/SC13 suspensions equivalent to 3×10Chlamydiaceae DNA samples  The specificity of the new real-time PCR was evaluated on 22  samples Table 2 DNA of strain 10–743/SC13 was amplified 30 times in the same run to determine intra-assay repeatability, and 11 times in separate runs on different days for inter-assay reproducibility. The respective CVs were then calculated.Chlamydiaceae 23S-rtPCR A panel of 125 DNAs extracted from cloacal swab samples collected from pigeons in a previous study Chlamydiaceae strains in chickens and pigeons highlighted the necessity of specific and fast detection tools for the investigation of their epidemiological and clinical importance. Thirteen ACP strains have been isolated up to now in France, Germany and Italy (enoA) gene has been selected as target. This gene locus had been previously included in a Multi-Locus Sequence Typing scheme for Chlamydia spp. enoA sequences of ACP strains in in silico to those of the nine established Chlamydiaceae species Figure S1) and phylogenetic analysis  was tested with genomic DNA extracts of several bacterial and fungal species. Neither the DNA samples from non-chlamydial species (n = 22), nor the DNA samples from C. psittaci (n = 9), C. abortus (n = 4), C. pecorum (n = 6), C. felis (n = 1), C. caviae (n = 2) and newly described atypical chicken (ACC) isolates included in this study (n = 6) gave rise to a measurable signal. As expected, all DNA extracts from French (n = 2), German (n = 2) and Italian (n = 9) ACP isolates  with the new ACP-specific real-time PCR  according to Menard and colleagues C. psittaci was also found in two samples from Genevilliers  was found to possess an All in all, as a rapid and specific diagnostic tool is now available, it seems straightforward to include ACP investigation to analyses of diagnostic samples from birds and to undertake systematic studies to characterize the epidemiology and etiology of ACP infections in avian populations.Chlamydiaceae from pigeons has been developed and preliminary validated. The use of this new tool could contribute to a better understanding of the importance of these bacterial agents.A sensitive and specific real-time PCR assay for the detection of atypical Figure S1Alignment of partial enoA sequence for ACC (08–1274/3 reference), ACP (10–743/SC13 reference) and various established Chlamydiaceae strains . Nucleotide homologies are represented by dots. The numbers refer to alignment positions. ACP-specific primer sequences are boxed and the probe sequence is underlined.(TIF)Click here for additional data file.


Relationship between stability and activity of enzymes is maintained by underlying conformational flexibility. In thermophilic enzymes, a decrease in flexibility causes low enzyme activity while in less stable proteins such as mesophiles and psychrophiles, an increase in flexibility is associated with enhanced enzyme activity. Recently, we identified a mutant of a lipase whose stability and activity were enhanced simultaneously. In this work, we probed the conformational dynamics of the mutant and the wild type lipase, particularly flexibility of their active site using molecular dynamic simulations and time-resolved fluorescence techniques. In contrast to the earlier observations, our data show that active site of the mutant is more rigid than wild type enzyme. Further investigation suggests that this lipase needs minimal reorganization/flexibility of active site residues during its catalytic cycle. Molecular dynamic simulations suggest that catalytically competent active site geometry of the mutant is relatively more preserved than wild type lipase, which might have led to its higher enzyme activity. Our study implies that widely accepted positive correlation between conformation flexibility and enzyme activity need not be stringent and draws attention to the possibility that high enzyme activity can still be accomplished in a rigid active site and stable protein structures. This finding has a significant implication towards better understanding of involvement of dynamic motions in enzyme catalysis and enzyme engineering through mutations in active site. Understanding the relationship of enzyme conformational flexibility with its stability and activity is a very active area of research. Many studies comparing conformational flexibility of homologous thermophilic-mesophilic enzyme pairs, using various techniques like fluorescence quenching Bacillus subtilis, we created a very thermostable mutant named “6B” para-nitrophenyl acetate (PNPA) and para-nitrophenyl butyrate (PNPB). Comparative details of catalytic parameters of the two enzymes are given in By performing multiple rounds of directed evolution and mutation recombination on a lipase “lipA” from mesophilic bacterium et al. first solved the crystal structure of wild type B. subtilis lipase and identified the active site residues B. subtilis lipase follows two steps reaction, acylation and deacylation . To probe the flexibility of two molecules, data from all the three simulations were combined and the root mean square fluctuation (RMSF) for Cα atoms for all residues were compared for 2–20 ns MD runs  belongs to the global tumbling of protein molecule, hence was similar for both proteins (∼8.9 ns). However, faster rotational correlation time (фfast), representing sum of motional freedom of probe with respect to protein and segmental flexibility of local site (active site in present case), was different in two proteins. Its value is ∼0.21 ns in wild type while ∼4.05 ns in 6B. Lower value is due to faster depolarization which in turn represents higher flexibility of the local site. Furthermore, the amplitude associated with the faster correlation time is significantly smaller in 6B when compared to wild type indicating increased rigidity in 6B. Acrylodan anisotropic decay corroborates the MD simulation studies that active site of 6B lipase may be more rigid than wild type.We further probed the active site dynamics of wild type and 6B lipases by time-resolved fluorescence anisotropy measurement. This method has been widely used to probe the flexibility of macromolecules Our results from MD simulation and time-resolved fluorescence anisotropy decays suggest that active site of 6B lipase is more rigid than wild type lipase. This is in accordance with the prevailing idea of conformational stabilization being associated with increase in conformational rigidity. However, how a rigid active site can be capable of supporting higher enzyme activity? In any enzymatic reaction, even the simplest one substrate–one product ones, substrate goes through multiple geometric as well as electrostatic rearrangements during its chemical transformations. Correspondingly, for efficient catalysis, reorganization of enzyme active site is necessary so that it can change its shape to have complementarities with transforming chemical entity. Compelling need of dynamic fluctuations or flexibility for enzyme catalysis often originates from the simple fact that it bestows enzymes the capability of active site reorganization and allows it change its conformation during catalysis. However, relative level of active site reorganization during enzyme catalysis was shown to vary depending upon enzymes et al.B. subtilis lipase), using the quantum mechanical and molecular mechanical techniques, has shown that these enzymes require minimal reorganization in active site during catalysis. The active sites in these enzymes were found to have pre-organized geometry that largely minimizes conformational reorganization during catalysis. We compared the crystal structures of wild type B. sublilis lipase in free form and in complex with a phosphonate inhibitor, an analog of 1st tetrahedral transition state et al.As evident from Numerous studies have attempted to uncover the possible relationship of conformational dynamics to enzyme activity. Various techniques such as NMR, MD simulation and single-molecule fluorescence were used to probe dynamics of many enzymes like cyclophilin A, adenylate kinase, peptidylprolyl isomerase catalytic domain, dihydrofolate reductase and flavin reductase B. subtilis lipase suggest that increasing active site rigidity not necessarily decrease enzyme activity, rather as presented here, can be associated with increase in enzyme activity. It should be noted that in earlier reports of engineered enzymes which were both more stable and comparable/more active at room temperature than their parent molecule, most of the mutations were spread over regions of molecules which were away from active site B. subtilis lipase directly probed the dynamics of active site argues that stable version of lipase “6B” is not only structurally more stable and active than wild type protein, but its active site is also more rigid as postulated based on static crystal structures.Despite of conceptual ambiguity and contradictory reports on role of dynamics in enzyme catalysis, prevailing notion is for efficient catalysis enzymes need to acquire structures that are compatible with binding to cofactor, substrate and its various forms while undergoing chemical transformation in the active site. And conformational dynamics or flexibility plays the vital role of a lubricant helping enzymes to do so. This implies that decreasing flexibility or increasing rigidity decreases the enzyme activity, as shown previously by many studies In conclusion, our study provides the evidence that positive correlation between conformational flexibility and enzyme activity need not be stringent but active site rigidity and enzyme activity can be simultaneously increased. Interestingly, Gutteridge and Thornton All the lipase variants were over-expressed and purified following reported methodologies MD simulations and analysis were performed using GROMACS simulation package 391 in DMF = 20,000 M−1.cm−1) for >2 h in 50 mM sodium phosphate buffer (pH 7.2) at room temperature followed by extensive buffer exchange with same buffer in centrifugal filtering device . Percentage acrylodan labeling was calculated by measuring concentration of acrylodan  and total protein. >80% acrylodan labeling was achieved.50 µM (∼1 mg/ml) of S77C mutants of both wild type and 6B lipases was incubated with 250 µM of acrylodan (RIII) and 90° (I⊥).Time-resolved fluorescence experiments were performed using a Ti-Sapphire picoseconds laser and time-correlated single-photon counting setup, coupled to a micro-channel plate photomultiplier tube as described earlier I(t) is the fluorescence intensity at time t and αi is the amplitude of the ith lifetime iτ such that Σαi = 1. The mean lifetime mτ = Σαiτi.Time-resolved fluorescence intensity decays were analyzed by de-convolution of observed sample decays with the IRF to achieve the intensity decay function represented by,III (t) and I⊥ (t) asIII (t) and I⊥(t) are fluorescence intensity when emission polarizer was oriented at 0° (III) and 90° (I⊥) to the excitation beam. r(t), the anisotropic decay function was analyzed as a sum of two exponential terms,0 is the intrinsic (time zero) fluorescence anisotropy. φfast and φslow are fast and slow rotational correlation times associated with amplitudes βfast and βslow respectively such that βfast+βslow = 1.Time-resolved anisotropy decays were analyzed by globally fitting Text S1Information on time-resolved fluorescence intensity decay profiles of acrylodan and time-resolved fluorescence intensity as well as anisotropy decay of tryptophans.(DOC)Click here for additional data file.Figure S1Location of active site residues and mutations. Stereo figure for (TIF)Click here for additional data file.Figure S2A) RMSD of Cα atoms of wild type and 6B lipases from their energy minimized crystal structures in two simulations as a function of MD simulation time. (B) RMSF of all atoms of individual residue in 2–20 ns MD simulation time . Spheres denote active site residues.Active site dynamics by MD simulation. ((TIF)Click here for additional data file.Figure S3Far UC CD spectra of acrylodan labeled S77C mutant in wild type background and wild type lipase. Spectra were recorded in 0.1 cm pathlenght cuvette for 0.1 mg/ml proteins in 50 mM sodium phosphate buffer (pH 7.2) using a JASCO J-815 specropolarimeter. All reported spectra are an average of four accumulations. Wavelength scans were carried out in the Ellipticity mode at a scan speed of 50 nm/min, bandpass of 2 nm, at response time of 2 s and wavelength step of 0.5 nm. All spectra were corrected for buffer base line by subtracting the respective blank spectra recorded identically without the protein.(TIF)Click here for additional data file.Figure S4Typical time-resolved fluorescence intensity decay profiles of acrylodan attached to C77 in wild type and 6B lipase background.(TIF)Click here for additional data file.Figure S5A) intensity decay and (B) anisotropic decay profiles of tryptophans in wild type and 6B lipase.Time-resolved fluorescence of tryptophans. Typical time-resolved fluorescence ((TIF)Click here for additional data file.Figure S6Structural overlap of active site in free and transition state analog bound crystal structure of wild type lipase. Stereo figure for (TIF)Click here for additional data file.Figure S7Active site geometry during MD simulation. Frequency distribution of RMSD of catalytically important atoms  between MD structural snapshots (2–20 ns) of wild type and 6B lipase and respective free enzyme crystal structures .(TIF)Click here for additional data file.Table S1Parameters associated with time-resolved fluorescence measurements of acrylodan and tryptophans.(DOC)Click here for additional data file.