Deleterious alleles have long been proposed to play an important role in patterning phenotypic variation and are central to commonly held ideas explaining the hybrid vigor observed in the offspring of a cross between two inbred parents. We test these ideas using evolutionary measures of sequence conservation to ask whether incorporating information about putatively deleterious alleles can inform genomic selection (GS) models and improve phenotypic prediction. We measured a number of agronomic traits in both the inbred parents and hybrids of an elite maize partial diallel population and re-sequenced the parents of the population. Inbred elite maize lines vary for more than 350,000 putatively deleterious sites, but show a lower burden of such sites than a comparable set of traditional landraces. Our modeling reveals widespread evidence for incomplete dominance at these loci, and supports theoretical models that more damaging variants are usually more recessive. We identify haplotype blocks using an identity-by-decent (IBD) analysis and perform genomic prediction analyses in which we weigh blocks on the basis of complementation for segregating putatively deleterious variants. Cross-validation results show that incorporating sequence conservation in genomic selection improves prediction accuracy for grain yield and other fitness-related traits as well as heterosis for those traits. Our results provide empirical support for an important role for incomplete dominance of deleterious alleles in explaining heterosis and demonstrate the utility of incorporating functional annotation in phenotypic prediction and plant breeding. a priori prediction of deleterious alleles correlates well with effect sizes for grain yield and that variants predicted to be more damaging are on average more recessive. We develop a simple model allowing for variation in the heterozygous effects of deleterious mutations and demonstrate its improved ability to predict both phenotypes and hybrid vigor. Our results help reconcile alternative explanations for hybrid vigor and highlight the use of leveraging evolutionary history to facilitate breeding for crop improvement.A key long-term goal of biology is understanding the genetic basis of phenotypic variation. Although most new mutations are likely disadvantageous, their prevalence and importance in explaining patterns of phenotypic variation is controversial and not well understood. In this study we combine whole genome-sequencing and field evaluation of a maize mapping population to investigate the contribution of deleterious mutations to phenotype. We show that  Understanding the genetic basis of phenotypic variation is critical to many biological endeavors from human health to conservation and agriculture. Although most new mutations are likely deleterious , their iIn addition to its global agricultural importance, maize has long been an important genetic model system  and centModern maize agriculture takes advantage of hybrid maize plants that result from the cross between two parental inbred lines . These cIn this study, we set out to investigate the contribution of deleterious alleles to phenotypic variation and hybrid vigor in maize. We created a partial diallel population from 12 maize inbred lines which together represent much of the ancestry of present-day commercial U.S. corn hybrids , 30. We ha−1), with all observations taken from the inside two rows to minimize effects of shading and maturity differences from adjacent plots. We measured plant height , height of primary ear , days to 50% pollen shed (DTP), days to 50% silking (DTS), anthesis-silking interval , grain yield adjusted to 15.5% moisture , and test weight .We formed a partial diallel population from the F1 progeny of 12 inbred maize lines , S1 Fig.Yijkl is the phenotypic value of the lth genotype evaluated in the kth block of the jth replicate within the ith year; μ, the overall mean; iς, the fixed effect of the ith year; δij, the random effect of the jth replicate nested within the ith year; βkij, the random effect of the kth block nested within the ith year and jth replicate; αl, the fixed genetic effect of the lth individual; iς · lα, the random interaction effect of the lth individual with the ith year; and ε, the model residuals. We calculated the broad sense heritability (H2) of traits based on the analysis of all individuals  following the equation:i = 3 (number of years) and j = 3 (number of replicates per year).We estimated Best Linear Unbiased Estimates (BLUEs) of the genetic effects in ASReml-R  with the following linear mixed model:P values >0.05, r = 0.98 for DTS and DTP, The BLUE values for each cross can be found in i and j. Note that for ASI, lower trait values are considered superior. General combining ability (GCA) was estimated following Falconer and Mackay [We estimated mid-parent heterosis (MPH) as:d Mackay , and theWe extracted DNA from the 12 inbred lines following  and sheahttps://github.com/vsbuffalo/scythe) and for quality and sequence length (≥20 nucleotides) with Sickle (https://github.com/najoshi/sickle). We mapped filtered reads to the maize B73 reference genome (AGPv2) with bwa-mem [We trimmed raw sequence reads for adapter contamination with Scythe . Because these parents are highly inbred, knowing their homozygous genotype also allows us to know the genotype of the F1 derived from any two of the parents.We called single nucleotide polymorphisms (SNPs) using the samtools . To dealsamtools , SNPs wesamtools ; for allsamtools ; and forsamtools . Alignmewww.panzea.org)) obtained from alignments to a set of sequencing reads ascertained from a broad germplasm base [r = 0.995), suggesting the degree of relatedness among lines is not sensitive to using B73 as the reference genome.To test whether alignment to the B73 reference introduces a bias in relatedness estimation, we computed kinship matrices using both our SNP data as well as genotyping-by-sequencing data . We define “GERP-SNPs” as the subset of SNPs with GERP score >0, and at each SNP we assign the minor allele in the multi-species alignment as the likely deleterious allele. Finally, we predicted the functional consequences of GERP-SNPs based on genome annotation information obtained from SnpEff [http://ensembl.gramene.org/Zea_mays/Tools/AssemblyConverter?db=core).We used genomic evolutionary rate profiling (GERP)  estimatem SnpEff . The mulhttp://www.panzea.org/) and allele frequencies from the > 1,200 maize lines sequenced as part of HapMap3.2 [To compare GERP scores  to recombination rate and allele frequencies, we obtained the NAM genetic map  from theapMap3.2 . To compapMap3.2  for moreYi is the BLUE value of the ith hybrid, μ is the average genotypic value, αj is the allele substitution effect of the jth GERP-SNP, dj is the dominant effect of the jth GERP-SNP, Xij = {2p, 2p − 1, 2p − 2}, ε is the model residuals, and Wij = {−2p2, 2p(1 − p), −2(1 − p)2} are the genotype encodings for genotypes A1A1, A1A2, and A2A2 in the ith hybrid for the jth GERP-SNP with p of the A1 allele.We estimated the additive and dominant effects of individual GERP-SNPs using a GBLUP model  implemena = α − 2p(1 − p)d) and dominant (d) effects from the GVCBLUP output file  or complete dominance (α = 0). Then, to assess correlations between SNP effects and GERP scores, we calculated the degree of dominance (k = d/a) [k, we truncated GERP-SNPs with |k = d/a|>2 for all further analyses.The additive and dominance SNP encoding ensures that the effects are independent for a given GERP-SNP. We extracted additive   for SNPsTo compare the variance explained by our model to that explained by random SNPs, we used a 2-dimensional sampling approach to create 10 equal-sized datasets of randomly sampled SNPs (including SNPs with GERP score < = 0) matched for allele frequency (in bins of 10%) and recombination rate (in quartiles of cM/Mb). For each dataset we fit the above model separately and estimated SNP effects and phenotypic variance explained by each SNP.s by assuming that yield is a measure of fitness. We assigned the yield-increasing allele at each GERP-SNP a random dominance value in the range of 0 ≥ k ≥ 1 and calculated its equilibrium allele frequency p under mutation-selection balance using k > 0.98 and k ≤ 0.98. We then simulated datasets using binomial sampling to choose SNPs in a sample of size n = 12 inbreds.To test the relationship between GERP score and dominance under a simple model of mutation-selection equilibrium, we estimated the selection coefficient We imputed missing data and identified regions of identity by descent (IBD) between the 12 inbred lines using the fastIBD method implemented in BEAGLE . We thenhttps://github.com/yangjl/zmSNPtools); blocks with no SNPs with positive GERP scores were excluded from further analysis. For a particular SNP with a GERP score g, the homozygote for the conserved (major) allele was assigned a value of 0, the homozygote for the putatively deleterious allele a value of 2g, and the heterozygote a value of (1 + k) × g, where k is the dominance estimated from the GBLUP model above.Because there is no recombination in an inbred parent, this allows us to project the diploid genotype of each F1 based on the haplotypes of the two parents. In the projected diploid genotype of each F1, haplotype blocks were weighted by the summed GERP scores of all GERP-SNPs  and validation sets (20%) 100 times. After model training, we obtained prediction accuracies by comparing the predicted breeding values with the observed BLUE values in the corresponding validation sets. For comparison, we permuted GERP scores using 50k SNP (≈ 100Mb or larger) windows which were circularly shuffled 10 times to estimate a null conservation score for each IBD block. We conducted permutations on all GERP-SNPs as well as on a restricted set of GERP-SNPs only in genic regions to control for GERP differences between genic  and intergenic regions . We conducted permutation cross-validation experiments using the same training and validation sets.r) used for the cross-validation experiments, where the latter is defined as the correlation between real and estimated values; the two statistics will converge to the same value when there is no error in SNP/haplotype effect estimation [We estimated the posterior phenotypic variance explained using all of the data to derive correlations between breeding values estimated from the prediction model and observed BLUE values. Note that the correlation used here is different from the prediction accuracy .Sequencing data have been deposited in NCBI SRA (SRP103329) database, and code for all analyses are available in the public GitHub repository  of its phenotype from mixed linear models  to contra priori, we made use of Genomic Evolutionary Rate Profiling (GERP) [We resequenced the 12 inbred parents to an average depth of ≈ 10×, resulting in a filtered set of 13.8M SNPs. Compared to corresponding SNPs identified by previous studies see , we obseg (GERP)  scores og (GERP) . GERP scg (GERP) . Sites wTo compare the burden of deleterious variants between our elite maize lines and traditionally cultivated landraces, we used genotypes from the maize HapMap3.2  for our Population genetic theory predicts that deleterious variants should be at low overall frequencies, and that such variants should be enriched in regions of the genome with extremely low recombination . Using dper se , from ≈ 0 for flowering time traits to as much as 24% for grain yield   modelingllel see . GERP-SNllel see . We founin yield . Distribk=da see  across tk=da see  and matck) for grain yield .We then evaluated the relationship between GERP score and SNP effect size, dominance, and contribution to phenotypic variance. We found weak or negligible correlations between effect size and GERP score for flowering time and grain quality, but a strong positive correlation for fitness-related traits . The varin yield , such thWe investigated a number of possible caveats to the results presented in a priori as putatively deleterious, we implemented a genomic prediction model that evaluates complementation at the haplotype level by incorporating GERP scores of individual SNPs as weights (see k) estimated from our GBLUP model explained a greater amount of the posterior phenotypic variance for most traits per se .et al. [et al. find no evidence for hitch-hiking associated with selective sweeps during domestication, and the differences we observe in the burden of deleterious variants closely mimic results from simulations of partially recessive deleterious alleles in populations that have recently undergone demographic bottlenecks, but no additional selection [Using GERP scores as a proxy for deleterious alleles, we then ask whether our elite maize inbreds show an increased burden of deleterious alleles compared to a set of traditional landrace varieties. We find that modern inbreds are characterized by an increase in the proportion of deleterious variants fixed within the population , consistet al. , supportelection .We next use the set of SNPs with GERP > 0 scores (or GERP-SNPs) to investigate the phenotypic effects of deleterious variants. Across phenotypes, our results largely mirror previous work, finding that dominance contributes substantially to grain yield  while trWe also find that more strongly deleterious alleles (those with higher GERP score and a larger negative effect on yield) are more likely to be recessive for grain yield. Such a genome-wide relationship between dominance and fitness has not been well demonstrated in other multicellular organisms, but supports previous empirical evidence from gene knockouts in yeast , 63. Thiet al., [After showing that GERP-SNPs explain a substantial portion of the observed phenotypic variation when combined with our estimates of dominance and effect size, we more rigorously test the direct utility of GERP scores using cross-validation prediction methods. We show that for both plant height and grain yield, our GERP-enabled prediction model has significantly improved accuracy compared to randomized data, even when only considering SNPs within genes . As genoet al.,  for a reet al., , and ourper se among hybrids [et al., [et al., [Finally, our results also have implications for understanding the genetic basis of heterosis. We observed substantial heterosis for a number of traits in our diallel , includi hybrids . We argu hybrids . Combine hybrids  Fig 1d)per se am hybrids , 53, enr hybrids , and eve[et al.,  and Huan[et al., ), but wein silico enables us to predict grain yield and other traits, including heterosis, with greater accuracy. Together, these results help reconcile alternative explanations for hybrid vigor and point to the utility of leveraging evolutionary history to facilitate breeding for crop improvement.In this study, we use genomic and phenotypic data from a partial diallel population of maize to show that an incomplete dominance model of deleterious mutation both fits predictions of population genetic theory and explains phenotypic variation for fitness-related phenotypes and hybrid vigor. We find genome-wide support for hypotheses predicting that more damaging variants are more recessive. Finally, we show that leveraging evolutionary annotation information S1 Figa) Twelve maize inbred lines were selected and crossed in a half-diallel fashion. Each inbred lines was used as both male and female and the resulting F1 seed was bulked. (b) Density plots of normalized BLUE values for the seven phenotypic traits. We used the “scale” function in R to normalize the BLUE values by first centering on zero and then dividing the numbers by their standard deviation. The seven phenotypic traits are plant height (PHT), height of primary ear (EHT), days to 50% pollen shed (DTP), days to 50% silking (DTS), anthesis-silking interval (ASI), grain yield adjusted to 15.5% moisture (GY), and test weight (TW).((PDF)Click here for additional data file.S2 Figr) and the asterisks (*) indicate the correlation coefficients are statistically significant . Units for various traits are plant height , height of primary ear , days to 50% pollen shed (DTP), days to 50% silking (DTS), anthesis-silking interval , grain yield adjusted to 15.5% moisture , and test weight .The upper right panels show the scatter plots of all possible pairwise comparisons of two traits. The red line is a fitted loess curve. In the lower left panels, the numbers are the Spearman correlation coefficients ((PDF)Click here for additional data file.S3 FigIn the upper panel, regions in red are IBD blocks identified by pairwise comparison of the two parental lines of a hybrid. The vertical dashed lines define haplotype blocks. In the lower panel, hybrid genotypes in each block are coded as heterozygotes (0) or homozygotes (1).(PDF)Click here for additional data file.S4 FigRed solid and grey dashed lines define the best-fit regression line and its 95% confidence interval.(PDF)Click here for additional data file.S5 Figots indicate mean GERP scores of putatively deleterious SNPs (GERP scores > 0) carried by the 12 parental maize lines (bin size = 1 cM). Vertical red lines indicate centromeres.(PDF)Click here for additional data file.S6 FigAdditive and dominance effects are indicated by red and blue colors respectively.(PDF)Click here for additional data file.S7 Figk) in each trait. Red lines show the phenotypic variance explained using the observed k.Histograms show the results for the randomly shuffled (10 times) degrees of dominance ((PDF)Click here for additional data file.S8 FigSolid and dashed lines represent significant and non-significant linear regressions, with grey bands representing 95% confidence intervals. Data are only shown for SNPs which explain more phenotypic variance than the genome-wide mean.(PDF)Click here for additional data file.S9 FigSolid and dashed lines represent significant and non-significant linear regressions, with grey bands representing 95% confidence intervals. Data are only shown for GERP-SNPs which explain more variance than the genome-wide mean and found in regions above the first quantile of the recombination rate (cM/Mb).(PDF)Click here for additional data file.S10 Fig(a) Total per-SNP variance explained for grain yield per se by deleterious (red lines) and randomly sampled SNPs (grey beanplots). (b) Density plots of the degree of dominance (k). Extreme values of k were truncated at 2 and -2 for visualization. (c-e) Linear regressions of additive effects (c), dominance effects (d), and degree of dominance (e) of seven traits per se against SNP GERP scores. Colors in (c-e) are the same as the legend for (b). Solid and dashed lines represent significant and nonsignificant linear regressions, with grey bands representing 95% confidence intervals. Data are only shown for deleterious alleles that explain more variance than the genome-wide mean.(PDF)Click here for additional data file.S11 FigThe solid blue line indicates the regression line fitted to data simulated under mutation-selection balance (see (PNG)Click here for additional data file.S12 Figper se  and heterosis  under additive , dominance , and incomplete dominance  models. Prediction accuracy using real data is shown on the left (green) and permutation results on the right (grey). Horizontal bars indicate mean accuracy and the grey dashed lines indicate the overall mean accuracy. Stars indicate real data having significantly  higher cross-validation accuracy than permuted data.Beanplots represent prediction accuracy estimated from cross-validation experiments for traits (PDF)Click here for additional data file.S13 Figper se  and heterosis  under additive  and dominance  models. Prediction accuracy using real data is shown on the left (red) and permutation results on the right (grey). Horizontal bars indicate mean accuracy of each trait and the grey dashed lines indicate the mean accuracy of all traits. Stars indicate real data having significantly  higher cross-validation accuracy than permuted data.Beanplots represent prediction accuracy estimated from cross-validation experiments for traits (PDF)Click here for additional data file.S14 FigEach line represents the posterior breeding values of a diploid hybrid (red circle), its best parent (black diamond), and predicted breeding values of simulated AAB triploid (blue square) and ABB triploid (green triangle) plants based on estimated effect sizes and dominance values for each SNP.(PDF)Click here for additional data file.S1 TableAbbreviations for phenotypic traits are plant height , height of primary ear , days to 50% pollen shed (DTP), days to 50% silking (DTS), anthesis-silking interval , grain yield adjusted to 15.5% moisture , and test weight .(CSV)Click here for additional data file.S2 Table(CSV)Click here for additional data file.S3 Table(CSV)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(CSV)Click here for additional data file.S6 Table(CSV)Click here for additional data file.S7 Table(CSV)Click here for additional data file.S8 Table(CSV)Click here for additional data file.


To date hiPSC-CMs used for cardiotoxicity testing display an immature, fetal-like cardiomyocyte structural and electrophysiological phenotype which has called into question the applicability of hiPSC-CM findings to the adult heart. The aim of the current work was to determine the effect of cardiomyocyte maturation state on hiPSC-CM drug responsiveness. To this end, here we developed a high content pro-arrhythmia screening platform consisting of either fetal-like or mature hiPSC-CM monolayers. Compounds tested in the screen were selected based on the pro-arrhythmia risk classification  established recently by the FDA and major stakeholders in the Drug Discovery field for the validation of the Comprehensive In vitro Pro-Arrhythmia Assay (CiPA). Here we show that maturation state of hiPSC-CMs determines the absolute pro-arrhythmia risk score calculated for these compounds. Thus, the maturation state of hiPSC-CMs should be considered prior to pro-arrhythmia and cardiotoxicity screening in drug discovery programs.Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) offer a novel  The S7B ICH guidelines put emphasis on screening compounds early in drug development for IKr current blockade using heterologous cells that overexpress just the hERG (Kv11.1) potassium channel. Although these guidelines have prevented potentially arrhythmogenic drugs from entering the market, the emphasis on the single ion channel  assay without consideration of the integrated multi-channel nature of the human cardiac cell and action potential has most likely led to falsely labelling safe and effective drugs as pro-arrhythmic2. Mislabeling compounds in early development phases of drug discovery has led to cessation of development of potentially safe and effective drugs, and thus the pharmaceutical industry and patients are missing out on opportunities for new therapies3. False positive findings for cardiotoxicity and proarrhythmia liability of novel drug candidates may also be due to discordance between a compound’s effects in animals and animal cells compared to those in humans4. Ideally pre-clinical cardiotoxicity and pro-arrhythmia screening should be determined using human cardiomyocytes or mechanically and electrically syncytial monolayers of human cardiomyocytes. Alternatively human cardiomyocytes can also be used to form 3-dimensional (3D) tissues6 and the addition of non-myocyte cells in 3D bioengineered human cardiac tissues has been shown to promote more natural growth and maturation7.Over the last decade the International Conference on Harmonization’s (ICH) guideline has dictated the type of pre-clinical 10. The evolving human based approach for pre-clinical cardiotoxicity is called the Comprehensive in vitro Proarrhythmia Assay (CiPA for short). Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) are central to CiPA as a human model system that may be used in place of the standard hERG assay for pre-clinical cardiotoxicity testing13. hiPSC-CMs can be generated in nearly unlimited quantities, can be cryopreserved and are now offered by several commercial vendors16. Importantly hiPSC-CMs possess the complex array of ion channels that make up the cardiac action potential, which offers a naturally integrated system with advantages over heterologous cell systems in which a single ion channel is tested13. Moreover, human stem cell derived cardiomyocytes can be used to form electrically coupled syncytia of monolayers that can be used to quantify electrical impulse propagation and study mechanisms of re-entrant arrhythmias18.Human based pre-clinical cardiotoxicity approaches are currently being developed and validated via collaboration between academic laboratories, federal regulatory agencies and the pharmaceutical industry21. Recent publications have relied on extracellular matrix hardness to mature the phenotype of single hiPSC-CMs and purified monolayers of hiPSC-CMs22. Yet, the impact that maturation state of hiPSC-CMs has on responsiveness to drug compounds us unclear. Recently we showed that the maturation state of hiPSC-CMs impacts on the ion channel expression profile and electrophysiological phenotype of human cardiac monolayers22. Extracellular matrix mediated maturation of hiPSC-CM monolayers significantly induced expression of mature cardiomyocyte markers including cardiac specific troponin I (cTnI), sodium channel (NaV1.5), inward rectifier potassium channel (Kir2.1) and connexin43 (Cx43). Furthermore, extracellular matrix mediated maturation induced functionally mature hiPSC-CM monolayers with rapid impulse propagation velocity (up to 50 cm/s), rapid action potential upstroke (up to ~150 V/s) and hyperpolarized resting membrane potential (−78 mV). In the current study we have applied extracellular matrix mediated maturation of hiPSC-CM monolayers plated in 96-well plates for high throughput assessment of drug effects on action potential duration using spontaneously beating and electrically paced preparations. Here we generated customized 96-well plates in which half of the monolayers were fetal-like and the other half were mature hiPSC-CMs , intermediate risk  or high risk  for causing Torsade de Pointes (TdP) we determined the effect of maturation state on hiPSC-CM monolayer responsiveness. Results indicate that the maturation state of hiPSC-CM monolayers influences the electrophysiological responsiveness and thus should be considered when using hiPSC-CMs as part of CiPA for drug discovery projects.However a limitation of the current state of the field involves the maturity of hiPSC-CMs) were generated essentially as before22. PDMS vulcanized silicone transparent sheeting was obtained from SMI  with 40D  hardness and 9 mm diameter coverslips were cut out to fit in each well of 96 well plates. PDMS coverslips were manually added to each well of 96 well plates (Corning) and each plate was subsequently sterilized via ethylene oxide sterilization. PDMS coverslips were then matrigel-coated  prior to plating hiPSC-CMs. Thawing and plating of cryopreserved vials of cells into 96-well plates was as essentially described before22. Briefly, 5 × 104 cells were plated per well and allowed to form continuous monolayers and maintained in RPMI (Life Technologies) media supplemented with B27 + insulin (Life Technologies). Monolayers were maintained in culture for seven days before electrophysiological testing. Immature fetal-like hiPSC-CM monolayers were generated in 96 well plates without the PDMS coverslip inserts. Fetal-like hiPSC-CMs were also plated on matrigel coated plastic bottoms.hiPSC-CMs were used from two different commercial sources: Cellular Dynamics International  and Cellartis (Takara Bio USA). Custom made 96-well plates with inserts of PDMS  and ventricular myosin light chain 2  shown in Fig. Confluent monolayer formation was monitored and confirmed using time-lapse microscopy . Figure 23. Pluripotent stem cell experiments were performed with approval of the HPSCRO (Human Pluripotent Stem Cell Research Oversight Committee) of the University of Michigan. iPSCs were maintained in feeder free conditions (on matrigel) in xeno-free iPS Brew Media  with manual marking and picking to remove spontaneous differentiation. Cardiac directed differentiation was performed as previously described using the small molecule based approach now commonly referred to as the GiWi protocol24. Briefly, pure hiPSCs were singularized using versene, plated as monolayers in 6 well plates (1 × 106 hiPSCs/well) and maintained in stem cell media until reaching ~95% confluence. On day 0 of this protocol cardiac directed differentiation was initiated by culturing stem cell monolayers in RPMI media supplemented with B27 (-insulin) and the glycogen synthase kinase-3 inhibitor CHIR99021 (12 µM). On day 1 CHIR99021 was removed and cells are cultured in RPMI with B27 (-insulin) until day 3. On day 3 the small molecule Wnt inhibitor IWP4 (5 µM) was added to the cells and not removed until day 5. Days 5–7 the cells are maintained in RPMI with B27 (-insulin). On day 7 the RPMI media was supplemented with B27+ insulin and maintained in this media with daily changes until day 30. On day 30 of directed differentiation cell cultures were trypsinized and cardiomyocytes were purified using magnetic activated cell sorting to target and deplete non-myocytes from the cell population which resulted in cardiomyocytes enriched to ~98% purity . Purified hiPSC-CMs were plated in 96-well plates for maturation as described above for commercially available cell lines.In parallel experiments purified hiPSC-CM monolayers were generated in our laboratory using the established BJ-iPSC line, which was derived using mRNA reprogramming22 with slight modification. A schematic of the 96-well plate optical mapping set up is shown in supplemental Fig. 25 with automated peak detection capability and automated repolarization quantification to determine APD80 . Supplemental Fig. Optical mapping was performed as essentially described recentlyCompounds were obtained from the SCREEN-WELL® Cardiotoxicity library  or through Sigma. Compounds obtained from the SCREEN-WELL® library  were diluted in DMSO as 10 mM stock and serially diluted to the indicated concentrations in HBSS . Compounds not on the CiPA list, including amiodarone, nilotinib and doxorubicin also were part of the SCREEN-WELL® Cardiotoxicity library and were handled in the same way. Fluoxetine was obtained from Sigma (fluoxetine HCl-F132) and was diluted in DMSO to make 10 mM stock, then further diluted in HBSS at the indicated concentrations for screening experiments. On the day of experimentation maintenance media was removed from the monolayers, which then were loaded with FluoVolt (per manufacturer protocol in HBSS) and subsequently treated with test compounds diluted in HBSS for 30 min prior to action potential data acquisition. Action potentials were recorded in the presence of each test compound.22 mature hiPSC-CMs were larger in cross-sectional area  and also had evidence of bi-nucleation compared to fetal-like hiPSC-CMs 22. Myofilament markers of mature ventricular cardiomyocytes (β-MyHC and MLC2v) were elevated in mature hiPSC-CM monolayers . However, 10.0 µmol L−1 fluoxetine caused quiescence in 100% of fetal-like monolayers tested (8/8). This finding is consistent with a recent report using immature hiPSC-CM monolayers which showed no effect of fluoxetine to prolong the action potential duration, but quiescence at high dose. On the other hand, fluoxetine prolonged the action potential duration in mature monolayers even at the lowest concentration (1.0 nmol L−1), slowed the spontaneous beating rate and did not induce quiescence at any concentration tested. Thus, unlike other compounds tested mature hiPSC-CM monolayers are more sensitive to the effects of fluoxetine to prolong the action potential duration than immature monolayers, although fetal-like monolayers’ electrophysiological function was completely inhibited at the highest concentration.Fluoxetine is a compound with hERG channel blocking effectsTerfenadine is an antihistamine compound that also blocks the hERG channel Terfenadine is classified as a compound with intermediate risk to cause QT prolongation of the human ECG. Supplemental Figure Nilotinib is an anti-cancer kinase inhibitor compound with possible side effects to prolong the QT interval. We tested the effect of nilotinib on hiPSC-CMs and the results are presented in Figs 31. It is a compound with complex multi-channel blocking effects including inward as well as outward currents32. Shown in Table Amiodarone is an anti-arrhythmic compound used to treat arrhythmias like ventricular tachycardia and atrial fibrillation due to its effect to prolong the action potential duration80 of hiPSC-CM monolayers was quantified relative to vehicle control values obtained in each plate. In other words, the APD80 or CaTD80 quantified at each concentration of each compound was divided by the APD80 or CaTD80 quantified for vehicle control wells. Risk score values for each compound are presented in Table The effect of each compound to prolong or shorten the APDIn summary the results of this study show the impact of maturation state of hiPSC-CMs on drug compound responsiveness. Fetal-like hiPSC-CMs appear to be more sensitive to compounds considered to be of intermediate or high risk for causing pro-arrhythmia and APD prolongation. The maturation state of hiPSC-CMs is important to consider when using these cells for pre-clinical pro-arrhythmia and cardiotoxicity screening in drug discovery programs. Furthermore, we have presented a new method for dictating the functional and structural maturation state of hiPSC-CM monolayers. Using this approach, it is possible to test a compound’s effects on either fetal-like or mature human cardiomyocytes and this may add value to pre-clinical toxicity screening by providing a comprehensive examination of drug effects on varying developmental cardiac phenotypes .E-4031 is the only compound tested in which a full concentration curve was generated and fit to a sigmoidal curve, this was the only compound that yielded a maximal effect at the concentrations tested. The other compounds tested at concentrations up to 10 µM did not reach a maximal effect in all cases; this maximal concentration is well above the EC50 concentration for all compounds used in pre-clinical pro-arrhythmia testing. Nevertheless, these concentrations were sufficient to determine effectiveness of the platform to detect action potential prolongation, a surrogate for pro-arrhythmia. Also, comparison with human adult cardiomyocytes obtained from fully formed human hearts would be an ideal comparator for maturation; however adult human cardiomyocytes are not readily available for high throughput screens and are not amenable to formation of electrically coupled monolayers for determination of drug induced pro-arrhythmia. Furthermore, human adult cardiomyocytes are not readily available for study and the viability of these cardiomyocytes isolated typically from transplant or cadaveric hearts is notoriously low.Supplementary Information


ACPT, the gene encoding acid phosphatase, testicular, which segregates with hypoplastic amelogenesis imperfecta in two unrelated families. ACPT is reported to play a role in odontoblast differentiation and mineralisation by supplying phosphate during dentine formation. Analysis by computerised tomography and scanning electron microscopy of a primary molar tooth from an individual homozygous for the c.746C>T variant revealed an enamel layer that was hypoplastic, but mineralised with prismatic architecture. These findings implicate variants in ACPT as a cause of early failure of amelogenesis during the secretory phase.We identified two homozygous missense variants  and c.746C>T, p.(P249L)) in  This results in enamel that is over 95% mineral by weight,1 much higher than dentine (70%) or bone (65%).2Amelogenesis, the formation of enamel, involves the secretion of a proteinaceous enamel matrix by ameloblasts. Progressive mineralisation follows through a series of repeated, cyclical processes that break down and remove matrix protein while simultaneously facilitating the growth of calcium hydroxyapatite crystallites.3 Different forms of AI exist. Insufficient or absent matrix secretion causes hypoplastic AI with thin and variably mineralised enamel. Defects during the maturation stage result in hypomineralised AI, where enamel is of full thickness but weak. AI may occur in isolation or as part of syndromic conditions.Amelogenesis imperfecta (AI) describes a group of inherited conditions characterised by defective amelogenesis, with a prevalence reported as high as 1 in 700.AMELX (MIM*300391), AMBN (MIM*610259) and ENAM (MIM*606585)), enamel proteases (MMP20 (MIM*604629) and KLK4 (MIM*603767)), cell adhesion proteins (LAMA3 (MIM*600805), LAMB3 (MIM*150310), COL17A1 (MIM*113811), FAM83H (MIM*611927) and ITGB6 (MIM*147558)), endocytosis proteins (WDR72 (MIM*613214)), calcium transport proteins (SLC24A4 (MIM*609840)) and pH sensors (GPR68 (MIM*601404)).4 In addition, variants have been identified in C4orf26 (MIM*614829), AMTN (MIM*610912)5 and FAM20A (MIM*611062), encoding proteins for which functions are less clear.Variants in many genes have been implicated in both non-syndromic and syndromic AI to date. These include genes encoding enamel matrix proteins  causing recessive hypoplastic AI in two families.Here we report the identification of two different homozygous missense variants in testicular acid phosphatase See Two consanguineous UK Pakistani families segregating autosomal recessive rough, but hard hypoplastic AI  were asc7 As both probands were from first cousin unions, only biallelic, homozygous variants within autozygous regions  variant in exon 7 predicted to lead to a missense change, p.(P249L) (NP_149059.1). In family 2, a homozygous c.428C>T variant was identified in exon 4, also predicted to lead to a missense change p.(T143M). Sanger sequencing confirmed the  members .ACPT variants are predicted to affect function by a number of different algorithms (8 the Exome Variant Server (http://evs.gs.washington.edu/EVS/) and the ExAC database (v0.3). The c.428C>T, p.(T143M) variant was identified in ExAC in 9 out of 89 042 alleles and has been assigned rs546603773 with 0.02% MAF in dbSNP146 . P249 is predicted to form a twist between two alpha helices (Swissmodel Q9BZG2), and substitution of a rigid proline at position 249 with the much larger leucine (BLOSUM62 score −3) is likely to influence the structure of the active site by disrupting that twist.Comparison of ACPT protein sequences in mammals, and of related human proteins lysosomal acid phosphatase 2  and prostatic acid phosphatase  , reveals3 and was comparable to control enamel. The underlying dentine of the tooth from individual IV:3 was mildly hypermineralised with respect to the dentine of the control tooth. Scanning electron microscopy (SEM) showed that control enamel consisted of the typical prismatic architecture (μm) compared to that of the control tooth (around 800 μm). The enamel that was present for the tooth from individual IV:3 appeared to have a prismatic-like architecture, which was more defined nearer to the EDJ  of this 426 amino-acid protein and all give rise to the same distinctive form of AI.The 10 It is expressed by secretory, but not maturation stage ameloblasts,9 but the function of ACPT during amelogenesis remains unclear. It has been suggested that it elicits odontoblast differentiation and mineralisation by supplying phosphate during dentine formation.11 It is also expressed in the brain, where it may be important for neuronal development and synaptic plasticity.12 Examination of the tooth from family 1 individual IV:3 showed that the dentine appeared to be hypermineralised in comparison to that of the control tooth, although no dentine abnormalities were identified upon clinical examination and intraoral dental radiographs. There was also no clinical information to suggest bone involvement, although no formal assessment of the bone phenotype was made. Further analysis of other teeth from individuals with homozygous variants in ACPT will be required to assess whether the enamel and dentine findings observed through CT and SEM analysis are typical for individuals with homozygous ACPT variants. There was also no clinical information to suggest bone involvement, although no formal assessment of the bone phenotype was made.Examination of an extracted primary molar tooth by CT and SEM revealed that the enamel was hypoplastic but similarly mineralised in comparison to control enamel. ACPT is one of a group of enzymes capable of hydrolysing esters of orthophosphoric acid in acidic conditions.ACPT AI variants reported to date are missense variants (ACPT, or with missense variants affecting other ACPT domains. Interrogation of the ExAC database for variants predicted to lead to loss of ACPT function showed that only heterozygous individuals had been identified for each of the 22 variants observed. This may suggest that ACPT has other important functions and that while missense variants result in AI, homozygous loss of function may be embryonic lethal.The finding that defects in ACPT cause hypoplastic AI is consistent with an essential role for ACPT in the secretory phase of amelogenesis. It is perhaps surprising, given its important role in other tissues, that ACPT defects do not cause syndromic disease. The fact that all variants  may sugg11 Choi et al.11 utilised an antibody to block extracellular ACPT domain function and found that odontoblast differentiation was inhibited but proliferation was unaffected. There are no current data to suggest dentinogenesis is significantly affected with homozygous ACPT variants.ACPT may be involved in switching odontoblast proliferation to differentiation via beta catenin signalling inhibition, and in dentine mineralisation via production of phosphate and activation of tissue non-specific alkaline phosphatase.ACPT cause rough, hard hypoplastic AI, demonstrating an essential role for this protein in the secretory phase of amelogenesis.In summary, we independently discover that missense variants in the extracellular domain of


Basement membranes (BMs) are specialized extracellular scaffolds that provide architecture and modulate cell behaviors in tissues, such as fat, muscle, endothelium, endometrium, and decidua. Properties of BMs are maintained in homeostasis for most adult tissues. However, BM ultrastructure, composition, and localization are rapidly altered in select uterine tissues that are reprogrammed during pregnancy to enable early maternal-embryo interactions. Here, our data exhibit both static and dynamic BMs that were tracked in mouse uterine tissues during pre-, peri-, and postimplantation periods of pregnancy. The data exhibit spatial-temporal patterns of BM property regulation that coincide with the progression of adapted physiology. Further interpretation and discussion of these data in this article are described in the associated research article titled, “Embryo implantation triggers dynamic spatiotemporal expression of the basement membrane toolkit during uterine reprogramming”   Specifications TableValue of the data•These data of H&E stainings and schematics are useful for researchers interested in tissue and cellular-level histological changes that occur in mouse uterine tissues during early pregnancy.•The presented electron micrographs provide a context of cells and basement membrane for interpretation of cell–matrix and cell–cell orientation and interactions.•The immunofluorescence data include entire cross-sections through uterine tissues that allow comparative analysis of dynamic and homeostatic localization of basement membrane components during pregnancy.•The positive and negative control data provide evidence of immunofluorescence detection specificity and are informative to researchers that apply the same antibodies in future experiments.1The data in this article include hematoxylin and eosin (H&E) histological visualization of uterine tissue changes that naturally occur during early mouse pregnancy . A schem22.1Healthy adult CD1 mice , Wilmington, MA, USA) were bred and the presence of a vaginal plug the following morning was established as day 1 of pregnancy 2.2Uterine samples were embedded in Optimal Cutting Temperature (OCT) compound , cryosectioned , and collected onto slides . Samples were processed and stained with hematoxylin and eosin (H&E) using routine methods at the Vanderbilt University Medical Center Translational Pathology Shared Resource . Briefly, samples were carefully acclimated to room temperature, washed with phosphate-buffered saline (PBS) for 3 min to remove OCT, fixed with 10% neutral buffered formalin for 3 min, and rinsed with running water. Staining was carried out by incubating in hematoxylin and then eosin by dipping 15 times in each dye, rinsing with running water between dyes. Sections were then dehydrated in 3 exchanges of ethanol and 2 exchanges of xylene and mounted in non-aqueous media with a coverslip.Cryosections processed for immunofluorescence were air-dried and fixed in −20 °C acetone  then were washed several times with phosphate-buffered saline (PBS)  and PBS with 0.2% Tween . Nonspecific binding was blocked by incubation of samples with 10% normal goat or horse serum . All antibodies were diluted in PBS/0.1% Tween with 5% goat serum. The following primary antibodies were applied to the sections: rat anti-collagen IV NC1 . Then samples were cured The authors declare no conflicts of interest.


Cellular signaling systems precisely transmit information in the presence of molecular noise while retaining flexibility to accommodate the needs of individual cells. To understand design principles underlying such versatile signaling, we analyzed the response of the tumor suppressor p53 to varying levels of DNA damage in hundreds of individual cells and observed a switch between distinct signaling modes characterized by isolated pulses and sustained oscillations of p53 accumulation. Guided by dynamic systems theory we show that this requires an excitable network structure comprising positive feedback and provide experimental evidence for its molecular identity. The resulting data-driven model reproduced all features of measured signaling responses and is sufficient to explain their heterogeneity in individual cells. We present evidence that heterogeneity in the levels of the feedback regulator Wip1 sets cell-specific thresholds for p53 activation, providing means to modulate its response through interacting signaling pathways. Our results demonstrate how excitable signaling networks can provide high specificity, sensitivity and robustness while retaining unique possibilities to adjust their function to the physiology of individual cells. To ensure reliable information processing, cellular signaling systems need to faithfully sense inputs in noisy environments while maintaining the flexibility to adjust their function to different physiologies. A commonly observed strategy to enable robust signal detection is the pulsed activation of signaling pathways in a digital-like responseA well-known example of a pulsatile signaling pathway in mammalian cells is the tumor suppressor p53. As a central hub of the cellular stress response, p53 maintains genomic integrity in proliferating cells and during tissue homeostasis38A key feature of the signaling network is that p53 transcriptionally activates its own suppressors Mdm2 and the phosphatase PPM1D/Wip112To investigate the design principles underlying dynamic signal processing in the p53 network, we combined quantitative single cell data with an abstracted mathematical model of selected molecular interactions. Many previous p53 modeling approaches focused on the negative feedbacks mediated by Mdm216171322To analyze p53 dynamics in response to different doses of DNA damage, we used previously generated single cell data obtained from a breast cancer cell line expressing a fluorescent reporter system 14. Cells1415As previously reported1213142627When we compared IPI distributions in cells treated with no, intermediate or high levels of NCS, we observed increasing coherence of the p53 pulse trains with increasing stimuli . To gainOur analysis indicates that there are two possible modes of function for the p53 system: Highly stimulated cells show a coherent pulse train resembling oscillations  with a sHow can the same molecular network give rise to oscillations and stochastic pulses while preserving pulse amplitude and width? To address this question we turned to dynamical systems theory30The negative feedback loops by Mdm2 and Wip1 are prominent regulatory elements of the p53 network. It is well known that negative feedback can give rise to limit cycle oscillations131617To gain a deeper understanding of the dynamic regimes covered by the mathematical negative feedback model, we systematically analyzed its behavior for a range of parameter values . This pr32We therefore extended the range of possible p53 network topologies by including a positive feedback (negative-positive feedback (NPF) systems  and supp343536The NPF system should also exhibit an oscillatory regime to fully capture the behavior of the p53 system. Indeed, the proximity of excitable and oscillatory regimes with respect to parameter variation is a hallmark of excitable systems. Accordingly, we find for our NPF system that sustained input results in sustained oscillations . ImportaTo better understand the onset of oscillatory dynamics in the NPF system, we again analyzed its behavior upon stimulus variation. There are various types of transitions to oscillations possible for NPF systems, many of which have in common the onset of oscillations with large amplitude3031Based on these considerations we suggest that the p53 system exhibits two different dynamic regimes controlled by stimulation strength: In basal state the system is excitable and DSB noise causes irregular appearance of pulses by random occurrence of stimulations above threshold. These pulses occur repeatedly in the oscillatory regime at stronger and sustained stimulation, as the input signal is constantly supercritical, explaining the onset of oscillatory pulses with large amplitude.The dynamics of our abstract NPF model closely resembles p53 behavior observed in basal state, upon intermediate and upon strong stimulation . ExcitabAs dynamical systems theory suggested the existence of positive feedback in the p53 pathway, we aimed to generate a plausible model of the underlying molecular network. There are numerous positive and negative feedback loops reported for p53, mostly based on the transcriptional activity of the tumor suppressor3942*) phosphorylates the histone variant H2AX, which serves as a scaffold for the recruitment of further proteins involved in DDR and damage repair. These regions of phosphorylated H2AX (γH2AX) may spread over several thousand basepairs around damage loci* subsequently stabilizes p53 by phosphorylating Mdm2 and p53  and other feedbacks by phosphorylation and dephosphorylation . A centra priori that this contributes to the excitable p53 response. ATM may only act as an intermediate signal activating an independent excitatory circuit. To distinguish between these possibilities, we again employed the abstract NPF model and either inhibited the activating signal or the species X  with parameters based on previous publications 1325. In 13b, allowing us to mimic the action of the radiomimetic drug NCS used in live-cell measurements of DSB dynamics (see r. The population mean number of DSBs is <DBS(t)> = (Ns − Nb) exp(−rt) + Nb, where t is the time since stimulation, Ns the dose dependent maximal number of inflicted DSBs and Nb = b/r is the background damage level. This allows us to estimate the basal break (0.7 DSB/h) and repair rates (0.35 DSB/h) from measured data (trepair> ~ ln(Ns)/r. Hence, even high numbers of induced DSBs would be repaired after 20 hours with these values of r. Since measurements showed the persistence of DSBs beyond this time, we expanded our model to include DSBs of variable complexity. It has been suggested that complex breaks (cDSBs) occur when several clustered DSBs are generated within a chromatin loopisolated DSB (iDSB), leading to biphasic DSB kinetics53Due to the prominent role of positive feedback on ATM, we decided to explicitly consider the generation and repair of DSBs in our model. Recently, we measured DSB dynamics in single cells over time and observed considerable variability in their number and half-life, highlighting the stochastic nature of DSB repair15mics see . DSB repred data . These rTo test whether the combination of an excitable p53 model and stochastic DSB kinetics are sufficient to describe single cell dynamics of p53 in different conditions, we simulated three varying levels of DNA damage. Without externally induced DSBs, average background damage did not elicit a p53 response and the system resided mainly at steady state with subthreshold fluctuations . HoweverNext, we simulated a medium damage dose through a higher initial break rate, leading to a substantial increase in DSBs . The sysFinally, we simulated a strong damage dose resulting in high amount of DSBs including many cDSBs. As a result, DNA damage was not entirely repaired within the simulated time; the p53 system received sustained input throughout the simulation and showed oscillatory dynamics  and I. IIn summary, our model with excitable and oscillatory dynamics was able to reproduce the main characteristics of p53 behavior in single cells: a smooth transition between steady state, irregular pulses and regular oscillations while preserving pulse amplitudes and durations. This is based on the combination of negative and positive feedbacks, which lead to a bifurcation scheme  and phasSo far, the only source of variability was given by the stochastic DSB process as the deterministic core model was identical for all cells. Hence, the same initial DSB time course would lead to a collective first response, either a pulse or no pulse, within the population. However, it was previously demonstrated that in clonal cell populations the number of responsive cells gradually increases with the amount of induced DSBsOur qPCR analysis  suggestsWe next simulated thousands of trajectories, each with its individual Wip1 production rate according to the distribution described above and DNA damage represented by the stochastic DSB process. We binned the ensemble according to the maximal number of inflicted DSBs and tested for a pulse within the first six hours. This defines two regions in the DSB-Wip1 production rate plane  correspoWe next simulated an experiment with a given dose of a damaging agent by first sampling individual Wip1 productions rates and then simulated DSB dynamics with a fixed initial break rate. This results in a two dimensional distribution of cells within the DSB-Wip1 production rate plane .Taken together, our model simulations suggest that Wip1 levels set a cell-specific activation threshold for the p53 system.all-or-none pulse generator and that Wip1 is a major regulator of its cell-specific excitation threshold towards DSBs.To test the model hypothesis that the responsiveness of the p53 system is determined by Wip1 steady state concentrations, we first established a cell line overexpressing Wip1 fused to the red-fluorescent protein mCherry. We verified effectiveness of the overexpression in terms of reduced ATM and Chk2 phosphorylation by Western Blot analysis . Upon inIn this study, we combined insights from dynamical systems theory with experimental measurements to identify design principles that enable robust yet versatile signal processing by the tumor suppressor p53. We showed that an excitable network structure comprised of both negative and positive feedbacks is capable of reproducing the p53 response in healthy and stressed cells. While pure negative feedback systems also generate limit cycle oscillations corresponding to highly damaged cells, they fail to reproduce two key features of p53 dynamics observed in single cells: pulses with uniform amplitudes during entry and exit from the oscillatory regime and the occurrence of isolated pulses triggered by spurious endogenous DNA damage. However, our theoretical considerations only pointed towards the existence of positive feedback without constraining its molecular manifestation. We therefore investigated various postulated transcriptional feedbacks including autoregulation of p53 RNA. However, we did not observe expression changes at the level and timescale expected for regulators of pulse formation . While w5all-or-nothing response is characteristic for excitable systems such as the well-known FitzHugh-Nagumo model131422Combining positive feedback around ATM with a regulatory module based on negative feedback regulation resulted in stable p53 levels in healthy cells with few DSBs. Only when a threshold for ATM activity was reached, the system responded with a single full amplitude pulse. This all-or-nothing response characteristic of excitable systems allows for high sensitivity as the positive feedback essentially serves as a signal amplifier. Therefore, type I excitable systems naturally provide specificity and sensitivity to enable robust signal processing. The information content of a single pulse of defined amplitude is necessarily binary, suggesting that type I excitable systems are well suited to transmit decisive signals. Accordingly, it has been described that the stochastic entry into and exit from the competent state of the bacterium Bacillus subtilis is regulated by such a systemExcitable systems can be classified into two categoriesThe p53 system, however, does not only signal the presence or absence of DSBs, but also encodes the extent of DNA damage through the number of uniform pulses in a given time period121314all-or-nothing responses with versatile regulation of pathway sensitivity by threshold repositioning.In addition to heterogeneity in pulse numbers, single cell measurement also revealed cell-specific activation thresholds for the p53 responseAs a prominent modulator of the p53 system, Wip1 provides an entry point for crosstalk between the DNA damage response and other major signaling pathways. It has been reported that its expression levels are regulated by MAP kinase signaling6364652+ spikingThere is growing evidence that pulsatile intracellular dynamics play an essential role in different cellular contexts702 in RPMI 1640 containing 10% FCS, penicillin/streptomycin and appropriate selective antibiotics  to maintain transgene expression.The MCF7 and A549 p53 reporter cell line has been described before14292 concentration (5%), and humidity. Cells were imaged every 15–20 minutes for the duration of the experiment using Nikon Elements software.For imaging, we seeded cells in poly-D-lysine-coated glass-bottom plates (MatTek Corporation) two days before experiments. The day of the experiment, media was replaced with fresh one lacking phenol red and riboflavin. Cells were imaged on a Nikon Ti inverted fluorescence microscope with a Hamamatsu Orca R2 camera and a 20x plan apo objective (NA 0.75) using appropriate filter sets (Venus: 500/20 nm excitation (EX), 515 nm dichroic beam splitter (BS), 535/30 nm emission (EM); CFP: 436/20 nm EM, 455 nm BS, 480/40 nm EX; mCherry: 560/40 nm EM; 585 nm BS; 630/75 nm EM, Chroma). The microscope was enclosed with an incubation chamber to maintain constant temperature (37 °C), COWe used custom-written Matlab (MathWorks) scripts based on code developed by the Alon labThe single cell p53 trajectories were analyzed using wavelet transformations and smoothing splines . Peak deThe deterministic p53 model was formulated as a system of coupled ordinary differential equations (ODEs); the equations are given explicitly in the Supplement. Bifurcation analysis and numerical solutions were obtained with the PyDSTool frameworkbs is the break rate during stimulation and bb the basal break rate. The switching time between these two rates is given by Ts, which corresponds to the time span of active NCS. This approach towards time inhomogeneous Markov processes via step functions still yields analytically tractable expressions for the next-jump densities needed for the SSA algorithm. Details of the implementation and parameter values used can be found in the supplement. Simulations of the stochastically driven p53 system were carried out by pre-computing realizations of the DSB process and augmenting the r.h.s. of the ODE system by a corresponding forcing term.where We extracted mRNA using High Pure RNA Isolation kits (Roche) and generated complementary DNA M-MuLV reverse transcriptase (NEB) and oligo-dT primers. Quantitative PCR was performed in triplicates using SYBR Green reagent (Roche) on a StepOnePlus PCR machine (Applied Biosystems). Primers sequences: β-actin forward, GGC ACC CAG CAC AAT GAA GAT CAA; β-actin reverse, TAG AAG CAT TTG CGG TGG ACG ATG; Wip1 forward, ATA AGC CAG AAC TTC CCA AGG; Wip1 reverse, TGG TCA ATA ACT GTG CTC CTT C; p21 forward, TGG ACC TGT CAC TGT CTT GT; p21 reverse, TCC TGT GGG CGG ATT AG; p53 forward, TGA CTG TAC CAC CAT CCA CTA; p53 reverse, AAA CAC GCA CCT CAA AGC; PIDD forward, GAT GTT CGA GGG CGA AGA G; PIDD reverse, CAG GTG CGA GTA GAA GAC AAA G; PTEN forward, AAG GGA CGA ACT GGT GTA ATG; PTEN reverse, GCC TCT GAC TGG GAA TAG TTA C; TIGAR forward, CCT TAC CAG CCA CTC TGA GC; TIGAR reverse, CCA TGT GCA ATC CAG AGA TG; 14-3-3σ forward, CCC TGA ACT TTT CCG TCT TCC; 14-3-3σ reverse, GGT GCT GTC TTT GTA GGA GTC; Wip1 forward, ATA AGC CAG AAC TTC CCA AGG; Wip1 reverse, TGG TCA ATA ACT GTG CTC CTT C.5 A549 reporter cells in 6well plates and transfected them one day later with 25 nM of Wip1-targeting or scrambled control siRNA using the TransIT-X2 Dynamic Delivery System (Mirus Bio LLC) according to the manufacturer’s instructions. After two days, we trypsinized cells and plated 0.5 × 105 cells/well in a 24 well glass-bottom plate (MatTek) coated with fibronectin and proceeded with live-cell imaging as described above.We seeded 2.5 × 10Stellaris RNA FISH probe designer (Biosearch Technologies) on the reference sequence NM_003620.3 (PPM1D). Hybridization was performed at a final concentration of 0.1 μM probe following manufacturers instructions (Stellaris RNA FISH Protocols - adherent cells). Coverslips were mounted on Prolong Gold Antifade (Life technologies). For single molecule RNA quantification, 11 z-stacks of each cell were acquired with 300 nm step-width. Quantification of RNA counts per cell was performed using the Star Search analysis tool for spot detection (http://rajlab.seas.upenn.edu/StarSearch/launch.html).MCF7 cells were cultured for 24 h on uncoated coverslips (thickness: #1). Cells were washed and fixed with 2% Paraformaldehyde for 10 min at room temperature, washed again and permeabilized over night with 70% Ethanol at 4 °C. Custom probe sets for single molecule FISHWe harvested cells, lysed them in the presence of protease and phosphatase inhibitors, and extracted proteins, which we quantified using the Bradford assay. Equal protein amounts were separated by electrophoreses on 3–8% Tris-acetate gradient gels (Thermo Fisher Scientific) and transferred to polyvinylidene fluoride membranes (Amersham) by electroblotting overnight. We blocked membranes with 5% bovine serum albumin (Carl Roth) and incubated them overnight with primary antibody. Primary antibodies used were phospho-Chk2 (Thr-68) from Cell Signaling, phospho-ATM (S1981) from Rockland and glyceraldehyde-3-phosphate dehydrogenase from Sigma-Aldrich The next day, we washed the membranes, incubated them with secondary antibody coupled to peroxidase, and washed them again. Protein levels were detected using chemiluminescence .How to cite this article: Moenke, G. et al. Excitability in the p53 network mediates robust signaling with tunable activation thresholds in single cells. Sci. Rep.7, 46571; doi: 10.1038/srep46571 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Staphylococcus aureus are associated with persistent infections. Phenotypically, SCVs are characterized by slow growth and they can arise upon interruption of the electron transport chain that consequently reduce membrane potential and thereby limit uptake of aminoglycosides . In this study, we have examined the pathways by which the fitness cost of SCVs can be ameliorated. Five gentamicin resistant SCVs derived from S. aureus JE2 were independently selected on agar plates supplemented with gentamicin. The SCVs carried mutations in the menaquinone and hemin biosynthesis pathways, which caused a significant reduction in exponential growth rates relative to wild type  and reduced membrane potentials. Fifty independent lineages of the low-fitness, resistant mutants were serially passaged for up to 500 generations with or without sub-lethal concentrations of gentamicin. Amelioration of the fitness cost followed three evolutionary trajectories and was dependent on the initial mutation type (point mutation vs. deletion) and the passage condition (absence or presence of gentamicin). For SCVs evolved in the absence of gentamicin, 12 out of 15 lineages derived from SCVs with point mutations acquired intra-codonic suppressor mutations restoring membrane potential, growth rate, gentamicin susceptibility and colony size to WT levels. For the SCVs carrying deletions, all lineages enhanced fitness independent of membrane potential restoration without alterations in gentamicin resistance levels. By whole genome sequencing, we identified compensatory mutations in genes related to the σB stress response (7 out of 10 lineages). Inactivation of rpoF that encode for the alternative sigma factor SigB (σB) partially restored fitness of SCVs. For all lineages passaged in the presence of gentamicin, fitness compensation via membrane potential restoration was suppressed, however, selected for secondary mutations in fusA and SAUSA300_0749. This study is the first to describe fitness compensatory events in SCVs with deletion mutations and adaptation of SCVs to continued exposure to gentamicin.Small colony variants (SCVs) of the human pathogen  CS. aureus, the electron acceptors hemin of the cytochromes and menaquinone (isoprenylated form of menadione) are required for electron flow in the electron transport chain . The following transposon mutants were retrieved from the Nebraska Transposon Mutant Library (hemB::ΦNΣ (NE1845), JE2 menD::ΦNΣ (NE1345), JE2 rpoF::ΦNΣ (NE1109) and JE2 SAUSA300_1252::ΦNΣ (NE142). Strains were grown in TSB at 37°C with shaking at 200 rpm or on TSA agar plates with or without addition of gentamicin (Sigma). Minimal inhibitory concentrations (MICs) of gentamicin were determined using a twofold microbroth dilution assay according to rpoF::ΦNΣ (MV216) and MV118 SAUSA300_1252::ΦNΣ (MV218) mutants was performed by transduction with bacteriophage φ11, selecting for transductants on erythromycin plates (5 μg/ml) (All strains used in this study are derivatives of the  Library : JE2 hem5 μg/ml) .Selection of spontaneous gentamicin resistant SCVs was performed on TSA plates supplemented with 4 μg/ml of gentamicin, by applying proper dilutions of JE2 over-night (ON) cultures on the plates. SCV colonies were picked after 48 h of incubation and re-streaked on gentamicin-free TSA plates to examine the stability of the SCV phenotype. If no revertants appeared in the re-streak, one colony from each independent selection was saved. The mutation frequency of gentamicin resistant SCVs was calculated as the ratio of the number of gentamicin resistant mutants divided by the total number of cells (determined by plating proper dilutions on TSA plates).Genomic DNA (gDNA) was isolated from 1 ml ON cell culture using DNeasy Blood and Tissue Kit (Qiagen). Cell lysis prior to gDNA isolation was achieved by pre-treating ON cultures with lysostaphin (5 mg/ml) for 1–2 h. Genes were amplified with two primer pairs to secure proper quality along the entire genes of interest. Genes of interest were amplified by PCR using Taq DNA polymerase (Thermo Scientific). Primers used for amplification are available in Supplementary Table S. aureus USA300_FPR3757 reference genome (Genbank accession no. NC_07793). Variants were called at standard settings. To exclude false-positive variant calls due to alignment of reads to the S. aureus USA300_FPR3757 reference genome, we sequenced the JE2 strain that is the ancestral strain of the selected SCVs. Variants identified in our JE2 sequence were excluded in the selected SCVs and evolved strains by the function ‘Filter Variants against Control Reads.’Whole genome sequencing was performed at the Department of Clinical Microbiology at Hvidovre Hospital on a MiSeq . DNA concentrations were normalized using a Qubit . Libraries were made with Nextera XT DNA sample preparation kit , genomes multiplexed to 24 isolates per run and sequenced with 2 × 150 bp paired-end reads. Analysis of output reads from the MiSeq was performed in CLC Genomics Workbench version 8.0. Reads were aligned to the 6 cells, was transferred into fresh growth medium, allowing for growth of approximately 10 generations per transfer. After every 50 generations of evolution, samples from each lineage were plated on TSA plates and visually inspected for growth compensation based on colony size. Restored fitness in compensated lineages could also be recognized by visual inspection of the culture cell density. If cells in a lineage reverted to normal colony phenotype, one colony was saved from that lineage. The strains not showing changes in colony size were passaged for 50 days (∼500 generations), at which point one colony from each lineage was saved.Compensatory evolution was performed in TSB and in TSB supplemented with gentamicin at aaa12 MIC of the respective SCV strain. Five independent lineages started from single colonies for each strain were passaged under both culturing conditions. The evolution experiment was performed via serial passaging in 10 ml falcon tubes containing 1 ml growth medium in each tube for proper aeration. Every 24 h 1 μl, corresponding to approximately 106 CFU/ml in 1 ml TSB or in 1 ml TSB supplemented with gentamicin (aaa12 MIC of the parent SCV strain). Three hundred microliter was transferred to each well of the bioscreen plate with measurements taken every 5 min at 600 nm wavelength. The relative growth rates were calculated as the growth rate of the mutant divided by the growth rate of the WT strain. Three biological replicates were performed for each mutant, with three technical replicates per biological. (ii) colony forming unit (CFU) counts at stationary phase after 24 h growth was determined by growing cells in 1 ml TSB in a 10 ml falcon tube with constant shaking at 200 rpm. Cells from ON cultures were diluted to a starting inoculum of 106 CFU/ml. CFU quantification was determined on TSA plates. Three biological replicates were performed for each strain.Fitness was estimated by two parameters. (i) Growth rates in exponential phase were measured in a Bioscreen C reader (Oy Growth Curves Ab) at 37°C. Bacteria from ON cultures were diluted to a final concentration of 10600 of 0.2. Fifteen microliter culture was transferred to 1 ml filtered phosphate-buffered saline (PBS). To each cell solution 10 μl of fluorescent membrane potential indicator dye, DiOC2(3), was added and cells were stained for 30 min at room temperature. Data was recorded on a BD Biosciences Accuri C6 flow cytometer , with emission filters suitable for detecting red and green fluorescence. Settings on the flow cytometer were as follows: 50000 recorded events at a FSC threshold of 15000 and medium flow rate. Gating of stained cell population and analysis of flow cytometry data were performed in CFlow® (BD Accuri). As an indicator of membrane potential the ratio of red to green fluorescence intensity was calculated. The assay was verified using the two SCV strains with transposon insertions in hemB (NE1845) and menD (NE1345).Assessment of variations in membrane potential was estimated using a flow cytometry assay based on the BacLight Bacterial Membrane Potential Kit (LifeTechnologies). Cells from ON cultures were inoculated in 30 ml TSB in 300 ml Erlenmeyer flasks and grown to an OD∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001). Statistical analysis was performed in GraphPad Prism 4 .Significant difference was calculated by 1-way ANOVA, with a post-hoc analysis of Tukey’s Multiple Comparison Tests  in order to identify the resistance conferring mutations. Only a single mutation was identified for each mutant (Table 2). Four mutations were located in the menaquinone (MenA Asn198Lys and MenD Ala413fs) and hemin (HemH Glu263* and HemB Pro240Leu) biosynthesis pathways. The fifth strain contained a deletion in the SAUSA300_1683 gene (SAUSA300_1683 Leu274fs), encoding for the bi-functional enzyme 3-deoxy-7-phosphoheptulonate synthase [EC: 2.5.1.54]/chorismate mutase [EC: 5.4.99.5]. This enzyme is required for the biosynthesis of chorismate, the first precursor molecule of the menaquinone biosynthesis pathway (2(3) (Table 2). The reduction in membrane potential of the SCVs correlated with 8–16 times increased gentamicin MIC (16–32 μg/ml), compared to the MIC of the WT strain (2 μg/ml). The menD and SAUSA300_1683 displayed menadione auxotrophy, while the hemH and hemB displayed hemin auxotrophy. Growth complementation with menadione could not be achieved for menA (Table 2).Spontaneous gentamicin resistant mutants were selected on TSA plates containing 4 μg/ml gentamicin, corresponding to 2x MIC of WT  pathway . All fivfor menA  . Furthermore, the SCVs experienced 10–30 fold lower CFUs in stationary phase, when grown in TSB .We estimated the fitness cost of the SCV mutations using two parameters (i) exponential growth rate and (ii) CFU in stationary phase. The relative growth rate of the five SCV mutants were 0.59–0.72 in TSB, while being 0.49–0.62 in TSB supplemented with gentamicin compared to the WT strain grown in TSB .To investigate if fitness could be ameliorated in the SCVs and address the compensatory mechanisms involved, we conducted an evolution experiment with and without sub-lethal concentrations of gentamicin (aaa12 MIC), selecting for mutants with improved fitness. For each SCV mutant we passaged five lineages without and five lineages with gentamicin and at regular intervals screened for higher fitness by visual examination of bacterial colony size on TSA plates. To separate potential adaptation to the growth medium from SCV specific compensatory events we passaged five WT lineages for 500 generations in TSB in parallel. None of the evolved WT lineages displayed improved fitness in terms of exponential growth rate or stationary CFU count, indicating that hemH, menA or hemB) and the reversion occurred only when passaged without gentamicin. Interestingly, in a single passage (∼10 generations) revertants with WT colony size accounted approximately for 50% of the total colonies in the population (tested upon plating on antibiotic-free plates), where no revertants had been observed at the former passage. This fast take over cannot be explain solely with increased growth rates but might also indicate that revertants utilize nutrients that the SCV mutant cannot, which is supported by the observation that revertants grow to approximately 10-fold higher cell densities than SCVs . Reversion to WT colony size proceeded within 50–310 generations for the 12 lineages. As the reverted clones in a single passage constituted 50% of the population, the rate for reversion to WT colony phenotype was treated as a stochastic event. The rate of reversion was estimated to be approximately 10−8–10−9 per cell per generation . The relative growth rates for the compensated strains ranged from 0.89–1.00, compared to 0.60–0.72 of the ancestral SCVs . The lineages also gained sensitivity toward gentamicin  and an assessment of fitness was therefore not possible to do in TSB supplemented with gentamicin .Out of the 50 passaged lineages, only 12 reverted to WT colony size  and evolved without gentamicin reverted to WT colony phenotype, even though they displayed improved fitness in terms of growth rate and CFU in stationary phase . The relative growth rates in TSB of menD lineages were 0.65–0.73 compared to 0.63 of the ancestral menD, while the relative growth rates of SAUSA300_1683 lineages were 0.65–0.76 compared to 0.59 of the ancestral SAUSA300_1683. Only three of the lineages displayed twofold reduced MIC compared to respective ancestral SCVs, while the remaining seven lineages retained the same MIC as respective ancestral SCVs . The increased growth rates of the 10 lineages resulted in a trade-off with significantly reduced growth rates for the majority of the lineages, when grown in TSB supplemented with gentamicin .None of the 10 lineages derived from deletion SCV mutants (n = 22/25) displayed improved growth rates in TSB supplemented with gentamicin, while the growth rates were increased for 15/25 in TSB . Increased levels of resistance to gentamicin (2–8 fold) were observed for 20/25 lineages .None of the 25 lineages evolved with gentamicin restored colony phenotype to WT levels. Nonetheless, the majority of lineages  revealed intracodonic mutations in 12/15 lineages (Table 3). We identified reversion to WT sequence on nucleotide level in eight lineages and for two lineages on amino acid level. In two lineages, compensatory mutations substituted the SCV conferring amino acid with a non-synonymous amino acid compared to the WT sequence. The acquisition of intracodonic compensatory mutations in the 12 lineages correlated with reversion of membrane potential to the level of the WT  and gentamicin re-sensitization . In the remaining three lineages, we did not identify any intragenic mutations in the SCV conferring genes. These lineages indeed displayed lower levels of fitness amelioration compared to the lineages carrying intracodonic compensatory mutations. The two lineages (E68 and E69) retained membrane potentials as ancestral SCV and remained resistant to gentamicin, while lineage E47 displayed partial growth rate and membrane potential restoration and gentamicin re-sensitization  exhibiting improved fitness, as well as the five WT control lineages. All of the evolved SCV lineages still contained the original SCV mutation , rsbU (n = 1) and rpoF (n = 2)]. The spoVG gene encodes for the downstream modulator SpoVG of the σB general stress response  . This correlates well with the observed growth rate trade-off in the majority of menD and SAUSA300_1683 lineages evolved without gentamicin . Furthermore, three of the lineages evolved without gentamicin displayed non-synonymous missense mutations in the sensor histidine kinase srrB of the staphylococcal respiratory response two-component system SrrAB  . None of Library . The expem SrrAB . Two of menD and SAUSA300_1683 lineages evolved with or without gentamicin, 12/17 lineages acquired mutations in the gene SAUSA300_1252, encoding a alanine/glycine:cation symporter. Premature stop-codons and INDELs causing frameshifts suggest that the symporter is non-essential and that the mutations cause a loss of function. We inactivated SAUSA300_1252 with a transposon insertion in SCV strain MV118 (MV218) to assay the fitness effect in TSB and TSB supplemented with gentamicin. We could not identify any difference in terms of exponential growth rate between MV118 and MV218 in TSB or TSB supplemented with gentamicin .Independent of whether Figure 4). We WGS seven menD and SAUSA300_1683 lineages evolved in the presence of gentamicin. All of the seven lineages contained mutations in either fusA and/or SAUSA300_0749, while none of the lineages evolved without gentamicin contained mutations in these genes . The gene fusA encodes the elongation factor G (EF-G) and mutations were identified in three lineages . The combination of fusA and a SCV conferring mutations has previously been described for in vitro selected kanamycin resistant mutants in S. aureus (SAUSA300_0749 encodes a product of unknown function and has not previously been associated with gentamicin resistance. A premature stop-codon in strain E74 (Gln3∗) suggests that the gene is non-essential and that loss-of-function confer the resistance.Increased levels of gentamicin resistance were detected in 20/25 of the lineages evolved with gentamicin compared to respective ancestral SCV mutants  that evolved without gentamicin. In 12/15 lineages, evolved mutants displayed WT colony morphology and relative fitness of 0.89–1.00 compared to 0.60–0.72 of the ancestral SCVs . The fitness compensation correlated with restoration of membrane potential  and re-sensitization to gentamicin . Sequencing of the respective resistance genes revealed intracodonic suppressor mutations in all of the 12 lineages, leading to either nucleotide reversion to WT sequence, reversion to WT sequence on amino acid level or substitution of the SCV conferring amino acid mutation (Table 3). For the remaining three lineages that did not display fully WT phenotype characteristics, we could not identify any secondary intragenic mutations. Restored fitness has previously been associated with reversion in S. aureus SCV isolates with point mutations as the resistance conferring mutation . Rather this indicates that revertants can utilize nutrients that SCVs cannot.The largest fitness increase was observed in lineages derived from SCVs with a point mutation  in these lineages, but the parental SCV level of gentamicin resistance was maintained . For 7/10 of lineages derived from SCVs with deletions evolved without gentamicin, we detected mutations related to the σB stress response, namely . Furthermore, we detected mutations in alanine/glycine transporter encoded by the gene SAUSA300_1252 in 9/10 lineages . The introduction of pre-mature stop-codons or frame-shift mutations indicated that the mutations caused a loss-of-function of the gene products. We could show that transposon inactivation of rpoF in a SCV mutant conferred improved exponential growth rates in the absence of gentamicin, but lower growth rates with gentamicin, correlating with the observation of the passaged lineages containing mutations in σB stress related genes .Selection for restoration of membrane potential to WT level only occurred in lineages derived from point mutation SCVs that evolved without gentamicin. In the evolved lineages that originated from SCVs with deletions, restoration of membrane potential did not occur under any growth conditions. The relative growth rate increased 2–17% . The SCV lineages evolved in presence of gentamicin (1/2 MIC) experienced enhanced resistance to gentamicin (20/25 lineages)  and increased growth rates in the presence of gentamicin (22/25 lineages) . Missense mutations in fusA (3/7 lineages) and/or mutations in SAUSA300_0749 (5/7 lineages) most likely accounted for the increased gentamicin MIC, as they were identified in multiple parallel lineages and exclusively in lineages passaged with gentamicin . Mutations in fusA that encodes for the ribosomal translation elongation factor, EF-G, can confer resistance to fusidic acid and aminoglycosides and fusA mutations in SCV strains have previously been observed  concentrations of gentamicin. At this concentration, the exponential growth rates were further decreased for the ancestral SCVs compared to growth in antibiotic-free medium, suggesting that membrane-depolarization does not completely prevent uptake of gentamicin  in an rpoB mutant , and whether evolution proceeded with or without gentamicin. Switching between fast growing variants and slow growing of fections . Membraning SCVs .MV, WP, and HI conceived and designed the study. Experiments were performed by MV, WP, BL, and JN. MV, WP, JN, HW, and HI analyzed the data. MV, WP, HW, and HI drafted the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We assessed the CT attenuation density of the pulmonary tissue adjacent to the heart in patients with acute non-ST segment elevation myocardial infarction   Specifications TableValue of the data•The data can be used to evaluate inter-observer variability of semi-automated assessment of lung water assessed on cardiac computed tomography data sets.•This data can be used to evaluate the relation between subjective assessment of ground-glass opacification and pulmonary attenuation density.•These data on high attenuation density volume in patients with myocardial infarction can be used in further studies to compare values with other cohorts.1The visual severity of three levels of ground-glass opacification (GGO) is related to pulmonary attenuation densities. Further the interobserver variability of these automated measurements are presented.1.1Automated segmentation of the lungs was performed by two independent observers in 53 patients; 27 with left ventricular ejection fraction ≥45% and 26 patients with left ventricular ejection fraction <45%. No significant difference between observers was found in the measurement of pulmonary attenuation density: mean difference 4 HU (95% CI of −31 to 39 HU). Also no significant difference was found between observers in the measurement of high density ratio (Mean difference of 0.5% with a 95% CI of −2 to 3). Bland–Altman plot of pulmonary attenuation densities and high attenuation volumes are given in 1.2CT data sets from 367 patients with acute non-ST segment elevation myocardial infarction were analysed. No GGO was present in 292 patients mild-moderate GGO was found in 65 patients, and severe GGO in 10 patients. This categorization correlated with increasing mean pulmonary attenuation density and mean high pulmonary density ratio A and B.2Coronary computed tomography angiography data sets were acquired before invasive treatment from 367 patients with acute non-ST-segment elevation myocardial infarction high pulmonary density volume and the high pulmonary density ratio was assessed as: high pulmonary density volume / total measured lung tissue volume, in %.The pulmonary attenuation density and the high pulmonary density ratio was obtained using pulmonary densitometry in the following way: Full view images in 3 mm slice thickness were loaded into the workstation  using the pulmonary density analysis tool, which automatically traced the part of the left and right lung within the scan field A. VoxelsComparison between groups of subjective levels of GGO was tested using one way ANOVA. Interobserver variability in the assessment of lung water was evaluated using the Bland–Altman method


Chromosomal translocations are a hallmark of cancer cells and give rise to fusion oncogenes. To gain insight into the mechanisms governing tumorigenesis, adequate model cell lines are required.de novo (CD74-ROS1) or existing translocations are reverted back to the original configuration (BCR-ABL1). To this end, we co-apply two guide RNAs to artificially generate two breakpoints and screen for spontaneous fusion events by PCR.We employ the versatile CRISPR/Cas system to engineer cell lines in which chromosomal translocations are either generated The approach we use is efficient and delivers clones bearing translocationsin a predictable fashion. Detailed analysis suggests that the clones display no additional undesired alterations, implying that the approach is robust and precise.The online version of this article (doi:10.1186/s12864-016-3084-5) contains supplementary material, which is available to authorized users. Chromosome abnormalities are a characteristic feature of cancer cells. Recurrent chromosome rearrangements, like translocations, are often found in various tumour types, and there is overwhelming evidence that they are key drivers of tumorigenesis . BalanceThe first ever identified chromosome translocation in cancer was the Philadelphia chromosome originating from a balanced translocation between chromosomes 9 and 22 . The PhiChromosome rearrangements involving ROS1 gene have been found in 1–2 % of patients with non-small cell lung cancers. Several fusion partners are known for ROS1, among which CD74 is the most common . The CD7Streptococcus pyogenes that can be reprogrammed by short RNAs  to induce a DNA double-strand break at any position that is followed by a protospacer adjacent motif (PAM) (NGG for S. pyogenes Cas9). Repair of the double-stand break can either occur by non-homologous end joining or by homology-directed repair, depending on whether a homology template is present or not. The CRISPR/Cas system has been used for genome engineering in a large number of species and for a wide variety of purposes  and 4 L20 (BCR-ABL1 reversion) were selected for further analysis at the genomic DNA level. PCR analysis indicated that the mutant clones contained the desired translocation and that this translocation was absent in parental eHAP cells  and FKBP rapamycin binding (FRB) domain system . AlternaWhile the high efficiency we observed is desired when engineering chromosomal translocations, it may be undesired in other instances, e.g. when engineering double knockouts. We suspect that at least in some instances, the simultaneous delivery of two guide RNAs will cause translocations and other genomic rearrangements as unwanted side effects. While these can easily be assessed in clonal cell lines that proliferate almost indefinitely, they may be more difficult to detect in scenarios where cell populations are more heterogeneous.We used the haploid human cell line eHAP for the experiments presented here. In our view, this choice offers three major advantages, all of which are based on the fact that the cell carries a single genome copy: (i) Genotyping is a lot more straightforward than in diploid cells, (ii) Reversion back to wild-type configuration is hampered because a suitable homology template is missing and (iii) Cell lines derived contain 100 % allele burden with regard to the chromosomal translocation. However, we believe that this approach would be equally feasible in diploid cells. To exemplify this, we transduced diploid 293 T cells with two gRNAs for CD74 and ROS1 and detected both the CD74-ROS1 fusion and the reciprocal ROS1-CD74 fusion by PCR  to guaranty cell line clonality. Monoclonal cell lines were expanded using Microlab STAR Line robotic system (Hamilton Company).For the primary PCR screen, genomic DNA was prepared using DirectPCR Lysis reagent (PeqLab) containing Proteinase K (Sigma). Genomic DNA was isolated from selected clones using the Gentra Puregene Cell Kit (Qiagen) according to manufacturer’s instructions. PCR was performed using GoTaq Polymerase (Promega) according to manufacturer’s instructions. PCR products were analysed using 1 % TAE agarose.Total RNA was purified using RNAeasy Plus Mini Kit (Qiagen) and cDNA was synthesized using SuperScript® III Reverse Transcriptase (Thermo Fisher Scientific) according to manufacturer’s instructions.Spectral karyotyping was performed and analyzed by WiCell Cytogenetics. In brief, metaphase chromosome spreads were prepared on slides according to standard cytogenetic procedures. These slide preparations were then hybridized according to the DNA spectral karyotyping hybridization and detection protocol provided by Applied Spectral Imaging (ASI) using the supplied SKY probes and detection system. Images were captured and analysed using the HiSKYV spectrum imaging system from ASI.


To the Editor:1]. Remarkably, it has been reported that 2 out of 10 women with HEV may die during the third trimester [2]. Despite that, epidemiological data on infection and disease during childhood are limited [2]. HEV infection usually causes a mild self-limiting disease, although fulminant hepatitis and death are also described [2]. Liver transplant recipients, who developed a chronic HEV infection through blood transfusion, subsequently developed permanent hepatic graft damage [3]. A recent cohort study, by Zhang and colleagues, among more than 110.000 healthy participants of 16 to 65 years old in China [4] suggested that the infection with hepatitis E virus (HEV) genotype 4 could be a vaccine-preventable disease.Hepatitis E virus (HEV) represents the most important etiological factor of acute clinical hepatitis among adults in many regions of the developing world, with significant adverse outcomes in terms of morbidity and mortality related burden especially among pregnant women [1]. HEV is considered more prevalent in industrialized countries than previously thought, while HEV acquisition through blood transfusion is underestimated, causing persistent disease in immunosuppressed patients [5]. Currently, the reduction of the risk of HEV through blood donation screening has been controversial [5]. An interesting review in this direction, by Wang et al., suggested that immunization against HEV infection would be beneficial for populations at risk [6]. Furthermore, the immunological therapies during the last decades in general have been considered that will determine a promising role [7]. Currently, infection with hepatitis E has been reported to be a geographically widely distributed disease [Accordingly, we advocate the need for cost-effectiveness studies in order to discuss a potential consensus to vaccinate a pool of blood donors, who donate haema products to immunosuppressed or undergoing transplantation patients and women receiving assisted conception treatments.


GDPD5), a transmembrane glycosylphosphatidylinositol (GPI)- specific glycerophosphodiesterase and member of a larger GDE family [GDPD5 was strongly associated with favorable clinical outcome, while low GDPD5 expression correlated with poor outcome in independent patient cohorts [Neuroblastoma is an embryonal cancer of early childhood that originates from the developing sympathetic nervous system, usually arising in the adrenal gland. It is the most common malignancy during infancy, accounting for about 10% of childhood cancer mortality, and there is an urgent need for new therapeutic approaches. Neuroblastoma is a highly heterogeneous disease, characterized by relatively few recurrent somatic mutations . In manyE family . In our E family , as illu cohorts  , as we discussed . TherefoFrom a clinical perspective, the new findings suggest that activation of the GDE2 signaling pathway by pharmacological means might be of benefit to patients having low GDE2 expression levels. As an ecto-phosphodiesterase, GDE2 is in theory a convenient drug target. However, it will be quite challenging to develop drug-like allosteric activators of GDE2. Downstream effectors of the GDE2-GPC6 cleavage pathway might be more amenable to therapeutic targeting, such as the RhoA-ROCK signaling cascade whose inhibition is known to mimic GDE2 activation in promoting neurite outgrowth.In conclusion, the new findings establish GDE2 as a cell-autonomous inducer of neuroblastoma differentiation with prognostic value. Future studies should address how glypican release from the cell surface triggers transmembrane signaling events and, together with GDE structure-function studies, they may open new therapeutic possibilities for overcoming the differentiation-inhibited state of neuroblastoma cells.