Mutants lacking SIT4 or KTI12 display a shift towards nonhydroxylated forms of long chain bases and sphingolipids, suggesting regulation of hydroxylase (SUR2) or ceramide synthase by Sit4p. We have identified novel subunits of the Sit4 complex and have also shown that known Sit4 regulatory subunits—SAP proteins—are not involved in the ceramide response. This is the first observation of separation of function between Sit4 and SAP proteins. We also find that the Sit4p target Elongator is not involved in the ceramide response but that cells deficient in Kti12p—an accessory protein with an undefined regulatory role—have similar ceramide phenotypes to sit4Δ mutants. Therefore, Kti12p may play a similar secondary role in the ceramide response. This evidence points to a novel Sit4-dependent regulatory mechanism in response to ceramide stress.Ceramide is a building block for complex sphingolipids in the plasma membrane, but it also plays a significant role in secondary signalling pathways regulating cell proliferation and apoptosis in response to stress. Ceramide activated protein phosphatase activity has been previously observed in association with the Sit4 protein phosphatase. Here we find that  Ceramide is a building block for complex sphingolipids which comprise an important structural component of the plasma membrane. It is also a secondary signalling molecule that accumulates in response to stresses such as heat shock . It is tAlthough it is known that the cellular response to ceramide is important for the regulation of cell proliferation and cell death pathways, the precise molecular mechanisms for this regulation still remain elusive. It is vital to further understand the way cells respond to stress in order to develop strategies to modify them, either to accelerate cell death using targeted anticancer drugs or to prevent accumulation of toxic products in sphingolipidoses –7.Saccharomyces cerevisiae has been used effectively as a model to study sphingolipid metabolism, and Saccharomyces cerevisiae, which is separate from the activity of the major PP2A phosphatases Pph21p and Pph22p myo-inositol. Yeast strains used in this study are listed in Yeast were routinely grown in yeast extract peptone dextrose medium  at 30°C with shaking. Glucose was replaced with 2% galactose to induce expression of 3 cells/mL in YPD containing ceramides/long chain bases or an equal volume of ethanol as an untreated control. Cultures were grown until the untreated control reached exponential phase (from 15–36 hours depending on the strain) and the OD600 measured for both treated and untreated cultures. After 24 hours, an additional dose of ceramide/long chain base was added to counteract the effects of compound degradation. The amount of growth in each concentration of ceramide/long chain base was then expressed as a percentage of the growth in untreated media. This method of standardising growth enables the comparison of slow-growing mutants such as sit4Δ to a faster-growing wild-type strain. Raw OD600 data is provided in Supplementary Tables 1 and 2 . A minimum of three biological replicates were performed for each strain and a one-way ANOVA with Bonferroni post-test was used to determine if growth was significantly different from the wild type (CY4029).C2-ceramide, C2-phytoceramide, dihydrosphingosine (DHS), and phytosphingosine (PHS) powders were purchased from Enzo Life Sciences and resuspended in 100% ethanol. Stock solutions (5 mg/mL) were stored at −20°C for a maximum of 1 week. Yeast cultures were diluted from a starter culture to 5 × 10μg of anti-HA antibody per mg of beads, following the manufacturer's instructions. Total protein extracts were prepared from 50 mL cultures grown for 8 hours in YPD supplemented with galactose. Cell pellets were resuspended in 400 μL B60 buffer ). An equal volume of glass beads was added and cells disrupted using a bead beater for 1 minute, followed by centrifugation at 15700 g, 4°C for 5 minutes. The supernatant was transferred to a new tube and centrifuged at 15700 g, 4°C for 20 minutes. The cleared protein extract was quantified using spectrophotometry and 3.5 mg of total protein extract was incubated with 1.5 mg of antibody-coated beads for 30 minutes at 4°C. Unbound proteins were removed by three washes with 1 mL B60 buffer, and antibody-bound proteins were eluted with 50 μL of 10% (v/v) SDS for 10 minutes at room temperature. The beads were then removed with a magnet and the supernatant used for Western blot analysis. SDS-PAGE of 100 μg of total protein from each strain and immunoprecipitation supernatants  was carried out using 12% acrylamide gels and then Western blotted at 100 V for 1 hour. Blots were probed with anti-HA (F7 Santa Cruz), anti-c-myc (A14 Santa Cruz), or anti-Tpd3  and secondary antibodies conjugated to horseradish peroxidase (Roche Diagnostics) were detected by chemiluminescence and exposed to X-ray film.Dynabeads (Invitrogen) were coupled with 5 600 0.2 and grown until they reached OD600 of 2. A total of 10 OD units of cells were collected and washed once with sterile water. Lipid extraction was performed by a two-step lipid extraction method   myo-inositol  and grown at 24°C for 4 h until they reached OD600 of approximately 2. A total of 10 OD units were harvested, and lipids were extracted using chloroform/methanol/water (10 : 10 : 3) and analysed as previously described [Overnight cultures grown at 24°C in YPD were diluted to ODSIT4 leads to significant resistance to 15 μM dihydroceramide (P < 0.0001). However, mutation of the four SAP regulatory proteins, either individually or in combination, does not confer resistance to dihydroceramide . Therefore, our data suggest that Kti12p might play a regulatory role in the ceramide response that is independent of Elongator.As Sit4p plays a major role in the phosphoregulation of the Elongator complex , 21 and sistance  to some sistance . In addisit4Δ and kti12Δ mutants show significantly more growth (P < 0.005) than the parental CY4029 strain at concentrations of 10–15 μM (sit4Δ and kti12Δ mutants in excess dihydrosphingosine (DHS) is indistinguishable from CY4029 , sit4Δ shows significant (P < 0.05) resistance to 3–6 μM PHS  and phytoceramide C  form inositol phosphoceramide B (IPC-B) and inositol phosphoceramide C (IPC-C) respectively. IPC-C and the corresponding MIPC-C generated from it form the relatively more abundant species of their sphingolipid class in the wild type . Interesd MIPC-C . The kti mutants .Previous studies suggested that Tpd3p and Cdc55p could be part of the CAPP complex as deletion of these genes conferred resistance to ceramide . Indeed,The aim of this study was to further investigate the role of the Sit4 phosphatase in response to ceramide and to determine if this signalling pathway is directly related to the biosynthesis of ceramides and sphingolipids. The phosphorylation status of Orm1p regulates the activity of serine palmitoyltransferase and therefore the production of all downstream products of the sphingolipid pathway. Orm1p is phosphorylated by Ypk1p and evidence suggests that dephosphorylation may involve Sit4p and/or its TOR-dependent subunit Tap42p , 26. HowThe Sit4 phosphatase is a well-characterised regulator of tRNA modification via the Elongator complex , 27–29. sit4Δ mutant. Importantly, this is the first separation of function observed between the sit4Δ and sapΔΔΔΔ mutants. This suggests that an alternative Sit4 phosphatase complex is involved in the regulation of the ceramide response, supporting the idea that this process is independent of Elongator functions that require Sit4/Sap complexes. The identification of a Sit4p/Tpd3p/Cdc55p trimer also supports the theory that the ceramide activated protein phosphatase could be acting via a previously unknown mechanism. The Sit4 phosphatase has multiple regulatory subunits including the Sit4 associated proteins (SAPs) Sap4p, Sap155p, Sap185p, and Sap190p. A quadruple deletion of all SAPs is sensitive to excess ceramide, in contrast to the resistant sit4Δ and kti12Δ mutants and the decreased levels of ceramide and long chain bases indicate that there is regulation of the biosynthetic pathway at some level by Sit4p and/or Kti12p. The decreased level of endogenous ceramide and PHS in the mutants presumably enables them to survive an otherwise toxic concentration of these compounds. This suggests that deletion of SIT4 and KTI12 mediates a downregulation or partial inactivation of ceramide synthesis rather than a complete block, as there are clearly sufficient precursors available for effective biosynthesis of sphingolipids. The presence of multiple genes encoding enzymes for synthesis and degradation of ceramides is a key way in which sphingolipid metabolism can be maintained when the pathway is partially blocked. Phosphoregulation of ceramide synthases has not been previously observed, but three phosphorylated serine residues are conserved in both Lag1p and Lac1p ceramide synthases and could be potential targets for dephosphorylation by Sit4p [sit4Δ and kti12Δ mutants, lac1Δlag1Δ mutants are resistant to the tRNase toxin zymocin, but the mechanism of action is due to a defect in plasma membrane integrity caused by decreased levels of the sphingolipid M(IP)2C and not via Elongator [The alteration of the sphingolipid makeup in by Sit4p , 33. In longator . sit4Δ and kti12Δ mutants, the relative proportion of lipids synthesised from dihydroceramides/DHS is higher than those synthesised from phytoceramides/PHS, suggesting that there could be a defect in the Sur2 hydroxylase which hydroxylates both long chain bases and ceramides [sit4Δ could cause a shift towards the synthesis of nonhydroxylated sphingolipids by these enzymes. However, these enzymes contribute a minor level of ceramide synthase activity compared to Lag1p, Lac1p, and Lip1p [In eramides . This iseramides  Dysregulnd Lip1p , so a chThese new insights into the novel ceramide-associated functions of Sit4p and Kti12p are helpful in understanding the diverse roles these proteins play in the cell and expand our knowledge of their importance beyond their association with the Elongator complex. Relatively little is known about the human orthologues of Sit4p and Kti12p, and thus yeast studies are vital in unravelling the essential role they play in regulating cell proliferation and cell death in both healthy and malignant cells. sit4Δ and sapΔΔΔΔ mutants and the interaction of Sit4p with the alternative regulatory subunits Cdc55p and Tpd3p also support this theory. Alterations in the levels of ceramides, long chain bases, and complex sphingolipids in sit4Δ and kti12Δ mutants indicate that these proteins are also likely to regulate the sphingolipid biosynthesis pathway. Future work will be targeted at delineating the underlying mechanism(s) underlying these observations.This study indicates that the roles of Sit4p and Kti12p in the ceramide response are distinct from their roles in the regulation of the Elongator complex and are therefore likely to be mediated via a novel mechanism. The separation of function between 600readings and % growth values for all data points in Figures 2 and 3 respectively.Supplementary Tables 1 and 2 include ODClick here for additional data file.


The Qß RT gene encoding the Read-Through protein was used as a mutation reporter. To reduce uncertainties in mutation frequencies due to selection, the experimental Qß populations were established after a single cycle of infection and selection against RT− mutants during phage growth was ameliorated by plasmid-based RT complementation in trans. The dynamics of Qß genome replication were confirmed to reflect the linear process of iterative copying (the stamping-machine mode). A total of 32 RT mutants were detected among 7,517 Qß isolates. Sequencing analysis of 45 RT mutations revealed a spectrum dominated by 39 transitions, plus 4 transversions and 2 indels. A clear template•primer mismatch bias was observed: A•C>C•A>U•G>G•U> transversion mismatches. The average mutation rate per base replication was ≈9.1×10−6 for base substitutions and ≈2.3×10−7 for indels. The estimated mutation rate per genome replication, μg, was ≈0.04 , although secondary RT mutations arose during the growth of some RT mutants at a rate about 7-fold higher, signaling the possible impact of transitory bouts of hypermutation. These results are contrasted with those previously reported for other riboviruses to depict the current state of the art in riboviral mutagenesis.Riboviruses (RNA viruses without DNA replication intermediates) are the most abundant pathogens infecting animals and plants. Only a few riboviral infections can be controlled with antiviral drugs, mainly because of the rapid appearance of resistance mutations. Little reliable information is available concerning i) kinds and relative frequencies of mutations , ii) mode of genome replication and mutation accumulation, and iii) rates of spontaneous mutation. To illuminate these issues, we developed a model  sensu stricto) represent a special urgency, because these viruses display an exceptional capability to generate resistance mutations against antiviral drugs. Unfortunately, little is known about the rate and nature of spontaneous mutation in riboviruses. Thus, characterization of their mutation process may be helpful in the development of improved ways to counteract riboviral diseases. In this study, we investigated the mutation process in vivo of a model ribovirus, the bacteriophage Qß, focusing on three key aspects: i) the kinds and relative frequencies of mutations, ii) the mode of genome replication, and iii) the rate of spontaneous mutation. Our results, combined with other information about riboviral mutagenesis, depict a ribovirus mutation spectrum largely dominated by transitions, a predominantly linear mode of genome replication, and a mutation rate per genome replication on the order of 0.04 for bacteriophages and plant viruses but perhaps an order of magnitude higher for mammalian riboviruses.Viral disease is a subject of major concern in public health. Diseases produced by riboviruses (RNA viruses  Riboviruses (RNA viruses with no DNA replication intermediates) infect organisms from prokaryotes to higher eukaryotes and frequently cause deadly diseases. The mortality, morbidity, and economic burden of ribovirus-borne diseases strongly impact human society, especially in developing countries where neither sanitation nor treatment may be adequate Although the evolutionary forces driving high riboviral mutation rates remain unclear  in riboviruses, again a reflection of mutation reporters that do not sufficiently sample the genome. Only three spontaneous mutation spectra based on a cognate riboviral gene of adequate size are available and, unfortunately, none seems to be fully illustrative. The tobacco mosaic virus rate and spectrum A complete portrait of spontaneous mutagenesis in riboviruses is important not only for understanding their prevalence but also for improving ways to prevent and to treat riboviral diseases. For instance, accurate information on riboviral mutation kinds and rates may facilitate the creation of more stable attenuated vaccines Escherichia coli, although it can also propagate in other gram-negative bacteria with an F pilus. Its 4217-nt long genome is organized in three cistrons that encode (from 5′ to 3′) the A2 or Maturation protein, which mediates both the binding of Qß to the host and post-replicative host lysis; the Coat protein and its elongated A1 or Read-Through (RT) protein, which is required for Qß capsid assembly and for host infection; and the catalytic ß subunit of the Qß replicase.  cellular components translate the ß subunit of the phage replicase, which then polymerizes with four host subunits  and binds the Qß genome; iii) the ß subunit copies the (+)-strand genome to produce a (−)-strand RNA that in turn is used as template to produce more (+) strands; iv) (+) strands serve as templates for the production of the phage proteins; v) 40–60 minutes after infection, by which time the host cell is filled with phage particles, partially assembled virions, and phage-specific side products, the cell lyses, releasing (10–40)×103 particles of which only 10–50% are infectious  in three different ways: i) a forward-mutation test in which mutants carrying phenotypically detectable RT mutations were isolated and sequenced and μg was estimated from the frequency of observed nonsense mutations and indels; ii) single-burst reversion tests in which two different RT− mutants were employed (one carrying a single-base substitution and the other a four-base insertion) and μg was estimated from the corresponding reversion rates; and iii) a phenotype-blind forward-mutation test in which some first-generation progeny of the RT mutants detected by the first method were isolated and sequenced and μg was estimated from the frequency of all secondary RT mutations generated de novo. The distributions of RT+ revertants observed in the reversion tests were used to infer the mode in which Qß replicates its genome, and the spontaneous Qß mutation spectrum was obtained from the RT mutations collected through the forward-mutation tests.Here, we used the gene encoding the RT protein (excluding the portion that encodes the Coat protein) as an The basics of the experimental system and the strains used in this study are described in Mutations arising in a mutation-reporter (target) sequence can be of two types. “Detectable” mutations are those that display the mutant phenotype when present as a single mutation. “Undetectable” mutations lack the mutant phenotype when present as a single mutation but may nevertheless be observed when they arise in the presence of a detectable mutation, in which case they are sometimes called “hitchhiker” mutations . Sometimes, especially with mutants with equivocal phenotypes, no mutation is found in the target, reflecting either some imperfection in the screening method or a mutation elsewhere in the genome whose effect mimics that of the reference mutation; such isolates are thereafter included in the non-mutant total. Another distinction is often relevant: some mutations produce a fully mutant phenotype but others produce an intermediate phenotype . In this study, yet another dimension is added. Each Qß mutant originally isolated as requiring a helper host to generate a plaque or each of a number of non-mutant control plaques was re-plated and up to four next-generation plaques were harvested and sequenced. When all members of such a family contain the same mutation, we call it the “primary” mutation, and if some of the next-generation plaques contain additional mutations, we call them “secondary” mutations, which may arise when mutation rates are sufficiently high.RT− mutations, indicated that Qß requires ≈75 min to lyse an infected RTH cell . Among 7517 plaques tested in four independent experiments, 47 candidate RT mutants were recovered and sequenced. Of these, 30 contained at least one primary RT mutation  Most of the primary mutations were missense but two (one in mutant RT23 and one in RT37) were indels consisting of single-base additions. Two mutants each carried two primary mutations; in RT18, both were missense; in RT41, one was missense and the other was a synonym. Three mutants  each carried a nonsense mutation that generated a stop codon; RT40 is a special case because it converted the leaky UGA codon that terminates the Qß Coat protein to a far less leaky UAA stop codon. In two cases, the primary mutation displayed at most a very weak phenotype upon re-plating: the primary mutation of RT27 was a synonym and that of RT33 was missense. These mutants are included in RT secondary mutations One-step growth curves of wild-type (wt) Qß in RT-helper (RTH) cells, which complement RTH cell . Thus, tmutation . . However, because a tendency towards enhanced mutability of any base within a G/C-rich sequence has been observed in both E. coliP = 0.059 and for the 7-mers has P = 0.034 . Nevertheless, these small differences, combined with the homogeneity in base composition of the analyzed sequences, made the “total G” (GT) non-significant in both analysis . Overall, a larger sample of mutations would probably indicate more clearly the existence (or absence) of any effect of the G/C content of the local sequence on Qß-replicase error tendencies.The mutations were widely distributed over the target . BecauseTo determine how mutations accumulate in the Qß (+)-strand progeny during replication and thus to estimate the rate of spontaneous mutation per genome replication in Qß, it is necessary to know the mode by which Qß produces its progeny during cell infection. Two distinct modes are possible. One is linear, wherein the infecting (+)-strand genome is used repeatedly as a template and then at least some of the resulting (−)-strand RNAs are each used repeatedly as templates; consequently, at the end of the infection cycle, each of the many (+)-strand progeny has experienced only two replications, from (+) to (−) and from (−) to (+). In this model, due to the many (+)-strand progeny contributed by the fewer (−)-strand templates, most replication errors will produce a single mutant during the second round of replication and only a small fraction of errors will generate a clone of mutants when a replication error occurs in the first round of replication and is further repeatedly copied in the second round IN and the other using RTSUB ×10−6  and roughly 4560 infected cells were introduced into each of the 250 experimental cultures, the expected total number of revertant bursts produced by preexisting RT+ phages was ≈5.3, in close agreement with the observed five large revertant bursts. The variation in numbers of revertants among these five bursts is consistent with the observed variation in burst sizes of wt Qß growing in the RTH host, 847±308 , and individual bursts with sizes from 300 to 3000 have been observed. In the case of RTSUB, among the 500 cultures assayed, one had to be discarded and another contained 935 plaques; in this case, the expected number of bursts from preexisting RT+ revertants was 3.5. None of the cultures containing bursts attributable to preexisting RT+ phages were included in the analyses.To determine which model best fits the distribution of mutants in Qß, two separate single-burst reversion tests were conducted see , one usiIN, the distribution closely fitted a Poisson, supporting a linear mode of genome replication for Qß and strongly inconsistent with an exponential mode. With RTSUB, the distribution deviated significantly from a Poisson, showing an excess of plates containing ≥3 revertants. Even within a linear replication mode, however, these results may reflect either or both of two causes. The first is that different reversion pathways during the first and second rounds of replication will tend to have different rates at any particular site. With RTIN, the reversion target for the first replication consists of 5′-UUAAUUAAGUUC-3′ where the target is underlined and reversion to wild-type would probably occur by the deletion of UUAA or, perhaps less likely, by pseudoreversion by the loss of one base from any of the four homo-dinucleotides, producing a gene with one extra codon. Unusually, the second-replication target is 5′-UUAAUUAAGAAC-3′, which is identical to the first-replication target except for the outermost flanking bases. Thus, the two error rates might be very similar and the ratio of (+)-strand to (−)-strand products might have been large enough so that errors accumulated mostly during the second replication and the resultant revertant bursts were largely composed of clones of size 1. With RTSUB, however, reversion must have occurred along the available single-base-substitution pathways , each of which differs between replications and which might therefore have displayed large rate asymmetries, which can easily exceed 100-fold in the case of DNA genomes The revertant distributions differed for the two mutants . With RTg) for a ribovirus, it is necessary to know (i) the mutation frequency f, (ii) the number of infection cycles c that elapse between the initial infection and the scoring of mutants, (iii) the average number of times n that each genome is replicated per infection cycle, (iv) the number of detectably mutable bases in the mutational target (T), and (v) the genome size (G). In the present case, G = 4217 nt, c = 1, and, from our results, n≈2. Although T = 591 RT bases for estimating the indel mutation rate (μI), that number cannot be used when estimating the corresponding base-substitution rate (μSUB) because, while nearly all indels are detectable, many substitutions fail to produce a mutant phenotype. Instead, μSUB may be estimated from the number of substitutions that generate a stop codon (nonsense mutation) because, like indels, nonsense mutations are generally detectable. When considering nonsense mutations, T equals one-third of the number of paths in the mutational target that may generate a stop codon (one-third because each base can mutate by three different paths) T = 66 paths leading to a stop codon in the RT target. Thus, pathf = 3/(7517)(66) = 6.047×10−6, SUBf = 3pathf = 1.814×10−5 per base, and μSUB = SUBf/cn = 9.0704×10−6. Because 2 indels were found, If = 2/(7517)(591) = 4.502×10−7, and μI = If/cn = 2.251×10−7. Hence, μg = (μI+μSUB)G = 0.039.To estimate the rate of spontaneous mutation per genome replication  were detected among 112 sequenced sub-isolates.  Thus, SUBf = 9/(112)(591) = 1.36×10−4, μSUB = SUBf/cn = 6.80×10−5, and μSUBg = μSUBG = 0.287. This value is greater than the corresponding value from the nonsense-mutation method by 7.4-fold and may, as discussed later, signal the impact of transient hypermutation.In addition to the primary mutations detected by their phenotypes, some hitchhiking mutations were found. These secondary mutations may be used for an independent estimate of μIN and RTSUB using the results of the single-burst reversion tests. First, some definitions are needed: the number of cultures = C; the average number of infected cells per tube = N; the average burst size = B; the number of initial [(+)-strand→(−)-strand] copies = c1 with an error rate μ1 per copy; the number of succeeding [(−)-strand→(+)-strand] copies = c2 with an error rate μ2 per copy and a burst size B = c2 that ignores unpackaged genomes; and there are n = 2 two rounds of replication per infection. Then the average total number of mutational events per infected cell will be c1μ1+c2μ2; however, these components cannot be disentangled with our data, so we will assume that c2μ2≫c1≥1 , in which case the average total number of mutations per infected cell will be c2μ2 = Bμ2.Mutation rates can also be estimated for the reversion of the mutants RTm− where m is the average number of mutational events per culture NB, whence μ2≈μ = m/NB. For RTIN, the fraction of null tubes was 31/239, m = 2.04, N≈4560 infected cells per tube, and B = 328±93 , so that μ(RTIN) = (1.37±0.39)×10−6. For RTSUB, the fraction of null tubes was 238/498, m = 0.738, N≈35, B = 859±165 , and μ(RTSUB) = (2.46±0.47)×10−5. The ratio μ(RTSUB)∶μ(RTIN)≈18 which, given the indel sample size of 2, agrees well with the corresponding ratio of the two kinds of mutations (substitutions and indels) in the spectrum (43∶2≈22) or by rate (9.07×10−6)∶(2.25×10−7)≈40).For a set of cultures of which some contain 0 mutants, the fraction of null tubes is ef/2 but, as directly above, to assume that all detected mutations arose in the second round of replication, those arising in the first round being too infrequent to be readily observed, in which special case, μ = f as above. Here, f is simply the sum of all observed RT+ revertants divided by all the Qß progeny in all tubes, NBC. For RTIN, the total number of revertants was 510 (IN) = 510/(4560)(328±93)(239) = (1.43±0.40)×10−6, a value close to the null-class value because of the excellent agreement between the observed distribution and the Poisson expectations  = 446/(35)(859±165)(498) = (2.98±0.58)×10−5, again a value close to the null-class value but slightly higher due to the occurrence of a small excess of plates with larger numbers of revertants compared to the expectations of the Poisson distribution (SUB mutated codon (UAG) may change producing an RT+ revertant is not known, the estimated μ(RTSUB) is an upper limit corresponding to 8 paths or 2⅔ substitutions.Another way to estimate these reversion rates is to use μ =  was 510 , so thatctations . For RTS was 446 , so thatribution . BecauseRT and genome base compositions are indistinguishable . The spectrum, based on 45 single-base changes, is a mixture of 32 primary mutations plus 11 secondary mutations found hitchhiking on some primary mutations, plus 2 single synonymous mutations (at target sites 18 and 294) arising during sequencing that showed no primary mutation. This spectrum has three defining characteristics. One is its strikingly low frequency of indels, only 2 among 30 RT mutants and 45 mutations, thus representing only about 4% of the total mutations, while in spectra from several DNA-based microbes , indels comprise about 40% of the mutations  of indels over substitutions, similar numbers of transversions (6) and transitions (5), and a remarkably high frequency (9/23) of mutants with multiple mutations (“multiples”) c≈6. In this study, only mutants carrying lethal mutations were recovered. Thus, if many of the TMV base-substitutions were leaky, then, given c≈6, the high frequency of indels might have reflected their fully mutant phenotypes in contrast to the often leaky substitutions; however, although the TMV target sequence contained 115 paths to stop codons, no nonsense mutations were recovered in the small sample of substitutions. Perhaps some other factor impinged on this system, such as photodynamic mutagenesis.The first, using (+)-strand tobacco mosaic virus (TMV) and a target-complementation system Another spectrum, obtained in a mutation-accumulation experiment using almost the entire genome as a mutational target for the dsRNA phage φ6, also exhibited a strong transition∶transversion bias (46∶5 = 9.2) and only one indel in trans, was probably contaminated with mutations arising during reverse transcription and PCR amplification of the isolated virus, with no way to sort out which mutations were of viral and which of processing origin because the existence of any relation between the detected mutations and a mutant phenotype was not examined.A (+)-strand tobacco etch potyvirus spectrum in vivo based on deep sequencing of plasma samples from untreated patients revealed an approximately 75-fold ratio of transitions to transversions with all four transitions present at similar frequencies, whereas kinetic studies in vitro of the viral replicase revealed a strong bias in favor of G•U and U•G mismatches For the (+)-strand hepatitis C virus, mutation sampling Taken together, the informative parts of these spectra indicate that riboviral mutation spectra differ from those characteristic of DNA viruses and cellular organisms in displaying many more transitions than transversions and an even smaller proportion of indels.With the aims of determining the way in which mutations accumulate during riboviral replication and estimating the rate of spontaneous mutation per genome replication, we investigated the mode in which Qß replicates its genome. Results from two independent single-burst reversion tests indicated that this mode is essentially linear, with the genome of each Qß progeny resulting from only two replications: from the original parental (+) strand to a (−) strand and then to a new (+) strand. Our results further suggest that most replication errors occur during the second round of replication, which in turn reveals the specific mismatches that produced the substitutions in the mutational spectrum.RT+ revertants deviated significantly from the expected Poisson distribution for RTSUB but not for RTIN. With no reason to suspect that the two strains replicate their genomes differently, this discrepancy may reflect intrinsic differences between their reversion targets. The reversion target in RTIN is the same in both rounds of replication, while reversion in RTSUB may occur through up to 8 different single-base-substitution pathways in each round of replication. Thus, reversion rate asymmetries between the two rounds of replication may be anticipated for RTSUB, allowing some reversion to occur during the first round of replication and thus producing some revertant clones of size >1 during the second round.An interesting result is that the distribution of i.e., revertants) differed somewhat from the expected Poisson for a linear mode of replication, suggesting an exponential component in the replication dynamics that was estimated to generate ≈1% of the total progeny IN, and RTSUB. In a log-log plot, exponential replication will display a linear relationship between the cumulative distribution of mutants and the number of mutants per class, with a slope close to −1. In linear replication, however, the plot will not be linear and the slope for the cumulative distribution will be steeper because most mutants arise in clones of size 1. In agreement with this reasoning, the data for T2, which replicates exponentially r and the w mutants and excluding all classes containing ≥16 mutants , while the plots for φ6, RTIN, and RTSUB display nonlinear relationships.The mode of genome replication in riboviruses has been addressed in only a few instances. Using the single-burst reversion test, a predominantly linear mode was reported for the phage φ6 in silico modeling of the optimal riboviral replication strategy in response to the error rate and the availability of resources, among other parameters SUB revertant distribution may depart from a Poisson distribution mostly due to asymmetries in the reversion rates at the first and the second rounds of replication.In a recent report e.g., Overall, the empirical data gathered to date on the riboviral mode of replication indicate that, regardless of the single- or double-stranded genome structure of the virus, the strategy of preference is mainly linear. The advantages that this mode of replication may confer to riboviruses over an exponential mode have been evaluated previously e.g., .g). The first is based mainly on the small set of three nonsense mutations detected among 30 RT mutants. Because many base substitutions do not produce a detectable phenotype, the estimation of the μSUB fraction of μg = (μSUB+μIN)G from the frequency of nonsense mutations is a preferred method because nonsense mutations are highly detectable and their target size is easy to determine from the codon composition of the mutation target. However, this method has two drawbacks: nonsense mutations are typically a small fraction of all substitutions, so that sufficient mutants must be harvested and sequenced for a reliable estimate g = 0.039 per replication or about 0.08 per infection cycle. For this nonsense-based estimate of μg, RT mutants were collected after one-step growth of wt Qß, so that c = 1 in the calculations. While some prior RT mutations may have arisen during the growth of the wt Qß stocks in non-complementing NR16205 lawns, lethal indels and nonsense mutations would have been subjected to strong negative selection. In some riboviruses, mutants bearing lethal mutations can grow in the presence of complementation in trans provided by a plasmid  or by a gene inserted into a host chromosome  of the RT− mutant will be 0.50 per infection cycle. Applying the method described in Burch et al. g = 0.039, the probability of loss of an RT− mutant with s≥0.50 arising in the first infection cycle of wt Qß on a host lawn would be ≥42% at the end of the growth phase ; then μINg = (4217/4)(1.37×10−6) = 0.0014. For RTSUB, μtarget = 2.46×10−5 and the potential number of mutating bases is 3; then μSUBg = (4217/3)(2.46×10−5) = 0.035. The sum of the indel and the substitution rates is μg = 0.036 (0.041 if the indel reversion target size is taken as 1), a value (perhaps deceptively) close to that of μg = 0.039 calculated from the spectrum.The second method for estimating μg applies only in cases where the mutations are not required to produce a mutant phenotype, which can arise when a target is sequenced without regard to phenotype  or when, as in the present case, hitchhiker mutations arise secondarily to and in combination with a driver mutation, the target then consisting of the entire sequence of the mutation reporter. Hitchhikers could arise during any of the roughly 3 infection cycles that generate a Qß plaque but, in order to be detected, most would have to arise in the first cycle with μg = 0.287. This value may be an underestimate because the low ratio (6/7) of missense mutations to synonymous mutations among the secondary RT mutations suggests significant selection against missense mutations during plaque growth even in RTH lawns; if the hitchhikers were a random set, then missense mutations would comprise about ¾, or 9.75, of 13 substitutions. In fact, RTIN has an average burst size in RTH cells that is 2.9-fold smaller than that of wt Qß, a difference that implies a selection coefficient of s≈0.65 per infection cycle. An RT mutant with s≥0.65 arising with μg = 0.287 in the first infection cycle on a RTH lawn would have a ≥40% probability of being lost by the end of the growth phase  but all were synonyms, so that replicase mutators were apparently not impacting our set of RT mutations. Instead, the excess of secondary mutations among our RT mutants may have arisen by the action of an abnormal replicase ß subunit produced by an error of translation or protein conformation.The presence of more mutants with multiple mutations than expected from a random distribution is remarkably widespread among DNA and RNA genomes and is probably more often due to transient hypermutation caused by some temporary perturbation of replication-fidelity factors than due to mutator mutations g was obtained by the nonsense-mutation method. While the rate obtained from the reversion tests was similar, its accuracy depends on the extent to which the two mutants fairly sample the whole genome, and the similarity may have been fortuitous. Both selection and transient hypermutation may have played an important role in the production of the RT mutations considered in the third method. Unfortunately, even our favored μg estimate is based on small samples of mutations (3 nonsense and 2 indels), which enlarges the margin of potential sampling error. When our first and second μg estimates are combined with the fraction (0.4) of random mutations that are lethal for the (−)-strand-RNA vesicular stomatitis virus RT mutants, in close agreement with the 30 observed and providing modest further support for μg≈0.04.Among the three values, our best estimate of μWhile the mutation rates per genome replication estimated here and reported for TMV IN mutant carries a tandem duplication of 2158-UUAA-2161 that corresponds to 416–419 in the target sequence. Cell transformations with the plasmids were performed using CaCl22 and 100 µg/ml trimethoprim (TMP), while NR16205 cells were grown in LB containing 15 µg/ml tetracycline. Cells and phages were plated using LB bottom agar with 2.0% Bacto agar. The top agar was always made up in distilled water. For counting plaques or scoring mutants, the top agar contained 0.4% Sigma-Aldrich Noble agar; for other uses, it contained 0.8% Bacto agar. All growth was at 37°C.Plasmids and bacterial strains are listed in 600≈0.5 (108 cells/ml) at a multiplicity of infection (MOI)≈0.01 for 20 min at room temperature, centrifuged to remove non-adsorbed phages, resuspended, and serially diluted in LB+TMP. Samples diluted 103- and 105-fold were held for 3 h at 37°C with gentle shaking, and 100-µl aliquots were removed from each dilution every 10 min and plated with RTH cells. Plates were incubated overnight and the follow-on titers were used to estimate Qß densities over time. Three one-step growth experiments were conducted in parallel for each wt Qß isolate used to generate one-step lysates. Visual inspection of the resulting curves sufficed to determine the time (≈75 min) for Qß to complete one infection cycle in RTH cells. These one-step curves were also used to estimate the burst size of wt Qß in RTH cells according to the protocol detailed for RTIN and RTSUB (see NR16205 cells were transformed with pQßm100 (which expresses wt Qß) and plated on NR16205 lawns to yield wt Qß plaques, which were independently harvested into tubes containing 1 ml D broth  and 25 µl of chloroform. For one-step growth curves in RTH cells, 10 µl of phage suspension from a wt Qß isolate was mixed with 1 ml of cells at ODTSUB see .RT+ revertants among RT− bursts was monitored as in a previous study RT− mutants  as above and one-step lysates were recovered by adding chloroform after 75 min of growth. Samples from the lysates were plated on RTH lawns at ≈70 plaques per plate and well-isolated plaques were independently sampled into 96-well plates containing 0.6 ml D-broth per well (reserving six un-inoculated wells as cross-contamination controls). For each of four independent lysates, three different rounds of 630 isolations each were performed. In each round, a control plate containing 8 wt and 82 RTIN isolates was also established to confirm the ability of RTH cells to complement −RT mutants and the inability of any RTH cells remaining in the isolates to grow in LB supplemented with tetracycline. Isolates were spotted in parallel on lawns of NR16205 and RTH cells using a 6×8-array replica plater. After a few losses, a total of 7517 plaques were tested. Isolates that grew poorly in NR16205 cells were re-tested in both bacterial strains and the RT-coding genes of two independent sub-isolates per putative RT mutant were sequenced. After this first round of sequencing, two additional sub-isolates as well as the original isolate were sequenced for each verified RT mutant. The original wt Qß isolate used to develop each lysate and two sub-isolates of it were also sequenced.To limit the number of infection cycles to one before seeking spontaneous mutants, 600≈0.5) mixed with phages at MOI≈0.1 in Noble top agar. After overnight incubation, the plates were covered with 7 ml of SM buffer with gelatin g for 10 min. The supernatant was supplemented with polyethylene glycol (PEG 8000) to 10% w/v and NaCl to 1 M, incubated for 1 h on ice, and centrifuged at 3,000 g for 15 min at 4°C 4, 10 mM Tris-HCl, pH 8, and the resulting concentrated phages were used as sources for RNA purification. Phage RNA was isolated using the QIAamp Viral RNA Mini Kit. From the extracted RNAs, 10 µg were then treated with DNase I (New England BioLabs) to degrade residual host DNA. The DNase-treated product was purified using the RNAeasy Mini Kit. From the purified RNA, 1 µg was subjected to reverse transcription with the Omniscript RT Kit and about 25 ng of the RT product was amplified with PfuTurbo DNA polymerase (Stratagene). PCR products were confirmed by agarose gel electrophoresis, purified with the QIAquick PCR Purification Kit, and sequenced using BigDye Terminator v3.1 (Applied Biosystems). All kits were purchased from Qiagen and were used according to the manufacturer's recommendations. Sub-isolates showing secondary mutations were subjected to a second round of RT, amplification and sequencing. The primers utilized in the RT, PCR, and sequencing reactions and the PCR cycling parameters are listed in Plate lysates were prepared from RTH cells  of the base substitutions observed in RT with the expected content according to the base composition of the whole gene. When applying this last test, each upstream position (from +1 to +6 or +7) was considered as an independent replicate. All tests were performed as per Sokal and Rohlf The Figure S1RT mutation with selection coefficient s is lost during plaque growth in a host lawn. The black line represents the estimations for μg = 0.039 while the gray line represents the estimations for μg = 0.287.Probability that a new (TIF)Click here for additional data file.Figure S2IN and RTSUB. Three independent curves were obtained per RT mutant. In all cases, the first bursts appeared between 30 and 40 min after infection. If the 20 min allowed for adsorption are also considered, it means that Qß requires a minimum of 50 to 60 min to complete an infection cycle in RTH cells. Thus, if any of the progeny released in the first bursts would have immediately infected a new cell, the first second-generation bursts might have been expected 100 min after the first infection. Indeed, the curves show a slight increase of Qß density at that time. For this reason, values collected 100 min after infection (empty symbols) were not considered in the curve-fitting analyses conducted to characterize RTIN and RTSUB single-burst dynamics. Squares represent outliers that were automatically excluded from the analyses, and the resulting fitted curves are shown as dashed curves. PFU = plaque-forming units. See One-step curves for RT(TIF)Click here for additional data file.Table S1IN and RTSUB one-step curves shown in Parameters of the sigmoidal curves fitted to the RT(DOC)Click here for additional data file.Table S2Primers and PCR cycling parameters for amplifying and sequencing.(DOC)Click here for additional data file.


Species-related Hg variations were highly and positively linked to feather δ15N values, thus highlighting the occurrence of efficient Hg biomagnification processes within subantarctic marine trophic webs. By contrast, Hg contamination overall correlated poorly with feeding habitats, because of the pooling of species foraging within different isotopic gradients corresponding to distinct seabird habitats . However, when focusing on oceanic seabirds, Hg concentration was related to feather δ13C values, with species feeding in colder waters  south of Kerguelen Islands being less prone to be contaminated than species feeding in northern warmer waters . Within the context of continuous increase in global Hg emissions, Kerguelen Islands that are located far away from anthropogenic sources can be considered as an ideal study site to monitor the temporal trend of global Hg contamination. The present work helps selecting some seabird species as sentinels of environmental pollution according to their high Hg concentrations and their contrasted foraging ecology.Using top predators as sentinels of the marine environment, Hg contamination was investigated within the large subantarctic seabird community of Kerguelen Islands, a remote area from the poorly known Southern Indian Ocean. Chicks of 21 sympatric seabirds presented a wide range of Hg concentrations, with the highest contaminated species containing ∼102 times more feather Hg than the less contaminated species. Hence, Kerguelen seabirds encompass the whole range of chick feather Hg values that were previously collected worldwide in poorly industrialized localities. Using stable isotopes, the effects of foraging habitats (reflected by δ For example, (i) benthic foragers should have relatively high feather Hg concentrations in relation to the substantial production of Me-Hg in coastal marine sediments 15N) should show the highest feather Hg concentrations. Finally, the longer the chick rearing period, the higher the chick feather Hg concentrations should be, because much of the dietary Hg accumulated in soft tissues is mobilized and excreted into growing feathers In a first descriptive step, Hg was determined in 21 seabird species to assess contamination levels of marine ecosystems within the poorly known southern Indian Ocean. In a second explanatory step, the effect of differences of seabird foraging ecology on feather Hg concentration was tested, because ingestion of food is the main route of Hg exposure in birds Most previous investigations on pollutants in birds were conducted on adults that present some disadvantages related to their foraging areas, moult schedule and migration patterns. Instead, we focused on chicks as indicators and sentinels of contamination Animals were cared for in accordance with the guidelines of the ethics committee of the Institut Polaire Français Paul Emile Victor that approved fieldwork in the present study .Fieldwork was carried out from 2003 to 2012 on Kerguelen archipelago , which is located in the southern part of the Subantarctic Zone, in the immediate vicinity of the Polar Front −1 dry mass). Our measured values were 0.24±0.01 µg•g−1 dry mass, n = 56. Blanks were analysed at the beginning of each set of samples and the detection limit of the method was 0.005 µg•g−1dry mass.Prior to chemical analysis, all body feathers were cleaned of surface lipids and contaminants using a 2∶1 chloroform: methanol solution for 2 min followed by two successive methanol rinses. They were then cut with scissors into small fragments. A first sub-sample of homogenized feathers was oven dried for 48 hr at 50°C and then analyzed in an advanced Hg analyzer spectrophotometer (Altec AMA 254). Hg determination involved evaporation of Hg by progressive heating until 800°C under oxygen atmosphere for 2′30 min and subsequent amalgamation on a gold trap. The net was heated to liberate the collected Hg that was measured by UV atomic absorption spectrophotometry. Samples were analysed for total Hg, which approximates the amount of Me-Hg since essentially all Hg in feathers is under organic form 2 for δ13C and δ15N, respectively. Replicate measurements of internal laboratory standards (acetanilide) indicate measurement errors <0.10‰ for both δ13C and δ15N values.A second sub-sample of homogenized feathers was weighed (∼0.3 mg) with a microbalance and packed into a tin container. Relative abundance of C and N isotopes were determined with a continuous flow mass spectrometer (Thermo Scientific Delta V Advantage) coupled to an elemental analyzer (Thermo Scientific Flash EA 1112). Results are presented in the δ notation relative to Vienna PeeDee Belemnite and atmospheric NStatistical tests were performed using R 2.7.1 13C and δ15N values, and the duration of the chick rearing period) were tested using Pearson correlations. In multivariate analyses, the influence of species and continuous explanatory variables on feather Hg concentrations were investigated using General Linear Models (GLMs). Feather Hg concentrations were log transformed and the models were constructed with a normal distribution and an identity link function. Explanatory variables were defined as follows: species as a factor, and feather δ15N, δ13C values, and the duration of the chick rearing period as covariates. The influence of the sampling year on Hg concentrations was not incorporated in model selection, since, as most species were sampled in only one year  was estimated following Johnson and Omland iw can be interpreted as approximate probabilities that the model i is the best one for the observed data, given the candidate set of models. Model fit was assessed by a chi-square goodness-of-fit test 2adjR was calculated for each model Biologically relevant models were constructed by incorporating the different variables and their interactions. Continuous variables that were significantly correlated were not included in the same models. The most parsimonious models were selected according to the bias-adjusted Akaïke’s Information Criterion (AICc), which is a small-sample bias adjustment H = 260.23, P<0.001, n = 21). Mean Hg concentrations ranged from 0.05±0.01 to 5.31±1.12 µg•g−1 dry mass in South-Georgian diving-petrels and northern giant petrels, respectively .Univariate analysis showed that total Hg contamination varied widely within the seabird community, with chick feather Hg concentrations differing significantly between species , while feather Hg concentration was highly significantly and positively correlated with δ15N values . Feather Hg concentration was also significantly and positively related to the duration of the chick rearing period . Furthermore, feather δ15N and δ13C values were positively correlated , and they were significantly related to the duration of the chick rearing period . When focusing on oceanic seabirds  a highly significant and positive correlation was found between feather Hg and both δ13C  and δ15N values   .15N  and were significantly and positively related to their δ15N values . The second-ranked model included an effect of species, δ13C and their interaction, but it had a low likelihood when compared to the first-ranked model  and foraging habitats (δ13C) on chick feather Hg concentrations, which, by contrast, are little explained by the duration of the chick rearing period. However, univariate analysis showed a positive relationship between Hg contamination and the duration of the chick- rearing period, the most likely explanation being that assimilated Hg accumulates during chick growth over weeks and months and is ultimately excreted in newly grown feathers at the end of the period 15N likely results from the longer chick rearing period of large seabirds  that feed at higher trophic positions than smaller species with shorter growth period (e.g. petrels).Statistical analyses pointed out the important effect of species, feeding habits  more feather Hg than the less contaminated species. Both the lowest and highest Hg values occurred in flying birds, with contamination levels of the flightless penguins ranging from low to intermediate values. No other feather Hg concentrations are available from Kerguelen seabirds, but a preliminary analysis conducted on internal tissues of adults of five species of zooplankton-eating petrels −1 for common terns in the German North Sea). Elsewhere, however, Hg concentration ranges from 0.05 to 5.6 µg•g−1 . This range is remarkably similar to that from the present investigation, indicating that seabirds from only one location (Kerguelen) encompass the whole range of values that were collected worldwide in poorly industrialized areas. Consequently, comparison of Hg levels between distant locations using seabirds as sentinels of environmental contamination necessitates collecting feathers from many species, because a small subset could not be fully representative of the whole seabird assemblage, and thus of the surrounding marine environment.A review of the existing literature on seabird chicks  shows th−1) that also includes albatrosses, i.e. the species group that contains the highest feather Hg concentrations among seabirds −1) and La Réunion  to 14.2‰ , which, assuming a trophic enrichment factor of 2.7‰ for carnivorous organisms As expected, the overall statistical analysis indicated a δrds only . The fea15N, and, to a lesser extent, δ13C values . The skua Hg content is also in agreement with feeding on blue petrels, because petrel muscle contains disproportionately more total Hg than fish and crustaceans The subantarctic skua was clearly an outlier species within the Kerguelen seabird assemblage, with chick Hg concentration being high when compared to feather δC values . At the 13C effects on feather Hg concentrations within the Kerguelen seabird community, and, in multivariate analysis, species and δ15N produced the best model. This result seems to contradict our hypothesis that foraging habitat should play an important role in shaping seabird Hg contamination. However, the large range of seabird δ13C values indicates that, again, species that forage within different isoscapes were pooled, thus resulting in a confounding effect 13C values ≥ −18‰ were all neritic species feeding either along the shoreline (the kelp gull) or on pelagic (the southern rockhopper penguin and common diving petrel) or benthic prey (the gentoo penguin and Kerguelen shag)  . The rel13C values in oceanic seabirds. Taken into account the latitudinal δ13C gradient within the Southern Ocean At a larger spatial scale, the importance of foraging habitat is exemplified by the positive correlation between feather Hg concentrations and δThe pattern of Hg contamination of Kerguelen seabirds is remarkable due to its wide range of values, but the circumpolar annular structure of the Southern Ocean


Twenty-one patients  who had previously undergone cardiopulmonary exercise testing (CPET) pre- and 6 months postoperatively underwent maximal exercise testing 49 ± 15 months postoperatively using an electrically braked bicycle ergometer. Breathing gases were analysed and the patients' physical fitness levels categorized according to Åstrand's and Wasserman's classifications. Mean peakVO2 was 22·8 ± 5·1 ml × kg−1 × min−1 at the 49-month follow-up, which was lower than at the 6-month follow-up . All but one patient presented with a physical fitness level below average using Åstrand's classification, while 13 patients had a low physical capacity according to Wasserman's classification. A significant decrease in peakVO2 was observed from six to 49 months postoperatively, and the decrease was larger than expected from the increased age of the patients. CPET could be helpful in timing aortic valve surgery and for the evaluation of need of physical activity as part of a rehabilitation programme.Exercise testing is underutilized in patients with valve disease. We have previously found a low physical work capacity in patients with aortic regurgitation 6 months after aortic valve replacement (AVR). The aim of this study was to evaluate aerobic capacity in patients 4 years after AVR, to study how their peak oxygen uptake (peakVO The natural history of chronic aortic regurgitation (AR) is characterized by insidious development and progression . SymptomAccording to current recommendations (2) and physical fitness (2 following AVR in patients with chronic AR.Cardiopulmonary exercise testing (CPET) has been used for a long time in healthy adults and athletes, for determining peak oxygen uptake  or any other significant heart valve disease at preoperative echocardiographic examination, acute endocarditis or coronary heart disease .Twenty-six patients, fulfilling the study entry criteria, who had undergone CPET before and 6 months after their AVR . The pneumotachograph and gas analysers were calibrated prior to each test.The testing was carried out with the patients in a sitting position, using an electrically braked bicycle ergometer  and with continuous electrocardiographic monitoring . The patients breathed through an open, low-resistance mouthpiece with their nostrils clamped. Exhaled airflow was measured indirectly by pressure gradients using a linear pneumotachometer , and OThe exercise protocol was chosen individually at the time of the preoperative CPET and consisted of an initial workload of 30–100 Watts for 5–6 min, followed by a continuous increment in workload of 10–20 Watts per minute. Each patient underwent the same protocol at all follow-ups. Patients were instructed to pedal with a constant speed of 60 revolutions per minute until exhaustion. Systolic blood pressure was measured non-invasively every third minute during the test, while perceived exertion, dyspnoea and chest pain were assessed using the Borg scales .2 values were compared with a population-based reference material  was used.Data are presented as mean ± standard deviation (SD), and normality was assessed with the Shapiro–Wilk's test. Means were compared with paired Patient characteristics are presented in 2 was 0·2 ± 0·3 l × min−1  lower, and weight-indexed peakVO2 was 3·1 ± 3·5 ml × kg−1 × min−1  lower at the second follow-up. This corresponds to an annual decrease in peakVO2 of 2·4% in l × min−1 or 3·4% in ml × kg−1 × min−1 per year. This decrease was larger than expected from the increase in patient age, according to studies of longitudinal changes in peakVO2  presented with a decrement in weight-indexed peakVO2. The mean ventilatory efficiency  was within normal range (Cardiopulmonary exercise testing data are presented in 2 (ml × kg × min−1) that was in the lowest 5% range according to the reference material by According to Åstrand's classification, all but one patient had a weight-indexed, age-adjusted physical fitness below average . No stat2 at the 49-month follow-up . Furthermore, no significant differences for echocardiographic variables were found between patients with ‘low’ and ‘normal’ physical fitness according to Wasserman's classification.There was no correlation between systolic left ventricular function at rest (i.e. ejection fraction) and peakVO2 changes in patients with AR following AVR are scarce  and weight-indexed (ml × kg−1 × min−1) measures, which rules out that the decrement was solely an effect of the increased body mass of the patients at the late follow-up.After reporting previous findings (2 between patients and healthy controls 1 year after AVR, and in a subgroup of patients, peakVO2 was significantly higher postoperatively than preoperatively.This is in contrast with the results of 2. To our knowledge, deterioration in peakVO2 following surgery has not been described by others, although the follow-up period in the present study was longer than seen elsewhere.Two studies (Several factors that affect aerobic capacity may contribute to this difference and need to be taken into consideration. First, the data from early and late follow-up must be comparable, which was confirmed by similar respiratory exchange ratios, well above one, at both CPETs .2 decreases with age (2 in the lowest 5% range as calculated by algorithms from Second, peakVOwith age , and ourwith age . Howeverwith age , and a t2 remains unchanged owing to peripheral compensatory mechanisms (The majority of our patients were on cardiac medication, including β-blockers, with no significant differences in reported use of any medication between follow-ups. Although β-blockers decrease maximal heart rate during work, it is unclear whether, and to what extent, they reduce physical work capacity in patients with AR. In patients with coronary artery disease, peakVO2 in healthy individuals is the level of physical activity (2 in our patients was, at least in part, attributable to a more sedentary lifestyle postoperatively. 2 between a group of healthy controls and patients who had received aortic heart valve prosthesis 1 year postoperatively. This could indicate that the heart valve or the open heart surgery per se did not affect peakVO2. However, of the patients in their study, only one presented with AR preoperatively, and the patients were considerably smaller than in the current study and therefore had lower reference values than our patients.One of the important determinants of peakVOactivity . The parFinally, a subnormal postoperative left ventricular function cannot be ruled out despite the normalization of the recorded echocardiographic parameters, which were comparable in Wasserman's classes ‘low’ and ‘snormal’, and without statistically significant in-between group differences.In contrast to the solid evidence for beneficial effects of exercise training in patients with coronary artery disease (2 with a three (2 and normalized left ventricular function, assessed by echocardiography, within 1 year (In studies published more than 20 years ago , a positThe conflicting results from previous studies may possibly be explained by diversity in length or character of the training protocols studied. Unfortunately, details of training programmes are sparsely presented, and no study compares different training modalities, making it troublesome to recommend a certain exercise regimen. Furthermore, the groups studied are often heterogenic, with several valvular pathologies intermixed. The date of the studies ranges from 1980 (2 was observed from six to 49 months postoperatively, in patients operated upon for chronic AR representing an impaired aerobic capacity. Using CPET as part of the preoperative screening and follow-up could be helpful in timing aortic valve surgery and for the evaluation of need of physical activity as part of a rehabilitation programme aiming at decreasing morbidity and improving quality of life in patients with AR undergoing AVR.A significant decrease in peakVO


BIN1, CLU, CR1 and PICALM that show replicable association with risk for disease. We have thoroughly sampled common variation in these genes, genotyping 355 variants in over 600 individuals for whom measurements of two AD biomarkers, cerebrospinal fluid (CSF) 42 amino acid amyloid beta fragments (Aβ42) and tau phosphorylated at threonine 181 (ptau181), have been obtained. Association analyses were performed to determine whether variants in BIN1, CLU, CR1 or PICALM are associated with changes in the CSF levels of these biomarkers. Despite adequate power to detect effects as small as a 1.05 fold difference, we have failed to detect evidence for association between SNPs in these genes and CSF Aβ42 or ptau181 levels in our sample. Our results suggest that these variants do not affect risk via a mechanism that results in a strong additive effect on CSF levels of Aβ42 or ptau181.Recent genome-wide association studies of Alzheimer's disease (AD) have identified variants in  APP) gene and the presenilin 1 and 2 genes (PSEN1 and PSEN2 respectively). While only apolipoprotein E (APOE) has been clearly identified as a susceptibility gene in the more common form of AD, data from recent genome-wide association studies has implicated several other common risk variants BIN1), clusterin , complement component receptor 1 (CR1) and phosphatidylinositol binding clathrin assembly protein (PICALM) have already been reported to show replicable association with risk for AD Alzheimer's disease (AD) is the most common form of dementia and is neuropathologically characterized by extracellular senile plaques containing amyloid beta (Aβ) and intracellular neurofibrillary tangles containing hyperphosphorylated tau protein. Mendelian forms of the disease are caused by mutations in the amyloid precursor protein  and tau phosphorylated at threonine 181 , as endophenotypes for genetic studies of AD 42 and/or ptau181 levels. In cases where risk variants have already been identified this approach allows us to validate or generate hypotheses regarding the biological mechanism of risk. We can also take advantage of the increased statistical power and decreased heterogeneity of the biomarker phenotype relative to qualitative clinical diagnosis to identify novel variants that affect biomarker levels and aspects of disease CALHM1 on CSF Aβ42 levels MAPT and PPP3R1 that are associated with both biomarker levels and rate of progression of AD 42 levels for variants in CLU and CR1 and to attempt to generate biological hypotheses of risk mechanism for BIN1, CLU, CR1 and PICALM.In our previous work we have shown the utility of using two well-established cerebrospinal fluid (CSF) biomarkers for AD, 42 amino acid fragments of amyloid beta (AβCSF for the Washington University in St. Louis (WU) series was collected from 407 individuals after overnight fasting. CSF collection and processing as well as CSF biomarker measurements were performed as described previously http://adni.loni.ucla.edu). The Principal Investigator of this initiative is Michael W. Weiner, M.D., VA Medical Center and University of California – San Francisco. ADNI is the result of efforts of many co-investigators from a broad range of academic institutions and private corporations, and subjects have been recruited from over 50 sites across the U.S. and Canada. The initial goal of ADNI was to recruit 800 adults, ages 55 to 90, to participate in the research — approximately 200 cognitively normal older individuals to be followed for 3 years, 400 people with mild cognitive impairment (MCI) to be followed for 3 years, and 200 people with early AD to be followed for 2 years.” For up-to-date information see www.adni-info.org. Sample characteristics, including age, clinical dementia rating, gender, APOE ε4 status and mean and standard deviation of the CSF biomarkers can be found in http://adni.loni.ucla.edu/). The genotypes from this study will be provided upon request to the authors.Data from 257 samples with biomarker data and either AD or cognitively normal diagnoses from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were also used. Data used in the preparation of this article were obtained from the ADNI database . It is also possible that the inclusion of more AD cases and older individuals in the ADNI data or differences in the number of freeze thaw cycles prior to analysis (1 cycle for WU samples and 2 cycles for ADNI samples) accounts for some of the variation in the biomarker measurements. CSF biomarkers in the two samples show association with similar covariates 2 cutoff of 0.8 was applied. A total of 283 SNPs were selected (see For each gene we downloaded the list of SNPs in the gene region (and approximately 500 kb of flanking sequence) from HapMap. These SNPs were then evaluated for putative functional effects using SNPseek and Pupasuite. SNPs with putative function and SNPs that showed association in the original published reports were designated as forced tags in the tagging algorithm in Haploview when an rhttp://www3.appliedbiosystems.com/cms/groups/mcb_support/documents/generaldocuments/cms_058198.pdf), a means of running multiple TaqMan assays together on one chip. 125 ng per sample was added to the reaction mix and spread over 64 assays, the chips were thermocycled as described in the linked protocol and imaged. Results were analyzed using the Applied Biosystems Genotyper software (https://products.appliedbiosystems.com/ab/en/US/adirect/ab?cmd=catNavigate2&catID=607267&tab=Literature). Samples were analyzed on a plate-by-plate basis in the context of all the samples to eliminate variation in calls between plates. SNPs that deviated from HW equilibrium , had a genotyping rate lower than 95% or a minor allele frequency of less than 5% were removed. Samples with a genotyping rate lower than 95% were also removed. After application of these quality control criteria there were 664 samples and 233 SNPs.Genotyping was performed using Applied Biosystems OpenArray technology  as significant covariates to be included in the model. Gender was not significantly associated with CSF ptau181, and was not included in the model. Association with genotype was tested using ANCOVA after adjustment for these covariates. For the combined analysis we also included site as a covariate. All analyses were also performed without CDR as a covariate but there were no qualitative differences in the results.Ptau42 levels were not normally distributed even after a variety of transformations were applied. For this reason Aβ42 analyses were performed using permutation based testing in PLINK (1 million permutations) APOE ε4 genotype as covariates; the ADNI model included CDR and APOE ε4 genotype. Age was not significantly associated with biomarker levels in the ADNI sample (due to lack of variation in age in the ADNI sample) and was therefore not included as a covariate for analyses of that sample alone. Site was included in the combined analysis in addition to age, CDR and APOE ε4 genotype. There were no qualitative differences in the results when run without CDR as a covariate.AβThe alpha level for this study using Bonferroni correction for 233 tests is 0.00021. A less conservative correction using the Eigen values of the SNP correlation matrix to estimate the effective number of tests yielded an adjusted alpha of 0.00022 Haplotype and set-based analyses were performed using PLINK with default settings Power for the overall F test in a one-way, three-group analysis of variance was calculated using proc power in SAS. The effect size, measured in “fold-difference” between the means at which power was estimated at 0.80 was calculated for minor allele frequencies from 0.10 to 0.50 and alpha levels of 0.05 and 0.00021 (the Bonferroni correction for 233 tests) assuming markers do not deviate from Hardy-Weinberg Equilibrium .BIN1. rs3820757 (p = 0.31), rs744373 (p = 0.44) and rs2276582 (p = 0.48) had the smallest p-value for association with CSF Aβ42 levels but did not show statistically significant association in the combined sample . Haplotype analyses also failed to identify significant association with Aβ42 and ptau181.We failed to detect significant association between the CSF biomarker levels and SNPs in ociation . The SNPCLU, which has been implicated in risk for AD, and CSF Aβ42 (p = 0.79) or ptau181 (p = 0.78) levels (42 levels in CLU were rs10216623 (p = 0.011), rs2640734 (p = 0.036) and rs17057419 (p = 0.056); but these p-values do not pass multiple test correction. The top hits in CLU for association with CSF ptau181 were rs2439497 (p = 0.0010), rs2640734 (p = 0.004) and rs576256 (p = 0.0081) in the combined sample. The p-value threshold for Bonferroni correction for the entire study is 0.00021; therefore none of these p-values pass the multiple test correction. Set-based analyses of 57 SNPs from the CLU fine mapping set showed that there was evidence for association with ptau181 levels (p = 0.034). However this p-value is not significant after correction for the 4 SNP sets that were tested. There was no evidence for association in the set-based analyses for Aβ42 levels (p = 1). Haplotype analyses failed to identify significant association with either CSF phenotype.We failed to detect evidence for association between rs11136000 in ) levels  and 4 inCR1 that is implicated in risk for disease from recent GWAS is rs6656401. We failed to detect association between this SNP and either CSF Aβ42 (p = 0.63) or ptau181 (p = 0.52) levels in the combined sample. In CR1 no SNPs were significant with either phenotype . Haplotype analyses failed to detect significant association with Aβ42 and ptau181.The SNP in henotype  and 4 anPICALM SNP identified in the recent GWAS studies showed no evidence of association with either CSF Aβ42 or ptau181 levels (42 levels were rs7113656 (p = 0.0090), rs11234454 (p = 0.010) and rs10792828 (p = 0.011). The top hits for CSF ptau181 levels were rs638509 (p = 0.00098), rs694353 (p = 0.0010) and rs10898433 (p = 0.0012). Set-based analyses of 138 SNPs in the PICALM fine-mapping region failed to detect evidence for association with either Aβ42 (p = 0.56) or ptau181 (p = 0.47). Haplotype analyses also failed to identify significant association with these CSF phenotypes.Rs3851179, the 1 levels  and 4. TPICALM and APOE ε4, in at least one study the effects of risk associated SNPs in PICALM were found to be much stronger in the presence of the APOE ε4 allele APOE ε4 and performed association analyses between PICALM SNP genotypes and CSF Aβ42 and ptau181 in APOE ε4 positive and APOE ε4 negative substrata and using an APOE ε4 by SNP interaction term in the combined sample. We failed to detect statistically significant associations in the APOE ε4 negative and APOE ε4 positive substrata and in the interaction analysis  all SNPs in this study had power estimated at greater than 0.80 for at least a 1.05 fold difference  on CSF biomarker levels if it were present. The lack of significant associations suggests that there is not likely to be a strong additive genetic effect between the SNPs in this study and CSF levels of Aβ42 or ptau181. A recently published GWAS of 17 plasma lipoproteins in a sample of over 17,000 individuals identified 43 associated loci 181 in the CLU gene region. This result, and the lack of signal with Aβ levels, are unexpected given data suggesting additive effects of CLU and APOE on Aβ deposition in mice While there were some suggestive associations of CSF ptau42 and ptau181, variants in these genes may modulate risk for AD through mechanisms that do not directly alter CSF levels of Aβ42 or ptau181. CLU, PICALM and CR1 participate in other processes not related to Aβ or tau aggregation, processing or clearance, and therefore studies of the role of these proteins in the brain may reveal evidence for additional disease mechanisms, which go beyond Aβ or tau accumulation. In fact there are several studies that link these genes with lipid metabolism and inflammatory pathways. Two of the identified AD susceptibility genes  have known functions in the immune system, which suggests a possible role for the immune system in the risk for AD. An alternative interpretation of our results is that, given the lack of association with AβOur study was designed specifically to detect additive genetic effects of common SNPs. Failure to detect significant association in this study design does not rule out, or even directly address, the possibility that these genes harbor rare variation that influence these biomarkers or that common variants in these genes have very small effects on these biomarkers. Finally, this approach may not detect complex, non-additive genetic mechanisms, such as complex gene-gene or gene-environment interactions that may modulate biomarker levels.Table S1181 and Aβ42 levels in the Washington University (WU), Alzheimer's Disease Neuroimaging Initiative (ADNI) and combined sample sets.A complete list of SNPs in the study, position, minor allele frequencies (MAF), and p-values for association with CSF ptau SNPs with values of #N/A failed to meet QC criteria.(DOCX)Click here for additional data file.Table S2Association of SNPs in interaction with APOE ε4 alleles. For each SNP in the PICALM gene region p-values for association with CSF ptau181 and Aβ42 levels for the SNP by presence/absence of the APOE ε4 allele interaction term, association in individuals without an APOE ε4 allele and association in individuals with an APOE ε4 allele are shown.(DOCX)Click here for additional data file.


Hirundo rustica) breed almost exclusively in the Northern Hemisphere. However, since the early 1980's, a small disjunct breeding population has become established in eastern Argentina, presumably by birds previously derived from those breeding in North America. Currently, it is unknown where these individuals go following breeding and how they have adjusted to a reversal in phenology. Their austral wintering period corresponds to the breeding period of the northern ancestral population and so they can potentially return to these more traditional breeding sites or they may occupy other South American wintering regions left vacant by conspecifics returning to the Northern Hemisphere.Barn Swallows  approach to investigate potential wintering areas in Central and South America of individuals breeding in Argentina. Feather isotope values differed from those expected and measured at local breeding sites in Argentina indicating molt after the austral breeding period and away from the breeding grounds. Potential molting origins were identified applying likelihood-based assignment methods to a δ2H isoscape for South America and dichotomous prior information on the distribution of C3 and C4 vegetation types based on modeled vegetation-δ13C values. Barn Swallows now breeding in Argentina have changed their migratory behavior but presumably use the same cues as those used by the ancestral population, molting their feathers during the austral winter, likely in north-eastern South America.We used a three-isotope ( While avian migration systems appear well established, involving the regular periodic movement by individuals of several thousand kilometers Hirundo rustica) in Argentina However, there are generally few opportunities to examine the evolution of such adaptive processes due to the rarity of well-documented cases of new migratory systems in nature. Moreover, until recently, it has been extremely difficult to infer movements of small birds at continental scales due to limitations in conventional approaches to tracking animal movements All animals in this study were handled in accordance with The North American Bird Banding Council guidelines. This work was conducted under all necessary permits for capture and sample collection granted by the correspondent Argentinean wildlife authority in Buenos Aires province (Dirección de Administración de Áreas Protegidas y Conservación de la Biodiversidad).We sampled 100 breeding Barn Swallows during the austral summer (November-January) of 2006 and 2007 at colonies along the Atlantic coast of Buenos Aires province, Argentina. Tail feathers clearly grown prior to breeding were identified based on wear δ2H, δ13C and δ15N analysis at the Stable Isotope Laboratory of Environment Canada, Saskatoon, Canada. The non- exchangeable hydrogen of feathers was determined using the method described by 2 gas derived from high-temperature (1350°C) flash pyrolysis of 350±10 µg feather subsamples and keratin standards using continuous-flow isotope-ratio mass spectrometry. Measurement of the two keratin laboratory reference materials  corrected for linear instrumental drift were both accurate and precise with typical mean δ2H ± SD values of −197±0.79‰ (n = 5) and −54.1±0.33‰ (n = 5), respectively. All results are reported for non-exchangeable H expressed in the typical delta notation, in units of per mil (‰), and normalized on the Vienna Standard Mean Ocean Water – Standard Light Antarctic Precipitation (VSMOW-SLAP) standard scale.All feathers were cleaned of surface oils in 2∶1 (v/v) chloroform:methanol solvent rinse and prepared for δ13C and δ15N analyses, between 0.5 and 1.0 mg of feather material was combusted online using a Eurovector 3000  elemental analyzer. The resulting CO2 and N2 was separated by Gas Chromatograph (GC) and introduced into a Nu Horizon  triple-collector isotope-ratio mass-spectrometer via an open split and compared to a pure CO2 or N2 reference gas. Stable nitrogen (15N/14N) and carbon (13C/12C) isotope ratios were expressed in delta (δ) notation, as parts per thousand (‰) deviation from the primary standards: atmospheric nitrogen and VPDB (Vienna Pee Dee Belemnite carbonate) standards, respectively. Using previously calibrated internal laboratory C and N standards (powdered keratin and gelatin), within runs, precisions for δ15N and δ13C were better than ±0.15‰.For δ2H, δ13C and δ15N values between known breeding grounds  versus unknown wintering grounds using t-tests. Some individuals were sampled for both feathers grown on the breeding and wintering grounds. In those cases, we used a paired t-test to identify differences between growth origins. Multivariate Analysis of Variance (MANOVA) was used to test simultaneously for isotopic differences among feathers using Pillai's trace statistic. All statistical analyses were performed using R Version 2.10.1 We tested for mean differences in feather δ2Hf, δ13C) could have resulted from growth at given locations within the δ2H isoscape of δ13C isoscape of δ2H isoscape corresponding to the growing season of South America δ2H (δ2Hf) isoscape using the empirical equation reported for non ground-foraging Neotropical migrants Naturally molted tail feathers from 100 individuals from Argentina were used to assign Barn Swallows to their molting origins by using normal probability density functions c) among individuals growing their feathers at the same locality for δ2H (σ = 14.4‰) was estimated using the standard deviation of the residuals from the same regression equation reported by δ2Hf isoscape represented a potential origin for each feather sample:c,σc) represents the probability that a given cell (pixel) represents a potential origin for an individual of unknown origin (y*), given the expected mean δ2Hf for that cell (μc) based on the predicted value for that cell within the isoscape, and the expected standard deviation (σc) of δ2Hf among individuals growing their feathers at the same locality.The expected standard deviation  and the rest as “0” (unlikely) n = 84) and those grown locally in Buenos Aires province (n = 16) differed significantly for the three isotopes simultaneously  and for δ2H  and δ15N , but not in δ13C values  when tested separately (n = 16) and known breeding (n = 16) locations collected from the same individuals  as well as in δ2H  and δ15N  but not in δ13C values  (n = 16) formed a tight group , while feathers grown outside of the breeding season (n = 100) were more broadly distributed   . Feather = 2.8‰) . Molt orenezuela .Oceanodroma leucorhoa), a European long-distance migrant which has founded a new breeding population within its wintering range in South Africa Feathers induced to grow by swallows breeding in Buenos Aires province differed isotopically from those grown outside of the breeding season presumably during the austral winter. Thus, the ancestral  molt phenology was replaced by a new  migratory strategy in this newly formed breeding population. Our isotopic assignment of wintering locations corresponded with the northeastern region of South America (specifically northern Brazil, French Guiana, Suriname, Guyana, and Venezuela, areas known to also be frequented by wintering swallows from North America The molt schedule for the new disjunct population of swallows within the annual cycle was the same as that for the ancestral population, namely following breeding and presumably on the austral wintering grounds. Thus, rather than adjusting their molt cycle to new environmental conditions, the Argentinean population presumably used the same cues as those used by the ancestral populations. Molt in birds is triggered by thyroid hormones in turn modulated by photoperiod The broad range of feather isotope values representing the austral wintering period of swallows breeding in Argentina suggest a number of possible molting areas in the southern portion of their breeding range. Indeed, we cannot rule out the possibility that some of the individuals we examined were in fact new arrivals from North America