Tiliqua rugosa) populations was compared between a rangeland environment and cropping environment using linear body size index (LBSI) and haematology. Animals in the cropping site were smaller, suggesting genetic differences as the result of geographical isolation. The animals in the cropping site had a lower LBSI and many were experiencing a regenerative anaemia. The anaemia was postulated to be the cause of the low LBSI. The anaemia appeared to be the result of haemolysis and was likely to be caused by exposure to agricultural chemicals applied in the cropping site but not the rangeland site. Elevated white blood cell counts in lizards in the rangeland site suggested that they were experiencing an inflammatory disease of possible ecological significance. Together, these results demonstrate the value of combining physical and haematological parameters when studying the impact of agricultural practices on wildlife. They also show that reptiles may be useful as sentinel species for livestock and humans.Agricultural practices, including habitat alteration and application of agricultural chemicals, can impact wildlife resulting in their decline. Determining which of these practices are contributing to declines is essential if the declines are to be reversed. In this study, the health of two geographically separated sleepy lizard ( Much is known about habitat fragmentation of agricultural environments and how it negatively affects animal habitats, vertebrate populations  and its A species' decline may reflect threatening processes that are having wider ecosystem ramifications . As canaDespite reports of declines in reptile assemblages , abnormaTiliqua rugosa) has the potential to be an important sentinel of environmental health. This medium-sized lizard occurs throughout southern Australia, has flexible habitat requirements and lives in diverse vegetation types modified by livestock grazing or cereal cultivation [2–1 km2) that overlap during the breeding season (September–December) [°C and then feed mostly on annual forbs, seeds and occasionally on carrion [The sleepy lizard (tivation . It is aecember) . Young aecember)  and refeecember) . They em carrion ,19. LittHaematology is minimally invasive and can be used to monitor the health status of reptiles . With otOur study explores the health of two free-ranging (wild) populations of the sleepy lizard from unimproved rangelands and the nearby ‘intensively managed’, fragmented landscapes of southern Australia's cereal croplands using physical and haematological measures of health. We propose that cropland individuals will display ‘secondary effects’ of cultivation based on compromised health measures  compared to rangeland individuals which exhibit a pseudobasal range of health measures.3.3.1T. rugosa were captured for sampling at one rangeland (Baseline) site (BS0–120 km2) near Mt. Mary  and adults and juveniles at three severely modified (Severe) landscape-scaled sites  over a large area (68×84 km or 571 200 ha) across the croplands. The Baseline and the Severe sites are separated by the Murray River  and less habitat alteration, and therefore provided a relative basal range of physiological health. Conversely, animals sampled from the Severe sites were exposed to the cumulative effects of habitat alteration and exposure to numerous agricultural chemicals associated with cereal cultivation. These sites varied in size  and were selected based on the spatial configuration of lizard habitat such that each site contained combinations of revegetated saltbush and roadside verge and patches of remnant mallee woodland. All Severe sites captured the widespread decline in structural connectivity of lizard habitat at the landscape scale . The Baseline and Severe sites were sampled in November 2010 and during September and November 2010, respectively. Mean monthly rainfall (March 2010 to February 2011) was 37.6 mm  at the Baseline site and 49.9 mm  for the Severe sites. Monthly maximum temperature varied from 12.7°C (August) to 31.7°C (January) in the Baseline site and 16.1°C (August) to 32.2°C (January) in Severe sites.This study took place in the South Australian Murray Mallee (SAMM) region . Adult Tay River . In the 3.2n=30; Severe habitat alteration, n=30) and one covariate for body condition (two measures: linear body size index (LBSI) or ectoparasite load, where n=30 for each) to investigate lizard health. All animals were grouped into two juveniles  and adults which included two sub-adults (SVL>200 mm) [We used a single treatment   but not >200 mm) . The eff>200 mm) .Lizards were surveyed in both types of sites by employing a single reptile visual encounter survey published for another study . Surveys3.3n=85). PCV was not determined for Baseline animals.Heparinized blood from the Severe sites was transferred to a capillary tube and the percentage of the blood that was composed of RBCs (packed cell volume (PCV)) was determined using a microcentrifuge  with the 100× objective and recording the percentage of heterophils, lymphocytes, monocytes and other granulocytes . Ten ranTotal WBC counts were not done for samples collected from the Severe sites because the estimated WBC count is linked to the number of RBCs. Thus, varying degrees of anaemia add considerable uncertainty to the actual count. Additionally, the quality of the blood smear made from blood with a low PCV is often poor, resulting in an uneven distribution of cells adding additional uncertainty to the WBC estimate. Automated total WBC counts were preferable but due to unforeseen circumstances were not possible for this study.3.4r=0.73) and independence [T. rugosa  from different populations had not been determined.Body size was assessed using the unity of LBSI. LBSI was calculated from the residuals of a ranged major axis (RMA) regression between log-transformed body mass and log-transformed body length. It meets the assumptions of linearity (pendence . Lizards3.5Bothriocroton hydrosauri (Acari: Ixodidae) and Amblyommalimbatum were highly visible especially with a hand lens. Tick load was measured as the number of ticks per individual and not grouped by species or tick life stage for this studyThe presence or absence of ticks for each individual was recorded by searching all surface areas of a lizard's body. All stages of both species of ticks, 3.6t-tests were applied to health measures to test our claim that individuals of Severe sites will display ‘secondary effects’ of cultivation unlike Baseline individuals which should show pseudobasal values. Data were transformed where appropriate.Multi-factorial analyses of variance using permutation tests, a RMA regression and Student rimer-E v6 PERMOVA add-on.Differences in differential counts were examined using a multivariate, one-way nested Type I PERMANCOVA  –33, with3.7During the study period, two sleepy lizards were found dead with injuries consistent with being run over by a vehicle in the Severe site. Representative tissues were collected from these animals, fixed in formalin, paraffin-embedded and 4 μm sections were routinely stained with haematoxylin and eosin and examined microscopically. A Prussian blue stain was done to assess liver iron concentrations.4.−1, well above the range (4444–25 231 cells μl−1) of the other sleepy lizards sampled at Baseline site. We treated these animals as statistical outliers and they were not included in the subsequent analysis. To maintain orthogonal analyses between Baseline and Severe sites, 28 adult animals were randomly selected post hoc from the Severe site for statistical analysis.Data were collected from a total of 30 adults at the Baseline site and 75 adults and 14 young (juveniles and sub-adults) at the Severe sites . Two ani4.1r=0.73, RMA regression F1,54=20.94, n=56, p≤0.001) . Twenty-one per cent (12) of animals weighed more than 800 g, 38% (21) between 640 and 775 g and 46% (23) between 460 and 600 g. Overall, LBSI was lower in the Severe sites than the Baseline site (Log-transformed body mass of adults was related to log-transformed body length (p≤0.001) . Overalline site .Figure r=−0.52; n=28, p≤0.005). Conversely, adults at the Severe sites had a lower tick load which was not correlated with LBSI . Both LBSI and tick load were more variable in the Baseline than the Severe site, although these measures within each population were highly variable . Infrequently, mitotic figures were seen in RBCs in animals with elevated numbers of polychromatophilic RBCs. Mitotic figures were not seen in blood smears from animals in the Baseline sites. Mature cells stained uniformly and with normal intensity. Examination of mature RBCs revealed that the majority of the sleepy lizards from the Severe sites had at least some RBCs that had circular defects in their cytoplasm that did not stain, these were interpreted as areas where the cytoplasm was missing (b). These defects in the cytoplasm varied in diameter, but the diameter was never more than 20% of the length of the cell. Similar defects were not found in the RBCs collected from animals at the Baseline site. Blood parasites were not seen in any of the blood films examined.Mean percentage of polychromatophilic RBCs were almost thirteen times higher in the Severe (13.2±1.5) than Baseline (1.7±0.4) sites (table 1). In this study, a very conservative cut-off of more than 10% polychromatic RBCs was used to define an animal with an abnormally high degree of polychromasia. Of 30 animals, 17 were recorded with values of more than 10% ranging between 11 and 34%. Cells in earlier stages of development than polychromatophilic RBCs were also commonly seen in the blood. All animals with high levels of polychromasia exhibited a normal sequence of the RBC maturation a,b. Infr missing b. These −1) [In the Baseline sites, an additional three animals had WBC counts  that exceeded the high normal limit for other reptiles (15 000 cells μl−1) ,35. Althpseudo F1,52=10.08, n=56, p(9948 permutations)≤0.001), the differential haematology of adult lizards  remained consistently different between Baseline and Severe sites ≤0.001) and this was not due to dispersion in distances from the centroids of the treatment levels, i.e. locational differences . There was no interaction with LBSI and treatment ≥0.253). Principle component (PC)1, PC2 and PC3 principle component axes of the PERMCOVA explained 49, 28 and 14%  which is also atypically high and a very consistent result. Differences among the differential counts were mostly weighted by lymphocyte percentage and no other haematological measures of Severe site animals (PC1). PC2 was largely weighted by heterophil percentage of Baseline site individuals and PC3 by polychromasia found in Severe site animals. H:L ratio explained less 1% in all ordinations.Excluding the differentials of two ‘outlier animals’, values of H:L ratio, monocytes and other granulocytes were square-root transformed due to right-hand skewness and all except heterophil differentials and polychromasia percentages were interdependent . Exploratory data analyses indicated that log-transformed LBSI and not tick load was structuring different haematology . Despite4.3p≥0.05). Notably, there was no correlation between both arcsine transformed polychromasia (%) and H:L ratio .PCV was determined for 85 sleepy lizards in the Severe sites. The PCV ranged from 7 to 41% with an average of 25%. Forty-two lizards (49%) had PCVs of less than 25%, 16 of these  had PCVs of less than 20% and three animals had PCVs of less than 10%. PCV had no relationship to body condition, other haematological measures or elapsed sampling days since brumation , and are not discussed further.4.4r=−0.46, n=75, p=0.0002). All other differential indices had no consistent relationship with sampling duration.Sampling duration (CUMDAYS) was not correlated with any of the WBC health indices. However, per cent polychromasia of adults decreased significantly with CUMDAYS (Pearson 4.5Diffuse vacuolar degeneration (formation of non-lipid vacuoles in the cytoplasm) was present in the liver from one animal. This liver also contained a moderate degree of granular pigment in sinusoidal macrophages (phagocytic and antigen processing cells) and in zone 1 hepatocytes that was Prussian blue (iron) positive (not shown). No microscopic lesions were found in the second lizard. Although multiple sections of the digestive tract were examined in both animals, intestinal parasites were not seen.5.Declines in wildlife populations in agricultural areas can be caused by habitat alteration, exposure to agricultural chemicals and factors that may or may not be related to agricultural practices including infectious diseases. Identifying the factor or factors that may impact wildlife in agricultural environments can be challenging but is critical if processes are to be reversed. In this study, we use traditional field techniques (LBSI) for body condition score with less frequently used haematological techniques to assess the disease status and impacts of agricultural practices on sleepy lizards found in a cropping environment (Severe site) and a grazing environment (Baseline site) separated by a river. The experiment was also designed to determine whether differing environmental conditions within the Severe sites would have a greater or lesser impact on the LBSI and haematologic values.The use of the LBSI and its components, body length and the animal's weight, as a measure of body condition demonstrated significant differences between the Severe and the Baseline animals, with the Severe site animals having a lower LBSI than those of the Baseline site. This finding appeared to confirm our original hypothesis that the fragmented and degraded Severe habitat was suboptimal and this suboptimal environment was reflected in the animals' condition. However, our data did not show any variation between sampling areas in the Severe site and the haematological results (discussed below), suggesting that widespread anaemia in animals in the Severe sites and not habitat itself may have resulted in the low LBSI, a conclusion that would not have been reached had haematology not been done.Comparing physical characteristics, our findings also showed that phenotypically the adult sleepy lizards in the croplands, which are south of the Murray River barrier, are smaller in size (body length) than animals north of the river in the rangelands. This could suggest that extended geographical separation of these populations has resulted in genetic drift or selection resulting in animals in the Severe sites having a shorter body length. This hypothesis would be supported by a recent unpublished study that has found that the two populations come from different genetic lineages . Alternately, prolonged suboptimal conditions in the Severe sites, such as reduced food availability or protein malnutrition, might result in the animals not achieving their maximum growth potential. This alternative seems unlikely as food availability during the study in the Severe sites is less likely to be a factor owing to higher total rainfall in the southern SAMM.Despite living in a fragmented environment and, in many instances, experiencing anaemia, H:L ratios were not influential in explaining differences for the animals in the Severe sites as compared with animals in the Baseline sites. Heterophil  and neutrophil  to lymphocyte ratios have been used to assess stress in individual animals and populations of domestic and wild animals ,35. TypiMycoplasma sp., a bacterium that has had significant impacts on wild reptile populations and thus this population requires an intensive disease investigation [Our finding of moderately to markedly elevated WBC counts in five (17%) of the sleepy lizards from the Baseline site negates our original assumption that samples from these lizards would be a reasonable representation of the basal range leucocytes for our species in the wild and illustrates the difficulty of linking leucocyte profiles to environmental condition for wild animals . These vtigation . A correIt would have been ideal to have used manual counting methods such as phloxine stains to determine the absolute total WBC counts, rather than depend on estimated counts from a blood smear . This woOur study provides strong evidence that many of the sleepy lizards collected in the Severe sites were experiencing either a blood loss or RBC destructive (haemolytic) anaemia. The percentage of polychromatophilic RBCs in the lizards from these landscapes was significantly higher on average than the percentages in the less disturbed rangelands and very high values were seen in individual animals in the Severe sites, but not the rangelands, indicating that these animals were producing new RBCs at a greater rate in response to a decrease in RBC mass ,39. The Blood loss was initially considered as a cause of anaemia. Ectoparasites, such as ticks that were found on these lizards and mosquitoes that would have been present in the environment can cause anaemia in their hosts. The tick burden found on animals from the Severe sites, however, was less than that found on the Baseline animals and although the tick load in the Baseline animals was correlated with a decrease in LCBI in this study and in a previous study , these aTwo lines of evidence support haemolysis and not chronic blood loss as the cause of the anaemia detected in these lizards. The first is the robust and orderly nature of the regenerative response seen in these lizards. This type of response is expected in both red cell destructive anaemia and acute blood loss. Chronic blood loss, which would have been more likely in these animals, given the presence of anaemia over the study period, would have resulted in a different haematological picture . With chThe causes of haemolytic anaemia are many. They can be immune-mediated where the body produces antibodies against an epitope on the surface of the cell. The epitope can be a normal cellular component or a viral, bacterial or parasitic protein, a drug or a toxin that is on the surface of the cell . Blood pN,N′-dimethyl-4,4′-bipyridinium dichloride) (Syngenta), a non-selective, contact-chemical weedicide, is used extensively in Severe sites on cropping farms and causes oxidative damage to animal tissue, particularly the lungs and kidneys, if ingested. Fox and rabbit baiting with the poison 1080 is also commonly used in this area and can be applied at any time during the year. Reptiles are generally considered to be less sensitive to the effects of 1080 as compared with mammals [The lizards in the Severe sites were exposed to a variety of agrochemicals that could potentially act as toxins. Paraquat ).Locust and mouse plagues occurred during the study period resulting in the increased use of rodenticides and insecticides. Aerial spraying with Green Guard ULV (Becker Underwood Pty. Ltd) was done in November and December of 2010 east of the Baseline site. Green Guard contains fungal spores that kill locusts and a study on their impact on one reptile suggested that they were unlikely to be harmful . Green GSchistocerca gregaria) [Podarcis bocagei) in Portugal exposed to ‘a cocktail’ of agricultural chemicals . Lizards in the exposed population from Portugal were more likely to exhibit hepatocyte vacuolation and this was also seen in one of the necropsied sleepy lizards [Acanthodactylus boskianus) [Both the organophosphate chlorpyrifos and fipronil could have played a role in the anaemia seen in the sleepy lizards in the Severe sites. Evidence of acute poisoning of reptiles has been observed in Africa following the application of chlorpyrifos to control the desert locust (regaria) ,44 and tregaria) . Additio lizards ,4. In a On the other hand, the timing of the application of organophosphates and fipronil argues against them being the cause of the anaemia. Organophosphate application was only carried out from the beginning of October until the end of November. Anaemic animals and animals with polychromasia were found in September before the spraying occurred and therefore the only way that these chemicals could have been contributory would if the lizards were exposed to residual concentrations from the previous year.Mouse baiting with wheat coated with zinc phosphide or wheat pellets containing zinc phosphide, increased significantly in 2010 and 2011 and these were distributed in the Severe sites and not the Baseline site. Most application would have occurred in March and April when the cereal crops were sown, but could have been applied in the winter and then again in the spring as well . Sleepy lizards may have consumed these poisoned baits and it is also possible they could have consumed poisoned mice. Zinc phosphide is rapidly converted to phosphine gas when it is exposed to hydrochloric acid in the stomach. It causes cell death in many organs as the result of disruption of energy metabolism in the mitochondria. It affects RBCs by oxyhaemoglobin to methaemoglobin and thus could have resulted in the damaged RBCs seen in the sleepy lizards and the resultant haemolytic anaemia .Sleepy lizards enter brumation soon after grain crops are sown. Studies on wound healing suggest that reptiles at temperatures below their prefered optimum temperature zone have a reduced metabolic rate and healing is delayed . It woulThe long-term impact of this haemolytic anaemia on the sleepy lizard population in the Severe sites is not known. Our data suggest that it resulted in reduction in body condition in many animals. However, given that animals with normal PCVs and blood smears were seen at the end of the study, it is possible that the sleepy lizards reduced their activities while recovering from the anaemia and because reptiles have relatively low metabolic rates were able to survive this insult.In conclusion, this study shows the power of combining both physical and haematological measurements when assessing the health of reptiles across ecosystems. Using this combination of tools, we were able to demonstrate that sleepy lizards across a wide agricultural ecosystem were experiencing anaemia and a reduction in body condition that was likely to be the result of the application of one or more agrochemicals. We were also able to demonstrate that an infectious disease of potential ecological importance was present in the sleepy lizards in the rangeland site and that phenotypic differences could be found between sleepy lizards in the rangeland site and cropping site, possibly as the result of the physical barrier of a large river separating them. These findings also suggest that the sleepy lizard and possibly other reptile species may prove important sentinels for the impact of the use of agrochemicals on ecosystems and that more detailed and controlled studies need to be done on how these chemicals impact reptiles.


During mitotic entry, centrosomes separate to establish the bipolar spindle. Delays in centrosome separation can perturb chromosome segregation and promote genetic instability. However, interphase centrosomes are physically tethered by a proteinaceous linker composed of C-Nap1  and the filamentous protein rootletin. Linker disassembly occurs at the onset of mitosis in a process known as centrosome disjunction and is triggered by the Nek2-dependent phosphorylation of C-Nap1. However, the mechanistic consequences of C-Nap1 phosphorylation are unknown. Here, we demonstrate that Nek2 phosphorylates multiple residues within the C-terminal domain of C-Nap1 and, collectively, these phosphorylation events lead to loss of oligomerization and centrosome association. Mutations in non-phosphorylatable residues that make the domain more acidic are sufficient to release C-Nap1 from the centrosome, suggesting that it is an increase in overall negative charge that is required for this process. Importantly, phosphorylation of C-Nap1 also perturbs interaction with the core centriolar protein, Cep135, and interaction of endogenous C-Nap1 and Cep135 proteins is specifically lost in mitosis. We therefore propose that multisite phosphorylation of C-Nap1 by Nek2 perturbs both oligomerization and Cep135 interaction, and this precipitates centrosome disjunction at the onset of mitosis. Centrosomes are the primary microtubule-organizing centers in animal cells. They are composed of centrioles, short cylinders of nine triplets of highly stabilized microtubules arranged into a pinwheel configuration and surrounded by pericentriolar material (PCM) from which microtubules are nucleated . CentrosOwing to their organization, centrosomes in G2 cells undergo two distinct separation events during mitotic progression. The first occurs in late G2 or early M, when the two centrosomes, each now containing a pair of centrioles, move apart to establish the opposing poles of the mitotic spindle. The second separation event occurs as cells exit mitosis, when the pair of centrioles within each pole splits apart or ‘disengages’, enabling each daughter cell to inherit two centrioles, which are now separated to form the two centrosomes. However, although progress has been made into understanding the biochemical regulation of these events , the mecBoth before and after centriole duplication, the two centrosomes generally remain in close proximity throughout interphase. In part, this is due to the action of the microtubule and actin cytoskeletons, which push against the cell cortex to keep the centrosomes in the cell center . HoweverIn terms of its composition, a number of linker components have been identified, including C-Nap1 , rootletin, Cep68, LRRC45, centlein and β-catenin . C-Nap1 So if these proteins constitute the linker then what regulates their disassembly at the G2/M transition? This is the role of the Nek2 protein kinase, a member of the human NIMA-related kinase family . Nek2 phSo what controls the activity of Nek2? Nek2 undergoes autophosphorylation within its activation loop in response to homodimerization through a leucine zipper present downstream of the N-terminal catalytic domain . HoweverExperimental approaches that interfere with centrosome disjunction, such as Nek2 depletion, do not prevent bipolar spindle assembly or mitotic progression. This is because multiple processes contribute to centrosome separation, including force generation by microtubule-based motors that drive poles apart through anti-parallel microtubule sliding . However1/2) of ∼30 seconds, but no recovery of rootletin . We hypothesize that most centrosomal C-Nap1 is assembled into a stable linker structure, but excess C-Nap1 trafficked to the centrosome along microtubules is released owing to the limited binding capacity at the proximal ends of centrioles.To study the mechanisms regulating centrosome disjunction, we first raised a polyclonal antibody against rootletin to confirm the presence of intercentriolar fibers in interphase cells. This antibody revealed filamentous structures that extend from each of the two centrosomes and that in some, albeit not all, cells could be seen linking the two centrosomes . These footletin . The lim1/2 of ∼5 seconds  dynamic with a t seconds . To test seconds . Depleti seconds . As expe seconds .supplementary material Fig. S1B).We next sought to determine how C-Nap1 recruits Nek2 to the centrosome. C-Nap1 was identified through interaction of its CTD (residues 1964–2442) with Nek2 in a yeast two-hybrid assay . Using tin vitro kinase assays over 4 hours to achieve maximal phosphorylation . Of these, ten match sites that were phosphorylated by Nek2 in vitro and three others match sites that we identified in vivo. We conclude that Nek2 not only phosphorylates many sites within the CTD of C-Nap1, but that it is likely responsible for the bulk of phosphorylation on this domain in vivo. However, it remains possible that other kinases can also phosphorylate this domain in cells.We then investigated which site(s) within the entire CTD (residues 1964–2442) might be phosphorylated by Nek2 by performing rylation . Analysirylation . As a rerylation . There wonsensus . There win vitro . Furtherin vitro and distributed across this domain were mutated to acidic residues . It also failed to assemble into patches when expressed at high levels and induced only a relatively low level of centrosome splitting . Yeast two-hybrid and co-immunoprecipitation assays confirmed that the S10D mutant had a reduced capacity for self-association. However, there was no loss of association of the S10D mutant with Nek2 in either yeast two-hybrid or co-immunoprecipitation experiments . Moreover, we observed a clear dose-dependent response in terms of loss of centrosome association as the number of phosphomimetic mutations increased from five to ten . Thus, we conclude that the affinity of this domain for the centrosome is reduced in proportion to the number of sites phosphorylated.To determine whether one or more specific sites might be crucial, we generated two further phosphomimetic mutants – CTD-S5D.1, which had five of the ten sites mutated in the S10D construct, and CTD-S5D.2, which had the other five sites mutated . We founin vivo analysis but only two (S2234 and S2394) were identified as Nek2 phosphorylation sites in vitro. This is consistent with SIK2 being the primary kinase that phosphorylates S2392 in cells. To test the importance of the S2392 site alone, we generated a single phosphomimetic point mutant, CTD-S2392D. However, this mutant behaved in a similar manner to the wild-type protein, localizing strongly to the centrosome, assembling into patches and inducing centrosome splitting . Hence, phosphorylation at this site alone is insufficient to regulate C-Nap1. Nevertheless, SIK2 might cooperate with Nek2 to achieve a threshold of C-Nap1 phosphorylation necessary to trigger linker disassembly.Another kinase, SIK2, can phosphorylate C-Nap1 and has been reported to regulate its localization to the centrosome . SIK2 prsupplementary material Fig. S2A). It also did not form patches and neither did it induce centrosome splitting . Taken together, these data support the hypothesis that phosphorylation of C-Nap1 by Nek2 displaces it from centrosomes during mitotic progression and, although not essential for centrosome separation, this might contribute to its timing.To test whether the phosphorylation of C-Nap1 by Nek2 regulates its affinity for centrosomes in mitosis, we generated a CTD-S10A mutant in which the same ten phosphorylation sites that were previously mutated to acidic residues were converted to alanine. When expressed at low levels in interphase cells, this phospho-null mutant exhibited similar recruitment to the centrosome as the wild-type protein  and induTo assess centrosomal C-Nap1 phosphorylation through the cell cycle, we generated three phospho-specific antibodies against sites phosphorylated by Nek2. We have previously reported two of these antibodies. The ‘RRLD’ anti-phosphorylated (p)C-Nap1 antibody (directed against a peptide containing both S2417 and S2421) is specific for phosphorylated C-Nap1 in western blotting, and it confirmed the phosphorylation of C-Nap1 at this site in mitotic cells . HoweverTo determine whether the extent of C-Nap1 phosphorylation might be subject to additional regulation, we treated G2-arrested cells with the PP1 inhibitor calyculin A. This led to a fourfold to fivefold increase in centrosomal pC-Nap1 staining with both antibodies . Inhibitsupplementary material Fig. S4B). We then examined the localization of C-Nap1 and Cep135 in cells in which centrosomes were prematurely split in response to Nek2 overexpression or addition of epidermal growth factor (EGF), both of which induce centrosome splitting in a Nek2-dependent manner . Importantly, by performing reciprocal co-immunoprecipitation experiments, we found that endogenous C-Nap1 and Cep135 associated in S-phase-arrested cells, but not in cells arrested in M phase with nocodazole or the Eg5 inhibitor S-trityl-l-cysteine (STLC)  . InteresIn this study, we provide mechanistic insight into the process of centrosome disjunction that breaks the proteinaceous linker that holds centrosomes together during interphase . Our datOur results firstly demonstrate that the large coiled-coil proteins C-Nap1 and rootletin act as stable components of the intercentriolar linker. They also provide further evidence that although C-Nap1 is focused at the proximal ends of centrioles , rootletNek2 can phosphorylate many sites (>25) within the ∼50-kDa C-Nap1 CTD. This notion of multisite phosphorylation confirms earlier studies that suggest that Nek2 catalyzes the incorporation of at least 13 moles of phosphate per mole of this domain . ImportaIdentification of a large number of phosphorylation sites allowed us to analyze the preferred sequence for Nek2 phosphorylation based on a protein substrate rather than peptide libraries. This led to the definition of a consensus motif of LxxS/TΦ. An oriented peptide-library screen identified [F/L/M]xxS/TΦ[R/H/X] as the optimal motif for Nek2, which fits very well with the consensus identified from our studies . HoweverThe generation of phospho-specific antibodies allowed us to address the extent of C-Nap1 phosphorylation at centrosomes in cells. This revealed a number of interesting points about the regulation of centrosome cohesion. Firstly, phosphorylation of centrosomal C-Nap1 was detected in interphase before centrosome disjunction occurred. Secondly, the extent of phosphorylation increased as cells progressed from S to G2. Thirdly, incubation of cells with a PP1 inhibitor led to a further substantial increase in centrosomal C-Nap1 phosphorylation. We propose that a low level of C-Nap1 phosphorylation is present from S phase onwards, when Nek2 is first expressed and recruited to the centrosome. The steady increase in this phosphorylation could reflect increased centrosome recruitment of Nek2 in response to phosphorylation by Mst2. However, during interphase, the overall stoichiometry of phosphorylation is below that required to trigger centrosome disjunction, most likely as a result of the counteracting phosphatase PP1. Only upon inhibition and/or removal of PP1 at mitosis does the phosphorylation of C-Nap1 overcome the threshold required to precipitate centrosome disjunction. Indeed, PP1 is both inhibited at this time through Cdk1-mediated recruitment of inhibitor-2, and released from the Nek2–Mst2 complex by Plk1-mediated phosphorylation of Mst2 . Consistin vivo analysis that were not phosphorylated by Nek2 in vitro, including S2392 that was reported to be phosphorylated by the SIK2 kinase  was subcloned into pLeics 20 or pGEX for expression in mammalian cells with an N-terminal Myc tag or bacteria with an N-terminal GST tag, respectively. The rootletin CTD (residues 1651–2018) was fused to an N-terminal maltose-binding protein (MBP) by subcloning into the pMALc2X vector, expressed in bacteria and purified by amylose resin affinity chromatography. Cep135 constructs have been described previously . Site-di2. Transient transfections were performed with Fugene HD (Roche) according to the manufacturer's instructions, and cells were analyzed after 24 hours. For G1/S and G2 arrest, cells were incubated with 1.6 µg/ml aphidicolin (Sigma) and 10 µM RO-3306  for 16 hours, respectively. Specific inhibitors were used as indicated for Plk1 , aurora A  supplemented with 10% fetal calf serum, 100 IU/ml penicillin and 100 µg/ml streptomycin. Cells were grown at 37°C under 5% COsiRNA oligonucleotides against GAPDH , C-Nap1  and rootletin  were transfected using Oligofectamine (Invitrogen).Cell lysates were prepared as indicated in NEB buffer , single-32P]-ATP in 40 µl of kinase buffer  for 30 minutes at 30°C. Reactions were stopped with 50 µl of 3× sample buffer and analyzed by SDS-PAGE and autoradiography. Substrate phosphorylation was quantified by scintillation counting of protein bands excised from dried gels. Excised bands were immersed in 3 ml of Optiphase HiSafe 2 liquid scintillant  and 32P incorporation was determined by quantification in a LS6500 scintillation analyzer (Beckman Coulter). For phospho-site mapping, proteins were separated by SDS-PAGE, gels were stained with Coomassie Blue for 30 minutes and then destained. The C-Nap1 CTD protein was excised and phospho-sites were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis.Kinase assays were performed as described previously , using 0Rootletin antibodies were generated against the MBP-tagged rootletin C-terminal fragment expressed in bacteria. Immunizations were performed in rabbits by Cambridge Research Biochemicals and antisera were purified on an affinity column made from the same C-terminal fragment of rootletin tagged with GST. The production and purification of antibody against pC-Nap1 was performed as described previously , with thHeLa or U2OS cells were fixed with ice-cold methanol for 30 minutes at −20°C, and immunofluorescence microscopy was performed as described previously . PrimaryP-values were calculated for t1/2 or percentage recovery where indicated using Student's t-test.FRAP analysis was performed on a Leica SP5 confocal laser scanning microscope using a 100× oil objective (NA 1.4) and a scan zoom of 3. A square region of interest (ROI) of 50×50 pixels centered on both centrosomes was bleached with 40 iterations and 100% laser power (488-nm argon laser). Two images were captured before bleaching with a 1-second interval. An image was taken every second (488-nm argon laser at 4% power) after bleaching over a 30–90-second period. For each time-point, the fluorescence intensity of the photobleached ROI (P1) was determined using Leica software. The fluorescence intensity of an unbleached ROI in the cell was determined (U2) and a normalized intensity (In) was calculated using P1/U2. The background fluorescence intensity (Bk) was set as the first frame after photobleaching, and this value was subtracted from all frames, such that the fluorescence intensity for the ROI at a given time is equal to In−Bk. The amount of fluorescence recovery was then calculated as the fluorescence intensity value of a given frame divided by the fluorescence intensity value of the frame immediately before photobleaching and was expressed as a percentage . Images Saccharomyces cerevisiae, PJ69-4A, or in pLEICS-81 (LexA-DBD) and pLEICS-82 (VP16-AD) plasmids transformed into S. cerevisiae, L40. Interacting clones were selected by growth on synthetic dropout medium lacking appropriate amino acids, and interaction activity (Miller units) was measured using β-galactosidase assays.Yeast two-hybrid interaction assays were performed using constructs generated in either pGBDU (GAL4-DBD) and pACTII (GAL4-AD) plasmids transformed into


Added to perfusion medium, Aβ1-40 is able to enter into synaptosomes; it exerts its inhibitory effect at extracellular sites when release is stimulated by nAChRs and intracellularly when release is evoked by mAChRs. Moreover, our data show that Aβ1-40 acts as non competitive antagonist of heteromeric α4β2* but not of α3β4* nAChRs which modulate [3H]NA overflow. Positive allosteric modulators of nAChRs counteract its inhibitory effect. It might be that compounds of this type could be useful to prevent, slow down the appearance or reverse the cognitive decline typical of the normal processes of brain aging.Contradictory results have been reported on the interaction of beta-amyloid (Aβ) with cholinergic receptors. The present paper investigates the modulatory effect of Aβ1-40 on the neurotransmitter release evoked by nicotinic (nAChRs) and muscarinic (mAChRs) receptors. Aβ1-40 inhibits both nicotinic and muscarinic-evoked [ The predominant clinical symptoms early associated with Alzheimer’s disease (AD) include a deficiency in memory capabilities and these deficits are linked to a selective impairment of cholinergic function  or incubation times  to these receptors producing a functional inhibitory effect , leaving unchanged the function of inhibitory subtypes  to investigate the functional effects of Aβ1-40, present outside or inside the nerve endings, on the presynaptic modulation of the release of dopamine (DA) evoked by nicotinic and muscarinic agonists in rat nucleus accumbens (NAc); and (b) to explore whether selective agents can antagonize the action of Aβ.The results indicate that Aβ1-40 inhibits both nicotinic and muscarinic cholinergic modulation of DA release acting respectively from outside and inside the nerve endings. Moreover, the inhibitory effect of Aβ1-40 on nAChRs can be antagonized by desformylflustrabromine (DFBr) and galantamine with a mechanism that presumably involves the positive allosteric site of nAChR.Adult male rats  were housed at constant temperature (22 ± 1°C) and relative humidity (50%) under a regular light–dark schedule (light 7.00 a.m.–7.00 p.m.). Food and water were freely available. The animals were killed by decapitation and the brain was rapidly removed at 0–4°C. Fresh tissue was dissected according to Paxinos and Watson  sectionsin vitro analysis just before the administration.For our experiments, synthetic human Aβ1-40 was dissolved in a CSF at a concentration of 100 μM (stock solution). Then, this solution was filtered through a Millipore 0.2 μm pore membrane and stocked in small aliquots at −80°C. Working solutions were freshly prepared by diluting an aliquot of Aβ1-40 stock solution at the final concentrations used for As far as the characteristics of the Aβ peptides we employed in our study, we have previously shown that in our experimental conditions the solutions of Aβ are mostly formed by Aβ monomers. However, we cannot completely exclude that small amounts of Aβ oligomers are also present in light of the fact that aggregation is a concentration and time-dependent process  in the presence of 6-nitroquipazine , to avoid false labeling of serotonergic terminals and of desipramine , to avoid false labeling of noradrenergic terminals. In a set of experiments, hippocampal synaptosomes were incubated with [3H]noradrenaline  in the presence of 6-nitroquipazine.In release experiments, NAc synaptosomes were incubated for 20 min at 37°C with Dopamine (21.2 Ci/mmol (0.784 TBq/mmol)) and noradrenaline (12.1 Ci/mmol (0.448 TBq/mmol)) were purchased from Perkin Elmer, Monza, Italy. Nicotine hydrogen tartrate salt, choline, 4-aminopyridine, 6-nitroquipazine, desipramine, beta-amyloid (40-1), horseradish peroxidase-conjugated anti-mouse secondary antibody, Ponceau Red were from Sigma ; Monoclonal antibody 6E10 was from Covance ImmunoTechnologies, Dedham, MA; 5-iodo-A-85380, dihydro-β-erythroidine, α-conotoxin MII, oxotremorine sesquifumarate, desformylflustrabromine hydrochloride, galantamine hydrobromide, SR 165845, beta-amyloid (1-40) were from Tocris .DA overflow, confirming previously results  is not altered by Aβ1-40 (100 nM). Figure 3H]DA overflow induced by 5IA85380 an α4, α6 nAChRs agonist, is inhibited by Aβ1-40 (100 nM) to a similar extent (−36%). In presence of α-conotoxin MII (50 nM), a specific inhibitor of α6 nAChRs, the 5IA85380-evoked [3H]DA overflow is significantly decreased (−44%) and further inhibited (−45%) by Aβ1-40 indicating that α-conotoxin MII—resistant nAChRs (α4- non α6) are inhibited by Aβ1-40. As expected, choline (1 mM) doesn’t elicit [3H]DA overflow from NAc synaptosomes, which is mostly modulated by non α7 nAChRs subtypes . Conversely, when the Aβ antibody is entrapped into synaptosomes  indicating a typical non-competitive antagonistic effect.Figure The possibility of rescuing the inhibitory effect of Aβ was investigated using two α4β2 nicotinic compounds, DFBr and galantamine, supposed to act as positive allosteric modulators at the α4β2 nAChRs . Similarly, galantamine (10 nM), which is ineffective on the 5IA85380-evoked [3H]DA overflow, also shows the capacity of antagonizing the inhibitory effects of Aβ1-40  but counteracted by the specific α3β4 antagonist SR165845 , doesn’t produce any inhibitory effect.Figure 3H]DA release has also been investigated. Figure 3H]DA overflow, probably activating an M5 mAChR subtype present on DA nerve endings . When defining the receptor subtypes we use asterisks to indicate the possible presence of unidentified nAChR subunits. Conversely, Aβ is not effective on the α3β4 nAChRs that elicit [3H] NA overflow in the hippocampus. As shown in Figure The inhibitory effect of Aβ1-40 is evident both when the nAChR subtypes are stimulated by nicotine, 5IA85830 alone and in the presence of α-conotoxin MII, which excludes the involvement of the nAChRs containing the α6 subunit (likely α6β3β2 and/or α6α4β3β2). Since the inhibitory effect of Aβ against the 5IA85380-evoked [The nicotinic-evoked DA release is of exocytotic type involving the activation of α4β2* receptors present on the DA terminals, a subsequent depolarization of the nerve endings and the activation of voltage-operated calcium channels  than those effective in interfering with the nicotinic modulation outside the nerve endings (100 nM; cf. Figures A different view emerged when considering the muscarinic control of DA release in the same brain area. In a recent study, we pharmacologically characterized as M5 the mAChR subtype which modulate DA release in the rat NAc and reported that it can be inhibited by the extracellular application of Aβ1-40 at nM concentration (Grilli et al.,  Figures . This fi Figures . Quite i Figures  and to pIt is well accepted that the facilitation of neurotransmitter release by M1, M3 and M5 mAChRs is mediated by signal transduction pathways involving the protein kinase C (Zhong et al., In conclusion, we have demonstrated that Aβ1-40 inhibits both nicotinic- and muscarinic-evoked DA overflow by two different mechanisms: interacting extracellularly with a nAChRs binding site or through an internal modulation involving the downstream signal transduction of M5 mAChR subtypes. Moreover, we have found that the inhibitory effect of Aβ1-40 on nAChRs could be rescued by DFBr and galantamine with a mechanism which probably involved the positive allosteric modulator site of α4*nAChRs.The demonstration that the inhibitory effect of Aβ can be selectively reverted may open up new and important therapeutic perspectives, especially with regard to the potential use of drugs of this type in the early stages of the disease when it could be very important to slow down its progression. As reported in the introduction, a variety of studies indicates that Aβ may have an important role in cognitive dysfunction and memory deficits. It might be that compounds of this type could be useful even in healthy subjects to prevent, slow down the appearance or reverse the cognitive decline typical of the normal processes of brain aging.Guendalina Olivero performed the release and the dot-blot experiments, revised critically the paper and approved the final version; Jiayang Chen, Stefania Preda, and Elisa Mura performed the release experiments and revised critically the paper and approved the final version; Massimo Grilli contributed to the design of the work and coordinated the release experiments, performed the dot-blot experiments, revised critically the paper and approved the final version; Stefano Govoni and Mario Marchi provided a substantial contributions to the design of the work and to the interpretation of data and wrote the paper.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.


It has been questioned whether the inhibition data obtained with an experimental probe substrate such as MPP+ or ASP+ might be used to predict the inhibition against other, clinical relevant substrates such as metformin. Here we compared the OCT2 inhibition profile data for the substrates metformin, MPP+ and ASP+. We used human embryonic kidney (HEK 293) cells stably overexpressing human OCT2 as the test system to screen 125 frequently prescribed drugs as inhibitors of OCT2-mediated metformin and MPP+ uptake. Data on inhibition of OCT2-mediated ASP+ uptake were obtained from previous literature. A moderate correlation between the inhibition of OCT2-mediated MPP+, ASP+, and metformin uptake was observed . Of note, the correlation in the inhibition profile between structurally similar substrates such as MPP+ and ASP+ (Tanimoto similarity T = 0.28) was even lower (rs = 0.27) than the correlation between structurally distinct substrates, such as ASP+ and metformin  or MPP+ and metformin . We identified selective as well as universal OCT2 inhibitors, which inhibited transport by more than 50% of one substrate only or of all substrates, respectively. Our data suggest that the predictive value for drug-drug interactions using experimental substrates rather than the specific victim drug is limited.The importance of the organic cation transporter OCT2 in the renal excretion of cationic drugs raises the possibility of drug-drug interactions (DDIs) in which an inhibitor (perpetrator) drug decreases OCT2-dependent renal clearance of a victim (substrate) drug. In fact, there are clinically significant interactions for drugs that are known substrates of OCT2 such as metformin. To identify drugs as inhibitors for OCT2, individual drugs or entire drug libraries have been investigated  In a total incubation volume of 125 μL the final concentrations of the test drugs were 20 or 200 μM. Final substrate concentrations were 1000 μM for [14C]metformin and 50 μM for [3H]MPP+. Cells were incubated at 37°C for 3 min, a time-point well before kinetics of OCT2-mediated uptake of MPP+ and metformin reached steady-state  = 100 –(V / V0 * 100), where V and V0 are the net uptake rates with and without test drug.For the transport assays HEK cell lines stably transfected with human OCT2 (HEK-OCT2) or the vector only (HEK-VC) were used. The HEK-OCT2 cell line was established and characterized previously , 11. HEKdy-state . Uptake rs between the two variables. Bland-Altman analysis was used to quantify the level of agreement. Each of the 125 drugs was represented on the Bland-Altman graph by assigning the mean of the two measurements (% inhibition of OCT2-mediated uptake of MPP+ and metformin) as the abscissa value, and the difference between the two values as the ordinate value.To investigate whether structurally distinct substrates may display different inhibitory profiles for the same set of test drugs, the inhibition values for one substrate were plotted against the inhibition values for the other substrate. Spearman correlation tests were used to determine the strength of the monotonic relationships in vitro data were compared with data published by Kido et al. [+ transport. Kido et al used a similar experimental screening approach, namely a drug library tested at 20 μM in HEK 293 cells stably overexpressing OCT2.For a further in-depth investigation of the substrate dependence of OCT2-inhibition, our o et al. , who stu50 values) were measured as the substrate uptake in the presence of increasing concentrations of test drugs. These experiments were performed as described above . IC50 values were calculated with GraphPad Prism 5.0 . IC50 was estimated by a sigmoidal inhibition model and was fit to the equation V = V0/ (1 + (I / IC50)n) by nonlinear regression. V is the net uptake in the presence of the inhibitor, V0 is the net uptake in the absence of the inhibitor, I is the concentration of the inhibitor and n is the slope.Experimental half-maximal inhibitory concentrations , where c represents the number of bits set to 1 common to the structural fingerprints of compounds A and B and a and b represent the number of bits set to 1 in fingerprints of A and B, respectively. The Tanimoto coefficient (T) has a range from 0 to 1 with higher values indicating greater similarity than lower ones.Structural similarity between the OCT2 substrates metformin, MPPChemMine . The pai+ uptake in HEK-VK and HEK-OCT2 cells was performed using the unpaired two-sample t test. Significant inhibition of OCT2 mediated metformin or MPP+ uptake was determined by the one-sample t test. Univariate relationships were tested by Spearman’s correlation coefficient. Data were presented as means ± standard error of the mean. A value of P < 0.05 was considered statistically significant.Comparison of metformin or MPP+ or metformin uptake. We used the inhibition data set generated with 20 μM drug concentrations. The molecular descriptors (independent variables) were calculated with Marvin  and ChemMine [A standard multiple regression was performed to assess the ability of the molecular descriptors topological surface area (TPSA), number of aromatic rings, net charge at pH 7.4), distribution coefficient (logD at pH 7.4), and molecular weight to predict the percent inhibition of OCT2-mediated MPPChemMine . They we.4, distrChemMine , 13. Mul+ (50 μM) in HEK-OCT2 cells was time-dependent and uptake reached steady-state after approximately 15 min  and MPPy 15 min . For the was 3.2 . The dru was 3.2  and 200  was 3.2  Figs. DaAt 20 μM, eighty-three of the 125 tested drugs (66%) significantly inhibited OCT2-dependent metformin uptake. Fifty-seven of these drugs inhibited OCT2-mediated metformin transport by more than 50% . At 200 + uptake when a drug concentration of 20 μM was used. Thirteen drugs most potently inhibited MPP+ transport by more than 50% , quantitative measures for the inhibition of metformin and MPP+ uptake were correlated for each drug and tested using the Spearman's rank correlation. At an inhibitor concentration of 20 μM a moderate (rs = 0.63) but significant correlation (p < 0.0001) between the inhibition of OCT2-mediated metformin and MPP+ uptake was observed .To investigate whether the observed inhibitory potency of a drug differs with the substrate used in the experiments , classified as ‘universal’ OCT2 inhibitors, included amitriptyline, clomipramine, donepezil, doxepin, omeprazole, telmisartan, and trimipramine , logD (at pH 7.4), and molecular weight. Additional analyses were performed to ensure there was no collinearity between the explanatory variables. Significant regression equations were found. The models included TPSA, the number of aromatic rings and the net charge as explanatory variables. For inhibition of OCT2-dependent MPP+ transport, F  was 8.5 (F-statistics P = 0.000036) with an R2 of 0.17. For inhibition of OCT2-dependent metformin transport, F was 27.7 (P < 0.0000001) with an R2 of 0.41.Multiple linear regressions were calculated to predict the degree of OCT2-dependent MPPin vitro IC50 values and comparison with unbound Cmax values  achieved in patients are recommended by the International Transporter Consortium and the FDA as a criterion whether a drug might be a clinically relevant OCT2 inhibitor and therefore should be evaluated as an inhibitor in man [The respective cmaxet al. [values were obtained from Regenthal et al. . For this purpose we determined the in vitro IC50 values of the 7 most potent inhibitors of OCT2-mediated metformin uptake , such as the tricyclic antidepressants clomipramine, doxepin, opipramol and trimipramine, the synthetic opioid methadone, the acetylcholinesterase inhibitor donepezil, the typical antipsychotic fluphenazine, the benzodiazepine oxazepam, and the nonbenzodiazepine hypnotic zolpidem. The steroidal antimineralocorticoid spironolactone, the synthetic hormone drospirenone, the alpha blocker tamsulosin, the angiotensin receptor antagonist telmisartan, and the muscarinic antagonist trospium chloride were also determined as potent inhibitors (> 85% inhibition) of OCT2-mediated metformin uptake. Indeed, doxepin, trimipramine, and trospium chloride were identified as potent OCT2-inhibitors before, however the respective studies did not use metformin but MPP+ as the probe substrate [50 values in a low micromolar range [In this ubstrate , 18. We ar range –21.+ and ASP+. One important finding is that the profiles of OCT2 inhibition showed a moderate but significant correlation between the substrates MPP+, ASP+, and metformin. Particularly the rather weak correlation between the structurally less diverse substrates MPP+ and ASP+  is surprising. Although inhibition profiles of OCT2-mediated MPP+ and ASP+ uptake were derived from two independent studies, assay conditions were highly comparable between these studies and thus do not explain the differences in the inhibition profiles. Of note, Thévenod et al. recently demonstrated marked differences in the IC50 values for example of cimetidine when directly comparing the substrates MPP+ and ASP+, suggesting a strong substrate-dependence in the inhibitor affinities [et al. also demonstrated the substrate-dependent inhibition of OCT2 and concluded that the development of predictive models of drug-drug interactions with OCT2 must take into account the substrate dependence of ligand interactions with OCT2 [Using our own and previously published experimental data, we directly compared the inhibition profiles of a set of drugs for the structurally distinct OCT2 substrates metformin, MPPfinities . The datfinities , 24. Indfinities . Belzer ith OCT2 .The mode of inhibition has been evaluated in previous studies. Different types of inhibition, e.g., competitive, non-competitive, uncompetitive, and mixed-type inhibition have been identified , 25. Mor+ and metformin uptake as the dependent variables. Irrespective of the substrate, the regression models included TPSA, number of aromatic rings, and net charge as significant predictive variables, confirming their general importance [2 = 0.41) and MPP+ (R2 = 0.17).In addition to the pharmacophore-based approach, other studies tried to identify molecular descriptors suitable to discriminate between OCT2 inhibitors and non-inhibitors using the quantitative structure-activity relationship (QSAR) approach , 8, 13. portance , 8, 13. portance , 8, 13, max value) of the inhibitor drug reaches a critical level relative to its Ki or IC50 value for OCT2 inhibition. In drug development, it is recommended to conduct a clinical drug-drug interaction study if the IC50 value obtained in cells expressing OCT2 is less than or equal to 10-fold the unbound Cmax value in humans [Because OCT2-mediated drug-drug interactions are dose dependent, it is imperative to evaluate whether the unbound plasma concentration  was further quantified for nine drugs which were among the most potent inhibitors of OCT2-mediated metformin transport in our screening assay  of metformin by a maximum of 73%, i.e., the fraction of CLR that is tubular secreted. For comparison, the maximum inhibition of metformin CLR in clinical drug-drug interaction studies was between 37% and 35% for the OCT2-inhibitors pyrimethamine, trimethoprim, and cimetidine [in vivo findings, it is important to note that OCT2 inhibitors may also be inhibitors of MATEs, which are localized at the apical membrane of proximal tubule cells, and clinical inhibition interactions with metformin may involve MATE1 or MATE2-K in addition to, or even instead of, OCT2 [Complete block of tubular metformin transport would decrease renal clearance , although the mechanism is not understood. Even if stimulation would occur in vivo, we consider transporter inhibition as considerably more critical since it leads to reduced renal drug secretion and thus potentially drug toxicity.While several drugs inhibited OCT2-mediated substrate uptake or had no effect, we also noted significantly enhanced substrate uptake in the presence of some other drugs. “Negative” inhibition, i.e., transporter stimulation in vitro inhibition assays with the respective clinically used OCT2—substrates (e.g. metformin) for the prediction of potential drug-drug interactions in vivo. The observed substrate dependence of inhibitor affinities also highlights a limitation of previous pharmacophore and structure activity models that were developed to predict in silico OCT2-mediated drug-drug interactions of new molecular entities during drug development [Our findings confirm the hypothesis that inhibition of OCT2 by clinically used drugs is strongly substrate-dependent. Therefore it is important to conduct elopment , 23. TheS1 FigEach bar represents one compound tested in HEK-OCT2 cells at a concentration of 200 μM. Data are presented as the mean ± standard error ; ASS, acetylsalicylic acid.(TIF)Click here for additional data file.S2 FigEach bar represents one compound tested in HEK-OCT2 cells at a concentration of 200 μM. Data are presented as the mean ± standard error ; ASS, acetylsalicylic acid.(TIF)Click here for additional data file.S1 TableList of frequently prescribed drugs which were included in the screening library with their Anatomical Therapeutic Chemical (ATC) codes and Chemical Abstracts Service (CAS) numbers and experimentally determined inhibition of OCT2 by these compounds. MF, metformin; ASS, acetylsalicylic acid.(PDF)Click here for additional data file.


In vitro evaluation of P-glycoprotein (P-gp) inhibitory potential is now a regulatory issue during drug development, in order to predict clinical inhibition of P-gp and subsequent drug–drug interactions. Assays for this purpose, commonly based on P-gp-expressing cell lines and digoxin as a reference P-gp substrate probe, unfortunately exhibit high variability, raising thus the question of developing alternative or complementary tests for measuring inhibition of P-gp activity. In this context, the present study was designed to investigate the use of the fluorescent dye rhodamine 123 as a reference P-gp substrate probe for characterizing P-gp inhibitory potential of 16 structurally-unrelated drugs known to interact with P-gp. 14/16 of these P-gp inhibitors were found to increase rhodamine 123 accumulation in P-gp-overexpressing MCF7R cells, thus allowing the determination of their P-gp inhibitory potential, i.e., their half maximal inhibitor concentration (IC50) value towards P-gp-mediated transport of the dye. These IC50 values were in the range of variability of previously reported IC50 for P-gp and can be used for the prediction of clinical P-gp inhibition according to Food and Drug Administration (FDA) criteria, with notable sensitivity (80%). Therefore, the data demonstrated the feasibility of the use of rhodamine 123 for evaluating the P-gp inhibitory potential of drugs. ABCB1), is an ATP-binding cassette (ABC) membrane transporter acting as a drug efflux pump ) divided by its in vitro P-gp inhibitory potency (IC50) is greater than or equal to 0.1 or, for orally administered drugs, its nominal gut concentration ([I2]) divided by its IC50 towards P-gp is greater than or equal to 10 /IC50 and [I2]/IC50 ratio in relation to relevance or non relevance of clinical DDI studies dealing with P-gp and digoxin was performed using a binary classification decision tree, given a fixed discrimination threshold, resulting in four possible outcomes /IC50 and [I2]/IC50 were calculated with IC50 values determined from the rhodamine 123 assay for each DDI study (data not shown) and were used to predict P-gp-related DDI for the 26 clinical studies according to FDA criteria ([I1]/IC50 > 0.1 and/or [I2]/IC50 > 10). Prediction results for the 26 clinical studies are indicated in 50 values from rhodamine 123 assays and FDA criteria  in the present study. However, it is noteworthy that a high rate of false positives (51%) has also been reported in previous predictions of clinical P-gp inhibition with a much larger clinical data set (n = 101) [2] criterion proposed by the FDA, for which a clinical digoxin study becomes warranted for many drugs with a quantifiable IC50 /IC50 > 0.03 and/or [I2]/IC50 > 45 /IC50 > 6.5). Applying the “P-gp IC50 working group” criteria to IC50 values generated from rhodamine 123 accumulation assays allowed the enhancement of specificity and accuracy to 50% and 73.1% . The findings indicate the suitability of the rhodamine 123-based assay for in vitro prediction of the clinical risk of interactions with P-gp, notably during drug screening and early development. However, the P-gp inhibitory potential of drugs not interacting with the R-site of P-gp is likely to be complementarily investigated using additional substrates of the pump, thus confirming that accurate prediction of clinically significant P-gp drug interactions require the use of multiple P-gp substrates [The fluorescent dye rhodamine 123 was demonstrated to be convenient for characterizing the P-gp inhibitory potential of various reference P-gp inhibitors. As an exception, itraconazole and sertraline produce a negative result in the rhodamine 123 assay and are assumed not to interact with the R-site of P-gp. For drugs inhibiting efflux of rhodamine 123, IC


The results showed that Cd caused a significant increase in the urinary excretion of cystatin C that occurred 3–4 weeks before the onset of polyuria and proteinuria. Serum levels of cystatin C were not altered by Cd. Immunolabeling studies showed that Cd caused the relocalization of cystatin C from the cytoplasm to the apical surface of the epithelial cells of the proximal tubule. The Cd-induced changes in cystatin C labelling paralleled those of the brush border transport protein, megalin, which has been implicated as a mediator of cystatin C uptake in the proximal tubule. These results indicate that Cd increases the urinary excretion of cystatin C, and they suggest that this effect may involve disruption of megalin-mediated uptake of cystatin C by epithelial cells of the proximal tubule.Cadmium (Cd) is a nephrotoxic environmental pollutant that causes insidious injury to the proximal tubule that results in severe polyuria and proteinuria. Cystatin C is a low molecular weight protein that is being evaluated as a serum and urinary biomarker for various types of ischemic and nephrotoxic renal injury. The objective of the present study was to determine if cystatin C might be a useful early biomarker of Cd nephrotoxicity. Male Sprague–Dawley rats were given daily injections of Cd for up to 12 weeks. At 3, 6, 9 and 12 weeks, urine samples were analyzed for cystatin C, protein, creatinine, β Cd is an important industrial and environmental pollutant that can damage various organs including the lung, liver, kidney and bone ATSDR . In addi2-microglobulin and metallothionein, and the proximal tubule-derived enzyme N-acetyl-β-d-glucosaminidase (NAG) , serum creatinine and urinary protein are not sensitive markers of Cd-induced kidney injury. Over the years, several other urinary biomarkers have been found to be more sensitive indicators of Cd-nephrotoxicity. Some of the biomarkers that have proven to be most useful include low molecular weight proteins such as βCystatin C is a 13 kDa cysteine protease inhibitor that is produced by cells throughout the body. Cystatin C is abundant in serum/plasma and is readily filtered at the glomerulus. Serum levels of cystatin C have been proposed as a useful marker to estimate glomerular filtration rate .The present studies were aimed at further characterizing the possible utility of cystatin C as an early urinary and/or serum biomarker of Cd nephrotoxicity. In addition, we examined the effects of Cd on the localization of cystatin C in the kidney. These studies involved the use of a well-established model of long-term Cd-exposure in the rat and the direct comparison of the cystatin C results with those of a panel of standard markers of Cd toxicity and kidney function (β2 at a Cd dose of 0.6 mg (5.36 µmol)/kg in 0.25–0.35 ml isotonic saline for up to 12 weeks. Control group animals (n = 6) received daily injections of the saline vehicle alone. After 3, 6, 9 and 12 weeks of treatment, the animals were placed in individual metabolic cages and 24 h urine samples were collected. The animals were allowed free access to water at all times. Food was also available ad libitum, except during the period in which the urine samples were being collected. The 12 week Cd treatment protocol was repeated twice and data from the two treatment protocols were pooled whenever possible. In another study, groups of animals were treated with varying doses of Cd  5 days per week for 1–3 weeks. Before the start of each experiment, the Cd concentrations of all stock solutions used for the various treatment protocols were verified by Chemical Solutions, Inc. using the technique of inductively coupled plasma mass spectroscopy.Animal work was conducted in compliance with the United States NIH Guide for the Care and Use of Laboratory Animals  (R+D Systems) according to the manufacturer’s protocol.2-microglobulin, were determined by microsphere-based Luminex x MAP technology using the MagPix xPONENT 4.1 equipment. The Multiplex technology allows for the determination of multiple analyses in a single sample and provides much greater sensitivities and dynamic ranges than commonly-used ELISA’s. This technique is similar to the assay that has been used to determine urinary levels of Kim-1 in our previous studies  were deparaffinized in xylene, rehydrated with a series of alcohol washes, and then incubated for 20 min at 95 °C in a citrate buffer solution . The sections were quenched for endogenous peroxidase by incubation in 0.3 % hydrogen peroxide in methanol at −20 °C. After quenching, the sections were blocked at room temp for 15 min in undiluted Background Reducing Buffer . The samples were then incubated overnight at 4 °C in the primary antibodies, either a 1:100 dilution of goat anti-cystatin C  or a 1:100 dilution of rabbit anti-megalin .The primary antibodies were visualized using the avidin–biotin horseradish peroxidase technique according to the manufacturer’s protocol . The samples were then counterstained with hematoxylin. Negative controls consisted of tissue sections that were incubated without the primary antibody.In other experiments, a dual-labeling indirect confocal immunofluorescence procedure was used to visualize cystatin C and megalin in the same tissue sections. Fresh cryosections of rat kidney (5–20 µm) were fixed and permeabilized for 10 min in −20 °C methanol and then incubated for 15 min in undiluted Background Reducing Buffer . The samples were then incubated overnight at 4 °C in the primary antibodies at a 1:100 dilution of goat anti-cystatin C  or a 1:100 dilution of rabbit anti-megalin . The samples were washed in PBS and incubated for 40 min in the secondary antibodies at a 1:200 dilution of TRITC conjugated chicken anti-rabbit IgG  and a 1:100 dilution of Alexa Fluor488-conjugated donkey anti-goat IgG . Samples were then washed in deionized water, mounted and viewed. Controls consisted of samples that were incubated without the primary antibodies.For most of the studies, samples were viewed with a Nikon Eclipse E-400 microscope using a ×40 objective. Images were captured with a digital camera (Media Cybernetics) using automated exposure times and gain settings. The digital images were processed using the Image-Pro Plus image analysis software package (Media Cybernetics). To further characterize the patterns of cystatin C and megalin labeling in specific nephron segments, some of the samples were also examined using a Nikon Eclipse Ti microscope fitted with a Nikon A1R confocal interface with Nikon Elements C software on a HPZ400 computer. A stack of up to 100 images per section was acquired in 0.05 micron increments under a ×60 oil objective and representative images were selected from each stack.Negative controls for all labeling studies consisted of kidney sections that were incubated without the primary antibodies, as well as sections that were incubated with non-diluted, non-immune serum from the same species in which the primary antibodies had been generated. To rule out the possibility that any apparent labeling may have resulted from fluorescence “spill over” when the FITC labeled samples were viewed with the TRITC filter configuration and vice versa, all experiments also included a group of samples that were labeled with each of the TRITC- or FITC-tagged antibodies individually. When the TRITC-labeled samples were viewed with the FITC filter configuration and the FITC-labeled samples were viewed with the TRITC filters, no labeling was evident in any of the samples. All labeling experiments were repeated at least three times and appeared to be highly reproducible.For the immunohistochemistry images in Fig. http://onlinelibrary.wiley.com/doi/10.1111/j.1365.tb03313.x/abstract).Fluorescence co-localization of cystatin C and megalin images in Fig. Statistical analyses were done using the GraphPad Prism Computer Program. Data for the various serum and urinary parameters were evaluated by two different types of analyses. The first approach involved the use of standard two-way ANOVA, followed by post hoc Tukey’s tests to determine the differences among the various treatment groups, whenever the p value for the ANOVA was less than 0.05. This was done because similar tests have been commonly used in many of the previous studies on the urinary excretion of these markers in similar animal models  and Kim-1 (f). As may be seen, treatment with Cd, increased urine volume (graph a) and total urinary protein excretion (graph b). These changes reached levels of statistical significance after about 9 weeks of Cd exposure. Cd had no significant effect on the urinary excretion of creatinine even after 12 weeks (graph c). The development of polyuria and proteinuria, with no change in creatinine excretion is characteristic of Cd-induced proximal tubule dysfunction  and the more-recently described marker Kim-1 (graph f). It should be noted that in the present study, even though Kim-1 appeared to be slightly increased after as little as 6 weeks into the treatment protocol, the increase did not reach a level of statistical significance until 9 weeks. Our previous studies with Kim-1 using this same model showed significant increases in urinary Kim-1 after only 6 weeks. We cannot explain the reason for this slight discrepancy. However, it is interesting to note that when the Kim-1 data from weeks 3 and 6 of the present study were analyzed without inclusion of the 9 and 12 week data, the increase in Kim-1 was statistically significant (p < 0.05) at 6 weeks. This illustrates the fact that as the variance of the biomarker data increases with longer exposure times, the statistical significance of changes that might be evident at earlier time points can be obscured. In this context, the significance of results of a particular biomarker at any given time point is to a certain extent dependent on the duration of exposure in the overall study.Figure 2 microglobulin were also within reference ranges provided by the manufacturer of the reagents (Millipore Inc.). Moreover, similar values for urinary cystatin C, β2 microglobulin and Kim-1 have been reported by other investigators  began to lose weight early in the treatment protocol. Accordingly, their treatment was terminated after only 1 week. Results of the complete study are shown in Fig. In order to evaluate the possible functional significance of the Cd-induced increase in urinary cystatin C excretion, we utilized an immunohistochemical procedure to examine the effects of Cd on the localization of cystatin C in kidney tissue sections. As may be seen in the control sections shown in Fig. In examining these images, we noticed that the general pattern of cystatin C labeling was similar, in many respects, to previously-published images showing the localization of the proximal tubular transport protein megalin . Over time, however, Cd exposure altered the localization patterns of cystatin C and it co-localized more strongly with megalin. For 9 weeks and 12 weeks of Cd exposure, the Pearson’s correlation coefficients between cystatin C and megalin were 0.70 and 0.78, and the Manders co-localization coefficients were 0.95 and 0.91, respectively. It should be noted that these particular images could not be used for more sophisticated statistical analyses because the fluorescence data in each image is essentially treated as n = 1. This is in contrast to the immunoperoxidase images shown in Fig. Cystatin C is an emerging marker of both ischemic and nephrotoxic kidney injury  is that they are very sensitive, but also general, markers of kidney injury. Even though they are sensitive markers of injury, none of the markers are specific indicators of Cd toxicity per se. Thus, even with the use of these biomarkers to detect kidney injury, appropriate patient histories and direct analyses of Cd in tissues and fluids are still necessary for the appropriate diagnosis of Cd-induced kidney injury  (Prozialeck et al.


The impressively low cost and improved quality of genome sequencing provides to researchers of genetic diseases, such as cancer, a powerful tool to better understand the underlying genetic mechanisms of those diseases and treat them with effective targeted therapies. Thus, a number of projects today sequence the DNA of large patient populations each of which produces at least hundreds of terra-bytes of data. Now the challenge is to provide the produced data on demand to interested parties.In this paper, we show that the response to this challenge is a modified version of Spark SQL, a distributed SQL execution engine, that handles efficiently joins that use genomic intervals as keys. With this modification, Spark SQL serves such joins more than 50× faster than its existing brute force approach and 8× faster than similar distributed implementations. Thus, Spark SQL can replace existing practices to retrieve genomic data and, as we show, allow users to reduce the number of lines of software code that needs to be developed to query such data by an order of magnitude.The online version of this article (doi:10.1186/s12859-016-0904-1) contains supplementary material, which is available to authorized users. In this paper, we present an enhancement to Apache Spark, which is a distributed computing framework, to accommodate efficiently SQL queries on genomic datasets. Although one can use existing technologies to import genomic datasets as SQL tables, the poor performance of those technologies to common genomic queries has made them an unattractive choice among users of Next Generation Sequencing (NGS) data.As sequencing costs drop, more and more research centers invest in massive sequencing projects that aim to build huge databases of thousands of genomes and their associated phenotypic traits. For example the Oregon Health and Sciences University (OHSU) and the Multiple Myeloma Foundation (MMRF) are sequencing 1000 patients with Acute Myeloid Leukemia (AML) and Multiple Myeloma respectively . In anotAccess to those data, though crucial for the advancement of cancer treatment, remains a challenge for researchers and data scientists.Scripts must be created to analyze these experimentsIt requires users to manually parallelize the execution of those tools in distributed environments which get adopted to serve the increasing amounts of generated data.It creates storage overheads with the possible creation of intermediate files that are used to transform files.Today there are two tiers of data access: a top and bottom tier. The top tier involves the downloading of FASTQ, BAM, or VCF files from an archive such as the SRA  or CGHUBAssuming that genomic data in the order of Terabytes and Petabytes reside in distributed environments as in , we propIn this work we use Spark SQL which is the distributed SQL execution engine of the Apache Spark  frameworIn this work we assume that all genomic data are in ADAM format. ADAM , 10 is aADAM records consist of serializable objects that are stored in a distributed friendly column based format. It uses Apache AVRO  as a datSpark SQL fully recognizes Parquet files and consequently ADAM files as relational tables and it also infers their schemas. This allows users to natively query ADAM files from SPARK SQL.15 records and it is prohibitively slow to compute.Although Spark SQL provides impressive expressive power and thus it can execute any genomic query, the main obstacle for its adoption to query genomic data has been its slow performance on two of the most frequently encountered queries: 1) random range selection, and 2) joins with interval keys. Random range selection in a collection of aligned reads took several minutes to run in a small cluster, which is embarrassingly slow given that samtools need only a few seconds. Fortunately, the rapid evolution of the open source libraries that we use (in particular Parquet on which ADAM files depend and whose API Spark SQL uses for their filtering) improved the execution of those queries by an order of magnitude as we show in the results section. Regarding the execution of interval joins between two tables, Spark SQL uses the obvious execution of filtering on their cross product. However, given the sizes that are involved in genomic data such an approach is unrealistic. If we consider for example an interval join between 1 billion aligned reads with 1 million variants, the cross product between them is 10The contribution of this paper addresses the second performance bottleneck: joins on interval keys. We present a modification to Spark SQL that enhances the efficiency of interval joins and it thus makes it suitable to query genomic data. For this reason we use interval trees to interval join two tables in a distributed setting.The first generation of tools that access genomic data involves packages such as Samtools , vcftoolThe second generation of relevant software involves the Genome Query Language (GQL) , which pThe third generation leverages the Hadoop ecosystem to easily provide data on demand on a distributed setting. For example, the GenomeMetric Query Language (GMQL)  uses ApaThis section describes how we modified Spark SQL to add support for range based joins. The first step of the modification involves the grammar of Spark SQL, which we extended to simplify the syntax of those queries. Next, before describing our modification to the execution engine of Spark SQL, we provide a brief description of the interval tree and interval forest data structures which this modification utilizes.Although the existing syntax of Spark SQL suffices for a user to describe a join between two tables on interval overlap condition, it looks complex and counter intuitive for a user of genomic collections that routinely uses this operation. If we consider for example tables A  and B , then according to the current syntax of Spark SQL, an interval join looks like the following:RANGEJOIN and GENOMEOVERLAP. In case of an interval based join, the former keyword replaces JOIN and the latter, which is followed by two tuples as arguments, specifies the overlap condition and is the only argument of the ON condition.To eliminate the complexity of such a frequent operation, we enhanced the vocabulary of Spark SQL with two extra keywords, namely Using those new keywords, one can type the query of the previous example as follows:n intervals in O :chromosome(string):txStart(long):txEnd(long):function(string)〉. If table A contains entries 〈 “ gene1" :chr3:100:1000: “ function1" 〉 and 〈 “ gene2" :chr3:4000:5000: “ function2" 〉 then table A1 is In the first stage of the join between distributed tables A and B on interval keys and assuming A is the table with the fewest records, Spark SQL first creates distributed table A1 which is a transformation of table A into a key-value pair whose keys are the indices of each record. Note those indices are easy to obtain in Spark using the built-in function and the contents of table A2 are In the second stage of the implementation, the driver of the Spark cluster collects A2 into its local memory and it uses it to create an interval forest according to the description of the previous subsections. Then the driver broadcasts the resulted interval forest to the worker nodes.index values of table A2. In order to create table T1, Spark SQL transforms table B by using its interval keys to look up the interval forest that all worker nodes obtained from the previous step. For example consider table B with schema 〈id(string):chromosome(string):readStart(long):readEnd(long)〉. If table B contains entries In the third stage, Spark SQL creates table T1 with records that consist of a tuple whose first element involves a record from table B and its second element is one of the and A2 is the table that we created in the previous paragraph whose interval keys created the interval forest, then only the first tuple of table B will query successfully the interval forest since its interval overlaps with the first interval of table A2. Thus the contents of table T1 are The last stage of the operation involves the generation of the final distributed table, which is the result of the range join and it consists of a tuple where the first element involves a record from table A and the second element involves a record from table B. In order to construct the output, Spark SQL joins table T1 with table A1 on the integer keys of A1 which have to match with the second element of the tuples of T1. So, in our example the transformation of T1 gives table T with contents We demonstrate the suitability of Spark SQL on querying genomic datasets through a series of queries that involve random access of ranges and range joins. In our examples we used the ADAM representation of the raw data (BAM file of size 250 GB) of the platinum genome NA12878. Our hardware consisted of a Spark cluster with 5 workers all of which were m2.4xlarge instances on the Amazon EC2cloud.We start by demonstrating the maturation of the technologies that we use through a random access of a simple range of gene NPM1. The query that we type is the following:We ran the query against two different versions of the Parquet library that comprises the storage model of ADAM and whose API Spark SQL uses to evaluate filter predicates on Parquet encoded files. The earlier version of this library took 10 min to run while the latest version took 75 s. The difference was due to the fact that although the earlier versions of Parquet were evaluating a predicate on every single record of a file, recent ones utilize metadata to ignore retrieving unnecessary blocks of data. Of course, a minute long latency for such a query still seems incompetent compared to the second long latency that samtools obtain in single node through secondary indexes, but the observed trends make us believe that future improvements on the used libraries are going to bridge that gap.9 records with all 94 K records of the clinvar vcf that is provided at the dbsnp archive for build 142. Of course, the brute force solution which is a filtering operation on the cross product of the two tables is unrealistic since the cross product consists of a number of records in the order of 1014. The query that we used is:In the second query, we demonstrate the efficiency of our implementation of interval joins. Note that this query joins all mapped reads of NA12878 which is in the order of 10Table The next experiment demonstrates the scalability of our range join implementation by modifying the number of Spark workers that are used for the execution of the previous query. Figure To examine the small slope of the curve of Fig. intersect feature of BEDtools to retrieve all those alignments of NA12878 that overlap with any locus of the clinvar dataset.We used the We wrote custom software using the samtools API to further process the retrieved alignments and discard those whose reads contain the reference allele.Our final experiment stresses the tremendous savings in programmer productivity that the use of Spark SQL yields compared to the alternatives that researchers use today. The query that we used in this example was: “Are there any reads of the NA12878 dataset that align with the reference genome only with matches or mismatches (M CIGAR operations only), overlap with any variant location of the clinvar dataset and contain the respective alternate allele?”. Using existing genomic processing software, we implemented the same query in two steps: WHERE statement that filters out rows with either complex CIGAR strings or with sequences that do not contain the alternate allele in the respective positions; the resulted Spark SQL script, which we also include as an additional file  or with annotated files.Out of the two categories of software that query large amounts of data, NoSQL systems and distributed SQL execution engines, in this work we use a distributed SQL execution engine to address these needs because of its expressive power, and its scalability. As traditional relational databases are hard to scale, large amounts of data can be accessed via NoSQL systems such as MongoDB , HBase , and CasOf course, Spark SQL is not the only distributed SQL execution engine, but we chose it in this work because of its sophisticated and extensible query planner. Big Data users have been using distributed SQL execution engines as an abstraction of distributed operations, such as map and reduce, through relational algebra operations. Earlier engines, such as Shark , Hive 2, and ImpThe central message of this paper is that a state of the art distributed SQL execution engine, such as Spark SQL, can be modified to provide an interactive SQL interface on all kinds of genomic data. Of course, other tools, such as samtools and bedtools can provide similar functionality, but Spark SQL provides a simple and expressive mechanism of querying heterogeneous genomic data over distributed hardware setups. And we expect that as big data technologies mature, the performance of Spark SQL is going to match the performance of today’s popular tools.Project name: GenApProject homepage: branch rangeJoinsExtraPredicates-1.3 of https://github.com/kozanitis/spark. see Additional file 1 for instructions on how to clone and build the project.Operating systems: LinuxProgramming Language: ScalaOther requirements: Maven, Java. We verified that the project builds with Maven 10.10.4 and runs with Java version 1.7.0_51Licence: Apache 2


O-glucoside) and its aglycone , isolated from a 50% ethanol extract of Plantago major seeds (Plantaginaceae), were established to be potent inhibitors of the Maillard reaction. These compounds also inhibited the formation of advanced glycation end products in proteins in physiological conditions and inhibited protein cross-linking glycation. These results indicate that P. major seeds have potential therapeutic applications in the prevention of diabetic complications. Plantagoside (5,7,4′,5′-tetrahydroxyflavanone-3′- Nεe-(carboxymethyl)lysine +; 1H-NMR  δ: 2.70 , 3.07 , 4.64 , 5.32 , 5.81 , 5.82 , 6.56 , 6.70 ; 13C-NMR  δ: 41.9 (C-3), 60.7 (glc-6), 69.8 (glc-4), 73.3 (glc-2), 75.9 (glc-5), 77.1 (glc-3), 78.4 (C-2), 95.0 (C-8), 95.8 (C-6), 101.7 (C-10), 102.4 (glc-1), 106.4 (C-6′), 109.2 (C-2′), 128.6 (C-1′), 135.2 (C-4′), 145.7 (C-3′), 145.8 (C-5′), 162.8 (C-9), 163.4 (C-5), 166.7 (C-7), 196.1 (C-4).Plantagoside (2): negative-ion FAB-MS m/z: 303 [M-H]+; 1H-NMR  δ: 2.70 , 3.07 , 5.32 , 5.81 , 5.82 , 6.56 .5,7,3′,4′,5′-Pentahydroxyflavanone  was added to AlCl3 (8 g) and NaCl (1.4 g) and melted by heating at 180°C. After 10 min, the reaction mixture was cooled and dissolved in 2 N HCl, and 3 (2 mg) was extracted with ethylacetate. 1H-NMR  δ: 6.20 , 6.46 , 7.10 , 12.98 .5,7-Dihydroxy-3′,4′,5′-trimethoxyflavone ( P. major seeds. The active compounds were characterized as plantagoside (1) and its aglycone (2) after analyzing the FAB-MS, 1H-NMR, and 13C-NMR spectral data  and 2  were approximately 83- and 5.5-times stronger, respectively, than that of aminoguanidine , which was used as a known Maillard reaction inhibitor [50, 25.0 μM), baicalein (IC50 > 100 μM), quercetin , and maritimein ). These results indicated that 1 had the highest inhibitory activity among the known isolated natural products.We examined 200 natural plant extracts to determine their inhibitory effects on the Maillard reaction and obtained satisfactory results with an extract ofral data . Flavanojaponica  and Heliacteatum . α-Mannoed for 1 . The Mainhibitor  in our enhibitor . It has nhibitor , quercetnhibitor , and mar 2 IC50, .0 μM wer 1 and 2 in physiological conditions, collagen, one of the major proteins in the human body, was used as a substrate instead of BSA. The incubation temperature was changed to 37°C from 60°C. The inhibitory activities (IC50) were 14 μM for 1, 42 μM for 2, and 2500 μM for aminoguanidine. The inhibitory activity of each compound was 2–25-times lower than that obtained using the original conditions. When BSA was used as the substrate and the reaction temperature was high, the rank order of the inhibitory activity of each compound remained unchanged. These results demonstrated that our improved Maillard reaction inhibitor screening method is very useful for bioassay-guided isolation of effective compounds and evaluation of the inhibitory activities of such compounds. Plantagoside was identified using this assay, and it was found to inhibit the formation of AGEs in physiological conditions at a lower concentration.To clarify the inhibitory activities of3, which inhibits by reducing Amadori products to a secondary amine [3 (lane 3) inhibited the dimerization of lysozyme, while 12.5–200 μM plantagoside also caused inhibition in a concentration-dependent manner (lanes 4–8). The results showed that plantagoside can inhibit the formation of protein-protein cross-links via glycation and the formation of AGEs in proteins.For evaluating the inhibitory activity of plantagoside against glycation-dependent cross-link formation, each inhibitor, that is, plantagoside and aminoguanidine, which inhibit cross-link formation by linking with the carbonyl groups of Amadori products , or NaCNry amine , was incα-acetyllysine or N-α-acetylarginine. Plantagoside with N-α-acetyllysine and N-α-acetylarginine as the substrate possessed 46% and 73% inhibitory activities, respectively,  at a concentration of 25 μM and strongly inhibited the formation of AGEs with N-α-acetylarginine ; myricetin, 6 (7.9 μM); 5,7,3′,4′,5′-pentahydroxyflavanone, 2 (18.0 μM); and dihydromyricetin, 7 (45.0 μM); 5,7,3′,4′,5′-pentahydroxyflavone possessed the highest activity among the aglycones. The results suggested that the putative compound 5,7,4′,5′-tetrahydroxyflavone-3′-O-glucoside (5) would possess a potent inhibitory activity at a submicromolar concentration, given that the inhibitory activity was 15-times higher after 3′-O-glycosylation of 5,7,3′,4′,5′-pentahydroxyflavanone (2). Therefore, we intend to synthesize 5, which has not been obtained from natural resources.To develop a more effective inhibitor, we investigated the relationship between the skeletal structures of the aglycones of plantagoside (flavone, P. major seeds that contain these flavanones are known as “Shazenshi,” which is a well-known crude drug. The seed of P. asiatica is used as a diuretic in traditional Chinese medicine. There are no reports on the treatment or prevention of diabetic complications using this drug; however, the present study suggests that Shazenshi has potential as a therapeutic agent to combat diabetic complications.In this study, we demonstrated the inhibitory activity of plantagoside and its aglycone against the Maillard reaction. In Europe and the USA, the