Objectives: Effluents contain a diverse abundance of antibiotic resistance genes that augment the resistome of receiving aquatic environments. However, uncertainty remains regarding their temporal persistence, transcription and response to anthropogenic factors, such as antibiotic usage. We present a spatiotemporal study within a river catchment  that aims to determine the contribution of antibiotic resistance gene-containing effluents originating from sites of varying antibiotic usage to the receiving environment.Methods: Gene abundance in effluents  was compared against background samples of the receiving aquatic environment (i.e. the catchment source) to determine the resistome contribution of effluents. We used metagenomics and metatranscriptomics to correlate DNA and RNA abundance and identified differentially regulated gene transcripts.Results: We found that mean antibiotic resistance gene and transcript abundances were correlated for both hospital  and farm  effluents and that two β-lactam resistance genes (blaGES and blaOXA) were overexpressed in all hospital effluent samples. High β-lactam resistance gene transcript abundance was related to hospital antibiotic usage over time and hospital effluents contained antibiotic residues.Conclusions: We conclude that effluents contribute high levels of antibiotic resistance genes to the aquatic environment; these genes are expressed at significant levels and are possibly related to the level of antibiotic usage at the effluent source. The rise of antibiotic resistance in clinical pathogens is occurring at an alarming rate, severely jeopardizing the sustainability of antibiotic use in human and veterinary medicine.The impact that anthropogenic activities are having on the resistome has fuelled a great deal of research and debate concerning the augmentation of the resistome and the emergence of antibiotic-resistant pathogens.,Metagenomics, combined with the Search Engine for Antimicrobial Resistance (SEAR),In this study, we examined ARG abundance across a series of monthly effluent samples that originated from two sites of varying antibiotic usage . ARG abundance was compared against background samples of the receiving aquatic environment (i.e. the source of the river catchment) to determine the relative contribution of effluents to the resistome. In addition, we employed metatranscriptomics to detect ARG transcripts and correlated them to the corresponding ARGs in each sample, facilitating the identification of differentially expressed transcripts over the sampling period. This study also assessed the selective pressures acting on the sampled microbial communities through use of LC–MS to detect antibiotic residues in the samples, as well as examining antibiotic usage data for the site of high antibiotic consumption. The combined data from this study are used to assess the impact of anthropogenic activities on the resistome.Samples were collected from three sources within the River Cam catchment, Cambridge, UK, on 2 May 2013 and five further samples over a 5 month period between August 2014 and December 2014 an average of 5 weeks apart . Quantification standards were created for the three most used compounds in each class of antibiotics prescribed at Cambridge University Hospitals in 2013 as described below. No standards could be generated for aminoglycosides or trimethoprim.,Monthly antibiotic usage data for periods overlapping sample collection were obtained for Cambridge University Hospitals. Hospital antibiotic usage was calculated as DDDs (per 1000 bed days), which is the assumed average maintenance dose per day for a given drug and is used as a statistical measure of drug consumption.et al.t-tests were used to determine significant deviation of abundance ratios from zero. The resulting two-tailed P values then underwent false discovery rate (FDR) correction using the Benjamini–Hochberg method (α = 0.05) and were used to identify differentially regulated transcripts.,Differentially regulated transcripts were identified as in Franzosa In order to compare the relative ARG abundance in each sample type, metagenomic DNA from three sites was sequenced on multiple occasions. This study generated 102 giga bp (Gbp) of sequencing data across all samples   were being expressed, metatranscriptomics was used to interrogate effluent samples for the presence of ARG transcripts. Two RNA samples from both the hospital and the farm effluents failed sequencing library quality checking and were removed from the study Table . A totalet al.ρ = 0.9, two-tailed P <0.0001) and farm effluents   and a significant 2-fold mean change in transcript abundance was observed for blaOXA transcripts  [data not shown and Table S1 (available as JAC Online)]. The β-lactam genes blaGES and blaOXA were present but not overexpressed in the farm effluent samples.To identify differentially regulated transcripts, particularly overexpressed ARGs, across our effluent samples, we applied the global model for metagenome versus metatranscriptome regulation described by Franzosa ) Figure . The dev) Figure . The β-lblaGES and blaOXA) in the hospital effluent samples, to investigate whether the genes were overexpressed as a result of anthropogenic activity we looked at the effect of hospital antibiotic usage on the abundance of β-lactam ARG transcripts. Antimicrobial drug usage data were obtained for the hospital and used to calculate the total volume of drugs used in the hospital each month (Table S2). Monthly drug usage for each antibiotic class was converted into a DDD (per 1000 bed days) value and the relative β-lactam usage was calculated for each month preceding metatranscriptome sample collection; monthly β-lactam usage  was found to change in line with relative ARG transcript abundance in the three sequential hospital effluent metatranscriptomes . In total, 23 antibiotic residues from the testing panel were detected in the hospital effluent across all the sampling dates. However, in the sequentially sampled monthly metatranscriptomes, β-lactam antibiotic residues (for flucloxacillin) were only detected in November 2014  and the mean abundance values for the effluents were significantly greater than the mean abundance value for the background river catchment.This study also incorporated LC–MS and antibiotic usage data for the site of high antibiotic consumption, Cambridge University Hospitals. Although anecdotal, the similar trends observed between β-lactam transcript abundance and the hospital β-lactam usage over the same 3 month period, combined with the presence of antibiotics at low concentrations in the effluents, gives weight to the argument that anthropogenic activities may impact ARGs in the environment.blaGES and blaOXA were expressed in both hospital and farm effluents but they were only found to be overexpressed in hospital effluents. This significant overexpression of ARGs occurring in an environment that is heavily impacted by antibiotic use, compared with the much lower expression found in farm effluents (subject to a much lower use of antibiotics), may be an example of human activity augmenting the aquatic resistome.In terms of the overexpression of β-lactam resistance genes, the genes The combined data from this study were used to assess the impact of anthropogenic activities on the resistome. To date there have been limited temporal studies in this area and the use of background sampling is still to be routinely adopted. The powerful combination of metagenomics and metatranscriptomics provides further insight into a complex problem and we believe this to be the first report of ARGs being overexpressed in effluents. Although we try to link between ARG expression and antibiotic usage at the effluent source Figure , it mustCombining genomic technologies and environmental metadata to inform antibiotic stewardship is an exciting prospect and one that is being actively pursued. Future studies should consider including metatranscriptomics to identify ARG transcripts in environmental samples, developing the methodology further or using a single-cell approach to gain greater resolution of the species involved in the expression of genes of interest.,While similar approaches that combine metagenomics and metatranscriptomics have been used to study the impact of anthropogenic activities on microbial communities,To conclude, our results indicate that effluents originating from sites of antibiotic usage and entering a river catchment are regularly contributing ARGs to the resistome; these ARGs are expressed and are more abundant than in background samples of the river catchment. The clinical impact of these ARGs re-entering the human population after release into the natural environment is clearly an area of future work, and consideration must also be given to the role of effluents in effective antibiotic stewardship.Supplementary DataClick here for additional data file.


The prediction of the chloride-induced corrosion is very important because of the durable life of concrete structure. To simulate more realistic durability performance of concrete structures, complex scientific methods and more accurate material models are needed. In order to predict the robust results of corrosion initiation time and to describe the thin layer from concrete surface to reinforcement, a large number of fine meshes are also used. The purpose of this study is to suggest more realistic physical model regarding coupled hygro-chemo transport and to implement the model with parallel finite element algorithm. Furthermore, microclimate model with environmental humidity and seasonal temperature is adopted. As a result, the prediction model of chloride diffusion under unsaturated condition was developed with parallel algorithms and was applied to the existing bridge to validate the model with multi-boundary condition. As the number of processors increased, the computational time decreased until the number of processors became optimized. Then, the computational time increased because the communication time between the processors increased. The framework of present model can be extended to simulate the multi-species de-icing salts ingress into non-saturated concrete structures in future work. One of the main long-term durability problems of reinforced concrete structure is the corrosion of reinforcing bars (rebar) in concrete. The corrosion can be resulted from several necessary conditions, and one of them is a high concentration of chloride ions near rebars, where the chloride ions come from deicing chemicals used in the winter on roadways and parking structures or seawater for the off-shore structures. Once the chloride content on the surface of steel reinforcement reaches a threshold value and the moisture and oxygen are sufficiently provided, the corrosion of steel bar is initiated ,2. The cTo simulate more realistically the durability performance of reinforced concrete structures, sophisticated numerical methods for fully coupled moisture and chloride transport processes and reliable material models for the transport parameters are needed. In addition, in order to predict accurately the moisture and chloride distributions in a large reinforced concrete structure, a large number of fine finite element meshes are needed. For the use of the large meshes in numerical analysis, in this study, a parallel algorithm will be employed to a parallel processing system with up to 2000 processors. To consider more realistic boundary conditions on concrete structures, humidity model applied with random stochastic process will be demonstrated and approximately 1.5 million nodes and three million elements will be used. Furthermore, multi-boundary conditions to describe the actual chloride concentrations and humidity distribution will be applied instead of only constant boundary conditions.The two fully-coupled partial differential equations governing the coupled chloride and moisture diffusion through non-saturated concrete are simply derived by employing the mass balance equations and Fick’s law ,15.J) through a unit area of porous media depends on the gradient of chloride ions as well as the gradient of moisture as. Thus, Fick’s law is modified in this study to include the coupling effects between moisture and chloride transfer. The governing equations are shown in Equations (1) and (2).clD = chloride diffusion coefficient (cm2/day); fC = free chloride concentration ; HD = humidity diffusion coefficient; H = pore relative humidity; First, the flux of chloride ions  and (4),Equations (3) and (4) can be rewritten as,The general boundary conditions are as below, problem .To numerically solve the chloride diffusion problem, many material parameters must be determined: the moisture capacity (and (6)) .The moisture capacity of the concrete was developed based on the multiphase and multiscale model . Assumin995a, b) ,19,20,21A and B = chloride adsorption related constants, 0.3788 and 1.14, solβ = ratio of pore solution volume to concrete weight, L/g, and C-S-H gel to concrete (g/g) .Chloride diffusion coefficient in saturated concrete was studied by Xi and Bazant (1999) as following Equation (17),H), temperature (T), and free chloride concentration (In Equation (17), the functions of the chloride diffusivity consist of the concrete curing time (ion (Cf) .First factor of chloride diffusion coefficient accounts for the effect of the water–cement ratio (The second influence factor is to consider the effect of composite action of the aggregate and the cement paste in Equation (19),f3(H), in Equation (20) is to consider the effect of relative humidity level on the chloride diffusion coefficient. A model proposed by Bazant et al. (1972) can be used, which was developed initially for moisture diffusion [The third factor, iffusion .(20)f3 to introduce the temperature effect of the forth factor in chloride diffusion coefficient as shown in Equation (21),U can be found in the paper of Ababneh et al. (2003) [The detail description of diffusion process activation energy, . (2003) .m = 8.333 and 0.5, respectively, according to Xi and Bazant (1999) [The dependence of chloride diffusion coefficient on free chloride concentration t (1999) .nel is the total number of elements in space domain and In order to solve a time-dependent coupled moisture-chloride diffusion problem, a large linear system equation was derived with finite element method. The finite element formulation will be briefly introduced in this section. The continuous variables in the coupled chloride and moisture diffusion equations, free chloride  and (25) are defined in terms of nodal values, The nodal free chloride concentrations and relative humidity are solved by substituting the approximated values of Equations (24) and (25) into governing equations of Equations (5) and (6), and applying the Galerkin procedure to the weak forms, then the finite element matrix can be obtained as shown in Equation (29):In detail, the components in element matrices are as Equations (33)–(38),Finally, Equation (39) is also discretized in time space with time interval The value of parameter Equation (39) is simplified as linear system equation.In order to implement the parallel finite element program for the coupled moisture and chloride problem, various programs were employed such as Triangle for mesh generation, ParMETIS, PETSc , and MPI (Message Passing Interface) ,29,30,31In this study, Triangle was used for the mesh generation of triangle element, which was created at Carnegie Mellon University. Triangle generates exact delaunay triangulations, and are suitable for finite element analysis .PETSc (3.0.0 p8) is a large and versatile package integrating distributed vectors, distributed matrices in several sparse storage formats, Krylov subspace methods, preconditioners, and Newton-like nonlinear methods with built-in trust region or linesearch strategies and continuation for robustness. It is designed to provide the numerical infrastructure for application codes involving the implicit numerical solution of PDEs, and it uses on MPI for portability to most parallel machines. The PETSc library is written in C, but may be accessed from user codes written in C, Fortran, and C++ .MPI (Message Passing Interface) is a standardized and portable message-passing system designed to function on a wide variety of parallel computers. The standard defines the syntax and semantics of library routines and allows users to write portable programs in the main scientific programming languages  ,28,29.ParMETIS extends the functionality of METIS and includes routines based on a parallel graph-partitioning algorithm that are especially suited for parallel computations and large-scale numerical simulations involving unstructured meshes. In typical FEM computations, ParMETIS dramatically reduces the time spent in interprocess communication by computing mesh decompositions such that the number of interface nodes/elements is minimized .A parallel program is typically developed by dividing the program into multiple fragments that can execute simultaneously, each on its own processor. In the finite element analysis, this can be accomplished by applying a domain decomposition method. Domain decomposition method is the method usually used for solving large scale system equations and it is also suitable for parallel programming because of data locality . There aIterative solver must be used in the iterative domain decomposition method. In this study, for the iterative solver, GMRES  was chosen for both global and local matrix. GMRES is mainly chosen because of its ability to solve non-symmetric linear system as in the case of our problem. To improve the convergence of this problem, the additive Schwarz method preconditioner was applied. The Castlewood Canyon bridge is located on Highway 83 in the Black Forest of central Colorado. The original two-lane reinforced concrete arch bridge was built in 1946. The arches are 1.93 m wide by 1.78 m deep at the base with the depth tapering down to 1.0 m at the highest point. This bridge was severely dilapidated and was in need of repairing, enlarging, and strengthening. Parts of the concrete had spalled off of the deck, columns, and arches, and the steel rebar under concrete were severely rusted. In 2003, the original arch was repaired, the spandrel columns and decks were replaced and widened from about 0.9 m to 1.0 m including railings, and the overall length of the bridge was increased from 114 m to 123 m as shown in In order to analyze the penetration of chloride and humidity in a concrete bridge, a large number of meshes are needed to capture the diffusion phenomenon within thin layer from concrete top surface to steel rebar. For depicting in detail concrete cover depth on rebar, the information of nodes and elements are created by mesh generator. Triangle as mesh generator is specialized for creating two-dimensional finite element meshes.For castle wood canyon bridge, approximately 1.5 million nodes and three million elements were generated for input files as shown in Environmental humidity model plays an important role of diffusion of chloride in concrete. The humidity model used in this study was proposed by Bazant and Xi (1993) . Even thThe environmental humidity model consists of three different components as shown in Equation (43) and demonstrated in variance .(43)H=H, 0.0046 .For the chloride concentration on the top surface of concrete, various boundary conditions were used to actualize the realistic boundary conditions as illustrated in Speed-up is measured for the performance of the parallel implementation of finite element program. The definition of speed-up is a process for increasing in performance between two systems processing the same problem. With regard to speed-up in this study, 8–2048 processors were used in this study and the meshes with the number of about 1.5 million nodes were analyzed. When using up to eight processors, the program was not operated due to memory capacity when input data can be assigned on each memory which means the problem was too huge to solve with a couple of processors.As the number of processors used in the analysis increased, speed-up was improved up to 512 processors because speed-up was better than ideal condition. After more than 512 processors were used, speed-up gradually increased because the communication time between the processors increased. As shown in (1) Constant boundary conditionThe physical and material models of the castle wood canyon bridge used in this paper were mentioned above. The validation of these models was secured by Ababneh et al. and Suwito et al. ,15. AbabIt was assumed that the concrete bridge contained initially no chloride ions and has 60% relative humidity (RH). The top surface of concrete bridge was exposed to 3% NaCl and 100% RH. To analyze the diffusion of coupled chloride and humidity, 8 to 2048 processors and approximately 1.5 million nodes were used with parallel finite element method.Obviously, this example is not to simulate the concrete behavior under service condition. The triangle element meshes were employed and the whole domain was partitioned into 16 sub-domains to the same as the number of processors shown in (2) Periodic boundary conditionIn order to simulate the real diffusion phenomenon in concrete, the periodic boundary condition should be required. In (1)The parallel finite element program was developed based on the robust mathematical material model. The program can be used to simulate the coupled moisture and chloride penetration into non-saturated concrete structures. Chloride ion is one of sources causing the steel corrosion in reinforced concrete structures. The material parameters related to chloride and moisture diffusion in concrete are taken into account. These parameters include chloride and moisture diffusion coefficients, moisture capacity, chloride binding capacity, and the coupling parameters reflecting the coupling effects between moisture and chloride transfer in concrete.(2)For the implementation of parallel FE analysis, Triangle for mesh generation, ParMetis, PETSc, and MPI are employed. This program also used the overlapping domain decomposition method with additive Schwarz preconditioner. As the result of simulation, the computation time decreased until the number of processors became optimized when the number of processors increased. Then, the computational time increased because the communication between the processors increased.(3)The present model can be used to simulate the unsaturated concrete structures subjected to other aggressive chemicals from de-icing salt. The framework of present model can be extended to simulate the multi-species de-icing salts ingress into non-saturated concrete structures in future work.


Porphyromonas gingivalis are associated with persistent periodontal attachment loss and can be difficult to eliminate by scaling and root planing. Azithromycin (AZM) inhibits P. gingivalis and is actively accumulated by most human cells. We used an in vitro infection model to compare the effectiveness of AZM in killing intracellular P. gingivalis to the combined regimen of amoxicillin (AMX) and metronidazole (MET). Transport of [3H]‐AZM by human gingival fibroblasts was characterized. Monolayers of Smulow–Glickman gingival epithelial cells or gingival fibroblasts were infected with P. gingivalis (strain 33277 or W83). After extracellular bacteria were eliminated with teicoplanin, infected cells were treated with therapeutic concentrations of AZM, AMX, or AMX + MET. Viable intracellular bacteria were released by cell lysis and plated on blood agar for enumeration. Antimicrobial activity against planktonic P. gingivalis was also evaluated. While survival of intraepithelial P. gingivalis 33277 was not significantly different after treatment with the three regimens, survival in infected fibroblasts was significantly lower after AZM treatment (65.9 ± 5.5%) compared with AMX (92.2 ± 3.5%) or AMX + MET . Carnitine, a competitive inhibitor of AZM transport, reduced killing by AZM by ~55% (P < 0.05). Survival of intrafibroblast P. gingivalis W83 was also significantly lower after AZM treatment compared with the other regimens (P < 0.05). At therapeutic concentrations, AZM was significantly more active against intracellular P. gingivalis than against planktonic P. gingivalis (P < 0.0083). Gingival epithelial cells and fibroblasts possess a transport system that accumulates AZM and enhances elimination of intracellular P. gingivalis. Compared with the combination of AMX and MET, AZM was equally effective against intraepithelial P. gingivalis 33277 and significantly more effective against both strains of P. gingivalis from infected gingival fibroblasts. The results suggest that AZM could be a reasonable alternative to the regimen of AMX and MET for periodontal patients who should not take these agents due to known side effects or compliance issues.Invasive infections by  Aggregatibacter actinomycetemcomitans and Porphyromonas gingivalis, have the ability to invade pocket epithelium and underlining connective tissue, evading the host immune system and lingering in the periodontal tissue. This could partly explain the unresponsiveness and recurrence of periodontitis  is a macrolide antibiotic derived from erythromycin. Its properties include broad‐spectrum activity against most species of periodontal pathogens, a plasma half‐life of over 65 h, ability to be actively taken up by mammalian cells, and more sustained concentrations in gingival tissues and gingival crevicular fluid than in serum  and metronidazole (MET) is the most commonly used antibiotic regimen in periodontal therapy and is effective in the treatment of both chronic and aggressive periodontitis  gingival epithelial cells derived from human attached gingiva  and a well‐characterized laboratory strain (W83) were grown in Trypticase soy broth  supplemented with 1 mg/mL yeast extract , 5 µg/mL hemin  and 1 µg/mL menadione (Sigma‐Aldrich) at 37°C in an anaerobic chamber .All targeted antibiotics, including AZM, AMX, MET, and moxifloxacin (MFX), were from Sigma‐Aldrich. Teicoplanin was acquired from Selleck Chemicals LLC . The MIC of each antibiotic against planktonic 6 cells/mL. AZM transport was assayed by measuring changes in cell‐associated radioactivity over time  at a concentration of 10 µg/mL for time course assays and at 10–50 µg/mL for kinetic assays to determine the Michaelis constant (Km) and maximal velocity of transport (Vmax). After the indicated interval (1–30 min for uptake time course assays and 3 min for kinetic assays), 0.5‐mL aliquots of cell suspension were rapidly withdrawn, layered over 0.3 mL of a mixture of canola oil‐dibutyl phthalate (3:10), and centrifuged for 30 sec at 15,000 × g in a microcentrifuge  for 20 min at 37°C. Volume determinations were corrected for extracellular water trapped in the pellet, which was determined by incubation under the same conditions with [14C]‐inulin  , harvested by brief treatment with 0.25% trypsin ethylenediaminetetraacetic acid (Invitrogen) and suspended in HBSS at a density of 103H]‐AZM. To trigger efflux of intracellular AZM stores, we abruptly diluted AZM in the extracellular medium 11:1 with 37°C HBSS. The decrease in intracellular AZM concentration was monitored for 60 min.To observe the efflux of AZM, gingival fibroblasts were loaded to a steady‐state intracellular AZM concentration by incubation for 20 min at 37°C in HBSS containing 10 g/mL [P. gingivalis from overnight culture were harvested, resuspended in cell culture medium specific to the corresponding host cell lines, and laid over monolayers to infect at a 100 bacteria to one host cell ratio for 90 min. Afterward, extracellular bacteria were removed by HBSS washes and treatment with 100 µg/mL teicoplanin for 1 h. The monolayers were again washed four times with HBSS, and an aliquot of the final wash was plated on reduced blood agar  to ensure that HBSS washes and treatment with teicoplanin removed viable extracellular bacteria  was added to the epithelial model to evaluate its influence on killing of P. gingivalis  of 394 ± 39.0 ng/min/106 cells . AZM showed little effect, while the positive control, MFX, killed more than 99% of planktonic bacteria. The differences between AZM and the other regimens were statistically significant  . It appeared that AZM was significantly more effective against intrafibroblast P. gingivalis 33277 than against planktonic bacteria , but this phenomenon was not observed from either AMX or AMX + MET.All tested antibiotic regimens showed different levels of killing against intrafibroblast P. gingivalis 33277, all tested antibiotic regimens showed significant suppression of intracellular bacteria . Killing of intraepithelial P. gingivalis was ~43%, ~38%, and ~33% of the control colony‐forming units after treatment with AZM, AMX + MET, and AMX, respectively . Only AZM exhibited significantly greater killing of intraepithelial P. gingivalis relative to planktonic P. gingivalis .As for intraepithelial P. gingivalis 33277, whereas AZM alone killed ~30% of the bacteria. In the presence of carnitine, more than half of the killing effect produced by AZM was reversed . The difference in effects produced by carnitine alone and in combination with AZM was not statistically significant (P > 0.05).A separate series of transport assays in which 2 mM L‐carnitine and 4 µg/mL AZM were co‐incubated with SG epithelial cells for 4 h indicated carnitine reduced the steady‐state intracellular AZM concentration from 92.0 µg/mL to ~68.5 µg/mL (data not shown). Carnitine alone reduced approximately 10% of intraepithelial P. gingivalis W83 generated from AMX and AMX + MET were comparable . In contrast to its activity against the 33277 strain, AZM killed ~53% of planktonic P. gingivalis W83, which is significantly more active than the other two regimens . The positive control (MFX) killed approximately 90% of bacteria . In addition, AZM produced significantly stronger antimicrobial activity against intrafibroblast W83 than against their planktonic counterparts .A similar trend was observed with killing of intrafibroblast Our data indicate that human gingival fibroblasts take up and accumulate relatively high intracellular concentrations of AZM through an active transport system. When gingival fibroblasts were cultured in medium containing 5 µg/mL AZM, the steady‐state intracellular AZM concentration was approximately 55.8 µg/mL. Intracellular stores of AZM appear to move out of fibroblasts when the extracellular concentration drops, which could help maintain high concentrations in tissue fluid. SG gingival epithelial cells used in this study also have an active transport system that exhibits similar characteristics and concentrates AZM more than 20 times inside , their activity against planktonic bacteria was rather modest. This could be partially explained by the experimental conditions. When exposed to normal aerobic tissue culture atmosphere, P. gingivalis, an obligate anaerobe, typically synthesizes proteins and enzymes such as heat shock proteins and superoxide dismutase for survival (instead of proteins for multiplication)  almost completely eliminated planktonic P. gingivalis within 4 h. MFX is a fluoroquinolone antibiotic and exerts its bactericidal effect mainly through inhibition of DNA gyrase, which is required for DNA replication, transcription, and repair  divided by the MIC , it is comparable with the activity of MET, clindamycin, and doxycycline reported in a previous in vitro study (Eick et al., The role cell invasion by bacteria plays in the pathogenesis of periodontitis is controversial. While bacterial invasion and spreading from cell to cell has been proposed as a possible mechanism in periodontal and cardiovascular diseases (Deshpande et al., P. gingivalis and makes it more effective than the combination of AMX + MET in eliminating the bacteria from infected gingival fibroblasts. In gingival epithelial cells, AZM was equally effective in eliminating P. gingivalis 33277. It is reasonable to prescribe AZM instead of AMX + MET in periodontal applications for patients who are allergic to β‐lactam drugs or are hypersensitive to the side effects of AMX or MET. In theory, it should be easier to obtain a high degree of compliance with AZM compared with the combined regimen. Within the limitation of this study, the data suggest that AZM is a reasonable alternative to AMX + MET when prescribing a systemic antibiotic to treat P. gingivalis‐associated periodontitis.Our data suggest that human gingival fibroblasts possess an active transport system that accumulates AZM at intracellular concentrations at least 10‐fold higher than those in the extracellular environment. This accumulation enhances the antimicrobial activity of AZM against intracellular The authors have no conflicts of interest to declare.


Immunoglobulin G4-related disease (IgG4-RD) is a multiorgan condition manifesting itself in different forms. This study aimed to investigate protein expression profiles and to find the possible biomarker for IgG4-RD by liquid chromatography mass spectrometry (LC-MS) using tissue sections in IgG4-RD patients. Protein expression profiles in five IgG4-related pancreatitis and three normal pancreatic samples were compared using LC-MS and were validated by quantitative real-time PCR (qRT-PCR), immunoblotting, and immunohistochemistry. ELISA was employed in the serum of 20 patients with systemic IgG4-RD before and during steroid treatment.P < 0.01). These results were confirmed by immunoblotting and qRT-PCR. The average number of galectin-3 + cells in various organs of IgG4-RD patients, including salivary glands, lungs, and lymph nodes, was higher than in controls. Galectin-3 was detectable in macrophages, dendritic cells, and stromal myofibroblast-like cells, but not in lymphocytes by immunofluorescence staining. Serum galectin-3 levels were higher in patients with IgG4-RD compared with healthy donors and remained high during steroid therapy. LC-MS indicated that the levels of 17 proteins were significantly higher and 12 others were significantly lower in IgG4-related pancreatitis patients compared to controls. Among these proteins, galectin-3 levels were 13-fold higher in IgG4-related pancreatitis ( Galectin-3 was overexpressed in IgG4-RD and the levels were indirectly related to clinical activity. Immunoglobulin G4-related disease (IgG4-RD) is an autoimmune multiorgan condition, characterized by a dense lymphoplasmacytic infiltration with a high number of IgG4-positive plasma cells and high IgG4 levels in serum , 2. The Chronic antigen exposure stimulates IgG4 production, leading to a shift in the IgG4 : IgG1 ratio. The mechanism driving this switch still remains unclear. However, Th2 interleukins such as IL-4, IL-5, and IL-13 can mediate the transition from IgG1 to IgG4 –9. HowevRecent advancements in technical procedures and bioinformatic methods improved the sensitivity of mass spectrometry, making proteomic analysis on formalin-fixed paraffin embedded (FFPE) tissues possible . In thisμm thick tissue sections (10 × 10 mm) were dissected using a needle and solubilized in 20 uL of Liquid Tissue buffer and protein digestion was performed with trypsin  for 18 h at 37°C. Samples were dried and solubilized in 0.1% formic acid  and 1 μg aliquots for each sample were separated by nanoflow reversed-phase LC  equipped with cHiPLC Nanoflex (Eksigent). Eluted peptides were analyzed by a quadrupole-time-of-flight hybrid mass spectrometer .Proteins for LC-MS analysis were extracted from FFPE tissue samples  using the Liquid Tissue MS Protein Prep kit  . All casβ (AB SCIEX). False discovery rates (FDRs) were determined after peptide/protein identification using Proteomic System Performance Evaluation Pipeline provided as a part of ProteinPilot (AB SCIEX). Label-free quantification of peptides was performed using Progenesis QI for Proteomics . Proteins identified by at least two distinct peptides were used for further analysis.Mass spectra were searched against the Uniprot/Swissprot human proteomic database (2014-6 release) from the European Bioinformatics Institute using ProteinPilot version 4.5Immunoblot analysis was performed for protein extracts from FFPE tissues using the Qproteome FFPE Tissue kit . The antibodies used were anti-galectin-3  and anti-beta-actin . Protein bands were visualized with a chemiluminescence substrate , and blots were imaged using Ez-Capture MG . Bands were analyzed using the CS Analyzer .μL volume per well using Fast SYBR Green Master Mix . These reactions were performed with an Applied Biosystems 7500 Fast real-time PCR machine. Expression was normalized to GAPDH, using the 2−ΔΔCt method. The primer sequences were LGALS3  and GAPDH .Total RNA was extracted from FFPE samples using the NucleoSpin total RNA FFPE kit . cDNA synthesis was performed using the ReverTra Ace qPCR RT kit . Amplifications were carried out in triplicate on a 96-well plate in a 10 n = 5), bile duct (n = 3), retroperitoneum (n = 1), aorta (n = 1), kidney (n = 2), salivary gland (n = 6), lung (n = 4), ureter (n = 1), and lymph node (n = 6) from 29 patients between January 2007 and August 2015. Paraffin embedded sections from IgG4-RD patients were immunostained with the following antibodies: alpha-smooth muscle actin , CD3 , CD11c , CD123 , CD20 , CD68 , galectin-3 (1 : 100), IgG , and IgG4 . The REAL™ EnVision™/HRP detection system  was used to detect immunohistochemical signals. Double immunofluorescence staining was performed using the TSA Plus Fluorescence kit .Analyzed specimens comprised of FFPE tissues from IgG4-RD patients retrieved from the archive of the department of Diagnostic Pathology, Kyoto University Hospital: pancreas  treatment (pretreatment sera were available from 11 patients) and from five healthy control individuals . All experiments were performed in duplicate. Results were compared with samples of patients treated with a tapering dose of PSL.Sample collection and use of clinical records were authorized under the written consent of patients, and the study was conducted according to the principles expressed in the Declaration of Helsinki. The Ethics Committee of Kyoto University approved this study (R0305).t-test or Mann–Whitney U test and two-way analysis of variance (ANOVA) followed by Bonferroni's multiple comparisons test were used. Differences with a P value smaller than 0.05 were considered statistically significant.Data were analyzed with GraphPad Prism 6  or R version 3.2.0. To compare continuous variables, unpaired Student's P value < 0.05) and showing a twofold difference in their expression between IgG4-related pancreatitis and normal pancreatic samples were selected for further analysis; the levels of 17 proteins were higher and those of 12 proteins were lower in IgG4-related pancreatitis tissues than in healthy pancreas .LC-MS revealed that 956 proteins were differentially expressed between IgG4-related pancreatitis and normal pancreatic samples Figures . Among tpancreas . We selen = 5) showed a 3-fold up-regulation of LGALS-3 expression compared with healthy pancreas   from each specimen. The average number of galectin-3-positive stromal cells was higher in organ samples from IgG4-RD patients compared with healthy pancreas or lymph node samples. The differences between healthy pancreas and IgG4-related pancreatitis samples and between healthy lymph node and IgG4 lymphadenopathy were statistically significant (arisons) .Immunofluorescence staining showed that galectin-3 colocalized with CD68, CD11c, and CD123, suggesting that galectin-3 was expressed in macrophage, myeloid, and plasmacytoid dendritic cells Figures . NotablyP value < 0.01 for both comparisons; Galectin-3 levels in serum of IgG4-RD patients were 7.8 ± 0.58 ng/mL and 10.7 ± 0.58 ng/mL before and during PSL treatment, respectively, that is, 2- and 2.5-fold higher than 3.8 ± 0.46 ng/mL found in healthy donors  when compared to galectin-3 levels before the treatment. Galectin-3 levels in serum were on average 1.37 ± 0.15-fold higher after the last follow-up treatment, on average 24 months after the start of the therapy, compared to relative to the levels before the treatment . LGALS3, is a member of the galectin family and expressed in numerous cells, including epithelium cells of gastrointestinal and respiratory tracts and renal tubules, fibroblasts, chondrocytes, osteocytes, and endothelial cells. This protein has pro- and antiapoptotic activity [We chose the protein galectin-3, identified by LC-MS with high confidence and differential expression in FFPE samples of IgG4-related pancreatitis tissues. Galectin-3, encoded byactivity –18 and ractivity –21. Galeactivity , 23. Higactivity , 25.Galectin-3 is highly expressed in tissues affected by several autoimmune diseases, such as systemic lupus erythematosus, polymyositis, dermatomyositis, rheumatoid arthritis, Behcet's disease, systemic sclerosis, and Crohn's disease. Moreover, galectin-3 shows higher expression in active than in inactive diseases –28. Galeα production [α1β1 integrins and the α subunit of αMβ1 integrin , and these integrins are used as receptors [ Trypanosoma cruzi infection model [This study demonstrated an increase in galectin-3 expression in IgG4-RD patients. Galectin-3 was expressed in cells involved in immune response activity, including macrophages, dendritic cells, myofibroblasts, and epithelial cells. Galectin-3 signal was found in stromal deposition. Dendritic cells are specialized in antigen presentation cells and connect the innate and adaptive immune system . They haoduction , 32. Galoduction , 34. Galeceptors . Galectieceptors . In addieceptors . Recent eceptors , 11 Ritueceptors . Extraceeceptors . Inhibiton model . Additioon model . Likewison model . Therefoon model , 36, 37,In our study, galectin-3 serum levels in patients with IgG4-RD before and during PSL treatment were significantly higher compared with those in healthy donors. IgG4 levels in serum decreased dramatically after PSL treatment, while galectin-3 levels in serum remained high throughout the treatment. Galectin-3 serum levels increased with PSL treatment and gradually decreased with the tapering of PSL. This implies that galectin-3 cannot serve as a realistic biomarker for IgG4-RD in routine clinical practice. Glucocorticoid therapy could be a bias, because galectin-3 expression increases significantly in macrophages and lung Clara cells after glucocorticoid treatment . SimilarIn conclusion, galectin-3 was overexpressed in IgG4-RD and the levels were indirectly related to clinical activity and treatment. Further studies will need to explore the exact mechanism behind the function of galectin-3 in IgG4-RD and other autoimmune diseases.


CBL locus. Ectopic expression of wild-type c-CBL in SCC-35 cells downregulated MET expression and decreased cell viability. These results suggest MET overexpression is related to altered c-CBL expression, which may influence tumorigenesis.MET is frequently overexpressed in head and neck squamous cell carcinoma (HNSCC) and degraded by c-CBL E3-ubiquitin ligase. We investigated genetic variations of c-CBL in HNSCC and the relationship between c-CBL and MET expression. High MET, low c-CBL expression was detected in 10 cell lines and 73 tumor tissues. Two novel mutations , and the single nucleotide polymorphism (SNP) P782L were identified from archival tumor tissues. 27.3% of loss of heterozygosity was found at  It is projected that 52,610 new cases of head and neck cancer (HNC) will be diagnosed in the United States in 2014, accounting for just over 3% of estimated US cancer diagnoses ,8, thereOne molecular target of interest is the receptor tyrosine kinase (RTK) MET, which is involved in cell motility, cell scattering, and proliferation, thus contributing to angiogenesis, invasion, and metastasis in cancer cells. As we showed in 2009, MET is highly expressed, amplified, and mutated in HNSCC; moreover, we demonstrated that MET inhibition abrogated cell proliferation and migration/motility, suggesting that MET would be an effective target in HNSCC . Howeverc-CBL, CBL-b, CBL-3 [The mammalian CBL gene is located on human chromosome 11q23.3 ,13. CBL b, CBL-3 . The TKBin vivo [In the case of MET, the binding of its cognate ligand hepatocyte growth factor (HGF) activates the receptor, which is characterized by receptor dimerization and phosphorylation of tyrosine residues within the juxtamembrane (JM) domain . c-CBL in vivo . In HNSCCBL locus in tumor/normal pairwise tissues revealed significant LOH . Taken along with our previous studies of MET in HNSCC, our investigation suggests that CBL mutations can occur exclusive of MET mutations [In the investigation described below, we observed low expression of c-CBL and moderate to high expression of MET in HNSCC tumor tissues. Similar findings were obtained by immunoblot analysis of HNSCC cell lines. Moreover, we identified two novel somatic mutations  in the TKB domain of c-CBL. Loss of heterozygosity (LOH) analysis of the t LOH 27.%, n=6/22In a previous study we determined MET to be highly overexpressed and often mutated in HNSCC . Since cTo further evaluate the relationship between c-CBL and MET in HNSCC, we analyzed the expression of MET and c-CBL in a panel of HNSCC cell lines Figure . MET wasCBL in lung cancer [CBL in HNSCC, genomic DNA was isolated from FFPE patient tumor specimens (n=20) and HNSCC cell lines (n=16). No CBL mutations were detected in the cell lines. However, we identified 3 missense mutations among three different patients  samples, based on microsatellite markers within the CBL locus and 400bp upstream of the CBL locus on 11q, as well as two control markers on 11p  or a vector containing c-CBL wild-type (c-CBL WT). At 48h post-transfection, the expression of c-CBL and MET was determined by immunoblotting. Expression of c-CBL was confirmed in the cells transiently transfected with c-CBL WT, but not in those transfected with EV Figure . By usinCBL was mutated and LOH was detected at the CBL locus. Additionally, both our current data, as well as our previous publication clearly demonstrate that MET is activated in HNSCC, and pMET expression was concomitant with MET expression [c-CBL protein expression is low in normal and HNSCC patient tumor specimens, while MET and pMET expression are increased. This pattern of c-CBL and MET protein expression was largely recapitulated in HNSCC cell lines. In HNSCC tumor specimens, pression . Taken tCBL locus. It is important to note that in certain hematologic malignancies CBL shows uniparental disomy with activating CBL mutations [c-CBL has been shown to regulate the expression of a number of proteins such as RTKs and other signal transduction molecules . Herein,utations . This wautations . Therefoutations ,24.MET mutations and c-CBL expression or vice versa. As has been previously reported, the JM domain of MET binds to c-CBL, which leads to its degradation [MET is largely overexpressed in HNSCC and we have shown that it can be effectively targeted using small molecule chemical inhibitors . To dateradation ,26. Our CBL deletions were reported [CBL were responsible for the enhanced expression of MET in HNSCC, since we determined high expression of Y1003 in our primary tumor specimens. Although further studies are necessary to characterize the function of the identified TKB mutants in HNSCC, we believe that our data supports the notion that the overexpression of MET is likely due to dysregulated receptor processing as a result of impaired c-CBL activity in the L254S and L281F mutants. Our in vitro studies using HNSCC cell lines revealed a concomitant decrease of MET and cell viability upon ectopic CBL expression. The mechanisms underlying the c-CBL-mediated downregulation of MET and its impact on cell viability in HNSCC need to be investigated further, as well as the role of these newly identified mutations.The two novel mutations that we identified in HNSCC were localized to the TKB domain of c-CBL. The TKB domain is required for binding and ubiquitination of MET . The TKBreported . Based oCBL is mutated and has LOH in HNSCC. In tumor tissues, low c-CBL expression was concomitant to high MET and pMET expression. It would now be useful to determine the role of c-CBL as a prognosticator and/or predictive biomarker in HNSCC.In summary, c-CBL expression is low, and at the gene level nd Floor, Chicago, IL 60637.This human subjects research was approved by the Institutional Review Board (IRB) at The University of Chicago and covers all research conducted in the laboratory. Archived tissues were obtained under consent-waived protocols for de-identified patients (10-653N) or deceased patients (10-654N). The IRB can be contacted at The University of Chicago, McGiffert Hall, 5751 S. Woodlawn Ave., 2Upon approval from the IRB, tissue blocks for the study were selected from patients with HNSCC who were treated at the University of Chicago Medical Center (diagnosed between 1992 and 2005). The tissue microarrays (TMA) used in this study were composed of 73 tumor cores, 12 dysplasia cores, and 18 adjacent normal cores derived from 41 patients. TMAs were built using the ATA-27 Arrayer from Beecher Instruments  as previously described [The cell lines SCC-35 ,20, SCC-Cells were harvested and washed in 1X phosphate buffered saline (PBS), then lysed in ice-cold M-PER lysis buffer plus HALT protease and HALT phosphatase inhibitors . Total cell lysates (50 μg/well) were separated by SDS-PAGE electrophoresis and transferred onto immobilon-P membranes . Membranes were blocked with 5% BSA in Tris-buffered saline containing Tween-20 (TBST)  for 1h at room temperature and incubated with the appropriate primary antibody at 4°C overnight. Membranes were then washed three times with TBST and probed with the appropriate horseradish peroxidase (HRP)-conjugated secondary antibody. The membranes were again washed three times in TBST and bands were visualized using Western blot chemiluminescence reagent  on a Chemidoc Gel documentation system (BioRad). The following antibodies were used: c-CBL ; MET ; and β-actin .CBL alterations performed by sequencing the reverse strand. Mutational analysis was performed using Mutation Surveyor v2.61 .Genomic DNA was isolated from formalin-fixed, paraffin embedded (FFPE) patient tissues using the QIAamp DNA Minikit  according to the manufacturer's instructions. Exons 2 to 16 of c-CBL were amplified and sequenced as previously reported . The PCRCBL LOH analysis was conducted as previously described [CBL gene - and two control markers on 11p) were selected for analysis  was used to analyze the chromatograms. The ratio of the allelic areas was calculated for each tumor and paired normal DNA sample. When the qLOH  was ≤0.5 or ≥2.0 for CBL and at least one other 11q marker in at least two separate experiments, the sample was considered to have an allelic imbalance and was interpreted as LOH.escribed . BrieflyHNSCC cell lines (SCC-35 and SCC-151) were transiently transfected using Fugene HD reagent  according to the manufacturer's instructions. Cells were transfected with 4μg of plasmid DNA containing no insert  or c-CBL wild-type (WT). After 48h cell lysates were collected for protein expression by immunoblotting.5 cells/well in a 96-well plate) for 24h in serum-free media and complete media.The cells were cultured for 24h following the transfection in complete media. Cell viability was determined using a standard MTT assay  by culturing the cells (1×10


Met mRNA was expressed rhythmically during the reproductive cycle, with peak mRNA accumulation just prior period of oocytes programming of sex. Further, we revealed evidence that Met proteins self-associate in the absence of methyl farnesoate, and that the presence of methyl farnesoate stimulates dissociation of Met multimers with subsequent association with SRC. Results demonstrated that the Met subunit is highly dynamic in controlling the action of methyl farnesoate through temporal variation in its expression and availability for receptor assembly.The methyl farnesoate receptor (MfR) orchestrates aspects of reproduction and development such as male sex determination in branchiopod crustaceans. Phenotypic endpoints regulated by the receptor have been well-documented, but molecular interactions involved in receptor activation remain elusive. We hypothesized that the MfR subunits, methoprene-tolerant transcription factor (Met) and steroid receptor coactivator (SRC), would be expressed coincident with the timing of sex programming of developing oocytes by methyl farnesoate in daphnids. We also hypothesized that methyl farnesoate activates MfR assembly.  Methyl farnesoate is an acyclic sesquiterpenoid hormone and the unepoxidated form of juvenile hormone III found in insects. Methyl farnesoate is synthesized by juvenile hormone acid o-methyltransferase236While environmental cues, such as changes in photoperiod102612Aedes aegyptiDaphnia magna and Daphina pulex corroborated our earlier results and confirmed the protein complex as a methyl farnesoate responsive receptor (MfR)15in vivo. These experiments supported Met and SRC as being the receptor protein complex mediating male sex determination.Previously, we demonstrated that methyl farnesoate activated the daphnid methoprene-tolerant transcription factor (Met) in the presence of the steroid receptor coactivator (SRC) ortholog derived from Although the environmental signals that stimulate male sex determination have been elucidated and the MfR receptor subunits identified, the intra-molecular interactions of daphnid MfR activation remain elusive. We hypothesized that daphnid Met actively contributes to the assembly of the MfR. Evidence for this dynamic role of Met was sought by evaluating the temporal expression of the MfR subunit mRNAs along with subunit protein-protein interactions within the cell in response to methyl farnesoate.A. aegypti. Here, we cloned SRC from D. pulex for use in our assessment. The derived daphnid SRC nucleotide sequence  domain, has 100% sequence similarity to that previously deduced in D. pulex and in D. magna and 37.5% to A. aegypti.We initially demonstrated that daphnid Met associated with SRC to form the functional MfR using SRC derived from sequence  was 97.8d genome . The dapMet mRNA levels revealed that levels of this MfR subunit transcript oscillates over the course of each molt/reproductive cycle, with base level expression at the beginning and end of each cycle, and peak expression at 36 hours post molt  would be expressed in a temporal fashion such that mRNAs would be present and available for protein production just prior to or during the period of susceptibility to male sex determination. Analysis of ost molt . SRC mRNost molt . This mRSome bHLH-Pas proteins have been shown to exist in cells as homo-multimersConcentration-response analysis revealed that the BRET ratio generated from cells with both Met fusion constructs (photon donor and fluorophore) decreased in response to increasing concentrations of methyl farnesoate, with a maximum decrease at 3 μM methyl farnesoate . The decBRET assays performed with cells co-expressing various combinations of Rluc2-SRC, mAmetrine-Met, and free Rluc2 or mAmetrine all produced measurable BRET ratios. However, methyl farnesoate significantly increased the BRET ratio only in assays containing Rluc2-SRC along with mAme-Met . These rConcentration-response analysis with the mAme-Met and Rluc2-SRC constructs confirmed that methyl farnesoate stimulates Met and SRC association, with significant association beginning at 10 μM . TherefoAedes SRC. The reporter gene activation increased with increasing concentrations of methyl farnesoate, with significant transcriptional activation at concentrations ≥10 μM , compared to that measured in previous assays using the shorter A. aegypti FISC (9-fold)Members of the SRC family typically house 4–6 “LxxLL” binding motifs (where “L” is leucine and x represents any amino acid), that are responsible for binding of the SRC to ligand-bound partner receptorsSRC mRNA did not significantly change over the course of the daphnid molt cycle, conceivably due to its probable involvement in other reproductiveMet mRNA oscillated over the course of each molt cycle, peaking in expression at 36 hours post molt, just prior to the window of oocyte susceptibility to methyl farnesoateMet mRNA results in the accumulation of Met protein during the developmental window of susceptibility to methyl farnesaote resulting in the programming of oocytes to develop as malesThe relative accumulation of Drosophila melanogaster Met proteins form spontaneous homomultimers2628Some of the protein-protein interactions between subunits of the orthologous juvenile hormone receptor, in insects, have been characterized. For example, BRET analyses revealed that daphnid Met forms homo-multimers that partially dissociate in the presence of methyl farnesaote. Although the level of dissociation never exceeded 50% even with the addition of increasing concentration of the hormone. This partial dissociation of Met multimers may reflect the dissolution of inactive Met complexes  to hormone-activated complexes . Many bHLH-PAS proteins operate as heterodimeric protein complexesBRET assays also revealed that methyl farnesoate stimulated the association of Met with SRC. The ligand-stimulated dimerization of daphnid Met and SRC is consistent with the reported dimerization of mosquito Met and FISC (SRC ortholog) in the presence of juvenile hormone161522We hypothesized that daphnid Met actively contributes to the assembly of the MfR. Results support this hypothesis. Firstly, Met mRNA accumulates in cells, presumably to provide ample protein, just prior to the period of sensitivity to the Met ligand, methyl farnesoate. The resulting Met protein accumulates in cells as multimers , that di333435The identification of the early responses of Met to methyl farnesoate enhances our basic understanding of hormone-receptor interactions in crustaceans, an economically and ecologically important genera. As methyl farnesoate is a critical regulator of crustacean reproduction and development, an understanding of the molecular actions of the hormone may lead to strategies for the enhancement or sustainable maintenance of crustacean populations.Methyl farnesoate , was dissolved in DMSO for delivery to the assay solutions. Final DMSO concentration in all assay solutions including controls was 0.001% v/v in BRET assays and 0.0005% v/v in luciferase reporter gene assays.SRC was cloned from tissues of Daphina pulex . Daphnids were cultured in incubators set at 20 °C and a 16:8 hour light/dark cycle. The daphnids were maintained at a density of 20 daphnids in 40 ml of media and were fed once daily with 1.4 × 108 cells of algae (Pseudokirchneriella subcapitata) and 0.4 mg (dry weight) TetrafinTM fish food suspension prepared as described previouslyA. aegypti FISC nucleotide sequence (ABE99837) was used to search for the daphnid SRC in the wFleaBase: the Daphnia Genome Database (http://wfleabase.org). Total RNA from adult female D. pulex was isolated using the SV Total RNA Isolation System (Promega). RNA integrity was verified by agarose gel electrophoresis (2.0%), and purity by the 260/280 nm ratio. Forward (5′-GGGATTCTAAAACAAAATTGGTACC-3′) and reverse (5′-GAGTCAAGGTCTTGGTTGGATTC-3′) oligonucleotide primers were designed to amplify the entire daphnid SRC open reading frame. Amplification of the daphnid SRC was performed with an iCycler Thermal Cycler  using 0.25 U Phusion Hot Start DNA Polymerase , 5 μl of 5x Phusion GC Buffer, 0.75 μl DMSO, 200 μM dNTP, 0.4 μM primers, 50 ng template cDNA in 25 μl total. PCR conditions consisted of an initial denaturation at 98 °C for 30 sec, followed by 40 cycles of 10 sec at 98 °C, 30 sec at 58 °C, and 4 min at 72 °C, followed 5 min at 72 °C for final extension. Amplified DNA fragments were cloned into pCR-XL-TOPO vector  following the manufacturer’s protocol. Plasmid DNA was sequenced by Life Technologies-ThermoFisher Scientific. The deduced D. pulex SRC amino acid sequence was aligned to A. aegypti FISC (UniProtKB: Q1KML9), D. magna SRC (UniProtKB: M1UYR5), and the recently cloned D. pulex (UnipProtKB: M1VDR2)http://www.ebi.ac.uk/Tools/msa/clustalo/). Putative bHLH and PAS domains were determined by their 100% sequence similarity to corresponding domains in both D. magna and the previously cloned D. pulex.The D. magna were reared as described by Hannas et al.® at 4 °C for 24 hrs, then stored at −80 °C. Whole animal tissue was homogenized using a Next Advance Bullet Blender®, and RNA isolation and reverse transcription was completed as previously describedThree hundred adult female Met and SRC) mRNA over the course of the daphnid molt cycle. Using forward (5′-CGTGACAAGCTCAATGCCTA-3′) and reverse (5′-GGCTTCATTCGAAGATCCAC-3′) primers, a 149 base pair sequence was amplified from the daphnid Met bHLH DNA-binding domainSRC bHLH DNA-binding domainOligonucleotide primers were designed to measure relative amounts of each MfR subunit  and amplification mixtures consisting of 12.5 µL 2x SYBER green (ThermoFischer Scientific), 300 nM primers, 500 ng DNA in a total volume of 25 µL. Reaction mixtures were heated to 95 °C for 5 min, followed by 40 cycles of 95 °C for 5 sec then 60 °C for 1 min. Mixtures were then heated to 90 °C for 15 sec, cooled to 60 °C for 1 min, reheated to 90 °C for 15 sec and re-cooled to 60 °C for 15 sec. A single melting peak was detected for each sample, indicating amplification occurred only for the target DNA sequence. The comparative CT method (2−ΔΔCT) was used to assess relative levels of Met and SRC mRNA . Met and SRC mRNA levels were normalized to the mRNA levels measured in organisms at 0 hr.Renilla luciferase 2 protein (Rluc2), which served as the photon donor during BRET . The daphnid SRC gene was amplified (with a stop codon) from the TOPO cloning vector using primers harboring AgeI (forward) and BstBI (reverse) restriction enzyme sites, and sub-cloned into the pMT-B vector (ThermoFischer Scientific). Rluc2  was amplified from its original storage plasmid (pcDNA) using primers harboring XhoI (forward) and BstBI (reverse). The reverse BstBI primer also contained a short 24 nucleotide “linker” sequence (AGCGGAAGTGGTAGCGGAAGTGGC) to lengthen the distance between the two proteins and decrease probability of incorrect folding. The Rluc2-linker sequence was sub-cloned at the 5′-terminus of the pMT-SRC plasmid, to create pMT-Rluc2-linker-SRC (referred to as Rluc2-SRC).The association of Met and SRC was assessed using bioluminescence resonance energy transfer (BRET) methodology. Daphnid SRC was fused to the MetmAmetrine (mAme) to serve as the fluorophore during BRET . The Met gene was amplified (with a stop codon) using primers harboring NotHFI  and BStBI (reverse) restriction enzyme sites, and sub-cloned into the pMT-B vector. mAme was amplified from pBad cloning vector using primers harboring KpnI (forward) and ApaI (reverse) restriction enzyme sites, and sub-cloned at the 5′-terminus of the pMT-Met, to create pMT-mAme-linker-Met (referred to as mAme-Met).The previously cloned Met gene was amplified (with stop codon) using primers harboring NotHFI  and BstBI (reverse) restriction enzyme sites, and sub-cloned into the pMT-B vector. Rluc2 was amplified from pcDNA storage vector with primers harboring KpnI (forward) and EcoRI (reverse) restriction enzyme sites and sub-cloned at the 5′-terminus of the pMT-Met, to create pMT-Rluc2-linker-Met (referred to as Rluc2-Met).Met was also fused to Rluc2, for use with mAme-Met, to assess spontaneous association and dissociation of Met multimers. The Drosophila Schneider (S2) cells (Invitrogen). Cells were grown in Schneider’s medium , containing 10% heat inactivated fetal bovine serum (Gibco), 50 mg/ml penicillin G , 50 mg/ml streptomycin sulfate (Fisher Scientific) and incubated at 23 °C under ambient air atmosphere. Cells were seeded at a density of 3 × 106 in 35 mm × 6 well plates and transfected 24 hours after plating.BRET assays were performed in Rluc2-SRC/mAme-Met). Transcription of the transfected genes was induced with CuSO4 (500 μM). Twenty-four hours later, cells were treated with methyl farnesoate for 1 hour in phosphate-buffered saline. Coelenterazine 400 A (5 μM) was then added and light emission was measured immediately at 410 ± 40 nm and 535 ± 15 nm using a FluoroStar fluorimeter (BMG Labtech). The ratio of light emitted at 535 nm/410 nm , 1: 6  and the reporter gene vector . Following transfection, transcription was induced with CuSO4 (500 μM for 24 hours). Cells then were treated with methyl farnesoate in Ex-cellTM 420 insect serum-free medium with L-glutamine . Cells were harvested after 24 hours of incubation with methyl farnesoate. Firefly and Renilla luciferase activity were assessed using the Dual-Glo® luciferase system (Promega) and manufacturer’s protocol. Firefly luciferase activity was normalized to Renilla luciferase activity, and each methyl farnesoate treatment group was normalized to DMSO control treated cells.Luciferase-based reporter gene transcription assays were conducted to assess the ability of the activated Met:SRC to initiate gene transcription. S2 cells were transfected with plasmids containing Met fused to the Gal4 DNA binding domainSignificant differences between data points were evaluated using Student’s t test (p < 0.05) or a one-way analysis of variance (ANOVA) followed by a Tukey’s multiple comparison procedure (p ≤ 0.05), as indicated. Statistical analyses were performed using Origin software .How to cite this article: Kakaley, E. K. M. et al. Agonist-mediated assembly of the crustacean methyl farnesoate receptor. Sci. Rep.7, 45071; doi: 10.1038/srep45071 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Learning a second language is crucially important in an increasingly global society, yet surprisingly little is known about why individuals differ so substantially in second language (SL) achievement. We used the twin design to assess the nature, nurture and mediators of individual differences in SL achievement. For 6263 twin pairs, we analyzed scores from age 16 UK-wide standardized tests, the General Certificate of Secondary Education (GCSE). We estimated genetic and environmental influences on the variance of SL for specific languages, the links between SL and English and the extent to which the links between SL and English are explained by intelligence. All SL measures showed substantial heritability, although heritability was nonsignificantly lower for German (36%) than the other languages (53–62%). Multivariate genetic analyses indicated that a third of genetic influence in SL is shared with intelligence, a third with English independent of intelligence and a further third is unique to SL. An Australian study with a relatively small sample of 251 adolescent twin pairs investigated teacher-rated achievement in SL learning and reported high heritability estimates (72%) with shared environmental factors explaining 20% of the variance.2 The only adequately powered study using non-self-report SL measures was conducted with a subsample of the present study: teacher-rated achievement for 14-year-old twins from the Twins Early Development Study (TEDS) yielded a substantial heritability estimate of 42%, shared environmental influences of 32% and non-shared environmental influences of 26%.3 Importantly, this study also showed shared etiology between age 12 achievement in English and SL at age 14, demonstrating substantial phenotypic (0.44) and genetic correlations (0.49) between the first and SL achievement scores. However, these results were based on teacher ratings, and, as twins often have the same teacher for a given foreign language, this measure could lead to rater bias and to an inflated estimate of shared environment. In summary, the few available studies suggest that there is substantial heritability in SL achievement; however, the results to date are mixed, as would be expected, given the diverse measures used in these studies.Learning a second language (SL) is increasingly important in modern global societies; however, surprisingly little is known about the origins of individual differences in foreign language acquisition. Given the importance of SL ability in the modern world, it is striking that only a handful of published studies have used genetically sensitive methods to investigate the etiology of individual differences in SL achievement. To our knowledge, the twin design has been applied in only three studies. A Dutch study using over 1600 12 to 26-year-old twin pairs, reported a high heritability estimate (71%).5 We have shown that achievement in the first language (English) is highly heritable in the early school years6 and at the end of compulsory education.7 In our previous report on SL, we showed that SL at the age of 14 was substantially correlated phenotypically (0.44) and genetically (0.49) with first language achievement scores.3It is possible that SL achievement reflects a broader language skill. Indeed, early first language skills have been shown to be closely related to achievement in SL even after a 10-year gap.second language learning aptitude, which is generally considered as a specific ability for SL learning.8 One way to look at this construct is in terms of ability to learn several languages; however, few students take more than one foreign language General Certificate of Secondary Education (GCSEs) and those that do are likely to be self-selected for SL-learning aptitude. SL-learning aptitude is typically measured using language-learning exercises, such as the Modern Language Aptitude Test9 that are very similar to the actual learning outcome they are used to predict, although the underlying psychological mechanisms remain poorly understood.10 Language-learning aptitude has been hypothesized to include memory, phonetic coding ability, language analytic ability and grammatical sensitivity,13 all of which appear to be related to intelligence. For example, both language analytic ability and memory are usually considered important components of intelligence.10 Furthermore, it is not clear whether aptitude is something different from intelligence.14 We did not have a measure that specifically addresses SL-learning aptitude. However, in addition to investigating whether SL achievement reflects broader language aptitude that includes first language, we were able to address, for the first time, the extent to which SL achievement is even more general in the sense of general intelligence. Intelligence has been shown to be a significant predictor of SL achievement, as well as academic achievement in general.18 In terms of genetics, intelligence, such as academic achievement, is highly heritable (~0.50).19 For these reasons, it is important to include intelligence in a multivariate genetic investigation of SL achievement.The strongest predictor of SL achievement is a construct called In summary, the current study goes beyond our previous report in three ways. First, our sample is three times larger. This increased power enabled us to investigate the main SLs studied at school separately, and also allowed for more powerful multivariate genetic analyses. Second, instead of teacher ratings, our analyses were based on standardized examinations (GCSEs) taken at the end of compulsory education in the United Kingdom. Third, we included intelligence in multivariate analyses. These measures allowed us to investigate the extent to which SL achievement reflects a broader language skill (first language achievement) and an even broader cognitive ability (intelligence). We report results for twins with GCSE scores at the age of 16 in English and SL and for whom intelligence scores were also available. We show, for the first time, the results of trivariate analyses investigating the association between intelligence, English and SL achievement.20 The sample is a representative sample of the UK population when compared with data from the National Statistics Office.6The sampling frame for the present study was the TEDS sample. TEDS is a large longitudinal sample involving over 16 000 twin pairs born in England and Wales during 1994–1996. Although there has been some attrition, more than 10 000 twin pairs have remained actively involved in the study. Since infancy, rich cognitive and behavioral data have been collected from the twins, including academic achievement.21 DNA testing was conducted when zygosity was not clear from physical similarity criteria. Both same-sex twin pairs and opposite-sex twin pairs were included in the study, with the overall sample including 2229 monozygotic (MZ) pairs, 2050 same-sex dizygotic (DZ) twin pairs and 1984 opposite-sex DZ twin pairs.The present study included 12 526 individuals (6263 twin pairs) from whom GCSE scores were obtained for English or SL; intelligence scores were available for 4481 individuals (2240 pairs). The sample size for each measure is shown in the results. Children who had major medical or psychiatric problems were excluded from the analyses. Because the present study investigated achievement in first and second languages, children who did not have English as their first language were also excluded from the analyses; however, no information about the extent of bilingualism was available. Zygosity was assessed using a parent questionnaire of physical similarity, which is 95% accurate when compared with DNA testing.https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/251184/SFR40_2013_FINALv2.pdf), yielding a correlation of 0.98, which indicates high accuracy of parent- and self-reported examination scores; data were not available to make this comparison specifically for SL.We used the GCSE grades for language achievement measures at the age of 16. GCSEs are standardized examinations taken in the United Kingdom at the end of compulsory education. The GCSE courses usually begin at the age of 14 and children choose from a variety of subjects, from traditional academic subjects such as English and mathematics, to history, geography, music and foreign languages. English, mathematics and science are compulsory subjects; all other courses are chosen from a variety of available subjects. Many schools also require students to take at least one modern foreign language course. These foreign language GCSE courses include reading, writing, listening and speaking the SL; however, only one mean exam grade is awarded for each SL GCSE examination. The examinations are graded between A* and G, which we coded from 11 (A*) to 4 (G). Students typically choose 10 or more GCSEs; receiving five or more grades between A* and C (inclusive) is a requirement for further education. All GCSE scores were collected by questionnaires sent by mail or by telephone from the parents or the twins themselves. Parent- and self-reported grades for English were compared with the grades obtained from the National Pupil database for 7367 twins . The most popular foreign languages taken at GCSE level were French (1323 twin pairs), Spanish (407 twin pairs) and German (450 twin pairs). We analyzed these three language grades separately in addition to the mean SL GCSE grade. GCSE English achievement was used as a measure of first language achievement and was computed as the mean of English language and English literature grades.22 and Raven's Progressive Matrices.23 Mill Hill vocabulary is a test of verbal ability, which consists of multiple-choice items. For each item a single word is presented at the top of the screen. Participants choose an answer that has the closest meaning to the target word. Raven's Progressive Matrices is a non-verbal ability task, consisting of a series of incomplete patterns (‘matrices'). In each case, the participant is asked to identify the missing part of the pattern. These measures were obtained from the twins at the age of 16 using web-based testing. Intelligence, general cognitive ability (‘g'), was indexed as the mean of the standardized verbal and non-verbal scores. Intelligence scores were available for 4481 individuals, as these data were only collected from a subsample of the TEDS twins .Intelligence, or general cognitive ability (‘g'), was assessed from Mill Hill Vocabulary score24 For all analyses, outliers beyond three s.d.'s from the mean were removed. Finally, all measures were transformed to the standard normal distribution using the rank-based van der Waerden transformation26 to correct for the negative skew. This negative skew, demonstrating a ceiling effect, was similar to that observed in the UK population as illustrated in UK national statistics .Before genetic analyses, all measures were corrected for age and sex differences using regression, creating standardized residual scores. This procedure is regularly used in TEDS for analyses of twin data to avoid inflation of estimates of shared environment as members of a twin pair are otherwise identical for age and MZ twins are also identical for sex.7 We conducted similar analyses specifically for SL achievement in the present study and confirmed our previous findings suggesting significant quantitative, but no qualitative sex differences. Boys have slightly higher estimates for heritability, whereas girls have slightly higher estimates for shared environment. These differences were, however, small and had overlapping confidence intervals. For these reasons, and to increase power in the present study and to decrease the complexity of reporting, all analyses were conducted on the basis of the full sample, combining sexes and including opposite-sex pairs.The measures were described in terms of means and variance, comparing boys and girls and identical (MZ) and fraternal (DZ) twins; the mean differences for age and sex and their interaction were tested using analysis of variance (ANOVA). We have previously reported full sex-limitation genetic modeling for GCSE achievement and found little evidence for sex differences in genetic and environmental estimates.Phenotypic correlations were calculated between the composite GCSE SL and GCSE English, between the main GCSE SL languages of French, German and Spanish, and between SL measures and intelligence. The correlations between GCSEs in individual languages were based on a restricted sample and range, as only a minority of students took two or more GCSEs in a SL.27 By comparing twin correlations for MZ and DZ twins, the relative contributions of A, C and E can be estimated. Both MZ and DZ twin pairs growing up in the same family share the same environmental influences; therefore, the correlation between twin pairs for shared environmental influences is assumed to be 1.0. Non-shared environmental influences are assumed to be unique to individuals, that is, uncorrelated between twins and not contributing to similarities between them.The twin method was used to estimate the relative contribution of additive genetic (A), shared environmental (C) and non-shared environmental influences (E) for the variance of SL, English and intelligence measures and for the covariance between them. The twin method offers a powerful natural experiment by comparing the similarity of MZ twins to DZ twins, as MZ twins share 100% of their segregating genes, and DZ twins, just as any other siblings, share 50% of their segregating genes.28 These A, C and E estimates can be calculated more accurately and with confidence intervals using structural equation models with maximum likelihood estimation. We used the structural equation modeling program OpenMx.29 Univariate parameter estimates are reported for all measures.Cross-twin correlations can be used to estimate ACE parameters. A is approximately double the difference between MZ and DZ correlations; C can be calculated by deducting the heritability estimate from the MZ correlations; and E can be calculated by deducting the MZ correlations from unity. E also includes measurement error.rG) is an index of pleiotropy: it estimates the extent to which the same genes influence two traits independent of the heritability of the traits. By weighting the genetic correlation by the heritabilities of two traits, genetic mediation of the phenotypic correlation can be estimated. An algebraically equivalent representation of the same analysis is the Cholesky decomposition (12 in rC) and non-shared environmental influences (rE). Two bivariate genetic analyses were conducted to assess the links between achievement in SL and achievement in first language (English), and assess the links between achievement in SL and intelligence.Bivariate genetic analysis extends univariate analysis of variance to the covariance between two variables. Similar to univariate decomposition of variance, the phenotypic covariance between traits can be decomposed into A, C and E components on the basis of cross-twin cross-trait correlations, examining the covariance between twin pairs across different traits See . Geneticposition , which ion 12 in . These aTrivariate genetic analysis extends bivariate genetic analysis to consider all three variables simultaneously: intelligence, English and SL. Trivariate genetic Cholesky analysis was used to estimate (1) the extent to which the heritability of SL can be explained by genetic influence that is shared with intelligence and English, (2) how much is explained by English independent of intelligence and (3) how much genetic influence is specific to SL, independent of both intelligence and English.Means and s.d.'s are presented in For subsequent analyses, scores were age and sex regressed and normalized using the van der Waerden transformation, as explained in the Materials and Methods section.E) that do not contribute to similarities between the twins accounted for the remaining fifth of the variance (22 and 20%). Interestingly, German language achievement at the age of 16 yields a lower heritability estimate of 36% and a higher shared environmental influence of 45%, although these estimates are not significantly different from French or Spanish. All twin correlations and detailed model-fitting results, together with confidence intervals, are presented in Phenotypic correlations among the three variables are substantial. English and SL correlate 0.70 . Intelligence correlates moderately with both English  and SL . Correlations between specific languages are also substantial (0.69–0.79), as shown in 12 path  of the heritability of SL achievement see .We conducted similar analyses for the specific languages of French, Spanish and German. To investigate further the relationships between SL English and intelligence, a trivariate genetic analysis was conducted. We found that most individual differences in SL achievement are accounted for by genetic differences, rather than school, family and other environmental influences. This conclusion holds for both Spanish and French, although there may be less genetic influence and more shared environmental influence for German.3 which might be because different measures were used. In the present study we used standardized examination scores at the end of compulsory education, as compared with teacher ratings of academic achievement in our earlier report. Secondly, the teacher-rated measure used previously was collected at the age of 14, which is typically in the middle of SL learning. Our current measure was obtained at the end of formal SL education, when individual differences may have become more stabilized.These heritability estimates are higher than those in our earlier study,Our bivariate results demonstrate a general genetic factor of language achievement at the end of compulsory education in the United Kingdom in the sense that achievement in English and SL is influenced to a large extent by the same genes. Furthermore, genetic influence on SL achievement cannot be explained by intelligence alone. SL heritability is just as much explained by English achievement as it is by intelligence, and the genetic bivariate relationship between SL and English is stronger than the bivariate genetic relationship between SL and intelligence. A more comprehensive picture is provided by our trivariate results, which show that genetic influences on intelligence contribute about one-third of the heritability of SL achievement. A further third of the heritability of SL can be accounted for by genetic influence on English independent of intelligence, pointing to a general factor of language. The final third of the heritability of SL is unique to SL, that is, independent of both intelligence and English.27 Second, the instructed language learning studied here could differ from learning in a natural setting, and therefore the results of this study cannot be generalized to SL acquisition outside of classroom settings,31 and only apply to those who have chosen to take GCSE in SL. Third, some schools in the United Kingdom require students to take at least one foreign language GCSE, whereas others do not allow pupils to choose more than one; therefore, we could not investigate the genetic and environmental origins of individual differences in choosing one or more foreign language GCSE courses. Furthermore, because SL GCSE is compulsory in some schools but not in other schools, it might not be a random group of students who took one or more foreign language GCSE courses. Finally, the foreign language GCSE examination consists of four parts: reading, writing, listening and speaking, which make it a reliable measure of overall academic achievement in language learning. However, only one composite grade per language is awarded at GCSE level, so that we could not distinguish these different aspects of language learning as they relate to English achievement or intelligence. We created the composite of English language and English literature because there is substantial overlap with the course content measuring reading, writing, speaking and listening skills. Nonetheless, we checked whether analyzing the English language grade by itself yields similar results; the results are highly similar to those shown for the composite measure. It is also noteworthy that both GCSE English and GCSE SL are assessed by standardized examinations, whereas intelligence is not. Thus, it is possible that shared method variance contributes to the correlation between English and SL.We believe our study is the first adequately powered study to employ standardized examination results for SL learning at the end of compulsory education in order to estimate genetic and environmental influences on the variance and covariance of first and SL achievement and intelligence. There are, however, at least four limitations that need to be acknowledged. First, the usual assumptions about twin method were made, which are described in detail elsewhere.34 Further research is needed to study the etiology of the associations between these predictors and achievement in SL using a multivariate genetic design, and this is one of our goals for future research. Another goal is to understand the role of specific cognitive abilities, not just general intelligence, on SL achievement. One strategy that could prove useful in this regard is to study individuals with discrepancies between GCSE grades in English and SL.The present results suggest several questions for further research on academic achievement in SLs. Our future research involves longitudinal investigations into SL achievement, for example, a longitudinal analysis exploring how early English achievement and intelligence relate etiologically to SL at the age of 16. We will also explore whether the conclusions presented here for the entire sample hold at the extremes of exceptionally high or low SL achievement. If appropriate samples can be found, multivariate genetic analyses should be conducted in different foreign languages to investigate the extent to which the same genetic and environmental factors influence learning diverse foreign languages. This was not possible in the present study because few students took more than one foreign language GCSE. Furthermore, all of the students in this study were native speakers of English. It would be of considerable theoretical interest to explore the role of first and SL typological distance as an influence on SL etiology, that is, how the differences between languages on various aspects of linguistic structure influence the rate of language learning and achievement. A large body of literature has shown that SL-learning aptitude, learning styles and quality of instruction are significant predictors of the rate of SL learning.35 Genotype–environment correlation may be increasingly important during adolescent development; achievement in language learning could be influenced by how much students use the language outside the school, their interest in the different cultures and self-efficacy.We have demonstrated here that genes explain a larger proportion of differences between children in SL achievement than do shared environmental influences of school and home environment. It is important to note that genes not only influence the aptitude and achievement of children directly, but also their appetite for knowledge and hence indirectly their eventual achievement. This is an example of genotype–environment correlation; as children grow older they tend to select, modify and tailor their environment on the basis of their genetic propensities.Achievement at the end of compulsory education is of major, and increasing, importance to society and to individuals because these results are used to make decisions regarding further education and occupation. The findings of our study will become even more important once specific genes responsible for academic achievement in SL learning are identified, unique environmental factors are ascertained and gene–environment interplay is better understood.