Aconitum alkaloid in Radix Aconiti Lateralis Preparata  with potent pharmacological activities, such as analgesia and anti-inflammation. The present study developed a simple and reliable method using BMA as a marker compound for the quality control of processed aconite roots and their products.Benzoylmesaconine (BMA) is the main 18 column by gradient elution with acetonitrile and aqueous phase, containing 0.1% phosphoric acid adjusted with triethylamine to pH 3.0.After extraction, a high-performance liquid chromatography (HPLC) determination of BMA was conducted on a RP-CA distinct peak profile was obtained and separation of BMA was achieved. Method validation showed that the relative standard deviations (RSDs) of the precision of BMA in all intra-day and inter-day assays were less than 1.36%, and that the average recovery rate was 96.95%. Quantitative analysis of BMA showed that the content of BMA varied significantly in processed aconite roots and their products.This HPLC method using BMA as a marker compound is applicable to the quality control of processed aconite roots and their products. Aconitum are widely distributed across Asia and North America. For over two thousand years, Radix Aconiti Lateralis Preparata  has been used in China to relieve joint pain and treat rheumatic diseases [Aconitum alkaloids including aconitine, mesaconitine and hypaconitine. For example, before used in proprietary herbal products, the toxicity of these alkaloids can be lowered by hydrolysis into much less poisonous benzoylaconines which are the products of deacetylation of the 8β-acetoxyl [Aconitum alkaloids [per oral) significantly increased the pain threshold in rats. Its analgesic potency was as potent as that of aconite roots at 1000 mg/kg  [Plants of the genus diseases . Studiesdiseases ,3. Proceacetoxyl . Previoulkaloids . By complkaloids . It was er oral) . Recentler oral) , antinocer oral) . Due to 18 column when its percentage was over 10% [18 column was required to stand such an alkaline buffer (pH > 8) [The present study developed a suitable analytical method for identification and quantification of BMA to simplify the quality control procedures. Several HPLC methods have been reported , none of(pH > 8) ,11. At t(pH > 8) -14. In tNine batches of the processed aconite roots were purchased from herbal medicine markets in Sichuan, Shanxi and Guangdong provinces in China Table .Guifulizhong Wan , Sanqisangyao Capsule , Haimabushen Wan , and Jinguishenqi Wan . The main indications of these products are muscular disorders, joint pain and arthritis. Qingfuguanjieshu Capsule (QC), a new antiarthritic herbal preparation being developed in our research group [The Chinese proprietary products containing processed aconite roots used in this study included ch group ,16, was Acetonitrile was of HPLC grade . Twenty-eight per cent (28%) ammonia solution , 95% ethanol , chloroform , ethyl acetate, triethylamine, 85% phosphoric acid, diethyl ether anhydrous  and hydrochloric acid  were of guaranteed reagent grade. Deionized water was prepared using a Millipore water purification system .1H-NMR and MS) [The reference standard for BMA was prepared from mesaconitine  which was heated at 100°C in dioxane-water (1:1) for 6 hours and purified by column chromatography and crystallization ,11. The  and MS) .An Agilent 1100 series LC system  was used in the study, which consisted of a G1311A quaternary pump, a G1322A degasser, a G1315A diode-array detector and a G1313A autosampler.18  was used as the stationary phase companied by Alltima RP-C18 guard column (ID 7.5 × 4.6 mm). Elution of the alkaloids was carried out using a gradient of acetonitrile (A) and buffer solution  at a flow-rate of 1.0 ml/min. The gradient elution of the mobile phase was 13–18 % A in 0–20 min, 18–21 % A in 20–40 min, 21–22 % A in 40–45 min and 22–70 % A in 45–50 min. Detection was carried out at 240 nm with a reference wavelength of 550 nm at room temperature. The injection volume was 20 μl for all HPLC runs.Alltima RP-CProcessed aconite roots were pulverized into powder, passed through a 0.45 mm sieve, and stored in a desiccator. The powder (1.5 g) was extracted with 50% ethanol three times  by sonication  at room temperature, and then vortexed for 2 min respectively. The mixture was centrifuged for 10 min at 3000 rpm . The supernatants were combined and transferred to a 10.0 ml volumetric flask, with 50% ethanol making up the volume.Powdered pills or contents of capsules of the proprietary products (approximately 1.0 g) were accurately weighed. Each sample was dissolved in 10 ml of HCl solution (0.05 M) by sonication for 60 min, and extracted with ethyl acetate three times (10 ml each time). The acidic aqueous solution was separated and basified with 600 μl of 28% ammonia solution and further extracted with 10 ml of mixed solvents of diethyl ether and ethyl acetate (1:1) three times by vortexing for 2 min. The resulting mixtures were centrifuged at 3000 rpm  for 5 min and the combined supernatants were evaporated to dryness under air stream. The residue was dissolved in 1.0 ml of HCl solution (0.01 M) by sonication for 1 min.BMA was accurately weighed and dissolved in HCl solution (0.01 M) to produce a stock standard solution at a final concentration of 0.4084 mg/ml. This stock solution was used to prepare standard solutions for method validation and calibration curves. The standard solutions were stored at 4°C and remained stable for at least one month. Calibration curves were established at seven concentration (μg/ml) points of 4.08, 10.21, 20.42, 40.84, 81.68, 122.52 and 204.20 respectively. For recovery test, a standard solution was prepared at a concentration of 12.25 μg/ml.Expressed as relative standard deviations (RSDs), precision was evaluated by HPLC runs with standard solutions at three concentrations under the optimal condition five times in one day for intra-day variation test and twice a day on three consecutive days for inter-day variation test.Six aliquots of QC were conducted for repeatability test. The processing of the aliquots followed the same method described in the section of preparation of sample solutions. The RSDs of the six aliquots were calculated for evaluation of repeatability.HCl solution  was added to accurately weighted QC (approximately 0.1 g) in which the content of BMA was known. The sample solution was spiked with 1000 μl of the standard solution of BMA for recovery test. The processing of the prepared samples (n = 6) followed the method described in the section of preparation of sample solutions.Data analysis, including calculation of standard deviation (SD) and linear regression, was conducted using Excel 2003 . P values less than 0.05 were considered as statistically significant.The use of phosphoric acid (0.1 %) with triethylamine as the mobile phase produced better symmetry of the peak in the chromatogram. A gradient elution program was developed to isolate BMA and to determine the content of BMA in the proprietary products. Figure By adjusting the triethylamine content to obtain the pH values from 2.3 to 5.6, we investigated the pH dependence of the retention time. The results show BMA retention time remained relatively stable in the range of 42–44 min as pH value increased  were evaluated for their efficiency in extracting BMA from processed aconite roots. Since BMA is an alkaloid, an acidic extraction solvent (0.01 M HCl) was also tested. The results show that the extraction efficiency of these solvents was in the following order: 50 % ethanol > 25% ethanol > 0.01 M HCl > 75 % ethanol > 95 % ethanol. For highest efficiency, 50 % ethanol was selected for extracting BMA in processed aconite roots in the present study  by sonication for 60 min, which were subsequently extracted with ethyl acetate for three times (10 ml each time). The acidic aqueous solutions were then basified with 600 μl of 28 % ammonia solution and further extracted with 10 ml of mixed solvents of diethyl ether and ethyl acetate (1:1) for three times. The recovery rate of BMA was 90.64% (SD 0.58%) when diethyl ether was the extraction solvent. The recovery rate was nearly perfect when ethyl acetate was the extraction solvent; however, there was a small interference peak at the retention time of 43 min. Thus, a mixed solvent of diethyl ether and ethyl acetate (1:1) was used, whereby the recovery rate was 96.95% (SD 1.01%) and no interference peak was observed.The BMA peaks in processed aconite roots and in their proprietary products were identified through comparison of the retention times and UV spectra with those of the reference standards. Peak purity was confirmed by data from a photodiode array detector (DAD). Furthermore, a comparative study was carried out with QC samples and QC without processed aconite roots (negative control). There is no peak corresponding to BMA in the chromatogram of the negative control Figure .2). The following equation was obtained: Y = 18.518X + 5.651 .The linearity of the BMA concentrations (μg/ml) versus peak areas was investigated in the range of 4.08–204.20 μg/ml; the result is expressed as the value of the coefficient of determination  at least three times larger than noise (N), was determined to be 8 ng for BMA with an injection volume of 20 μl.The precision of the intra-day (five times per day) and inter-day (twice a day for three consecutive days) data was indicated by RSDs which were less than 1.36% for BMA at three concentrations (Table The RSDs of the repeatability test were less than 0.29% for BMA at 132.8 μg/g (SD 0.4 μg/g) in the QC samples (n = 6). The average recovery rate obtained was 96.95% (SD 1.01%) with RSDs of 0.01% (n = 6). This chromatographic system is suitable for quantitative determination of BMA in processed aconite roots and their proprietary products.The content of BMA in the five proprietary products, and nine batches of processed aconite roots were determined using the established HPLC method described above. The content of BMA Tables  and 4 waSignificant variations in terms of BMA content were found among different batches of processed aconite roots and among different proprietary products Tables  and 4. DAs herbal products containing processed aconite roots are increasingly used for anti-inflammation and analgesia, simple and reliable methods for quality control of these products are urgently needed. It was reported that BMA was effective in anti-inflammation and analgesia in animals ,6. Thus,In the present study, extraction method was optimized. Results from the recovery test show that the use of two solvents is better than that of a single solvent in preparing samples of proprietary products.Aconitum alkaloids using a reversed phase C18 HPLC column, tailing peaks are usually caused by the retention effects of free silanol groupings. Instead of using THF as an organic solvent or basic buffer in the mobile phase, we used triethylamine to improve separation and peak shapes. Moreover, this HPLC method should be easily repeated in other labs. The present study also indicates that the retention volumes of BMA remained relatively unchanged over an acidic pH region (Figure In the analysis of n Figure .Method validation data indicate that the developed HPLC method as described in this paper is reliable, reproducible and accurate for the determination of BMA in processed aconite roots and their products. The results also show that the content of BMA varied significantly in different batches of the processed aconite roots including five proprietary products. This method is suitable for routine assessment of the quality of processed aconite roots and their products.BMA: benzoylmesaconine; DAD: photodiode array detector; GC-MS: gas chromatography-mass spectrometry; HPLC: high-performance liquid chromatography; LC-MS: liquid chromatography-mass spectrometry; RSDs: relative standard deviations; SD: standard deviation; SPE: solid phase extraction; THF: tetrahydrofuranThe authors declare that they have no competing interests.Qingfuguanjieshu Capsule and helped with data acquisition, HX contributed to the design of the study, LL, the principal investigator of the project, contributed to the conception and design of the study, revised and finalized the manuscript. All authors read and approved the final version of the manuscript.YX contributed to the conception and design of the study, carried out the experimental work, and drafted the manuscript, ZJ contributed to the design of the study and helped revise the manuscript, HZ participated in the design of the study and performed statistical analysis, YW and ZL participated in the experimental work of


To the Editor: New Delhi metallo-β-lactamase 1 (NDM-1) and OXA-48-group β-lactamase have been increasingly reported as carbapenemases responsible for carbapenem resistance in Enterobacteriaceae worldwide (Klebsiella pneumoniae carbapenemase (KPC)–type β-lactamase is the most common carbapenemase among Enterobacteriaceae, especially K. pneumoniae. Isolates producing NDM-1 were first reported in the United States in 2010 . She was readmitted to the same hospital because of fever in March 2013.K. pneumoniae and extended-spectrum β-lactamase–producing E. coli. Although production of KPC-type β-lactamase was initially suspected in K. pneumoniae, the unusually high level of resistance to amikacin (MIC >32 μg/mL) and gentamicin (MIC >8 μg/mL) increased concern for presence of an NDM-1 producer, which is frequently highly resistant to aminoglycosides because of production of 16S rRNA methyltransferase (A urine culture collected at the time of readmission grew carbapenem-resistant K. pneumoniae isolates from India (armA) was also confirmed by PCR and sequencing and accounted for the high-level aminoglycoside resistance. The isolate belonged to sequence type (ST) 14, as determined by multilocus sequence typing, and has been reported to be common among NDM-1–producing K. pneumoniae in Europe , and dedicated personnel monitored compliance with these measures around the clock.Enterobacteriaceae by using rectal swab specimens was conducted for all inpatients at the acute-care hospital and for all residents of the unit at LTCF 2. Testing did not identify any other patients colonized with NDM-1–producing Enterobacteriaceae.The patient was eventually discharged to another long-term care facility (LTCF 2) in April 2013. A point surveillance testing for NDM-1–producing K. pneumoniae, but those carrying the NDM-1 gene could not be obtained by either method, suggesting that the 2 genes were not located on the same plasmid. For E. coli, transformants and transconjugants carrying the NDM-1 gene were obtained, which indicated that this gene was located on a self-conjugative plasmid.In transformation and conjugation experiments, transformants carrying the OXA-232 gene were obtained from Enterobacteriaceae, in particular K. pneumoniae, poses a diagnostic challenge in regions to which KPC-producing K. pneumoniae is endemic. In our case, recognition of resistance to multiple aminoglycosides by an automated instrument, which was confirmed to be high level by the disk diffusion method , prompted early detection and implementation of appropriate infection prevention measures. Production of 16S rRNA methyltransferase by KPC-producing K. pneumoniae is extremely rare, and no cases have been identified in the United States. Therefore, we propose that high-level resistance to amikacin and gentamicin can serve as a clue for suspecting potential NDM-1–producing isolates in clinical diagnostic laboratories.Detection of NDM-1– or OXA-48-group–producing Enterobacteriaceae producing OXA-48-group carbapenemase, including variants such as OXA-232, do not have characteristic susceptibility patterns and may easily not be recognized in areas with a high background prevalence of KPC-producing organisms. Therefore, organisms producing OXA-48 or their variants might have already spread in the United States.Conversely,


The endoplasmic reticulum (ER) is a continuous membrane network in eukaryotic cells comprising the nuclear envelope, the rough ER, and the smooth ER. The ER has multiple critical functions and a characteristic structure. In this study, we identified a new protein of the ER, TMCC1 (transmembrane and coiled-coil domain family 1). The TMCC family consists of at least 3 putative proteins (TMCC1–3) that are conserved from nematode to human. We show that TMCC1 is an ER protein that is expressed in diverse human cell lines. TMCC1 contains 2 adjacent transmembrane domains near the C-terminus, in addition to coiled-coil domains. TMCC1 was targeted to the rough ER through the transmembrane domains, whereas the N-terminal region and C-terminal tail of TMCC1 were found to reside in the cytoplasm. Moreover, the cytosolic region of TMCC1 formed homo- or hetero-dimers or oligomers with other TMCC proteins and interacted with ribosomal proteins. Notably, overexpression of TMCC1 or its transmembrane domains caused defects in ER morphology. Our results suggest roles of TMCC1 in ER organization. The functions of the ER, one of the largest organelles in cells, have been studied extensively, including the translocation of proteins across the ER membrane The ER has a characteristic shape that is evolutionarily conserved. Based on membrane curvature, the ER structure can be divided into 2 distinct morphological domains: sheets and tubules First, 2 families of integral membrane proteins have been identified as being responsible for the formation of ER tubules: reticulons and DP1/Yop1p Second, ER sheets assemble through the actions of proteins restricted to ER sheets, such as CLIMP-63, p180, and kinectin. CLIMP-63 is involved in attaching ER membranes and microtubules tmcc1 locus in humans has been reported to be involved in hereditary congenital facial palsy tmcc1 may not be the causative gene Genes encoding putative proteins of the transmembrane and coiled-coil domain (TMCC) family have been found in many organisms. However, the properties and functions of TMCC proteins are unknown. TMCC1, a representative member of the TMCC family, also remains uncharacterized. However, the Caenorhabditis elegans. Sequence alignment of TMCC1 from various organisms showed several conserved regions that share high sequence similarity . Sequence alignment showed that the 3 TMCCs have highly similar protein sequences , and thamilarity . This evTo identify the TMCC1 protein, we generated an anti-TMCC1 antibody in rabbits. An N-terminal fragment, TMCC1(1–200), was chosen as the antigen because this region is unique among TMCC family members in human; the protein fragment was also used to purify the polyclonal antibody against this region of TMCC1. In western-blotting experiments performed on whole cell extracts of HeLa cells, anti-TMCC1 recognized a protein band with a molecular weight similar to the theoretical molecular weight of TMCC1, and this band was not detected by the pre-immune serum . MoreoveNext, we tested for TMCC1 protein expression in several human cell lines. As shown in After identifying TMCC1 as a protein expressed widely in human cells, we examined the subcellular localization of TMCC1. We chose COS-7 cells for immunolabeling experiments because these cells are large. Labeling by anti-TMCC1  showed tOur immunolabeling results indicated that TMCC1 localized to the rough ER. To confirm this, we monitored the localization of TMCC1 transiently transfected into cells: HeLa cells were transfected with a plasmid encoding GFP-TMCC1 and then examined by fluorescence microscopy. When expressed at low levels, GFP-TMCC1 localized throughout the ER, showing an almost identical distribution as calnexin, an integral ER protein that is used widely as an ER marker . The locBecause TMCC1 contains 2 adjacent transmembrane domains at the C-terminus, we investigated whether these domains were responsible for targeting TMCC1 to the ER or if other regions of the protein were also necessary. We transfected HeLa cells with plasmids to express either GFP-TMCC1 lacking the transmembrane domains (aa 1–575) or only the C-terminal transmembrane domains of TMCC1 (aa 571–653), and then stained the cells with calnexin antibody. GFP-TMCC1(1–575) localized in the cytosol and showed no specific pattern of distribution, whereas GFP-TMCC1(571–653) colocalized with calnexin , much liTo confirm the ER localization of TMCC1 further, we isolated ER proteins from cells: HeLa cells were homogenized and ER proteins were purified using discontinuous sucrose-gradient centrifugation . BecauseAfter identifying the C-terminal transmembrane domains of TMCC1 as the potential ER-targeting region of the protein, we sought to examine the topology of the N-terminal region of TMCC1. We transfected TMCC1 with GFP tagged to the N-terminus into COS-7 cells and then immunolabeled these cells. The cells were first fixed with paraformaldehyde and then permeabilized with either digitonin or Triton X-100. Digitonin selectively permeabilizes the plasma membrane and leaves other membranes intact, whereas Triton X-100 permeabilizes cellular membranes non-selectively. The fixed and permeabilized cells were labeled with GFP and calnexin antibodies. Calnexin has a large ER luminal domain and a short cytoplasmic tail. Because the monoclonal calnexin antibody recognizes an epitope present within the ER lumen, and the ER membrane was intact in digitonin-permeabilized cells, calnexin was detected only in cells permeabilized with Triton X-100 . By contTo further confirm the above result, we performed protease protection assays. HeLa cells were incubated with digitonin to permeabilize the plasma membrane, and then treated with trypsin to digest exposed proteins. Under these conditions, the control protein cathepsin D, which is an aspartyl protease present within lysosomes, was not digested by trypsin because it was protected by the lysosomal membrane. By contrast, TMCC1 was digested by trypsin, indicating that the N-terminus of TMCC1 was present in the cytoplasm . Thus, tCoiled-coil domains are known to mediate protein-protein interactions, and several ER proteins containing coiled-coil domains are thought to form oligomers by using these domains Because the coiled-coil domain adjacent to the C-terminus of TMCC1 is highly conserved among TMCC family members and this domain is required for intermolecular interaction between TMCC1 proteins, we tested whether TMCC1 interacts with other TMCC proteins. We transfected HEK293T cells with plasmids encoding GFP-tagged TMCC2 or TMCC3 and then immunoprecipitated endogenous TMCC1. Rabbit IgG was used as the negative control for immunoprecipitation, and GFP-TMCC1(571–653) served as the negative control for the interaction of exogenous proteins with endogenous TMCC1 because this fragment did not interact with full-length TMCC1 . Both GFEscherichia coli. As shown in To understand the functions of TMCC1, we performed mass spectrometry to identify TMCC1-binding proteins. HEK293T cells were transfected with the FLAG-TMCC1 plasmid, and cell lysates were used for anti-FLAG immunoprecipitation. Immunoprecipitated proteins were resolved by SDS-PAGE and stained with Coomassie Brilliant Blue R-250, and protein bands were identified using mass spectrometry. As shown in We have shown that TMCC1 is an evolutionarily conserved protein and have provided first evidence of TMCC1 expression in human cells. Using immunolabeling and ER-isolation experiments, we have demonstrated that TMCC1 is a rough ER protein. The C-terminal transmembrane domains of TMCC1 were shown to target the protein to the ER, and the N-terminal region and C-terminal tail of TMCC1 were shown to face the cytoplasm. Furthermore, we have demonstrated that TMCC1 can interact with TMCC proteins and with ribosomal proteins, and that TMCC1 overexpression deforms the ER. Therefore, we conclude that TMCC1 is a rough ER protein that may regulate ER membrane organization and the attachment of ribosomes to the ER.TMCC1 localization in rough ER was demonstrated by immunolabeling and also by isolating ER proteins. We observed almost identical labeling patterns for GFP-TMCC1 and calnexin by immunostaining. In the magnified immunofluorescence micrographs, the signals of GFP-TMCC1 overlapped with, but were not exactly merged with, those of calnexin . The difBy immunostaining, we found that each transmembrane domain of TMCC1 localized to the ER . We BLASWhen TMCC1 transmembrane domains and full-length protein were transiently transfected into cells and expressed at high levels, the ER structure was deformed. Overexpression of several ER-membrane proteins has been reported to cause similar defects in ER morphology E. coli, this protein stimulates transcription termination in the S10 operon leader Our selective-permeabilization experiments using digitonin showed that the N-terminal region of TMCC1 resides in the cytoplasm and not in the ER lumen. Thus, the long, cytoplasmic N-terminal region of TMCC1 may bind to diverse targets much like other ER proteins In human, TMCC family includes at least 3 members. As shown in In summary, we have characterized TMCC1, a member of the conserved TMCC family, and have shown that TMCC1 is an integral ER-membrane protein. Consistent with these results, the overexpression of TMCC1 or its transmembrane domains perturbed ER organization. However, we did not observe any substantial defect in ER morphology after RNAi-mediated suppression of TMCC1 expression, which may be because of the presence of other TMCC members. We have also identified the association of TMCC1 with ribosomal proteins. Thus, TMCC proteins may help recruit proteins such as those associated with ribosomes to the ER membrane and thereby regulate ER organization.The cDNA clones of human TMCC1 (Accession No.: NM_001017395) and TMCC3 (Accession No.: NM_020698) were purchased from American Type Culture Collection (I.M.A.G.E. Clone ID: 5527623 and 5264859). The cDNA clone of human TMCC2 (Accession No.: NM_014858) was obtained from Kazusa DNA Research Institute, Japan. The coding sequences of the TMCCs were cloned into pEGFP-C1 (Clontech), pEGFP-N3 (Clontech), or pFLAG-CMV2 (Sigma-Aldrich). TMCC1 fragment aa 1–200 was cloned into pET-28a(+) (Novagen). TMCC1 fragments aa 1–200 and 101–350 were cloned into pGEX-4T-3 . TMCC1 fragments aa 1–575, 571–653, 571–615, and 615–653 were cloned into pEGFP-C1. TMCC1 fragments aa 1–575, 1–200, 225–460, 310–575, 571–653, 460–575, and 225–315 were cloned into pFLAG-CMV2.E. coli BL21 (DE3) as a fusion with either a 6xHis or a glutathione S-transferase (GST) tag. The 6xHis and GST fusion proteins were purified using Ni2+-nitrilotriacetic acid resin (Qiagen) and GSH-beads , respectively. The 6xHis-tagged TMCC1 fragment was used to immunize rabbits, and the antibody produced against TMCC1 was purified from rabbit sera using the GST-tagged protein immobilized on nitrocellulose membranes . Mouse monoclonal antibodies against FLAG (M2), α-tubulin (DM1A), β-actin (AC-15), and a rabbit polyclonal antibody against FLAG were obtained from Sigma-Aldrich. Normal rabbit IgG, a rabbit polyclonal antibody against GFP (FL), and a goat polyclonal antibody against Sec61α (G-20) were from Santa Cruz Biotechnology. A mouse monoclonal antibody against mitochondria (MTC02) was purchased from Abcam, and a goat polyclonal antibody against GST was from Amersham Pharmacia Biotech. A mouse monoclonal antibody against CLIMP-63 (G1/296) was obtained from Alexis, and a mouse monoclonal antibody against RPL4 (4A3) was from Abnova. Mouse monoclonal antibodies against calnexin and BAP31 were kindly provided by Cancer Institute and Hospital, Tianjin, China. A rabbit polyclonal antibody against cathepsin D (Ab-2) was from Calbiochem and a rabbit polyclonal antibody against RPS6 was from Cell Signaling Technology. Secondary antibodies conjugated with Alexa Fluor dyes  were purchased from Invitrogen.To generate antibodies against TMCC1, a fragment of TMCC1, 1–200, was expressed in 2. Plasmids were transfected into HEK293T cells by using Lipofectamine and Plus reagents (Invitrogen). Lipofectamine 2000 (Invitrogen) was used for transfecting plasmids and small interfering RNAs (siRNAs) into HeLa and COS-7 cells. Two siRNA duplexes targeting TMCC1 were synthesized by Shanghai GenePharma: siTMCC1-1, CGAUUGGAAGAACAGCUAA; siTMCC1-2, GCAGACAGAAUCAGAACAA.HEK293T, HeLa, U2OS, and COS-7 cells were cultured in Dulbecco’s Modified Eagle Medium supplemented with 10% fetal bovine serum (FBS). Hep G2, U-937, and HEL cells were cultured in RPMI 1640 Medium supplemented with 10% FBS. SH-SY5Y and U87 cells were cultured in Eagle’s Minimum Essential Medium (EMEM) supplemented with 10% FBS. Caco-2 cells were cultured in EMEM supplemented with 20% FBS. HL-60 cells were cultured in Iscove’s Modified Dulbecco’s Medium supplemented with 20% FBS. A549 cells were cultured in F-12K Medium supplemented with 10% FBS. All cells were obtained from the American Type Culture Collection and grown at 37°C in a humidified atmosphere with 5% COCells grown on glass coverslips were fixed with cold methanol at -20°C for 5 min or with 4% paraformaldehyde in phosphate-buffered saline (PBS) at room temperature for 15 min. After fixation, cells were labeled with primary antibodies and subsequently with Alexa Fluor dye-conjugated secondary antibodies. Nuclei were labeled with Hoechst 33258 (Sigma-Aldrich). Coverslips were mounted with Mowiol  and examined using an inverted fluorescence microscope . To label Sec61α, COS-7 cells were extracted with 1 mg/mL saponin in PBS for 5 min at room temperature before fixing with methanol.g for 20 min at 4°C to remove cell debris, nuclei, and mitochondria. The supernatant was then centrifuged at 150,000 × g for 30 min at 4°C in an ultracentrifuge (Beckman Coulter) using a TLA-100.4 rotor to obtain a total microsomal pellet. The pellet was resuspended in ice-cold resuspension buffer  by using a Kontes 18 glass homogenizer. Next, a discontinuous sucrose gradient was prepared in centrifuge tubes with the following solutions layered from top to bottom: 1.2 mL of 0.3 M sucrose, 0.3 mL of 1.15 M sucrose, 0.1 mL of 1.25 M sucrose containing the total microsomes, 0.3 mL of 1.35 M sucrose, and 0.4 mL of 2 M sucrose. The tubes were centrifuged at 180,000 × g for 90 min at 4°C using a TLS-55 swinging-bucket rotor. The material at each interface was diluted to 0.3 M sucrose and collected by centrifugation at 150,000 × g for 30 min at 4°C. These samples were analyzed by western blotting.The protocol for isolating ER was adapted from methods described elsewhere 2) for 5 min at room temperature, and then treated in the absence or presence of 0.25% trypsin for 5 min at 37°C. Reactions were stopped by adding a protease inhibitor cocktail (Roche Applied Science), and samples were analyzed by western blotting.HeLa cells were incubated with or without 20 µM digitonin (Sigma-Aldrich) in KHM buffer  and clarified by centrifugation. To immunoprecipitate TMCC1, Protein A Agarose beads (Invitrogen) were pre-incubated with normal rabbit IgG or the TMCC1 antibody at 4°C, and then incubated with cell lysates. To immunoprecipitate FLAG-tagged proteins, anti-FLAG M2 Agarose beads (Sigma-Aldrich) were added directly to cell lysates and incubated at 4°C. After incubation, the beads were washed with lysis buffer and boiled in electrophoresis sample buffer. Samples were resolved by SDS-PAGE and analyzed by western blotting.HEK293T cells were lysed on ice using a lysis buffer , and protein bands were excised from the gels, reduced, alkylated, and digested in-gel with trypsin 2, 0.25 M sucrose, and protease inhibitor cocktail) by using a Kontes 7-mL glass homogenizer. The homogenates were centrifuged at 3,000 × g for 30 min and then at 14,000 × g for 30 min at 4°C to remove cell debris, nuclei, and mitochondria. The supernatant was then centrifuged at 270,000 × g for 1 h at 4°C in an ultracentrifuge using a TLA-100.4 rotor. The pellet was resuspended in ice-cold buffer B  by vigorously vortexing for 30 min at 4°C, and then the sample was centrifuged at 14,000 × g for 15 min at 4°C. The supernatant was carefully laid on the top of buffer C  in a centrifuge tube, and then was centrifuged at 270,000 × g for 1 h at 4°C to collect ribosomes. The ribosomes were resuspended in ice-cold buffer D , incubated with GST or GST-TMCC1(101–350) at 4°C, and then pulled down using GSH-beads. The pull-down samples were analyzed by western blotting.GST and GST-TMCC1(101–350) proteins were purified using GSH-beads. The protocol for ribosome preparation was adapted from methods kindly provided by Dr. Alan M. Lin . HeLa cells were homogenized in ice-cold buffer A ; 24 h post-transfection, cells with low and high levels of exogenous proteins were fixed with methanol and co-stained with FLAG and calnexin antibodies. Scale bar, 10 µm.(TIF)Click here for additional data file.Figure S2Subcellular localization of TMCC2 and TMCC3. COS-7 cells were transfected with plasmids encoding GFP-tagged TMCC2 or TMCC3; 24 h post-transfection, cells were fixed with methanol and stained with an anti-calnexin antibody. Scale bar, 10 µm.(TIF)Click here for additional data file.


Extramedullary myeloid tumor (EMMT) is a rare neoplasm of immature myeloid cells that arises at an extramedullary site . The mos9/L. Magnetic resonance imaging (MRI) of the right thigh demonstrated a heterogeneous mass extending towards the distal part in the anterolateral section of the right femoral neck, completely involving the vastus lateralis and intermedius muscles  induction chemotherapy regimen consisting of idarubicin  and cytosine arabinoside . After 4 weeks, the control bone marrow aspiration was completely normal. The lesion had also disappeared completely in the control MRI of the thigh. The patient was administered a high-maintenance dose of ara-C at 3 g/m2 for 6 days for consolidation. Treatment is ongoing.A 47-year-old male patient was admitted to the orthopedics clinic because of swelling and pain in the right thigh for 1 month. His past medical history was unremarkable. Physical examination indicated a 10 cm-long solid soft tissue lesion in the anterior and lateral parts of the right thigh. Complete blood count results were as follows: white blood cell count of 15.1x109/L, hemoglobin level of 11.9 g/dL, and platelet count of 94x10 muscles . The pat muscles . After tEMMTs are composed of myeloid blasts. They can easily be confused with lymphomas or soft tissue sarcomas ,4. EMMTsConsequently, EMMT might be taken into consideration in the differential diagnosis of venous thromboembolism and soft tissue malignancies in the case of swollen thighs.The authors of this paper have no conflicts of interest, including specific financial interests, relationships, and/ or affiliations relevant to the subject matter or materials included.


V˙O2 kinetics in pediatric populations investigated gender differences in prepubertal children during submaximal intensity exercise, but studies are lacking in adolescents. The purpose of this study was to test the hypothesis that gender differences exist in the V˙O2 and heart rate (HR) kinetic responses to moderate (M) and heavy (H) intensity exercise in adolescents. Twenty‐one healthy African‐American adolescents  performed constant work load exercise on a cycle ergometer at M and H. The V˙O2 kinetics of the male group was previously analyzed . For both genders, V˙O2 and HR kinetics were described with a single exponential at M and a double exponential at H. The fundamental time constant (τ1) of V˙O2 was significantly higher in female than male at M  and H , respectively. The functional gain (G1) was not statistically different between gender at M and statistically higher in females than males at H: 9.7 ± 1.2 versus 10.9 ± 1.3 mL min−1 W−1, respectively. The amplitude of the slow component was not significantly different between genders. The HR kinetics were significantly  slower in females than males at M  and H . The G1 of HR was higher in females than males at M: 0.53 ± 0.11 versus 0.98 ± 0.2 bpm W−1 and H: 0.40 ± 0.11 versus 0.73 ± 0.23 bpm W−1, respectively. Gender differences in the V˙O2 and HR kinetics suggest that oxygen delivery and utilization kinetics of female adolescents differ from those in male adolescents.The majority of the studies on  V˙O2) response to exercise is used to evaluate cardiorespiratory and skeletal muscle function in exercise physiology (Whipp and Wasserman V˙O2 response to constant work rate exercise reflects indirectly muscle oxygen (O2) consumption  and cardiac output kinetics  and body mass with a balance beam scale . Stage of maturation was estimated by self‐assessment method proposed by Morris and Udry  and gas exchange threshold (LTGE) via respiratory measurements  and LTGE were used to determine the individual work rates for each of the exercise intensity domains investigated. On the subsequent visits, the subjects performed a series of six square‐wave exercise tests; two per day, at selected work rates, which corresponded to: (a) 90% LTGE  and (b) LTGE + 25% of Δ . Each subject exercised three times at the moderate and heavy intensities. The tests were preceded by a 3‐min baseline period and a 3‐min warm‐up period at 20 W. At the end of the test, the work rate was abruptly reduced to 20 W for a 10 min (active recovery period) and followed by an additional 5 min (passive recovery) while the subjects remained seated quietly on the cycle. The pedaling rate was kept constant at 60 rpm for all exercise intensity tests. During moderate exercise, subjects exercised for 5 min at the predetermined work rate. During heavy exercise, subjects were asked to pedal until they had achieved a steady state which was defined as 2 min of a <5% change in V˙O2 and a <3% change in HR and respiratory exchange ratio.The exercise tests were performed on an electronically braked cycle ergometer  at approximately the same time of day. The subjects were reported to the laboratory on four occasions within a 2‐week period. They were instructed to refrain from eating and exercising in the 2 hours prior to their scheduled exercise tests. The experimental procedures were the same of those used to study the male adolescents. In the first experiment, the subjects performed a 20 W minInstructions to begin and end testing were given by voice without warning. ‘‘Steady‐state’’ values were calculated by averaging data recorded over the last 30 sec of exercise. All square‐wave tests performed were assigned in a randomized sequence to avoid ordering effects. A break of 60–90 min was enforced between exercise bouts conducted on the same day.2 and CO2 analyzers were calibrated as previously reported , pulmonary oxygen uptake (V˙O2), and carbon dioxide release (V˙CO2)] were continuously monitored. These measurements permitted the determination of the ventilatory equivalents for O2 (VE/V˙O2) and CO2 (V˙E/V˙CO2) as well as the respiratory exchange ratio (V˙CO2/V˙O2). A three‐lead electrocardiogram (SensorMedics) was continuously displayed and used to record HR during the test. Systemic systolic/diastolic blood pressure was measured every 3 min during the maximal exercise test with an automated cuff system .A facemask  was carefully fitted and sealed with a gel  before the exercise and data collection to obviate any gas leaks. The subjects were given several minutes to familiarize themselves with the breathing apparatus in order to minimize unusual breathing patterns. To measure gas exchange, subjects breathed through a mass flow sensor (hot‐wire anemometer) connected to a metabolic cart system . Before each exercise test, the volume sensor was calibrated using a 3‐L syringe while the OV˙O2and HR kinetics data from individual repetitions of moderate and heavy exercise intensities were processed before the estimates of the parameter values. First, the data values greater than 2 SD from their local mean were omitted from those used for parameter estimation. Second, the responses for each trial were linearly interpolated to obtain a value at each second. Corresponding values on a second‐by‐second basis were then ensemble averaged to produce a mean dynamic response. Then, averaged values every 5 sec were calculated and utilized for kinetic analysis. The data obtained during the first 20 sec were excluded from the analysis  available in Matlab  customized and applied to the mean responses. The following models were used:The Y = V˙O2 and HR, YBL represents the steady‐state values at baseline ; A1 and A2 are the amplitudes of the exponential terms; τ1 and τ2 are the time constants; and δ1 and δ2 are the time delays. The Heaviside step function (Abramowitz and Stegun H(t−δ1) and H(t−δ2) are used to constrain the exponential terms to their corresponding time domains. Subscripts ‘‘1’’ and ‘‘2’’ denote the fast  and slow components of V˙O2 and HR dynamic response, respectively. From the fundamental and slow‐phase amplitudes  and the change in work rate from baseline (ΔWR), the functional gains of the primary response (G1=A1′/δWR) and the end‐exercise response (GTOT=[A1′+A2′]/δWR) were calculated. Both models  were used to characterize each dataset obtained at moderate and heavy exercise intensities.Model 1:t1/2, half time) of the V˙O2 and HR kinetics was determined to assess the relationship between V˙O2 and HR responses to moderate and heavy exercise intensities in both adolescent groups.The interval of time to reach half of the amplitude .All data are expressed as means ± SD. Comparison of estimated kinetic parameters within a group were performed using a mixed model analysis of variance accounting for repeated measures on each subject. Post hoc analysis with a t‐test and least significant differences was used to discern differences in the parameters among intensity domains. An F‐test was performed to evaluate whether the data were fit significantly better by model 2 than model 1. The square of the correlation coefficient was used to evaluate the goodness of fit for each model. Pearson's correlation was used to assess a linear association between selected variables. For all tests, a V˙O2 and peak of V˙O2 normalized to the body weight of the female group were 59 and 73% of that of the male group, respectively. The WR in female was 64% of that of the male group, whereas the peak of HR (191 ± 6 bpm) was similar in both adolescent groups. V˙O2 and WR at the LTGE were significantly higher (P < 0.05) in males. In females as compared to males, the V˙O2 at the LTGE was 0.89 ± 0.16 versus 1.56 ± 0.28 L min−1 and occurred at work rates of 73 ± 14 and 115 ± 23 W, respectively.The female group was selected to match the age and body mass index of the male group previously investigated  and reported in Table V˙O2 kinetics of the male group were estimated and analyzed in another previous study  increased with increasing exercise intensity in both groups  increased with exercise intensity in both groups  differed significantly among the two exercise intensity domains only for the females but not for the males, moreover, it differed between groups at any intensity. The fundamental time constant (τ1) was independent of exercise intensity only for the females. In both groups, a V˙O2 slow component became evident after approximately 2–3 min (δ2) of the phase II of exercise responses at H. The mean value of the Phase III time constant of the response (τ2) was not different between the two gender . The exhaustion time of the heavy exercise test for females (7.6 ± 0.6 min) was similar to that observed in males (7.8 ± 0.6 min). The magnitude of the functional gain of the fundamental phase (G1) in males was similar to that measured in females at moderate intensity while was lower than females at heavy exercise intensity. Moreover, there was no gender difference in GTOT at M, whereas it was found lower in males than females at H.In both adolescent groups, the kinetics response at M was well fitted by a monoexponential model , whereas that at H by a double‐exponential model  according to the F‐test. The mean τ1 of V˙O2 and V˙O2,peak for male  and female  adolescents.There was no correlation between the V˙O2 kinetics were characterized by the single‐and double‐exponential model for M and H, respectively. The HR mean value at the end of the exercise (HRE) increased by 20% with exercise intensity in both groups  of the Phase II of exercise response at H for males and females, respectively. The mean value of the τ2 was similar for both gender . In males, the G1 and GTOT were approximately 50% lower than that determined in females at M and H. The GTOT was independent from the exercise intensity for both gender groups.The HR kinetics as for the V˙O2 and HR kinetics, a linear association between τ1 of V˙O2 and HR kinetics was investigated in both groups of adolescents  and was not significant at H , whereas in females the correlation between τ1 of V˙O2 and HR was not significant at both exercise intensities . The correlation between t1/2 of V˙O2 and HR kinetics was also investigated in both adolescent groups. In males, a significant correlation was observed at M  and H , whereas in females the correlation was not statistically significant at both exercise intensities .To assess the relationship between ts Table . In maleV˙O2 kinetics in pediatric populations have investigated age and gender differences in prepubertal children during submaximal high‐intensity exercise, but studies are lacking in adolescents. In this study, V˙O2 and HR responses to constant work rate exercise of moderate and heavy intensities were characterized in females and compared to those of African‐American male adolescents. The main findings of this study showed gender differences in the V˙O2 and HR kinetic response to moderate and heavy exercise intensity in adolescents: (1) the primary time constant of V˙O2 and HR kinetics in females is lower than that of males; (2) the primary gain of V˙O2 kinetics is independent of exercise intensity for both groups, whereas it is greater in females than males only at heavy exercise intensity while the primary gain of HR kinetics is higher in female than male; (3) there was no gender difference in the slow component of V˙O2 kinetics; and (4) V˙O2 and HR kinetics were significantly correlated only for the male adolescent group.The majority of the studies of V˙O2 kinetics response to moderate and heavy exercise. This result confirms that not only boys   of males was 50% lower than females for both moderate and heavy exercise intensities. As the total gain ΔV˙O2/ΔWR in males was only 5–12% significantly lower than females, the corresponding ΔV˙O2/ΔHR in males was 78 and 61% higher than those in females at moderate and heavy exercise intensities, respectively. The higher total gain of HR of female in comparison to that found in male at both exercise intensity suggest that gender differences exist in the cardiovascular regulation during exercise. This result suggests a difference in stroke volume and/or oxygen extraction between male and female. Previous studies showed that the higher HR during exercise in females than males is related to regulatory mechanisms of the cardiovascular system to compensate the lower stroke volume changes in girls than boys (Armstrong and Welsman Beside the V˙O2 kinetics at moderate was different than that at heavy exercise intensity. For M condition, several studies attributed the V˙O2 kinetic regulation to the bioenergetic processes at cellular level rather than central or peripheral oxygen delivery limitations which appear to be relevant only at H or above (Grassi V˙O2 kinetics in adults reported as indirect evidence of oxygen delivery limitation at H, a slower HR kinetics at H than M (McNarry et al. τ1 and G1 of V˙O2 were found dependent on exercise intensity. In contrast, our results showed a G1 of V˙O2 independent of exercise intensity in females similarly to the previous finding on male adolescents (Lai et al. V˙O2 kinetics supports our results, suggesting that this kinetics are limited by oxygen delivery in adolescents (Marwood et al. 1 parameters are linearly related to the work rate from rest to V˙O2peak (Whipp and Wasserman Although gender difference observed on HR kinetics is substantial at both exercise intensity, it cannot be excluded that their effect on e Grassi . A previ1 and τ1 between M and H to specific recruitment of type I and II fibers during muscle contraction in adults (Barstow et al. V˙O2 kinetics (Breese et al. τ1 (Pringle et al. 1 (Pringle et al. V˙O2 kinetics of female in comparison to male adolescents are consistent with a lower percentage of type I muscle fibers in girls than boys as previous reported on a study in adolescents (Glenmark et al. 1 was similar in females and males at M while it was even higher in females than males at H. The relationship between G1 and type I muscle fiber reported in previous studies (Pringle et al. 1 is expected to increase with higher amounts of type II muscle fiber as G1 is related to the phosphate cost and P/O2 ratio (Rossiter Several studies attributed the differences observed in GRossiter . NMR stuRossiter  indicateRossiter  confirmeRossiter  in femal1 and τ1 observed cannot be explained only by muscle fiber distribution but rather by a combination of factors related to gender differences in biochemical properties, oxygen delivery, and pattern of the recruitment of muscle fiber at moderate and heavy exercise intensity.The slow component observed in female adolescents was consistent with that observed in male adolescent (Lai et al. V˙O2 and HR kinetics found in male provides only indirect evidence for impairment of systemic oxygen delivery. Measurement of cardiac output kinetics provides quantitative information to investigate the relationship between oxygen delivery and utilization at the onset of exercise. Nevertheless, cardiac output kinetics are quite close to those observed for HR as the stroke volume varies during the first 10–30 sec of the onset of a constant workload exercise (Miyamoto et al. The results of this study should also be interpreted in light of several considerations reported in the following paragraphs. The relationship between V˙O2/WR slope and stroke volume by V˙O2/HR slope in both males and females (Cooper et al. V˙O2/HR slope increased with age regardless of the gender and were both higher in boys than girls for all age groups investigated. Under the assumption that females would be more mature than male participants, the gender differences observed in our age‐matched study appear to be conservative. The gender differences between boys and girls with similar maturation level are expected to be higher than those observed in our study.The growth and maturation affect the cardiorespiratory response to exercise. In our experimental design, the adolescent groups were age matched without a maturity assessment as suggested by previous investigators (Mirwald et al. V˙O2 kinetics study in young women reported that high progesterone and estrogen level during the follicular and luteal phases of the menstrual cycle were not associated with changes in the regulation of V˙O2 kinetics and local muscle oxygen delivery at the onset of moderate exercise (Gurd et al. Another potential factor affecting the cardiovascular and respiratory responses of the girls of this study is the hormonal changes during the menstrual cycle which could have contributed to the variability in the physiological responses (Wheatley et al. V˙O2 kinetics. Previous studies applied mass balance relationships at steady state to quantify the extent of central and peripheral factors limiting maximal oxygen consumption at whole‐body level (Di Prampero and Ferretti Beside the empirical models used to characterize the kinetics of physiological variables and to identify the limitations to the physiological response, biophysical‐based mathematical models of the system can be used to describe the processes of oxygen transport and metabolism during exercise and analyze the effect HR kinetic parameters on V˙O2 kinetics at both exercise intensity. Although the primary gain is independent of exercise intensity, female adolescent showed a higher primary gain than male only at high exercise intensity providing evidences in gender differences in the energy cost. The faster HR kinetics in male than female and the association between HR and V˙O2 kinetics in male can in part explain the gender difference observed in V˙O2 kinetics. The HR changes relative to work rate are higher in female than male indicating gender differences in the mechanisms regulating the cardiorespiratory response to exercise.In summary, the dynamic responses to square‐wave exercise of moderate and heavy intensity in a group of female adolescents differ from those previously observed in male adolescents. Female adolescents consistently displayed slower


Protein-protein interface holds important information of protein-protein interactions which play key roles in most biological processes. In the past few years, a lot of efforts have been made to improve interface residue recognition by characterizing protein-protein interfaces and extracting relevant features. However, most previous studies were carried out in a qualitative level, and there are also some inconsistencies between them.In the present work, to improve interface residue recognition, we built a novel quantitative residue protein-protein interface propensity index (QIPI) and gained a comprehensive picture of protein-protein interface through analyzing protein-protein interfaces on our comprehensive protein-protein interfaces dataset . Furthermore, in order to assess the effect of QIPI in improving the protein-protein interface prediction, we developed an interface residue recognition method SPR (Single domain based Patch Recognition) based on the QIPI. The evaluation results proved that our novel QIPI is able to improve the interface residue recognition.Through a comprehensive quantitative analysis of protein-protein interface, we constructed a novel quantitative protein-protein interface propensity index (QIPI), which could be easily applied to improve the interface residue recognition and helpful in understanding the protein-protein interface.http://www.scbit.org/QIPI/.QIPI and SPR are available to non-commercial users at our website: The online version of this article (doi:10.1186/s12918-016-0351-7) contains supplementary material, which is available to authorized users. Protein-protein interactions play crucial roles in many biological functions –3. A detIt is indicated that protein-protein interfaces are characterized by several distinguishing properties from the rest of the surfaces in terms of geometric and chemical complementarities between interfaces, ranging from hydrophobic forces, electrostatic forces, surface planarity, interface biased residue composition to inter-residue contacts –15. KnowIn this work, we performed a novel analysis of protein-protein interface on our comprehensive protein-protein interfaces dataset . Because the interface and non-interface surfaces have different solvent accessibility, it is not well known whether their difference is due to the differences in solvent accessibility or differences in functionality (such as protein-protein interaction). The bias effect of solvent accessibility should be excluded in the protein-protein interface analysis. We analyzed the interface using non-interface surface as reference to remove the bias effect of solvent accessibility. In a convincing manner, a novel quantitative residue interface propensity index (QIPI) was constructed from our analysis and an interface residue recognition method SPR (Single domain based Patch Recognition) was developed based on the quantitative index to evaluate the interface prediction power of QIPI. The result shows that the QIPI not only characterizes protein-protein interfaces, but also helps to improve the interface residue recognition.Protein complexes were retrieved from the latest version of Structural Classification of Proteins — extended (SCOPe) database (v2.05) . A previA dataset of protein-protein interfaces , which consists of 4506 interfaces, was thus obtained from the Astral2.05-40 dataset.The Astral2.05-40-4506 was used as the comprehensive interface dataset to analyze characteristics of protein-protein interfaces and develop our interface prediction method. We used the independent dataset Docking Benchmark 2.0  to evaluTwo protein-protein interface datasets were widely used to assess interface residue recognition methods in the previous study. The first dataset consists of 25 CAPRI targets and 176 interfaces. The second dataset Enz35 set consists of 35 protein interfaces  and thes2 is defined as surface residue. Surface residues were classified into two groups: interface and non-interface. The interface is formed by spatially neighboring residues whose ASA between single domain and complex were changed more than 1 Å2 per site and cross-interface contacts distance < 5 Å. The other surface residues are non-interface [http://www.bioinf.manchester.ac.uk/naccess/). Only surface residues were considered in the analysis and assessment. Similarly, only unbound structures were used for interface prediction.For a single domain, the residue whose accessible surface area (ASA) > 1 Ånterface , 26, 27.fi be the number of interface residues of type i, and Fi be the number of non-interface surface residues of type i. The frequency of residue i in the interface and non-interface surface were calculated as wi = fi/∑mfm and Wi = Fi/∑mFm (m is the residue type), respectively. The relative interface ratio (RIR) of residue type i was given by (wi/Wi). As the similar criteria, we analyzed the frequency and RIR of secondary structure elements in interface. In order to analyze the independent and cooperation effect of residues and secondary structures, we considered 60 classes of residues as defined by 20 residue types multiplied by 3 secondary structure states and analyzed the frequency and RIR of the 60 kinds of residues at interface.Let At for residue type i from the Astral2.05-40-4506. The ASA threshold At was defined that ASA frequency (percentage of residues in the ASA bins) of interface residue type i was very close to the ASA frequency of non-interface surface ones in the At bin was the number of interface residue type i whose ASA < At, and fIL(i) was the number of interface residue type i whose ASA ≥ At. As the similar definition, the fSS(i) and fSL(i) are generated for the non-interface surface residue type i. The relative interface ratio (RIR) of residue type i in ASA was given by (fIL(i)/fIS(i))/(fSL(i)/fSS(i)).In order to describe the ASA propensities for interface and non-interface surface residues, we got the ASA threshold Cij was the number of interface-crossing contacts between residues of types i and j. The raw contact frequency between residues of types i and j was calculated as . Here, m and n are residue types in the interface-crossing contacts. The contact preference between residue types i and j was calculated as log2/(wi × wj)), where wi and wj were defined as above.Interface size and residue number is calculated separately for each side of an interface. Domain size is also calculated for each domain. The summary of statistic result was shown in histogram and probability density function curve.Based on characteristics of interface especially the QIPI in our analysis, a novel method SPR (Single domain based Patch Recognition) was developed as an interface predictor to assess the effect of interface features founded by us. Therefore, in SPR, we focus on (i) patches generated on the protein surface as virtual interfaces, which is described in the section of patch generation and (ii) the scoring function to evaluate the quality of a virtual interface, which is described in the section of scoring function.Patch generation on the protein surface2.Step I: Identification of surface residues. As in the above analysis, surface residues are defined as accessible surface area (ASA) > 1 ÅStep II: Generation of residue side-chain distance matrix. For a protein sequence, the minimum distance between side-chain atoms of each residue pair (Cα to Cα distance in the case of glycine) was calculated as the element of residue side-chain distance matrix. If the minimum distance of a residue pair >25 Å, the corresponding element in the matrix was 25 Å.Step III: Construction of candidate interface patches. A random surface residue was selected as the seed residue, and neighboring surface residues whose ASA and distance to the seed residue satisfy the standard in the Table Step IV: Merging the candidate interface patches. For candidate interface patches in a protein, two patches were merged into a new patch when the ratio of identity residues between two patches was not less than the threshold Table . The merIn the SPR algorithm, the patch generation on the protein surface follows the four steps.The final predicted interface is defined as the top-ranked candidate interface patch measured by the following scoring function for interface-residue recognition.patch for measuring the predicting patch as an interface is a linear combination of four terms: the interface preference potential for residues preference (Eres), hydrophobic score (Ehydro), residue conservation preference (Econs) and solvation score (Esol). That is given as follows:i are to-be-determined weight factors, which are obtained by training on Astral2.05-40 dataset (see below). The Eres and Ehydro are used potentials from the AAindex database [Eres, Ehydro, Econs, and Esol sees below.Eres was calculated as:Residue interface propensity score. We use a scoring function to calculate similarity between patch and interface based on the sum of residue interface propensity which is calculated from QIPI. The score for a given patch, whose residue interface propensity score i is the relative accessible surface area of residue r at sequence position i which belongs to the patch; RIRr and REFr are the relative interface ratio and the reference ASA of residue type r, respectively. The RIRr for 20 amino acid residues are obtained from QIPI. The REFr is the element of JANJ780101 [2.Ehydro is the hydrophobic score of the query patch, which is given below:Hydrophobic score. The term i is the hydrophobic score in the CASG920101 [3.Residue conservation score. Residue conservation was assessed by the self-substitution score based on the sequence profile. Sequence profiles were built by using PSI-BLAST  to searcir is the self-substitution score in the position-specific substitution matrix produced by PSI-BLAST for the residue type r at sequence position i, and Brr is the diagonal element of BLOSUM62 for residue type r.4.Esol was adapted from the one used in Cyscore [Solvation energy score. The  Cyscore , which ii,sphere is defined as the sphere volume in the solvent accessible surface and Vi,out represents the volume out of the solvent accessible surface on residue i in the patch, respectively. The radius of the sphere is set to be 1.2 Å. The Cyscore is a new empirical scoring function for protein–ligand scoring and outperforms famous methods in the field. A novel curvature-dependent surface-area model of the solvation energy score contributes obviously to improve the prediction power of Cyscore. So we used this term in our interface residue recognition scoring function.The score Edatabase . The AAiNJ780101  in AAindNJ780101  for resiSG920101  matrix oInterface prediction has to satisfy two competing demands, covering as many real interface residues as possible, meanwhile predicting as few false positives as possible. These two demands are evaluated by coverage and accuracy, respectively. For all predictions of interface residues, the numbers of true and false positives are TP and FP, respectively. The number of real interface residues which isn’t identified by the predictor is false negative (FN). Then, the coverage isThe two criteria were used as the performance assessment in our study because a good interface recognition method could identify more real interface residues with less false positives.The parameters used in SPR were trained on the Astral2.05-40-4506 dataset that consists of 4506 interfaces from domains with less than 40% identity to each other. Subsequently, the SPR was trained and optimized with a cost function (F) as follows:The optimization goal was to maximize the cost function F value. This training process could balance the accuracy and coverage to avoid the overfitting of parameters. To evaluate the robustness of the SPR, a 10-fold cross-validation for SPR on Astral2.05-40-4506 dataset was carried out.After training of SPR using the above process, the performance of SPR was tested on two datasets CAPRI25 and Enz35 using accuracy and coverage compared with several popular interface recognition programs , 23.To gain an overall performance of SPR, we further tested it on two independent datasets, CAPRI25 and Enz35, by making comparison with several popular interface prediction programs, Meta-PPISP , con-PPIIn this section, we first show the characteristics of protein interfaces in our analysis and develop a novel quantitative residue interface propensity index (QIPI). Secondly, we explore the contribution of the QIPI to improvement of interface-residue recognition. Finally, we demonstrate the performance of SPR by comparing it with several existing popular interface prediction programs.Each protein surface was divided into two disjoint groups: interface and non-interface. Interface properties including residue composition, secondary structure, solvent accessibility, contact preference and interface size were analyzed using Astral2.05-40-4506.Figure relative interface ratio (RIR) of residues by comparing the residue composition of the interfaces with that of the non-interface surfaces. Figure We calculate the The secondary structures are represented simply by three states: helix (H), strand (E) and coil(C). Fig. Figure In summary, the residue composition is a crucial interface feature and the QIPI could be used in improving the interface-residue recognition.relative interface ratio (RIR) of residue type i in ASA was calculated by comparing ASA propensities between interface and non-interface surface residues. The RIR results show that the percentage of interface residues with larger ASA are more than that of non-interface surface ones as the above threshold At. The solvent accessibility features of residues may be used in generating candidate interface patches for interface prediction.In order to analyze solvent accessibility, ASA propensities of interface and non-interface surface residues are compared in Fig. Cij/∑m,nCmn), where Cij is the number of contacts formed by residues of types i and j. Figure 2/(wi × wj)), where wi and wj are frequencies of residue types i and j, respectively. In Fig. In Fig. Combined with the RIR of residues and contact preferences, we may conclude that Arg, Phe, Trp and Tyr have the highest interface propensity. The reason is that RIR of these residues >1.2 . As shown in Table To evaluate the robustness of SPR, a 10-fold cross-validation was carried out on the training set Astral2.05-40-4506. The average of coverage and accuracy were 0.506 ± 0.020 and 0.267 ± 0.019 respectively  a large-scale comprehensive interface dataset Astral2.05-40-4506 for analysis; 2) novel quantitative interface propensities using non-interface surface as reference to remove the bias effect of solvent accessibility; 3) a novel quantitative residue interface propensity index (QIPI) and other interface features improving interface residue recognition confirmed by the interface prediction method SPR.Previously, lots of researches revealed that the interfaces have more hydrophobic and aromatic residues but puzzled by the observation that Arg and His also present more frequently at interface , 22, 40.The interface contact preference contacts in our analysis included three types of contacts: Cys–Cys, contacts between residues with opposite charges, and contacts between hydrophobic residues. The fact that Cys–Cys contacts have one of the highest preferences indicates the important role of this type of contacts in protein–protein interactions. These results are consistent with previous reports which claimed that disulfide bonds, salt bridges, and hydrophobic interactions represent the main forces in protein–protein interactions , 41–44. 2 and about 86% of interface sizes is in the range of 0-2000 Å2. Our observation is consistent with the interface size distribution reported by previous researches. In these studies, Yan et al. found that the distribution of interface sizes has a peak in the range of 600-800 Å2 (whose average is 1227 Å2) [2 [We analyzed the distributions of interface size, interface number and domain size. As shown in Fig. 1227 Å2)  and Lo C7 Å2) [2 . CompareBased on the above results, we constructed a novel quantitative residue interface propensity index (QIPI) which could be easily applied in the interface residue recognition approach. We concluded that QIPI shows clearly the effective improvement in interface residue recognition especially the coverage but its expense is losing accuracy as shown in Table In conclusion, we constructed a novel quantitative residue interface propensity index (QIPI) through building a comprehensive non-redundant protein-protein interface dataset Astral2.05-40-4506 and quantitatively analyzing the protein-protein interface by considering the effect of relative solvent accessibility of interface residues factors distributions. The QIPI with other interface features from our analysis was helpful to explore protein-protein interfaces, and solved some inconsistent observations in previous studies such as interface propensity of Arg and His. Moreover, the QIPI successfully improved the protein-protein interface residue recognition, which was confirmed by the contribution test Table , perform


Environmental factors are determinant for the appearance of autoimmune thyroid diseases (AITD) in susceptible subjects. Increased iodine intake, selenium, and vitamin D deficiency, exposure to radiation, from nuclear fallout or due to medical radiation, are environmental factors increasing AITD. Cigarette smoking is associated with Graves’ disease and Graves’ ophthalmopathy, while it decreases the risk of hypothyroidism and thyroid autoimmunity. Viral infections are important environmental factors in the pathogenesis of AITD, too, particularly human parvovirus B19 (EVB19) and hepatitis C virus. Among the many chemical contaminants, halogenated organochlorines and pesticides variably disrupt thyroid function. Polychlorinated biphenyls and their metabolites and polybrominated diethyl ethers bind to thyroid transport proteins, such as transthyretin, displace thyroxine, and disrupt thyroid function. Among drugs, interferon- and iodine-containing drugs have been associated with AITD. Moreover intestinal dysbiosis causes autoimmune thyroiditis. To reduce the risk to populations and also in each patient, it is necessary to comprehend the association between environmental agents and thyroid dysfunction. Graves’ disease (GD) and Hashimoto’s thyroiditis (HT) are the principal clinical presentations of autoimmune thyroid diseases (AITD), characterized by lymphocytic infiltration of the thyroid parenchyma, and clinically by thyrotoxicosis and hypothyroidism, respectively. AITD lead to an immune attack on the thyroid, whose mechanisms are still unclear. Genetic susceptibility and environmental triggers interact as the principal active part toward the development of the disease.Autoimmune thyroid diseases prevalence is about 5% , 2 whileAutoimmune thyroid diseases commonly affect more frequently females than males, such as in many other autoimmune diseases .This is probably due to differences between male and female immune systems , which aIn females, the immunological changes during pregnancy and their regression in the postpartum period are determinant, even if the predisposition of females to AITD is observed in nulliparous women, too. Microchimerism  is an endogenous factor associated with AITD .Antithyroid antibodies frequency has a peak around 45–55 years, and hypothyroidism due to HT is more frequent in advanced age.The HT prevalence and that of ATAs differ among races –10.per se  in siblings of AITD patients) . The conAmong genes linked to AITD and/or the presence of ATA , 16, whoEnvironmental factors influence the occurrence of AITD of approximately 20%, as they are associated with the activation of innate immune response and AITD development in susceptible individuals , 18.The prevalence of ATA increased in children and adolescents exposed to radiations about 6–8 years after the Chernobyl accident. Thyroid peroxidase antibodies (TPOAb) prevalence was higher in radiation-exposed Belarusian children (6.4 versus 2.4% in not exposed) and in adolescents exposed to radioactive fallout 13–15 years after the Chernobyl accident . The radIodine is essential for thyroid function. Constant iodine prophylaxis and increased iodine intake gradually reduce iodine deficiency-related thyroid disorders . In the P < 0.001). Elevated circulating selenium level was associated with reduced odds ratio  of subclinical hypothyroidism , hypothyroidism , AT , and enlarged thyroid   .l-selenomethionine treatment. The authors concluded that the short-term l-selenomethionine supplementation has a restricted impact on the natural course in euthyroid HT.A paper  evaluateThe data about the effect of smoking on ATA (TgAb and TPOAb) and chronic AT , 33 are A meta-analysis reported the association of smoking with HT and postpartum thyroid dysfunction . By contOn the whole, smoking decreases the risk of appearance of TPOAb and TgAb and autoimmune hypothyroidism of approximately 40%; this protective effect disappears few years after cessation. It has been suggested that while activating nicotine receptors on immune cells, the autoimmune profile moves away from Th1 and Th17 responses , 43.The proportion of smoking people was more elevated in patients with severe ophthalmopathy (64.2% in GO and 47.9% in GD versus 30% in control subjects) , 44–47. Viruses activate the adaptive and innate immunity and might cause HT. Human T-cell lymphotropic virus-1, herpes simplex virus, rubella, mumps virus, Epstein–Barr virus, enterovirus in HT, retroviruses  in GD have been shown . AcquireP < 0.03), suggesting that acute EVB19 infection could be associated with the appearance of AT , particularly in papillary TC (PTC), leading to hypothesize that EVB19 is implicated in thyroid carcinogenesis . In anotin situ hybridization  . AmiodarAs intestinal dysbiosis occurs, the epithelial barrier fails to function and there is the appearance of intestinal and systemic disorders. The intestinal tract is determinant in metabolizing nutrients, drugs, and hormones, exogenous and endogenous iodothyronines, and micronutrients implicated in thyroid homeostasis. Different autoimmune disorders have a pathogenetic link with dysbiosis, not yet clarified in AITD. It has been hypothesized that intestinal dysbiosis may cause AT. Hyper- and hypothyroidism, frequently in AITD, are associated with bacterial overgrowth in small intestinal or with changes in composition of microbiota .BsmI and TaqI polymorphism) or environmental factors (lack of dietary uptake and sun exposure) (Vitamin D is responsible for anti-inflammatory and immunoregulatory effects . Differexposure) . A studyxposure) , 109.Long-term human studies on the effects of environmental chemicals on thyroid-related outcomes such as growth and development are still lacking. The human exposure scenario with lifelong exposure to a vast mixture of chemicals in low doses and the large physiological variation in thyroid hormone levels between individuals render human studies very difficult. Polychlorinated biphenyls (PCBs) have thyroid-disrupting effects, and it is suggested that also bisphenol A, phthalates, brominated flame retardants, and perfluorinated chemicals show thyroid-disrupting characteristics , 111. PCCadmium (Cd) is considered a category I carcinogen . Cd accumulates in liver, pancreas, kidneys, and also in the thyroid. Cd in blood correlates with concentrations in the thyroid. Cd blood and urine levels are more elevated in women in fertile age, than in men. Mitochondria are the main intracellular targets for Cd. In chronic Cd toxicity, multinodular goiter, thyroglobulin hyposecretion, and parafollicular cell hyperplasia are frequent .Manganese (Mn) is toxic at high levels. Oxidoreductases, transferases, hydrolases, lyases, isomerases, ligases, glutamine synthetase, and Mn superoxide dismutase are Mn-containing enzymes. Mn superoxide dismutase is the main antioxidant enzyme able to neutralize the toxic effects of reactive oxygen species. Environmental or occupational exposure to high levels of Mn causes a neuropathy similar to idiopathic Parkinson’s disease, known as manganism. Dopamine and its metabolites are altered in manganism and Parkinson’s disease, as they are able to inhibit TSH secretion. Dopamine and dopaminergic receptors are involved in neurodevelopment and TSH modulation. This suggests that excessive Mn exposure during gestation is linked to altered neurodevelopmental outcomes, due to a dysregulation of dopaminergic control of TSH on thyroid hormones levels .via the food chain, biocontaminate the residents as documented by high levels in the urines and the scalp hair compared to individuals living in adjacent non-volcanic areas. Trace amounts of metals are essential nutrients but, at higher concentrations, can be toxic for living cells. Metals can behave both as endocrine disruptors, perturbing the hormonal system, and as carcinogens, promoting malignant transformation. Similar to other carcinogens, the transforming effect of heavy metals is higher in developing organisms, such as the fetus (contaminated via the mother), and individuals in early childhood. The metal concentration in tissues has been rarely measured in the thyroid (Thyroid cancer incidence is markedly increased in volcanic areas. In the volcanic area of Mt. Etna in Sicily, a non-anthropogenic pollution with heavy metals has been documented, a consequence of gas, ash, and lava emission. Soil, water, and atmosphere contamination,  thyroid .Although the genetic background accounts for approximately 70% of the risk for developing AITD, environmental triggers have an important role in the AITD development in susceptible individuals. Radiation exposure, and increased iodine intake, selenium, and vitamin D deficiency are environmental factors increasing the AITD risk. GO and GD are associated with cigarette smoke , 118, whFSM, FP, AA, and BS gave substantial contribution in the conception and design of the work, and in writing the paper; gave the final approval of the version to be published; agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. AA and BS revised it critically for important intellectual content.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.


The behavior of L divided by the stiffness parameter A Monte Carlo study of the mean-square radius of gyration  SpecifiM is not very large [Considering the fact that for (semiflexible) circular DNA, the configurations not only of the trivial knot but also of non-trivial knots are visualized by electron microscopy ,13, and notation ,23), whiN junction points connected by N bonds of length b. Let ith bond vector from the ith point to the Nth bond vector U of the ring has been given in terms of the angle N) between β the reciprocal of the product of the Boltzmann constant T [The present MC model and method are the same as those in the previous studies ,8,9—i.e. follows ,10,11, instead of It is seen from Equation  that λ−1Equation , we makeN-sided regular polygon of side length b—which is the most stable configuration—and sequentially deform it by the virtual motion introduced by Deutsch [v be the unit vector along the vector distance between a pair of joints randomly chosen under the condition that they not be next to each other. If the ith and jth joints  is the angle between N. An ensemble of U, which we call the mixed ensemble.Then, the adoption of the next trial configuration sampling  on the bFollowing the procedure of Vologodskii et al.  and of tiioannou . Howeveriioannou . Furtherk of the scattering vector are evaluated. The quantity ith junction point, given byN identical isotropic point scatterers at each junction, ith and jth junction points.Now, by the use of the trefoil-knot ensemble, the mean-square radius of gyration N: N with In practice, MC simulations have been carried out for the discrete KP rings of ishimura  has beenN.The ratio  Deguchi  are alsoemselves ,17 usingemselves  of degreN are also plotted against For comparison, the ratio  of Ref.  and thos of Ref. , respectus study . The impFor small .=π2/βλL . AdditioIn Equation , and thoEquation  with EquEquation  are plotN.The mean-square radius of gyration Equation  with EquEquation . The val of Ref.  1.2 . Consideis limit ,34, therk of the scattering vector. The function Finally, we give the results for the scattering function Equation  for the =Lk2P(k) . The sol of Ref. . The ploian ring .k being the magnitude of the scattering vector have been evaluated for the KP ring of the trefoil knot by MC simulations. The behavior of L measured in units of the stiffness parameter The mean-square radius of gyration The double-logarithmic plots of M  excluded-volume effects on semiflexible ring polymers. Even for semiflexible polymers, the excluded volume effects become remarkable if ) scheme . In thisprevious ,8,9 studprevious . The str


In a ferric chloride injury model of the carotid artery, GF C57BL/6J mice had increased occlusion times compared to colonized controls. Interestingly, in late atherosclerosis, HFD-fed GF  −/−Ldlr) mice as germfree (GF) and kept these mice for 16 weeks on an atherogenic high-fat Western diet (HFD) under GF isolator conditions and under conventionally raised specific-pathogen-free conditions (CONV-R). In spite of reduced diversity of the cecal gut microbiome, caused by atherogenic HFD, GF −/−Ldlr mice and CONV-R −/−Ldlr mice exhibited atherosclerotic lesions of comparable sizes in the common carotid artery. In contrast to HFD-fed mice, showing no difference in total cholesterol levels, CONV-R −/−Ldlr mice fed control diet (CD) had significantly reduced total plasma cholesterol, very-low-density lipoprotein (VLDL), and LDL levels compared with GF −/−Ldlr mice. Myeloid cell counts in blood as well as leukocyte adhesion to the vessel wall at the common carotid artery of GF −/−Ldlr mice on HFD were diminished compared to CONV-R −/−Ldlr controls. Plasma cytokine profiling revealed reduced levels of the proinflammatory chemokines CCL7 and CXCL1 in GF −/−Ldlr mice, whereas the T-cell-related interleukin 9 (IL-9) and IL-27 were elevated. In the atherothrombosis model of ultrasound-induced rupture of the common carotid artery plaque, thrombus area was significantly reduced in GF −/−Ldlr mice relative to CONV-R −/−Ldlr mice. Ex vivo, this atherothrombotic phenotype was explained by decreased adhesion-dependent platelet activation and thrombus growth of HFD-fed GF −/−Ldlr mice on type III collagen.Atherosclerotic plaque development depends on chronic inflammation of the arterial wall. A dysbiotic gut microbiota can cause low-grade inflammation, and microbiota composition was linked to cardiovascular disease risk. However, the role of this environmental factor in atherothrombosis remains undefined. To analyze the impact of gut microbiota on atherothrombosis, we rederived low-density lipoprotein receptor-deficient ( Atherosclerosis, a major burden of Western lifestyle-associated diseases, is a chronic inflammatory process of the vessel wall arising at sites of disturbed blood flow. The development of atherosclerotic plaques depends on hypercholesterolemia and has been linked to low-grade inflammation-triggered by innate immune signaling . In addi2–6–−/−Apoe) mouse model, lacking the Toll-like receptor (TLR) adaptor protein Myeloid differentiation primary response 88 (MyD88), a reduction in lesion size was noted (Tlr2)-deficient hypercholesterolemic −/−Ldlr mice were shown to have only minimal lesions compared with wild-type (WT) −/−Ldlr controls , did not show an altered lipid profile and had similar levels of aortic cholesterol esters and aortic root plaque size compared to their conventionally raised (CONV-R) controls  or a high-fat Western diet (HFD) for 16 weeks, respectively. Our results demonstrate that the commensal microbiota reduced plasma cholesterol levels in CD-fed −/−Ldlr mice, but not in HFD-fed −/−Ldlr mice. The presence of the microbiota in HFD-fed −/−Ldlr mice did not affect late atherosclerotic lesion size at the carotid artery but increased myeloid blood cell counts and platelet deposition to collagen coatings, associated with increased thrombus growth in the carotid artery following ultrasound-induced plaque rupture.The possible contribution of commensal microbiota to Western diet-induced carotid artery atherosclerosis and plaque thrombogenicity in the −/−Ldlr mice are a well-established model of familial hypercholesterolemia, characterized by 2-fold higher plasma cholesterol levels compared to WT controls on a normal CD  control. Download FIG S1, PDF file, 0.03 MB.Sterility controls on the feces from GF Copyright © 2019 Kiouptsi et al.2019Kiouptsi et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the −/−Ldlr littermates on CD with mice that at the same age were fed with an atherogenic HFD for 16 weeks. We noted vast changes in diversity between the groups (beta-diversity)  . In CONVecreased . Generalecreased  and D. Fntestine , was signtestine . Collect10.1128/mBio.02298-19.2FIG S2FIG S2, PDF file, 0.2 MB.Taxon summary on the genus level. Download Copyright © 2019 Kiouptsi et al.2019Kiouptsi et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mBio.02298-19.7TABLE S1Table S1, PDF file, 0.03 MB.Differences in microbial taxa between HFD and CD mice. Download Copyright © 2019 Kiouptsi et al.2019Kiouptsi et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the −/−Apoe mice  particles. Intriguingly, this microbiota-dependent effect on the plasma cholesterol levels and the lipoprotein profile was abolished when the −/−Ldlr mice were fed atherogenic HFD for 16 weeks  Representative ultrasound B-images of the carotid arteries of HFD mice. (B) Measurement of the wall thickness of the anterior carotid wall from the right (RCC) and left common carotid (LCC) arteries. (C) Cumulative atherosclerotic plaque size of RCC (right) and LCC (left) in B-mode. Mean plus SEM (error bars) are shown for the groups (2 to 5 mice per group). For panels B and C, CONV-R mice are shown by gray bars, and GF animals are shown in white bars. Independent samples were tested by Student Copyright © 2019 Kiouptsi et al.2019Kiouptsi et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mBio.02298-19.8TABLE S22) and relative (%) values for atherosclerotic plaque area at the carotid artery and aortic root (zero-level) of the 40 CONV-R (gray) and GF (white) animals fed for 16 weeks with HFD. Animals are color coded as in Table S2, PDF file, 0.04 MB.Absolute  with group assignment and sex as factors and age as covariate. The effect of age was statistically significant  = 7.002, P = 0.0125). However, there was no significant difference between male and female animals  = 0.48, P = 0.493) and between CONV-R and GF mice  = 1.41, P = 0.244) even after adjusting for the effect of age. In conclusion, the age of −/−Ldlr mice influenced relative plaque size, but the GF housing condition had no significant influence on late atherosclerotic lesion size in the carotid artery after 16 weeks of HFD feeding.To investigate whether age significantly impacts atherosclerotic lesion size of the e values  and E. I−/−Ldlr mice on HFD relative to CONV-R controls. Feeding on a HFD for 16 weeks increased white blood cell counts in CONV-R −/−Ldlr mice relative to GF −/−Ldlr mice about 2-fold    and C. I−/− mice . In cont−/− mice . In linecontrols . Thus, o3) injury model of the common carotid artery, GF C57BL/6J mice kept on a CD also showed reduced thrombus growth compared to CONV-R C57BL/6J controls, as shown by significantly prolonged occlusion times (846.7 ± 54.5 s in GF mice relative to 635.1 ± 43.8 s in CONV-R mice)  . Likewisin vivo, we applied an established ultrasound-induced plaque rupture model of the carotid artery plaque, resulting in local collagen exposure -positive surface area coverage on type I and type III collagen compared to the blood of HFD-fed CONV-R −/−Ldlr mice (IIbβ3) was decreased on type III collagen in platelets from GF −/−Ldlr mice compared to CONV-R −/−Ldlr mice when fed CD  compared to CONV-R −/−Ldlr mice (12 mice/group). The degree of reduction relative to CONV-R −/−Ldlr mice is indicated in green. The numbers below the panels indicate the following parameters: 1, morphological score; 2, platelet surface area coverage; 3, thrombus contraction score; 4, multilayer score; 5, thrombus surface area coverage; 6, phosphatidylserine exposure; 7, P-selectin expression; 8, integrin αIIbβ3 (GPIIbIIIa) activation. Independent samples were tested by Student t tests. *, P < 0.05. (B and C) End-stage representative images of whole-blood platelet deposits after 3.5 min on collagen type I (B) and collagen type III (C). Download FIG S4, PDF file, 0.7 MB.(A) Standardized whole-blood flow chamber analysis for platelet deposition on collagen type I and collagen type III. (A) Subtraction heatmap of control diet (CD)-fed GF Copyright © 2019 Kiouptsi et al.2019Kiouptsi et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mBio.02298-19.5FIG S5−/−Ldlr and CONV-R −/−Ldlr mice on collagen type I and collagen type III. Means ± SEM are shown for groups. For all the panels, CONV-R animals are shown as black dots, while GF animals are shown as white dots. Download FIG S5, PDF file, 0.1 MB.Descriptive statistics on the standardized whole-blood flow chamber analysis for platelet deposition of HFD-fed GF Copyright © 2019 Kiouptsi et al.2019Kiouptsi et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mBio.02298-19.6FIG S6−/−Ldlr and CONV-R −/−Ldlr mice on collagen type I and collagen type III. Means ± SEM are shown. Independent samples were tested by Student t tests. **, P < 0.01. For all the panels, CONV-R animals are shown as black triangles, while GF animals are shown as white triangles. Download FIG S6, PDF file, 0.1 MB.Descriptive statistics on the standardized whole-blood flow chamber analysis for platelet deposition of CD-fed (control diet fed) GF Copyright © 2019 Kiouptsi et al.2019Kiouptsi et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the −/−Ldlr mice atherogenic HFD for 16 weeks resulted in a significantly reduced diversity of the cecal gut microbiota compared to feeding mice CD. In accordance with previous reports, this resulted in a decrease of the Bacteroidetes phylum and an increase in Firmicutes in the HFD group compared with littermate controls kept on a CD   , but the−/−Ldlr mice compared with their HFD-fed CONV-R −/−Ldlr counterparts, pointing to a stimulatory effect of the gut microbiota on experimental atherothrombosis. This finding expands on previous work from our laboratory, demonstrating that the presence of commensals promotes arterial thrombus growth in the ligation-injured carotid artery   , 48, a cI (GPVI) –51. Sinc−/−Apoe mouse model  (−/−Ldlr mice were rederived as germfree (GF) by aseptic hysterectomy and maintained as a GF mouse colony in sterile flexible film mouse isolator systems. The germfree status of mice was tested weekly by PCR for detection of 16S rDNA and by bacterial culture. All experimental animals were 9- to 29-week-old male or female mice housed in the Translational Animal Research Center (TARC) of the University Medical Center Mainz under specific-pathogen-free  or GF conditions in EU type II cages with two to five cage companions with standard autoclaved lab diet and water ad libitum, 22°C ± 2°C room temperature, and a 12-h light/dark cycle. All groups of mice were sex and age matched, and all mice were free of clinical symptoms. All procedures performed on mice were approved by the local committee on legislation on protection of animals .B6.129S7Ldlrtm1Her/J mice (/− mice)  were pur−/−Ldlr mice were fed 16 weeks with an adjusted calories diet  that had been vacuum packaged, irradiated, and microbial analyzed . Control mice were kept on an autoclaved control diet .http://www.wernerlab.org/software/macqiime)  correction . Linear discriminant analysis (LDA) effect size (LEfSe) was performed using the online tool available at http://huttenhower.sph.harvard.edu/galaxy/.MiSeq 16S amplicon V4-V5 sequence data were analyzed using MacQIIME v1.9.1 (acqiime)  as descracqiime) , 55. BriPlasma samples were subjected to fast-performance liquid chromatography . Different lipoprotein fractions were separated and evaluated based on flowthrough time. Cholesterol levels were quantified using an enzymatic assay  according to the manufacturer’s protocol.Lesion development in the left common carotid artery was quantified by hematoxylin-and-eosin (H&E) staining of 4-μm longitudinal cryosections.EDTA anticoagulated mouse whole blood was collected from anesthetized mice , by intracardial puncture. Platelet and total and differential white blood cell counts were determined using an automatic cell counter .g, and cell pellets were subsequently stained with different antibody cocktails for analysis by flow cytometry. Flow cytometry was conducted with a FACS Canto II, using FACSDiva software (BD Biosciences). Cell populations were discriminated by the following antibody cocktail: anti-CD45 , anti-CD115 , anti-Gr1 , anti-CD11b , anti-B220 , and anti-CD3 . Cell populations and marker expression were gated using the FlowJo analysis program (Treestar): leukocytes (CD45+), neutrophils (CD45+ CD115-Gr1high), monocytes (CD45+ CD11b+ CD115+), and lymphocytes (CD45+ CD3+ and CD45+ B220+).Whole blood was collected in an EDTA-buffered tube, subjected to red blood cell lysis, and centrifuged for 5 min at 300 × Cytokine levels in mouse plasma samples were measured using the ProcartaPlex Multiplex Immunoassay technology from Affymetrix , according to the manufacturer’s protocol.3 platelets/μl, and 250 μl of suspension was injected via a jugular vein catheter. Thrombus formation of murine platelets was assessed by high-speed epifluorescence microscopy 10 min after plaque rupture. To characterize leukocyte adhesion and rolling in vivo, leukocytes stained with acridine orange  were imaged.Mice were anesthetized by intraperitoneal injection of a solution of midazolame (5 mg/kg body weight), medetomidine (0.5 mg/kg body weight), and fentanyl (0.05 mg/kg body weight). Citrated whole blood was collected by intracardial puncture. Murine platelets were isolated and labeled with Rhodamin B (20 μg/ml). The labeled platelet suspension was adjusted to a final concentration of 150 × 10−/−Ldlr mice were fed high-fat diet with 42% from fat for 16 weeks. After the mice were anesthetized by intraperitoneal injection of a solution of midazolame , medetomidine , and fentanyl , a polyethylene catheter  was implanted into the right jugular vein, and the right carotid artery was dissected free from surrounding tissue. The animal was injected intravenously with Rhodamin B-labeled platelets obtained from a donor mouse with the same genetic background, hygiene status, and feeding procedure. A subset of mice were also injected with acridine orange for leukocyte staining.Plaque rupture and measurement of acute thrombus formation were performed as described earlier . Ldlr−/−2 filter paper that was soaked with 10% (wt/wt) FeCl3 solution for 3 min laterally to the common carotid artery  , 34. Mea2, 0.42 mM NaH2PO4) containing 1% bovine serum albumin (BSA) and mounted in parallel plate flow chambers.Experiments were performed as described previously  with min−1, over the microspot coatings. The platelets were stained by 2 min after perfusion with Tyrode’s HEPES buffer (pH 7.45) , supplemented with fluorescein isothiocyanate (FITC)-labeled rat anti-mouse CD62P monoclonal antibody (MAb) (1:40) , phycoerythrin (PE)-labeled rat anti-mouse JON/A MAb (1:20) , and Alexa Fluor 647 (AF647)-labeled annexin A5 (1:200) . Representative end-stage bright-field microscopic images were taken from each microspot during staining. After 2 min of stasis, remaining labels were washed away by perfusion with label-free Tyrode’s HEPES buffer, after which three representative end-stage fluorescence images were collected per microspot.Blood samples were collected by retro-orbital puncture of mice under isoflurane anesthesia into 40 μM PPACK, 5 U/ml heparin, and 50 U/ml fragmin  and perfused for 3.5 min, at a wall shear rate of 1,000 sMicroscopic images  were recorded with an EVOS fluorescence microscope , equipped with green fluorescent protein (GFP), red fluorescent protein (RFP), and Cy5 light-emitting diode (LED) cubes, and an Olympus 60× oil immersion objective, basically as described previously . RecordeP < 0.05  after correction for multiple comparisons, where required. Subtraction heatmaps were produced by using the R package version 3.2.5 (www.r-project.org).For each flow run, parameter values from individual bright-field and fluorescence images were averaged to obtain one value per parameter per microspot. These values were linearly normalized to a scale from 0 to 10 per individual parameter. Gene effect heatmaps were obtained by subtracting the normalized average values per parameter of GF mice minus CONV-R mice. Differences compared to CONV-R mice were considered statistically significant with t test to compare two groups and analysis of variance (ANOVA) with Tukey post hoc test for more than two groups.Data are presented as means ± standard errors of the means (SEM). Statistical calculations were performed with GraphPad Prism 5  using the independent samples Student’s https://www.ebi.ac.uk/ena) under the accession numbers ERS2865886 to ERS2865897. The applied commands and the LDA effect size are provided as supplemental material (Sequence files and metadata for all samples used in this study have been deposited in the ENA database (material . Other d10.1128/mBio.02298-19.9TEXT S1TEXT S1, DOCX file, 0.1 MB.Commands. Download Copyright © 2019 Kiouptsi et al.2019Kiouptsi et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the