Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a member of the ATP binding cassette (ABC) transporter superfamily that functions as a cAMP-activated chloride ion channel in fluid-transporting epithelia. There is abundant evidence that CFTR activity  is regulated by protein kinases and phosphatases via phosphorylation and dephosphorylation. Here, we review recent evidence for the role of protein kinases in regulation of CFTR delivery to and retention in the plasma membrane. We review this information in a broader context of regulation of other transporters by protein kinases because the overall functional output of transporters involves the integrated control of both their number at the plasma membrane and their specific activity. While many details of the regulation of intracellular distribution of CFTR and other transporters remain to be elucidated, we hope that this review will motivate research providing new insights into how protein kinases control membrane transport to impact health and disease. CFTR is a member of the ATP-Binding Cassette (ABC) transporter family, that hydrolyzes ATP to pump substrates, such as ions, vitamins, drugs, toxins, and peptides across biological membranes , the most common autosomal recessive disorder among Caucasians. At present, more than 2000 mutations have been identified while 127 are confirmed as disease causing  protein is a polytopic integral membrane protein that functions as a cAMP- and phosphorylation-activated chloride , involved in channel regulation through ATP binding and hydrolysis, and two membrane-spanning domains (MSD), that form the pore of the channel. CFTR, however, is distinct in its structure as it possesses a regulatory (R) domain that contains multiple phosphorylation sites and a large proportion of charged amino acid residues Figure . This diHiggins, .− secretion through CFTR is the sum of the activity of each individual CFTR channel and the number of CFTR molecules present at the apical membrane. CFTR activity depends on the intrinsic structure of the CFTR protein, on several post-translational modifications, including phosphorylation, and on the binding and hydrolysis of ATP at the NBDs. The number of CFTR molecules at the PM results from a balance between anterograde trafficking (through which CFTR is delivered from the ER to the plasma membrane—PM), endocytosis (a process through which CFTR is retrieved from the membrane into vesicles), and recycling . Both, the activity of individual channels and the channel number at the PM are regulated by the interactions of CFTR with multiple protein partners and by post-translational modification  is a ubiquitous, pleiotropic, and constitutively active Ser/Thr protein kinase with a heterotetrameric structure, where the holoenzyme contains two α  subunits offering the potential to simultaneously phosphorylate different substrates. Additionally, CK2 has two β regulatory, polyamine-binding subunits , a green tea flavonoid, prolongs the rescue of F508del-CFTR PM localization by cysteamine . SYK is a cytoplasmic non-receptor tyrosine kinase best known for its pro-inflammatory role in immunoreceptor signaling in leukocytes  was shown to strongly augment ClSuch a role of SYK in regulating protein trafficking has been reported previously for other substrates. SYK can bind through its SH2 domain to the phosphorylated form of the membrane protein TGN38 and this association leads to increased PM expression of TGN38, reinforcing that tyrosine-based motifs may play a broader role in integrating trafficking and signaling events , a rare familial form of hypertension  protein kinases comprises four members, WNK1 through 4 . LMTK2 is a member of the lemur family of membrane-anchored kinases with multiple aliases such as kinase/phosphatase/inhibitor-2 (KPI2), brain-enriched kinase (BREK), apoptosis-associated tyrosine kinase (AATYK2), or cyclin-dependent kinase-5 (cdk5/p35)-regulated kinase, describing different functions and tissue localizations of the protein. Despite the original prediction of a dual-specificity serine-threonine/tyrosine kinase, biochemical studies have shown that purified LMTK2 kinase domain phosphorylates only serine and threonine, but not tyrosine residues (Wang and Brautigan, − secretion by inducing endocytosis and inhibiting PM accumulation of CFTR (Luz et al., The site for CFTR phosphorylation by LMTK2 is the inhibitory PKA/AMPK-site S737 (Wang and Brautigan, It remains unknown whether LMTK2 phosphorylation of CFTR-S737 may also inhibit CFTR channel function in addition to reducing the PM density of CFTR. Furthermore, the effects of AMPK- and PKA-mediated phosphorylation of CFTR-S737 on the PM CFTR abundance are unknown. Hence, it remains to be determined whether the phospho-dependent inhibitory effects on CFTR-S737 are differentially mediated by each of the three kinases, PKA, AMPK, and LMTK2 (Figure − secretion at least in part by attenuating the PM abundance of CFTR channels; however, the mechanism through which LMTK2 activity is regulated at the apical PM in HBE cells is unknown (Luz et al., LMTK2 likely plays a physiologically relevant role in regulating the inhibitory CFTR-S737 site in HBE cells because, similar to mutagenesis of the S737 site, LMTK2 knockdown produced a two-fold increase in the PM abundance of wt-CFTR and a three-fold decrease in CFTR endocytosis. When compared to the LMTK2 knockdown, the kinase-dead LMTK2 fragment produced lesser effect on the PM abundance and endocytosis of CFTR, possibly because endogenous LMTK2 diminished the effects of the kinase deficient fragment when compared to LMTK2 knockdown (Luz et al., − secretion in cells expressing wt-CFTR (Luz et al., LMTK2 knockdown increased CFTR mediated ClIn summary, published data support a model whereby phosphorylation of S737 by PKA or AMPK closes CFTR channels, while phosphorylation of S737 by LMTK2 reduces the PM density of CFTR. More research is needed to determine the specific contribution of the kinases to regulation of CFTR function in different tissues and under different physiological and disease states. Because rescued F508del-CFTR has decreased PM stability, targeting LMTK2 phosphorylation of CFTR may offer a novel approach to investigate the stability defect and to design pharmacological approaches to stabilize rescued F508del-CFTR. These findings may also point to a new direction in elucidating the mechanisms of decreased CFTR function in lung diseases resulting from cigarette smoke inhalation.CFTR processing, trafficking, and activation are regulated by multiple protein-protein interactions. While interactions resulting in phosphorylation at the CFTR R domain regulate channel opening, other interactions at the CFTR termini modulate CFTR stability at the PM. For example, syntaxins interact with the CFTR N-terminal tail and PDZ-proteins bind to the PDZ-interacting domain at the CFTR C-terminal tail. The multiprotein scaffolds anchor CFTR to the cytoskeleton and allow CFTR to regulate other channels. Recent evidence, reviewed here, has identified novel protein partners, including the kinases CK2, SYK, WNK4, and LMTK2 regulating the biogenesis, turnover, and trafficking of CFTR. Such evidence increases our understanding of the complex CFTR interactome and points to novel directions in search of additional therapeutic targets to rescue F508del-CFTR and to increase the efficiency of current generation CFTR modulators.CF, AS, DB, and PJ discussed and wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Angiotensin II (AII) type 2 receptor (AT2R) negatively regulates type 1 receptor (AT1R) signaling. However, the precise molecular mechanism of AT2R-mediated AT1R inhibition remains poorly understood. Here, we characterized the local and functional interaction of AT2R with AT1R. AT2R colocalized and formed a complex with AT1R at the plasma membrane, even in the absence of AII. Upon AII stimulation, the spatial arrangement of the complex was modulated, as confirmed by Förster resonance energy transfer (FRET) analysis, followed by AT2R internalization along with AT1R. AT2R internalization was specifically observed only in the presence of AT1R; AT2R alone could not be internalized. The AT1R-specific inhibitor losartan completely inhibited both the conformational change and the internalization of AT2R with AT1R, whereas the AT2R-specific inhibitor PD123319 partially hindered these phenomena, demonstrating that the activation of both receptors was indispensable for these effects. In addition, treatment with the protein kinase C (PKC) inhibitors inhibited the ligand-dependent accumulation of AT2R but not that of AT1R in the endosomes. A mutation in the putative phosphorylation sites of AT2R also abrogated the co-internalization of ATR2 with AT1R and the inhibitory effect of ATR2 on AT1R. These data suggest that AT2R inhibits ligand-induced AT1R signaling through the PKC-dependent pathway. Angiotensin II (AII) is a pleiotropic peptide hormone with crucial roles in the development of cardiovascular diseases, including hypertension, atherosclerosis, and heart failure11124AT2R expression in adults is restricted to a few tissues, including the brain and the uterus7in vitro and in vivo. The receptor complex was internalized by endocytosis in a manner dependent on the activities of AT1R, AT2R, and PKC. We also revealed that such internalization was associated with alterations in the relative orientations of AT1R and AT2R, in which their C termini were brought in close proximity to each other, by Förster resonance energy transfer (FRET) analysis. These findings shed light on the previously unknown molecular mechanisms of AT2R-mediated inhibition of ligand-induced AT1R activation.Here, we utilized fluorescent protein-tagged AT1R and AT2R to identify a more physiologically relevant relationship between AT1R and AT2R and found that AT2R interacts with AT1R both As AT2R signaling has been reported to counteract AT1R-dependent signaling124We next investigated the selectivity of the AT2R-dependent attenuation of ERK activation. Treatment with the EGFR inhibitor AG1478 produced no inhibitory effects on AII-AT1R-dependent ERK activation , showingper se did not correlate with that of ERK activation shown in According to the results shown in 9Because AT1R has been well documented to accumulate in the endosome upon AII stimulation1212FRET analysis is a powerful tool for studying molecular interactions in a living cell. Thus, we further analyzed FRET data for CFP-tagged AT2R and YFP-tagged AT1R. Whereas only a weak FRET signal was detected in quiescent cells , the sigTo further clarify the relationship between AT1R and AT2R, we next examined the effects of receptor antagonists on the AII-induced association of the receptors. Treatment with losartan, an AT1R inhibitor, completely abolished the FRET signal between the two receptors as well as the internalization of both receptors , indicatBecause PKC is a well-known downstream effector of AT1R2Finally, we evaluated the effect of PKC on the AT2R-mediated inhibition of AT1R signaling. However, the utilization of PKC inhibitors might not be suitable because PKC is reported to mediate AT1R-dependent ERK activationAT1R activates many downstream effectors, including ERK, which is reported to be a major regulator of AII-induced cardiovascular diseasesin vivo. Treatment with the AT2R inhibitor PD123319 enhances the AII responsiveness in the rat thoracic aorta after pressure overloadAt2r (AT2R-KO), which develop normal blood pressure in the resting state, display enhanced vasoconstriction after AII injectionIn general, it is widely accepted that AII counteracts AT1R-mediated vasoconstriction One possible mechanism for such cell type-specific AT1R signaling inhibition by AT2R might be ascribed to the relative expression of the receptors. In most adult tissues, AT2R levels, which are much lower than AT1R levels under physiological conditions, are increased upon exposure to environmental cues that activate AII-AT1R signaling66As we clearly demonstrated, AT2R accumulated with AT1R in the endosomes after AII stimulation. In a previous report, the uptake of AT2R was shown to occur only in the presence of promyelocytic leukemia zinc finger protein (PLZF)PKC is a crucial downstream effector of the AT1R signaling pathway. Paradoxically, PKC has been reported to be indispensable for AT1R endocytosisEcoRI and NotI sites of the pCXN2-YFPC and pCXN2-CFPC vectors, respectivelyEcoRI and NotI sites of pCXN2-CFPC vectors. cDNA for Entacmaea quadricolor eqFP650 (TurboFP650)Rattus ERK2 cDNA was amplified by PCR using the following primers: ERK2 forward primer, 5′-GGCTCGAGATGGCGGCGGCGGCGGCGGCG-3′; ERK2 reverse primer, 5′-CCGCGGCCGCTTAAGATCTGTATCCTGGC-3′. The resulting PCR product was subcloned into the XhoI and NotI sites of the pFX-eqFP650 vector to obtain pFX-eqFP650-ERK2. All constructs were confirmed by sequencing analysis.Human AT1R and AT2R cDNAs were obtained by conducting RT-PCR of the total RNA from human umbilical vein endothelial cells using the following primers: AT1R forward primer, 5′-CCGAATTCACCATGTACCCATACGATGTTCCAGATTACGCTATTCTCAACTCTTCTACTGAAG-3′; AT1R reverse primer, 5′-CCAGATCTCTACAGATCCTCTTCAGAGATGAGTTTCTGCTCGCGGCCGCACTCAACCTCAAAACATGGTG-3′; AT2R forward primer, 5′-CCGAATTCACCATGGACTACAAAGACGATGACGACAAGAAGGGCAACTCCACCCTTGC-3′; and AT2R reverse primer, 5′-CCAGATCTCTACAGATCCTCTTCAGAGATGAGTTTCTGCTCGCGGCCGCAAGACACAAAGGTCTCCATTTC-3′. These primers were designed for the insertion of HA- and FLAG-tags after the initial methionine, as previously describedAII, LPA, and PD123319 were obtained from Sigma . EGF and losartan were purchased from PeproTech  and LKT Laboratories , respectively, and staurosporine and AG1478 were purchased from Calbiochem . Hoechst 33342 and Gö6983 were obtained from Invitrogen  and Cayman Chemical , respectively. Antibodies against FLAG and HA were purchased from Stratagene  and Roche , respectively, and antibodies against ERK1/2 and phospho-ERK1/2 were purchased from Cell Signaling Technology . A series of antibodies against phosphorylated serine and threonine (Phosphoserine detection set and Phosphothreonine detection set) were obtained from Enzo Life Sciences .HeLa cells were cultured in Dulbecco’s modified Eagle’s medium  supplemented with 10% FBS. Expression plasmids were introduced into cells with FuGENE HD (Roche), according to the manufacturer’s protocol.2, 3 mM EGTA, 0.1 mM Na3VO4, 20 mM NaF and complete EDTA-free protease inhibitor ] for 20 min on ice and clarified by microcentrifugation. Supernatants were subjected to SDS-PAGE, and the separated proteins were transferred to polyvinylidene difluoride membranes . The membrane was incubated with a primary antibody followed by a peroxidase-labeled secondary antibody. Signals were developed by ECL Western Blotting Detection Reagent  and detected using an LAS-1000 UV mini image analyzer . The intensities of the bands were quantitated using the associated software. Note that samples were incubated with SDS sample buffer at 50 °C but were not boiled to detect AT1R and AT2R while preventing their aggregation.Immunoblotting was performed as previously described, with some modifications3VO4, and complete EDTA-free protease inhibitor (Roche)] and precipitated with an anti-FLAG antibody with protein A-Sepharose beads. Proteins bound to the beads were separated by SDS-PAGE and detected by immunoblotting.HeLa cells expressing HA-AT1R-YFP and Flag-AT2R-CFP were lysed in NP-40 lysis buffer [10 mM Tris-HCl, pH 7.4, 150 mM NaCl, 5 mM EDTA, 0.5% NP-40, 10% glycerol, 1 mM NaC) was calculated on a pixel-by-pixel basis for the entire image by using the following equation: FRETC = FRET-(0.5 × CFP)-(0.02 × YFP), where FRET, YFP, and CFP correspond to the background-subtracted images of cells co-expressing CFP and YFP acquired through the FRET, YFP, and CFP channels, respectively. The bleed-through fractions of CFP and YFP fluorescence were 0.5 and 0.02, respectively, through the FRET channel. FRETC images are presented in pseudocolor mode. A mask image for the entire cell was created based on the YFP fluorescence intensity, and FRETC values in the region were quantitated using MetaMorph software.Intermolecular FRET analysis was performed as previously described34Fluorescence images of eqFP650-ERK and Hoechst-stained nuclei were acquired as described above, except different filter sets were used . A mask image for the nuclear region was created based on the Hoechst fluorescence intensity, and the fluorescence intensities of eqFP650-ERK in the nucleus and the entire cell were quantitated to measure ERK activity.How to cite this article: Inuzuka, T. et al. Attenuation of ligand-induced activation of angiotensin II type 1 receptor signaling by the type 2 receptor via protein kinase C. Sci. Rep.6, 21613; doi: 10.1038/srep21613 (2016).


In this article, the octahedral interstitial model was re-examined in terms of the interstitial occupancy and X-ray Raman spectroscopy (XRS) spectra. The interstitial occupancy calculated using first-principles molecular dynamics simulations was negligibly small compared to that of the interstitial model. The oxygen K-edge spectra calculated for the interstitial model exhibited two additional low-energy peaks originating from water molecules and hydroxides that are interacting with interstitial protons, respectively, whereas these low-energy peaks were not observed in the experimentally measured spectra. These results suggest that the interstitial model cannot explain the XRS spectra of ice VII at pressures above 13 GPa and that more precise structure measurements and analyses are necessary to reveal the nature of the pressure-induced transition.The neutron diffraction pattern of D Water is a simple molecule consisting of two hydrogen atoms and one oxygen atom. However, water exhibits an extremely complex phase diagram that includes more than fifteen phases. Under compression at room temperature, water transforms at 2.2 GPa from ice VI to ice VII, which consists of two interpenetrating sublattices of water molecules forming a bcc oxygen lattice and two random hydrogen-bond networks. As the pressure is increased from 2.2 GPa to 60 GPa, the bcc oxygen lattice remains stable, with reduced lattice constants; however, the hydrogen-bond networks evolve from statically random to dynamically random and eventually to the symmetric state. In this process, ice VII exhibits intricate phenomena originating from the complex proton dynamics, and X-ray diffraction provides very little information about these phenomena.Pc = 13 GPa from that of the ice VII structure was reported by Guthrie et al.et al. concluded that some D2O molecules are dissociated at pressures above Pc, and that protonic species begin to localise at the interstitial sites. A new low-frequency Raman band in the metastable region of ice VII has been reportedTc ≈ 100 K, Pc ≈ 14 GPa) as a possible common origin of these anomalies.Although ice VII has been traditionally considered as a single stable phase of water ice, the literature contains several reports on the transition of the structure and properties at approximately 10–20 GPa4Pc, especially the change of the hydrogen position predicted by the octahedral interstitial modelK-edge XAS spectrum, which can be directly compared to the XRS spectrum measured in the dipole limit, was calculated for the ice VII model and the octahedral interstitial model; these spectra were subsequently compared with the experimental XRS spectra.Therefore, scrutinising the nature of the transition at a0, at pressures between 2 GPa and 40 GPa. The molecular dynamics simulations were performed for 100 ps with a time step of 0.1 fs using an NVT ensemble at temperatures of 300 K and 800 K controlled by a Nose-Hoover thermostata0/8 at the centre of the octahedral interstitial sites. The first-principles molecular dynamics simulations were performed using the Vienna ab initio simulation package (VASP) codeFirst, the occupancy of interstitial hydrogen was evaluated using the trajectories generated by first-principles molecular dynamics simulations. The initial structure was the geometrically optimised ice VII model  containiK-edge XAS spectra were calculated using the 2 × 2 × 2 supercell of the ice VII model .Then, the oxygen II model  as well ral site . Both moK-edge for dense ice were measured at the BL12XU beamline of SPring-8, Japan. X-rays with an energy of 9.887 keV were incident on the target loaded into a Be gasket; the X-rays scattered at an angle of 30° were counted using the backscattering analyser operated at the Si (5 5 5) reflection. Nano-polycrystalline diamondsQ is small (Q·r ≪ 1) with respect to the radius r of the core wave function. This condition is satisfied in the present measurement where Q = 2.7 Å−1 and r = 0.069 Å. XRS is more frequently used in high-pressure experiments for light elements than XAS because XRS uses hard X-rays that can easily penetrate the sample cell.Finally, XRS spectra of the oxygen −4 at 300 K and less than 2 × 10−2 even at an elevated temperature of 800 K, implying that no significant water dissociation occurs in the ice in this pressure and temperature range. This result is in contrast to the occupancy of approximately one deuteron/(unit cell) predicted by the interstitial model. Moreover, it was found that the interstitial model is more unstable by 2.0 eV per water molecule in energy compared to the ice VII model.First, the occupancy of the interstitial hydrogen evaluated by the molecular dynamics simulation is shown in K-edge XAS spectra averaged over all oxygen atoms  + C where A = 10000, B = 490 eV and C = 1750 .


The hypothesis of a km-thick ice shelf covering the entire Arctic Ocean during peak glacial conditions was proposed nearly half a century ago. Floating ice shelves preserve few direct traces after their disappearance, making reconstructions difficult. Seafloor imprints of ice shelves should, however, exist where ice grounded along their flow paths. Here we present new evidence of ice-shelf groundings on bathymetric highs in the central Arctic Ocean, resurrecting the concept of an ice shelf extending over the entire central Arctic Ocean during at least one previous ice age. New and previously mapped glacial landforms together reveal flow of a spatially coherent, in some regions >1-km thick, central Arctic Ocean ice shelf dated to marine isotope stage 6 (∼140 ka). Bathymetric highs were likely critical in the ice-shelf development by acting as pinning points where stabilizing ice rises formed, thereby providing sufficient back stress to allow ice shelf thickening. The development of pan-Arctic Ocean ice shelves during peak glacials was proposed in the 1970s, an idea that has been disputed due to lack of evidence. Here, the authors present geophysical mapping data supporting the presence of such an ice shelf during the peak of the penultimate glaciation ∼140–160 ka. In 1888, Sir William Thomson speculated about extensive and thick floating ice, and elaborated on possible effects of isolating Arctic Ocean water masses from the remaining World Ocean3418O record measured in benthic foraminifera4918O variations in benthic foraminifera predicts more ice volume than available sea-level records indicate16O is stored in a huge floating ice shelf that, once melted, has only a minor effect on sea level4918O and geological sea-level records was in addition suggested to be caused mainly by massive Antarctic ice shelvesWhen the ice-shelf theory was developed in the 1970s and 1980s, the climatic implications of a huge floating Arctic Ocean ice shelf and extensive sea ice were addressedSeafloor mapping of the Yermak Plateau off northern Svalbard provided the first evidence of thick glacial ice grounding in the Arctic Ocean1416et al.Here we present new multibeam bathymetry and sub-bottom profiles documenting ice scours and other glacial landforms extending across the central Arctic Ocean that compel us to assess the concept of a coherent ∼1-km thick ice shelf extending over the entire Arctic Ocean. Our new observations from the LR off the Siberian margin, the Arlis Plateau and the continental slope north off Herald Canyon , merged Two sets of highly parallel streamlined submarine landforms cross the southern LR crest at about 81° N 143° E . These fThe Arlis Plateau  was alsoIn addition, the seabed of the Chukchi Borderland is heavily affected by ice grounding142122Sediments deposited atop the ice-grounded surfaces on bathymetric highs in the central Arctic Ocean have been dated using several methods: radiocarbon dating of MIS 3-1 refs , 26, ast2731Emiliania huxleyi in three samples at 1.69–1.72 m.b.s.f.New data for SWERUS-C3 sediment cores from the ice-grounded areas are shown in Polarstern in 1995 (PS2757-8)  . This coS2757-8) . The entE. huxleyi and Gephyrocapsa spp., suggesting a MIS 5 age.On the Arlis Plateau, core SWERUS-L2-13-PC1  of deep ice grounding in the central Arctic Ocean have been discussed since the first evidence was mapped on the central LR and sediment cores from this area were dated146 m3 s-1) of warm (>0 °C) Atlantic water between about 200 and 600 m, would strongly impact negatively on ice-shelf development16While the morphological evidence suggests an Arctic Ocean-wide ice shelf at MIS 6, is such a feature oceanographically possible? The answer to this question lies in the details of the oceanographic conditions at the time. The present influx of >3 Sv  to estimate that a 700±300-m thick ice shelf covering the entire Arctic Ocean would increase the δ18O ocean value by 0.12±0.09‰ (SMOW). It follows that using a δ18O value for shelf ice of −40±10‰ (SMOW), and the estimated MIS 6 ice-shelf volume of 4.67 × 106 km3, the MIS 6 δ18O ocean can be calculated to have increased by 0.14±0.03‰ (SMOW). This difference in calculated δ18O ocean compared with Mix18O value and its relation to global eustatic sea level of that time.Shackleton and OpdykeFinally, we emphasize that our results do not exclude the possibility that large ice shelves developed in the central Arctic Ocean during other glaciations than MIS 6. On the contrary, it seems likely that ice shelves were reoccurring components in most of the Quaternary glaciations considering the land-locked nature of the Arctic Ocean. Furthermore, the difficulty in precisely dating Arctic Ocean sediments leaves a high degree of uncertainty regarding the timing of several glacial landforms in general. However, the development of the large MIS 6 ice shelf may, in part, have been catalysed by the long duration of this glacial stage, where the eccentricity of Earth's orbit during the glacial maximum ∼140 ka caused particularly cold springs and summersIB Oden expedition within the Swedish–Russian–US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) program. The expedition started/ended in Tromsö, Norway, July 5/October 3. Rotation between the two legs was carried out in Barrow, Alaska. The data presented in this work were collected during Leg 2 and outside the Russian Exclusive Economic Zone.The new seafloor mapping data presented in this work were collected during a two-leg 90-day long expedition in 2014 with Swedish IB Oden. This system has a Seatex Seapath 330 unit for integration of GPS navigation, heading and attitude. Sound velocity control was achieved through regular CTD  stations supplemented with XBT (expendable bathythermograph). All data were acquired using Kongsberg Seafloor Information System (SIS) and processed using a combination of the software Caris and Fledermaus-QPS. The processed data were gridded to a horizontal resolution ranging between 15 × 15 and 30 × 30 m. Seafloor morphology was interpreted in the three-dimensional environment of Fledermaus and maps were subsequently produced in the GIS software ArcMap. Sub-bottom profiles were collected using the Kongsberg SBP 120 3° × 3° chirp sonar integrated with the multibeam in IB Oden. The chirp sonar was operated continuously using a 2.5–7-kHz pulse. Any use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the US Government.Bathymetric mapping was carried out using the Kongsberg EM 122  multibeam echosounder hull mounted in Following S≡SA−S here is the salinity difference between inflowing water with salinity SA and the outflowing ice-shelf water with salinity S. The thermodynamic balance of the ice-shelf water layer, which governs the basal melt F, is given bywhere Δc is the heat capacity of sea water, ΔT≡TA−Tf the temperature difference, Tf the freezing temperature at the hydrostatic pressure of the shelf ice base, Q the upward heat flow per unit area through the ice, A the shelf area and L the latent heat of freezing. By combining the thermodynamic relation with where Combining this with the salinity equation yieldswhere we have introducedχSA represents a characteristic salinity difference; ΔT ∼ 2 °C, gives χ ∼ 0.03. We will here consider the limiting case where the conductive heat flux through the ice is small compared with the ocean heat flux, that is, assuming that cΔTM >> QA. This is reasonable for thick shelf ice and with this limit Here, implying that the density difference is given byD is the pressure at the ice-shelf base. Thus the salinity and density difference depends only on the salinity and temperature outside the cavity and the pressure at the shelf base. As Δρ is taken to be known, we can use the results of ref. M and the upper-layer depth H in the cavity. We provide here a short summary of the physical explanation: The turbulence intensity in the ice cavity should be very weak, as there is no wind forcing and presumably weak tidal currents. Thus, it is reasonable to assume that the buoyant layer of the freezing-point water in contact with ice shelf is fairly shallow, having a depth that is small compared with the height of the openings in the LR, typically about 800 m. The widths of the gaps in the ridge are also generally wider than the internal Rossby radius, which should be less than 10 km. In this regime, the outflow in the ridge gaps will be subjected to rotational hydraulic control and a rough upper bound on the volume transport is given by ref. 48where g is the acceleration of gravity, f the Coriolis parameter and ρ0=1,000 kg m−3 a constant reference density. The diapycnal upwelling into the upper layer in the ice cavity is equal to MA, the inflow of water from the outside. We use a simple but physically well-founded representation of MAwhere E is the supply of mixing energy per unit area. Further, when Q is negligible,where F/M ≈ cΔT/L << 1. Thus, to a good approximation M=MA, which yields the following steady-state relations for the upper-layer depth and volume flowTA and the mixing energy supply E. E=10−3 W m−2, a value representative for the present-day Arctic Ocean, and E=10−4 W m−2. Given the absence of wind-generated turbulence in the cavity, the former value is certainly too large. Focusing on the more feasible case with E=10−4 W m−2, one finds that the results are not strongly sensitive to the ambient water temperature.Here, we assume that these relations provide rough upper bounds on the cavity upper layer depth and the exchange flow for given values of the ambient water temperature How to cite this article: Jakobsson, M. et al. Evidence for an ice shelf covering the central Arctic Ocean during the penultimate glaciation. Nat. Commun. 7:10365 doi: 10.1038/ncomms10365 (2016).Supplementary Figures 1-3


I]/iK), an equilibrium binding term that does not distinguish between inhibitor binding and inhibitory effect. Since its initial appearance in the literature, around a century ago, the perceived mechanistic methods used in its production have spurred countless inhibitory equations. These equations are overly complex and are seldom compared to each other, which has destroyed their usefulness resulting in the proliferation and regulatory acceptance of simpler models such as IC50s for drug characterization. However, empirical analysis of inhibitory data recognizing the clear distinctions between inhibitor binding and inhibitory effect can produce simple logical inhibition models. In contrast to the common divergent practice of generating new inhibitory models for every inhibitory situation that presents itself. The empirical approach to inhibition modeling presented here is broadly applicable allowing easy comparison and rational analysis of drug interactions. To demonstrate this, a simple kinetic model of DAPT, a compound that both activates and inhibits γ-secretase is examined using excel. The empirical kinetic method described here provides an improved way of probing disease mechanisms, expanding the investigation of possible therapeutic interventions.Reproducibility of biological data is a significant problem in research today. One potential contributor to this, which has received little attention, is the over complication of enzyme kinetic inhibition models. The over complication of inhibitory models stems from the common use of the inhibitory term (1 + [ That is enzyme inhibitors are subject to the same mass action kinetic principles used to define the Hill–Langmuir equation and the Michaelis–Menten equation. However, the way enzyme inhibition equations are currently produced suggests that kinetically enzyme inhibitor interactions are as unique as the enzyme inhibitor system they are used to represent. This problem stems from the supposed mechanistic derivation of the principle inhibition equations. Mechanistic approaches resulted in an ambiguous inhibitory term that does not distinguish between the stoichiometric enzyme inhibitor binding interactions, defined by the inhibition constant  is observed. In contrast, the non-competitive equation produces an exclusive decrease in the maximum reaction rate (V1), and the mixed non-competitive inhibition equation describes inhibition where both substrate affinity and reaction rate are affected.When modeling the competitive inhibition equation an exclusive decrease in the substrate affinity . This unusual theory excludes the possibility an inhibitor could affect both substrate affinity and catalytic activity in one enzyme inhibitor binding interaction.The mixed non-competitive model, as a combination of the competitive and non-competitive models, describes inhibition that affects substrate affinity and the catalytic rate of the enzyme. However, based on the reaction schemes used to generate the competitive and non-competitive inhibition models both one to one enzyme inhibitor binding events are already accounted for . To ratiThe complexity only continues to grow from there, with the uncompetitive inhibition equation that describes inhibitors that produce linear changes in both substrate affinities and catalytic rate . This unI]/iK) found in every equation suggests that it is working in a similar way. This notion is entirely incorrect. The inhibitory term in the competitive inhibition equation (K1) by multiplying into it. The inhibitory term in the non-competitive inhibition equation (V1) by dividing into it. A rearrangement of the non-competitive inhibition equation demonstrates that the described decrease in catalytic activity is directly dependent on an inhibitor binding term that is identical to the mass action terms used to describe, ligand receptor interactions in the Hill–Langmuir equation and substrate enzyme interactions in the Michaelis–Menten equation (K1) results from the substrate affinity term being divided by the percent of the enzyme population that is not interacting with the inhibitor \docnhibitor . This in and αKi  , maximum reaction velocity (V1 → Vi1) or both. This distinction between binding and effect provides an easy way of describing the vast spectrum of changes in enzymatic activity that can result from the influence of inhibitors or activators. The modularity produced by describing inhibition in this fashion also provides a base equation that can be expanded to explain more complex kinetic interactions.By tying inhibitory effects to mass action inhibitor binding terms, all three base inhibitory equations and equations derived to explain situations they fail to cover, can be replaced with a simple empirical relationship  Walsh, . (3)\doc studied . The chaγ-secretase, an enzyme that cleaves the C terminal of the amyloid precursor protein. This cleavage leads to the production of (1–X) amyloid fragments which results in the formation of the β-amyloid peptides (1–40) and (1–42) (β-amyloid (1–42) is highly associated with the pathology of Alzheimer’s disease -L-alanyl]-S-phenylglycine t-butyl ester). DAPT is described as having complex kinetic interactions with γ-secretase. At low amyloid precursor protein concentrations, low concentrations of DAPT have been observed to increase γ-secretase catalytic production of amyloid-β 1–40 and 1–42 (EC50 72 nM)  . The for disease . Cellula0 72 nM) . However0 72 nM) . At high0 72 nM) . These o protein . HoweverK1) can be described using a term that mimics the Michaelis–Menten equation. At higher substrate concentrations the binding of an additional substrate molecule (K2) pushed the γ-secretase to an increased rate of substrate hydrolysis (V2). At even higher substrate concentrations (K3) the γ-secretase activity is inhibited by the substrate. However, fitting this equation  and inhibition at high DAPT concentrations  are both described mathematically using mass action terms. γ-secretase can be described . Elevated concentrations of substrate would occur in systems setup to over express substrate. While the disassociation constant between the enzyme and inhibitor is somewhat higher than the IC50 this inhibitory effect may be amplified by the inhibitory effects of the third substrate binding interaction (K3 605 nM expression plasmid). At lower substrate levels DAPT (IC50 140 nM) would be interacting with a γ-secretase population fluctuating between enzymes interacting with a single substrate (Kx2 553 nM) or two (Kxx1 70 nM) producing an apparent higher IC50 resulting from the mix. Additionally the EC50 for activation (72 nM) falls very close to the disassociation constant for DAPT induced stimulation (Kx1 30 nM). Using these models allows for facile hypothesis generation, such as, a dimmer of DAPT may be a practical way to eliminate the activation of γ-secretase produced by lower concentrations of DAPT.So to start with the substrate interactions can be modeled with an expansion of the Michaelis–Menten equation that accounts for a change in the enzyme activity over increasing substrate concentrations  Walsh, . (4)\docubstrate . The simry term, , almost ry term, , the stiescribed  and 3. T0 values  describeγ-secretase were produced, analyzed and fit to the data \doe of one  and an Rrelation . A markerelation . Howeverrelation . To evalrelation . Not surrelation –4B, a siThe improper fit produced by γ-secretase inhibitor. Elan Pharmaceuticals, rather than doing a thourough characterization, used the standard IC50 method  Residuals produced by le for C  n = 230 BoxplotR .Click here for additional data file.


We then used multivariate statistical analysis to identify factors responsible for the variation in microbial abundance on the ice sheet. EFM gave the most accurate and reproducible results of the tested methodologies, and was therefore selected as the most suitable technique for cell enumeration of ice containing dust. Cell numbers in surface ice samples, determined by EFM, ranged from ~ 2 × 103 to ~ 2 × 106 cells ml−1 while dust concentrations ranged from 0.01 to 2 mg ml−1. The lowest abundances were found in ice sampled from the accumulation area of the ice sheet and in samples affected by fresh snow; these samples may be considered as a reference point of the cell abundance of precipitants that are deposited on the ice sheet surface. Dust content was the most significant variable to explain the variation in the abundance data, which suggests a direct association between deposited dust particles and cells and/or by their provision of limited nutrients to microbial communities on the GrIS.Measuring microbial abundance in glacier ice and identifying its controls is essential for a better understanding and quantification of biogeochemical processes in glacial ecosystems. However, cell enumeration of glacier ice samples is challenging due to typically low cell numbers and the presence of interfering mineral particles. We quantified for the first time the abundance of microbial cells in surface ice from geographically distinct sites on the Greenland Ice Sheet (GrIS), using three enumeration methods: epifluorescence microscopy (EFM), flow cytometry (FCM), and quantitative polymerase chain reaction (qPCR). In addition, we reviewed published data on microbial abundance in glacier ice and tested the three methods on artificial ice samples of realistic cell (10 Glaciers and ice sheets cover 10% of Earth's land area and contain distinct microbe-dominated ecosystems that are highly sensitive to climate warming  has been used to enumerate microbial cells in aqueous and sediment samples, including glacier ice, and sediments  is the largest ice body in the northern hemisphere and hosts Earth's largest seasonally melting glacier surface ice ecosystem  on artificial ice samples of known, and realistic, cell and mineral particle concentrations prior to analysis of our samples. We then used multivariate statistical analysis to test the significance of environmental characteristics and reviewed the published data on microbial abundance in glacier ice in order to put our results into context.http://promice.org) and were named after the nearest settlement or geographical feature . Additional samples of surface ice were taken at “Dark Site” (DS), one of the darkest 5 km pixels in optical satellite imagery after Box et al. . The corers were autoclaved and kept sterile in polypropylene bags prior to use. The ice cores were transferred to sterile 750 ml WhirlPak bags . At Saddle, samples were obtained using a 9 cm diameter Kovacs coring drill, using sterile autoclaved corers. A deeper (220 cm) surface ice core was extracted at Saddle and cut into sections 10–30 cm long. Saddle samples were taken in order to compare microbial cell numbers of winter snow layers, from 2012 to 2013, with the summer 2012 refrozen melt layer  were extracted at each site, except Saddle, using a small handheld drill and custom-built stainless steel corers  was furnaced at 550°C for 5 h prior to use. The cell abundance of the D. acidovorans culture used was determined by EFM immediately before preparing the artificial ice samples. The dust concentrations used were from 0.1 to 100 mg ml−1, and the cell concentrations used ranged from 102 to 107 cells ml−1, resulting in cell:dust ratios between 1 and 108 cells mg−1, roughly equivalent to 0.2–20,000,000 cells per dust particle. Samples containing no cells and/or no dust were tested in parallel.Artificial ice samples were prepared using deionized water, quartz dust, and a culture of A was quantified asAccuracy eX is the expected abundance and mX the measured value. A can range between 1 (100% accuracy) and 0 (no cells or twice as many as expected), and it can assume negative values when the measured abundance is more than twice as high as the expected value; however, for better plot clarity negative A values were manually corrected to 0. Standard deviations of triplicate measurements, representing the reproducibility of the analyses, were calculated and expressed as percentage of mean; values >100% were manually corrected to 100% for better clarity in the contour plots.where CPH analyzer with a TNM-1 nitrogen unit . Nitrate (NO−3) and phosphate (PO3−4) were analyzed by ion chromatography (IC) using an IonPac AS 14 column . Ammonium (NH+4) was determined on a Fiastar 5000 analyzer . The detection limits, calculated as 3 standard deviations of procedural blanks, were 1.17 mg l−1 for DOC, 0.20 mg l−1 for TDN, and 4.4 μg l−1 for NH+4. No NO−3 or PO3−4 were detected in the procedural blanks and so 0.05 and 0.025 mg l−1 were assumed to be the detection limits for nitrate and phosphate, respectively, determined by previous testing. The remainder of the sample was filtered through a pre-weighed GF/F 0.7 μm glass fiber filter  in order to determine the dust load. The filter papers were then dried at 105°C for 5 h and re-weighed, and the amount of dust normalized to filtrate volume.Prior to analysis, ice samples from each location were pooled together and placed in a pre-furnaced (550°C for 5 h), foil-covered beaker and allowed to melt at 4°C. After melting, subsamples for EFM (150 ml) and FCM (15 ml) were taken. EFM enumerations were conducted immediately after subsampling, whereas samples for FCM were fixed with paraformaldehyde  and stored at 5°C until analysis. From the remaining sample, 300 ml was filtered through Sterivex GP 0.22 μm polyethersulfone filters  into acid washed Duran bottles. The filters were subsequently used for DNA extraction, while the filtered water was used for physico–chemical analysis. pH and electrical conductivity (EC) were measured using a Multi 3430 multimeter with a SenTix 940 pH electrode and a TetraCon 925 conductivity cell . Dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) were measured on a TOC-VSamples were analyzed by EFM after staining with the DNA stain acridine orange (AO). 10 ml of sample was filtered onto a sterile 0.2 μm MontaMil black polycarbonate filter . Dried filters were placed in a Petri dish containing AO  for 2 min, then in deionized water for another 2 min, dried and mounted on microscopic slides with immersion oil. More than 300 AO-stained cells were enumerated on each slide with an Olympus BX50 epifluorescence microscope  using the filter block U-N31001 . Blanks with no cells were counted in parallel.−1 were diluted 10- and 100- fold with 0.1 μm filtered deionized water, respectively, to prevent potential blockage of the cell sorter sample tubing. To control for autofluorescence and dust background, stained and unstained aliquots were processed in parallel. For stained samples, 2 μl of 10,000× SYBR Gold  stock solution was diluted to 1 ml in phosphate buffered saline (pH 7.4), and 1 μl of this solution was used to stain 2 ml of sample for 30 min at room temperature (~23°C) prior to analysis. The cell sorter was operated with samples interrogated at a flow rate of 21 μl min−1 for 30 s with 488 nm laser excitation and fluorescence emissions in the 520–550 nm channel measured along with forward and back scatter. Populations were gated manually.For FCM, samples were analyzed using a SH-800-EC cell sorter  according to protocols optimized for supraglacial meltwater. All samples were vortexed on a Vortex-Genie 2  for 30 s before each stage of processing. Field samples and most artificial ice samples were analyzed undiluted while artificial ice samples with dust concentrations of 10 and 100 mg ml−1). The primers used were 341F (5′-CCTACGGGAGGCAGCAG-3′) and 518R (5′-ATTACCGCGGCTGCTGG-3′). The cycle program was 95°C for 30 s followed by 50 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 30 s. The reaction was completed by a final 72°C elongation step for 6 min and followed by high-resolution melt curve analysis in 0.5°C increments from 72 to 98°C. All qPCR reactions were performed in triplicate and were prepared under DNA free conditions in a pressurized clean-lab with a HEPA filtered air inlet and nightly UV-irradiation. Standards of bacterial 16S rRNA genes were prepared by extracting DNA from a serially diluted culture of E. coli. The gene copy number of the highest standard was 1.12 × 107 μl−1. The detection limits were 1.6 × 102 and 1.7 × 103 gene copies per μl of reaction volume for the artificial ice samples and the Greenland ice samples, respectively. Due to the much diluted nature of our samples, potential inhibition due to humic acid or other inhibitory compounds was considered unlikely and was not evaluated.DNA was extracted from the Sterivex filters using the PowerWater Sterivex DNA Isolation Kit , following the manufacturer's protocol. An unused Sterivex filter was extracted alongside the samples as a procedural control. Quantitative PCR of 16S rRNA genes was performed using a CFX96 Touch system . Reaction mixtures  consisted of 1 μl of template DNA, 10 μl of SYBR Premix DimerEraser , and 0.6 μl of forward and reverse primers  were determined by this method; however, this bias is probably small due to the high reproducibility of cell enumeration by EFM in a high-abundance and dust-free bacterial culture.Accurate enumeration of microbial cells in glacial samples with high debris contents is notoriously difficult due to the problems associated with masking by debris and the difficulty in obtaining adequate sample volumes , and consistent with particle concentrations measured by FCM , with two exceptions . The FCM analysis resulted in lower cell numbers (1.5 – 65% EFM) in all cases except one . The 16S rRNA gene copy numbers determined by qPCR produced values of the same order of magnitude as those measured by EFM, assuming 5–10 copies per cell, except for the DS and TAS samples where the qPCR values were an order of magnitude higher than those determined by EFM  and dust concentrations (0.01–2 mg ml−1) determined in surface ice samples in this study  was an order of magnitude higher than the other analyzed core samples, especially in comparison with the immediately underlying and overlying snow layers . It should be noted however that, due to the small amount of sample volume available for analysis and the expected low cell concentrations, few replicates were measured and the differences are thus not significant. The abundances fall in the range reported from snow on glaciers on the Tibetan Plateau , followed by surface type , nitrate concentration , and days since last snowfall . Although the day of sampling was not a significant factor in this analysis , it is essentially an artifact of the sampling design, and, therefore, another RDA was conducted with this parameter as a covariate, thus showing only the results for the ecologically meaningful variables. This analysis explained 96.2% of the total variation; dust content explained 41.8% of the variation , followed by surface type , the N-position , and days since last snowfall . Figure R2 = 0.89 with all data used; R2 = 0.81 with APO samples removed).Analysis that ignored FCM data and APO samples explained 97.3% of the total variation in the data. Dust content was the most significant variable, explaining 55.9% of the variation (pseudo3 cells ml−1) were found in samples from the accumulation area of the ice sheet  or in those affected by fresh snow (KAN_L), and are similar to abundances found in atmospheric waters  and the number of days since the last snowfall Figure . We sugg3 to ~2 × 106 cells ml−1, while the dust concentrations were found to be between 0.01 and 2 mg ml−1. Dust content was the most significant factor explaining the variation in abundance data. Surface type (ice vs. firn), number of days since last snowfall, N-S position and nitrate concentration were also identified as significant controls. We suggest that the surface of the Greenland Ice Sheet receives a “baseline” cell supply via deposition of atmospheric waters, and that wind-borne dust deposited on the ice sheet likely contains additional cells and may provide limiting nutrients for microbial growth. Ablation areas with high dust concentrations and longer melt seasons are therefore expected to contain higher numbers of active microbes compared to the accumulation area and those portions of the ablation area that contain little dust and are primarily seeded with atmospheric waters.We quantified for the first time the abundance of microbial cells in surface ice from geographically distinct sites on the GrIS, including ablation and accumulation areas, using three different methods . EFM generated the most accurate and reproducible results of the three methods, and is therefore recommended for the cell enumeration of glacier ice. Cell abundance of surface ice samples, determined by EFM, ranged from ~2 × 10MS conceived and designed the study with inputs from JB, EG and CJ; MS, MS, JZ and JB collected samples; EG prepared the artificial ice samples and performed microscopy and qPCR assisted by MS, KC and CJ; AE, IS, JG and TI did flow cytometry analyses; JB provided glaciological and climate data for sampling sites; all authors contributed to the discussion of the results; MS wrote the paper with inputs from EG, KC, JB, IS, AE, TI, and CJ.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.


Aim. To assess the effectiveness of nanosilver gel (NSG) in comparison to chlorhexidine gluconate (CHX) and camphorated phenol (CP) against Enterococcus faecalis (E.f) biofilm. Methods and Materials. Two tests were done, methyl thiazolyl tetrazolium (MTT) assay and confocal laser scanning microscopy (CLSM) analysis, to determine the effectiveness of NSG, CHX, and CP on E.f biofilm. Polystyrene microtiter 96- and 6-well plates were used for MTT and CLSM, respectively. Nanosilver gel was in three concentrations , chlorhexidine gluconate used was 2%, and camphorated phenol and normal saline were as control. Analysis was done using one-way ANOVA; the post hoc test was run for multiple comparisons. The level of statistical significance was set at P < 0.05. Results. One-way ANOVA showed significant differences among groups  (P < 0.001) and also showed significant difference between groups (P < 0.001), f-ratio 87.823. A post hoc Tukey's test revealed no significant difference between chlorhexidine gluconate and 0.05% nanosilver gel (P > 0.05). Conclusions. 0.1% and 0.2% nanosilver gel is more effective on Enterococcus faecalis biofilm as compared to chlorhexidine gluconate and camphorated phenol. Enterococcus faecalis have also been isolated from infected root canal treatment [ E. faecalis has been frequently found in root canal-treated teeth in prevalence values ranging from 30% to 90% of the cases. Root canal-treated teeth are about nine times more likely to harbor E. faecalis than cases of primary infections [ E. faecalis, including its ability to compete with other microorganisms, invade dentinal tubules, and resist nutritional deprivation [Microorganisms and their by-products are considered to be the major cause of pulp and periradicular pathosis. Anaerobic bacteria especially black-pigmented Gram-negative species have been linked to the signs and symptoms of these diseases . Facultareatment . E. faecrivation .Various nanoparticles have gained popularity as antimicrobial agents as a result of their broad spectrum of activity and biocompatibility; recent studies have focused on using nanoparticulate materials to disinfect root canals. Nanosilver (NS) shows antibacterial effect; it also exhibits novel physicochemical and biological activities . E. faecalis [Chlorhexidine is a synthetic cationic bis-guanide that consists of two symmetric 4-chlorophenyl rings and two biguanide groups, connected by a central hexamethylene chain . At highfaecalis .Camphorated phenol is among phenolic group of medicaments which have been applied either on a cotton wool pellet placed in the pulp chamber or on a paper point placed in the root canal, with the rationale being that the antimicrobial effect is delivered through vaporization of the medicament . The ant Enterococcus faecalis biofilm using methyl thiazolyl tetrazolium (MTT) assay and confocal laser scanning microscopy (CLSM) analysis.The aim of this study was to compare the effectiveness of various concentrations of nanosilver gel with 2% chlorhexidine gluconate and camphorated phenol on Enterococcus faecalis biofilm.The hypothesis tested was that nanosilver gel, chlorhexidine gluconate, and camphorated phenol are equally effective on E. faecalis biofilm.Two tests were done  to determine the effectiveness of nanosilver gel, chlorhexidine gluconate, and camphorated phenol on E. faecalis (ATCC 29212) from Nanjing Biotechnology Co. Ltd. was used, to create the bacterial inoculum; isolated colonies (24 hours) of pure cultures of E.f grown aerobically on brain heart infusion (BHI) agar plates were suspended in 5.0 mL BHI. The cell suspension was spectrophotometrically adjusted to match the turbidity equivalent to 0.5 McFarland standards.Pure strain of E. faecalis biofilm.Polystyrene microtiter 96-well plates were used to evaluate the effect of medicaments onμL of the 0.5 McFarland standards inoculum E. faecalis prepared was added to 1–7 columns and A–G rows and then 150 μL of sterile BHI liquid medium was added to the microtiter plate where bacterial cells were seeded plus one column more (1–8 columns); the plate was then covered with the lid and sealed with parafilm and incubated at 37°C for 24 hours afterwards.50 μL of the experimental medicaments was added to different columns to test their effectiveness. The plate was sealed and then incubated at 37°C for 24 hours. The biofilm was formed on the base of the plate after 24 hours; 50 normal saline  as positive control;0.05%, 0.1%, and 0.2% nanosilver gel (Shenyang Dekang Medicine Technology Co. Ltd);2% chlorhexidine gluconate (Shantou Makat Hi-tech Co. Ltd);camphorated phenol .Medicaments were as follows:μL of MTT solution was then added to the experimental wells, the plate was covered with aluminium foil to attain dark environment, and it was there after incubation at 37°C for 4–6 hours. After 4–6 hours the medium was aspirated and 150 μL of dimethyl sulfoxide (DMSO) was added to each experimental well. The plate was kept in a microplate reader where it was shaken first for 10 minutes and then the absorbance value was measured at 630 nm wavelength.The medium was carefully aspirated; then each well was rinsed with sterile phosphate buffered solution (PBS) 2-3 times for about 5 minutes during each wash. 10 Polystyrene microtiter 6-well plates were used.μL of the 0.5 McFarland standards inoculum E. faecalis prepared was added on the surface of the coverslip and left there for 5 minutes. Then carefully 5 mls of sterile BHI liquid medium was added along the side walls of the plate; the plate was sealed with the parafilm and then incubated at 37°C for 24 hours for formation of E. faecalis biofilm on glass coverslips.Sterile 22 × 22 coverslip was placed in a 6-well culture plate and left there for five minutes. 500 μL of the experimental medicaments was added; the plates were sealed and then incubated at 37°C for 24 hours. 200 μL of the prepared AO/EB dye solution was added, and the plates were left in the dark for 15 minutes. Then the specimens were observed under CLSM with absorbance wavelength of 543 nm for AO (green) and 488 nm for EB (red) dyes under 200 magnification.The culture medium and medicine were carefully aspirated without touching the coverslip. The cells were then washed twice with sterile PBS solution for 2 minutes each time. 300 At the absorbance of 630 nm the results are shown in Mean and standard deviation values for each experimental group and control groups were calculated using SPSS 20.0 software and the percentage inhibition for each group of experimental drug was calculated using the following formula below and results are shown in P < 0.001) and also showed significant difference between groups (P < 0.001), f-ratio 87.823. A post hoc Tukey's test revealed no significant difference between chlorhexidine gluconate and 0.05% nanosilver gel (P > 0.05).Statistical analysis using one-way ANOVA showed significant differences among groups   has provided the ability to examine biofilms in situ without the limitations encountered with the SEM, albeit at lower magnifications. CLSM is now being used to determine the true architecture of plaque and the location of selected bacteria within the biofilm. The use of CLSM requires that the organisms in the biofilms be stained with fluorescent stains. These stains are designed to emit light at specific wavelengths and can be used to probe specific cellular functions. Using a suite of such stains allows the biofilm researcher to quantify all the cells and determine which ones are viable . E. faecalis biofilm. The results of this study demonstrated antibacterial activity against bacterial strains by all the intracanal medicaments tested. The bacterial strains chosen for this study belong to bacterial species that are clinically relevant, since they are part of the endodontic pathogens and are also new emerging pathogens causing infections in other clinical fields [The null hypothesis of the present study has been rejected. Nanosilver gel was found to be more effective than chlorhexidine gluconate and camphor phenol againstl fields –18. The The silver nanoparticles showed efficient antimicrobial property compared to other medicaments due to their extremely large surface area, which provides better contact with microorganisms. The nanoparticles get attached to the cell membrane and also penetrate inside the bacteria. The bacterial membrane contains sulphur-containing proteins and the silver nanoparticles interact with these proteins in the cell as well as with the phosphorus containing compounds like DNA. When silver nanoparticles enter the bacterial cell, it forms a low molecular weight region in the centre of the bacteria to which the bacteria conglomerate, thus protecting the DNA from the silver ions. The nanoparticles preferably attack the respiratory chain, cell division finally leading to cell death. The nanoparticles release silver ions in the bacterial cells, which enhance their bactericidal activity –22.The biologic effects of silver are believed to be closely related to silver ion . Studies Enterococcus faecalis biofilm formation at different concentrations, even at much lower concentration than chlorhexidine gluconate.Results of the current study indicate a dose dependent antimicrobial activity of nanosilver especially when compared with chlorhexidine gluconate; nanosilver gel showed the ability to inhibitThe current study shows that camphorated phenol has lower inhibition effect compared to nanosilver gel and 2% chlorhexidine gluconate which coincides with the finding when camphorated phenol was compared to calcium hydroxide .It was found out that CHX was less effective in eliminating E.f biofilm  which co E. faecalis as intracanal medicament. More studies using animal models and clinical studies are to be done to get a better understanding of the effects of nanoparticles on periodontal tissues; also more data on the cytotoxicity of silver nanoparticles are needed on appropriate model organisms.According to the results of the current study, at a very low concentration nanosilver gel can be used to reduce bacteria load especially the most resistant


AMP-activated protein kinase (AMPK) inhibits several anabolic pathways such as fatty acid and protein synthesis, and identification of AMPK substrate specificity would be useful to understand its role in particular cellular processes and develop strategies to modulate AMPK activity in a substrate-specific manner. Here we show that SUMOylation of AMPKα1 attenuates AMPK activation specifically towards mTORC1 signalling. SUMOylation is also important for rapid inactivation of AMPK, to allow prompt restoration of mTORC1 signalling. PIAS4 and its SUMO E3 ligase activity are specifically required for the AMPKα1 SUMOylation and the inhibition of AMPKα1 activity towards mTORC1 signalling. The activity of a SUMOylation-deficient AMPKα1 mutant is higher than the wild type towards mTORC1 signalling when reconstituted in AMPKα-deficient cells. PIAS4 depletion reduced growth of breast cancer cells, specifically when combined with direct AMPK activator A769662, suggesting that inhibiting AMPKα1 SUMOylation can be explored to modulate AMPK activation and thereby suppress cancer cell growth. AMPK senses cellular energy and switches off pathways involved in protein and fatty acid synthesis, but the selectivity of AMPK for different pathways is unclear. Here, the authors show that PIAS4-dependent SUMOylation and inactivation of AMPK preferentially restores activity of the mTORC1 pathway. D-ribofuranoside (AICAR)3AMP-activated protein kinase (AMPK) is an evolutionarily conserved energy rheostat sensing lowered energy levels and adjusting multiple metabolic pathways to mount an appropriate reactionAMPK inhibits fatty acid synthesis by phosphorylating CoA carboxylase (ACC)11AMPK functions as a heterotrimeric complex comprising a catalytic (AMPKα) and two regulatory subunits (AMPKβ and AMPKγ)There are several ways in which mammalian AMPK is regulated. On energy deprivation, AMPK is activated in several stagesIn budding yeast, the AMPK orthologue SNF1 is regulated by several posttranslational modifications. Acetylation of Sip2 (β-subunit) inhibits SNF1 kinase activity and prolongs lifespanHere we present evidence that AMPK activation induces SUMOylation of its catalytic subunit AMPKα1. SUMO E3 ligase PIAS4 catalyses the SUMOylation of AMPKα1, which inhibits AMPK activity specifically towards mTORC1 signalling. Our results therefore uncovered a novel regulatory mechanism by which AMPKα1–mTORC1 signalling is specifically modulated.S-transferase (GST)-tagged AMPKα1 or AMPKα2 from HEK293 cells followed by western blotting (WB) indicated that both PIAS3 and PIAS4 associated with AMPKα1 and AMPKα2  or AMPKα-null  immortalized MEFs and validated AMPKα1- and AMPKα2-specific antibodies  pathway component Mth1 ref. . We therα1+/−;α2+/+) or with deletions of AMPKα1 , AMPKα2  or both . In control MEFs, AICAR treatment lead to the activation of AMPKα noted in expected changes in mTORC1 substrates  and p-ACC, and Pias4 depletion specifically potentiated mTORC1 suppression by AICAR , AICAR treatment did not alter mTORC1 signalling , AICAR treatment efficiently inhibited mTORC1 signalling and activated ACC similar to control MEFs; Pias4 depletion specifically potentiated the inhibition of mTORC1 signalling by AICAR , phosphorylation of ACC was abolished and AICAR treatment did not suppress mTORC1 signalling; Pias4 depletion no longer have any effects on mTORC1 signalling  or PIAS4-depleted (siPias4) MEFs, to phosphorylate a recombinant GST–TSC2 fragment  containing the AMPK phosphorylation site S1345 ref. . As expe−/− MEFs . Notably−/− MEFs . This re−/− MEFs .in vitro phosphorylation of GST–TSC2 by AMPKα1 immunoprecipitated from Flag–PIAS4-WT- or Flag–PIAS4-C335F-expressing cells, and noted that the ability of PIAS4 to inhibit AMPKα1 kinase activity was significantly reduced by the C335F mutation (C335F) , to disrupt the E3 ligase activity (C335F) . These rTo further explore the possible role of SUMOylation in the regulation of mTORC1, we depleted Ubc9, the sole SUMO E2 enzymeConsidering the requirement of the PIAS4 E3 ligase activity for AMPK inhibition, it was of interest to directly investigate whether AMPKα is SUMOylated. To this end, AMPKα1 . Subsequin vitro using SUMO3/E1/E2 and bacterially produced AMPK complex  and GST–PIAS4. As a positive control for the assay, SUMOylation of p53 was detected in the presence of SUMO3/E1/E2/ATP and its SUMOylation was markedly enhanced by GST–PIAS4 .To investigate whether SUMOylation affects AMPKα1 subcellular localization, we initially analysed localization of total AMPKα1 from AICAR-activated AMPKα-null MEFs reconstituted with GST–AMPKα1-WT or GST–AMPKα1-K118R, which both form complexes with AMPKβ1/2 in both cytoplasmic and nuclear compartment . ConsideWe subsequently investigated in which subcellular compartment AMPKα1 SUMOylation occurs using a proximity ligation assay (PLA)11As PIAS4 depletion was found to potentiate AMPK activity towards mTORC1  and AMPK4Our study identifies PIAS4-mediated SUMOylation as a novel and specific regulatory mechanism to attenuate AMPKα1 activity towards mTORC1 following AMPK activation.PIAS4 was also noted to be important for rapid inactivation of AMPK following AICAR withdrawal . Althougin vivo is specifically mediated by AMPKα1 in MEFs, and providing an explanation for the inability of PIAS4 to regulate mTORC1 signalling in these cells. An alternative explanation could be provided by the significantly lower levels of total AMPKα in MEFs only expressing AMPKα2  stoichiometry of SUMOylation of AMPKα1  togetherThe nuclear SUMOylation of AMPKα1 and cytoplasmic localization of TSC2 suggests that TSC2 phosphorylation is mediated by AMPKα1 that has shuttled from the nucleus to the cytoplasm following SUMOylation and licensing. Such a requirement could provide the specificity observed between AMPKα1 substrates TSC2 and ACC/Raptor, where AMPKα1 phosphorylation of the latter substrates would not require prior shuttling. Although further investigations are required to dissect these mechanisms, our observation that AMPK activity is regulated in a substrate-specific manner is interesting, considering the various AMPK modifications and interacting proteins.AMPK is physiologically activated by AMP/ADP via three mechanisms: inhibition of α-Thr172 dephosphorylation by both AMP and ADP, promotion of α-Thr172 phosphorylation and allosteric activation of already phosphorylated AMPK by AMPEnhancement of AMPK activity towards mTORC1 and associated cytostatic effects in MDA-MB-231 breast cancer cells following PIAS4 depletion indicate that inhibition of AMPKα1 SUMOylation could provide a specific way to inhibit cancers with hyperactive mTORC1 signalling.pFlag–PIAS1 (mouse), pFlag–PIASxα (rat), pFlag–PIASxβ (rat), pFlag–PIAS3 (mouse) and pFlag–PIAS4 (mouse) have been describedAntibodies against p-Raptor , Raptor , p-ACC , ACC , p-4EBP1 , 4EBP1 , p-S6K , S6K , p-S6 , S6 , p-AMPKα , AMPKα , AMPKβ1/2 , AMPKγ2 , TSC2  and glyceraldehydes 3-phosphate dehydrogenase  were purchased from Cell Signaling; p53  were from Santa Cruz Biotech; AMPKα1  and L-Glutathione Reduced (G4251) from Sigma; Protein G Sepharose (17-0618) and Glutathione-Sepharose (17-0756) from GE Healthcare; SAMS peptide (12–355), P81 Phosphocellulose Squares (20–134) and recombinant human AMPK  protein (14–840) from Millipore; ATP, [γ-32P]  from PerkinElmer; BL21-A1 competent cells (C6070-03) from Invitrogen; Poly-Prep chromatography columns (731–1550) from Bio-rad; recombinant human p53 protein (SP-454-020) from R&D Systems; and SUMO3 conjugation kit (K-720) from Boston Biochem.AICAR was obtained from Toronto Research Chemicals (A611700); metformin hydrochloride (04635) and phenformin hydrochloride (P7045) were from Sigma; A769662 from Abcam (ab120335); rapamycin from Cell Signaling (9904); Slide-A-Lyzer Dialysis cassette (66380) and HisPur Ni-NTA magnetic beads from Pierce (88832); NEM (E3876), Trypan blue solution (T8154), All siRNAs were purchased either as pools or individual siRNAs from Dharmacon and are listed in Human pLKO.1-shPIAS4-5 (TRCN0000004115) and pLKO.1-shPIAS4-8 (TRCN0000004118) constructs were from the TRC collectionSaccharomyces cerevisiae strain. The ProQuest pre-made human fetal brain cDNA library and a human liver cDNA library in EXP-AD502 (Invitrogen) were transformed into pDEST32-AMPKα1 or pDEST32-AMPKα2 yeast strains, to perform screenings. AMPKα1/brain (4.2 × 106), AMPKα2/brain (2.9 × 106), AMPKα1/liver (2.1 × 106) and AMPKα2/liver (2.0 × 106) colonies were screened and positive clones were subjected to sequencing.Yeast two-hybrid screens were performed using the Gateway ProQuest Two-Hybrid System (Invitrogen) essentially as described by the manufacturer. To generate bait plasmids, AMPKα1 (encoding amino acids 10–559) and AMPKα2 (full length) in pENTR221 (Invitrogen) were transferred to the pDEST32 (Invitrogen) and transformed into MAV203 AMPKα1+/−;α2lox/lox and AMPKα1−/−;α2lox/lox primary MEFs−1) selection for 7 days. Immortalized AMPKα1+/−;α2lox/lox and AMPKα−/−;α2lox/lox MEFs were then transduced with adenoviral vectors expressing green fluorescent protein or Cre recombinaseAMPKα1+/−;α2+/+, AMPKα1+/−;α2−/−, AMPKα1−/−;α2+/+ or AMPKα1−/−;α2−/− MEFs, respectively. NIH3T3, HEK293, HEK293FT and MDA-MB-231 cells were obtained from ATCC and maintained in DMEM medium supplemented with 10% fetal bovine serum (Gibco), 1% L-glutamine and antibiotics (penicillin and streptomycin). All the cells have been tested to be free of mycoplasma contamination. siRNAs were transfected twice at a final concentration of 40 nM by using Lipofectamine 2000 (Invitrogen) on day 0 and day 1 according to suggested protocol; plasmid transfections were performed on day 1 or when combined with siRNA transfections on day 2 using Lipofectamine 2000. Cells were collected on day 2 (only plasmid) or day 3 for analysis.To generate immortalized MEFs, pregnant female mice were maintained in Laboratory Animal Center of the University of Helsinki. MEF isolation was approved by the National Animal Experiment Board in Finland. WT, Total RNAs from cell lysates were isolated using the RNeasy isolation kit (Qiagen) according to manufacturer's instructions and reverse transcribed using Taqman MULV reverse transcriptase and random hexamers (Applied Biosystems). Real-time quantitative PCR was performed with StepOnePlus RT-PCR System (Applied Biosystems) using SYBR-green RT-PCR reagent (Applied Biosystems) and primers listed in −1 Aprotinin, 0.1 mM phenylmethyl sulfonyl fluoride (PMSF), 10 μg ml−1 Leupeptin, 10 mM β-glycerophosphate and protease inhibitor cocktail (Roche)) and lysates were cleared by centrifugation  followed by IP with antibody against AMPKα1 or AMPKα2 and protein G-Sepharose, and five washes with lysis buffer, and subsequently subjected for kinase assays or WB analysis.For IP, cells were lysed in IP lysis buffer , 10 μg ml−1 aprotinin, 0.5 mM PMSF, 10 mM β-glycerophosphate and 1 μg ml−1 leupeptin). Cleared  cell lysates were incubated with Glutathione-Sepharose overnight at +4 °C, then by washing the beads five times with ELB buffer followed by kinase assay or WB analysis. The sample size for each condition is 1 (n=1) within one experiment.For purification of GST-tagged proteins from transfected HEK293, cells were lysed in ELB buffer  instead of NER buffer provided by the kit. The fractions were analysed following purification with GST pulldown or analysed directly by WB. The sample size for each condition is 1 (n=1) within one experiment.Nuclear/cytoplasmic fractionation was performed using NE-PER Nuclear and Cytoplasmic Extraction Reagents (ThermoFisher) and nuclear fractions were extracted using ELB buffer  within one experiment.For total protein analysis, cells were lysed using SDS boiling buffer  and lysates were boiled at +98 °C and needled (25-gauge) ten times. Lysates were then cleared by centrifugation and protein concentration was measured by using Bio-Rad DC protein assay (Bio-Rad). Twenty micrograms of protein lysates were used for WB. For WB analysis, 8–12% SDS–PAGE gels were transferred to nitrocellulose membrane and blotted according to the antibody manufacturer's instructions. Immunoblots were developed using SuperSignal West Femto Maximum Sensitivity Substrate . Blots were cropped to include at least one marker position. Uncropped blots for all main figures were included in Cells on coverslips were fixed with 4% paraformaldehyde (PFA) for 15 min and then permeabilized using 0.1% Triton X-100 for 5 min. Cells were then blocked with 5% goat serum in PBS for 30 min, incubated with anti-GST antibody (1:500) for 30 min, washed three times with PBS, incubated with Alexa594 secondary antibody for 30 min, washed three times with PBS, labelled with 4,6-diamidino-2-phenylindole (DAPI) and mounted with Immuno-mount (Thermo Scientific).t-test. The sample size for each condition is 1 (n=1) within one experiment.Stained coverslips were analysed and imaged using Zeiss AxioImager.M2 fluorescent microscope. Transfected cells were identified by thresholding Alexa594 image using ImageJ 1.49a. Total GST–AMPKα1 levels were measured as the integrated density within the identified transfected cells. Nuclei were identified by DAPI stain. Nuclear levels of GST–AMPKα1 were measured as the integrated density within the nuclear region and expressed as a percentage of total GST–AMPKα1 for each identified transfected cells. The mean nuclear levels of GST–AMPKα1-WT and GST–AMPKα1-K118R cells from three equally weighed independent experiments were compared with Student's PLAs were performed using Duolink In Situ Red Starter Kit Mouse/Rabbit  according to the manufacturer's protocol. Briefly, cells were fixed with 4% PFA for 15 min and then permeabilized using 0.1% Triton X-100 for 5 min. After blocking with 5% goat serum in PBS for 30 min, cells were labelled with anti-GST  and anti-SUMO2/3  for 30 min. After washing with PBS for three times, cells were labelled with PLA probe plus and minus diluted in PBS for 1 h in a pre-heated humidity chamber. Ligation and amplification were performed as detailed by the manufacturer. Slides were mounted with Duolink Mounting medium with DAPI and were imaged using Zeiss AxioPlan2 with × 10 objectives.Forty images per coverslip of two independent experiments were analysed using ImageJ 1.49a. Cell nuclei were identified by DAPI stain . Regions of interest (ROIs) for PLA signal measurement of individual cells were created by dilating cell nuclei with 20 iterations followed by the watershed algorithm. GST transfected control was used to correct for background PLA signal by using it as a reference to set a threshold for PLA signal (imaged under Alexa 594 channel), where minimal signal is obtained in GST-transfected control. The same threshold was then applied to other samples. PLA signal was measured as arbitrary unit of integrated density within the ROIs. Integrated density for individual cells within GST-transfected control were measured and the maximum value (GSTmax) was used as cutoff, whereby cells with integrated density greater than GSTmax are identified as positive for PLA signal. Fisher's exact test was used for statistical analysis of percentage of positive cells.t-test was used for statistical analysis.PLA signal is also measured within the nuclear region of each cells and percentage of nuclear PLA signal is expressed as integrated density within the nuclear region divided by integrated density within the ROIs multiplied by 100. Student's n=1) within one experiment.Transfection efficiency was determined from coverslips (from the same transfection of coverslips used for PLA) stained for anti-GST antibody, five images per coverslips from two biological experiments. Cells that were clearly non-transfected were used as background reference for thresholding GST signal to a black and white binary image, of which pixels with intensity value above the threshold value is white and those below is black. A single threshold value is used for all samples. Each cell, represented by ROIs created as described above, is classified as transfected cells when it has more than 500 pixels of white. The appropriateness of such analysis was confirmed manually by the eye. Fisher's exact test was used for statistical analysis of transfection efficiency. The sample size for each condition is 1 . Lysates were sonicated and centrifuged , and supernatants were rotated with glutathione-sepharose beads in Poly-Prep chromatography columns at +4 °C for 2 h. Packed beads were washed three times with PBS followed by elution in 10 mM L-Glutathione Reduced, 50 mM Tris pH 8.0 ) or 10 mM L-Glutathione Reduced, 50 mM Tris pH 8.0, supplemented with 5 mM DTT (for GST–PIAS4). Eluted proteins ) were dialysed against Tris-buffered saline using Slide-A-Lyzer Dialysis cassette (10-kDa cutoff) at +4 °C overnight and stored at −70 °C.pDEST15-TSC2  and pDEST15-PIAS4 were transformed into BL21-A1 cells. Expression of GST–TSC2  was induced with 2, 5 μCi [γ-32P] ATP 3,000 Ci mmol−1 and 2 μg GST–TSC2  or 2.5 μg SAMS peptide in a final reaction volume of 25 μl at +30 °C for 30 min. For the kinase assay using GST–TSC2 fragment as substrates, reactions were terminated with 25 μl 2 × Laemmli sample buffer  glycerol, 0.01% bromophenol blue), boiled at +98 °C for 5 min and subjected to SDS–PAGE and autoradiography. For the kinase assay using SAMS peptide as substrates, reactions were terminated by spotting 10 μl reaction mixture to the centre of P81 phosphocellulose square. P81 squares were then washed two times with 1% phosphoric acid buffer, one time with H2O and one time with acetone. Dried P81 squares were transferred to scintillation vial containing 2 ml scintillation cocktail and radioactivity were measured with scintillation counter from three independent experiments. The sample size for each condition is 1 (n=1) within one experiment. Student's t-test was used for statistical analysis.Cells to be analysed were replenished with fresh DMEM medium with or without 2 mM AICAR for 2 h before lysing in ice-cold IP lysis buffer. Twenty-five micrograms of cleared lysates were incubated with 1 μl of affinity-purified AMPKα1 antibody (H1) at +4 °C with rotation overnight followed by addition of 20 μl of a 1:1 slurry of Protein G Sepharose prewashed with IP lysis buffer. Beads were washed three times with cold IP lysis buffer and two times with cold HEPES-Brij buffer  followed by a kinase assay in 50 mM HEPES pH 7.4, 1 mM DTT, 0.02% Brij-35, 5 mM MgClg for 2 min. Cell pellet was re-suspended with 100 μl 1 × Laemmli sample buffer, needled and boiled at +98 °C for 5 min before loading to SDS–PAGE. To prepare the sample for nickel affinity purification, rest of the cell suspension were centrifuged at 1,000g and re-suspended with 5 ml freshly prepared Lysis buffer . Samples were sonicated for 30 s on low power on ice and cleared by centrifugation at 16,000g, +4 °C for 10 min. Supernatants were then diluted with equal volume of Equilibration buffer  and incubated overnight with rotation at +4 °C with 100 μl HisPur Ni-NTA magnetic beads prewashed with Equilibration buffer. Beads were then washed and collected on a magnetic stand three times with Wash buffer 1  and three times with Wash buffer 2 . His-tagged proteins were finally eluted with 100 μl Elution buffer  for 20 min at room temperature and 1 min at +98 °C, and 20 μl protein elutions were resolved by 8% SDS–PAGE gel.Purification of 6His-tagged SUMO under denaturing condition was performed according to the protocol described previouslyIn vitro SUMOylation was performed according to the manual provided by SUMO3 conjugation kit  with a slight modification. Briefly, 9 μl of glutathione elution buffer  with or without GST–PIAS4, 2 μl 10 × Reaction buffer, 1 μl p53 protein (285 ng) or 0.5 μl AMPK  protein (500 ng), 2 μl SUMO E1 enzyme, 2 μl SUMO E2 enzyme, 2 μl SUMO3, 2 μl 10 × Mg2+-ATP Solution were mixed in a 20-μl volume and the reactions were carried out in +37 °C for 1 h. The reactions were terminated with addition of 5 × SDS–PAGE sample buffer and 1 μl 1 M DTT, and boiling at 98 °C for 5 min. Five-microlitre reactions were resolved by 10% SDS–PAGE gel and blotted with either p53 or AMPKα1 antibody. The sample size for each condition is 1 (n=1) within one experiment.5 immortalized AMPKα1−/−;α2−/− MEFs or 1 × 106 MDA-MB-231 cells were seeded on six-well plates and transduced the following day with lentiviral supernatants in the presence of 8 μg ml−1 polybrene overnight. Transduced AMPKα1−/−;α2−/− MEFs were selected with (10 μg ml−1) blasticidin (Invitrogen) and MDA-MB-231 cells were selected with (2.5 μg ml−1) puromycin (Gibco) for 1 week.For the production of lentivirus, lentiviral constructs (see Reagents) were co-transfected with VSV-G and Delta 8.9 packaging plasmids (Invitrogen) into HEK293FT cells using Lipofectamine 2000, followed by collection of supernatant 48 h later and filtering through a 0.45-μm filter (Millipore). For the lentiviral transduction, 1 × 10n=3) (1.5 × 105 cells per well) into 24-well plates. The following day (day 1) cells were treated with vehicle control (dimethyl dulfoxide), A769662 (150 μM), rapamycin (10 μM) or A769662 (150 μM)+rapamycin (10 μM). Cell proliferation was assessed by comparing number of viable cells on day 2, 3 and 4 with those of day 1 using Trypan blue exclusion and a TC20 cell counter (Bio-Rad) from three independent experiments. Student's t-test was used for statistical analysis. The sample size for each condition is 3 (n=3) within one experiment.Selected pools of lentiviral-transduced MDA-MB-231 cells were seeded as triplicates . Data were presented as mean+s.e.m. Statistical significance was set at P-values of NS>0.05, *<0.05, **<0.01 and ***<0.001.All experiments have been done at least twice and representative results are shown. Densitometric analysis of WB and 32P radioautography results was done using Image J 1.49a (NIH). Intensity of each band was measured and subtracted with background intensity from adjacent area. Values in the results section were presented as relative intensity versus control. Statistical analyses were performed either by using the analysis of variance followed by Fisher's least significant difference test (GraphPad Prism version 6.0c for Mac OS X) for  or by twHow to cite this article: Yan, Y. et al. SUMOylation of AMPKα1 by PIAS4 specifically regulates mTORC1 signalling. Nat. Commun. 6:8979 doi: 10.1038/ncomms9979 (2015).Supplementary Figures 1-14 and Supplementary Tables 1-4


In this report, we demonstrate a unique method for embedding magnetic structures inside a microfluidic channel for cell isolation. We used a molding process to fabricate these structures out of a ferrofluid of cobalt ferrite nanoparticles. We show that the embedded magnetic structures significantly increased the magnetic field in the channel, resulting in up to 4-fold enhancement in immunomagnetic capture as compared with a channel without these embedded magnetic structures. We also studied the spatial distribution of trapped cells both experimentally and computationally. We determined that the surface pattern of these trapped cells was determined by both location of the magnet and layout of the in-channel magnetic structures. Our magnetic structure embedded microfluidic device achieved over 90% capture efficiency at a flow velocity of 4 mm/s, a speed that was roughly two orders of magnitude faster than previous microfluidic systems used for a similar purpose. We envision that our technology will provide a powerful tool for detection and enrichment of rare cells from biological samples. Microfluidics provides an effective platform for manipulating small quantities of cell samples with sensitivity and precision1214517910121417181921222324262728The vast majority of the microfluidic IMS devices have applied a magnetic field via placing a magnet exterior to the microfluidic structures. However, because the magnetic field intensity decays rapidly with distance, it would be highly advantageous to place additional magnetic structures inside the microfluidic channels. This would furthermore provide a robust means of creating consistent field distributions in microfluidic devices. Previous work has involved complex microfabrication procedures (e.g. electroplating or sputtering) for fabricating microscale magnetic structures inside the microfluidic channels26273031323325μm) out of a ferrofluid of cobalt ferrite nanoparticles (5–13 nm in diameter). We tested our microfluidic channels for capturing RAW 264.7 cells that were magnetically labeled by microscale beads. We found that channels embedded with the magnetic structures yielded up to 4 times higher capture efficiency compared to that of channels without the structures. We built COMSOL models to simulate the magnetic field and magnetic field gradient distribution inside channels and generate insights into the mechanistic details. Both the experimental and modeling results indicated that the layout of the magnetic structures and the location of the magnet strongly affected the distribution of the trapped cells. With the enhanced magnetic field gradient, our device allowed 100% capture efficiency at a flow velocity of 0.5 mm/s and >90% capture rate at 4 mm/s. These velocities were 20–80 times faster than those of previous microfluidic IMS devices7212223In this report, we demonstrate a simple microfluidic device that contains microscale paramagnetic structures inside a microfluidic channel for cell isolation based on IMS. We used a molding process to fabricate these magnetic structures  via antigen-antibody interaction, as shown in 3738RAW 264.7 cells (a mouse leukaemic macrophage cell line) were conjugated with functionalized magnetic beads  trapped inside the channel divided by the total number of magnetically labeled cells that flow through the channel during the period. As shown in μm/s)2235We optimized the flow conditions to facilitate trapping of magnetically labeled cells and removal of unlabeled cells. We studied cell capture efficiency in microfluidic channels with and without the embedded magnetic microstructures as a function of flow rate. In either case, the microfluidic channel had a width of 0.96 mm and a depth of 100 F on a magnetic particle is governed by F = m∇B, where m is the magnetic moment of the particle, B is the magnetic flux density2630414243m = ΔBχV/μ0, where Δχ is the difference in magnetic permeability between the particle and surrounding buffer, V is volume of the particle, and μ0 is the magnetic permeability constant. m increases with B and reaches a saturation value ms, with a direction that is parallel to B. Under these circumstances, F = msB∇ and is proportional to ∇B26B and ∇B in the direction that is perpendicular to the glass substrate (By and Bd/dy) only, because the magnetic force in this direction provided the main mechanism for cell trapping. As shown in By and B/dyd were substantially enhanced in the space that was on top of the magnetic stripes, especially at the ends of the stripes. Bd/dy (andF) in this region was about 50 times stronger than that without the magnetic stripe underneath.The magnetic force By and magnetic field gradient Bd/dy. When the magnet covers the entire magnetic structures from above, By and B/dyd were the strongest at the upstream ends of the magnetic stripes (Bd/dy on top of the magnetic stripes was around −4000 T/m (i.e. the magnetic force was strongly attractive) and the regions between the stripes showed Bd/dy value around 700 T/m (i.e. the magnetic force was repulsive). Bd/dx on top of the magnetic stripes exerted a magnetic force that is opposite to flow drag force in direction (Bd/dy was around −50 T/m at the upstream end of the magnetic stripes (location 1) across most of the channel width. B/dyd was strongly negative at the edges of the magnetic stripes. However, we believe that these extreme B/dyd intensities at the stripe edges do not substantially affect cell trapping due to the very narrow regions they influence. Then B/dyd became slightly higher on the stripes than between the stripes at the more downstream location 2 (with around −80 T/m on the magnetic stripes and −55 T/m between the stripes). Bd/dx was uniform across the channel width at both locations 1 and 2  for 30 min at 37 °C for fluorescent labeling.RAW 264.7 cells  were grown in Dulbecco’s Modified Eagle Medium (DMEM) (Life technologies) supplemented with 10% fetal bovine serum (FBS)  and 1% penicillin/streptomycin (Invitrogen) in a humidified atmosphere of 5% COμl streptavidin-coated superparamagnetic polystyrene beads  were conjugated with 0.25 μg biotinylated anti-CD11b antibody  by incubating in 1 ml PBS overnight at 4 °C. The tube containing antibody conjugated magnetic beads was then placed in magnet  for 1 min and discard the supernatant to remove excess of antibodies. 1 ml fluorescently labeled RAW 264.7 cells in PBS were added to the beads (cell number: bead number = 1:4) and mixed well by pipetting. The mixture was incubated for 1 h at 4 °C on a rotator mixer at 24 rpm. Cell-bead complexes were then centrifuged and resuspended in PBS containing 7 wt% dextran (Sigma-Aldrich). Dextran was used here to increase density of PBS to prevent cells from settling in the tubing or channel2.5 μm thick photoresist AZ 9296 (Clariant) after UV exposure and development. A 10:1 mixture of polydimethylsiloxane  prepolymer was poured onto the silicon wafer to form a ~5 mm thick layer and cured in an 80 °C oven for 1 h, followed by being peeled and drilled for inlet and outlet. The PDMS structure was washed with liquid soap (Thermo Scientific), sterilized with 70% ethanol, rinsed with ultrapure water, and blow-dried with air before being put in contact with a pre-cleaned glass slide (1 mm thick) for bonding by reversible surface adhesion. The chip (including the glass slide and the PDMS structure) was baked at 80 °C for 30 min to strengthen the bonding. Ferrofluid  was added to a reservoir of the chip and entered the channel by gravity. The chip was put under house vacuum for 30 min to facilitate filling of ferrofluid into the channel. The ferrofluid-filled chip was baked for 15 min each at 30, 40, 50, and 60 °C sequentially, followed by an overnight baking at 70 °C. The PDMS structure was then peeled off from the glass slide (which bears the magnetic structure). The glass surface was cleaned carefully with acetone-dipped cotton stick to leave magnetic stripes.The process is shown in μm. After PDMS molding and drilling for inlet and outlet holes, the PDMS replica was aligned and bonded to the glass bearing the magnetic structure after oxidization of both surfaces in a plasma cleaner (Harrick Plasma). The assembled chip was baked at 80 °C for 1 h to ensure strong and irreversible bonding between PDMS and the glass.The microfluidic channel was fabricated by standard soft lithography45The experimental setup used for microfluidic immunomagnetic separation is shown in μl before being pumped into the channel. The accurate cell concentration was determined by counting cells in 20 μl suspension with a 96-well plate. Cell capture efficiency was defined as in equation (1):Cells suspended in PBS with 7 wt% dextran were counted with a hemocytometer and diluted to be roughly 10 cells/when the flow velocity was higher than 10 mm/s, the total number of magnetically labeled cells entered was determined by the percentage of labeled cells (89% for RAW 264.7), the cell concentration, and the volume of solution being pumped through the chip. The captured cells in the channel were imaged and counted in ImageJ software. Inverted fluorescence microscope  equipped with a 2X dry objective, a UV lamp and a CCD camera  was used for imaging. The excitation light was filtered by a D480/40 filter, and the emission light was filter by a D535/40 filter. When the flow velocity was lower than 10 mm/s, cell density was not uniform during the experimental duration, thus we determined the number of labeled cells by imaging. Videos were taken at rate of 6 frames per second at the entrance and exit of the channel and the number of labeled cells during a time interval was counted.3D steady-state model was built in COMSOL Multiphysics 4.3 to simulate the distribution of magnetic field within the microfluidic channel. We assumed no free current in the region and selected the Magnetic Field, No Currents interface from the AC/DC Module for the modeling. Instead of using infinite element domain, a sufficiently large air box (20 mm × 20 mm × 20 mm) was draw to cover the whole magnetic block and magnetic structures. In a current free region,ψ, is defined as:Scalar magnetic potential, For the paramagnetic stripes and surrounding air:and for the permanent magnet:μ0 is the permeability constant, μr is the relative permeability determined by the materials, and Br is the residual flux density of the permanent magnet (1.3 T). μr was estimated to be 200 for the magnetic stripes and 1 for air and the permanent magnet.where Together with the Guass’s law:ψ can be solved. Magnetic insulation condition was used as the boundary condition. Initial value of ψ is set to be zero.Bd/dy and Bd/dx, fine mesh  was used for the region covering the three magnetic stripes at the center of the 7-stripe-structure. One additional air box of 4 mm (W) × 0.5 mm (D) × 6 mm (L) was added to enclose all 7 stripes with a coarse mesh . This mesh size was also applied to the 4 magnetic stripes other than the 3 central ones. Large mesh size  was used for the permanent magnet and the outer large air box. Cubic discretization was used for high precision.To model the magnetic field gradient How to cite this article: Sun, C. et al. Paramagnetic Structures within a Microfluidic Channel for Enhanced Immunomagnetic Isolation and Surface Patterning of Cells. Sci. Rep.6, 29407; doi: 10.1038/srep29407 (2016).