Drosophila pupal wing increases its stability and promotes its clustering at intercellular junctions, and that Prickle negatively regulates Strabismus phosphorylation. Additionally, loss of phosphorylation of Dishevelled – which normally localises to opposite cell edges to Strabismus – reduces its stability at junctions. Moreover, both phosphorylation events are independently mediated by Casein Kinase Iε. We conclude that Casein Kinase Iε phosphorylation acts as a switch, promoting Strabismus mobility and Dishevelled immobility, thus enhancing sorting of these proteins to opposite cell edges.The conserved core planar polarity pathway is essential for coordinating polarised cell behaviours and the formation of polarised structures such as cilia and hairs. Core planar polarity proteins localise asymmetrically to opposite cell ends and form intercellular complexes that link the polarity of neighbouring cells. This asymmetric segregation is regulated by phosphorylation through poorly understood mechanisms. We show that loss of phosphorylation of the core protein Strabismus in the  Phosphorylation is a widespread means of controlling protein activity, regulating protein-protein interactions, protein stability and conformation . The actDrosophila, the core pathway controls the production of polarised hairs and bristles on many adult tissues, for example the trichomes that emerge from the distal edge of each cell in the adult wing.The core planar polarity proteins  regulate the production of polarised structures or polarised cell behaviours in the plane of a tissue. This includes polarised production of cilia and of stereocilia bundles in the inner ear, and the coordinated polarisation of tissue movements necessary for convergence and extension of the body axis . In DrosDrosophila pupal wing, the seven-pass transmembrane protein Frizzled (Fz), and the cytoplasmic proteins Dishevelled (Dsh) and Diego (Dgo) localise to distal cell ends, where the trichome will emerge. The four-pass transmembrane protein Strabismus  and Prickle (Pk) localise to proximal cell ends, and the atypical cadherin Flamingo  localises to both proximal and distal cell ends  causes planar polarity defects and a reduction in core protein asymmetry . Interes mutants .Xenopus . This revealed that a similar number of puncta were seen in the phosphomutant as in wild-type tissue, while many fewer puncta were seen in the phosphomimetic . The meaOther core proteins co-localised with both phosphomutant and phosphomimetic Stbm . OverallCore protein complexes within junctional puncta are highly polarised compared to other junctional regions . This isIn a wild-type situation, the alignment of core proteins in the same orientation within puncta correlates with low protein turnover, as measured by Fluorescence Recovery After Photobleaching (FRAP) assays . As the Hub-and-spoke FRAP showed that the stable amount of phosphomutant Stbm-EGFP at junctions was increased compared to wild-type Stbm-EGFP, while the unstable amount was unchanged . This suTaken together with our previous data that there is less phosphomimetic Stbm incorporated into puncta , this suwithin puncta , leading to a decrease in the absolute amount of stable Stbm . To investigate this, FRAP experiments were carried out on clone boundaries, in which Pk activity was present only in the same cell as Stbm, or only in neighbouring cells . In an oy stable . Stbm-EGecreased . If Pk iecreased . In contecreased . This inIf a major role of Pk was to regulate Stbm phosphorylation, and this phosphorylation regulates Stbm clustering into puncta, we would also expect Stbm phosphomutant clustering to be largely insensitive to loss of Pk. In wild-type wings, loss of Pk causes a reduction in puncta size . As expeHaving established that Dco regulates Stbm phosphorylation, and this controls the turnover and clustering of Stbm, we next questioned whether these mechanisms are sufficient to explain all the effects of Dco on the core proteins. In particular, does Dco also directly regulate Dsh in any way, or does Dco only regulate Stbm, which then leads to secondary effects on Dsh phosphorylation?dco hypomorphs  were recombineered using standard methods. N-terminal fusions of P[acman]-EGFP-stbm, P[acman]-mApple-stbm and P[acman]-mApple-dgo used plasmid PL452-N-EGFP (Addgene) as a source vector, or a modified version PL452-N-mApple where mApple replaced EGFP. Gene-specific primers were used to amplify EGFP/mApple and the selection cassette, and the resulting fragment was then recombineered into the relevant P[acman] construct, in frame with the open reading frame. The kanamycin cassette was then excised, leaving a single LoxP site between the EGFP/mApple tag and the open-reading frame. Phosphomutants were generated using recombineering with positive-negative selection into P[acman]-stbm  are described in CaSpeR-dsh-GFP , unless otherwise indicated. Flies raised at 29°C were imaged after 25 hr. To avoid dosage compensation effects, females of Full genotypes for each figure are shown in Adult wings were dehydrated in isopropanol and mounted in GMM , and incubated overnight on a 60°C hot plate to clear. Wings were photographed at 20x magnification. To quantify trichome swirling, ImageJ was used to draw around a region near the posterior cross vein in which trichomes deviated significantly away from their normal orientation. Data were compared using ANOVA with Dunnett’s multiple comparisons test.Pupal wings were dissected at 28 hr after puparium formation (APF) at 25°C. Briefly, pupae were removed from their pupal case and fixed for 25–60 min in 4% paraformaldehyde in PBS, depending on antibody combinations. Wings were then dissected and the outer cuticle removed, and were blocked for 1 hr in PBS containing 0.2% Triton X100 (PTX) and 10% normal goat serum. Primary and secondary antibodies were incubated overnight at 4°C in PTX with 10% normal goat serum, and all washes were in PTX. After immunolabelling, wings were post-fixed in 4% paraformaldehyde in PBS for 30 min. Wings were mounted in 25 µl of PBS containing 10% glycerol and 2.5% DABCO, pH7.5. Wings expressing mApple-tagged proteins were mounted in 12.5 µl Vectashield, as this preserved the fluorescence for longer.Primary antibodies for immunolabelling were rabbit anti-Stbm , rat antFor pupal wing westerns, 28 hr APF pupal wings were dissected directly into sample buffer. One pupal wing equivalent was used per lane. For phosphatase treatments, 6 hr APF prepupal wing extracts were made in lysis buffer . Lysates were treated with 400 units lambda phosphatase (NEB) for 1 hr at 30°C, before addition of sample buffer.Western blots were probed with rabbit anti-Stbm , affinitFor comparing levels of phosphorylated and unphosphorylated Dsh, bands on western blots migrated too close together to quantitate absolute band intensities. ImageJ was used to generate a band profile for each lane, and the maximum values of the phosphorylated and unphosphorylated bands were measured. Data is expressed as a ratio of this maximum intensity, and ratios from four biological replicate samples were compared using unpaired t-tests.Pupal wings were imaged on a Nikon A1R GaAsP confocal microscope using a 60x NA1.4 apochromatic lens. Wings without clones were imaged posterior to vein 4; wings containing clones were imaged wherever they appeared in the wing. 9 Z-slices separated by 150 nm were imaged at a pixel size of 70–80 nm, and the three brightest slices around apicolateral junctions were selected and averaged for each channel in ImageJ.Membrane masks and polarity nematics were generated in Packing Analyzer . MATLAB To compare puncta between wild-type and mutant tissue, a MATLAB script was used to select puncta using the same threshold value in wild-type and mutant regions of the same wings . Puncta Values for control and mutant regions of the same wings (for clones) were expressed as a ratio and compared using one sample t-tests; or were compared between images using unpaired t-tests or ANOVA for more than two genotypes. For all experiments n = number of wings.2 were selected, that covered a vertex and three half-cell edges. Alternatively elliptical ROIs were selected to bleach puncta (ROIs 1–1.5 µm2) or entire junctions between two cells on a clone boundary (ROIs 2–2.5 µm2). Three pre-bleach images were taken at two frames/sec, and ROIs were then bleached using a 488 nm Argon laser at 80% with eight passes , which resulted in 60–75% bleaching. Immediately following bleaching, five images were taken at 5 s intervals, followed by 10 images at 10 s intervals and 26 images at 15 s intervals. Laser power was adjusted to maintain constant power between different imaging sessions. If only EGFP was being imaged, a long pass GFP filter was used. If mRFP was present in the stock, EGFP was detected using a 525–550 band pass filter.For live imaging, a small piece of cuticle was removed from over the pupal wings of 28 hr APF pupae, and the exposed wing was mounted in a drop of Halocarbon 700 oil in a glass-bottomed dish. For FRAP analysis, images were 256 × 256 pixels, with a pixel size of 100 nm, and a pinhole of 1.2 AU. ‘Hub-and-spoke’ ROIs of 3–4 µmFor data analysis, ImageJ was used to manually reselect up to six bleached regions in each image for each time point. The laser off background was subtracted, and the values were corrected for acquisition bleaching and normalised against the average of the prebleach values. Data were then plotted on an xy graph using Prism (v7 Graphpad), bleached regions within the same wing were averaged and a one-phase exponential curve was fitted for each wing. Multiple wings were then combined and an exponential association curve was fitted. An extra-sum-of-squares F test was used to compare curve plateaux (y[max]), and stable fractions were calculated as 1-y[max].For hub-and-spoke and boundary FRAP experiments, the stable amount of protein was calculated by measuring the intensity of the ROIs from the three pre-bleach images, and averaging per wing. The intensity was then corrected for distance from the coverslip as previously described , and thiOverall junctional intensities, and stable and unstable amounts were compared between genotypes using unpaired t-tests, or one-way ANOVA for more than two genotypes. Post-hoc tests were used to compare individual samples: Dunnett’s multiple comparison test was used to compare the control to the rest of the genotypes in the experiment; Tukey-Kramer’s multiple comparison test to compare all genotypes within an experiment; and Holm-Šídák’s multiple comparison test was used to compare genotypes pair-wise.Each experiment was performed on multiple wings from different pupae, which represent biological replicates (n = number of wings). For each wing, 4 ROIs were selected for FRAP analysis, and these were treated as technical replicates and were averaged per wing to produce a y[max] and a stable amount per wing.Based on the mean intensity and standard deviation of a control set of wings, we calculated that a sample size of 6 wings per genotype would allow detection of differences of 20% in the means, in a pair-wise comparison, with a power of 0.8 and α 0.05 (using G*Power). As standard deviations were larger for some genotypes, we aimed for 10 wings per genotype. Data was excluded if the ROI recovery curve failed the ‘replicates test for lack of fit’ in GraphPad Prism, or if the wing moved out of focus during the course of imaging. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Utpal Banerjee as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "Reciprocal action of Casein Kinase Iε on core planar polarity proteins regulates clustering and asymmetric localisation" for consideration by As you will see, all of the reviewers were impressed with the importance and novelty of your work. I am including the three reviews at the end of this letter, as there are a variety of specific and useful suggestions in them. We appreciate that the reviewers' comments cover a broad range of suggestions for improving the manuscript. We look forward to receiving your revised manuscript.Reviewer #1:Drosophila wing PCP, and on Stbm polarization, stability at junctions, puncta size, etc. Thus they go well beyond the study of Kelly et al., 2016 especially in vivo, and in detail some of their results disagree. Intriguingly, phosphomutant and phosphomimetic Stbm both have abnormal and even dominant negative effects on PCP and are associated in decreased and increased junctional stability, respectively. The authors do a nice job incorporating this into their model.The manuscript examines the role the Casein kinase Dco plays in the regulation of core PCP proteins, especially Stbm and Dsh. The study confirms recent findings the Dco affects Stbm phosphorylation, and extends these by examining the effects of phosphorylation site mutants on Previous work had suggested that Stbm phosphorylation could be regulated by Dsh and Fz. However, the authors find little evidence of this in vivo from fz and dsh mutants. Instead, they find a strong effect from Pk. While they do not have a firm understanding of how this works, they provide some persuasive arguments that it is likely fairly direct, rather than through simple assembly of the PCP complex or through Fz or Dsh.Finally, they go on to show that Dco also has an independent effect on Dsh levels and phosphorylation.While this paper lacks the zing of recent studies on polarity-inducing feedback mechanisms, it is certainly a solid study that extends previous work on the role of PCP component phosphorylation. I think it deserves publication.Reviewer #2:Drosophila. Using immunofluorescence, live imaging, FRAP, biochemistry, and genetic mosaic approaches, they provide evidence that Stbm is less stable and more mobile when phosphorylated, and conversely, more stable when unphosphorylated. In contrast to Stbm, Dsh was found to be more stable when phosphorylated. They also provide evidence that Pk negatively regulates Stbm phosphorylation. Their findings suggest that Casein Kinase Ie mediates Stbm phosphorylation, confirming other reports, and extend this finding by providing genetic evidence that Casein Kinase Ie phosphorylates both Stbm and Dsh independently. They propose a model for how modifying differential protein stability could be means to regulate sorting of PCP proteins.In this study, Strutt et al. investigate the role of phosphorylation in the establishment of planar cell polarity (PCP) in eLife.Mechanisms that regulate the establishment and maintenance of PCP is of high interest to the fields of polarity and developmental biology. Although Stbm/Vang and Dsh/Dvl have been known to be phosphorylated for some time, and that their phosphorylation is important for PCP, it was not known how phosphorylation regulates PCP protein dynamics and function. By providing further support that Casein Kinase Ie-mediates phosphorylation of Stbm and Dsh and by demonstrating that phosphorylation alters PCP protein stability and sorting, this study provides important and substantial contributions to the field. A strength of the study is the use of tissue extracts from transgenic and mutant lines to measure phosphorylation states (as opposed to transfected cells), but the reliance on very subtle band shifts as the sole means to detect phosphorylation is a weakness. The manuscript text is generally well written, however the data and figures could have been presented more clearly. While statistics used were appropriate and thorough, the quantification is often confusing and needs to be made more transparent. Though the findings are significant and impactful with some mechanistic detail, there are concerns that the work does not go far enough to extend current knowledge and has limited accessibility in its current state for the broad readership of Major comments:Drosophila genotypes used with direct reference of how they are labeled/referred to in figures their phenotypes would be very helpful.- Inclusion of a table of - No biochemical evidence is shown to support that direct binding of Pk to Stbm protects Stbm from phosphorylation .- Figure 1 lays the foundation for all subsequent figures and could be presented more clearly for a broader audience. For example, the schematic in A makes sense to a PCP specialist but needs more context for someone less familiar with the field. Zoomed images for E-F will help better visualize trichome orientation, and a reorganization of E-M to better pair panels of the same genotypes would help. Additionally, an overlay of polarity vectors for I-J would be helpful as Stbm asymmetry is subtle and not apparent to the untrained eye.- The authors state that "only small puncta were observed in Stbm phosphomimetic flies, and non-puncta material also increased . However, in the Stbm phosphomutant, Stbm still clustered into large puncta, despite the loss of asymmetry ." Quantification of the puncta sizes in Figure 1I-J and Figure 2A-D are lacking and necessary as many of the future conclusions rely on these observations.- Figure 2G-H is a critical piece of data to support the authors model that -P promotes sorting of opposite PCP complexes, and should be presented more convincingly. Panel H shows Diego localized to both sides of cell junctions in Stbm phosphomutants, suggesting PCP complexes of opposite orientations are mixed. According to the model, puncta in wild type flies represent sorted PCP complexes, but is this observed during intermediate stages of polarization? Diego is clearly segregated in the fully polarized control in panel G, but at earlier stages, do they see puncta along a single junction that are sorted in opposite orientations? This control would strengthen the argument that it is the sorting of opposite complexes within puncta that is defective in their mutants. According to the model, stbmS(AII)E complexes/puncta should be sorted and thus, that data should be included stbmS(AII)E phosphomimetic for G-H panels.- Figure 3. Stable to unstable amounts should be displayed separately to better see the changes, it is hard to compare the relative amounts as currently displayed .- Figure 5. The western blot bands in A demonstrating a shift in Stbm are not obvious. This is main evidence that Pk influences Stbm phosphorylation, but it's not wholly convincing. In general, detecting changes in -P solely by band shifts is a general weakness of the overall approach since these differences are very subtle, hard to quantify, and open to other interpretations. Although this is probably beyond scope of this paper, generating a phospho-specific Ab or performing mass spec analyses of -P sites would go a long way towards strengthening the results and lending support to the overall model.- The model in Figure 7 would benefit from inclusion of Dco. In addition, do the authors think that Pk destabilizes Fz via inhibiting Dco-dependent -P of Dsh?Reviewer #3:The manuscript by Strutt and colleagues addresses the mechanisms by which protein complexes become asymmetrically distributed on cell junctions, a process important for establishing planar cell polarity. The authors identified an important role of CK1 in phosphorylating core proteins and thereby regulating their clustering/membrane association. This work gives interesting new insights into the role that phosphorylation plays in establishing the asymmetry of core proteins at cell junctions. The manuscript is well written and the data are convincing for the most part. I have a few concerns, which I expect could be addressed within a reasonable time by the authors:stbm[6] mutants still express Stbm protein, i.e. do these stainings show Stbm[6] and phosphomutant Stbm or only the phosphomutant Stbm?Figure 1J, L The authors claim that in Stbm phosphomimetic flies only small puncta are observed, whereas in Stbm phosphomutant flies, Stbm clusters in large puncta. The puncta are not obvious from these images. Higher magnification images should be shown and puncta size needs to be quantified. Moreover, the authors should mention whether Figure 2G, H I can see that in the Stbm phosphomutant flies Diego forms "non-polarized" puncta, however, I do not see evidence that these puncta co-localize with Stbm, as the authors claim.Figure 3A. The authors should briefly explain the concept of the 'hub-and-spoke' FRAP methods, so that readers do not have to look up the reference in order to understand the experiment. Moreover, images of the FRAP experiment should be shown (e.g. in the supplement) to allow readers to evaluate the data.Figure 3 FRAP analysis allows to estimate the mobile fraction of a protein, and the authors use this method to show that phosphorylation of Stbm increases its mobile fraction. It is however, less clear how the authors infer from the FRAP analysis that phosphorylation suppresses clustering in complexes. While complex formation might be one mechanism to reduce the mobile fraction of a protein, it is not the only one. The authors should elaborate on this issue. Reviewer #2:[…] A strength of the study is the use of tissue extracts from transgenic and mutant lines to measure phosphorylation states (as opposed to transfected cells), but the reliance on very subtle band shifts as the sole means to detect phosphorylation is a weakness. The manuscript text is generally well written, however the data and figures could have been presented more clearly. While statistics used were appropriate and thorough, the quantification is often confusing and needs to be made more transparent. Though the findings are significant and impactful with some mechanistic detail, there are concerns that the work does not go far enough to extend current knowledge and has limited accessibility in its current state for the broad readership of eLife.Major comments:Drosophila genotypes used with direct reference of how they are labeled/referred to in figures their phenotypes would be very helpful.- Inclusion of a table of We have added a table of all genotypes associated with each figure.- No biochemical evidence is shown to support that direct binding of Pk to Stbm protects Stbm from phosphorylation .We have discussed other possible models for how Pk might regulate Stbm phosphorylation in the manuscript, but we found evidence arguing against the other models that we considered. We agree however that we don't have direct evidence for the idea that binding of Pk to Stbm protects Stbm from phosphorylation; this is why we put the associated model figure in the supplementary data rather than in the main manuscript. However we think it is useful to suggest hypotheses about the mechanism, as this is then a basis for future studies. In the future we will be looking for direct evidence for this model, but such experiments are beyond the scope of the current manuscript.- Figure 1 lays the foundation for all subsequent figures and could be presented more clearly for a broader audience. For example, the schematic in A makes sense to a PCP specialist but needs more context for someone less familiar with the field. Zoomed images for E-F will help better visualize trichome orientation, and a reorganization of E-M to better pair panels of the same genotypes would help. Additionally, an overlay of polarity vectors for I-J would be helpful as Stbm asymmetry is subtle and not apparent to the untrained eye.These are all good points, and we have added extra introductory panels to the first figure. The adult wings in  have been replaced with higher magnification images. We have also overlaid polarity vectors on the images in Figure 2 and Figure 2 supplements 1 and 2. Finally, we have also included higher magnification images of puncta in these genotypes, in response to reviewer 3.- The authors state that "only small puncta were observed in Stbm phosphomimetic flies, and non-puncta material also increased . However, in the Stbm phosphomutant, Stbm still clustered into large puncta, despite the loss of asymmetry ." Quantification of the puncta sizes in Figure 1I-J and Figure 2A-D are lacking and necessary as many of the future conclusions rely on these observations.number is similar in wild-type and phosphomutant; suggesting a similar degree of "punctateness"; while the phosphomimetic is less punctate. The amount of Stbm in puncta (puncta area multiplied by puncta intensity) is however slightly lower in both the phosphomutant and phosphomimetic. We think the smaller puncta size in phosphomutant and phosphomimetic may be due to the fact that negative feedback limits the growth of individual puncta (as seen in our FRAP experiments using Fmi-EGFP and Fz-EGFP).We have now included measurements of puncta number and size in Figure 2. We previously attempted to threshold images using Stbm immunolabelling, using the same threshold for wild-type and mutant regions of the same wing. However as overall junctional levels of Stbm increase in both the phosphomutant and the phosphomimetic, this was problematic and resulted in apparent increased values in both cases. We have now got round this issue by using Fmi immunolabelling to threshold the images: as Fmi co-localises with Stbm and junctional levels of Fmi do not change in the phosphomutants, this successfully identifies puncta without "spreading" into neighbouring non-puncta regions. The major finding is that puncta We have modified the manuscript to take into account these quantitations; in particular we have stated that the phosphomimetic forms fewer puncta rather than that it forms only small puncta.However, the main conclusion still stands: that the Stbm phosphomimetic clusters into puncta more readily than the phosphomimetic and thus the coupling between puncta formation and asymmetry is lost.- Figure 2G-H is a critical piece of data to support the authors model that -P promotes sorting of opposite PCP complexes, and should be presented more convincingly. Panel H shows Diego localized to both sides of cell junctions in Stbm phosphomutants, suggesting PCP complexes of opposite orientations are mixed. According to the model, puncta in wild type flies represent sorted PCP complexes, but is this observed during intermediate stages of polarization? Diego is clearly segregated in the fully polarized control in panel G, but at earlier stages, do they see puncta along a single junction that are sorted in opposite orientations? This control would strengthen the argument that it is the sorting of opposite complexes within puncta that is defective in their mutants. According to the model, stbmS(AII)E complexes/puncta should be sorted and thus, that data should be included stbmS(AII)E phosphomimetic for G-H panels.within puncta would be reduced; and that most puncta would contain complexes in both orientations rather than seeing puncta along a single junction that are sorted in opposite orientations.We have not looked at Dgo localisation at earlier developmental stages, but we speculate that the sorting would be less good than at 28 hr APF. We expect that sorting pk mutants, in which Stbm is hyperphosphorylated. In our model hyperphosphorylation promotes Stbm mobility and thus the puncta that do form are unstable. This means that complexes are continually forming and unforming and that complexes of the same orientation fail to accumulate. It would be interesting to test this directly, but we are unable to do the twin clone experiment with our current reagents, as P[acman]-stbmS[All]E, P[acman]-mApple-dgo and P[acman]-EGFP-dgo are in the same attP site.We also don't predict that individual Stbm phosphomimetic complexes/puncta should be sorted. Our data suggest that Stbm phosphomimetics behave like - Figure 3. Stable to unstable amounts should be displayed separately to better see the changes, it is hard to compare the relative amounts as currently displayed .We agree that it is not easy to compare the unstable amounts in the current graphs. However, if we plot stable and unstable amounts separately, we will "lose" the other important data regarding total intensity. We have however added extra supplementary figures for all FRAP data, showing the total intensity, stable amount and unstable amounts as separate plots.- Figure 5. The western blot bands in A demonstrating a shift in Stbm are not obvious. This is main evidence that Pk influences Stbm phosphorylation, but it's not wholly convincing. In general, detecting changes in -P solely by band shifts is a general weakness of the overall approach since these differences are very subtle, hard to quantify, and open to other interpretations. Although this is probably beyond scope of this paper, generating a phospho-specific Ab or performing mass spec analyses of -P sites would go a long way towards strengthening the results and lending support to the overall model.pk mutants is sensitive to phosphatase.We agree that the band shifts are subtle, and that is why we have shown duplicates of the critical samples. We have now also included an extra supplementary figure panel  in response to reviewer 1, to show that the decreased migration of Stbm in We also agree that phospho-specific antibodies would be nice, but also that this is beyond the scope of this paper. Furthermore, we note that other researchers have made phospho-specific antibodies  and it is difficult to get enough sensitivity on westerns in an in vivo context.- The model in Figure 7 would benefit from inclusion of Dco. In addition, do the authors think that Pk destabilizes Fz via inhibiting Dco-dependent -P of Dsh?We have added Dco to the model diagram .In our previous work, we proposed two mechanisms by which Pk could destabilise Fz. In the first, Dsh would normally protect Fz from endocytosis (e.g. by promoting multimerisation); and that Pk binding to Dsh could block this protective function. In the second mechanism, we proposed that binding of Pk to Fz/Dsh could lead to recruitment of an enzyme that mediates a change in post-translational modification of Dsh or Fz. In either model, we could envisage either a direct role for Dco  or indirect roles . However, we think we might be speculating beyond what the data can really support if we included such ideas in the manuscript.Reviewer #3:[…] I have a few concerns, which I expect could be addressed within a reasonable time by the authors:Figure 1J, L The authors claim that in Stbm phosphomimetic flies only small puncta are observed, whereas in Stbm phosphomutant flies, Stbm clusters in large puncta. The puncta are not obvious from these images. Higher magnification images should be shown and puncta size needs to be quantified. Moreover, the authors should mention whether stbm[6] mutants still express Stbm protein, i.e. do these stainings show Stbm[6] and phosphomutant Stbm or only the phosphomutant Stbm?We have now shown higher magnification images of the puncta in Figure 2 and Figure 2—figure supplements 1 and 2. We have also provided quantitations of puncta number and size (see response to reviewer 2).We have also clarified in the manuscript that the clones of the phosphorylation site mutants are generated in the absence of endogenous Stbm.Figure 2G, H, I can see that in the Stbm phosphomutant flies Diego forms "non-polarized" puncta, however, I do not see evidence that these puncta co-localize with Stbm, as the authors claim.We have now shown in Figure 3—figure supplement 1 that EGFP-Dgo co-localises in puncta with the other core proteins, in both a wild-type and a Stbm phosphomutant background.Figure 3A. The authors should briefly explain the concept of the 'hub-and-spoke' FRAP methods, so that readers do not have to look up the reference in order to understand the experiment. Moreover, images of the FRAP experiment should be shown (e.g. in the supplement) to allow readers to evaluate the data.We have added more explanation to the text to better explain the methodology. We have also added some example FRAP images  for the first experiment, and the entire FRAP datasets are in the source data.Figure 3 FRAP analysis allows to estimate the mobile fraction of a protein, and the authors use this method to show that phosphorylation of Stbm increases its mobile fraction. It is however, less clear how the authors infer from the FRAP analysis that phosphorylation suppresses clustering in complexes. While complex formation might be one mechanism to reduce the mobile fraction of a protein, it is not the only one. The authors should elaborate on this issue.We agree that in general a reduction in the mobile fraction of a protein can be caused by mechanisms other than complex formation; for instance other explanations could be reduced vesicular trafficking or tethering to another structure such as the cytoskeleton. However, our model is based not only on the FRAP data but on the fact that we see changes in cluster formation (puncta) in our images (now quantitated in the revised manuscript). Taken together, we think our current working model is the most plausible. We would prefer not to add further speculation to the Discussion, which is already quite long.


Infectious bronchitis (IB) is still a major problem among poultry industry in Indonesia, IB outbreaks continue to happen even in vaccinated flocks. The emergence of new IB virus (IBV) variants might lead to mismatching between vaccine virus strain and circulating virus strain, this may be a reason of vaccination failure. Information about circulating IBV in a region is important to decide which IB vaccine should be used. However, information about recent IBV strains which circulated in Indonesia and their genetic characters were limited; therefore, the aim of our research was to determine the genetic characterization of S1 gene of IBV isolated from commercial poultry flocks in West Java, Indonesia.A total of 47 viral isolate samples collected from chickens with clinical sign and reduced in egg production. Six IB live vaccines were used as control, the reference vaccines represent IBV strains including H120, H52, 4/91, CR88, 233A, and 1-96. Primers XCe2+ and XCe2- were used to amplify S1 gene partially.Twenty-six of 47 samples showed positive result to S1 gene of IBV by reverse transcription-polymerase chain reaction. Three IBV isolates, Indonesia/K233A31/18, Indonesia/K4A9/17, and Indonesia/P3/17, were selected for nucleotide sequencing. Phylogenetic analysis of 352 nucleotides of the partial S1 gene shows that isolates Indonesia/K4A9/17 and Indonesia/K233A31/18 have 100% homology with IBV vaccine strain 4/91, while isolate Indonesia/P3/17 has 100% homology with IBV vaccine strain 233A.Our result indicates that at least two IBV strains were circulating among poultry in West Java, Indonesia, which is IBV close to vaccine strain 4/91 and 233A. The present study provides updates on the circulating IBV in commercial poultry flocks in West Java, Indonesia, and might use as guidance on selecting a proper IB vaccine strain to improve IB vaccination efficacy in certain region. Coronavirus of Nidovirales order [Coronavirus is enveloped, non-segmented, single-stranded, and RNA’s positive sense, comprises approximately 27–32 Kb in size [Coronaviruses have four structural proteins, glycoprotein spike, matrix, nucleoprotein, and envelope consist of lipid bilayer and three glycoprotein M, S, and HE [Infectious bronchitis (IB) is a poultry disease caused by es order . Coronav, and HE . Amino a, and HE .IB is still a serious problem among poultry industry in Indonesia, the prevalence of the disease is 40–60% in Java Island . The varThe previous study showed that the majority of IBV strain isolated in Indonesia were related to Massachusetts (Mass) and Connecticut (Conn), and serotype N2/62 originated from Australia , IBV locHowever, limited information available about IBV strain circulating among poultry in Indonesia and its genetic character; therefore, the aim of our study was to determine IBV field strain and genetic characterization of S1 gene of IBV isolated from poultry in West Java, Indonesia, to provide an update on cocirculating IBV variants in this region.The present study was performed in accordance with the regulations for Research in Animal Health of Indonesian Law on Livestock and Animal Health .A total of 47 samples isolated from problematic flocks showing IB such as clinical symptoms and reduction in production were used in this study. The samples were collected from commercial poultry flocks in some district in West Java Province: Sukabumi (n=36), Cianjur (n=1), Tasikmalaya (n=4), Bogor (n=4), and Subang (n=2). The samples were organ, cloacal swab, and tracheal swab. Six IB live vaccines were used as positive control, the vaccine represents IBV strain H120, H52, 4/91, CR88, 233A, and 1–96.Viral RNA was extracted using the total RNA Mini Kit (Geneaid®), extraction procedure was based on manufacturer’s instructions. The RNAs were dissolved in 50 µl RNase-free water and directly used for subsequent reverse transcription-polymerase chain reaction (RT-PCR) or stored at −20°C.Partial S1 gene amplification using one pair of primer : Forward2O (MyTaq™ OneStep RT-PCR Kit) up to 45 µl, and 4 μl primer (400 nM). Amplification reaction was carried out with thermal profile at 45°C, 20 min RT 95°C, 1 min polymerase activation, then 40 cycles  followed by final extension 72°C, 7 min.The PCR amplification reaction was carried out in 50 µl containing 5 μl RNA template, 25 μl 2× MyTaq one step mix (1×), 0.5 μl RT, 1 μl Ribosafe RNAse inhibitor, DEPC-Hhttp://www.megasoftware.net) [About 30 µl each of RT-PCR product of amplified S1 sequenced using BigDye® Terminator version 3.1 Cycle Sequencing Kit  with forward XCE2+ and reverse XCE2−primer. These samples were sent for sequencing  and sequenced from both directions. The sample nucleotide sequence results are compiled, aligned, and compared with sequence of S1 gene of control positive and also with sequence data of S1 gene of published IBV available in the GenBank . Phylogeare.net) ,15.Twenty-six of 47 samples showed positive result to S1 gene of IBV by RT-PCR. These samples were isolated from three different farms in West Java; therefore, we choose three positive samples only, one viral isolate from each farm for further nucleotide sequencing analysis. These three isolates are Indonesia/K4A9/17 and Indonesia/P3/17 from Sukabumi, while Indonesia/K233A31/18 from Bogor.Nucleotide sequencing of 352 nucleotide partial gene S1 indicates that isolates Indonesia/K4A9/17 and Indonesia/K233A31/18 have 100% homology with IBV vaccine strain 4/91, while isolate Indonesia/P3/17 has 100% homology with IBV vaccine strain 233 A. Among these three IBV isolates, the deviation between Indonesia/K4A9/17 and Indonesia/K233A31/18 was 0%, while Indonesia/K4A9/17 and Indonesia/K233A31/18 deviate 0% to Indonesia/P3/17. Difference of S1 gene sequence between these three IBV isolates with other vaccine strain was 2–29% . There wThere are 11 nucleotide differences within three IBV isolates . Differewww.megasoftware.net) [The phylogenetic tree  of the aare.net) ,15, the et al. [Ronoharjo, in 1977, was the first who isolated IBV in Indonesia, a few years later Darminto in 1985 were able to isolated IBV . The emeet al. , and latet al. -19. TherThe spike protein or S1 subunit of S glycoprotein is the major determinant of IBV so that a minor change in amino acid sequence of this protein would transform the virus strain . ChangesBased on our partial sequence of S1 gene results, there are no substitutions in 894-nt and amino acid residue - 298. Partial nucleotide sequencing of S1 gene of IBV Indonesia/K4A9/17 and IBV Indonesia/K233A31/18 was 100% identical with vaccine strain 4/91, and IBV Indonesia/P3/17 was 100% identical to vaccine strain 233A. No mutation, insertion, or deletion detected in nucleotide sequence of IBV isolates in this study. An explanation could be that, this is resulted from reisolation of vaccine strain virus circulating in the susceptible host or there is high recombination of IBV genome during cocirculation of vaccine virus and field virus .Phylogenetic three showed that three IBV isolates were relatively close to IBV from the UK, Israel, and the USA, respectively. In Indonesia, a latest study about genetic characterization of IBV isolated by Dharmayanti and Indriani  showed tThe present study provides updates on the circulating IBV in commercial poultry flocks in West Java, Indonesia. Partial sequencing of the S1 gene revealed at least two IBV strains circulating among poultry in West Java, which is IBV close to vaccine strain 4/91 and IBV close to strain 233A. Based on phylogenetic three, these three isolates were relatively close to IBV from the UK, Israel, and the USA, respectively.RS performed the work designed by RDS and ONP. All authors contributed in writing and revision of the manuscript. All authors read and approved the final manuscript.


Warming in the Arctic is larger than the global average. A primary reason for this Arctic Amplification is the albedo feedback. The contrasting albedo of sea ice and dark melted surface areas is the key component of albedo feedback. Cloud coverage over the changing surface and the response of the clouds to the changing surface conditions will modify the change in planetary albedo when sea ice melts. Space-based lidar measurements provide a unique opportunity for cloud measurements in the Arctic. The response of clouds to the changing sea ice concentration was directly observed. Based on CALIPSO satellite observations of cloud properties, this study found that cloud coverage in ice-free regions in the Arctic linearly increased with the area of ice-free water during the melt seasons in the past 10 years, while sea ice coverage varies significantly year-to-year. The observations suggest that when sea-ice retreats, cloud fraction of the ice-free region remains fixed at nearly 81%. The high cloud coverage over melted areas significantly reduces the albedo feedback. These results indicate that space-based lidar cloud and surface observations of the Arctic can help constrain and improve climate models. This phenomenon, called the Arctic Amplification, has been confirmed by observations4 as well as model simulations5.Given the initial forcing due to the increase in greenhouse gases, through internal feedbacks the climate system adjusts itself to a new equilibrium state. The basic adjustment is higher Surface Air Temperature (SAT). Due to several feedback mechanisms, the SAT increase in the Arctic is 2–4 times larger than the global mean6, atmospheric and oceanic heat transports: transport of heat flux that warms the polar area7, cloud cover and water vapor that alter the longwave irradiance to the surface8, soot on snow, increased black carbon aerosol concentrations9. A positive feedback acts to amplify the initial perturbation such as the increasing temperature resulting from extra emission of carbon dioxide, while a negative feedback tends to dampen it. The quantitative contributions of the feedbacks are still being debated. By applying the coupled feedback response analysis method, model assimilation results show that the albedo feedback is the major contributor to the Arctic Amplification10, while the cloud feedback is the second largest contributor5. However, using the radiative kernel technique, Pithan et al.3 showed that the dominant contributor is the temperature feedback (low latitude areas emit more longwave radiation to space than the polar areas for the same temperature increase because low latitude areas have a higher basic temperature), and that the albedo feedback is the second largest contributor. Model simulations indicate that the Arctic Amplification may still occur without the albedo feedback2.The mechanisms responsible for the Arctic Amplification include: Albedo feedback due to changes in sea ice extent11. The minimum sea ice extent, in September, has a trend of −11.4% per decade from 1979 to 2007 and the decline is accelerating12. The sea ice has been retreating the fastest in the Kara Sea, Barents Sea, and Beaufort Sea regions13. As the sea ice melts and ponds form, the albedo decreases greatly. The darker water surface absorbs more solar energy than the sea ice or snow covered surface. The extra absorbed energy will enhance the sea ice melt. This process is well known as the albedo feedback, which is a positive feedback mechanism contributing to the Arctic Amplification. Based on the radiative kernel technique14, a quantitative assessment of the albedo feedback’s contribution to the amplification is provided by the model3. However, observational assessment of and constraint to the albedo feedback are still lacking.With the increase in SAT over the last several decades the sea ice extent in the Arctic has retreated significantly15. A loss in sea ice extent of 0.1 Mkm2 is estimated to result in a 10–20% increase in moisture content in the Arctic16. Arctic regions with more sea ice are found to have a smaller cloud fraction and a smaller cloud liquid water content17. On average, clouds cool the Arctic from February to November through the shortwave forcing and warm the Arctic all year around through the longwave radiative forcing18. Detailed radiative effects in polar areas are complex and may vary from negative to positive due to the high frequency of temperature inversions. The response of clouds to sea ice retreat may have significant impacts on the radiative energy balance in polar regions. Because of the comparable albedo of sea ice and cloud, a change in cloud cover in response to an increase in open water during the melt period may significantly affect the radiative energy balance by adjusting the albedo feedback process.The climate system continually adjusts itself to the change in sea ice extent. The sea ice layer acts as a thermal and water vapor insulator between the atmosphere and the underlying water. As the ice layer becomes thinner and ponds grow, the exchange of water vapor and heat between the air and ocean increases. On the other hand, the water vapor evaporation will increase as the SAT increases if we assume fixed relative humidity over the open water. Reduction in sea ice will lead to increased heat and moisture fluxes from the ocean surfaceδTs) to the climate system, the system tends to adjust itself through a variety of feedback processes. For example, the net TOA flux . The radiative kernel can be used to assess climate feedbacks consistently across models. For example, the contributions from a variety of feedbacks to the Arctic Amplification were examined by comparing radiative kernels consistent results produced by climate models3. However, radiative kernels are generally obtained from model simulations. The anomalies of SIC and radiative forcing at TOA provide us with an opportunity to calculate the radiative kernel from observations obtained by space-based sensors.Given an initial perturbation  albedo is due to reflection from both the surface and the atmosphere. On a global scale, the atmospheric reflection contributes about 88% of the planetary albedo20. In the Arctic, the response of clouds to the change in sea ice extent, snow cover, and melt pond fraction will impact the TOA albedo, and hence the final contribution of the albedo feedback to the Arctic Amplification.Due to sea ice , the Arctic Ocean has an albedo of about 0.6521. The climate effects of sea ice and clouds have been intensively studied for several decades. Recent studies confirmed that the sea ice retreat has had a significant impact on the Arctic cloud cover. Arctic clouds can be influenced by the large scale atmospheric circulation, near surface stability and surface conditions22. The cloud properties differ significantly between meteorological regimes23. Synoptic regimes, such as the warm advection, cold advection, can impact clouds at different heights and influence the date of sea ice melt onset24.Both sea ice and clouds play essential roles in the climate system, and their longterm variations are the primary indicators of climate change17. Liquid clouds respond to the sea ice variability except during summer25. Results obtained from passive sensors show that low clouds can form over newly formed open water during early fall22. Based on simulations, Abe et al.26 found that the cloud fraction increased with the retreat of sea ice and that the increase in cloud cover would enhance the longwave warming. The minimum sea ice extent in 2012 was followed by a decrease in cloud cover in winter27, which may have led to a cooling of the surface and an increase in sea ice extent the following year. Hence, changes in cloudiness can potentially influence the sea ice extent28.Clouds and sea ice have a significant covariance under stable conditions29. By applying active sensors, combined CALIPSO and CloudSat observations can overcome the shortcomings of cloud products provided by passive observations in the polar regions. To this end CALIPSO and CloudSat measurements are used to study the cloud-sea ice-climate feedback: the feedback due to sea ice retreat and the response of clouds to the sea ice retreat.In this paper, we investigate the response of summer and early fall cloud cover to changes in sea ice extent and its impact on the shortwave and longwave radiation budget. Due to frequent temperature inversions and small temperature contrast between the surface and cloud in the Arctic, passive sensors have limited ability to detect clouds in the polar regions30. Several factors contribute to the variation in SIC and their impact depends on location. Focusing on the sea ice coverage, the Arctic can be divided into 3 different sections: the open water section, the permanent ice covered section, and the transitional section. Due to oceanic heat transport in the Atlantic section of the Arctic, the Greenland Sea, the Fram Strait, the Barents Sea, and the Kara Sea are open most of the year. The open water section is defined by the area with average SIC less than 20%. Surrounded by the continents and islands, the relatively closed portion of the Arctic Ocean  has average SIC greater than 90%. The section with average SIC greater than 90% is called “permanent ice covered” section. The transitional section of the Arctic Ocean has SIC varying from 20% to 90% with distinct seasonal variation, and it also exhibits significant inter-annual variations. These SIC variations have a considerable impact on the cloud coverage.In the context of global warming and significant sea ice retreat, both sea ice thickness and concentration show a regionally dependent variability25. The covariance of the sea ice anomaly and the cloud anomaly confirms the response of cloud cover to the change in sea ice. Based on 10-year observations, the covariance has different patterns. The directions of the cloud anomaly are mostly opposite to those of the sea ice anomalies for most years and regions. For example: the Beaufort Sea area, which has a strong positive sea ice anomaly, shows a negative cloud anomaly in 2006. The contrasting cloud and ice anomalies are distinctly regionally dependent in 2007, 2008, 2012, and 2014. Only part of the transitional section shows opposite cloud and sea ice anomalies in 2006, 2009, 2010, 2011, 2013, and 2015. Areas that have negative sea ice anomalies do not always have positive cloud anomalies and vice versa. For example, both the cloud and sea ice have positive anomalies in the East Siberian Sea area in 2009 and 2010, where the cloud and sea ice anomalies are negative in the Laptev Sea area in 2011 and around the Sevemaya Zemlya area in 2012.The mean SIC in the melt season, taken to be from July 1 to September 15 in this paper, is used to represent the sea ice coverage for a given year. Focusing on the anomaly of the mean SIC, calculated by subtracting the areal average from 2006 to 2015, we find that the mean SIC departs from the average, and that the anomalies show regional and inter-annual variations. The SIC anomalies of 2006 and 20015 are shown in Fig. On average, the uncertainty of the cloud fraction is 5% at the 95% confidence level in absolute units. In seven of ten years, the maxima of the cloud anomaly can exceed the uncertainty. However, the cloud anomalies in 2009, 2011, and 2014 are not significant as their values are smaller or comparable to the uncertainty. The cloud anomalies are heterogeneous even over a large portion of the ice anomaly area. In 2012, the ice anomaly is negative from the Beaufort Sea to the Laptev Sea area where the cloud anomaly is positive but with some negative spots.a for the correlation and b for the significance). About 40% of the area does not show significance in the correlation. The correlation coefficients are within the range between −0.4 and 0.4. Most of the area shows negative correlation, which means that cloud cover increases as the sea ice retreats. A part of the Arctic Ocean shows a positive correlation. The significant negative area includes the East Siberian Sea and the Beaufort Sea. The most significant positive area is the Kara Sea.Based on the ten years of observations, the Pearson correlation coefficient and the correlation significance are shown in Fig. 25 once again. The correlation coefficients between the sea ice anomaly and cloud anomaly are negative in most areas but positive in some areas. The region of negative correlation is more significant than the positive area. The nonuniform regional covariance reveals that the response maybe influenced by other factors such as atmospheric circulation. The significant but nonuniform response of clouds to the sea ice retreat may influence the albedo feedback. The time lag between cloud formation and the enhancement of evaporation is considered in the investigated periods of sea ice and cloud correlation. The sea ice anomaly is based on the average over the melt period from July 1 to September 15. The cloud anomaly is based on the average over the period from August 15 to October 15 which is later than that of the sea ice.Overall, the geographic distribution of the covariance between clouds and sea ice confirms the response of clouds to the sea ice lossAs the surface changes during the melt period from snow-covered sea ice to partially snow- melt pond-covered sea ice to totally open water, the albedo of this heterogenous surface will decrease. Because the cloud albedo lies between the albedo of snow and the albedo of dark open water, an increase in cloud cover due to loss of sea ice coverage is expected to partly compensate for the associated albedo decrease and tend to restore the TOA albedo during the sea ice melt period to the pre-melt value. The planetary albedo is determined by reflection from both the surface and the atmosphere. Under clear sky conditions, the TOA albedo is primarily determined by the surface condition. The albedo anomalies, calculated by subtracting the areal average from 2007 to 2010, under clear sky conditions, shown in Fig. However, the TOA albedo anomaly for all sky conditions, shown in Fig. : 2008, iUnder clear sky conditions, the TOA albedo is determined by the surface and the albedo anomalies are coincident with the anomaly of SIC. Under all sky conditions, the TOA albedo is determined by clouds and the surface. The modification of cloud cover in response to sea ice retreat will affect the TOA albedo anomaly.Clouds primarily scatter (and reflect) shortwave radiation and primarily absorb longwave  radiation. Clouds re-emit the absorbed radiation at the effective cloud temperature, which (except for temperature inversions) is usually lower than the surface temperature. The cloud is negatively related to the SIC at part of the Arctic area. When sea ice retreats, more clouds are expected to form and have radiative effects: (i) increase the solar energy reflected to space and thereby cool the atmosphere (surface), and (ii) reduce the outgoing longwave radiation which warms the surface. The net radiative effect of clouds may change from warming to cooling due to frequent temperature inversions and low solar elevations in the polar regions.2 anomaly in shortwave TOA irradiance in the Kara Sea and Laptev Sea areas. The Beaufort Sea area, which has a 8–10% smaller cloud fraction than the longterm average, shows a negative anomaly of 4–10 W/m2 in shortwave TOA irradiance.The cloud forcing anomalies of the TOA reflected shortwave irradiance are shown in Fig. 2 reflected to space compared to the longterm average  positive anomalies of the longwave radiative forcing. The cloud forcing anomalies of the TOA longwave radiation are negative (over −5%) in the Laptev Sea area which has a positive cloud fraction anomaly (2–5%).In addition to the reflection of sunlight, clouds also act as effective longwave absorbers/emitters that redistribute the longwave radiation. More cloud cover means less longwave radiation emitted to space and vice versa. Figure 2 negative cloud forcing anomaly of TOA longwave radiation. A positive cloud fraction anomaly occurs in the Laptev Sea and East Siberian Sea in 2007 and in the Beaufort Sea in 2008 where a total (shortwave and longwave) extra irradiance of up to 35 W/m2 escapes to space. A negative cloud fraction anomaly occurs in the Beaufort Sea in 2007 and in the Laptev Sea in 2008 where a total irradiance of 10–25 W/m2 escapes to space. The strength of ice albedo feedback in the climate system can be represented by a feedback parameter defined as14:δR is the change of TOA cloud radiative forcing, δσ is the change of the sea ice loss given a perturbation in the surface temperature δTs. The first part of the right hand side in Eq.  in the Laptev Sea which shows a strong positive cloud forcing anomaly (2–4%) of the TOA longwave irradiance. A positive cloud fraction anomaly (2–5%) occurs in the Beaufort Sea which has up to −5 W/mThe neutral cases which have anomalies less than 8% are discarded to avoid the small number problem which means divided by a small number to produce unstable cases. The cases in the distribution range greater than 3 times of deviation are also discarded. These values represent the situation that sea ice anomaly not exceed 20%. Limited by the length of the CERES, CALIPSO, CloudSat, and MODIS (CCCM) merged dataset used in this study (see the “Method” section of details), the radiative kernels are based on observations from 2007 to 2010.The albedo is determined by the surface type, the clouds above the surface and the response of clouds to the surface change. The response of clouds to the surface change shows regional variability as shown in Fig. We define a sensitive zone as one having a significant variation in SIC during the time period analyzed: July through October. The closed section of the Arctic, which is surrounded by the continents of Asia and North America and the islands of Greenland, Svalbard, and Franz Josef’s Land, is different from the Atlantic section of the Arctic. The ocean currents have a huge impact on the Atlantic section of the Arctic Ocean which consist of open water most of the time. However, the closed section of the Arctic experiences significant variation in sea ice extent. Figure A frequently used indicator of sea ice coverage is the minimum sea ice extent which occurs in September. Considering the effect of time evolution of melt and freeze up, we use the average sea ice extent from August 15 to October 15 to examine its relation to cloud cover. On the other hand, to take into account the lag between cloud formation and enhanced evaporation after sea ice melt, the average cloud fraction during the period from August 1st to October 30th was used in this part of study.a) of Fig. 2 in absolute value and 21% compared to the minimum sea ice extent in relative value. The correlation coefficients between clouds and SIC change from positive to negative Fig. The time series of the average cloud fraction (after detrending) and the average sea ice extent (after detrending) during the summer and autumn from 2006 to 2015 are shown in part (b) of the Fig. 2 which equals to the uncertainty of 15% in the cloud fraction. The high coverage over the melted dark water can compensate about 81% of the albedo-feedback in the Arctic Ocean area.Since the average cloud fraction only show weak relation to the change of sea ice extent, it is expected that a high percentage of melted areas, where pixels have SIC values smaller than 15%, to be covered by clouds. The statistical relation of the melted area and the melted area that is covered by clouds is shown in the right panel %. The albedo feedback is typically explained as the tremendous change in albedo occurring when the surface changes from snow or sea ice to open water. However, the dark melted (open water) areas are frequently covered by clouds. A cloud fraction of 81% over the melted areas can reduce the sea-ice/snow albedo feedback. We can conclude that: the high cloud coverage over the melted water dominates the albedo change in the albedo feedback process. On average, the extra cloud cover stimulated by sea ice loss is of second-order contribution.The cloud fraction shows a likely response to the variation in sea ice extent, but with outliers on a decadal time scale. The fluctuation of the average cloud fraction is within the uncertainty of the cloud fraction25.Previous studies were aimed at revealing the interactions of cloud cover, sea ice concentration, radiative heating and weather conditions. Weak but significant covariance between cloud cover and sea ice exists in different atmospheric regimesThe new insights provided in this paper include the response of clouds to the melting sea ice revealing that the cloud coverage over the melted area remains a constant of about 81%. The polar area has components of a melted portion, frozen portion and a portion in melting or freezing. Melting or freezing areas with SIC values in the range from 1 to 0.85 may have different cloud coverage. The average cloud fractions over the sensitive zone are about 82% to 85%, which are slightly higher than the cloud fraction over the melted area. The open surface area is expected to have more clouds than the freezing up area. Most probably, melting or freezing areas have the highest cloud coverage. For the melted area in the sensitive zone, it is evident that the melted area has a cloud fraction of 81%. This huge cloud coverage over the melted or melting dark water surface can also moderate the effects of albedo feedback. Both the large cloud fraction and the response of clouds to the melting of sea ice can contribute to the smaller TOA albedo change relative to the clear sky.32, air quality33, and the occurrence of extreme weather events36. Potentially, this cloud damping effect mechanism can enlighten the study of “white Arctic versus blue Arctic” concerning diverging stakeholder responses to environmental change37.The new findings give the areal distribution of the cloud response to variation in SIC. The covariance between cloud cover and sea ice is evident and statistically significant in portions of the Arctic. Based on the change of sea ice and clouds, we provided an observational radiative kernel of sea ice albedo feedback for the first time. These new findings may also improve our ability to correctly capture feedbacks in climate models and lead to more accurate simulations of climate in the Arctic, and its impact on the global climate affecting agriculture productivity39. The dataset covers the period from July 1, 2006 through April 30, 2011. The data from different platforms are collocated at the CERES 20-km near-nadir footprint. Radiation information used in this paper is provided by the CERES Single Scanner Footprint TOA/Surface Fluxes (SSF) dataset, including the shortwave irradiance (0.3–5 μm), Earth emitted longwave irradiance (4–40 μm).The synthesized information on radiation, cloud and surface conditions is investigated over the summer and early fall to examine the response of clouds to the sea ice retreat and to quantify the response. The joint description of the radiation field and cloud information is based on an integrated CERES, CALIPSO, CloudSat, and MODIS merged (CCCM) dataset. These data were obtained from the NASA Langley Research Center Atmospheric Science Data Center (ASDC). The advantages and the accuracy of the cloud and radiation products in the CCCM dataset were discussed by Kato and co-workers41, while the Cloud Profiling Radar (CPR) deployed on CloudSat, is sensitive to (liquid and ice) water particles. The sky is regarded to be overcast when a cloud is detected by CALIPSO or CloudSat.Cloud information is obtained from joint CALIPSO and CloudSat observations. The CALIOP laser deployed on CALIPSO is sensitive to ice particlesν is defined in terms of energy per unit area per unit time as42:Iν [sw and lw stand for the shortwave and longwave spectral ranges, respectively. In terms of the cloud fraction Fcl is the clear sky irradiance, and Fov is the cloudy (overcast) sky irradiance. The cloud radiative forcing is expressed as: Based on observations of cloud fraction and irradiances, we can calculate the TOA albedo and the cloud radiative forcing. The net irradiance at frequency F+ is the spectrally integrated upward shortwave irradiance at the TOA, Fs is the incoming solar irradiance ) at TOA, and θ0 is the solar zenith angle.The albedo is calculated by:2. The SIC data used in this paper are obtained from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave observations available at the National Snow and Ice Date Center (NSIDC)43. The SIC data have a resolution of 25 × 25 km with the EASE-Grid 2.0 projection. The grid data are available at NSDIC. When the surface has a SIC value greater than 85%, the surface grid box is regarded to be sea ice covered. The sea ice extent is obtained from the Multisensor Analyzed Sea Ice Extent - North Hemisphere (MASIE-NH) daily value dataset, which is also available at the NSIDC.The status of sea surface is represented by the SIC and sea ice extent. SIC is defined by the percentage of the area that is covered by the sea ice at a given point in the ocean. 0 means totally open water and 1 means totally covered by the sea ice. Sea ice extent means the total area that has SIC greater than 85% in the unit of Mkm44. For each grid point, we average the data over a 3° (latitude) × 8° longitude box and over a period of nine days to reduce the sampling uncertainty and smooth out the character of weather since most of the weather processes are short than nine days. Then an average over the investigated period is used to represent the value of the year. By subtracting the 4-year (2007–2010) areal average from the value of the year, we get the anomaly distribution.All irradiances, albedo values, and cloud fractions are gridded to the average on the EASE-Grid 2.0 25 km gridsThe CALIPSO level 2 cloud layer product with 5 km resolution (version 3) is used to verify the response of clouds to the retreat of sea ice on a decadal time scale from 2006 to 2015). The data are available at ASDC. The average cloud fraction is calculated over the sensitive zone which is defined in Fig.  to 2015.The data are being detrended by subtracting a linear fitting to remove the longtern trend in the process of time series and regression relation in Fig. In Figs


The expressed protein was purified by Ni2+-affinity chromatography, and showed muralytic activity when measured with 4-methylumbelliferyl-β-D-N,N′,N″-triacetyl chitotrioside as substrate. Addition of purified Rpf-1 to R. erythropolis culture efficiently improved bacterial cell growth. The purified protein also increased resuscitation of viable but nonculturable cells of R. erythropolis to culturable state. The conserved amino acid residues including Asp45, Glu51, Cys50, Thr60, Gln69, Thr74, Trp75 and Cys114 of the Rpf-1 were replaced with different amino acids. The mutant proteins were also expressed and purified with Ni2+-affinity chromatography. The muralytic activities of the mutant proteins decreased to different extents when compared with that of the wild type Rpf-1. Gln69 was found to play the most important role in the enzyme activity, substitution of Gln69 with lysine (Q69K) resulted in the greatest decrease of muralytic activity. The other amino acid residues such as Asp45, Glu51, Cys50 and Cys114 were also found to be very important in maintaining muralytic activity and biological function of the Rpf-1. Our results indicated that Rpf-1 from R. erythropolis showed muralytic activities and weak protease activity, but the muralytic activity was responsible for its growth promotion and resuscitation activity.Resuscitation-promoting factors (Rpf) are a class of muralytic enzymes, which participate in recovery of dormant cells and promoting bacteria growth in poor media. In the present study the expression vector of the  Clostridium and Bacillus have adopted sporulation as a means of surviving adverse environmental conditions   , secretoMicrococcus luteus rpf are widely spread among high G+C Gram-positive bacteria  medium at 30 and 37 °C respectively. All chemical reagents were analytical grade.The bacteria strains and plasmids used in this work are listed in analysis . R. erytrpf-1 gene of R. erythropolis KB1, a specific pair of primers  was designed based on the sequences of rpf-1 gene of R. erythropolis KB1. The pUCm-T vector containing the rpf-1 gene of R. erythropolis KB1 was used as a template. The PCR reaction condition was as follows: 98 °C for 5 min, one cycle; 98 °C for 10 s, 55 °C for 15 s, 68 °C for 90 s, 35 cycles; with a final extension at 72 °C for 10 min. The PCR product was purified and digested with HindIII and EcoRI, it was then inserted into the pET-32a (+) vector  digested with the same enzymes. The constructed ligation product pET-32a (+)-rpf-1 was transformed into E. coli DH5α and then into E. coli BL21 (DE3).To construct the expression vector of the E. coli BL21 (DE3) containing the pET-32a (+)-rpf-1 were inoculated into 100 mL LB medium supplemented with ampicillin antibiotics and cultivated at 37 °C overnight, it was then added to 1,800 mL of the same LB medium, continued to grow to an OD595nm of 0.6 and were induced with 0.8 mmol/L isopropyl-β-D-thiogalactopyranoside (IPTG) at 25 °C for 3 h. The bacterial broth was placed in centrifuge tubes and centrifuged at 8,500×g for 20 min at 4 °C, and the bacterial cells were collected and re-suspended in 50 mL of lysis buffer . The mixture was then sonicated with Ultrasonic Processor  in an ice bath . The broken cell solution was then centrifuged at 8,500×g for 20 min at 4 °C. The supernatant was collected and filtered through a 0.22 μm sterile filter . The recombinant protein was purified with Ni2+-affinity chromatography  according to the manufacturer’s instructions and analyzed by SDS-polyacrylamide gel.The rpf-1 gene sequence of R. erythropolis KB1 was analyzed and compared with those of the related bacteria. The hypothetical conserved amino acid resides for the enzymatic activities were selected and the encoding cordons corresponding to each of the conserved amino acid residues were substituted with those of the other amino acids. The sequences containing the site-directed mutagenesis were commercially synthesized by Sangon Biotech . Each mutation was confirmed by nucleotide sequence analysis. The sequences containing the site-directed mutagenesis were listed in E. coli BL21 (DE3). The mutant proteins were expressed and purified in the same way as described above.The SDS-PAGE on 12% acrylamide gels was performed as described by −1) was added to 300 μL of 22 μM Mcllvaine’s phosphate buffer . The mixture was then incubated at 37 °C for 30 min. Three mL of 0.3 M glycine/NaOH buffer (pH 10.6) was added to the mixture. The fluorescence intensity was detected with Varioskan LUX Multimode Microplate Reader  using excitation wavelength of 360 nm and a read-out of 455 nm. The result was compared with a standard curve of standard substance 4-methylumbelliferone. One unit of enzyme activity was defined as the amount of enzyme that generates 1.0 nmol of the product in 1.0 mL of reaction solution per minute.To determine muralytic activity of the recombinant Rpfs, the artificial fluorogenic substrate, 4-methylumbelliferyl-β-D-N,N′,N″-triacetylchitotrioside (4-MUF-3-NAG)  was used and the enzyme activity was analyzed as reported before . Briefly2+, Ca2+, Zn2+, Co2+, dithiothreitol (DTT), phenylmethanesulfonyl fluoride (PMSF), ethylene diamine tetra acetic acid (EDTA) and ethylene glycol tetra acetic acid (EGTA) were added to the reaction mixtures respectively. The mixtures were then incubated at 37 °C for 30 min and the muralytic activities were determined.To determine the effect of metal ions and chemical agents on enzyme activities of the recombinant Rpf-1, Mg−1), 0.1 mL of the enzyme solution and 0.4 mL of DDW. The mixture was incubated for 20 min at 25 °C. Then 3.5 mL of 5% trichloroacetic acid was added to the mixture and centrifugated at 2,000×g for 5 min. The supernatant was collected and mixed with 4.5 mL of 0.5 M NaOH, the optical density was determined at 440 nm (OD440). One unit of protease activity was defined as the amount of enzyme producing an increase of 0.001 OD440 under the conditions.Protease activity was determined with azocasein as substrate by the method of Kreger and Lockwood . ReactioR. erythropolis cells were grown in LB broth at 28 °C with shaking at 150 rpm overnight. The bacterial solution was then inoculated to 500 mL of LB broth and cultured at 28 °C. One mL of the bacterial culture was removed regularly at an interval of 4 h and the cell growth was monitored at a wavelength of 595 nm using an UV-2102PC UV-VIS spectrophotometer . To determine the effect of the recombinant Rpfs on the growth of R. erythropolis KB1, the purified proteins were added to the bacterial solutions and cultured under the same conditions. The OD595nm of different groups were detected.R. erythropolis cells were grown in LB broth at 28 °C overnight. The bacteria solution was harvested by centrifugation at 5,000 rpm at 4 °C for 10 min and washed three times with normal saline. The washed cells were then inoculated into 500 mL of steriled normal saline and maintained at 4 °C without shaking to induce the VBNC state. A total of 100 μL of the bacteria solution was removed regularly and the culturable cells were estimated by plating 0.1 mL of the samples on LB agar plates.The R. erythropolis cells from the stressed state, the purified recombinant Rpf-1 was added to the stressed cell samples. The mixtures were then incubated at 28 °C and the culturable cells were estimated by plate count method. All experiments were performed in triplicates.The recovery of the cold stressed cells was analyzed as reported before. Briefly, five mL of the bacteria solution was removed from the flask which had been kept at 4 °C for more than 1,350 days, and yeast extract was added to the solution at a final concentration of 0.025% (w/v). The bacteria cell mixture was then incubated at 28 °C and the culturable cell counts were estimated by plating 0.1 mL of the samples on LB agar. To determine effect of the recombinant Rpf-1 on the recovery of rpf-1 gene of R. erythropolis KB1 consisted of 564 bp which encoded a polypeptide of 187 amino acids. The similarities with Rpf-1 of Micrococcus luteus and RpfC of Mycobacterium tuberculosis were 26.11% and 28.24% respectively. The polypeptide contained the Rpf domain of about 70 amino acids, in which a conserved glutamate (Glu51) and two highly conserved cysteine residues (Cys50 and Cys114) were found. But the LysM domain was not found, it did not contain signal sequence either. The rpf-1 gene was inserted into pET-32a (+) to construct an expression vector pET-32a (+)-rpf-1, which was then transformed into E. coli BL21 (DE3) and expressed by introducing with IPTG at 25 °C. The recombinant Rpf-1 was purified by Ni2+-affinity chromatography from the whole-cell lysate preparation. The purified recombinant protein showed a single band with a mass of 37 kDa on SDS-PAGE, which corresponded to the deduced molecular weight of the Rpf-1 (18.80 kDa) and the fusion protein Trx-His-S tag of pET-32a (+)  . The Wes-32a (+) . The rectwo fold .Micrococcus luteus, RpfA-E of Mycobacterium tuberculosis and of S. coelicolor, and lysozyme C from animals, a total of seven highly conserved amino acid residues of the Rpf-1 of R. erythropolis KB1 were selected and substituted with other amino acids. The mutant proteins were expressed in E. coli BL21 (DE3) and purified with Ni2+-affinity chromatography. The purified mutant Rpfs showed single bands with the molecular weight of approximately 37 kDa on SDS-PAGE (50 and Cys114 (C50G+C114T) inhibited maximally the activities (86.68%). When the glutamine in position 69 was substituted with lysine (Q69K) the activity was greatly decreased (86.11%). However, the substitution of the tryptophan in position 75 with valine (W75V) increased the activity by almost two times.Based on the sequence alignments with Rpfs of the other bacteria, including the Rpf of SDS-PAGE , which wSDS-PAGE . For exaR. erythropolis KB1 cultures to determine the effect on the growth of the bacteria cells. As seen in R. erythropolis KB1 cells from 24 to 12 h. The growth rate reached the maximum in 48 h, and the promoting effect was correlated with the amount of the Rpf-1. The growth abilities were increased for 301.70% and 382.28% respectively in 48 h by addition of 10 nmol and 100 nmol of the recombinant Rpf-1. The biological activities of the Rpfs were found to be correlated with its muralytic activities. Addition of the recombinant Rpf-1 mutant with W75V increases the growth more effectively when compared with that of the equal amount of the wild type Rpf-1. The growth rates of the bacterial cells added with the wild-type Rpf-1 and mutant Rpf with W75V were 316.18% and 347.22% respectively when compared with that of the control group, with the maximum growths in 48 h. The growth level of the mutant Rpf with E51A group decreased slightly when compared with that of the wild-type group. Addition of the Rpf mutants with the C50G+C114T and Q69K showed less effects on the cell growth (from 105.72–151.45%), with the log phases of about 24 h. The growth rates of the mutants with C50G+C114T, D45A+E51K and the control groups reached to the maximum in 72 h , which was in the position 54 of the Rpf protein from Micrococcus luteus. The two highly conserved cysteine residues (Cys50 and Cys114) were also found in the Rpf-1 protein. The catalytic aspartic acid residues (Asp70) of the C-type lysozyme  and the catalytic threonine residue (Thr50) of the lysozyme of E. coli (45 and Thr60). The purified recombinant protein showed a 37 kDa band on SDS-PAGE, which corresponded to the deduced molecular weight of the Rpf-1 and the fusion protein Trx-His-S tag of pET-32a (+). The purified recombinant protein showed muralytic activity. The muralytic activity was not affected with 0.1 mM of Ca2+, Mg2+ and Co2+, DTT, EDTA, EGTA and serine protease inhibitor PMSF, but 0.1 mM of Zn2+ increased the enzyme activity by almost two times. In order to confirm the muralytic activity was produced by the recombinant Rpf-1 protein, we also purified and detected the enzyme activities of the purified Trx-His-S tag protein expressed by the empty vector pET-32a (+) under the same conditions, which showed no muralytic activity and biological activities  or lysine (E54K) essentially suppressed the enzymatic activity. Substitution of either Cys53 or Cys114 separately resulted only in partial loss of the activity, but substitution of both amino acids caused virtually complete inactivation of Rpf. The disulfide bond formation between the conservative cysteine residues of RpfC of Mycobacterium tuberculosis was recognized to support and modulate the catalytic domain conformation during catalysis by using NMR analysis  inhibited maximally the activities, and replacement both of the Asp45and Glu51 (D45A+E51K) greatly suppressed the enzymatic activities, which was consisted with the Rpf of Micrococcus luteus. But substitution of the conserved Glu51 with alanine (E51A) resulted only in partial loss of activity. According to the modeling and the structural data, residue Gln72 would be accessible within the active site cleft and might potentially be involved in the interaction of Rpf with its substrate. The Q72K replacement reduced muralytic activity against Micrococcus luteus cell walls by about 50.00%. But the muralytic and physiological activities of a protein bearing both Q72K and E54K alterations were not more significantly attenuated than those of the E54K mutant. We found that the Gln69 play very important roles and substitution of Gln69 with lysine (Q69K) resulted in the great decrease of the muralytic activity. Substitution of Trp60 with valine (W60V) had little effect on the enzymatic activity. While substitution of Trp75 with valine (W75V) increased the activity by almost two times, which showed the very important roles of this amino acid in enzymatic activities.Our results also showed that substitution of the two cysteines CysR. erythropolis KB1 and reduced the logarithmic phase from 24 to 12 h. And the mutant Rpfs have different growth promoting effects on R. erythropolis KB1. The promoting effect was showed to be correlated with amounts of the Rpf-1. The biological activities of the Rpf-1 were also found to be correlated with its muralytic activities. The mutant Rpfs with low muralytic activities also decreased growth promoting effects and recovery of the bacteria cells from VBNC state. For example, the biological function of the mutant Rpf with substitutions of Cys50 and Cys114 (C50G+C114T) was greatly reduced when it was added to the R. erythropolis KB1 cells. The highest growth promoting effect was founded in the wild type Rpf-1 and the mutant proteins with Trp75, while the lowest promoting effects were founded among the substitutions of Asp45+Glu51 and Cys50+Cys114.The purified recombinant Rpf-1 could efficiently stimulate the growth of 51, Gln69, Thr74, Trp75, Asp45+Glu51, Cys50+Cys114 with other amino acids lost their protease activities. Only the mutant protein with Thr60 retained 95.90% of the protease activity of the wild-type protein. The protease activity did not show obvious correlation with the growth promoting and recovery activities. The mutant of Thr74 still retained the most growth promoting effect, although its protease activity was lost completely. It has been reported that the RpfB of Mycobacterium tuberculosis had a partner RipA (Resuscitation promoting factor interacting protein), which was a proteolytic enzyme capable of cleaving peptide bonds within the peptide chain of peptidoglycan. RipA is supposed to play an important role during the final stage of the cell division -2+ can increase muralytic activity, but Ca2+, Mg2+, Co2+, DTT, EDTA, PMSF and so on have little effect on muralytic activity. The purified recombinant Rpf protein promoted the growth of R. erythropolis KB1 and promoted the resuscitation of VBNC state KB1 cells. The resuscitation effect was more significant with the increase of recombinant Rpf protein concentration.The muralytic activity of the recombinant Rpf protein was 1,760 U/mg and the protease activity was 1,634 U/mg. 0.1 mM ZnR. erythropolis cells and the recovery of non-culturable cells. The growth-promoting and resuscitation effects of Rpf are closely related to its muralytic activity.It was found that the muralytic activity of Rpf-1 changed after mutation, and the muralytic activity of C50G+C114T mutant lost by 86.68%, D45A+E51K mutant lost by 84.43%, Q69K mutant lost by 86.11%, and E51A mutant lost by 11.14%. While the muralytic activity of the W75V mutant increased by 94.45%. The growth-promoting and revitalizing effects of the C50G+C114T mutant disappeared, and the W75V mutant significantly increased the growth of 10.7717/peerj.6951/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.6951/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.6951/supp-3Supplemental Information 3Click here for additional data file.


Poly-ubiquitination is a post-translational modification that can impart diverse functions to its targets depending on the type of linkage . K48-ubiThe BRAF/MEK/ERK signaling cascade is by far the most common oncogenic signaling pathway in melanoma. Specifically, BRAF is mutated in about 70% of cutaneous melanomas, leading to constitutive activation of MEK/ERK signaling. MEK inhibitors have produced impressive results, but their benefits are often short-lived, underscoring the need for new targeting strategies. We observed that inhibition of UBE2N significantly reduced expression of the activating phosphorylation of MEK1/2(S217/221) accompanied by an upregulation of the inhibitory phosphorylation of MEK2(T394) . It remaIn addition to the cancer cell-intrinsic effects, UBE2N plays a pivotal role in regulating immune and inflammatory pathways. Particularly, UBE2N is found to inhibit the conversion of regulatory T-lymphocytes to cytotoxic T-effector cells . We have


V600E-mutated cancer cells. Last, we investigated whether 14-3-3 binding to the C terminus of CRAF is required for CRAF catalytic activity and observed that it was dispensable in vivo. Altogether, our study unravels the molecular mechanism by which 14-3-3 regulates dimerization-driven RAF activation and identified AMPKi as a potential agent to counteract drug resistance and adverse effects of RAF inhibitors in cancer therapies.The dimerization-driven paradoxical activation of RAF proto-oncogene Ser/Thr kinase (RAF) is the predominant cause of drug resistance and toxicity in cancer therapies with RAF inhibitors. The scaffold protein 14-3-3, which binds to the RAF C terminus, is essential for RAF activation under physiological conditions, but the molecular basis is unclear. Here we investigated whether and how 14-3-3 regulates the dimerization-driven transactivation of the RAF isoform CRAF by RAF inhibitors and affects drug resistance and toxicity by virtue of the dominant role of CRAF in these processes. We demonstrated that 14-3-3 enhances the dimerization-driven transactivation of CRAF by stabilizing CRAF dimers. Further, we identified AMP-activated protein kinase (AMPK) and CRAF itself as two putative kinases that redundantly phosphorylate CRAF's C terminus and thereby control its association with 14-3-3. Next, we determined whether the combinatory inhibition of AMPK and CRAF could overcome the paradoxical effect of RAF inhibitors. We found that the AMPK inhibitor (AMPKi) not only blocked the RAF inhibitor–driven paradoxical activation of ERK signaling and cellular overgrowth in Ras-mutated cancer cells by blocking phosphorylation of Ser-621 in CRAF but also reduced the formation of drug-resistant clones of BRAF Ras–RAF–MEK–ERK1–5–8–12–18–Dimerization-driven transactivation of RAF kinase is regulated by many factors. Canonical upstream Ras activation has been shown to facilitate RAF dimerization, probably through relieving the intramolecular interaction between the Ras-binding domain and kinase domain . SimilarXpS/TXP or RXXXpS/TXP motifs . These data demonstrated that 14-3-3 binding to the C terminus of CRAF indeed plays a critical role in the dimerization-driven transactivation of CRAF.Previous studies have suggested that 14-3-3 binding to the C terminus of RAF kinase is critical for its dimer-dependent activation . To confA). To do this, Nluc (the N terminus of luciferase) and Cluc (the C terminus of luciferase) were fused, respectively, to the CRAF kinase domain  with or without the S621A mutation or deletion of the 14-3-3 binding motif (hereafter referred to as ΔC). Then Nluc-CKD was co-expressed with either Cluc-CKD/S621A or Cluc-CKDΔC in 293T cells (B). The Cluc-fused R401H mutant (Cluc-CKD/R401H), which has a disrupted dimer interface, was used as a control. The RAF inhibitor PLX4720 (vemurafenib) induced much less luciferase signaling in 293T transfectants that express either Cluc-CKD/S621A, Cluc-CKD ΔC, or Cluc-CKD/R401H, in contrast to those expressing the WT counterpart (C), suggesting that CKD/S621A and CKDΔC have much less ability than CKD/R401H to associate with CKD upon inhibitor loading. To further confirm this finding, we next carried out a co-immunoprecipitation assay. As shown in D and E, treatment of 293 transfectants that express CKD with PLX4720 induced robust dimerization that is impaired by S621A mutation or deletion of the 14-3-3 binding motif (ΔC) as was done by R401H mutation. Taken together, these data indicate that 14-3-3 binding to the C terminus of CRAF improves the dimerization-driven transactivation of CRAF by facilitating its dimerization or stabilizing its dimers.To understand how 14-3-3 regulates the dimerization-driven transactivation of CRAF, we measured the dimer affinity of CRAF mutants with either deletion or mutation of the C-terminal 14-3-3 binding motif by complementary split luciferase assays A. To do 3T cells B. The Clnterpart C, suggesXSXP motif. Previous studies have suggested that the phosphorylation of Ser-621 is mediated by PKA, AMPK, or CRAF in different contexts , a direct target of PKA, whereas treatment with the AMPK inhibitor Compound C completely blocked the phosphorylation of acetyl-CoA carboxylase (ACC), a putative effector of AMPK, suggesting that the activity of PKA or AMPK, respectively, is inhibited in these cells. However, only the kinase-dead A373F mutant lost phospho–Ser-621 upon AMPK inhibition with Compound C , whereas PKA inhibition with H89 slightly enhanced phospho–Ser-621 in both WT and kinase-dead A373F CRAF . These data indicated that Ser-621 in the 14-3-3 binding motif of CRAF is phosphorylated redundantly by AMPK and CRAF itself, although the mechanism for the slight increase of phospho–Ser-621 in the presence of the PKA inhibitor is unclear and requires further investigation in the future. Further, we demonstrated by co-immunoprecipitation assay that the blockage of phospho–Ser-621 in kinase-dead A373F CRAF by Compound C impaired the association of 14-3-3 with this mutant (C and D).It is well-known that the binding of 14-3-3 to the C terminus of CRAF requires the phosphorylation of Ser-621 in the RScontexts –28. To cV600E-harboring cancers (–A–F). This paradoxical effect of vemurafenib on H1299 and Sk-mel-2 cancer cell lines was blocked by the AMPK inhibitor Compound C (A–F) or the shRNA-mediated knockdowns of AMPKα1, the predominant isoform of AMPKα in H1299 cells (G–I). Furthermore, the paradoxical stimulation of cell growth by vemurafenib in H1299 and Sk-mel-2 cancer cell lines was also inhibited by Compound C or AMPKα1 knockdown (A–G). Noteworthy, the concentrations of Compound C used in our experiments could effectively block the phosphorylation of ACC by AMPK (H) but had no apparent toxicity in these cell lines , which excludes the potential artifacts arising from this AMPK inhibitor. Altogether, these data further support that AMPK- and CRAF-mediated phosphorylation of the C-terminal 14-3-3 binding motif plays a critical role in the dimerization-driven transactivation of CRAF.The paradoxical activation of RAF–MEK–ERK signaling driven by RAF inhibitors is not only responsible for the intrinsic resistance of Ras-mutated cancers but also one of the important causes that lead to acquired resistance in BRAF cancers . Moreove cancers –20. As icancers –, A–F. Thmpound C , A–F or 99 cells , G–I. Funockdown , A–G. No by AMPK H but hadV600E-harboring cancers with RAF inhibitors. Hence we examined whether AMPKi would enhance the efficacy of RAF inhibitors by impairing the drug resistance in BRAFV600E-harboring cancers. To this end, we treated A375 and A101D, two BRAFV600E-positive melanoma cell lines, with vemurafenib alone or plus Compound C and identified the formation of drug-resistant clones by crystal violet staining. As shown in m) effectively blocked the phosphorylation of ACC by AMPK and dramatically reduced the formation of drug-resistant clones from both melanoma cell lines.As described above, the paradoxical activation of RAF–MEK–ERK signaling contributes significantly to acquired resistance in the treatment of BRAFin vitro upon purification, which can be restored by GST fusion–enhanced dimerization . These data suggest that the CRAF/DDEE/L397M/S621A and CRAF/DDEE/L397M/ΔC mutants have a lower dimer affinity than their parental protein, although they do not associate with 14-3-3, and further support that 14-3-3 binding to the C terminus of CRAF elevates its dimer affinity or stabilizes CRAF dimers.Dimerization of RAF kinase is required for both activation and catalytic activity , 33. Ourrization . In thisrization , 34 and nterface , these mT fusion , C and Din vivo, these dimers are so weak that they dissociate during purification and thus lose catalytic activity in vitro. This is consistent with our recent findings from oncogenic RAF mutants with β3-αC loop deletions that suggest that strong dimerization drives transactivation of RAF kinase, whereas weak dimerization is required for catalytic activity following its activation , anti-phospho-MEK1/2 (9154), and anti-MEK1/2 (9124) ; anti-phospho–Ser-621 ; anti-FLAG ; anti-HA ; anti-ERK2 ; anti-ERK1/2 ; and horseradish peroxidase–labeled secondary antibodies . PLX4720 (A-1131) was purchased from Active Biochem, H-89 (S1582) and Compound C (S7306) from Selleckchem; and D-luciferin (LUCK-2KG) from Gold Biotechnology. All other chemicals were obtained from Sigma.All expression vectors used in this study were either purchased from Addgene or synthesized by Integrated DNA Technologies, as noted in the text. All mutants were generated by PCR, tagged with either FLAG or HA or His, and cloned into vectors by Gibson assembly. The pCDNA3.1(+) expression vector (Invitrogen) was used for transient expression in mammalian cells and pET-28a (Novagen) for bacterial expression. To knock down AMPKα, shRNAs that target 5′-GAGGAGAGCTATTTGATTA-3′ or 5′-GCTTGATGCACACATGAAT-3′ in human AMPKα1 were cloned into the lentiviral vector with the U6 promoter by using traditional molecular methods. The shRNA against luciferase  was used as a control.6-tagged MEK1 (K97A) was expressed in bacterial BL21(DE3) strains and purified using a nickel column (Qiagen) and following our previous protocol . The AMPKα knockdown H1299 cell lines were constructed by lentiviral transduction as described before –38. For –protocol .5 cells/well. 24 h later, D-luciferin (0.2 mg/ml) and PLX4720  were added to the culture; the incubation was allowed to proceed for 30 min before the luciferase signals were measured by Promega GloMax® Multi Detection System.293T transfectants that express different pairs of Nluc- and Cluc-fused CRAF or CRAF mutants were plated in 24-well Krystal black image plates at a seeding density of 2 × 10in vitro kinase assays, the immunoprecipitants were washed once with kinase reaction buffer ) and then incubated with 20 μl of kinase reaction mixture (2 μg of substrate and 100 mm ATP in 20 μl of kinase reaction buffer) per sample at room temperature for 10 min. The kinase reaction was stopped by adding 5 μl/sample of 5× Laemmli sample buffer. Immunoblotting was carried out as described before  was added to the cell cultures with or without Compound C (0.62 μm). The culture medium was changed every other day, and the concentration of PLX4720 was increased 2-fold every time until it reached 0.8 μm. After 2 weeks of culturing, cells were fixed with 4% paraformaldehyde and stained with crystal violet solution. The clones were counted manually, and the graphs were generated using GraphPad Prism 6.Cells were seeded in 60-mm dishes at a density of 2 × 10t test in all experiments, and error bars represent standard deviation to show variance between independent experiments.All statistical analyses in this study were performed using GraphPad InStat (GraphPad Software). Statistical significance was determined by one-sample J. Yuan, W. H. N., J. Yap, B. C., X. H., and J. H. investigation; M. W. writing-review and editing; J. H. conceptualization; J. H. data curation; J. H. supervision; J. H. methodology; J. H. writing-original draft.


Mycobacterium tuberculosis nucleoid associated protein (NAP) HU has been shown to be druggable and essential for the organism’s survival. In this study, four diarylethenes were synthesized using a one-pot decarboxylated Heck-coupling of coumaric acids with iodoanisoles. The prepared compounds 1–4 were tested for their in vitro growth inhibition of M. tuberculosis H37Rv using the spot culture growth inhibition assay, displaying minimum inhibitory concentrations between 9 and 22 µM. Their cytotoxicity against BHK-21 cell line showed half inhibition at concentrations between 98 and 729 µM. The most selective hit (SI = 81), demonstrated inhibition of M. tuberculosis HU protein involved in maintaining bacterial genome architecture.Tuberculosis continues to be a great source of concern in global health because of the large reservoir of humans infected with the bacilli and the appearance of clinical isolates resistant to a wide array of anti-tuberculosis drugs. New drugs with novel mechanisms of action on new targets are urgently required to reduce global tuberculosis burden.  Mycobacterium tuberculosis complex, and is currently the leading cause of death from a single infectious agent in the world. Globally, 1.4 million people died from the disease and 10.4 million people were diagnosed with it in 2015  . 2′-Hydrterature ,12.1–4 were tested for M. tuberculosis H37Rv growth inhibition using the spot culture growth inhibition assay  and visualised using a phosphorimager .A 30-bp single stranded oligonucleotide was labelled at its 5′ end with [γ-32P] ATP using the T4 polynucleotide kinase. Double-stranded DNA substrate was prepared by annealing the unlabelled complementary oligonucleotide to the labelled one. The M. tuberculosis HU protein (PDB: 4PT4). The Maestro suite  was used for pre-processing of the protein followed by energy minimization with OPLS force field. Multiple conformers of the ligands were generated using LigPrep and docked against M. tuberculosis HU using Glide with extra precision docking [The initial topologies of the compounds were derived by using the Gaussian 09 package . These l docking .E)-2′-hydroxy-4′′-methoxy-1,2-diarylethene (1) and (E)-2′-hydroxy-3′′-methoxy-1,2-diarylethene (2) showed to inhibit the growth of virulent M. tuberculosis H37Rv with an MIC value of 9.0 µM. Their SI values were respectively 58 and 81 in relation to normal baby hamster kidney cells (BHK21). In addition, this is the first time that a 1,1-diarylethene 4 was found to significantly inhibit the growth of M. tuberculosis (MIC = 9.0 µM) in a selective fashion (SI = 55). Among the synthetised diarylethenes, 1 and 2 displayed inhibition of M. tuberculosis HU-DNA binding, with respective IC90 values of 200 and 150 µM. Both 1,2-diarylethenes 1 and 2 are efficient inhibitors of HU-DNA complex formation, and they are considered favourable scaffolds for further development as anti-TB drugs.The stilbenes (