L-lactate dehydrogenase. Our findings suggest that the primary cause of metabolic enzyme inhibition is not the evolution of regulatory metabolite–enzyme interactions, but a finite structural diversity prevalent within the metabolome. In eukaryotes, compartmentalization minimizes inevitable enzyme inhibition and alleviates constraints that self-inhibition places on metabolism.Metabolites can inhibit the enzymes that generate them. To explore the general nature of metabolic self-inhibition, we surveyed enzymological data accrued from a century of experimentation and generated a genome-scale enzyme-inhibition network. Enzyme inhibition is often driven by essential metabolites, affects the majority of biochemical processes, and is executed by a structured network whose topological organization is reflecting chemical similarities that exist between metabolites. Most inhibitory interactions are competitive, emerge in the close neighbourhood of the inhibited enzymes, and result from structural similarities between substrate and inhibitors. Structural constraints also explain one-third of allosteric inhibitors, a finding rationalized by crystallographic analysis of allosterically inhibited  Metabolites act as enzyme inhibitors, but their global impact on metabolism has scarcely been considered. Here, the authors generate a human genome-wide metabolite-enzyme inhibition network, and find that inhibition occurs largely due to limited structural diversity of metabolites, leading to a global constraint on metabolism which subcellular compartmentalization minimizes. The activity of metabolic enzymes depends on their structure, but also on their chemical environment and non-catalytic metabolite–enzyme interactions with inhibitors and activators12347However, the evolutionary origins of metabolic enzyme inhibition are neither, in essence, explained by the need to regulate metabolism, nor are the general principles that guide metabolic enzyme inhibition. Metabolic feedback inhibition for instance can be a direct consequence of the catalytic mechanisms itself5121314in vitro process, there is little information about its global nature. In order to obtain insights into the principles of metabolic self-inhibition, we curated and combined comprehensive enzymological knowledge obtained over a century of biochemical research, that has been collected in the Braunschweig Enzyme Database (BRENDA) databaseAs studying enzyme inhibition remains a laborious and mostly Over a period of nearly 30 years, the BRENDA databaseNext, we removed all entries that could not be matched to a unique metabolite , and restricted the network to those inhibitors that are human metabolites. This core of the data set consists of 1,311 studies which were specifically conducted on 333 human enzymes and 431 human metabolites. Then, we expanded the network to include ‘cross-species’ data, exploiting the fact that the principles which guide enzyme inhibition are the same across species . In thisγ<3, compared to a random network where γ=11.47; Retaining the topological organization and chemical make-up of the human metabolic network, the cross-species informed inhibitor network consists of 682 metabolic inhibitors (mapping to 26% of human metabolites) that inhibit 83% (621) of its distinct enzymatic reactions . The bipOwing to the rich amount of data, each enzyme EC category is similarly well covered by inhibitor information. In all, 208 out of 244 transferases are inhibited by at least one metabolite, 159 out of 205 oxidoreductases, 147 out of 161 hydrolases, 49 out of 66 lyases, 32 out of 39 isomerases, and 26 out of the 28 ligases . All enzTo classify the inhibitors, we adopted the chemical categorizations of the human metabolome database (HMDB 3.5)P value 4.8e−34 and 0.01 respectively), ‘Amino Acids, Peptides, and Analogues’ to inhibit Lyases , ‘Carbohydrates and Carbohydrate Conjugates’ to inhibit Isomerases and Hydrolases ; ‘Lipids’ inhibit Oxidoreductases and Isomerases ; ‘Organic Acids and Derivatives’ inhibit Oxidoreductases, Ligases and Lyases , ‘Aliphatic Acyclic Compounds’ inhibit Oxidoreductases and Hydrolases ; and finally ‘Aromatic Cyclic Compounds’ inhibit Oxidoreductases and Lyases  , followed by ‘Lipids’ , ‘Amino Acids, Peptides, and Analogues’ , ‘Aromatic Cyclic Compounds’ , ‘Aliphatic Acyclic Compounds’ , ‘Organic Acids and Derivatives’  and ‘Carbohydrates and Carbohydrate Conjugates’ , and a total of 721 (12.9%) by other metabolites . The dom 2.9e-2) . DespiteThe biochemical literature distinguishes three major inhibitory mechanisms: competitive, noncompetitive and uncompetitive . Of these, competitive inhibition implies indeed a structural relationship between inhibitor and substrate23525262728P value 2.84e-06, Next, we used computational structure prediction to enumerate similarities between substrates and inhibitors. Pairwise compound comparisons with fingerprint similarity fpSim, drug moFor most inhibitory interactions that constitute our network the mechanism is unknown. However significant similarity between inhibitor and at least one substrate is detected across the entire network. Vice versa, even the most similar metabolite out of a poolsize-corrected random sampling lacks structural similarity . Most ofEnzymes have not been exhaustively tested against all metabolites. We hence computed structural similarity coefficients for all metabolite pairs within the metabolic network. Considering the average structural similarity between substrate and inhibitor as cut-off, 97.7% of human metabolites  are structurally similar to at least one other human metabolite. A confined chemical structural diversity within the metabolome makes in essence every enzymatic reaction susceptible to competitive inhibition.L-lactate dehydrogenase (L-LDH). L-LDH is allosterically inhibited by its substrate, pyruvate333637Non-competitive and uncompetitive enzyme inhibition is not dependent on structural similarity between substrate and inhibitor, as the inhibitor does bind to a different site in the enzyme. Nonetheless, 33% of non-competitive and 31% uncompetitive inhibitors are structurally similar to the enzyme’s substrates . One illIn order to test whether structural similarity could explain the allosteric inhibition, L-LDH purified from rabbit muscle was co-crystallized with oxaloacetate and NADH, or malonate, respectively. The structures were solved by X-ray crystallography followed by molecular replacement, and refined at 1.87 and 1.58 Å resolution, respectively . The Km obtained for pyruvate and NADH were 0.300±0.035 and 0.095±0.012 mM, respectively. Moreover, we find that, similar to malonate, oxaloacetate is a non-competitive inhibitor of L-LDH with respect to pyruvate with moderate in vitro inhibition too (Ki=2.30±0.22 mM) (KiOAA/KmPyr=7.7) compared to malonate  . Even thP value 1.64e-99, t-test). Structural analogues are hence typically found within the close metabolic neighbourhood . As a consequence, inhibitors are enriched to occur within metabolic pathways . Indeed, the more central or essential a metabolic enzyme, the more likely its substrates are inhibitors . Furthermore, all of the most frequent inhibitors were essential metabolites  compartments may reduce unwanted enzyme–inhibitor interactionsThe metabolic network can however not randomly compartmentalize due to its chemical connectivity. We therefore examined the effect of compartmentalization upon including enzyme localization to cytoplasm, Golgi apparatus, lysosome, mitochondria, nucleus, endoplasmic reticulum (ER) and peroxisome to the inhibitor network. The maximum number of inhibitory interactions takes place within cytoplasm followed by mitochondria, the two compartments that host also the highest number of metabolic reactions . Accountin vitro data about enzyme function in thousands of carefully conducted small-scale experiments over a century. A data set of comparable depth not available for any other biological problem. We took the assumption that the basic principles of enzyme inhibition will be the same across species. The cross-species inhibitor information that could be mapped onto the topology of the human metabolic network reconstruction—itself based on experimental results derived from multiple species—is estimated to be the result of more than 9,000 years of single-person experimental work, and our network incorporates work of>18,000 research publications. The large size was required to outweigh, or at least statistically define, the testing bias that exists in the biochemical literature.Enzyme inhibition has been studied for decades in the context of enzyme function and in the regulation of metabolism, but there is still little information about its global nature. However, enzymologist collected The high coverage indeed alleviated a selective bias against a certain enzyme class or reaction mechanism, so that all human EC classes are equally well covered . The inhKi, Km values). First, for only a fraction of the inhibitors this information is available, second our network is cross-species and enzyme constants vary between species, and third, many enzymatic constants differ substantially if determined by more than one lab  are not inhibitedin vivo will be lower as the activity estimated in in vitro kinetic experiments. One illustrative example is TPI, a central enzyme in glycolysis. In vitro considered a ‘prefect enzyme’ limited only by the diffusion rates of its substrates, it has been suggested that TPI is multiple times more active in cells than is needed for glycolysisIn vivo however, a reduction of TPI activity by just 20% is sufficient to affect yeast metabolismA recent and illustrative example for metabolic constraints caused by enyzme inhibition concerns glyceraldehyde-3-phosphate dehydrogenase and PK, that promiscuously produce 4-phospho-erythronate and 2-phospho-Escherichia coli, like most bacteria, do not possess fructose-2,6-bisphosphate (F26BP), so the E. coli enzyme can’t have evolved to be regulated by the compound. Yet, F26BP, structurally similar to fructose-1,6-bisphosphate does inhibit E. coli fructose-1,6-bisphosphatase in vitro. In eukaryotic cell that use F26BP for regulation, its binding affinity is increased, especially in the presence of AMP, a non-competitive inhibitor for fructose-1,6-bisphosphatase845If enzyme inhibition emerges for structural reasons, it follows that structural similarity could form a basis for the evolutionary origin of regulatory mechanisms. An example is identified in the inhibition of fructose-1,6-bisphosphatase by fructose-2,6-bisphosphate, a regulatory metabolite in eukaryotic cells. E. coli reconstruction (iJO1366)E. coli specific biochemical reactions. The network expansion would hence both inhibit the existing as well as the newly introduced enzymes. Support for the relevance comes from synthetic biology, where engineered biosynthetic pathways are regularly of low activity, and in many cases it is required to metabolically evolve the host so that the product is formed474947Structurally driven enzyme inhibition, in particular its high frequency in affecting virtually all enzymes, might contribute to difficulties in designing synthetic metabolic pathwaysSeveral mechanisms reduce the problem of enzyme inhibition by separating biochemical reactions from each other. Metabolic oscillations for instance, as observed within central carbon metabolism, separate reactions by time. In yeast, the occurrence of metabolic oscillations has been associated with the separation of oxidative from fermentative metabolism which at any given time reduces the number of active reactionsL-lactate dehydrogenase in complex with two allosteric inhibitors, whose inhibitory properties are explained by their structural similarity to its typical allosteric regulator, pyruvate. Finally, enzyme inhibition emerges mostly in the metabolic neighbourhood of the inhibited enzyme, is dominated by the most conserved and important metabolites, which specifically interact with particular enzyme classes dependent on their chemical nature. This situation is associated with compartmentalization in the eukaryotic cell that reduce metabolic enzyme inhibition up to half and specifically, by preventing an enrichment of enzyme inhibition within the metabolic neighbourhood of the eukaryotic organelles. While metabolic enzyme inhibition is key for the self-regulation of metabolism, its primary cause is hence the chemical structure of the metabolome. Many non-catalytic metabolite–enzyme interactions mount to a constraint for the function of cellular metabolic network, so that the cells evolved mechanisms to limit the number of unwanted and inhibitory metabolite–enzyme interactions.In summary, we have constructed a global network of inhibitory metabolite–enzyme interactions by computationally merging detailed enzymological information with a genome-scale human metabolic network reconstruction. The obtained metabolite–enzyme inhibitor network pictures general principles that underlie enzyme inhibition as obtained on a cross-species basis. We find that thousands of inhibitory interactions render, in essence, every biochemical process sensitive to metabolic inhibition. Most inhibitory interactions emerge as consequence of a finite structural diversity that exists within the central parts of the metabolome. Structurally driven enzyme inhibition is mostly of competitive, but partially also of allosteric nature. We exemplify the latter by detailed enzymological and structural analysis of http://cts.fiehnlab.ucdavis.edu/). Unique metabolite IDs  were then assigned to Recon2 metabolites, and mapped with the list of inhibitors. In total, 682 compounds, out of 30,107 BRENDA inhibitors, were successfully mapped to the Recon2 metabolites. These 682 metabolites inhibit 621 enzymatic reactions as contained in the Recon2 model. In the enzyme-inhibition network, a metabolite and an enzyme node were connected if a metabolite is an inhibitor for the enzyme, constituting in total 5,989 edges in the network. Information related to different kind of inhibitions including competitive, uncompetitive or noncompetitive for inhibitors of the enzyme-inhibition network was extracted from the information stored in BRENDA. A similar approach was followed for 289 E. coli-specific enzymes Classification of 621 enzymes and 628 inhibitors was conducted following KEGG nomenclatureP value 0.05 was used as significance threshold. False discovery rate (FDR) for inhibition of a class of enzymes by a class of inhibitors was calculated as follows. First, inhibitors were randomly assigned to each inhibitor class, and this process was repeated for a hundred times. Then, an enrichment analysis for inhibition of a class of enzymes was performed on randomly assigned inhibitor classes. Finally, if P value of inhibition was better for a random group of inhibitors than the original inhibitor class then the counter was increased. FDR=counter/100.Inhibitors were counted for each class of compounds, and inhibitory interactions for each class of enzymes. The ‘phyper’ function in R was used for Hypergeometric test. Out of 682 inhibitors of the enzyme-inhibition network, structure-data files (SDF) were available for 638 metabolites in the PubChem database. Pairwise compound comparisons for all pairs of inhibitors were performed using with PubChem fingerprints (fpSim)E1, E2, E3, E4, E5), that have 2, 3, 3, 2, and 4 substrates each respectively, constituting in total a list of 14 substrates connected to the inhibitor. First, the similarity between the inhibitor and all 14 substrate metabolites is calculated. Then, 14 metabolites are randomly selected from the inhibitor network and their structural similarity compared with the inhibitor mapped to the enzyme. This random sampling is repeated 50 times, and eventually, 50 times the similarity score of the most similar random compound is plotted against the similarity score of the most similar enzyme metabolite.To examine similarity between an inhibitor and substrates, a list of all substrates of the enzyme was extracted from the network reconstructionP values were calculated for every pair of metabolic pathways using hypergeometric test. Inhibition from one pathway to the other considered significant when P value<0.01.Pathway to pathway similarity was calculated by extracting a list of pathways in accordance to the Recon2 modelFor every inhibitor, a list of genes directly involved in its metabolism was extracted from the reconstructionP value<0.05 was used as significance criterion to construct the compartment–compartment-specific inhibition network. Additionally, a FDR between a pair of compartments was calculated. First, for each compartment, the same number of compounds was randomly assigned, and this process was repeated for a hundred times. Then, an enrichment analysis for inhibition within and between a pair of compartments was performed following the same strategy as for the randomly assigned compounds. Finally, if the P value of inhibition between a pair of compartments is better for a random set of inhibitors compared to the original inhibitors then the counter was increased. FDR=counter/100.In the Recon2 model, there are in total seven compartments including Cytoplasm, Golgi apparatus, Lysosome, Mitochondria, Nucleus, ER and Peroxisomerc’, between 2 and 50) were created. First, for each metabolite ‘m’ and enzyme ‘e’ of the inhibition network (n’ (between 1 and ‘rc’) in which ‘m’ and ‘e’ are allowed to participate was randomly selected following a power-law distribution  a*bˆa/xˆ(a+1)’). Then, ‘m’ and ‘e’ was placed in ‘n’ random compartments. Finally compared to the total 5,989 interactions of the inhibition network . The reaction mixture contained 1 mM NADH, 50 ng of L-lactate dehydrogenase from rabbit muscle (Roche) and pyruvate was added to start the reaction. For Km determinations, a saturation curve of pyruvate was generated by varying the concentrations from 0 to 3 mM at saturating concentrations of NADH (1 mM). For the saturation curve for NADH, this substrate was varied from 0 to 1 mM at saturating concentrations of Pyruvate (3 mM). For Ki determinations, similar experiments for Km determinations were done in the presence of different concentrations of oxaloacetate (0–7.5 mM). For the Ki determination of oxaloacetate versus pyruvate, the reaction mixture containing NADH, L-LDH and oxaloacetate was incubated for 1 min and then the reaction was started by adding pyruvate. All the substrates and inhibitor were prepared fresh and the oxaloacetate stock solution was kept on ice maximum for 2 h. The kinetic data was analysed using the software Origin 9.0.The activity of L-LDH was measured spectrophotometrically following the NADH oxidation at 340 nm at 37 °C in a 50 mM buffer NaL-lactate dehydrogenase from rabbit muscle (Roche) was buffer exchanged into HEPES 40 mM pH 7.5 using a centrifugal concentrator  and then adjusted to a final concentration of 5 mg ml−1. For the L-LDH co-crystallized with NADH, 5 mM of the cofactor was mixed with the protein before the crystallization experiments. The crystals were grown using the vapour diffusion method at 20 °C in a solution containing 10% wt/v PEG 3350, 50 mM Bis-tris propane pH 6.5 and 100 mM NaF. The crystals appeared after 24 h reaching their maximum size after 4 days. The crystals were cryoprotected by adding the reservoir liquor supplemented with 20% w/v PEG 400 and 5 mM oxaloacetate before flash freezing in liquid nitrogen. In the case of the L-LDH co-crystallized with malonate, the protein was buffer exchanged as mentioned above. The crystals were grown in a buffer containing 0.1 M sodium malonate and 10% w/v PEG 3350. The crystals were cryoprotected by adding the reservoir liquor supplemented with 20% w/v PEG 400 and 2.5 mM oxaloacetate and then frozen immediately in liquid nitrogen.The Data for the L-LDH crystals with malonate were collected at Diamond Light source on station I04-1, and data for the L-LDH crystals with NADH and oxaloacetate were collected on station I03. Both data sets were collected at 100 K. The structures were solved by molecular replacement (PHASER) using coordinates for rabbit muscle L-LDH in which all ligands and water molecules were removed (PDB code 3H3F ref. ). The sthttp://www.brenda-enzymes.org/soap.php)t-test.SOAP from BRENDA .Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Trocar site hernias are rare complications after laparoscopic surgery but most commonly occur at larger trocar sites placed at the umbilicus. With increased utilization of the laparoscopic approach the incidence of trocar site hernia is increasing. We report a case of a trocar site hernia following an otherwise uncomplicated robotic prostatectomy at a 12 mm right lower quadrant port. The vermiform appendix was incarcerated within the trocar site hernia. Subsequent appendectomy and primary repair of the hernia were performed without complication. Trocar site hernias are rare complications after laparoscopic surgery with the overall incidence of 0–5.2% . However2, presented to our surgery clinic for a symptomatic right lower quadrant trocar site hernia, following robotic assisted radical prostatectomy. In December of 2010 he underwent an uncomplicated robotic assisted radical prostatectomy. At the time of the operation a 12 mm trocar was placed in the right lower quadrant, and it is unclear from the operative note whether the fascia was closed at the conclusion of the operation. He recovered from the surgery without issue but unfortunately developed widely metastatic disease over the next 18 months. Upon presentation to our clinic in May of 2012, he was complaining of a two-week history of right lower quadrant pain and a newly discovered mass in the vicinity of a previous trocar site. He initially noted the onset of the pain when performing pull-ups at a local gym, at which time he noted pulling sensation in the right lower quadrant. Following the initial onset of symptoms, he continued to have pain in the area and noted an intermittent bulge as well. He presented for initial evaluation by his primary care provider who obtained a CT scan of the abdomen and pelvis. The scan revealed a 10 mm right lower quadrant hernia with herniated fat and a tubular structure which was read as a possible omental vessel, with concern for incarceration , respectively , 4. In tThere have been rare reports of trocar site hernias containing the appendix  5–7]; h–7; h5–7]In conclusion, with an increasing number of laparoscopic cases and therefore trocar site hernias, these hernias could continue to be a source of serious morbidity. Based on our review of the literature, we suggest that routine closure of 10–12 mm trocar sites should be the standard regardless of location, as this could decrease the risk of morbidity from trocar site hernias.


Analytical ultracentrifugation showed this activity transition is associated with oligomerization to form tetramer, which might be the forerunner of a naturally occurring four-helix-bundle AFP in other flounders.A supersoluble 40-residue type I antifreeze protein (AFP) was discovered in a righteye flounder, the barfin plaice (bp). Unlike all other AFPs characterized to date, bpAFP transitions from moderately-active to hyperactive with increasing concentration. At sub-mM concentrations, bpAFP bound to pyramidal planes of ice to shape it into a bi-pyramidal hexagonal trapezohedron, similarly to the other moderately-active AFPs. At mM concentrations, bpAFP uniquely underwent further binding to the whole ice crystal surface including the basal planes. The latter caused a bursting ice crystal growth normal to  Organisms inhabiting ice-laden environments produce various cryoprotective agents to safeguard against freezing damage. Among them, antifreeze proteins (AFP) function by binding seed ice crystals to inhibit their growth456a-axes  perpendicular to the c-axisc-axis, (10–10) are the six equivalent primary prism planes, and (20–21) are pyramidal planes bound by one AFP type that produces a 12-sided hexagonal bipyramid with a 3.3:1 ratio of length to widthA seed ice crystal, the target ligand of AFP, is composed of ordered water molecules in a hexagonal lattice, which is defined by three equivalent sc-axis, –10 are tTf) and slightly elevates the melting temperature (Tm)Tf and Tm is defined as thermal hysteresis (TH), which reflects the strength of ice-growth inhibition by an AFP. Moderately active AFPs require mM concentrations to achieve a TH activity of approximately 1 °C. Hyperactive AFPs reach this TH value at one tenth of these concentrationsTf. With moderate AFPs rapid ice growth occurs from the two tips of the bipyramid  along the c-axis. In contrast, hyperactive AFPs direct explosive ice growth at Tf perpendicular to the c-axisRegardless of the AFP type, their binding to ice causes microcurvature of the ice front between the surface-bound-AFPs through the Gibbs-Thomson effect11Pseudopleuronectes americanus) plasma15th isoform to elute from reversed-phase HPLC (HPLC-6) was the first AFP to have its crystal structure solved, which is a single amphipathic α-helix1721Type I AFP was initially discovered as a mixture of small (3–4 kDa) alanine-rich isoforms in winter flounder  protein was extracted from 2 kg muscle paste, and from this extract approximately 1 g of native bpAFP of 95% purity was recovered . The bar1TASDAAAAAAATAAAAAAAAAATAKAAAEAAAATAAAAR40-NH2 is the full primary sequence of this isoform. This is a typical type I AFP sequence composed of 3 tandem repeats of the 11-residue consensus sequence TX10 . However, bpAFP is more alanine-rich (75%) than other type I AFP isoforms that are typically only two thirds alanine. The extra alanines, up to 10 in a row, take the place of Asn and Leu that are not thought to play a critical role in either structure or function of type I AFP. The N-terminal D1TASD sequence and C-terminal amidation that form the α-helix capping structures are well conserved17The barfin plaice AFP was separated into several fractions by reversed-phase HPLC . The one−1, which was determined spectrophotometrically  for the supernatants of their saturated solutions.A recombinant version of bpAFP (rbpAFP) was prepared from a fusion protein tagged with thioredoxin27−1, while the TH increased to 2.5–3 °C with increasing the concentration up to 200 mg·mL−1  bursting occurs along the c-axis of the ice trapezohedron to give needle-shaped crystals (−1), the crystal burst from the mid-section of the ice crystal normal to the c-axis  was assayed over the pH range 2 to 13 (The TH activity of rbpAFP and bpAFP (10 mg·mL 2 to 13 . As seen−1) was examined by CD spectroscopy at temperatures between 20 and 90 °C  of this alanine-rich protein and its transition from moderately active to hyperactive at high concentrations are exceptional properties not seen in other AFPs.We have discovered a 40-residue type I AFP from barfin plaice, which uniquely shows two forms of ice binding at different concentrations. Both bpAFP and rbpAFP bound to pyramidal planes of an ice crystal below 0.01 mg·mL2, T13, T24, and T35) with their 11-residue periodicity that will project the side-chains in a line along the alanine-rich helix. The alanine content of bpAFP is exceptionally high (75%), compared with that of other type I AFPs, such as wfAFP (62%), Alaskan plaice AFP (65%), and yellow-tail flounder AFP (69%)26 and E30, which will presumably form a salt-bridge similar to that between K18 and E22 in wfAFP. We speculate that bpAFP has water-holding properties similar to the 33-kDa type I AFP isoform (Maxi) that organizes ~400 water molecules in the interior of its four-helix bundle structure10 , and the repetitive unit of Maxi forms three helical turns with an average of 3.7 residues per turn, as opposed to 3.6 residues per turn in the classic α-helix22The CD profile of bpAFP, with two negative minima at 208 and 222 nm, and a high sequence identity with the other type I AFPs has enabled us to predict the monomeric α-helical structure of bpAFP with considerable confidence. The N- and C-terminal capping sequences are the same as in winter flounder type I AFP176, A17, and A28 along with a flanking row of Thr on one side and Ala on the other. The same ice-binding surface is present in bpAFP, and yet at low concentrations these two AFPs bind to slightly different pyramidal planesThe ice-binding site (IBS) of winter flounder type I AFP has been defined as its alanine-rich face including AThe hydrophobicity of the ice-binding face of type I and other AFPs2232We suggest this same process is at work here with bpAFP. A small percentage of the monomer associates in a concentration-dependent manner, presumably through its ice-binding site, to form a tetramer which, like Maxi, has a more extensive array of clathrate waters on its outer surface to match multiple planes of ice. This hypothesis explains why bpAFP has the properties of moderately active type I AFP at low concentrations, and hyperactivity at higher concentrations. Indeed, it is quite possible that Maxi evolved along these lines in order to help stabilize these tentative beneficial associations of four helices. By extending the length of the helix through repeated gene duplication, and with folding into a hairpin that can dimerize in an antiparallel way through clathrate waters, a more stable four-helix bundle structure would be achieved. We note that the antiparallel alignment of four bpAFP helices has the potential for electrostatic interactions between the N- and C-terminal cap structures, with two positive and two negative charges at either end.Barfin plaice  were cauEscherichia coli BL21 (DE3) Rosetta2 (Novagen). These cells in Luria-Bertani medium were harvested by centrifugation, washed by resuspension with 50 mM Tris-HCl buffer (pH 8.0) for disruption by sonication. The lysate supernatant was applied to Ni-NTA column to obtain the Trx-tagged bpAFP. This fusion protein (50 mg protein in 30 mL of PBS) was digested with thrombin at 22 °C for 16 h, and the products were applied to a Ni-NTA column to retain cleaved Trx and uncleaved fusion protein. The flow-through material was then applied to TSKgel ODS-80Ts (TOSOH) for reversed-phase HPLC, which produced an rbpAFP sample of 98% purity (The DNA encoding Trx-tagged bpAFP  was clon% purity . Average−1 of Rhodamine (Life Technologies) by mixing in a tube rotator at 25 °C for 4 h. Following removal of unreacted dye by ultrafiltration, 0.01, 0.02, 0.03, and 0.1 mg·mL−1 dilutions of the fluorescent peptide were prepared for FIPA analysis.Native and recombinant samples of bpAFP were fluorescently tagged for FIPA experiments. Native or recombinant bpAFP (4 mg) in 1 mL of 0.1 M ammonium bicarbonate (pH 7.9) was allowed to react with 50 μL of 5.0 mg·mL−1 was frozen in the photomicroscope apparatus and melted back to prepare a single seed ice crystal. Its bursting-growth and melting temperatures were determined as Tf and Tm, respectively. This measurement was repeated at least 3 times to average the values for TH activity (TH = |Tf − Tm|) shown in TH activity was measured with a LEICA DMLB100 photomicroscope  equipped with a Linkam THMS 600 temperature controller  according to procedures described in ref. c-axis identifiedca. 30 mL solution of the fluorescent bpAFP. Following slow growth for 120 min, the ice hemisphere was detached from the probe, rinsed to remove any contaminants non-specifically attached to the hemisphere, illuminated under UV light and photographed at −1 °C.For the FIPA experiments, a single ice crystal hemisphere of 2.5 cm in diameter was prepared and its −1 solutions of native and recombinant bpAFP dissolved into 10 mM sodium phosphate buffer (pH 7.4) using a JASCO J-725 CD spectrophotometer . The samples were set to a temperature between 20 and 90 °C at intervals of 5 °C, and the results were expressed as mean residue ellipticity (deg·cm2·dmol−1) at each wavelength  was used for sedimentation velocity measurements at 40,000 rpm at 4 °C with 2.5 mg of bpAFP in 0.5 mL AFP of 10 mM sodium phosphate (pH 7.9). Double sector charcoal-Epon cells equipped with quartz windows were used and concentration distributions were determined by absorbance optics. Sedimentation coefficient distributions were determined using standard methodologyHow to cite this article: Mahatabuddin, S. et al. Concentration-dependent oligomerization of an alpha-helical antifreeze polypeptide makes it hyperactive. Sci. Rep.7, 42501; doi: 10.1038/srep42501 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


IIa histone deacetylase (HDAC) isoforms such as HDAC5 are critical signal‐responsive repressors of maladaptive cardiomyocyte hypertrophy, through nuclear interactions with transcription factors including myocyte enhancer factor‐2. β‐Adrenoceptor (β‐AR) stimulation, a signal of fundamental importance in regulating cardiac function, has been proposed to induce both phosphorylation‐independent nuclear export and phosphorylation‐dependent nuclear accumulation of cardiomyocyte HDAC5. The relative importance of phosphorylation at Ser259/Ser498 versus Ser279 in HDAC5 regulation is also controversial. We aimed to determine the impact of β‐AR stimulation on the phosphorylation, localization, and function of cardiomyocyte HDAC5 and delineate underlying molecular mechanisms.Class HDAC5 revealed the β‐AR agonist isoproterenol to induce β1‐AR‐mediated and protein kinase A‐dependent HDAC5 nuclear accumulation in adult rat cardiomyocytes, which was accompanied by dephosphorylation at Ser259/279/498. Mutation of Ser259/Ser498 to Ala promoted HDAC5 nuclear accumulation and myocyte enhancer factor‐2 inhibition, whereas Ser279 ablation had no such effect and did not block isoproterenol‐induced nuclear accumulation. Inhibition of the Ser/Thr phosphatase PP2A blocked isoproterenol‐induced HDAC5 dephosphorylation. Co‐immunoprecipitation revealed a specific interaction of HDAC5 with the PP2A targeting subunit B55α, as well as catalytic and scaffolding subunits, which increased >3‐fold with isoproterenol. Knockdown of B55α in neonatal cardiomyocytes attenuated isoproterenol‐induced HDAC5 dephosphorylation.A novel 3‐dimensional confocal microscopy method that objectively quantifies the whole‐cell nuclear/cytoplasmic distribution of green fluorescent protein tagged AR stimulation induces HDAC5 nuclear accumulation in cardiomyocytes by a mechanism that is protein kinase A‐dependent but requires B55α‐PP2A‐mediated dephosphorylation of Ser259/Ser498 rather than protein kinase A‐mediated phosphorylation of Ser279.β‐ Histone deacetylase (HDAC) 5 is a class IIa HDAC isoform that is an important negative regulator of maladaptive cardiomyocyte hypertrophy and pathological cardiac remodeling.q protein‐coupled receptors (GqPCRs), such as the α1‐adrenergic receptor or the endothelin‐1 receptor, induces the phosphorylation of S259/S498 by HDAC kinases, such as protein kinase D2+/calmodulin‐dependent protein kinase II.qPCR agonists, our recent work indicates that stimulation of the Gs protein‐coupled β‐adrenergic receptor (β‐AR) with isoproterenol reduces HDAC5 phosphorylation at S259/S498 in cardiomyocytes, but may trigger HDAC5 nuclear export through a phosphorylation‐independent mechanism.HDAC5 contains at least 17 phospho‐acceptor residuesqPCR‐mediated nuclear export of HDAC5 in neonatal rat ventricular myocytes (NRVM).In recent years, phosphorylation of S279 has also been proposed as an important mechanism regulating HDAC5 subcellular localization in cardiomyocytes. S279 can be directly phosphorylated by protein kinase A (PKA) in in vitro kinase assays, and interventions that activate β‐AR/PKA signaling block G1‐AR subtype and PKA activity. Furthermore, our data indicate that β‐AR stimulation induces PP2A‐mediated dephosphorylation of HDAC5 at both the S259/S498 and the S279 sites, and that reduced phosphorylation at the S259/S498 sites is the principal mechanism of β1‐AR/PKA/PP2A‐mediated nuclear accumulation. Finally, we show that β‐AR activation increases the interaction between HDAC5 and PP2A catalytic and scaffolding subunits, as well as the PP2A targeting subunit B55α selectively. Silencing of B55α in NRVM blocked isoproterenol‐induced dephosphorylation at the S259 site, suggesting that this subunit is required for PP2A‐mediated dephosphorylation of HDAC5 downstream of β‐AR activation in cardiomyocytes. These findings point to a role for B55α‐PP2A‐mediated HDAC5 dephosphorylation and nuclear accumulation in preventing MEF2‐dependent gene transcription during short‐term β‐AR stimulation.Given that β‐AR signaling is a key therapeutic target in heart failure because of its critical role in the regulation of cardiac structure and function,t test, 1‐way ANOVA or 2‐way ANOVA as appropriate. Data sets that failed the D'Agostino and Pearson omnibus normality test were analyzed by Mann–Whitney test (2 groups) or Kruskal–Wallis 1‐way ANOVA by ranks (2 or more groups). ARVM experiments were performed in accordance with the Guidance on the Operation of Animals (Scientific Procedures) Act, 1986 (UK). NRVM experiments were conducted in accordance with the Australian Code for the Care and Use of Animals for Scientific Purposes  and were approved by the Alfred Medical Research and Education Precinct's Animal Ethics Committee.Detailed methodology is provided in Data To investigate the effects of β‐AR stimulation on the phosphorylation status of HDAC5 at S279, we made use of a recently described rabbit polyclonal antibody that detects phosphorylation of the conserved serine residue (S266) in HDAC4.1‐ or β2‐AR, ARVM were treated with CGP‐20712A (a β1‐AR‐selective antagonist) or ICI 118,551 (a β2‐AR‐selective antagonist) for 10 minutes prior to isoproterenol stimulation. CGP‐20712A blocked both isoproterenol‐induced dephosphorylation of HDAC5 at all 3 sites and isoproterenol‐induced phosphorylation of cardiac troponin I (cTnI) at S22/S23, established PKA target sites that are phosphorylated downstream of β1‐AR stimulation  was quantified. In preliminary experiments using z‐stack confocal microscopy, we found that the focal plane had a significant impact on the measured fluorescence intensity, particularly within the nuclear compartment  in an unbiased manner and calculation of the nuclear/cytoplasmic F ratio (Fnuc/Fcyto) at each time point. For time course experiments, Fnuc/Fcyto ratios obtained at the 15‐ and 45‐minute time points were normalized to the baseline value for each cell, to account for differences in the basal distribution of GFP‐HDAC5 between cells. Strict inclusion criteria were adhered to during the selection of cells for imaging and the postimaging quantification of signals was conducted in a treatment‐blinded manner  to capture information from the whole cell. Cells were imaged at baseline and at 15 and 45 minutes after the addition of vehicle control or isoproterenol, to allow the assessment of the temporal effects of each treatment. Additionally, myocytes were labeled with Cell Tracker Orange the day before imaging, and nuclei were labeled with DRAQ5 10 minutes before the final time point. Images subsequently obtained during excitation of the Cell Tracker Orange and DRAQ5 fluorophores with a laser beam at 561 or 640 nm, respectively, were used to objectively delineate the cytoplasmic and nuclear compartments Figure A. This aFnuc  over the course of the experiment  and secondly because isoproterenol stimulation induces significant nuclear accumulation of HDAC5 even when the S279 phosphorylation site has been ablated.In complementary experiments, we also investigated the impact of expressing each GFP‐HDAC5 variant on MEF2 activity in ARVM co‐expressing a luciferase reporter under the transcriptional control of a MEF2‐sensitive promoter. MEF2 is a well‐characterized binding partner of HDAC5, and disruption of their interaction following phosphorylation‐dependent nuclear export of HDAC5 permits MEF2‐dependent gene transcription that promotes maladaptive cardiomyocyte hypertrophy.p Figure F. These 1‐AR/PKA‐mediated HDAC5 nuclear accumulation, we also explored the mechanism(s) by which such dephosphorylation might occur. Since isoproterenol‐induced dephosphorylation occurs very rapidly  has been identified previously as a component of the PP2A complex that associates with heterologously expressed HDAC5 in HEK 293 cells.PP2A family members are holoenzymes, each consisting of a scaffolding (A) subunit, a catalytic (C) subunit, and a regulatory (B) subunit, with substrate specificity conferred by the identity of the B subunit isoform.B55α was readily detectable in ARVM, using a commercially available antibody Figure A. To expPPP2R2A transcripts into NRVM expressing GFP‐HDAC5. This resulted in a ≈50% to 55% reduction in B55α protein levels  isoproterenol stimulation induces the nuclear accumulation of HDAC5, through a mechanism that requires PKA activity; (2) The key determinant of HDAC5 subcellular localization is the phosphorylation status of S259/S498, with loss of phosphorylation at these sites promoting nuclear accumulation and repression of MEF2; (3) The phosphorylation status of S279 plays a relatively insignificant role in regulating the nuclear versus cytoplasmic distribution of HDAC5; and (4) Dephosphorylation of HDAC5 following β‐AR activation requires PP2A activity. In addition, our data provide evidence that the regulatory subunit isoform B55α targets PP2A to HDAC5 downstream of β‐AR stimulation in cardiomyocytes, and is required for the dephosphorylation of HDAC5 at S259. Collectively, these findings may have important implications regarding the molecular mechanisms underlying cardiomyocyte responses to β‐AR stimulation in physiological and pathological settings.qPCR stimulation.qPCR stimulation. Secondly, we provide data indicating that, upon β‐AR stimulation, B55α is likely to target the PP2A holoenzyme to HDAC5 to facilitate its dephosphorylation at the key regulatory phospho‐acceptor residues. The mechanism by which β‐AR stimulation induces an increased B55α‐PP2A/HDAC5 association in cardiomyocytes requires further investigation. In this regard, recent crystallographic analyses of the B55α‐PP2A complex have defined not only the structure of the holoenzyme but also the likely binding interfaces between the B55α subunit and another phosphoprotein substrate of B55α‐PP2A, Tau.Our findings concerning PP2A‐mediated dephosphorylation of HDAC5 add significantly to data from an earlier study in NRVM, which has shown that pretreatment with the PP2A inhibitor OKA inhibits the ability of isoproterenol stimulation to attenuate HDAC5 phosphorylation in response to GBacks and colleagues,2+] transient amplitudeThe cellular imaging methodology that we have established and utilized in the present study provides the opportunity to objectively determine the nuclear versus cytoplasmic distribution of fluorescently tagged proteins in live cardiomyocytes, or indeed any other cell type, through the concomitant use of fluorescent dyes with distinct spectral properties  to demarcate the nuclear compartment and the remainder of the cellular volume. A key advantage of this methodology is the ability to monitor total fluorescence in each compartment across the entire cell, without the potential subjectivity that arises from the use of investigator‐selected regions of interest and/or z‐section, variations in both of which we have found to have a marked impact on the intensity of the GFP‐HDAC5 fluorescence signal. Application of this method has allowed us to definitively determine the impact of isoproterenol stimulation on HDAC5 nucleocytoplasmic shuttling in adult cardiomyocytes, and to interrogate the roles of the S259/S498 and S279 phosphorylation sites in regulating HDAC5 localization. Our findings regarding the impact of isoproterenol stimulation on the subcellular distribution of HDAC5 are consistent with the earlier reports of Ha et al,Fcyto and increases in Fnuc and Fnuc/Fcyto across the whole cell without impacting on Fcell  to induce GFP‐HDAC5 nuclear export in ARVM, Figures  and 3, i Figures . These p Figures . Further Figures  and did 1‐AR subtype and requires both PKA and PP2A activity, with the latter targeted to HDAC5 through the PP2A regulatory subunit B55α. These findings reveal new avenues of investigation toward a better understanding of the molecular mechanisms through which altered sympathetic activity and β‐AR signaling impact on cardiac phenotype, particularly in the context of cardiac remodeling.To conclude, in the present study, we describe a new method for studying the nuclear versus cytoplasmic localization of GFP‐HDAC5 in adult cardiomyocytes, which has allowed us to conclusively demonstrate that β‐AR stimulation induces the nuclear accumulation of HDAC5 through a mechanism that requires PKA activity. Furthermore, we show that dephosphorylation of S259/S498 in HDAC5 is the key mechanism that triggers nuclear accumulation, and that such dephosphorylation occurs downstream of the βThis research was supported by the British Heart Foundation (Project Grant PG/12/48/29638 and Centre of Research Excellence Award RE/13/2/30182) and in part by the Victorian Government's Operational Infrastructure Support Program. Weeks is supported by an Overseas Research Fellowship from the Heart Foundation of Australia (O12M6802). Bernardo is supported by an Alice Baker and Eleanor Shaw Fellowship from the Baker Foundation .None.Data S1. Supplemental methods.Figure S1. Specificity of antibodies for pS259, pS279, and pS498 in HDAC5. A, Region of human HDAC4 used to generate an antibody against phosphorylated S266  and sequence alignment showing 100% amino acid identity with human HDAC5. The conserved PKA phosphorylation site  is underlined. B, Cell lysates from ARVM expressing GFP, wildtype (WT) GFP‐HDAC5, or nonphosphorylatable  variants of GFP‐HDAC5 were separated by SDS‐PAGE and analyzed by Western blotting. The pS266 HDAC4 polyclonal rabbit antibody detected a band of the correct molecular weight in cells expressing WT and S259/498A GFP‐HDAC5, but not in cells expressing S279A GFP‐HDAC5 or GFP alone, demonstrating cross‐reactivity with pS279 in HDAC5. Similarly, commercially available antibodies for pS259  and pS498 (Abcam 47283) detected bands of the correct molecular weights in cells expressing WT and S279A GFP‐HDAC5, but not in cells expressing S259/498A GFP‐HDAC5 or GFP alone. GFP and GFP‐HDAC5 were detected by immunoblotting with an anti‐GFP antibody .Figure S2. Selective activation of PKA in ARVM using N6‐benzoyl cAMP. Troponin I (TnI) phosphorylation was used as a readout of PKA activity in ARVM treated with isoprenaline (ISO) for 10 minutes, or with N6‐benzoyl cAMP (BNZ), 8‐CPT‐2′‐O‐Me‐cAMP (CPT), or vehicle control (CON) for 30 minutes. A, Five hundred micromoles per liter BNZ induced a similar increase in TnI phosphorylation as 10 nmol/L ISO. B, BNZ treatment increased TnI phosphorylation, whereas equivalent concentrations of CPT had no effect. C, Ten nanomoles per liter ISO and 500 μmol/L BNZ reduced the phosphorylation of HDAC5 at all 3 sites, whereas 500 μmol/L CPT had no effect.Figure S3. Variability associated with measurement of GFP‐HDAC5 nuclear and cytoplasmic fluorescence intensities in live ARVM. A, An ARVM expressing GFP‐HDAC5 was imaged as described in the Methods section. Five sequential z‐sections from an individual cell are shown. The fluorescent signal from GFP‐HDAC5 was used to define the cell boundary (solid white line), the nuclear boundaries (dashed red and yellow lines), and example regions of interest within the cytoplasm (dashed white lines). Scale bar is 10 μm. B, Measurements of the nuclear fluorescence can vary markedly, depending on the focal plane and the nucleus chosen for quantification. Graph shows average fluorescence intensity (F) measurements from 3 binucleated cells. Measurements were obtained from 3 sequential z‐sections per nucleus (red and yellow data points for Cell 1 correspond to the red and yellow regions of interest in A). C, There is variability associated with sampling small regions of interest within the cytoplasm. Graph shows F measurements for 8 regions of interest per z‐section from sequential z‐sections of the cell shown in A.Figure S4. B55α associates with GFP‐HDAC5. A, Protein lysates (5–15 μL) from ARVM were separated by SDS‐PAGE and the resulting Western blot probed with a mouse monoclonal antibody raised against rat B55α (Santa Cruz sc‐81606). B, Protein lysates from ARVM expressing GFP, GFP‐HDAC5, or neither were immunoprecipitated using a GFP‐Trap kit . Immunoprecipitates were separated on SDS‐PAGE gels and the resulting Western blots probed with antibodies against GFP, B55α, B56α, and B56δ.Figure S5. Isoproterenol increases the association between endogenous HDAC5 and B55α. HDAC5‐containing complexes were immunoprecipitated from NRVM cell lysates following treatment with 1 μmol/L isoprenaline (ISO) or vehicle (VEH) for 60 minutes and the resulting Western blots probed for HDAC5 and B55α. Representative Western blots and grouped data from 3 independent experiments. Unpaired t test. *P<0.05 vs VEH.Figure S6. Subcellular distribution of B55α in ARVM. ARVM were fractionated into Triton X‐100‐soluble (SOL) and ‐insoluble (INSOL) fractions via centrifugation following treatment with 10 nmol/L isoproterenol (ISO) or vehicle control (CON) for 45 minutes. Representative Western blots and quantitative data from 4 independent experiments. In each experiment, the B55α signal in CON and ISO fractions was normalized to the signal in the respective inputs. No significant differences were detected by unpaired t test. The GAPDH and histone 2B blots are the same as those that appear in Figure Figure S7. ISO had no effect on S279 and S498 phosphorylation in NRVM. NRVM expressing GFPHDAC5 were transfected with scrambled (Scr) or PPP2R2A (B55α) siRNAs for 48 hours prior to treatment with 1 μmol/L ISO or CON for 60 minutes. Grouped data from 4 independent experiments. No significant differences were detected by 2‐way ANOVA.Figure S8. Quantification of GFP‐HDAC5‐containing puncta in ARVM treated with 10 nmol/L ISO. A, Screenshots from Fiji analysis of GFP‐HDAC5‐containing puncta in live ARVM at baseline and 45 minutes after the addition of 10 nmol/L isoprenaline (ISO). B and C, Quantification of 0.1 to 10 μm2 objects at baseline (B) and following treatment with vehicle (VEH) or isoprenaline (ISO) for 45 minutes (C). n=25 to 27 cells from 2 hearts per group. The median and interquartile range are shown. Mann–Whitney tests; ns, not significant.Figure S9. Examples of mislocalized GFP‐HDAC5 in ARVM. Maximum intensity projections of ARVM transduced with adenoviruses to express GFP‐HDAC5. Z‐stacks were acquired as described in Methods. A, Examples of cells that were included in the analysis of GFP‐HDAC5 nucleocytoplasmic shuttling. B, Examples of cells that were excluded from the postimaging analysis of GFP‐HDAC5 nucleocytoplasmic shuttling because of the mislocalization of heterologously expressed GFP‐HDAC5 at baseline. Scale bar is 20 μm.Click here for additional data file.


At many marine-terminating glaciers, the breakup of mélange, a floating aggregation of sea ice and icebergs, has been accompanied by an increase in iceberg calving and ice mass loss. Previous studies have argued that mélange may suppress calving by exerting a buttressing force directly on the glacier terminus. In this study, I adapt a discrete element model to explicitly simulate mélange as a cohesive granular material. Simulations show that mélange laden with thick landfast sea ice produces enough resistance to shut down calving at the terminus. When sea ice within mélange thins, the buttressing force on the terminus is reduced and calving is more likely to occur. When a calving event does occur, it initiates a propagating jamming wave within mélange, which causes local compression and then slow mélange expansion. The jamming wave can also initiate widespread fracture of sea ice and further increase the likelihood of subsequent calving events. Observed sea-ice loss near ice sheets has, in many cases, been accompanied by accelerated iceberg calving. Here, using a new model, the authors show that iceberg calving from glaciers can be suppressed by a mélange of sea ice and icebergs, with an increased likelihood of calving as sea ice thins. Projections of the future ice sheet contribution to sea level rise can vary by several metres depending on the rate of iceberg calving at ice sheet margins1245759Model simulations of outlet glaciers111213141210In this study, I adapt the Discrete-Element bonded-particle Sea Ice modelUsing this new approach to modelling mélange, I show that when bonded by a matrix of thick landfast sea ice, mélange is capable of exerting sufficient buttressing force on the glacier terminus to shut down calving. Thinning of sea ice reduces mélange buttressing force on the terminus, increasing the likelihood of a calving event occurring. When a calving event does occur, it initiates a propagating jamming wave within the mélange, which can cause fracture of the sea-ice matrix. Such large-scale sea ice fracture within mélange decreases the buttressing force of mélange on the glacier terminus and further increases the likelihood of subsequent calving events.In winter months, sea ice in Greenland fjords can grow to many metres in thickness due to the freezing-in of small pieces of icebergs and strong pressure ridging19I consider two idealized channel configurations that resemble many fjords in Greenland. The ‘straight' channel configuration  has a unIn the narrowed channel configuration  preventing rotation of fractured icebergs away from the terminus11Previous studies have estimated that a width-averaged mélange buttressing force of order 10From late spring until early fall, mélange at the terminus of many marine-terminating outlet glaciers in Greenland primarily consists of icebergs with little-to-no interstitial sea ice. During this period, observations indicate that mélange typically moves at the same speed as the glacier terminus, punctuated by calving events that initiate short intervals of rapid down-fjord mélange motion at speeds thousands of times faster than the background rate of advance2223−1, away from the terminus over a period of 5 min in the narrowed channel configuration. 24et al.−1) and width (1–3 km) of the simulated jamming wave front are broadly similar to these observations, with some small differences in the rate of mélange slowdown following the passage of the jamming wave. Otherwise, individual iceberg speeds (∼1 m s−1) are comparable to iceberg-based GPS measurements that capture rapid mélange flushing eventsI simulate a summertime calving event by prescribing rapid forward motion of a 1,000 m-wide cluster of iceberg elements, at 2.5 m sThe vigorous calving at Jakobshavn in summer is in marked contrast to the complete lack of calving in winter. A rapid transition between these two states occurs in the spring, when sea ice within the mélange begins to slowly thin as incoming shortwave radiation increases and air temperatures warm. Several weeks before air temperatures in the fjord exceed freezing, sea ice rapidly breaks up in a period of hours to days7−1, away from the terminus over a period of 1 min. To understand the mechanism and speed of this spring transition, I simulate the first major calving event occurring in the midst of slow spring thinning of sea ice within mélange. Mélange in the narrowed channel configuration is initialized with sea-ice bonds of 2 m thickness and then brought to a statistical steady state through slow terminus advance where the buttressing force at the terminus is in the range associated with the resumption of calving Rij=λR min, length, bij=λb(ri+rj), and a prescribed thickness, where r is the radius of the two bonded icebergs. I choose λb to be small, as there should be minimal overlap in sea ice on icebergs  and most sea-ice deformation should occur in a narrow zone between icebergs. A sea-ice bond is created when two icebergs without an existing bond come within 10 m of one another. A sea-ice bond is broken, and removed from the simulation, when either the tensile, compressive or shear stresses on the bond exceed material strength thresholds for ice. The material properties of sea ice in mélange, which is composed of a mix of bergy bits and in situ sea ice with significant pressure ridging, are not well known. Consequently, I use strength thresholds falling in the middle of the experimentally measured range for old sea ice, reviewed in Timco and WeeksSea-ice bonds are elastic plates with width, The iceberg size distribution is a truncated log-normal distribution based on ship-based observations of iceberg size on the Greenland continental shelfIceberg diameters are randomly drawn from the distribution described above. Icebergs are then placed randomly within the channel and then compressed to a desired packing density. In the summer jamming wave simulations , a buffehttps://github.com/aarobel/melange-dem. LAMMPS-LIGGGHTS is a software package available publicly from the CFDEM project (http://cfdem.com) through an open-source licence. The DESIgn toolbox is available from the website of A. Herman (http://herman.ocean.ug.edu.pl/LIGGGHTSseaice.html).All code written by the author and used to run these simulations is available freely as a public GitHub repository at How to cite this article: Robel, A. A. Thinning sea ice weakens buttressing force of iceberg mélange and promotes calving. Nat. Commun.8, 14596 doi: 10.1038/ncomms14596 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Animation of mélange simulation with advancing terminus and 1-meter sea ice thickness in a narrow fjord configuration. Fjord sidewall elements are shaded brown, terminus elements are shaded gray, icebergs are shaded white and sea ice bonds are light blue lines. Open water is colored in dark blue.Animation of mélange simulation with prescribed calving event and no sea ice thickness in a narrow fjord configuration. Fjord sidewall elements are shaded brown and terminus elements are shaded gray. Icebergs are shaded according to the magnitude of their horizontal velocity. Open water is colored in dark blue.Animation of mélange simulation with prescribed calving event and 2-meter sea ice thickness in a narrow fjord configuration. Fjord sidewall elements are shaded brown, terminus elements are shaded gray, and sea ice bonds are light blue lines. Icebergs are shaded according to the magnitude of their horizontal velocity. Open water is colored in dark blue.


Furthermore, repertoire analysis indicates that high affinity IgE and IgG1 plasma cells differentiate from rare CD80+CD73+ high affinity memory clones without undergoing further mutagenesis. By identifying the cellular origin of high affinity IgE and the clonal selection of high affinity memory B cells into the plasma cell fate, our findings provide fundamental insights into the pathogenesis of allergies, and on the mechanisms of antibody production in memory B cell responses.The unique differentiation of IgE cells suggests unconventional mechanisms of IgE memory. IgE germinal centre cells are transient, most IgE cells are plasma cells, and high affinity IgE is produced by the switching of IgG1 cells to IgE. Here we investigate the function of subsets of IgG1 memory B cells in IgE production and find that two subsets of IgG1 memory B cells, CD80 IgE is an important mediator of protective immunity as well as allergic reaction, but how high affinity IgE antibodies are produced in memory responses is not clear. Here the authors show that IgE can be generated via class-switch recombination in IgG1 memory B cells without additional somatic hypermutation. Distinctive features of the differentiation of IgE−-producing cells limit the production of high affinity IgE. IgE germinal centre (GC) cells are transient and highly apoptotic, and do not give rise to functional IgE memory B cells (MBC) or high affinity IgE plasma cells (PC)4. Class switching of antigen-specific IgG1 cells to become IgE cells, known as sequential switching, has been proposed as the mechanism involved in the production of affinity-matured IgE antibodies in memory responses7, but the extent by which sequential switching compensates for the lack of functional IgE MBC is not known. Mice deficient in class-switch recombination to IgG1 display profoundly impaired affinity maturation of IgE antibodies5. IgE is still produced via direct class switching of IgM to IgE but other IgGs or IgA do not contribute to the IgE response.IgE antibodies that bind allergens with high affinity are capable of mediating life-threatening anaphylaxis. IgE antibodies are the least abundant in serum, and display the lowest serum half-life of all immunoglobulins9. These findings suggested a need for de novo class-switch recombination to IgE in memory responses and implicated a lack of memory IgE cells. By contrast the IL-4− independence of IgG1 production in memory responses indicated that there were memory IgG1 cells that differentiated into IgG1 plasma cells, a process that is independent of IL-410. It was later shown that IgE–B220+ B cells, but not IgE+B220+ B cells, mediate IgE production in secondary responses3, consistent with the observed lack of functional IgE memory cells11.Previous studies showed that IgE production in secondary responses required CD4 T cell help and the cytokine Interleukin (IL)-4, while production of IgG1 was independent of IL-412. Second, sequencing of the Sμ-Sε switch regions of human IgE genes found Sγ switch region repeat remnants indicative of sequential switching16. Third, repertoire analysis of the rearranged immunoglobulin genes in human peripheral blood B cells identified common lineages between IgG1 and IgE17, suggesting a parental-progeny relationship.Published work supports a function for human IgG cells in generating IgE-producing cells. First, studies of allergen reactivity demonstrated production of allergen-specific IgG1, IgG4 and IgE in allergic individuals, indicative of a co-ordinated regulation of these immunoglobulin isotypes20. It is not known if this process involves new somatic mutation, or if it results from the selective expansion and differentiation of pre-existing memory clones. Mouse MBC are heterogeneous in their origins, phenotypes and functions21. MBC may express IgM, IgG or IgA, and be of GC or extra-GC origin23. It was reported that IgG1 MBC preferentially differentiate into PC upon activation, while IgM MBC give rise to secondary GC24. Studies also identified a subpopulation of IgG1 MBC that preferentially forms PC upon activation, and another that forms GC cells25, but their function in IgE responses remains unknown.Memory antibody responses typically produce a fast increase in the levels and affinity of antigen-specific antibodiesHere, we demonstrate the ability of IgG1 MBC to generate IgE-producing cells in secondary responses. We found that the IgG1 MBC subset with a phenotype that is ‘pro-PC’ gives rise to an early burst of high affinity IgE that mediates anphylaxis, while another ‘pro-GC’ subset generates a late, low affinity and non-pathogenic IgE response. Thus, the contribution of all subsets of IgG1 MBC to IgE potentially modulates the overall IgE pathogenicity. Repertoire analyses of parental MBC and their progenies using high throughput RNA sequencing demonstrated that high affinity clones present at low frequency in the pro-PC MBC subset form the expanded repertoire of high affinity clones in their progeny. These results support a model in which high affinity PC clones are derived from the selection and expansion of rare high affinity IgG1 MBC clones without further mutagenesis. Our findings thus help enhance the understanding of general mechanisms of production of antigen-specific antibodies, as well as the generation and pathogenicity of IgE antibodies.Nippostrongylus brasiliensis (N.b.), and immunisation of TB monoclonal (TBmc) mice26. TBmc mice carry monospecific populations of CD4 T cells specific for chicken ovalbumin (OVA) and of B lymphocytes specific for an influenza virus hemagglutinin peptide (HA). PEP1 is a mutant variant of HA that displays greatly decreased binding to naive B cells from TBmc mice and is used to trace antibody affinity maturation6.The ability of subsets of mouse IgG1 MBC to give rise to IgE-secreting cells was analysed using well characterised models of type 2 responses: infection of BALB/c mice with the helminth parasite +, IgD+, CD138+ and TER-119+ cells, and were then stained with antibodies to IgG1, B220, PDL2, GL7, CD138, CD73 and CD8027. B cells were identified by B220 staining in a CD4− single cell/lymphocyte gate  , CD73−CD80+ single positive (SP), and CD73−CD80− double negative (DN) cells  Fig. . Expresslls Fig. . Notably 10 Fig. , and DP  10 Fig. . As expe+ IgG1 MBC subsets were sorted into DP, SP and DN subsets based on expression of CD73 and CD80. Subset identity, as well as lack of contaminating IgE cells, were confirmed by flow cytometry and RNA/cDNA expression analysis  gene in the 3′ untranslated region of the Il4 gene, thus reporting Il4 transcription through GFP expression. Purified IgG1 MBC and CD4 memory T cells were used in adoptive transfer experiments  that were then infected with N.b. Two weeks later, donor-derived IgEa and IgG1a were measured in the recipient mice  in all groups transferred with IgG1 MBC  indicating that all IgG1 MBC have the potential to contribute to serum IgE.DP, SP and DN IgG1 MBC and CD4 memory T cells were sorted from ice Fig. . IgEa an6. Ten weeks after primary immunisation, IgG1 MBC subsets and CD4 memory T cells were isolated and transferred to Rag1 knockout (KO) mice, and the recipient mice were immunised with OVA-PEP1. Serum antibodies were analysed at weeks 1, 2, 4 and 6.To determine the affinity of IgE derived from the different IgG1 MBC populations, we used the TBmc model of immunisation with OVA-PEP1+ MBC than in the other two groups  and CD73− IgG1 MBC (corresponding to SP plus DN IgG1 MBC) from OVA-PEP1 immunised TBmc mice were adoptively transferred into wild-type (WT) BALB/c mice . Read quality values indicated high quality sequencing, and rarefaction curves demonstrated sufficient sequencing depth  mutations, we determined the repertoire of VDJ heavy chain sequences of parental donor IgG1 MBC and their IgE and IgG1 derived cells (referred as IgE and IgG1 progenies of IgG1 MBC) using next generation sequencing. Samples utilised for sequencing contained roughly equivalent number of cells  contribute to high affinity binding to PEP1 in TBmc miceComparative analysis of the VDJ sequences of each donor IgG1 MBC subpopulation with their IgE and IgG1 progenies, resulted in several informative findings. First, VDJ genes in the IgE and IgG1 progenies of DP IgG1 MBC had more nucleotide and amino acid mutations, including more high affinity mutations, than the donor DP population. Second, IgE and IgG1 derived from DP IgG1 MBC had more mutations than the progenies of the SP or DN IgG1 MBC. Third, among the progeny of DP IgG1 MBC, IgG1 cells consistently carried more mutations than IgE cells Fig. , 7.Fig. The enrichment in high affinity mutations from donor DP IgG1 MBC to progeny cells is exemplified in Fig. In summary, there was a marked increase in affinity during the differentiation of DP IgG1 MBC cells into PC, and the establishment of a remarkable hierarchy of affinity of IgG1 antibodies over IgE antibodies.6; Supplementary Table The rapid appearance of high affinity PC could be explained by selective clonal expansion of DP memory precursors, and/or by additional somatic mutation and selection of memory clones. To address this, we established clonal relationships using the VDJ repertoire data. From a library of CDR3 amino acid sequences identified in DP donor IgG1 MBC and progenies containing sequences with 0.01% or higher frequency in at least one sample, we identified 35 CDR3 sequences that contain high affinity mutations . We identified 17,012 expressed genes in the data set. Inter-sample similarity analysis using multidimensional scaling (MDS) showed that all IgG1 MBC subsets were distantly related to IgG1 GC cells, the SP subset was intermediate between DP and DN subsets, and notably, the DN subset was the closest to naive B cells Fig. .Fig. 6Tr31. In the CMap, IgG1 GC cells and naive B cells yielded positive and negative scores, respectively  signatures of LPS, and LPS plus anti-CD40 activated B cells were generated from available data sets (GSE35998) and used in a connectivity map (CMap) analysisely Fig. . StrikinThe comparison of the three IgG1 MBC subsets identified 1114 DEG (Supplementary Dataset 25. Among DEG with higher expression in the DP subset were the transcription factors Arid3a (Bright) and Gtf2i, which regulate the IgH locus transcription32, E-box binding proteins Tcf4, Bhlhe41 and Zeb2, and, importantly, Zbtb20, a regulator of PC differentiation and longevity34. Importantly, DN IgG1 MBC expressed higher level of genes that promote the GC fate and inhibit the PC fate, such as Bcl635, Foxo137, Foxp139, Bach240 and Ets138. Metacore analysis of pathway/processes indicate B cell receptor (BCR) pathway, cell adhesion, proliferation, cytokine signalling, among the top enriched entities  identified transcription regulation, cell surface molecules , and kinases as mainly represented among DEG of DP or DN subsets, with the SP subset presenting an intermediate and more heterogeneous profile Fig. 25. Among25. The expression of DEG identified by Zuccarino-Catania et al. was determined in our RNA-seq data set. The comparison demonstrates many common DEG in DP and DN subsets analysed in both studies  and Bcl6 (GC). There are however some differences between that expression analysis and ours presented herein. For microarray analysis, Zuccarino-Catania et al. used total memory B cells , sorted based on PDL2 and CD80 expression25, while we sorted PDL2+IgG1+ memory B cells based on differential expression of CD73 and CD80. CMap comparison of both data sets demonstrated similarity between DP populations but not SP or DN populations  model. We used TBmc mice immunised with OVA-PEP1 as a source of donor IgG1 MBC and an adoptive transfer system as described above Fig. . We obtaRag1 KO (RKO) serum added to DP-serum , CD73−CD80+ (SP) and CD73−CD80− (DN) cells, and tested their ability to give rise to IgE-producing cells in a recall response. We found that only the DP IgG1 MBC subset generated IgE PC producing high affinity IgE capable of mediating anaphylaxis. SP and DN IgG1 MBC also gave rise to IgE PC, however, their response were delayed and the IgE antibodies produced were of low affinity and non-pathogenic.The mechanisms that generate and maintain the memory of IgE responses are poorly understood. In previous work, we showed that the differentiation of IgE cells follows a unique pathwayIn contrast, IgG1 PC was mainly generated from the DP IgG1 MBC and contained predominantly high affinity clones. Interestingly, within the progeny of the same DP IgG1 MBC, more IgG1 than IgE cells carried high affinity BCR mutations. The conditions that drive the same DP IgG1 MBC to generate IgG1 or IgE PC remain a major unresolved issue.6. Low affinity/allergen non-specific IgE, and high affinity IgG1, may protect from allergic reactions driven by high affinity IgE in different ways. Low affinity/allergen non-specific IgE bound to mast cells would dilute high affinity IgE on the surface of mast cells, decreasing the probability of mast cell degranulation. High affinity IgG1 may neutralise allergens in circulation, reducing their availability. In addition, allergen-IgG1 immune complexes bound to FcγRIIB on mast cells would negatively regulate FcεRI signalling41.Our observations predict that the IgE antibody pool would tend to be more heterogeneous and of lower average affinity than the IgG1 antibody pool. In fact, we observed delayed affinity maturation of the IgE response compared with the IgG1 response over the course of repeated immunisations in mice42, high affinity DP IgG1 MBC clones appear to have the greatest ability to become PC.When comparing the frequency of high affinity clones between the DP IgG1 MBC and their IgE and IgG1 PC progeny, we observed a striking enrichment of high affinity clones in the PC progeny. We asked if this occurred through direct expansion of pre-existing memory B cell clones, or if it required further somatic mutation and selection. By comparing the nucleotide sequences encoding high affinity CDR3 H domains of donor and progeny B cells, including silent mutations with no selective value, we discovered that most high affinity CD3-encoding nucleotide sequences in progeny cells were present in the donor memory B cells. These findings support a model whereby high affinity PC are derived from memory cell clones by selection and expansion without further mutagenesis. It is thus likely that clonal selection of IgG1 MBC would require specific antigen capture through high affinity BCR, and antigen processing and presentation to antigen-specific CD4 T cells. Analogous to GC cells that become PC43, is expressed and functions in at least a subset of activated DP IgG1 MBC. Since most high affinity PC derived from the DP IgG1 MBC subset do not carry additional mutations, and differentiation of IgG1 MBC into PC is fast, an intermediate GC phase before PC differentiation appears unlikely.Generation of IgE PC from DP IgG1 MBC implies that the enzyme activation-induced cytidine deaminase (AID), which mediates class-switch recombination and somatic hypermutation46, the DN response must depend on interactions with T helper cells. It is possible that DN IgG1 MBC with low affinity BCR are also preferentially selected for GC differentiation. This would ensure that the new memory pool, which is mostly derived from the DN IgG1 MBC , is of a broad affinity range. DN IgG1 MBC that switch to IgE may be also co-opted from low affinity clones and prevented to become GC cells by the intrinsic PC-driving activity of membrane IgE47.Interestingly, there was very little or no selection of high affinity memory clones in the differentiation of DN IgG1 MBC to IgE PC. This was surprising because the DN IgG1 MBC donor pool did contain high affinity clones, albeit at a lower frequency than the DP IgG1 MBC. Since DN IgG1 MBC differentiate into GC cells, and T-B cell interactions are essential for GC formation and T follicular helper cell differentiationZbtb20, a regulator of PC survival and longevity33. On the other hand, DN IgG1 MBC expressed higher levels of several inhibitors of activation, and of genes that inhibit PC differentiation and promote the GC fate, such as Bcl635, Foxp139 and Bach240.Interestingly, we found that the expression profile of DP IgG1 MBC was closer to that of activated B cells than to naive B cells, while the reverse was true for DN IgG1 MBC. DP IgG1 MBC appeared poised for rapid activation and differentiation into PC, expressing higher levels of transcription factors that regulate the IgH locus transcription, as well as 3. This is entirely consistent with the lack of IgE GC cells in the secondary response of IgG1 MBC shown in this manuscript.Interestingly, we described that IgE GC cells did not have switch footprints from the Sγ1 regions, and thus were derived from IgM cells and not from IgG1 cells+CD80+) MBC provided fast production of high affinity IgE antibodies, while the DN IgG1 (CD73–CD80−) MBC gave rise to a delayed response of low affinity non-pathogenic IgE. In addition, we showed that IgG1 MBC subsets have alternate functions with regards to the production of IgE and IgG1 subsets. Activation of IgG1 MBC results in rapid production of high affinity IgG1, formation of new IgG1 GC cells, and expansion of the IgG1 memory pool. In contrast, IgE cells generated from IgG1 MBC are exclusively IgE PC that secrete antibodies of broader affinity than IgG1 antibodies. These mechanisms restrict the production of high affinity IgE and reduce the pathogenicity of the IgE pool.In summary, our studies revealed an important role of IgG1 MBC subsets in generating and maintaining the memory of IgE responses. DP IgG1  and Rag1 KO BALB/c (stock 003145) mice were purchased from The Jackson Laboratory. CB17 mice  were purchased from Taconic Biosciences. TBmc mice26 were crossed with 4get mice to generate 4get TBmc mice. All mice were housed in the specific pathogen-free animal facility of the Biological Research Center (BRC) A*STAR, Singapore. Male and females mice between 6 and 8 week of age were used for experiments. Mice were killed by CO2 inhalation. All animal procedures were approved by the BRC/A*STAR and NYU School of Medicine Institutional Animal Care and User Committee. TBmc mice and 4get TBmc mice were immunised by intraperitoneal injection of 100 µg OVA-PEP1 , Sigma catalogue # A2512, conjugated to peptide YPYDVPDFASLRS (PEP1)) in alum6. BALB/c and 4get BALB/c mice were infected subcutaneously with 500 L3 larvae of N.b.BALB/c (stock 000651), 4get BALB/c3) for 30 min at 4 °C. Intracellular staining of Ki67 was conducted using anti-Ki67 antibody (clone 16 A8) and Foxp3 staining buffer as described by the manufacturer . Cell surface IgE staining was performed using R1E4 antibody48 which does not recognise FcεRI-bound or FcεRII- bound IgE3. Cells were analysed using an LSR II 5-laser flow cytometer (BD) or sorted using a FACSAria II 5-laser cell sorter (BD). Purified cells were used for transcriptomic analysis, VDJ repertoire sequencing, or for adoptive transfer experiments. Memory B cells (MBC) were isolated from pooled spleen and mesenteric LN (mLN) of TBmc mice at 10 weeks after immunisation with OVA-PEP1 in alum, or from BALB/c mice 10 weeks after infection with N.b. Memory B cells were pre-enriched by magnetic negative selection sorting using biotinilated antibodies to CD3e (clone145-2C11), IgD (clone 11-26c), CD138 (clone 281-2) and TER-119 (clone TER-119), and streptavidin-labelled magnetic beads . Negatively selected cells were stained with antibodies eVolve605 anti-CD4 (clone RM4-5), eFluro450 anti-IgM (clone II/41), APC-eFluro780 anti-B220 (clone RA3-6B2), PE-Cy7 anti-IgG1 (clone M1-14D12), PE anti-CD80 (clone 16-10A1), PerCP-eFluro710 anti-CD73 (TY/11.8), from eBioscience, and BUV395 anti-PDL2 (clone TY25) and APC anti-GL7 (clone GL7), from BD Bioscience. For flow cytometry sorting, the cells were first gated as IgM−CD4−IgG1+B220+GL7−PDL2+ (IgG1+ memory B cell gate), and the CD73+CD80+ (DP), CD73−CD80+ (SP) and CD73−CD80− (DN) subsets were subsequently sorted. T cells were isolated from pooled spleen and mLN of 4get TBmc mice at 10 weeks after immunisation with OVA-PEP1, or from 4get BALB/c mice at 10 weeks after infection with N.b. Single-cell suspensions from the pooled spleen and mLN were pre-enriched for CD4+ T cells using the Miltenyi T cell isolation kit II . The pre-enriched cells were then stained with the following antibodies: Alexa700 anti-CD4 (clone GK1.5), APC anti-CD45RB (clone C363.16A) and PerCP anti-CD25 (clone PC61.5), from eBioscience. CD4+CD25–CD45RBlow/intGFP+ cells were sorted by flow cytometry and are referred to as CD4 memory T cells. A list of all antibodies used is provided in Supplementary Table Single-cell suspensions were incubated with 10 µg/ml anti-CD16/32  for 15 min at 4 °C before surface labelling with antibody cocktails in staining buffer  γ-irradiated BALB/c or CB17 mice. For irradiation a Gammacell 40 Exactor irradiator with a 137Cs source was used. The recipient mice were subsequently immunised or infected, matching the treatment of the donor mice. Spleen, BM and serum were collected at indicated time points for analysis of serum antibodies, flow cytometry analysis of donor-derived B cells, or for collecting of RNA.IgG1 MBC subsets and GFPa and IgG1a antibodies (in CB17 recipients), were determined by ELISA as described6. To measure antigen-specific IgE, the sera were first depleted of IgG antibodies by incubation with GammaBind Plus Sepharose . For antigen-specific ELISA assays, 96-well plates were coated with 2 μg/ml HA (YPYDVPDYASLRS) or PEP1 peptides in PBS. For total IgE and IgG1 assays, plates were coated with 2 μg/ml of rat-anti-mouse IgE  or goat F(ab’)2 anti-mouse IgG1 (Southern Biotech) respectively. The plates were incubated overnight at 4 °C, washed with washing buffer (PBS + 0.05%Tween-20), and blocked with blocking buffer , for 1 h at room temperature. Serial dilution of serum samples and standard isotypes  in blocking buffer were then added to wells in duplicate and the plates were incubated 4 h at room temperature and then washed. For detection of IgE antibodies, the plates were incubated for 1 h at room temperature with goat anti-mouse IgE-HRP (Southern Biotech). For IgEa detection, the plates were first incubated with anti-mouse IgEa-biotin antibody , followed by streptavidin HRP . For IgG1 detection, goat anti-mouse IgG1-biotin antibody (Southern Biotech), followed by incubation with streptavidin HRP. For IgG1a detection, the plates were incubated with anti-mouse IgG1a-biotin  was added to each well, followed by incubation with Streptavidin HRP. After washing, 100 µl TMB substrate solution  was added to the wells. The reaction was stopped by addition of 50 µl 2 N H2SO4, and optical density was then measured at 450 nm using Tecan Plate Reader (reference at 590 nm).Serum levels of PEP1- and HA- specific IgE and IgG1, total IgE and IgG1, or total IgEFor the passive cutaneous anaphylaxis assay (PCA), 20 µl of IgG-depleted serum was injected intradermally into the ears of naive BALB/c mice. Twenty-four hours later, the mice were injected intravenously with 50 μg of OVA-PEP1 and 1% Evans Blue in PBS and were sacrificed 30 min later. The extravasation of Evans Blue, indicating increased vascular permeability due to anaphylaxis, was recorded by photography.+ MBC were isolated from pooled spleen and mLN of TBmc mice 10 weeks after immunisation. A fraction of each MBC purified subset was used for RNA extraction. Purified live IgG1+ MBC were injected intravenously into Rag1 KO mice together with CD4 memory T cells isolated from immunised 4get TBmc mice. Recipient mice were immunised with OVA-PEP1 in alum. Two weeks later, spleen and BM were collected for RNA extraction.TBmc and 4get TBmc mice were immunised with OVA-PEP1 in alum. DP, SP and DN IgG1+ MBC and from spleen and BM of recipient mice were extracted using RNeasy Mini Kit . cDNA was then synthesised using SuperScript II Reverse Transcriptase , and IgE and IgG1 amplicon sequence libraries were prepared by two-rounds of PCR amplification using LongAmp Taq DNA polymerase . The reaction mix for the first round of 15-cycles amplification contained a forward primer (5′-TGAAACTCTCCTGTGCAGCC) binding to the V region and reverse primers specific for the first exon of Cε (5′-AAGGGGTAGAGCTGAGGGTTC-3′) or Cγ1 (5′-TAGACAGATGGGGGTGTCGT-3′). For the second round of PCR amplification, barcodes for identifying and de-multiplexing individual samples, and Illumina adapter sequences were added to the template. Amplification was carried out for 30 cycles. Amplicons in the size range of 450–500 base pairs (bp) were gel purified using Qiaquick Gel Extraction Kit  and quantified using Quant-iT Picogreen dsDNA Assay kit . qPCR was performed on the amplicon library to ascertain the loading concentration using KAPA library quantification kit . The library was sequenced using the Illumina MiSeq to generate 250 bp paired-end reads at a sequencing ranging from 0.1 to 0.8 million reads per sample.Total RNA from donor IgG149. Clonotypes were clustered based either on CDR3 alone or CDR1, CDR2 and CDR3 together. Resulting clonotypes were then further grouped by amino acid identity. Selected clonotypes were further characterised by DNA identity. Sequence alignment, clustering and general data morphing was performed with custom scripts in pipeline pilot (www.accelrys.com). The VDJ H data sets have been deposited in NCBI Bioproject, under the accession code PRJNA319596.The VDJ sequences were analysed with the MiXCR software+ MBC were isolated using the Arcturus PicoPure RNA Isolation Kit . cDNA was synthesised using SuperScript II Reverse Transcriptase . Quantitative PCR (QPCR) for selected gene transcripts was carried out on an Applied Biosystems StepOnePlus Real-Time PCR system using Power SYBR Green PCR Master Mix . The following oligonucleotide pairs were used: 5′-GTACGACGAGAACGGGTTTG-3′ and 5′-AGTTCACAGTGCTCATGTTCAG-3′ for Cε mature transcript; 5′-GTACGACGAGAACGGGTTTG-3′ and 5′-GGATCCAGAGTTCCAGGTCACT-3′ for Cγ1 mature transcript; 5′-TGACAGGATGCAGAAGGAGA-3′ and 5′-GTACTTGCGCTCAGGAGGA-3′ for β-Actin trancript. Gene expression of mature Cε and Cγ1 transcripts was normalised to β-Actin.Total RNA from spleen cells was isolated using TRIzol . Total RNA from sorted naive B cells and IgG1N.b. using Arcturus PicoPure RNA Isolation Kit . RNA quality was assessed by a Bioanalyser (Agilent Technologies), all samples had RIN ≥ 7.4. From each sample, 2 ng of RNA were subjected to cDNA synthesis using NuGEN Ovation RNA-Seq System V2 kit  according to the manufacturer’s protocol. Libraries were made using NuGENEncore Rapid Library Systems kit  according to the manufacturer’s protocol with 500 ng of cDNA. The libraries were subjected to an indexed paired-end sequencing run of 2 × 51 bp on an Illumina HiSeq 2000 sequencer.RNA was isolated from sorted B cell subsets of BALB/c mice 10 weeks after infection with http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Quality checked, paired-end reads were aligned to the mm9 reference genome assembly using STAR aligner50. Reads were allowed to map across splicing junctions as per gencode mouse version M1 annotations51. FeatureCounts52 was used to calculate read counts covering each gencode gene. Then edgeR package53 was used to normalise raw read counts over genes to counts per million mapped reads (CPM) using the TMM method. Low abundance genes with CPM < 1 in all cell types were filtered out and subsequently differential gene expression analysis was performed in edgeR with a negative binomial model. DEG across cell types were defined based on a 0.05 false discovery rate (FDR) and a minimum expression threshold of log2CPM > 1. Enrichment analysis of gene ontology terms in DEG was performed using DAVID version 6.854. Signalling pathways and biological process networks significantly modulated by the DEG were identified using Metacore software suite licensed from Thomson Reuters Life Sciences Research. Connectivity map (CMap) analysis comparing RNA-seq gene expression profiles with gene expression signatures derived from public data was performed using the ‘gCMap’ package in R Bioconductor (version 1.16.0). The expression data sets have been deposited in NCBI GEO under the accession code GSE83436.The RNA sequencing reads were subjected to quality control testing using FastQC  for paired groups. Non-parametric Kruskal–Wallis rank-sum test was used to calculate P value in Fig. The The repertoire data sets generated and analysed during the current study are available in NCBI Bioproject, under the accession code PRJNA319596. The transcriptomic data sets are available in NCBI GEO under the accession code GSE83436.Supplementary InformationDescription of Additional Supplementary FilesSupplementary Dataset 1Supplementary Dataset 2Supplementary Dataset 3


Double-membrane autophagosomes are the hallmark of autophagy, a catabolic process conserved among eukaryotes. Autophagy is crucial for the degradation of unwanted structures such as unfolded proteins, protein aggregates and dysfunctional organelles, which, if accumulated, could impair cellular homeostasis. Hence, autophagy dysregulation leads to the development of several pathologies including neurodegeneration, metabolic diseases and cancer. Therefore, modulation of the autophagic flux is a new field being explored in the search of novel therapies for various illnesses. A better understanding on how autophagosomes are formed is thus crucial to find new molecular targets for drug development.During the initial steps of autophagosome biogenesis, activation of the Atg1/ULK kinase triggers the recruitment of other autophagy-related (Atg) proteins to a specialized site known in yeast as the phagophore assembly site (PAS). At the PAS, a precursor cistern called phagophore is generated and subsequently elongated and sealed into an autophagosome. These principles are highly conserved and therefore also found in mammalian cells. The sequential association of the Atg proteins to the PAS and their cross-talk is tightly regulated in time and space to avoid the formation of aberrant and potentially cytotoxic intermediates. While Atg proteins decorate autophagosomal membranes throughout the expansion of phagophores, most of them are absent on complete autophagosomes prior to their fusion with vacuoles/lysosomes . The cleIn our study, we proposed a model in which the Atg1 kinase can phosphorylate Atg4 at Ser307 on the surface of autophagosomes to locally inhibit Atg4 proteolytic activity [It is important to point out that Atg4 phosphorylation by Atg1 is very likely not the only way of regulating Atg4 proteolytic activity on autophagosomal membranes. For example, Atg4 is recruited onto autophagosomes by a recently described Atg8-PE association region (APEAR) motif, which preferentially binds Atg8-PE, and at least one C-terminal LC3-interacting region (LIR) motif [Legionella RavZ-mediated LC3-PE C-terminal processing relies on N- and C-terminal LIR motifs in the RavZ protease, which are involved in both the interaction with the substrate and the opening of the catalytic groove required to access the bond that has to be cleaved [Topologically, Ser307 is positioned at the entry of the groove accommodating the Atg4 catalytic site and therefore Atg1 cannot easily access it [ cleaved . With th cleaved . HoweverRemarkably, a similar inhibitory mechanism for the Atg4 deconjugating activity has been recently described in mammalian cells . Althoug