Nucleophosmin (NPM) is a nucleolar protein involved in ribosome assembly and cell homeostasis. Mutations in the C-terminal domain of NPM that impair native folding and localization are associated with acute myeloid leukemia (AML). We have performed a high-throughput screening searching for compounds that stabilize the C-terminal domain. We identified three hit compounds which show the ability to increase the thermal stability of both the C-terminal domain as well as full-length NPM. The best hit also seemed to favor folding of an AML-like mutant. Computational pocket identification and molecular docking support a stabilization mechanism based on binding of the phenyl/benzene group of the compounds to a particular hydrophobic pocket and additional polar interactions with solvent-accessible residues. Since these results indicate a chaperoning potential of our candidate hits, we tested their effect on the subcellular localization of AML-like mutants. Two compounds partially alleviated the aggregation and restored nucleolar localization of misfolded mutants. The identified hits appear promising as pharmacological chaperones aimed at therapies for AML based on conformational stabilization of NPM. Among them, NPM assists in ribosomal biogenesis, modulates the stability of tumor suppressors such as p53 and ARF, is involved in the control of centrosome duplication and participates in DNA repair processes2. NPM is a pentameric protein that consists of several domains. Each subunit contains a β-structured3 oligomerization domain of ca. 125 residues that forms the compact core and is connected through a long (125 aa) and flexible linker to the small (50 aa), globular, α-helical C-terminal domain4. NPM behaves as a nucleolar hub, interacting with many protein partners, as well as nucleic acids5. The binding to G-rich DNA and/or RNA involves the C-terminal domain6 which is probably responsible for the protein retention in nucleoli7. Although mostly nucleolar, NPM continuously shuttles between cytoplasm, nucleoplasm and nucleoli to perform its functions8. This traffic is mediated by importin α/β and CRM1 transport receptors9.Nucleophosmin (NPM), a protein normally enriched in cell nucleoli, is in charge of several functions that affect cell homeostasis10. In particular, NPM1 is the most frequently mutated gene in acute myeloid leukemia (AML)11. Mutations correlate with the aberrant cytoplasmic localization of NPM in blasts from the patients11. This mislocalization of NPM is a hallmark of this subtype of AML, termed “NPMc + ” on that basis, and seems to be a driver event in the development of the disease12.Dysfunction of NPM can lead to cancer pathologies11 involve frame shift insertions of few bases at the end of the NPM1 gene, resulting in a mutant protein with an abnormal sequence in the C-terminal 9–11 residues. The altered sequence implies the loss of one  or more frequently two  tryptophan residues11 that are essential for the packing of the hydrophobic core of the C-terminal domain, and therefore, this domain is unable to fold properly in mutated NPM4. The C-terminal domain of mutant A has been shown to completely lack any secondary structure, while mutant E keeps a partly folded structure4. The defective folding of the C-terminal domain results in the inability of NPM to bind G-rich sequences13, and consequently to be retained in the nucleolus7. In addition, the mutated C-terminal sequence functions as a novel nuclear export sequence (NES)14, that adds to the intrinsic, weak NES or NESs of NPM9, directing the exacerbated export of the protein by CRM1. Both factors, unfolding of the C-terminal domain and acquisition of a novel NES, have been shown to jointly contribute to the aberrant cytoplasmic accumulation of mutant NPM15.The AML-associated NPM mutations16. Due to the alterations described above, NPMc + AML can be considered a misfolding disease, which could be therapeutically addressed by using pharmacological chaperones, small molecules that bind to the mutated protein, increasing its conformational stability. As recently reviewed17, there are now several compounds with pharmacological chaperone potential for a large number of misfolding diseases that have been successfully tested in animal models, and a few that are already in phase II and III clinical trials. These compounds may restore the native fold and/or the proper localization of the mutants18. The search for pharmacological chaperones can be achieved through high-throughput screening (HTS) of compound libraries using differential scanning fluorimetry (DSF) or other methods monitoring increase of stability in the target protein20. This approach has been successfully applied to search for drugs stabilizing various misfolding mutants of enzymes involved in metabolic disorders21.Standard chemotherapy provides complete cure of AML in only about 30% of patients and, therefore, alternative pharmacological strategies are of interest. In this regard, NPM represents an attractive target for therapy14, further supports this notion. We have performed a HTS for compounds that increase the midpoint melting temperature (Tm) of the C-terminal domain of NPM. Several hits were subsequently validated based on their ability to bind and stabilize full length NPM and a C-terminal domain carrying AML-linked mutations, and their effect on human cells expressing YFP-tagged AML-related NPM mutants has been assessed. Structural bioinformatics analyses including pocket identification and molecular docking complemented with molecular dynamics (MD) simulations support a molecular mechanism of correction by these hits based on the stabilization of the hydrophobic core of NPM C-terminal domain. Our results have identified two compounds that are able to favorably modulate the dysfunction of AML mutants.Restoration of the native fold of mutant NPM would be expected to favor binding to nucleolar ligands and therefore increase retention of NPM in the nucleoli. The fact that reinsertion of W288 and W290, key elements for the folding of the C-terminal domain, within the sequence context of mutant A relocates the protein to the nucleoliTm-values of 56.8 ± 0.2 °C, 52.2 ± 0.4 °C, and 57 ± 1 °C, respectively, for C-terminal domain and 59.6 ± 0.1 °C, 56 ± 0.4 °C, and 63.5 ± 1 °C, respectively, for full-length NPM. Thus, although monitoring somehow different events –reflecting rather unfolding of the tertiary (DSF and Trp fluorescence) or secondary (CD) structures– the three methods confirm, in line with reported results22, that the C-terminal domain of recombinant NPM is slightly less stable in isolation than in the context of the full length protein.The NPM C-terminal domain displays a relatively autonomous thermal transition, albeit modulated by the rest of the protein. DSF Fig. , intrinsTm value for the C-terminal domain of NPM in the presence of each compound was compared to the value for the control (with 4% DMSO) to determine the up-shift in Tm (∆Tm). After removal of PAINS23, we reached a final list of 25 hit compounds that stabilized the domain with ΔTm > 6 °C, and the top-three, hereafter termed C1, C2 and C3, displayed the largest ΔTm ( > 17 °C) when tested at ~200 µM , screening a 2560 compound subset of the MyriaScreen diversity collection. The  µM Fig. . C1 and  µM Fig. . Based oS0.5 values of 68 ± 13 µM for C1, 105 ± 17 µM for C2 and 102 ± 23 µM for C3.We further confirmed by SPR experiments that the top three hit compounds also bind to full-length NPM Fig. . ResponsWe further used isothermal fluorescence experiments to validate a stabilizing effect of the top-hit C1 on full length NPM. As seen in the time course of the change in Trp emission fluorescence upon unfolding of the protein, addition of C1 significantly delayed the unfolding transition Figure . Of note4. Addition of C1 induced a slightly more negative ellipticity   and E (mutE), both full-length and fragments corresponding to the C-terminal region. The instability of these mutant forms, however, led to partially degraded preparations, not suitable for biophysical characterization. We thus used a synthesized peptide corresponding to the mutE C-terminal domain. This mutant domain displayed a far-UV CD spectrum compatible with the presence of α-helix secondary structure Fig. , which aity Fig. , compatiity Fig. , suggest°C) Fig. . Due to 24 (PDB ID 2LLH) for pockets on the protein surface. Two pockets were identified with a good druggability score ( > 0.9), as assessed by both the fpocket25 and LigSite algorithms26. The highest scoring pocket (pocket #1), located between helices H2 and H3, was visible in multiple conformers of the C-terminal domain of NPM; another one (pocket #2), scoring second and located between H1 and H2, showed a deep hydrophobic cavity protruding into the interior of the protein  being associated to the “covering” of a solvent accessible hydrophobic area, which represent a good druggable pocket in NPM. Interestingly top-hit C1 establishes in addition favorable polar interactions with solvent-accessible residues that may further stealth and stabilize the hydrophobic core.All together our results point to the large thermal stabilization provided by these compounds (ΔT27. Similar results were obtained with the HEK293T cell line (not shown). The observed behavior agrees with previously published results using ectopically expressed fluorescent protein-NPM constructs28, and reproduces the partially cytoplasmic localization of NPM in blasts of AML patients29, suggesting that this system is a valid model of the localization dynamics of NPM in AML. Additionally, and only in cells expressing mutant variants of YFP-NPM, we observed the presence of bright fluorescent dots, which we attributed to protein aggregation, probably due to the defective folding of the mutant proteins , and treated with compounds C1, C2 and C3. In the absence of compounds, cells transfected with wild type YFP-NPM displayed bright fluorescence in nucleoli Fig. . The nucins Fig. . In agre4 and hence more aggregated31. On the other hand, those cells expressing low amounts of mutant (A or E) YFP-NPM displayed less aggregates and relatively more nucleolar NPM staining. This could be due to the influence of endogenous, wild type NPM, expected to form mixed oligomers with the mutant protein28. Nevertheless, the aggregation cannot exclusively be ascribed to excessive overexpression of the constructs, since the exogenous:endogenous NPM ratio normalized by the transfection efficiency did not correlate with the presence of aggregates. Thus YFP-NPM mutE, displaying the highest density of aggregates, was expressed in lower amounts compared to other constructs . Interestingly, the concentration initially chosen (50 μM) seems to be optimal for getting the desired effects without excessive toxicity. Given the compounds toxicity, their effect on NPM localization / aggregation might be related to a stress-induced proteostatic response. We checked that this was unlikely, however, since the amount of the stress marker Hsp70, based on western blot, was not significantly altered upon treatment with the compounds  toxicity assays and found that the hit compounds, in particular C1, reduced cell viability with estimated ICs Figure . This re32 and avrainvillamide34 have been described to be able to promote NPMc + nucleolar re-localization. Although the molecular basis of the effect of these drugs is so far unclear, it was suggested that the binding of avrainvillamide to both NPM and CRM1 might inhibit NPM export. Our hit compounds, on the other hand, seem to have a different mechanism of action as pharmacological chaperones, largely increasing the conformational stability of NPM through binding to the C-terminal domain. Both C1 and C3 are Lipinski compounds, and neither of them is classified as PAINS23. These hits possess a chemical structure that may be subjected to hit-to-lead expansion and optimization through a medicinal chemistry campaign to increase their affinity for NPM and thus their potency in cells, improve their ADME/PK  and toxicity profile.Collectively our cellular experiments indicate that the compounds C1 and C3 are able to favor the nucleolar retention of NPM mutants and reduce their aggregation. Recently, two compounds, oridoninThrough HTS we have identified three compounds that stabilize the C-terminal domain of NPM. Two of them, C1 and C3, have subsequently been validated for pharmacological chaperone potential in a cellular system, where they can partially reverse the altered properties of mutated NPM. By most likely stabilizing the hydrophobic core of the C-terminal domain these compounds are able, on one hand, to enhance the stability of the mutants in the cell, which otherwise, given their defective folding, are aggregation-prone. More importantly, their action on mutant NPM appears to allow for the partial recovery of NPM interaction with nucleolar components, thus favoring nucleolar retention of the mutants. These compounds may serve as structural scaffolds that promote proper folding of the mutant NPM and are therefore endowed with interest as therapeutic leads for treatment of AML.A subset with the first 2560 compounds of the MyriaScreen Diversity Collection from Sigma Aldrich/TimTec  was used for screening. The compounds (average purity of 95%) were supplied at 2 mg/mL in 100% DMSO. The hits C1, C2, and C3  of NPM with N-terminal His-GST-tag, removable by TEV protease, was created by PCR, using as template a clone of human NPM kindly provided by Dr. Yanping Zhang36 (University of Texas). Full length NPM was produced as previously described9. The C-terminal domain was expressed and purified using a similar protocol, with a final gel filtration chromatography step in 25 mM Tris/HCl pH 7.5, 100 mM NaCl, 2 mM DTT, and 5% glycerol. Full-length NPM concentration values throughout the text refer to the pentamer. The integrity of the produced proteins was checked by mass spectrometry .A bacterial expression plasmid21. The experiments were performed in a LightCycler 480 Real-Time PCR System (Roche Applied Science), in a total volume of 25 μL in 384-well microplates (Roche Applied Science) with the C-terminal domain of NPM, which was diluted to 50 μM in 50 mM sodium phosphate buffer, pH 7.5, with 5X SYPRO Orange. Compounds were dissolved in DMSO and then added to the protein and SYPRO Orange solution to a final concentration of 80 μg/mL (corresponding to an averaged compound concentration of 200 μM) and 4% DMSO. Samples were incubated at room temperature for approximately 30 min before loading them into the PCR-instrument. Controls with 4% DMSO were performed on each plate. The unfolding curves where registered from 20 °C to 95 °C at 2 °C/min scan rate. The midpoint melting temperature (Tm), and the corresponding shift relative to the reference  were calculated for each compound. Compounds that increase the Tm of NPM C-terminal domain were considered to bind and stabilize the protein21.For the initial HTS step, we applied DSF by using the fluorescent dye SYPRO Orange that interacts with the hydrophobic areas of denatured proteinsex and λem 295 and 350 nm, respectively), was recorded in a QuantaMaster™ 300 fluorimeter  attached to a Peltier device, using quartz cuvettes with a path length of 0.3 cm, and 5 nm slits. For kinetic experiments, the compound (or control) solution was previously heated at 50 °C, then the protein was added and the time course of change in intensity at 350 nm was recorded.Since Trp residues of NPM locate in the C-terminal domain, their fluorescence properties report conformational information specific to that region also in the full-length protein. NPM (10 µM), wild type or mutant E C-terminal domain (50 µM) in 50 mM sodium phosphate buffer pH 7.5, were mixed with 150 µM C1 compound, previously dissolved in DMSO. Emission intensity of Trp , was added to a final concentration of 150 µM. CD spectra were obtained at 20 °C between 200 and 260 nm at a scan rate of 20 nm/min, while ellipticity at 222 nm of full length NPM (10 μM), wild type (50 μM) or mutant E C-terminal domain (70 μM) was recorded between 30 and 85 °C at 1 °C/min. Measurements were performed in a Jasco-810 spectropolarimeter equipped with Peltier temperature control, using a quartz cuvette of 0.1 cm path length.S0.5 ≈ KD) were carried out in a Biacore T200 instrument . Thereby, a solution of full length NPM (~ 4 μM) in 10 mM sodium acetate pH 4.0 was immobilized onto the surface of a CM5-S sensor chip  by the standard amine coupling procedure with PBS containing surfactant P20 (0.05%) as running buffer. The reached immobilization levels of NPM onto the CM5-S sensor chip were around 9,200 response units (RU). The low experimental response levels obtained, which indicate that part of the immobilized protein was not active for the binding (approx. 80%), did not affect in any case the measurements since the different quality control checkpoints were satisfactory: no drifts in baseline and control response, no carry-over between samples, no binding to blank/reference surface. After 1 h baseline equilibration, compounds C1, C2 and C3 were assayed in a concentration-dependent manner (0–500 µM), in running buffer containing 5% DMSO at 25 °C, 30 µL/min flow rate, contact and dissociation time of 60 s and final wash after injection with a 50% DMSO solution. Additional blank immobilization, solvent correction curve and negative control (assay buffer) were included for the analysis of the sensorgrams within the Biacore T200 Evaluation software (version 2.0). For the estimation of S0.5 and graph representation SigmaPlot 12.5 was used.Validation of binding and estimation of the concentration of compound at half maximal binding (24 (PDB ID 2LLH) using fpocket25 and LigSite26. The pockets were ranked based on druggability as computed by the fpocket program. Docking of C1 to all the 20 conformers of the C-terminal domain was performed with Glide . The docking modes were ranked based on the Glide score, and the top scoring binding pose was chosen for MD simulation using the Amber package suite37 Parameters for the ligand were generated using the general Amber force field38, and charges were calculated following the restrained electrostatic potential (RESP) method using Gaussian and Antechamber. All-atom models of the protein−ligand complexes were subsequently prepared with AmberTools, using the corresponding Amber99SB force field39. MD simulations were conducted in explicit solvent (TIP3PE water molecules), using a 1 fs time step propagator and Ewald particle mesh with a 10 Å cutoff. Each simulation was run for a total length of 200 ns and analyzed using the cpptraj40 and the Bio3d R-package41.Pocket detection analysis was performed on all 20 conformations in the NMR of structure of NPM C-terminal domain42 of 4 representative structures obtained through hierarchical clustering of RMSD based structural similarity38 of the 20 NMR structures24 (PDB ID 2LLH). 200 ns long MD simulations were performed for each of the resulting mutant models as described for the wild-type simulation above. The resulting trajectories were concatenated and a total of 4000 frames were extracted for pocket analysis using fpocket. The resulting pockets were filtered on distance to pocket #2 and ranked based on druggability score.Mutant variants of NPM were prepared through homology modelling using Modeller9. For subcellular localization analysis of YFP-NPM 9, cells were transiently transfected with the corresponding plasmid. The compounds  were added to the cells 3 hours after transfection, and cultures were maintained for further 24 h. To evaluate the effect of CRM1 inhibition on NPM localization, cells were treated for 3 h with 10 μM leptomycin B . After treatments, cells adhered on coverglasses were fixed with 3.7% formaldehyde and mounted onto microscope slides, using Vectashield aqueous mounting medium including DAPI (Vector Laboratories). For immunostaining, fixed cells were permeabilized with 0.2% (w/v) Triton X-100, blocked with 3% BSA and incubated with anti-fibrillarin antibody (1:50 dilution) and anti-mouse-Alexa 594 antibody (1:400 dilution) for 1 h at RT. Slides were examined at the SGIker Analytical and High Resolution Microscopy in Biomedicine Service (UPV/EHU), using a Zeiss Axioscop fluorescence microscope, and photographed with a Zeiss AXIO Observer.Z1 (mode Apotome 2). For semiquantitative assessment of subcellular localization and aggregation of NPM, more than 200 cells were blind-counted per condition, and classified according to two criteria: a) exhibiting predominantly nucleolar YFP-NPM or not, and b) displaying YFP-NPM aggregates or not.Cells  were cultured as previously describedToxicity was evaluated with the Cytoscan SRB Cytotoxicity assay kit (G-Biosciences) in 96 well plates, titrating HeLa cells (either transfected with YFP-NPM variants or not transfected) with 0–200 μM of compounds C1 and C3. Staurosporine (0–20 μM) was used as control of a toxic compound.Cells were cultured in 6-well plates, washed with PBS and scrapped in 300 µL RIPA buffer supplemented with protease inhibitors. The cells suspension was incubated with gentle agitation for 30 min at 4 °C, following centrifugation at 10000 xg, 4 °C for 20 min. Supernatant was collected and stored at −20 °C. Proteins were separated in SDS-poliacrylamide gel electrophoresis and transferred to nitrocellulose membranes. Primary anti-HSP70 (dilution 1:200), anti-α-tubulin (1:10000), anti-GFP (1:1000) and anti-NPM (1:400) were incubated overnight at 4 °C in 2.5% (w/v) milk in TBST. Secondary antibodies conjugated to HRP were used at 1:3000 dilution for 1 h, RT. Immunoblot images were recorded in MyECL Imager from Thermo Fisher Scientific and densitometry analysis was performed with Fiji software.Supplementary Information


Mycobacterium smegmatis and elucidates the involvement of superoxide in M. smegmatis growth. The maximum inhibition of superoxide generation was observed in the presence of diphenyleneiodonium chloride (DPI), an NADH oxidase inhibitor, compared to other standard inhibitors. After incubation for 24 h, the number of colony forming units (CFUs) was reduced by 6.8 log10 compared to the untreated culture. The inhibitory effect of DPI on M. smegmatis was reversed when the same culture was supplemented with menadione and pyrogallol, which are superoxide generators. Thus, this study reports the source of superoxide generation and its involvement in the growth of M. smegmatis.Superoxide generation is inevitable in aerobic organisms, most of which have developed mechanisms to detoxify superoxides. However, its significance has not been clearly understood in mycobacteria. This study demonstrates that NADH oxidase is the major source of superoxide in  Mycobacterium tuberculosis (Mtb) the causative agent of tuberculosis inside the phagosomes of macrophages is critical for its virulence   . ROS-medigure 1) . Furtherigure 1) , lower eigure 1) , yeast, igure 1) . Among RFigure 1)  . However2 or H2O . Recent ium spp. . InteresM. smegmatis MC2155 strain was a gift from AstraZeneca, India. Sub-culturing of the strain was routinely performed on Dubos albumin agar slants. The stock was maintained at -70°C and sub-cultured once in liquid medium before inoculation in the experimental culture medium. M. smegmatis culture was inoculated in 20 mL Dubos broth in a 100-mL flask incubated at 37°C on an orbital shaker  set at 150 rpm. Solutions of rotenone, antimycin A, DPI, menadione, pyrogallol, and dihydroxyethidum (DHE) were freshly prepared in dimethylsulfoxide (DMSO).Dubos medium was purchased from DIFCO, USA and 2-hydroxyethidium was purchased from Noxygen, Germany. All other chemicals were purchased from Sigma-Aldrich, USA. M. smegmatis was detected by the following modified HPLC-based method, described earlier  of Triton X100. After mixing, an equal volume of acidified methanol [with 1% formic acid (v/v)] was added and the cell suspension mix was kept on ice for 90 min. The supernatant was collected after centrifugation at 15,000 rpm for 45 min at 4°C and filtered through a 0.2-μm membrane filter . The filtrate was then analyzed using HPLC . The chromatographic separation was performed on a C18 reverse phase column . A gradient of solutions A [1% (v/v) formic acid in water] and B [1% (v/v) formic acid in acetonitrile] was used as the mobile phase at a flow rate of 0.4 mL/min. Chromatographic runs were started with 100% solution A, decreased linearly to 60% solution A during the first 8 min, and then kept constant at isocratic condition for a further 12 min. In the next 1 min, the gradient was set at 100% solution B, kept constant for a further 4 min, and equilibrated again with solution A for the next run. The 2-hydroxyethidium fluorescence was monitored by a fluorescence detector . The area under the curve of 2-hydroxyethidium and ethidium were considered and their concentrations were calculated based on a standard plot.Superoxide production in  earlier , 2009. Bi medium  containiM. phlei medium containing 100 μM DTPA and 1 mM NADH. Freshly prepared DHE was added at a final concentration of 25 μM and the mix was incubated at 37°C, following which HPLC samples were prepared as described earlier in this section.Superoxide production in the crude membrane was assessed by the method described above. Briefly, 15 μg of the crude membrane protein was added to 500 μL of M. smegmatis cells were harvested by centrifuging at 2,000 × g for 15 min and re-suspended in 15 mL buffer containing 1X PBS (pH 8.0), 1 mg/mL EDTA, 0.002% lysozyme, and 1% protease inhibitor cocktail. The pellet was lysed by probe sonication (SONICS Vibra cell) of 10-s pulses for 20 min. The lysate was then subjected to centrifugation at 5,000 rpm for 20 min at 4°C to remove unbroken cells and cell debris. The supernatant was further subjected to ultracentrifugation at 120,000 × g for 90 min at 4°C  and the pellet containing membrane proteins was obtained after washing with cold PBS. This membrane pellet was finally re-suspended in 50 mM Tris-HCl buffer at pH 8.0Crude membrane was prepared by a previously described method  with somM. smegmatis according to an assay described earlier  were supplemented with menadione (150 μM) and pyrogallol (300 μM) along with DPI and incubated for 24 h. Measurements of CFU/mL were determined after 3 days of incubation at 37°C on Dubos agar plate.The effect of menadione and pyrogallol on bacillus growth was determined in the presence of DPI (15 μM). Mid-log phase cultures . A continuous production of 2-hydroxyethidium led to its steady accumulation over a period of 150 min in whole cells and 30 min in membrane preparation  in the reaction mixture . The rate of NADH utilization was found to decrease with increasing DPI concentrations which indicates potential inhibition of NADH oxidase activity .NADH oxidase generates superoxide by transferring electrons from NADH to molecular oxygen. NADH oxidase activity in crude membrane preparation was measured by the decrease in the absorbance of NADH at 340 nm for 25 min. We observed that the rate of NADH utilization linearly increased with the increase in the total crude membrane protein concentration   . Interestingly, M. smegmatis cells were viable after treatment with these ROS modulators for 90 min, indicating that the observed fold changes in 2-hydroxyethidum were not due to cell death (data not shown).To identify the possible source/s of superoxide generation in igure 4) . Tempol es 4A,B)  Polyethyes 4A,B) . SimilarM. smegmatis growth. ETC inhibitors (Rotenone and Antimycin A), tempol and PEG-SOD did not affect the CFU counts of M. smegmatis even 10-fold higher concentration used than the superoxide detection experiment . In contrast, only DPI inhibited the growth of M. smegmatis, possibly owing to the depletion of superoxide within the cell .We further investigated the possible adverse effects of ROS modulators on M. smegmatis growth, we added menadione and pyrogallol, separately and along with DPI, to the M. smegmatis culture and observed their effect on superoxide production as well as bacilli growth. Menadione (150 μM) and pyrogallol (300 μM) increased superoxide production by 1.41 ± 0.062 and 1.14 ± 0.041 fold, respectively, when added separately, and by 0.45 ± 0.13 to 1.12 ± 0.101 fold and 0.99 ± 0.022 fold, respectively, when added along with DPI . DPI reduced the bacilli growth by a difference of 6.8 log10 compared to the growth in the untreated control. This effect was reversed when menadione or pyrogallol was added, showing a difference of only 1.5 or 1.9 log10, respectively, compared to the growth in the untreated control . To optimize the concentration of menadione and pyrogallol, a prior dose response study was carried out in the presence of a fixed concentration of DPI (data not shown). Thus, this study establishes that DPI inhibits growth through the inhibition of superoxide production in M. smegmatis.To determine the involvement of superoxide in 2 in the environment . The superoxide level needs a critical management by mycobacterial antioxidant enzymes to ensure its beneficial functioning in the bacilli. Thus, this justifies the expression of antioxidant enzymes in axenic cultures as reported earlier .Previous studies on different prokaryotic organisms have shown that NADH oxidase and menaquinone, associated with ETC, are the two major sites of superoxide generation in these organisms . DPI inhM. smegmatis  However, contribution of ETC in superoxide production remains unclear due to the lack of significant effect of any of the ETC inhibitors in M. smegmatis Thus, we identified NADH oxidase as the most probable source of superoxide production in M. smegmatis. Interestingly M. smegmatis possesses four isozymes of NADH oxidase (KEGG database). Further studies on these NADH oxidase isozymes will clarify their role in superoxide production.In accordance with earlier studies, our results clearly indicate that DPI significantly inhibits superoxide production in whole cells as well as in the membrane preparation of M. smegmatis bacilli . Reversion of the effect of DPI on the bacilli growth by superoxide generators  confirmed the involvement of superoxide in M. smegmatis growth . Previous in vivo studies have shown similar inhibitory effects of plant-derived antioxidants against M. intracellulare as well as against M. abscessus   . PEG-SODigure 5) . TherefoM. smegmatis and that NADH oxidase is its major contributor. Our results also suggest that superoxide may play an important role in the growth regulation of the M. smegmatis bacilli.The involvement of superoxide in the regulation of mycobacterial growth is a new finding and is in accordance with earlier reports on the involvement of superoxide in the growth regulation of some prokaryotes and eukaryotes . Thus, oThis study was designed and done by all authors. AY and KS participated equally in all this work, whereas MA helped them with membrane preparation and related studies under the guidance of DS.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Concepts for information storage and logical processing based on magnetic domain walls have great potential for implementation in future information and communications technologies. To date, the need to apply power hungry magnetic fields or heat dissipating spin polarized currents to manipulate magnetic domain walls has limited the development of such technologies. The possibility of controlling magnetic domain walls using voltages offers an energy efficient route to overcome these limitations. Here we show that a voltage-induced uniaxial strain induces reversible deterministic switching of the chirality of a magnetic vortex wall. We discuss how this functionality will be applicable to schemes for information storage and logical processing, making a significant step towards the practical implementation of magnetic domain walls in energy efficient computing. It has also been proposed to use the internal structure of the domain wall to encode information. For example, depending on the wire geometry and magnetic parameters, the domain wall structure can be that of a vortex consisting of a circulating pattern of magnetic moments in the plane of the wire, which point out of the plane at the centre of the wall  fields which limit packing density due to interactions between neighbouring elements. In order to utilise vortex domain walls in any commercially viable technology it will be necessary to develop electrical methods to control the chirality of individually addressable domain walls reversibly and with low power.Magnetic domain walls separate regions of a ferromagnetic material in which the magnetisation points in different directions. If the magnetic material is patterned into a quasi 1D object, such as a nanowire, the domain walls separate regions in which the magnetisation points in opposite directions and can be propagated along the length of the nanowire by the application of magnetic fields or electrical currents. This is highly attractive for implementation in magnetic data storageall Fig. . The sen13. Detailed modelling predicts that the implementation of these methods in devices consisting of single domain magnetic elements could lead to information storage devices with orders of magnitude better energy efficiency than present technologies relying on electrical currents14. To date, the use of inverse magnetostriction to control domain walls has resulted in movement between random pinning sites16 or between positions along the circumference of a ring structure18, local pinning of a domain wall at a position in a nanowire19, pinning at mobile ferroelectric domain walls20 and tuning of the domain wall velocity21 or width22. The possibility of switching the domain wall configuration by electric fields has not been considered before now.Electric fields can provide a practical and energy efficient means to control magnetisation because their application does not require large current densities and does not generate Oersted magnetic fields. One route to achieve coupling of the electric field to the magnetisation is via mechanical strain in a hybrid piezoelectric/ferromagnet structure. A voltage applied to the piezoelectric component induces a mechanical deformation which transfers to the ferromagnetic layer and alters the magnetic anisotropy via inverse magnetostriction. The method has been used to modify magnetic anisotropy and to demonstrate rotation of the magnetic easy axis directionIn this article we demonstrate that the chirality of a vortex domain wall can be controlled reversibly by creating a strain-induced inhomogeneous uniaxial magnetic anisotropy energy profile in the vicinity of the domain wall. Using micromagnetic calculations we simulate the magnetisation dynamics in response to a strain pulse and show that the chirality switching can arise from the nucleation of a second vortex core followed by the damped precessional motion of the cores. We discuss how the method might be implemented in device concepts for low energy electric field operated non-volatile information storage and logical processing. The use of electric fields to manipulate the configuration of magnetic domain walls will reduce the energy required to switch the magnetic state in non-volatile information storage and processing technologies by orders of magnitude.1/3Nb2/3)O3]0.68 -[PbTiO3]0.32 (PMN-PT) (011) substrate with top and bottom electrodes, onto which is fabricated a 20 nm thick Ni ring of outer(inner) diameter 7.7μm (5.7 μm). Application of an electric field between the top and bottom electrodes results in mechanical deformation of the PMN-PT substrate and induces a uniaxial strain of order 10−3 in the plane of the Ni ring. Images of the magnetic contrast were obtained using the x-ray photoemission electron microscope (X-PEEM) on beamline I06 at the Diamond Light Source synchrotron.The experimental demonstration was achieved by positioning a vortex domain wall along the circumference of a ring structure, close to the axis of the uniaxial anisotropy. The device Fig.  consistsC23. Switching of the polarisation vector between the <111> directions with components pointing out of the plane is mediated by a range of electric field for which the polarisation points in the plane. This is accompanied by a large uniaxial strain of order 10−3 in the plane in a narrow range of electric field around EC, which is approximately 0.18–0.19MV/m for our device  substrate is known to result in a two stage reversal of the ferroelectric polarisation vector at the ferroelectric coercive field Eice Fig. . This re24 or hundreds12 of nm up to several tens of µm24 and that different domain regions can represent different polarisation vectors as well as different structural phases25 because the [Pb(Mg1/3Nb2/3)O3]0.68 -[PbTiO3]0.32 composition sits close to a morphotropic phase boundary. The application of an electric field can induce reorientation of nanoscale domains and movement of the boundaries of micron scale domains within the same sample24. For our sample we cannot image the ferroelectric domain structure because the presence of the top electrode prevents escape of photoelectrons from the PMN-PT. We can, however consider the extreme cases: (i) the strain in the region of the vortex domain wall switches homogeneously  and (ii) the change in strain sweeps across the device . We find that both mechanisms can induce switching of the vortex wall chirality. We describe the first mechanism in detail here because the results of micromagnetic simulations most closely match the experimental results obtained, and the results of our investigations of the second mechanism are described in the Supplementary Note.A full understanding of the mechanism by which the vortex domain wall chirality switches would require knowledge of how the strain profile varies, both spatially and temporally. The structure of ferroelectric domains in PMN-PT and the processes involved in switching of the ferroelectric polarisation vector are areas of intense research at present. It is known that domains can range in size from tens26 using realistic parameters for nickel (see Methods). Results from the simulations, presented in Fig. We performed micromagnetic simulations using the OOMMF simulation packageU = −3 kJm−3 parallel to the x-axis. Here the minus sign denotes the axis of the anisotropy such that a positive or negative value for KU represents an easy axis parallel to the y or x axis respectively. A small uniaxial anisotropy could arise during fabrication of the rings due to different thermal contraction of the Ni and PMN-PT, or due to the ferroelectric domain state prior to electric field poling12. Upon the application of a uniaxial anisotropy of KU = +10 kJm−3  substrates were purchased from Atom Optics Co., Ltd. Atomic Force Microscopy measurements revealed a surface roughness of order 1 nm. Ti(5 nm)/Au(35 nm) electrodes were deposited onto the top and bottom sides of the PMN-PT by thermal evaporation. The ring pattern was defined using electron beam lithography before deposition of Ni(20 nm)/Al(2 nm) by magnetron sputtering followed by lift-off.3 edge (853 eV) as the contrast mechanism allowed sensitivity to in-plane moments with a spatial resolution of approximately 50 nm. Azimuthal rotation of the sample with respect to the incident polarization vector allowed unambiguous assignment of the magnetization direction in each domain. Additional electrical feedthroughs allowed the in-situ application of voltage to the PMN-PT whilst imaging.Magnetic contrast images were obtained using the x-ray photoemission electron microscope (PEEM) on beamline I06 at the Diamond Light Source synchrotron. Illuminating the sample at oblique (16°) incidence and making use of XMCD at the Ni L26 installed on the University of Nottingham High Performance Computing cluster. Simulations were performed for a half ring geometry with inner diameter = 5.7 µm, outer diameter = 7.7 µm and thickness = 20 nm. A zoomed-section is shown in Fig. −1. The damping constant is stated in the main text. The ends of the half ring section were set to critical damping to suppress the reflection of spin waves. Simulations were carried out using uniaxial anisotropy energy values of KU = −3 kJm−3 and +10 kJm−3.Micromagnetic simulations were carried out using the Object Oriented Micromagnetic Framework (OOMMF) packageSupplementary InformationSupplementary Video 1Supplementary Video 2Supplementary Video 3Supplementary Video 4Supplementary Video 5Supplementary Video 6


Helicobacter pylori infection is associated with the development of gastric and duodenal ulcers as well as gastric cancer. GroES of H. pylori (HpGroES) was previously identified as a gastric cancer-associated virulence factor. Our group showed that HpGroES induces interleukin-8 (IL-8) cytokine release via a Toll-like receptor 4 (TLR4)-dependent mechanism and domain B of the protein is crucial for interactions with TLR4. In the present study, we investigated the importance of the histidine residues in domain B. To this end, a series of point mutants were expressed in Escherichia coli, and the corresponding proteins purified. Interestingly, H96, H104 and H115 were not essential, whereas H100, H102, H108, H113 and H118 were crucial for IL-8 production and TLR4 interactions in KATO-III cells. These residues were involved in nickel binding. Four of five residues, H102, H108, H113 and H118 induced certain conformation changes in extended domain B structure, which is essential for interactions with TLR4 and consequent IL-8 production. We conclude that interactions of nickel ions with histidine residues in domain B help to maintain the conformation of the C-terminal region to conserve the integrity of the HpGroES structure and modulate IL-8 release. Helicobacter pylori (H. pylori) is a Gram-negative, microaerophilic spiral bacterium that infects nearly half of the global population1H. pylori in the human gastroduodenal mucosa leads to chronic gastritis and peptic ulcer, and is an important risk factor for gastric cancer34H. pylori as a class I carcinogen based on the strong association between the bacterial infection and gastric cancer678H. pylori infection is its induction of inflammatory responses, an important risk factor for malignancyH. pylori infection include TNF-α, IL-1β, IL-6 and IL-8 secreted by gastric epithelial and immune cells through activation of transcription factor NF-κB1011121314H. pylori, both in vitroin vivoH. pylori infection. A number of virulence factors of H. pylori-induced host IL-8 production have been identified, including cytotoxin-associated gene A (cagA)H. pylori GroES (HpGroES) stimulates the production of several proinflammatory cytokines in human peripheral blood mononuclear cells (PBMC) and triggers IL-8 production in gastric epithelial cellsHpGroES was also identified as a dominant gastric cancer-related antigen with significantly higher seropositivity in gastric cancer patients, compared with gastritis and duodenal ulcer patientsHpGroES-induced IL-8 production by gastric carcinoma cells involves activation of the MAPK and NF-κB pathways via a TLR4-dependent mechanismSeveral reports have demonstrated increased IL-8 response to H. pylori. It is a member of the co-chaperonin family of the GroEL/GroES complex which assist in the function of protein folding26HpGroES has a highly conserved region (domain A) and a unique C-terminal extension (domain B), which is absent from all other GroES-like proteins, except the closely related H. acinonychis27HpGroES contains 4 Cys residues rarely presented amino-acid in the GroES protein family that form disulfide bonds at C94–C111 and C95–C112 to generate a lasso-like structure2728HpGroES binds TLR4 on the cell membrane only in the presence of domain B. HpGroES lacking the disulfide bonds of domain B is unable to interact with TLR4 and induce IL-8 productionGroES, also known as heat shock protein (HSP) A, is an essential protein in HpGroES contributes to GroES-induced IL-8 secretion through a TLR4-dependent signaling pathwayHpGroES has high affinity to nickel ionsHpGroES domain B in TLR4 binding, metal binding, and IL-8 cytokine production, we conducted site-directed mutagenesis studies and characterized the mutant proteins for bioactivity, TLR4 receptor binding ability, and conformational changes. H100, H102, H108, H113 and H118 of domain B were identified as the key residues affecting IL-8 production and TLR4 binding. These histidine residues were capable of binding nickel ion and four of five residues are required for maintaining local structural integrity. Finally, SAXS shape predictions demonstrated that HpGroES assembles into a ring-shaped homoheptamer with an internal tunnel. Within this ring, these residues maintain the domain B orientation of the HpGroES structure, in turn, ensuring the correct conformation of the C-terminal region for interactions with TLR4.We previously demonstrated that domain B of HpGroES domain B is essential for IL-8 release by gastric epithelium cellsHpGroES. The WT and mutant sequences are presented in HpGroES were purified using a Ni-chelating column, followed by size-exclusion chromatography, yielding an oligomeric form (major peak) and a small shoulder peak corresponding to a unstable higher order form  analysis was performed to examine the direct interactions between WT or histidine mutants and TLR4. TLR4 was coated on the sensor chip and probed with WT or histidine mutant proteins. As shown in t manner , whereast manner . Saturatt manner ; the Kd ectively . In contectively . These rHpGroES.To identify the histidine residues that participate in nickel ion binding and further influence TLR4 interactions and IL-8 production, we assessed the nickel ion binding abilities of histidine mutants via CD spectroscopy, measuring ellipticity at 440 nm and 538 nm that represented the d-d transition when formation of nickel-protein complex31323334HpGroES.Data from vis-CD and SPR analyses showed that the H100A has a slight reduction in the nickel binding ability, but lacks the ability to bind TLR4. Additionally, H102A, H108A, H113A and H118A mutants lost the ability to bind nickel and leading to reduced binding to TLR4. To ascertain whether these mutations induced structural changes, we compared the secondary structures of WT and histidine mutants using far-UV CD. As shown in Dmax values were obtained from Guinier plot and P(r) curves  and Dmax values  were obtained for H102A, H108A, H113A, and H118A mutant proteins, respectively. Our data indicate that WT, H96A, H100A, H104A and H115A share an extended structure while H102A, H108A, H113A, and H118A have compact structures. Envelope models were further constructed from the experimental scattering profiles using DAMMIN and the domain B structure generated with 28 dummy residues in the C-terminus with CORAL model  (data not shown) of the domain A of HpGroES without the extended structure was in accordance with that of GroES of E. coli (34.0–35.0 Å) reported previously5152HpGroES. DAMMIN and CORAL models showed that domain B is contained within the extruded C-terminal portion. Thus, the extended structures of these models represent a close approximation of domain B of HpGroES, and nickel ion binding to domain B may be required to maintain its conformation.HpGroES, HX4DH, is located at positions 96–102 (HTGNHDH) according. Substitution of DH with AA results in decreased intracellular nickel content and reduced nickel tolerance28Dmax values. Among histidines from the first and second motif, 113–118 (HDHKKH), mutation of H108 and H113 displayed significant structural changes with decreased nickel binding ability. SAXS data revealed near-complete loss of the extended structures of domain B, suggesting that the C-terminal conformation is maintained through domain B binding to nickel ions. Furthermore, mutation of H118 in second motif led to significant loss of nickel binding ability. Far-UV CD spectra analysis showed that a ~10% increase in flexible coil structure of H118A than WT. H118A also exhibited the smallest size with disappearance of the extruded structure, signifying dramatic conformational changes. H118A completely lost its natural shape and was rearranged into an overall oblate ring shape. Moreover, IL-8 activity was almost abolished in the H118A implying that this residue is directly involved in binding nickel ions and potentially contributes to C-terminal conformation stability.As reported previously, the nickel binding motif of domain B of In the modeled structure, the first nickel ion is coordinated to three histidine residues  and the second nickel ion is ligated to H113 and H118 in domain B. Furthermore, various double mutations reduced the nickel ion binding strength significantly as compared to the single mutations, indicating that these five histidine residues can coordinate nickel ion. In general, the nickel ion preferentially adopts planar coordination geometry313233HpGroES participate in binding of nickel ion and maintaining conformational integrity. Mutation of these residues results in disruption of the conformation of extended domain B and further reduces secretion of IL-8 through loss of binding ability with TLR4. Our results collectively highlight critical roles for these histidine residues in terms of contribution to the overall structure of HpGroES protein. Furthermore, the unique C-terminal domain B conformation of HpGroES supports its function as a determinant of HpGroES pathogenesis in the H. pylori-induced innate immune response.In conclusion, the histidine residues H102, H108, H113 and H118 in domain B of 2+-chelating Sepharose column and HiLoad 16/600 Superdex 200 pg column were from GE Healthcare . Triton X-114 and protease inhibitor cocktails were purchased from Sigma-Aldrich . The ultrafiltration membrane (30 kDa cut off) was from Millipore . Cell culture medium RPMI was purchased from Hyclone , while FBS, penicillin, and streptomycin were from Life Technologies . Quantikine ELISA assay kits for human IL-8 and recombinant human TLR4 protein were from R&D Systems . Rabbit antibodies to HpGroES were produced in our laboratoryThe pQE30 plasmid was obtained from Qiagen , and the Phusion site-directed mutagenesis system from Thermo Scientific . The NiHpGroES gene was cloned using the pQE30 expression vector as described previouslyE. coli strain M15. To confirm the presence of the desired mutations, DNA sequences were determined. M15 cells containing the expression vector pQE30 carrying WT and histidine mutant gene fragments were grown to A600 values of 0.5–0.7, induced with 1 mM isopropyl β-D-thiogalactoside (IPTG), and harvested after 4 h at 37 °C. Recombinant proteins were purified on a Ni2+-chelating sepharose column. To remove endotoxin, soluble recombinant proteins were purified in buffer containing 1% Triton X-114, loaded onto the column and washed with binding buffer containing 0.1% Triton X-114 for elution of target proteins. The crude protein eluate was dialysis against 150 mM NaCl, 25 mM potassium phosphate, pH 7.4, 1 mM DTT, and 0.3% glycerol with 4 molar equivalence of NiSO4 and subjected to chromatography on a HiLoad 16/600 Superdex 200 pg column pre-equilibrated with the same buffer without NiSO4. The column was run at a flow rate of 2 ml/min. Fractions (1.5 ml) displaying the correct size of HpGroES were collected and concentrated using Ultrafiltration membrane (30 kDa cut off). For cell culture, protein solution was dialyzed against PBS. Protein concentrations were measured using the BCA protein assay kit . Purified recombinant proteins were separated via SDS-PAGE and visualized with Coomassie blue.The 2. Cell cultures were incubated for 16 h with 0.05 μM WT and histidine mutant and then the cell culture supernatant collected following centrifugation at 1500 rpm for 10 min. Levels of IL-8 in the culture supernatants were measured using the Quantikine ELISA assay kit . All experiments were performed in triplicate.The human gastric carcinoma cell line, KATO-III, was obtained from the Japan Cancer Research Bank . Cells were cultured in RPMI 1640 with 10% FBS, 100 μg/ml streptomycin and penicillin at 37 °C in 5% COHpGroES (1:200) or mouse mAb against TLR4 (1:200), followed by FITC- or TRITC-labeled secondary antibodies (1:500) and nuclei stained with DAPI (1:1000). Digital images were captured with a TCS SP5 confocal microscope .KATO-III cells were grown on coverslips overnight, followed by treatment with 0.05 μM WT and histidine mutants for 1 h. After washing with PBS, cells were fixed with 4% formaldehyde in PBS at room temperature for 15 min and blocked with 5% BSA in PBS for 1 h at room temperature. For immunostaining, cells were incubated with rabbit antibodies against 2SO4) and rinsed before use. WT and histidine mutants were diluted to suitable concentrations (20 μM) in 150 mM NaCl, 25 mM potassium phosphate buffer, pH 7.4, 1 mM DTT, 0.3% glycerol for vis-CD or 3 μM in 25 mM sodium phosphate buffer, pH 7.4, for far-UV CD. For each sample, three scans were performed to obtain an average spectrum, which was subtracted from the buffer spectrum to provide a baseline correction. The secondary structure percentages of WT and histidine mutants were determined using the CDSSTR software program (shown in CD spectra of proteins were measured at 4 °C in the far UV (190–260 nm) or visible range (300–600 nm) on a J-810 spectropolarimeter . The bandwidth and step resolution were set to 0.5 or 1 nm. The optical path length of the cuvette was 1 mm. A quartz cuvette was cleaned by soaking in potassium dichromate solution . The chip surface was regenerated by injecting 1 M NaCl for 30 s and 10 mM Glycine-HCl, pH 3.5, for 10 s. For all samples, blank injection with buffer alone was subtracted from the resulting reaction surface data. Data were analyzed using Biacore T200 evaluation software and fitted using GraphPad Prism software.All SPR experiments were carried out on a Biacore T200  with active temperature control at 25 °C following the manufacturer’s protocols. The running buffer used as PBS with 0.05% P20. For protein immobilization, TLR4 (20 μg/ml) in running buffer equivalent to 6000 RU was injected onto a CM5 sensor chip at a flow rate of 5 μl/min. Another flow cell without immobilized TLR4 coating was used to evaluate nonspecific binding. WT and histidine mutants were diluted in running buffer  and flowed across immobilized TLR4 for 240 s at a flow rate of 30 μl/min (association). The sample was replaced with running buffer, followed by disassociation of bound −1) was injected into the HPLC column. Next, the sample was directed into a quartz capillary for SAXS measurements thermostatted at 298 K. Data were collected at a rate of 1 frame per 30 s using a Pilatus 1M-F area detector. The energy of the X-ray beam was 15 keV (wavelength λ = 0.8266 Å), and the setup adjusted to achieve scattering q values of 0.007 Å−1 to 0.3 Å−1, q defined by 4πλ−1sinθ with scattering angle 2θ. Data were corrected for electronic noise, and sample transmission, followed by scaling to absolute intensity I(q) in units of cm−1 via scattering from water at protein sample conditions2 over all values of r and maximum particle dimensions (Dmax) by computing with autoGNOM. Rg estimates were also obtained using Guinier analysis. Ab initio modeling was performed with the program DAMMIN to obtain 10 to 15 independent dummy bead models that were subsequently averaged in DAMAVER software. Bead models of molecular envelopes for each structure were converted to surfaces with Chimera. Each DAMMIN model showed good fit to the experimental SAXS curve (χ2 = 1.4~2.1) and was calculated with normalized spatial discrepancy (NSD) values in the range 0.5–0.7. To construct the conformation of domain B missing from other crystal or solution structures, CORAL models of WT and histidine mutants were also built based on the domain A template of HpGroES from SWISSMODEL with Mycobacterium tuberculosis GroES (PDB: 1P3H) assembled with 28 dummy C-terminal residues. Rigid body modeling into SAXS-derived molecular envelopes was manually performed using the program Chimera.SAXS measurements were collected at beamline 23A1 of the National Synchrotron Radiation Research Center (NSRRC), Taiwan, with an online size-exclusion high pressure liquid chromatographic (SE-HPLC) system. Typically, 50 μL protein sample .Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Progesterone receptor membrane component 1 (PGRMC1) is a multifunctional protein implicated in multiple pathologies, including cancer and Alzheimer's disease. The recently published structure of PGRMC1 revealed heme-mediated dimerization that directed the PGRMC1-dependent cytochrome P450-mediated detoxification of doxorubicin. We describe here how the PGRMC1 structure also enables important new insights into the possible regulation of PGRMC1 function by phosphorylation. Predicted regulatory interaction sites for SH2- and SH3-domain proteins are in non-structured regions that could be available to cytoplasmic enzymes. Further to the published interpretation, we suggest that phosphorylation of PGRMC1 at position Y113 may promote the attested membrane trafficking function of PGRMC1. To stimulate further experimentation, we also discuss that heme-mediated dimerization of PGRMC1 and membrane trafficking may be mutually exclusive functions. These roles could potentially be reciprocally regulated by phosphorylation/dephosphorylation at Y113. It follows that the phosphorylation status of PGRMC1 should be further explored in order to better understand many of its proposed biological functions. N-terminal transmembrane domain, and a C-terminal cytochrome b5-related heme-binding domain . Moreover, PGRMC1 has been attributed with controlling diverse functions including neuronal guidance, membrane trafficking, modulation of cytochrome P450 activity, progesterone-responsiveness, steroidogenesis and regulation of the mevalonate pathway, etc. [Progesterone receptor membrane component 1 (PGRMC1) is 195 residue membrane-bound protein which contains a short luminal peptide, a single n Figure . It is tay, etc. . To be iNature Communications [The recent structure of PGRMC1 published in ications  confirmeications , 6. Furtications . Most imications .The new structure  also illet al. observed Y180-phosphorylated PGRMC1 to be more than ten-fold more abundant in post-synaptic density fractions of primary mouse neurons than in synaptic membranes [In a proteomics study, PGRMC1 was observed to be differentially phosphorylated between estrogen receptor-positive or estrogen receptor-negative breast cancers . Howeverembranes .Considering the combination of differential phosphorylation and the presence of signaling signatures in PGRMC1, one of us predicted that PGRMC1 occupies a signaling nexus position in a PGRMC1 signaling system  with proPhosphorylation of Y180 is predicted to be sterically inhibited by phosphorylation of S181 by CK2, and the observed T178 phosphorylation Figure  should avia a tyrosinate ion at Y113 would probably be impossible if Y113 were phosphorylated [in vivo (Figure Notably, CK2 is a constitutive kinase responsible for 20% of the mammalian phosphoproteome . Hence, orylated . Signifio Figure .b5 domain (Figure In the SH2-target sequence centered at Y139, the structure of PGRMC1 now reveals that while the Y139 hydroxyl is exposed , the aroin vivo. Tyrosine phosphorylation of Y180 and recruitment of an SH2-domain protein may induce allosteric structural changes to the surrounding PGRMC1 conformation.Considering this latter proposal, we suggest that binding of an SH2-domain protein to Y180, or an SH3-domain protein to the SH3-target sequence centered at P63, may produce conformational changes that expose Y139 and/or T178. Relevant to this, the structure of the polypeptide backbone surrounding Y180 was unstable under both crystallization and NMR conditions . This maNotably, from the Y139-OH group to C-alpha of V179, the atomic distance is only 16.66Å Figure , in a reThe PGRMC1 structure from residues 68-179 was obtained by NMR from a protein containing PGRMC1 amino acids 44-195 [An SH3-domain protein bound to the P63 SH3-target sequence would be adjacent to SH2-domain proteins bound to both Y139 and Y180 (Figure Phosphorylation of Y113 could cause steric interference incompatible with heme-binding , and yetSince PGRMC1 modulates vesicle trafficking , 15–18, et al. [Kabe et al.  concludeet al. . Intriguet al. , such asin vivo (Figure While these predictions and suggestions above remain to be experimentally substantiated, all of the described phosphorylations occur o Figure , and theIn summary, considering our analysis, we suggest that future research should focus on characterizing the state of PGRMC1 phosphorylation and its involvement in important disease processes such as cancer , 19 and


The effectiveness of infectious disease control depends on the ability of health managers to act in a coordinated way. However, with regards to non-notifiable animal diseases, farmers individually decide whether or not to implement control measures, leading to positive and negative externalities for connected farms and possibly impairing disease control at a regional scale. Our objective was to facilitate the identification of optimal incentive schemes at a collective level, adaptive to the epidemiological situation, and minimizing the economic costs due to a disease and its control. We proposed a modelling framework based on Markov Decision Processes (MDP) to identify effective strategies to control PorcineReproductive andRespiratorySyndrome (PRRS), a worldwide endemicinfectiousdisease thatsignificantly impactspig farmproductivity. Using a stochastic discrete-time compartmental model representing PRRS virus spread and control within a group of pig herds, we defined the associated MDP. Using a decision-tree framework, we translated the optimal policy into a limited number of rules providing actions to be performed per 6-month time-step according to the observed system state. We evaluated the effect of varying costs and transition probabilities on optimal policy and epidemiological results. We finally identifiedan adaptive policy that gave the best net financial benefit. The proposed framework is a tool for decision support as it allows decision-makers to identify the optimal policy and to assess its robustness to variations in the values of parameters representing an impact of incentives on farmers' decisions. These shortfalls and costs induced by animal diseases weigh heavily on the economy of farms and have a wider effect on the competitiveness of animal production chains. Beyond these direct impacts on the livestock sector, animal diseases can have a broader impact on regional and national agricultural economies , as well as on firms engaged in the processing of animal products for food.The control of animal diseases is a major concern for the livestock sector. Animal diseases are an important source of vulnerability due to the diversity of their economic impacts . They cre.g., regional) scale. Indeed, contagious pathogens spread among farms through numerous transmission pathways such as: animal purchases  creates a positive externality, in that his action benefits other farmers by lowering the risk of pathogen spread  where E[.] is the expectation operator and ρthe discount factor  is a major issue for swine industry in most producing countries. For example, annual costs due to PRRS virus have been estimated to be approximately 664 million dollars in the United States in 2011 . Within F and Fd) and 3 statuses for infected herds . When farmers implement biosecurity measures to prevent virus introduction, virus-free herds F become Fd (virus-free with biosecurity). Both F and Fd herds can be infected and then become I (with virus spread without control). When control measures to limit virus spread are implemented, infected herds become I0, with a lowered virus spread. When spread is controlled, I0 herds become IC (controlled infected herds). We assumed that farmers will not stop control measures in I0 herds until reaching status IC. Then, farmers can depopulate, IC herds then becoming Fd. As IC herds already experienced infection, we assumed that they will maintain biosecurity measures. On the other hand, IC herds can become I again when control measures are stopped without depopulation.F and Fd herds occurred from herds in I, I0, and IC statuses. Because of the control measures implemented by farmers in I0 and IC herds, virus transmission is reduced compared to transmission by I herds. The virus can also be introduced due to contacts with herds located outside of the modelled group of herds . Pig production systems are almost closed. However, the external risk is not nil, and, even with a very low value, could impair disease control and thus should be accounted for. Transitions from statuses F and Fd to status I were modelled using a frequency-dependent function [Fd to I is equal to the one from F to I, weighted by factor γ, representing the protection induced by biosecurity . Parameter values provided in s = |F + Fd + I + I0 + Ic = N}. The number of states is given by the combination  The set of states is given by S = {None, Incent1, Incent2, and Incent3. When using incent2, the same measures were advised but with a higher effect, corresponding either to an increasing efficacy of measures or a higher level of farmers’ compliance. For realism, we nevertheless considered that farmers’ compliance was not complete and that for each status, a given proportion of farmers did not implement control measures (we assumed that farmers with infected herds were less reluctant to implement the prescribed control measures than those within virus-free herds). When using incent3, measure efficacy and farmers’ compliance was much higher. In addition, depopulation-repopulation of infected herds was considered with no possible return to state I from state IC. With such an action, eradication is expected to be achievable.We modelled the consequences of the social planner’s action on farmers’ decisions by modifying the value of model parameters related to transitions between herd statuses . Four acd Incent3. Transitd Incent3 in linesa from state st =  to state st+1 =  was defined based on the number of herds moving from one status to another. The probability was not null if, for all statuses, the number of herds at time t + 1 is consistent with the one at timet given the transitions between herd statuses  = 1 − exp(−βF) and P(Fd → I) = 1 − exp(−βFd).The transition probability when using actionx herds chosen among Ict to go to Fdt+1 with probability z herds chosen among the remaining ones (Ict − x) to go to It+1 conditionally they are not going to Fd, with probability Fd while going to I is one. Once aggregated you end with the sub-formula in square brackets. Similarly, the second term in square brackets corresponds to the probability for w herds to go from Ft to Fdt+1 times the probability for l herds among remaining ones to go from Ft to It+1. The last three terms in square brackets are simpler and corresponds respectively to m herds going from Fdt to It+1, y herds going from I0t to Ict+1, and u herds going from It to I0t+1. Then, we sum over all of the possible values for x, w, and y, accounting for constraints on these sums, each being limited by the number of herds that can change of status .In this formula, the first term in square brackets corresponds to the product of two binomials. The first binomial denotes for the a ∈ A except for action None induced a fixed cost Cdiff(a). Moreover, at each time-step, the other control costs (C) and losses (L) due to the disease incurred by the social planner were expressed as functions of the number of herds in each herd status or transiting between statuses. We assumed that the magnitude oflosses in controlled infected herds (LIc) were lower than those in other infected herds (LI).Herds in statuses I0and IC had costs due to external biosecurity (Cbe) and internal biosecurity with vaccination (Cbi). Herds in status Fd had costs due to external biosecurity (Cbe). Finally, a cost related to depopulation CdepconcernedICherds becoming Fd(transition flow between the two statuses). For the social planner in state st =  at time t moving to state st+1 =  at time t + 1 when using action a, the reward at timet was:/)For the social planner, the choice of any action As herds were not individually modelled, we used the expected number computed using the transition probabilities given the initial and final states. The values of losses and costs are given in ρof 0.975 per time-step (6 months).As we considered an endemic disease, we looked for optimality in the long run. For the MDP resolution, we fixed an infinite horizon with a discount factor F and 15 in Fd), 40% of the herds in status IC (20 herds), and the remaining 20% in statuses I(5 herds) and I0 (5 herds). A program was developed in Java language  and the number of controlled infected herds (IC). These outputs, corresponding to non-transient states, were regarded as relevant for an endemic disease.Two outputs were of interest to represent the simulation outcomes: the number of virus-free herds representing the clearance level .To assess the advantage of using the optimal policy π* consists of a table of 316,251 lines . Such atable cannot be easily used under field conditions. To provide the social planner with a simpler but approximated policy made of alimited number of rules, π* was approximated using a decision-tree into π*,approx, providing the actions to be performed at each time-step according to the observed state of the system. Only 7.4% of the possible states can be reached from our initial state given our parameter values. The approximation of π* was done only using these states, called hereafter available states. A supervised classification approach was performed using the C4.5 algorithm [R package (RWeka Package). This method uses as dataset available states and their associated actions as known in the optimal policy and generates errors corresponding to misclassifications . We evaluated the quality of π*,approx by calculating the percentage of misclassifications.The optimal policy lgorithm , 40 avaiπ* and epidemiological results of varying costs and losses . First, we evaluated the frequency of visits of each state for all of the scenariosincluding the reference one , noted wg(s)for state s. The divergence index for scenario iwas the sum of the visit frequencies over all states for which the action implemented for state s in scenario i was not similar to the action implemented for the same state sin the reference scenario: usei(a) − useref(a) with usek(a) the cumulative proportion over time of the use of action a for scenario k = {i,ref}. For epidemiological results, we compared the median proportion of infected controlled herds (IC) and of non-infected herds (F + Fd) after 50 years in scenario i and in the reference. Finally, we compared the median discounted cumulative rewardsobtained after 50 years in scenario i and in the reference.As a result ofthe high computing time needed for each scenario (nearly 20 hours despite the use of multi-thread programming), we did not investigate interactions among factors. We compared F + Fd) and IC numbers is provided in IC and of (F + Fd) after 50 years were impacted , the protection due to biosecurity when in Fd (γ), the probability of transition from IC to I corresponding to virus reintroduction due to lower biosecurity and vaccination (φ), and the transmission rate due to I herds (βI). The parameter γ impacted more (F + Fd) than IC as it was directly associated to the risk of infection (leaving status Fd) and indirectly to the control (for IC). The probability of transition from I to I0 corresponding to the biosecurity and vaccination (ν) impacted mainly the mean number of IC (A description of the evolution of (impacted  by the per of IC  (which wF to Fd (α), had a direct influence on both virus clearance and control within the system. Hence, if the social planner chose an action different from None, the prevalence of infected herds and of controlled herds should vary. The parameters that most impacted model outputs were all influenced by the social planner except the transmission rate due to I herds. As the median value of the number of (F + Fd) herds was near equilibrium , Incent3was used , and a decrease in the probability of transition from IC to Fd when action Incent3was considered (noted κ(3)). A decreased value of LIc induced an increase in the cumulative use of action Incent1, a decrease in the cumulative use of action Incent3, and a decrease in the clearance level corresponding to an increase of the infection prevalence ), the use of each action and the total costs were impacted , the transition probability between F and Fd  for action Incent1only, the transition probability between IC and I (φ) for action Incent3only, and the fixed cost (Cdiff) for action Incent1.Variations of other parameter valuesbarely impacted In this paper, we proposed a framework which can be used by a decision-maker acting as a social planner to identify an adaptive strategy consisting of incentives in order to optimise the net financial benefit at the collective scale for a group of farmers. We applied this framework for the control of PRRS, an endemic non-notifiable disease. The computed policy providing better net financial benefit was adaptive. It illustrated the potential of adaptive approach to propose an optimal dynamic strategy. Even if some incentives were expensive, the optimisation over a long horizon took into account the incentive benefits to balance these high costs. This framework is a tool to help a social planner to define collective schemes, provided that the social planner is accurately informed about the health status of the herds.As an example, for PRRS, the Morrison’s Swine Health Monitoring Project is conducted on a convenience sample of 910 herds for which diagnostic status is reported weekly . To be uThe definition of the objective function is one of the most important components. According to the objective function, the MDP policies can be different as shown in . In our It is not straightforward to anticipate when a given disease situation will show a large impact of an adaptive policy compared to a fixed one.Of course, it is expected to vary with the pathosystem, as well as with the considered control options and incentives. As regards our case study on PRRS virus, the difference between the adaptive policy and a fixed one is small as regards saved euros (4%) but large as regards acceptability of the collective scheme. Indeed, eradication can almost be achieved without the need of implementing forever a very constraining action (depopulation). This action is already known by health managers as the main one that can impact PRRS herd prevalence.It is also known by that eradication of such an endemic disease cannot be achieved in a few years only. However, when to stop a control action such as depopulation was unknown. We highlighted that 10 years after the start of depopulation implementation in detected infected herds, this action could be progressively stopped and replaced by lighter ones for the next 10 years without impairing the large reduction in prevalence almost achieving eradication which would have been obtained with a fixed action on the same duration.Another main component of the framework to be decided with the decision-maker is the horizon of optimisation. In our case study, we used an infinite time horizon. It was retained as PRRS virus is highly prevalent  and ofteet al. [if … then … else …), using for example the approach of Gil et al. [To render the policy usable in field conditions, we proposed a way to approximate the optimal computed policy which was far too complex for practical purposes. For a decision-maker, having simple decision rules is important for practical use in field conditions as pointed out by Pichancourtet al. . It was l et al. . Howeverl et al.  and prodl et al. , an apprl et al.  considerLIc corresponding to the losses for Ic herds). In addition, some identified parameters correspond to the impact of the farmer’s response to a decision-maker action (incentive), such as the transition from IC to Fdwhich corresponds to depopulation when the social planner retains action Incent3.For such parameters, a knowledge on how farmers would respond to incentives is needed. To estimate farmers' responses, either data on previous use of incentives can be explored [The sensitivity analysis is a crucial step in modelling work to assess the impact of parameter uncertainty on model outputs . Performexplored  or behavexplored . Moreoveexplored  evaluatea prioritheir policy under a variety of epidemiological situations and incentive levels.Our framework is a novel contribution in terms of a decision-making support that can be applied to animal disease control situations. In the special case of non-notifiable diseases, control decisions are made by farmers based on the risk of their herd being infected and on disease consequences, sometimes in interaction with a social planner. In animal health literature, models focused on individual decision and scenarios comparing collective incentive schemes , 53. TheS1 FileThis archive contains the data and the Java code required to run the MDP model.(ZIP)Click here for additional data file.S2 FileThis archive contains the data used in the results section of the paper.(ZIP)Click here for additional data file.


Detailed TEM characterization reveals that LFO-YMO multilayers grown on both substrates have clear layer-by-layer morphology and distinct chemical-composition layered structure. The most notable feature is that LFO-YMO multilayers grown on (001)-SrTiO3 substrate have three types of domains, while those on (111)-SrTiO3 have only one. The multi-/twin- domain structure can be qualitatively explained by the lattice mismatch in this system. The details of the domain structure of LFO-YMO multilayers are crucial to understanding their magnetic properties.The microstructure of multiferroic LaFeO It is noticed that a and b of LFO are quite close, but those of YMO are not; they are quite different. For the sake of simplicity, the orthorhombic perovskite can be viewed as pseudo-cubic structure. LFO can be treated as Pa = 3.93 Å, while in YMO, Pa = Pb = 3.91 Å, and Pc = 3.68 Å. In other words, LFO is closer to a cubic structure, but YMO is closer to a tetragonal one. Theoretically, the multi-domain structure is related to the relaxation of the mechanical strain among YMO, LFO, and STO [ε is defined as a1,2 is the lattice constant of component layer 1 and 2 in the pseudo-cubic setting. Accordingly, the in-plane theoretical ε between STO and YMO (LFO), as well as YMO and LFO can be calculated and summarized in ε between YMO and STO, LFO and YMO, can be as large as 6%. Theoretically, the large mismatch can be relaxed by the formation of crystal defects, such as domain structure, dislocations, and grain-boundaries. If we only consider the lattice mismatch between LFO and YMO, generation of α-domain should be dominated to minimize the strain energy of this system [torsional torque should be considered, too [We would like to qualitatively explain the formation of multi-domain structures in YMO-LFO multilayers grown on (001)-STO substrate from the viewpoint of mechanical strain. The lattice constants of orthorhombic LFO are:  7.862 Å , and tho 7.357 Å . STO has and STO ,23. SAEDa1 + a2)  where a1s system ,23. But s system ,21. In tred, too ,23. Thusε in this system is outlined in When the substrate is changed to (111)-STO, the corresponding in-plane lattice mismatch Certainly, the above-discussion is qualitative. A quantitative method, like the first-principles calculation of formation energy in the different domain structures , should 3-LaMnO3 multilayer grown on (001)-STO substrate [Finally, it is valuable to mention that the above-mentioned domain structure characterization is very central to explaining the measured magnetic properties. Based on the above-mentioned microstructure analysis, the magnetic property of YMO-LFO multilayer grown on (111)-STO can be attributed to the ferrimagnetism generated at interface between YMO and LFO, since there is only a single domain. However, the ferromagnetic hysteresis loop measured in YMO-LFO multilayer grown on (001)-STO should be attributed to non-canceled multi-/twin-domain structure, rather than the designed interfaces. It has been reported that YMO films with multi-/twin-domain structures show the clear ferromagnetic hysteresis loop though YMO is an antiferromagnetic compound . Consideubstrate  may alsoThree LFO-YMO multilayers were grown on either (001)- or (111)-STO substrates  by pulsed laser deposition . The details of growth process and corresponding parameters can be found in . The TEMThe microstructure of LFO-YMO multilayers grown on (001)- and (111)-STO substrates is characterized by TEM. Detailed microstructure characterization manifests that there is mainly a multi-/twin-domain structure in LFO-YMO multilayers grown on (001)-STO, and only a single-domain structure on (111)-STO substrate. The formation of multi-/twin- and single-domain structures in YMO-LFO multilayers can be qualitatively explained by the lattice mismatch in this system. The characterization of domain structure in multilayers is of great importance to understanding ferrimagnetism in YMO-LFO multilayers.


NLR) proteins can contain additional domains besides canonical NB‐ARC ) and leucine‐rich repeat (LRR) domains. Recent research suggests that these additional domains act as integrated decoys recognizing effectors from pathogens. Proteins homologous to integrated decoys are suspected to be effector targets and involved in disease or resistance.Plant immune receptors of the class of nucleotide‐binding and leucine‐rich repeat domain (NLR proteins using the Interpro search. The involvement of the Zinc Finger–BED type (ZBED) protein containing a putative decoy domain, called BED, in rice (Oryza sativa) resistance was investigated by evaluating susceptibility to the blast fungus Magnaporthe oryzae in rice over‐expression and knock‐out mutants.Here, we scrutinized 31 entire plant genomes to identify putative integrated decoy domains in NLR proteins . We also demonstrated that modifying the expression of the ZBED gene modified disease susceptibility.This analysis showed that all plants tested had integrated various atypical protein domains into their NLR immune receptors is widespread and frequent in plants. The integrated decoy model is therefore a powerful concept to identify new proteins involved in disease resistance. Further in‐depth examination of additional domains in NLR proteins promises to unravel many new proteins of the plant immune system.This study suggests that integration of decoy domains in  210: 371–373.Malik & Van der Hoorn, See also the Commentary on this article by  R) genes broadly used by breeders code for NLR proteins. NLRs constitute huge and highly diverse gene families in plant genomes that can be further subdivided into coil‐coil NBS‐LRRs (CNLs), which contain an N‐terminal coil‐coil (CC) domain, and TIR‐NBS‐LRRs (TNLs), which have a Toll/interleukin‐1 (TIR) domain and are absent from monocot genomes , where 32 NLR proteins were found to carry the same additional domain  NLRs, including one that was found to code for the Xa1 functional resistance protein  proteins. Indeed, the majority of cloned dominant resistance  as well as > 2500 receptor‐like kinases (RLKs) (GP039790). It is noteworthy that the Interpro database contains several, different, accessions for a given molecular function ).To analyze a representative sample of NLR proteins from all available plant genomes, we used the NLR repertories defined by the Greenphyl database  was the presence of both the NB‐ARC domain IPR002182 and an LRR domain . According to the same logic, a set of 1393 canonical RLKs (Table S2) was defined by the presence of an LRR domain (same Interpro domains as above) and the protein kinase domain IPR000719. Other domains were frequently found in the NB‐ARC parts of the NLR proteins (AAA+ ATPase domain IPR003593) or the kinase domain of LRR‐RLK proteins ; these frequently found domains were therefore considered as usual components of these proteins and not as putative decoys .http://www.ebi.ac.uk/interpro/search/sequence-search) or the NCBI domain (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) search tools. The gene ontology (GO) terms (http://www.ebi.ac.uk/interpro/download.html) were assigned  to each Interpro domain to establish the global molecular function of decoy domains (Table S3).For re‐annotation of cloned R proteins, we used the Interpro database (Oryza sativa cv Nipponbare (L.) was PCR amplified  and cloned into the pBIOS2300OX transformation vector  under the control of the constitutive maize (Zea mays) ubiquitin promoter . Nipponbare and Kitaake cultivars were transformed as described previously  were conserved for further analysis. Siblings that were negative by PCR (thus not containing the transgene) were used as controls (termed null‐segregant (NS) controls). Individual T2 plants (homozygous over‐expressor and NS) from three independent monolocus lines were selfed and ZBED over‐expression was confirmed in the T3 progeny. In the case of transgenic plants in the Kitaake background , transformation was also carried out using the pBIOS2300OX empty vector in parallel with the ZBED over‐expression vector. The expression of the ZBED gene was measured in the first generation  and T1 seeds were amplified. For both vectors, T1 plants were selected on genetycin and then inoculated .The ZBED cDNA from et al., ko‐zbed) as well as siblings showing no insertion (wt‐zbed).For the knock‐out (KO) mutant, we retrieved the ASFH06 insertion line (Nipponbare background) from the OryzaTagline collection  were counted as a measure of susceptibility. Differences in total lesion numbers between Fig. Rice plant growth and inoculation were performed as described previously (Vergne Actin gene) were done as described in Grand et al.  late blight resistance protein R3a carries a FAM75 domain of unknown function in its C terminus; the R1 protein from a wild potato (Solanum demissum) species contains a domain of unknown function; and the putative soybean (Glycine max) R protein KR1  . From this, we concluded that the NLR repertoires from Greenphyl provide extensive coverage of the NLR diversity in plant genomes.The analysis of cloned R proteins and previous reports suggest that NLRs with integrated decoy domains may be common in many plant genomes .Conversely, we observed that the Greenphyl NLR data set contained rice and c. 15 500 NLR proteins and searched for domains that did not correspond to canonical CNL or TNL domains. This identified 456 NLR proteins (3.6%) harboring at least one unusual domain . The same analysis was performed with the more stringently defined data set of 2699 canonical NLRs. This identified 94 NLRs (3.5%) with unusual domains  than TNLs (4.7%). In addition, the frequency of NLRs with unusual domains varied between species  displayed additional domains that did not correspond to canonical domains for RLK proteins , signaling and oxidative metabolism (Table S3). However, most of the domains belonged to other very diverse classes that could not be regrouped, indicating that integrated domains encompass very diverse molecular functions.Most domains occurred at low frequencies and were often detected only once. Only three domains were found in many NLRs and in different species Fig. c: the prGP015132 and GP015056 and in TNLs of group GP000012  domains were found in CNLs of the groups Sorghum bicolor) CNL contains a NAC and two WRKY domains  that show 44% to 58% identity with the BED domains of Xa1 . ZBED had attracted our attention because its expression is negatively correlated to partial resistance to the blast fungus M. oryzae across a panel of rice varieties . This type of expression pattern has been reported to be a hallmark of regulators of disease resistance . To investigate whether ZBED has a role in immunity, rice plants over‐expressing the ZBED gene were produced. These plants did not show any obvious visible growth phenotype (data not shown); however, rice plants of the variety Nipponbare over‐expressing ZBED  as well as homozygous wild‐type siblings (wt‐bzed)  and inoculated them with M. oryzae. Loss of ZBED expression led to a significant increase in susceptibility  compared with the initial study by Césari et al. . Conversc. 15 500 and the more stringently defined 2699 NLRs, our analysis revealed a mean frequency of 3.5% for unusual domain integration  should be directed to the Fig. S1 ZBED over‐expression and knock‐out lines in the Nipponbare background.Fig. S2 ZBED transgenic lines (Kitaake background) are more resistant to the rice blast fungus.Fig. S3 Frequency of unusual domains in all Greenphyl > 15 500 NLR proteins.Fig. S4 Structure and expression of the ZBED protein and gene.Click here for additional data file.Table S1 Unusual domains in canonical plant NLR proteinsClick here for additional data file.Table S2 Unusual domains in canonical plant RLK proteinsClick here for additional data file.Table S3 The 90 putative integrated decoys identifiedClick here for additional data file.Table S4 Curated cloned plant R genesClick here for additional data file.Table S5 Rice NLRs with integrated decoys and their neighborhoodClick here for additional data file.