LONP1 gene are known to cause a broad spectrum of diseases, and LonP1 dysregulation is also implicated in cancer and age-related disorders. Despite the importance of LonP1 in health and disease, specific inhibitors of this protease are unknown. Here, we demonstrate that 2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oic acid (CDDO) and its -methyl and -imidazole derivatives reversibly inhibit LonP1 by a noncompetitive mechanism, blocking ATP-hydrolysis and thus proteolysis. By contrast, we found that CDDO-anhydride inhibits the LonP1 ATPase competitively. Docking of CDDO derivatives in the cryo-EM structure of LonP1 shows these compounds bind a hydrophobic pocket adjacent to the ATP-binding site. The binding site of CDDO derivatives was validated by amino acid substitutions that increased LonP1 inhibition and also by a pathogenic mutation that causes cerebral, ocular, dental, auricular and skeletal (CODAS) syndrome, which ablated inhibition. CDDO failed to inhibit the ATPase activity of the purified 26S proteasome, which like LonP1 belongs to the AAA+ superfamily of ATPases Associated with diverse cellular Activities, suggesting that CDDO shows selectivity within this family of ATPases. Furthermore, we show that noncytotoxic concentrations of CDDO derivatives in cultured cells inhibited LonP1, but not the 26S proteasome. Taken together, these findings provide insights for future development of LonP1-specific inhibitors with chemotherapeutic potential.The mitochondrial protein LonP1 is an ATP-dependent protease that mitigates cell stress and calibrates mitochondrial metabolism and energetics. Biallelic mutations in the  LONP1 gene  (A) have also been proposed to regulate anti-inflammatory and antioxidative stress response pathways -dien-28-oic acid (CDDO) and its methyl derivative CDDO-Me  A 15). T. TA) (15A) , 18, 19,A) A have alpathways , 22, 23.pathways , 25, PPApathways , 27, IκBpathways , mTOR   and valiA) inhibited not only the ATP-dependent protease activity of LonP1 as shown by degradation of fluorescently-labeled casein (FITC-casein) , but also the ATPase activity as shown by endpoint assays  and continuous enzyme-coupled assays . CDDO-anhydride is a derivative in which the R group is another CDDO molecule . Notably, TP-82, which is identical to CDDO but lacks the electron-withdrawing nitrile moiety   and also failed to inhibit the degradation of FITC-casein by LonP1 . Similarly, a pentacyclic triterpenoid enoxolone, lacking an electron-withdrawing group, did not inhibit the LonP1 ATPase . These results show that the electron-withdrawing moiety of CDDO derivatives is crucial for inhibiting LonP1. By contrast, compounds such as bortezomib and MG262 that are known to inhibit LonP1’s protease activity  , 29, 39 activity , 40 do nactivity . Bortezoactivity . These cactivity , 43, andactivity .Figure 2E and G), whereas CDDO-Me and -Im inhibited LonP1 after only 5 min at 30 °C (E and G and S2B). The reversibility of inhibition by CDDO derivatives was demonstrated by preincubating LonP1 for 60 min at 30 °C with CDDO-Me with a high concentration of compound (10 μM) to completely block the degradation of FITC-casein (H), followed by dialyzing the reaction mixture at 4 °C for 24 h, which restored proteolytic activity (I). Collectively, these results support the notion that CDDO derivatives reversibly block the ATPase activity of LonP1, and that inhibition occurs by a mechanism independent of peptide bond hydrolysis.We further showed that CDDO derivatives are slow-binding and reversible inhibitors of LonP1. The inhibitory effect of CDDO on ATP-dependent proteolysis was most pronounced after ≥20 min preincubation at 30 °C , E and GC-casein H, followactivity I. Collecmax, Ki, and αKi values  but different Y-intercepts. CDDO, CDDO-Me, and CDDO-Im had α-values of 5.4, 4.3, and 1.1, respectively (A). Collectively, these results demonstrate a noncompetitive mechanism by which CDDO and its methyl and imidazole derivatives inhibit the ATPase and protease activities of LonP1 and a competitive mechanism of inhibition by CDDO-anhydride . The Ki was determined by Lineweaver–Burk plots. The inhibitory dissociation constants for E and ES complex  were independent of the substrate concentration by contrast to IC50 values . The αKi values of these compounds were determined by plotting the reciprocal of Vmax against the inhibitor concentration and fitting the data by linear regression. The α values for CDDO and CDDO-Me were 5.4 and 4.3, respectively . While any of these nearly complete structures could be used to identify the binding pocket and to dock CDDO derivatives, we selected PDB entry 7NGF for our analysis, which contained bound ATP/ADP and the polypeptide substrate. The C-terminal end view of this LonP1 complex, clearly shows a homohexameric form of the protease . A 90° anticlockwise rotation of the LonP1 complex with bound ADP/ATP shows the protein substrate-binding domain together with the ATPase and protease domains of LonP1 ; the threaded polypeptide chain has been removed for clarity. The inset shows CDDO docked between two adjacent subunits, and ATP also bound between these subunits . Our docking results showed that CDDO derivatives were bound at two nonoverlapping sites within a hydrophobic channel at the interface between subunits adjacent to the ATP/ADP-binding site. We designated these sites as Site 1, which is distal to bound ATP/ADP (B) (at 20 Å away), and Site 2, which is more proximal (at ∼4 Å away) to the ATP/ADP-binding site (C). CDDO-Me, CDDO-Im, CDDO, and CDDO-anhydride could be docked at Site 1, consisting of amino acids from two adjacent LonP1 subunits . By contrast CDDO-anhydride interacted with three adjacent LonP1 subunits . Only CDDO and CDDO-anhydride could be docked at Site 2 . As CDDO-Me and CDDO-Im are the more potent inhibitors of LonP1 , which is in contrast with the other CDDO derivatives that showed noncompetitive inhibition . There was significant increase in apparent Km for ATP with minimal decrease in the Vmax. Additionally, LonP1 inhibition by CDDO-anhydride was overcome by increased ATP concentration, further supporting a competitive mechanism of inhibition. In the presence of CDDO-anhydride, the ATPase activity of LonP1 had a Ki of 9.5 ± 1.4 μM  (The proposed mechanism by which CDDO derivatives inhibit target proteins is through the formation of Michael adducts between these electrophilic compounds and nucleophilic groups within the protein (esidues) , 46. Foresidues) , 25, IKKesidues) , Jak2, aesidues) , which aD). Conservative amino acid substitutions were engineered by replacing both cysteine residues with the hydrophobic residue valine (C576V and C637V) or with the polar residue serine (C576S and C637S). In addition, phenylalanine 547 (F547), also positioned within the same hydrophobic cluster  was replaced by alanine (F547A). Intriguingly, C576V, C637V, C637S, and F547A did not ablate inhibition by CDDO; instead, these mutations increased inhibition as demonstrated by reduced IC50 values . Collectively, these data suggest that C576, C637, and F547 residues are critical for the geometry of the CDDO-binding pocket, and that C576 and C637 do not participate in the formation of adducts with CDDO derivatives thereby leading to LonP1 inhibition.Two cysteine residues at positions 576 (C576) and 637 (C637) are located near a hydrophobic cluster adjacent to the CDDO binding Sites 1 and 2 D. Conser cluster D, Site 10 values . Single o 8-fold . Compareectively . Controlectively , A and B2, respectively. As an example, results showed that the C576V substitution altered the side chain orientation of compound-binding pocket residues, increasing the number of interactions with CDDO . Increased hydrophobicity would reduce the flexibility of the compound binding pocket (Site 1), thereby stabilizing the interaction of binding site residues with CDDO . Several residues on the same side of C637 that interact with CDDO derivatives include M569, H561, Q575, K572, D554, E557, and M552 . Several residues from the neighboring subunit and opposite to C637 interact with CDDO, which include L620, H622, K559, E609, V555, P603, A606, G601, S605 . Amino acids F547 and F545 are buried and do not directly interact with CDDO derivatives, but they are within van der Waals interacting distance from K572, E557, and M552, which directly interact with CDDO . Therefore, we suggest that the mutation F547A reorients K572 closer to CDDO. By contrast to the C637V mutation, the impact of the C637S substitution is not clear from the modeled structures. It is possible that the serine substitution at C637 interacts with the backbone N-H or C=O moieties, thereby reducing the flexibility of the binding pocket leading to stronger interactions between binding site residues and CDDO derivatives , thus increasing compound affinity and inhibition. Our interpretation is speculative, and we acknowledge that the mutant-dependent decrease in IC50 values may be explained by other mechanisms as well. Interestingly at Site 2, E591 and K594, which are at the Walker Motif B of the ATP-binding site, QM/MM showed interaction with CDDO . The conserved E591 and K594 residues in homologs of LonP1 from bacteria to humans are essential for activating a water molecule leading to the nucleophilic attack on the γ-phosphate of ATP  and P648, E647, and D651 from the adjacent subunit . Although, it is possible that CDDO forms adducts with cysteine residues elsewhere in LonP1 leading to inhibition as has been shown for other CDDO target proteins, this appears unlikely as there are no other cysteine residues located in proximity of the compound-binding pockets.To gain insight into how amino acid substitutions at C576, C637, and F547 might introduce structural changes in LonP1, we conducted mutant modeling using Schrödinger Suite “Prime”  followed by quantum mechanics/molecular mechanics (QM/MM) minimization using “Jaguar.” The solvent accessibility surface area (SASA) of C576 and C637 is 45 and 38 Åith CDDO . The anaR721G) and showed that it retained partial ATPase activity with a Km for ATP of 71.70 ± 3.14 μM and a Vmax of 9.51, as compared with wild-type LonP1WT with a Km of 19.81 ± 0.72 μM and a Vmax of 9.66 (H and I). We have previously shown that the LonP1R721G mutant also retains ATP-dependent protease activity albeit reduced as compared with LonP1WT (R721G showed resistance to CDDO-Me (20 μM), as compared with LonP1WT (H). Similarly, LonP1R721G also showed resistance to CDDO-anhydride (20 μM) (I). These data suggest that pathogenic mutation within the LONP1 gene, as well as nonpathogenic polymorphisms, can influence compound sensitivity and may be informative and potentially exploited in compound design and chemotherapeutic applications.We were curious to know whether a naturally occurring pathogenic mutation in LonP1 might alter inhibition by CDDO derivatives. Biallelic mutations in the chromosomal gene encoding human LonP1 cause CODAS syndrome , 10. We  of 9.66 , H and I LonP1WT  (9). Int LonP1WT H. Simila (20 μM) I. These E). R721 is at the interface of two neighboring subunits near the CDDO-binding pocket leading to a relay of salt bridges. The interface has multiple polar interactions appearing to form a flexible channel lined by a number of salt bridges on adjacent subunits , which may permit the entry of CDDO derivatives to their respective binding pockets. R721 on one subunit (cyan) forms a salt bridge with E654 from the adjacent subunit (orange), which also forms a salt bridge with R500 of the same subunit (orange). E654 (orange) also forms a salt bridge with K517 (orange), which forms a salt bridge with E717 (cyan) that forms a salt bridge with K714 (cyan). Another salt bridge between R710 (cyan) and D651 (orange) is proximal to the CDDO binding at Site 1. It is possible that the missense mutation R721G likely disrupts this network of salt bridges, altering channel geometry such that the new topology at the subunit interface hinders binding of CDDO derivatives at Site 1. Additionally, substitution of R721 by the smaller glycine side chain is expected to generate significant a solvent accessible region for the increased dissociation rate of compounds from the binding pocket, reducing compound binding affinity and therefore decreased efficacy of inhibition by CDDO derivatives.Molecular modeling using the same cryo-EM structure of LonP1 provided some insights into the mechanism by which the CODAS mutation R721G ablated inhibition by CDDO derivatives E. R721 i+ superfamily of ATPases Associated with diverse cellular Activities, which mediate various cellular processes such as DNA replication, recombination, chromatin remodeling, ribosomal RNA processing, membrane fusion as well as ATP-dependent proteolysis (+ family (A). Control experiments demonstrated that in the absence of CDDO, the 26S proteasome hydrolyzed ATP in a concentration-dependent manner, whereas the 20S particle lacking the 19S component did not have ATPase activity (B). We sought to test the apparent selectivity of CDDO derivatives for LonP1 but not the 26S in cultured cells. There are no known proteins that are constitutively degraded by LonP1 under baseline conditions, which would permit us to assay protease inhibition by CDDO derivatives. Therefore, we employed experimentally derived HeLa cells lacking mitochondrial DNA (mtDNA) (referred to as HeLa ρ0 cells) , it is rapidly degraded by LonP1, thus providing a readout for protease activity (LonP1 belongs to the AAAteolysis . The 26S+ family . Althoug+ family A. Controactivity B. We sou0 cells) , in whicC). CDDO-Me at 1 μM led to increased protein levels of p53; however, ≥1 μM CDDO-Me was cytotoxic, inducing apoptosis as demonstrated by the increased levels of cleaved PARP and decreased levels of procaspase 3, which are indicative of caspase 3 activation (C). No change in the protein levels of LonP1 or actin was observed. Consistent with our previous observation, CDDO-Me primarily stabilized the full-length TFAM precursor protein (C). Like CDDO-Me, CDDO-anhydride (1.5–20 μM) selectively and effectively inhibited TFAM degradation by LonP1 (D), stabilizing the TFAM precursor as well as the mature form albeit to a lesser extent (D). The TFAM precursor may accumulate because of inefficient processing of the full-length polypeptide resulting from changes in mitochondrial membrane fluidity induced by CDDO derivatives as previously suggested (D). No change in procaspase 3 levels was observed up to 5 μM. However, concentrations of CDDO-Me >10 μM were cytotoxic, leading to decreased levels of procaspase 3, indicating its cleavage and the activation of apoptosis (D). CDDO-anhydride had no effect on the protein levels of LonP1 or actin.LonP1-mediated proteolysis of TFAM was inhibited by CDDO-Me at 0.125 to 0.5 μM, which did not block 26S proteasome-dependent degradation of p53 C. CDDO-Mtivation C. No cha protein C. Like Cby LonP1 D, stabilr extent D. The TFuggested . CDDO-anuggested D. No chapoptosis D. CDDO-aE and F). In both cases, there was no significant change in HO-1 transcript levels, thus under these conditions, LonP1 protein levels did not affect HO-1 transcription (E and F). This finding was also observed in the HeLa ρ0 cells, which showed that CDDO-Me stabilized HO-1 at ≥0.125 μM, and CDDO-anhydride stabilized HO-1 at ≥0.25 μM (G). Taken together, these data support the conclusion that noncytotoxic concentrations CDDO-Me and CDDO-anhydride selectively inhibit LonP1 but not the 26S proteasome without induction of apoptosis and suggest that CDDO derivatives can show target selectivity within the AAA+ family of ATPases.To examine the effects of CDDO-anhydride and CDDO-Me in cells that had an intact mitochondrial genome, we examined another potential protein substrate of LonP1, heme oxygenase 1 (HO-1). Published work suggested that LonP1 constitutively degrades HO-1, which catalyzes the degradation of heme within mitochondria . To democription , E and F≥0.25 μM G. Taken ER and UPRmt, respectively) have been postulated to impart an advantage to cancer cells, supporting cell survival, proliferation and evasion of immunosurveillance, and drug resistance .In this study, we demonstrate that CDDO, CDDO-Me, and -Im are allosteric noncompetitive inhibitors of the LonP1 ATPase, which directly block ATP binding and hydrolysis and hence they also inhibit ATP-dependent proteolysis. Allosteric inhibitors offer potential advantages in the development of protein-specific compounds as they do not bind primary orthosteric active sites, which are often highly conserved. Instead, they bind at remote sites that modulate active site conformation. As the geometry of allosteric-binding sites is frequently unique or with limited representation in cellular protein structures, this increases the potential for target specificity and selectivity. In addition, noncompetitive inhibitors bind not only to the free enzyme but also to the enzyme-substrate complex, thus inhibition is unaffected by fluctuating substrate concentrations. By contrast, CDDO-anhydride is a competitive inhibitor, which like CDDO-Me also inhibits LonP1 in cells , D and G+ ATPases. It is possible that CDDO derivatives may interfere with other AAA+ proteins such as the mitochondrial matrix ClpXP protease. Recent work has identified small-molecule inhibitors and activators of ClpXP  were purchased from Cayman Chemical, CDDO-Imidazole (CDDO-Im) was purchased from Tocris. CDDO-anhydride  and TP-8E. Coli, and purified using a nickel agarose column as previously described  for 30 min at 30 °C. Reactions were initiated by the addition of FITC-casein (0.1 mg/ml) and ATP (4.0 mM) and incubated at 37 °C. The kinetics of FITC-casein degradation was measured by the increase in relative fluorescence units (RFU) at 490–525 nm wavelength at 37 °C using a Spectramax or Biotek Synergy plate reader. For endpoint assays, aliquots of reactions incubated at 37 °C were removed at indicated time points and terminated by adding 5X reducing sample buffer (RSB). The decrease of intact FITC-casein was determined by SDS-PAGE followed by visualization using FluorChem or Chemi-Doc systems.Human LonP1 (1.0 μM monomer) was preincubated with CDDO derivatives, TP-82, enoxolone (5 μM) or DMSO vehicle control (1%) in buffer  were preincubated with CDDO-Me (10 μM) or DMSO (1%) for 60 min at 30 °C. After this period, respective aliquots (50 μl) were removed and assayed for FITC-casein degradation to confirm inhibition by CDDO-Me. The remaining 450 μl reaction was transferred to a Slide-A-Lyzer (100 kDa MWCO) and dialyzed against 500 ml Buffer K  for 24 h at 4 °C. After this period, the protein concentration was measured to determine protein recovery and the protease activity of LonP1, which had been preincubated with and without CDDO-Me was measured using the FITC-casein degradation assay.Reactions (500 μl) containing LonP1 (1.0 μM monomer) in buffer . The 26S and 20S proteasome were also assayed at 0, 0.75, 1.5, 3, 6, and 12 nM in the absence of CDDO derivatives. UltraPure ATP  was added, and reactions  were incubated for 60 min at 25 °C, then 5 μl was transferred in quadruplicate to a 384-well plate. Assay reagents were used to quench further ATPase activity and generate luminescence signals proportional to the concentration of ADP formed. Background (no enzyme control) luminescence values were subtracted, and resultant values were reported as a percentage of the no drug control (100%). Data were fit to four-parameter dose–response curves using GraphPad Prism. The error bars represent the standard deviation (SD) of four replicate reactions from at least three independent experiments.ADP-Glo (Promega) assays were performed according to the manufacturer's protocols. Purified wild-type or mutant LonP1 (400 nM monomer), the 26S proteasome (3 nM), or no enzyme controls were preincubated in 96-well plates  with ten different concentrations of CDDO and its derivatives, TP-82, enoxolone (5 μM) or DMSO vehicle control in buffer (40 mM Tris-HCl (pH 7.5), 20 mM MgClATPase reactions  were performed in 96-well plates at room temperature. LonP1 (400 nM monomer) was preincubated with DMSO (1–2%) vehicle control or CDDO derivatives in buffer  for 30 to 45 min at room temperature or 30 °C. The reactions were initiated by the addition of phosphoenolpyruvate , NADH (300 μM), pyruvate kinase and lactate dehydrogenase (PK-LDH) (12–20 U/ml), and ATP concentrations as indicated. The change in NADH absorbance at 340 nm was monitored in Spectramax plate reader for 5 min to obtain reaction velocities. Data were fit to the Michaelis–Menten curve using GraphPad Prism 5, and the error bars represent the standard deviation (SD) of four replicate reactions from at least three independent experiments.The cryo-EM structure of the LonP1 complex composed of nearly full-length subunits (PDB NGF) consisting of the amino-terminal protein substrate binding domain, the ATPase and protease domains, was used for identifying compound-binding pockets and docking of the CDDO derivatives. Three independent molecular modeling programs were used: (i) Q-siteFinder, (ii) SiteMap , and (iii) SiteID . Prior to subjecting the structure of LonP1 to the SiteMap program, Protein Preparation Wizard  was used to add hydrogen atoms, partial charges, protonation states, and optimization of H-atoms. The final structure was subjected to restrained minimization (1000 iterations) by ‘Impact’ program of Schrödinger Suite with OPLS_2005 force field. The other pocket finding software Q-SiteFinder and SiteID did not require addition of hydrogen bonds and partial charges; hence, the unaltered cryo-EM structure of LonP1 was used for CDDO-binding pocket analyses. In all three programs, the bound ATP and ADP as reported in the cryo-EM structure were taken into account. Potential CDDO-binding sites predicted by the three programs were visually inspected for their size and shape complementarity with the CDDO derivatives. Two pockets were predicted by all three programs  for the docking of CDDO, CDDO-Me, CDDO-Im, and CDDO-anhydride near the ATP/ADP-binding site.The docking of CDDO derivatives was conducted as follows. First, the molecular models of CDDO, CDDO-Me, CDDO-Im, and CDDO-anhydride were generated from “structure data files” (sdf) obtained from PubChem. The 3D structures of these compounds as well as their tautomeric forms were generated by using LigPrep, a ligand preparation tool of Schrödinger Suite. These structures were then docked into the selected binding sites using the “induced-fit docking” utility of the software “Glide” (Schrödinger Suite). The “Induced Fit Docking” workflow allowed the optimization of side chains in the binding pocket to filter the compounds for best binding energy. The top two poses exhibiting best binding energy were selected for structural analyses. All docking was done in the presence of ATP and ADP as reported in the cryo-EM structure. The charges on ADP/ATP were calculated by semiempirical quantum mechanical method PM3 , 74.The specific amino acid substitutions in LonP1 were generated by “Prime” utility of Schrödinger Suite. The hexameric cryo-EM structure of LonP1 was subjected to limited minimization (1000 steps) by “Impact” using the OPLS_2005 force field followed by molecular dynamics simulation. First, we applied the Quantum Mechanical/Molecular Mechanical (QM/MM) protocol using Q-site (Schrödinger Inc. NY) to calculate the partial charges on CDDO and its derivatives and ADP molecule, and on side chains within 6 Ǻ from both ligands. These charges were subsequently used to perform molecular dynamics (MD) simulations for 10,000,000 steps with 50 femtosecond step size. All the atoms more than 20 Å away from ADP and CDDO derivatives were constrained to their mean position in MD simulations.0) and LCL cells were generated as described previously (2 at 37 °C. LCL cells were cultured in RPMI supplemented with 15% FBS. HeLa Rho 0 cells were cultured in high glucose DMEM (25 mM) (Sigma) supplemented with sodium pyruvate (110 mg/ml) and uridine (50 mg/ml). CDDO-Me was purchased from Cayman chemicals, and CDDO-AH was synthesized as described previously  containing 2X Halt phosphatase and protease cocktail inhibitor (Thermo Scientific) for 20 min on ice. After centrifugation at 14,000 rpm for 15 min at 4 °C, the supernatant was collected and estimated for protein by Bradford’s method. In total, 30 to 40 μg of protein was separated by SDS-PAGE and immunoblotted with respective antibodies.RNA was isolated using RNAeasy kit (Qiagen) as described in the manufacturer’s protocol. In total, 500 ng of RNA was converted to cDNA using cDNA conversion kit (Applied Biosystems); 50 ng cDNA was used to estimate the relative quantification of HO-I transcripts after normalizing with GAPDH transcripts. The relative quantification (RQ) was calculated using CFX 96 software (Bio Rad) by ΔΔCt method and expressed as RQ ± standard error mean (SEM).All data are included within the manuscript.This article contains supporting informationThe authors declare that they have no conflict of interest with the contents of this article.


Pseudomonas aeruginosa and Escherichia coli. SABA1 inhibits biotin carboxylase (BC), the enzyme that catalyses the first half reaction of ACC. SABA1 inhibits BC via an atypical mechanism. It binds in the biotin binding site in the presence of ADP. SABA1 represents a potentially new class of antibiotics that can be used to combat the antibacterial resistance crisis.The rise of antibacterial-resistant bacteria is a major problem in the United States of America and around the world. Millions of patients are infected with antimicrobial resistant bacteria each year. Novel antibacterial agents are needed to combat the growing and present crisis. Acetyl-CoA carboxylase (ACC), the multi-subunit complex which catalyses the first committed step in fatty acid synthesis, is a validated target for antibacterial agents. However, there are at present, no commercially available antibiotics that target ACC. Ethyl 4-[[2-chloro-5-(phenylcarbamoyl)phenyl]sulfonylamino]benzoate (SABA1) is a compound that has been shown to have antibacterial properties against  Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp) are particularly problematic. These six pathogens are the leading cause of nosocomial infections worldwide and are known for their ability to “escape” destruction by many current antibioticsKlebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter) are Gram-negative. Gram-negative bacteria are generally more resistant to antibiotics than Gram-positive organisms, largely because of their outer membraneIn a 2020 report, the World Health Organisation called antimicrobial resistance (AMR) “a major threat to human health with significant global economic and security implications”The fatty acid synthesis type-II (FASII) pathway is a validated target for antibiotic development against Gram-negative bacteria,Acetyl-CoA carboxylase (ACC) is the multi-subunit complex that catalyses the first committed step in fatty acid synthesisBoth CT and BC are the targets of antibacterial compounds. The natural products andrimid and moiramide B both target CT and are competitive versus malonyl-CoAin vivo high-throughput screen capable of identifying FASII inhibitors in Pseudomonas aeruginosa and Escherichia coliE. coli (ΔtolC::tet) and prolongs the doubling time of the efflux compromised P. aeruginosa strain PAO397 by 30%50 of 4.0 µM against E. coli ACCIn 2015 a group from Microbiotix, Inc. developed an In this report, we definitively establish that SABA1 inhibits BC. Instead of binding in the ATP-binding site like all other known inhibitors of BC with antibacterial properties, SABA1 binds in the biotin binding site. We further demonstrate that SABA1 inhibits BC via an atypical mechanism where SABA1 binding is strongly enhanced by the presence of ADP.All reagents for protein expression, purification, and kinetic analysis were purchased from MilliporeSigma, Fischer Scientific, Bio-Rad, New England BioLabs, or Thermo Scientific except where noted. SABA1 was purchased from Hit2Lead.4, 500 mM NaCl, pH 8.0). The resuspended cell pellet was then either frozen or purified immediately.Biotin carboxylase with an N-terminal His tag4, 500 mM NaCl, pH 8.0). Protein was eluted with NPI-500  and collected in 1 mL fractions. Purity was determined by SDS-PAGE and pure fractions were pooled. The pooled fractions were first dialysed against 10 mM Hepes pH 8.0, 150 mM KCl, 1 mM EDTA, to remove any residual nickel, then 10 mM Hepes pH 8.0, 150 mM KCl. The pure protein was concentrated, aliquoted, and stored at −80 °C.Cells were lysed by sonication in the presence of DNase. The resultant lysate was clarified by centrifugation at 4 °C. The clarified lysate was loaded onto a Ni-NTA column pre-equilibrated with Buffer A. The column was washed with 200 mL of Buffer A then 200 mL of NPI-45  using the EnzChek® Phosphate Assay Kit (Molecular Probes) according to the manufacturer’s protocol. In brief, purine nucleoside phosphorylase converts 2-amino-6-mercapto-7-methylpurine riboside to ribose 1-phosphate and 2-amino-6-mercapto-7-methylpurine in the presence of Pi. This reaction is monitored at 360 nMFor inhibition studies that varied ATP or biotin, initial velocities were measured as previously reportedTo determine the inhibition pattern versus ATP, ATP was varied from 0.05 mM to 1.0 mM. SABA1 was held at fixed concentrations of 0.0 µM, 75 µM, or 150 µM. Biotin was held constant at 40 mM. To determine the inhibition pattern versus biotin, biotin was varied from 20 mM and 200 mM. SABA1 was held at fixed concentrations of 0.0 µM, 75 µM, or 150 µM. ATP was held constant at 0.2 mM. Each reaction was started with the addition of enzyme.i assay, ADP was varied from 0.19 µM to 19 µM. ATP was held constant at 0.6 mM, biotin was held constant 40 mM, and SABA1 was held constant at 100 µM. Each reaction cocktail was incubated in the presence or absence of SABA1 for 10 min. The reaction was started by addition of biotin.To determine the inhibition pattern versus ADP using the PTo determine the multiple inhibition pattern with respect to ATP, aminooxazole was varied from 0.2 µM to 3.2 µM. SABA1 was held at fixed concentrations of 0.0 µM, 75 µM, or 150 µM. ATP and biotin were held constant at 0.2 mM and 40 mM, respectively. To determine the multiple inhibition pattern with respect to biotin, desthiobiotin was varied from 1.0 mM to 20 mM. SABA1 was held at fixed concentrations of 0.0 µM, 75 µM, or 150 µM. ATP and biotin were held constant at 0.2 mM and 40 mM, respectively.As stated above, the components of ACC were purified separately. Purified BC, BCCP, and CT were combined in a 1:2:1 molar ratio and allowed to equilibrate for 1 h prior to assaying ACC. To determine the inhibition pattern versus ATP, ATP was varied from 1.0 µM to 16 µM. SABA1 was held at fixed concentrations of 0.0 µM, 50 µM, or 100 µM. Acetyl-CoA was held constant at 0.20 mM. The reaction was started by the addition of enzyme.v is the experimentally determined velocity, V is maximal velocity, A is substrate concentration, Km is the Michaelis constant, I is inhibitor concentration and Kis is the inhibition constant for the slope.Data for inhibition studies varying ATP or biotin were analysed by nonlinear regression using the programs of Clelandv is the experimentally determined velocity, V is maximal velocity, A is substrate concentration, Km is the Michaelis constant, I is inhibitor concentration and Kii is the inhibition constant for the intercept and Kis is the inhibition constant for the slope.Non-competitive inhibition data were fitted to v is the experimentally determined velocity, V is maximal velocity, L and J are the concentration of the two inhibitors, KL and KJ are the apparent inhibition constants of those respective inhibitors, and α is the interaction factor of the two inhibitors.Multiple inhibition data were fitted to v is the velocity in the presence of inhibitor, ov is the uninhibited velocity, Ki′ is the apparent inhibition constant, and I is the concentration of inhibitor.Data for inhibition studies varying ADP were analysed by nonlinear regression using the program Enzfitteri′ is the apparent inhibition constant, Kii is the real inhibition constant for the intercept, S is the substrate concentration, and Km is the Michaelis constant.The apparent inhibition constants were fitted then to The structure of SABA1 was obtained from the ZINC databaseis of 242 ± 32 µM + + i′) for the binding of SABA1 clearly decreases as the concentration of ADP increases  is tighter than the predicted binding affinity of the carboxybiotin analogue, N1′-methoxycarbonyl biotin methyl ester, to BC . The N1′-methoxycarbonyl biotin methyl ester is known to bind in the biotin binding siteThe kinetic data show that SABA1 does not bind in the presence of ATP. In order to determine a possible molecular mechanism that explains why ATP prevents SABA1 binding, SABA1 was docked onto BC with ATP analogue AMPPCP bound. With AMPPCP bound SABA1 adopts an inverted conformation with respect to the conformation it had with ADP bound . This inThe docking results could provide an explanation of how SABA1 can simultaneously appear competitive versus ATP and uncompetitive versus ADP. ADP is necessary for efficient SABA1 binding as it positions the sulphonamide group in a favourable conformation to hydrogen bond to R292 and N290. In addition, the β-phosphate of ADP hydrogen bonds to SABA1 further enhancing the binding affinity. On the other hand, the presence of ATP forces SABA1 into an inverted conformation in which the sulphonamide group is not able to form hydrogen bonds to strengthen binding to BC.,,The residues involved in hydrogen bonding between SABA1 and ADP-bound BC  are all involved in BC catalysisThis report definitively shows that SABA1 does inhibit BC and it does so with an atypical mechanism. Moreover, SABA1 is the first known inhibitor of BC with antibacterial properties that does not bind in the ATP-binding site. All other known BC inhibitors with antibacterial properties bind in the ATP-binding site. Since, biotin carboxylase is highly conserved amongst bacteria species


The Greenland ice sheet has been one of the largest sources of sea-level rise since the early 2000s. However, basal melt has not been included explicitly in assessments of ice-sheet mass loss so far. Here, we present the first estimate of the total and regional basal melt produced by the ice sheet and the recent change in basal melt through time. We find that the ice sheet’s present basal melt production is 21.4 +4.4/−4.0 Gt per year, and that melt generated by basal friction is responsible for about half of this volume. We estimate that basal melting has increased by 2.9 ± 5.2 Gt during the first decade of the 2000s. As the Arctic warms, we anticipate that basal melt will continue to increase due to faster ice flow and more surface melting thus compounding current mass loss trends, enhancing solid ice discharge, and modifying fjord circulation. Melting at the base of the Greenland Ice Sheet is often disregarded as a source of quantifiable mass loss. In this study, the authors find the basal mass loss is equivalent to 8% of the ice sheet’s present imbalance, and that the loss of mass from basal melt is likely to increase in the future. The average mass balance of the ice sheet between 2005 and 2015 is −254 ± 18 Gt per year with a spread between different mass balance estimates of 36 Gt per year6. Gravity methods implicitly include basal mass loss, while altimetry methods attribute all mass loss to either ice discharge or surface mass loss. Either method provides limited insights into the physical processes leading to the observed change in mass. In contrast, the input-output method relies on accurate process representation of the climatic and dynamic mass-loss terms and thus provides the possibility of predicting future changes. To date, the input-output method has overlooked basal mass balance entirely. Constraining basal melt is important for three reasons. Firstly, uncertainty in the partition of ice-sheet mass loss between surface mass balance and ice discharge, including the failure to acknowledge the basal mass balance term, limits our understanding of changes in ice-sheet mass budget in response to recent climate change. This impedes our ability to capture complex interactions and feedbacks between ice sheets and the climate system. Secondly, the presence or absence of basal meltwater is important for the evolution of the subglacial system8, and recent studies have highlighted the importance of subglacial discharge for modifying the mass loss from marine-terminating glaciers10, it therefore plays an important role for Greenland outlet glaciers’ contribution to future sea-level rise12. Finally, discharge of subglacial water modifies circulation in the fjord systems and may impact nutrient mixing14.Mass loss from the Greenland ice sheet is determined via one of three methods: through estimates of ice volume change from satellite altimetry15, winter velocity maps from 2000/2001 to 2018/201917, and average decadal/multi-decadal surface melt-water volumes from 1991–201218. This allows us to construct a baseline basal-melt value against which we can compare likely changes in basal melt rates in the recent past. We assume that all basal melt water is discharged to the ocean or land-margin since the geometry and high surface slopes of the ice sheet preclude the existence of long-term meltwater storage in subglacial lakes19. Although studies have found evidence of subglacial lakes21 and “units of disturbed radio-stratigraphy”23, associated volumes are negligible in the context considered here. Similarly, model results indicate that basal freeze-on rates are unlikely to be of significance for the basal mass budget24. Our results demonstrate that basal melt is a non-negligible component of the mass balance of the Greenland ice sheet, and that basal melt-water production is likely increasing and will continue to do so in the foreseeable future.Here, we provide the first estimate of ice-sheet-scale basal melt and its change through the first decade of the 2000s. We consider three sources of basal heat that generate melt Fig. a–c. The 27 and is masked with an independent estimate of where basal ice is likely at pressure melting point28 .Frictional heat is produced by ice sliding over the bed. We retrieve an estimate of frictional heat using the Elmer/Ice model, where the complete stress balance is solved (“Full Stokes”)Melt from frictional heating is concentrated in areas with high ice-flow velocities i.e. at major glacier outlets Fig. b, e. Mos34. We further assume that the water only penetrates to the bed at altitudes below 2000 m above sea level. This heat source has been calculated in previous studies34 using surface water volumes from a regional climate model35 but not translated directly into basal melt rates. Here, we use a recently published surface melt-water estimate based on an average of 13 regional climate models18. We estimate that the average basal melt due to surface melt-water injection was 5.2 ± 1.6 Gt per year in 1990–2010. Uncertainties stem from the reported 30% variability between regional climate model results. Note that there is significant variation between models on a sector-by-sector basis.Finally, we consider heat generated by surface melt water as it infiltrates the subglacial system Fig. c. We conThe basal melt due to surface melt water is focussed in areas where surface melt occurs, and where the water is subjected to large hydropotential gradients as it flows along the ice-sheet bed Fig. f. The he5). The basal melt also corresponds to more than half of the annual discharge of Sermeq Kujalleq (average of 1986–2018), the largest single Greenlandic glacier contributing to sea-level rise5. At ice-sheet scale, basal melt is primarily caused by frictional heating (51%), with surface-melt water heat and geothermal heat as secondary contributors .The largest basal mass loss occurs in the CW and SW sector (3.9 ± 0.7 Gt per year), followed by the SE sector (3.7 + 0.8/−0.7 Gt per year) and the NW sector (3.5 + 0.7/−0.6 Gt per year). The NO sector has the smallest basal mass loss (1.5 + 0.4/−0.3 Gt per year) due to a combination of low friction melting and small volumes of surface melt water. The largest mass loss due to surface melt-water heat occurs in the SW sector, while the largest losses due to friction heat and geothermal flux occur in the CW and NE sectors, respectively  velocities37 (see methods). The use of winter velocities entails that we are underestimating the friction heat while the simplified approach introduces additional uncertainties (see methods). We find that the basal melt from our simplified approach is 31% higher compared to the basal melt from the Full Stokes approach. The simplified stress-balance overestimates the basal melt in all sectors (except the CE sector) but the difference is not evenly distributed between sectors with the largest differences in the NE region (59%) and NW sector (52%) . In particular, we assume that the basal shear stress remains constant despite the velocities changing . Using this simplified approach, we estimate that the friction melt has increased from 10.6 ± 4.3 Gt in winter 2000/2001 to 11.8 ± 4.5 Gt in winter 2017/2018, corresponding to an increase of 10%  but all sectors experience an increase in basal melt caused by surface melt water ), and in basal melt due to surface melt water of 2.5 ± 2.1 Gt. This corresponds to a total increase of 2.9 ± 5.2 Gt.6, basal melt discharge is presently equivalent to 8% of this imbalance but has hitherto not been included in input-output estimates of total mass loss. Basal melt will change as the Greenland ice sheet responds to a warming climate. The frictional heat will increase if the areal extent of the fast-flowing regions expand, leading to an increase in basal melt production. However, the impact of climate change on ice-stream dynamics is complex and thus, we cannot predict by how much the friction term will increase. Based on the recent past  does not cover the southern tip of Greenland so in this region, the average geothermal flux map is based on only two datasets (26 and 26). We calculate the resulting melt rates from the geothermal heat assuming that the ice is at pressure melting point37.Eb is available energy at the bed, here the geothermal flux, ρi is the density of ice, and L is the latent heat of fusion. The β-parameter indicates the basal conditions. We construct β using a map of estimated basal conditions based on a combination of radar observations and model studies28, where bed conditions were classified as either “likely frozen”, “uncertain” or “likely thawed”. Here, we assume that β = 0 where grid cells are assigned as “frozen”, β = 1 where grid cells are “thawed”, and β = 0.5 for all “uncertain” grid cells.We use the average geothermal flux from three published studies41 and define the standard deviation of the geothermal flux σG asδ of the first dataset42, G1, is stated as ranging from 21 to 27 mW m−2 25, where we choose the higher value. The second dataset26, G2, does not supply an uncertainty and lacking any other information we use the standard deviation that is given for each data point. The third dataset27, G3, supplies an uncertainty. We use the standard deviation to calculate the basal melt from the spread Two sources contribute to the uncertainty of our estimate: The uncertainty of the geothermal flux maps and the unknown basal temperature. We assess the former by considering the spread in geothermal flux between the maps. Here, we adapt the approach of28 and construct two scenarios: a thawed scenario where we assume that all regions classified as uncertain are thawed , and a frozen scenario where we assume that all uncertain regions are frozen . We obtain the final uncertainties by considering two end members: 1) a “warm” scenario where all uncertain areas are assumed to be thawed and where the geothermal flux equals The second uncertainty is the unknown basal temperature of the ice. We continue to make use of the results from32. The ice-flow model uses the GIMP digital elevation model (Greenland Ice sheet Mapping Project43), and ice thicknesses and bed topography from BedMachine v3 calculated using a mass-conservation method44. We apply an ice cover mask45 in order to remove local ice caps and glaciers. Elmer/Ice uses an anisotropic mesh optimised to capture velocity and thickness variations, and insure a high resolution in the first 40 km from the ice-sheet edges. The resulting horizontal resolution ranges from ~500 m to ~50 km. Original model results have been re-gridded on a 1 km equidistant grid for the post-processing (http://elmerfem.org/elmerice/wiki/doku.php?id=eis:greenland). The internal ice temperature field comes from a paleo spin-up of the SICOPOLIS model33. The Elmer/Ice model is inverted in order to minimise the misfit between modelled and observed surface velocities. The inverse method uses a multi-year average of the surface velocity in 250 m resolution from the MEaSUREs (Making Earth System Data Records for Use in Research Environments) Greenland Ice Velocity data based on data from RADARSAT-1, ALOS, TerraSAR-X/TanDEM-X and Sentinel-1A and -1B46.The first estimate of frictional heat is obtained with the Elmer/Ice model, which is a Full Stokes ice-flow model resolving all stressesThe model is computationally expensive which makes it unfeasible to run an ensemble of models to obtain formal estimates of the uncertainties. Instead, we investigate the uncertainties associated with our simplified stress-balance model and based on insights from these experiments, we estimate the uncertainty of the Elmer/Ice output.37, coupled with the velocity observations to calculate the basal sliding velocity. In this model, we use the surface topography from the Climate Change Initiative  derived from the ArcticDEM  based mainly on the WorldView 1-3 satellites. This gives a long temporal baseline from 2007 until present day. We combine the CCI surface elevation with the BedMachine v3 bed topography data44. We apply an ice cover mask45 in order to remove local ice caps and glaciers. Ice-flow velocities are obtained from two sources: MEaSUREs and the PROMICE (Programme for Monitoring of the Greenland ice sheet) velocity product based on Sentinel-1A and -1B48. The MEaSUREs velocity maps cover the periods from winter 2000/2001 to winter 2017/2018 although the coverage is not continuous: Velocity maps are not available from 2001/2002 to 2004/2005. Only the latest velocity maps are complete so in order to get better coverage for our estimate of temporal changes, we apply the same methodology as described in5 and linearly interpolate missing values in time. We do not interpolate spatially since spatial changes are most likely larger than temporal changes for any given point. Data at the beginning or end of the time series are back- or forward-filled with the temporally nearest value for that grid cell.The second model that we use to obtain the frictional heat term is a simplified stress-balance equation, the shallow-ice approximationThe PROMICE dataset spans winter 2016/17 to winter 2018/19 and is based on intensity offset tracking. Here, the data coverage is near complete and no interpolation is necessary. We note that the PROMICE maps overestimate the velocities in the interior of the ice sheet where MEaSUREs relies on the more accurate InSAR.ud  and basal sliding ub37. Thus the total velocity isu is equivalent to the observed surface velocity uo. Our method thus retrieves the basal velocity using the observed surface velocity and the calculated deformational velocity. Theoretically, the surface velocity due to deformation is37A(T) is the flow law parameter, H is ice thickness, n the flow law exponent, and τb = τd = ρigH ∇ s, where ρi is ice density, g is gravity and ∇ s is the surface gradient. We perform this calculation on a 10 km grid where ice surfaces have been smoothed by a 20 km running mean . From the theoretical deformational velocities we thus get our basal sliding velocityL is latent heat of fusion of ice at 0 °C.The shallow-ice approximation employed here is based on the assumption that on spatial scales over several ice thicknesses, ice flow can be assumed to consist of two components: deformational velocity In the following, we discuss and quantify the uncertainties relating to our frictional heat estimate. We first present the uncertainties associated with the shallow-ice approximation and use the insights to estimate uncertainties for Elmer/Ice.A(T) depends on temperature .A main uncertainty is the unknown ice temperatures. The flow law parameter (cf. Eq. ). Since We rely on observed surface velocities to infer the basal sliding, and thus our results are also affected by uncertainties in the velocity data. To translate the velocity uncertainty into friction-melt uncertainty, we perturb all velocity data points by a randomly selected number between − 1 and 1 multiplied with the standard deviation for the point. In this way, we generate 1000 perturbed velocity maps for each MEaSUREs dataset from the years 2005/2006, 2007/2008, 2008/2009, 2009/2010, 2012/2013, 2014/2015, 2015/2016 and 2016/2017. We then calculate the friction melt for each perturbed velocity map and find that this leads to a distribution of friction melt values where 95% of values deviate less than ±1% from the mean value, and we therefore assign an uncertainty of ±1% caused by uncertainties in the velocity datasets.We primarily make use of winter velocities potentially leading to an underestimation of annual basal melt rates since summer velocities are typically higher. We use winter velocities due to the lack of complete maps from summer observations. However, with the recent launch of Sentinel-1, it is possible to construct complete summer velocity maps, and we have included two maps from summers 2018 and 2019. The resulting basal melt rates are 5% higher for these summer maps due to the increased ice-flow velocities. We note that in our simplified stress-approximation, an increase in surface velocity translates directly into an increase in friction heat because we assume that the resistance to sliding over the bed is constant regardless of velocity. Assuming that summer velocities are representative for at most 50% of the year, we estimate that exclusively using winter velocities leads to an underestimate of 2.5%.50 and the bed topography from BedMachine v3. In addition to the surface topography from the Climate Change Initiative, we use the two GIMP-derived surface topographies from50 and BedMachine that spans a time period between 20 February 2003 to 11 October 2009. Using the basal melt results from winters 2006/2007, 2007/2008 and 2008/2009, we investigate the impact of the difference in topographic datasets. We find that the difference is less than 4% and typically of the order of 2% depending on temperature offset. We use 4% as a conservative upper bound.Due to the simplicity of the shallow-ice approximation, we are also able to explore the impact of using different surface and bed topographies. We use two different bed topographies and three different surface elevation datasets. We use the kriging-based bed topography published in 2013Assuming that the uncertainties discussed above are independent, we use a simple error propagation (square root of the sum of squares) and get an uncertainty of ±27%. We assume that this uncertainty range is applicable to both the Elmer/Ice and the shallow-ice approximation models. While Elmer/Ice makes use of temperatures from a paleo spin-up run, its temperature field is still subject to uncertainties, and we consider that a ±5 °C uncertainty range is not unlikely.51 implying that our predicted basal sliding is incorrect. Furthermore, the shallow-ice approximation limits our horizontal resolution and may not resolve all the narrow (below 20 km wide) and fast flowing outlet glaciers. Comparison with outputs from the Elmer/Ice model shows that the simplified stress-balance leads to an overestimation of basal melt rates of 31%. Note that in this comparison we use the same temperature and surface velocity fields in both models so that the difference is mainly due to differences in resolution and stress approximation. The overestimation is particularly pronounced in areas with high surface velocities  and complex stress regimes (the Northeast Greenland Ice Stream). See also Supplementary Fig. 52. Our simple analysis infers negligible basal sliding in slow-flowing areas implying that we might be underestimating frictional heat in slow-flowing areas. However, the contribution of basal melt from slow-flowing area is likely orders of magnitudes smaller than the basal melt generated in fast-flowing areas, implying that this underestimation is within our stated uncertainty range.In addition to the uncertainties listed above, studies have shown that deformation predicted by the shallow-ice approximation deviates from observations particularly when sliding is presentWe use the shallow-ice approximation primarily to estimate the temporal change in basal melt, making use of the simplified ice-flow model in order to be able to conduct more model runs. Although the uncertainty of each individual year is 41%, we postulate that the uncertainty in the change in basal melt is significantly smaller. Below, we outline the reasoning behind this conjecture. Again we note that our simplified stress-approximation assumes that the basal stress is constant.We assume that the internal ice temperature is constant in time and thus the uncertainty from the unknown internal temperature is negligible when considering the change in basal melt. We also assume that the uncertainties imposed by the simplified stress balance and the low resolution are constant in time. This assumption is based on the consideration that while the general speed up of the ice sheet should lead to faster and potentially more widespread fast flow, the extent of areas exhibiting complex stress regimes is likely to remain the same, and thus the difference between a Full Stokes calculation and a shallow-ice approximation remains constant.Instead, uncertainties for the change in friction melt are firstly, based on the difference in slope for the three temperature offsets . The GrSMBMIP project compiles results from 13 regional climate models during 1980–2012 CE and we use the average values from all 13 models. The reported spread in modelled surface melt water volumes is 30% and we use this range as our uncertainty.We estimate the surface melt water contribution using previously published methodology36Φρw is the density of water, ρi is the density of ice, and zb and zs are the elevations of bed and surface topography, respectively.We assume that the subglacial water pressure is equal to the overburden pressure and that the subglacial water follows the steepest gradient of the hydropotentialQ is tracked and depends on the volume of water V, the change in hydropotential, and the change in phase transition temperature (last term)CT is the Clausius–Clapeyron slope (8.6*10−8 K Pa−1), and cp the specific heat of water 4184 J K−1 kg−1. We route the water using Eq. (As the basal melt water travels through the subglacial system it follows the hydropotential gradient, and energy is released. This energy sing Eq. , assumin34, that surface water immediately penetrates to the bed and that the englacial water is at the pressure melting point, meaning that the viscous heat dissipation contribution to basal melt is effectively equivalent to the ice volume melted to form the en- and subglacial conduits53. Note that we also assume that the water only penetrates to the bed at altitudes below 2000 m above sea level. Tests using equilibrium line altitude instead of the 2000 m elevation contour found that the resulting change in basal melt was less than 5%34. The viscous heat dissipation is the sole reason why the surface melt water increases the basal melt rates. We also keep track of the energy budget as meltwater is routed through the hydrological system, producing additional meltwater. This additional meltwater in turn may melt out more water in a positive feedback. We do not resolve the location of individual conduits explicitly and thus lacking information on their exact location, we assume that they are situated at the bed, and we calculate the potential energy of this additional melt. Locally, this leads to less than 1% increase in basal melt rates.We assume that all potential energy is converted to heatSupplementary MaterialPeer Review File


Most studies of chronic kidney disease (CKD) in Sub-Saharan Africa (SSA) have been conducted in urban settings. They relied on GFR estimated from serum creatinine alone and on the inexpensive, convenient urinary dipstick to assess proteinuria. The dipstick for proteinuria has not been directly compared with the gold standard albumin-to-creatinine ratio (ACR) in a large-sized study in SSA. We hereby assessed the influence of rural versus urban location on the level, interpretation, and diagnostic performance of proteinuria dipstick versus ACR.n = 587) and rural (n = 730) settings in South-Kivu, Democratic Republic of Congo (DRC), we assessed the prevalence, performance  and determinants of a positive dipstick proteinuria as compared with albuminuria (ACR). Albuminuria was subdivided into: A1 (< 30 mg/g creatinine), A2 (30 to 299 mg/g creatinine) and A3 (≥ 300 mg/g creatinine).In a cross-sectional population-based study of CKD in both urban (p < 0.001), whereas the prevalence of albuminuria (A2 or A3) was similar in both sites . In both sites, dipstick proteinuria ≥ 1 + had a poor sensitivity (< 50 %) and positive predictive value (< 11 %) for the detection of A2 or A3. The negative predictive value was 95 %. Diabetes [aOR 6.12 (1.52–24.53)] was a significant predictor of A3 whereas alkaline [aOR 7.45 (3.28–16.93)] and diluted urine [aOR 2.19 (1.35–3.57)] were the main predictors of positive dipstick proteinuria.The overall prevalence of positive dipstick proteinuria (≥ 1+) was 9.6 %  and was higher in rural than in urban residents (13.1 % vs. 4.8 %, ACR and dipstick proteinuria have similar positivity rates in the urban site whereas, in the rural site, dipstick was 2-fold more often positive than ACR. The poor sensitivity and positive predictive value of the dipstick as compared with ACR makes it unattractive as a screening tool in community studies of CKD in SSA.The online version contains supplementary material available at 10.1186/s12882-021-02431-w. In addition, we hypothesized that substantial differences between urban and rural lifestyles  could impact the level and interpretation of kidney markers.Chronic kidney disease (CKD) is a global public health problem, particularly in sub-Saharan Africa (SSA) , 2. DespThe design and methods of the study have been published . Partici2 , who had simultaneous assessment by bioelectrical impedance analysis  of BMI, relative and total fat mass, and relative and total muscle mass, based on the linear relationship between whole-body SMM and fat-free mass present in both genders .We measured visceral fat (% of body weight) and total body fat (% of body weight) by bioelectrical impedance analysis, using an OMRON BF508 body composition monitor  at a fixed frequency of 50 kHz. The results provided by an OMRON device equipped with such a technology were shown to be well correlated  were immediately performed on site by the study team. Thereafter, the samples were stored  in an ice pack carrier, transported on the same day to the laboratory of Hôpital Provincial Général de Référence de Bukavu, centrifuged as appropriate and stored at -20 °C. Frozen serum and urine samples were sent to the Clinical Chemistry laboratory of the Cliniques Universitaires Saint-Luc , where samples were thawed prior to analysis. Serum creatinine , urinary albumin and urinary creatinine were measured with a Roche Cobas analyzer . Serum cystatin C was measured using a PETIA method on the SPA PLUS® analyzer . This method has been standardized according to the reference material ERM-DA471/IFCC. An elevated serum CRP level was defined as ≥ 3 mg/L  as compared with the gold standard albumin-creatinine ratio (ACR), we excluded subjects with urinary dipstick positive for blood and/or leucocytes and/or nitrites. Urine pH was categorized as < 6.5, 6.5-7 and ≥ 7.5. A pH ≥ 7.5 was considered as alkaline . Urine sthnicity . CKD was 30 mg/g .t test, as appropriate. According to KDIGO , and qualitative variables as crude counts and percentages. Difference in proportions and means were compared by Pearson’s chi-square test or Student’s to KDIGO , ACR wasn = 24) and subjects who declined to participate (n = 9), 1317 adults  were included in the present study. Among 1296 of 1317 individuals who provided urine on site, 162 were excluded from further urine analyses because of positivity of urinary dipstick for blood and/or leucocytes and/or nitrites. A flow chart of the study population and laboratory measurements is depicted in supplementary Fig. p = 0.15). Compared to urban participants, rural individuals were older , less educated, and more likely to be farmers . The general characteristics of study participants are described in Table After excluding pregnant women , WC , HC , MUAC , relative body fat  and visceral fat (6.3 ± 3.6 % vs. 5.0 ± 2.7 %) than rural participants. In contrast, rural participants had significantly higher relative skeletal muscle mass  than urban subjects.The clinical characteristics of participants stratified by site and sex are provided in Table p < 0.001) than women, whereas women showed higher WC (84.1 ± 12.9 vs. 79.7 ± 9.4 cm), HC , MUAC (27.0 ± 3.7 vs. 26.4 ± 2.8 cm), BMI (24.1 ± 4.8 vs. 22 ± 3 kg/m2), relative body fat (33.3 ± 10 vs. 16.8 ± 8.0 %) and visceral fat (5.7 ± 3 vs. 5.3 ± 3.5 %) than men .As expected, male subjects had higher relative skeletal muscle , hypertension (22.5 % vs. 18.4 %) and diabetes (6.1 % vs. 2.9 %), whereas HIV prevalence (0.4 %) did not differ by site.p < 0.001). Compared to urban participants, the urine of rural participants was much more likely to be alkaline (pH ≥ 7.5)  and diluted . Urine osmolality did not differ significantly by site . Moreover, urinary osmolality did not correlate significantly with urine specific gravity, neither in the whole group , nor in the rural  and urban  subgroups  was 6.6 %  without difference by site.p = 0.07) and cystatin C  levels did not differ by site. eGFRcys was higher in urban than rural participants , whereas eGFRcr did not differ by site. Both serum creatinine  and cystatin C  was significantly higher in men than in women.Serum creatinine  were 17.2 and 86.7 %, respectively, whereas in the urban site, the sensitivity and specificity of dipstick proteinuria (≥ 1+) were 21.7 and 95.6 %, respectively.In comparison with A3, dipstick proteinuria had an overall sensitivity, specificity, PPV and NPV of 30.8 %, 89.9 %, 4.1 and 98.9 %, respectively. In the rural site, the sensitivity and specificity of dipstick proteinuria (≥ 1+) were 75 and 86.9 %, respectively, whereas in the urban site, the sensitivity and specificity of dipstick proteinuria (≥ 1+) were 11.1 and 94.6 %, respectively.In univariate logistic regression, rural residency [uOR 2.98 1.85–4.80)], alkaline urine [uOR 8.76 (4.35–17.61)] and diluted urine [uOR 3.90 (2.52–6.04)] were the main predictors of dipstick proteinuria. In multivariable logistic regression, alkaline urine [aOR 7.45 (3.28–16.93)] and diluted urine [aOR2.19 (1.35–3.57)] were the main predictors of dipstick proteinuria, whereas only diabetes [aOR 6.12 (1.52–24.53)] was a significant predictor of ACR ≥ 300 mg/g (but not of positive dipstick proteinuria)  of 9.6 %, much higher in the rural (13.1 %) than in the urban (4.8 %) site. Interestingly, the overall prevalence of significant (A2 or A3) albuminuria was 6.6 % and did not differ by site; thus, additional factors must explain the difference observed in dipstick proteinuria between rural and urban subjects. Physical activity, urinary concentration, diet, and urinary pH have previously been associated with the prevalence of dipstick proteinuria , 24.In this study, we found that the frequency of dipstick proteinuria increased when urine was more alkaline (pH ≥ 7.5). Interestingly, after adjustment for age, site, sex and other risk factors, alkaline urine remained independently associated with dipstick proteinuria. Testing for protein by dipstick is based on the protein error of indicators principle. In fact, the reagent area of urine dipstick is impregnated with tetrabromophenol blue indicator buffered to pH 3.0. In the presence of protein , there is ionization of the indicator (and hence pH) that leads to a change in color from yellow to green, then blue, depending upon the concentration . Thus, aThe present study included a large representative general population sample. To the best of our knowledge, it is the very first to compare in SSA the assessment of dipstick proteinuria with the gold standard ACR both in rural and urban sites. Although testing for proteinuria by dipstick would decrease costs, it would fail to diagnose most patients with albuminuria, an early marker of kidney disease.Our study has limitations. First, the estimates were based on single-time measurements rather than on repeat abnormalities over three or more months, as recommended by KDIGO guidelines . This isThis study provides a head-to head comparison of dipstick for proteinuria versus the gold standard ACR. Whereas in the urban site, ACR and dipstick had similar positivity rates, in the rural site, dipstick was around 2 times more frequently positive. Although the reasons for this discrepancy are probably multiple, they include a.o. urine pH and specific gravity. Overall, our results call for the use of ACR rather than dipstick in future studies of CKD prevalence in SSA, as it is a more accurate early marker of kidney disease. The expected association of ACR (but not positive dipstick) with diabetes further underscores the major limitations of the dipstick.Additional file 1: Supplementary Figure 1. Flow chart of the study population and data availability. Supplementary Figure 2. Correlation between urine specific gravity and osmolality in sub-group of urban (red line) and rural (gray line) subjects. Supplementary Table 1. Diagnostic performance of urine dipstick for the detection of ACR ≥ 30 mg/g (A2) and ACR ≥ 300 mg/g (A3). Supplementary Table 2. Diagnostic performance of urine dipstick in the study population.


Molecular switches that respond to a biochemical stimulus in cells have proven utility as a foundation for developing molecular sensors and actuators that could be used to address important biological questions. Developing a molecular switch unfortunately remains difficult as it requires elaborate coordination of sensing and actuation mechanisms built into a single molecule. Here, we rationally designed a molecular switch that changes its subcellular localization in response to an intended stimulus such as an activator of protein kinase A (PKA). By arranging the sequence for Kemptide in tandem, we designed a farnesylated peptide whose localization can dramatically change upon phosphorylation by PKA. After testing a different valence number of Kemptide as well as modulating the linker sequence connecting them, we identified an efficient peptide switch that exhibited dynamic translocation between plasma membranes and internal endomembranes in a PKA activity dependent manner. Due to the modular design and small size, our PKA switch can have versatile utility in future studies as a platform for visualizing and perturbing signal transduction pathways, as well as for performing synthetic operations in cells. In contrast, switches that shift between subcellular locations other than cytosol and nucleus are rare. In nature, we find cases where proteins change localization between two membrane systems. In the case of MARCKS and Src kinase, phosphorylation by protein kinase C (PKC) and both PKC and protein kinase A (PKA), respectively, could alter their subcellular localization (plasma membrane vs. cytosol)5. Developing a membrane switch would be useful in expanding the palette of molecular probes.Synthetic switch mechanisms are essential in developing molecular sensors and actuators with which scientists can probe biological phenomena by visualizing and perturbing underlying signal processes in living cells. Many of these switches rely on shifts in protein localization in cells that can be induced by post-translational modifications, such as phosphorylation at localization peptide sequences. For example, there are switches that exhibit translocation between cytosol and nucleus in response to phosphorylation by a target kinase6. However, a molecular switch that shifts its localization within the membrane systems based on the PKA activity has yet to be developed.PKA is a cAMP-dependent kinase that plays a fundamental role in multiple cell functions including regulation of sugar metabolism, muscle contraction, heart rate, and blood pressure. There have been multiple PKA biosensors developed based on various switch mechanisms9. As farnesylation alone is not sufficient for plasma membrane targeting, many plasma-membrane-targeted farnesylated proteins including K-Ras4b also require the presence of a cluster of positively charged residues near the CAAX motif 15. Phosphorylation of serine-181 by Protein Kinase C (PKC) leads to a disruption of K-Ras4b’s localization at the plasma membrane17. The electrostatic interaction between the positively charged residues in the protein and the negatively charged lipids in the plasma membrane is responsible for biasing the trafficking of K-Ras4b to the plasma membrane18. Phosphorylation in this region removes this bias by disrupting the favorable electrostatic interaction, a mechanism known as the farnesyl-electrostatic switch (FES). Later studies indicated that K-Ras4b uses more complicated mechanisms than a simple electrostatic switching for versatile membrane binding13.To generate a synthetic molecular switch that translates the phosphorylation by PKA into its membrane localization, we looked into the regulatory mechanism of K-Ras4b. The localization sequence of K-Ras4b is found in the C-terminus where the combination of polybasic residues and the CAAX motif  targets the protein to the plasma membrane. The CAAX motif serves as a signal for enzymatic processing  that leads to the attachment of a farnesyl group19, a PKA recognition motif within PKA substrate sequences consists of two sequential arginines21. By aligning the PKA substrate sequence in tandem with conjugation to a farnesylation sequence, we designed an amino acid sequence that functions as a PKA phosphorylation switch that shuttles between the plasma membrane and the endomembrane depending on the PKA activity.While PKC requires a cluster of positively charged residues for substrate recognition20. We flanked a single lysine with the two Kemptide sequences, and a single leucine was removed from the second Kemptide sequence to maintain a consecutive sequence of positively charged residues. We then fused a farnesylation substrate recognition sequence (TKCVIM), previously demonstrated to be sufficient for farnesyltransferase processing23. This resulted in a peptide design  was then subtracted from the intensity values at each time point (ΔF). We then plotted ΔF/F0 as a function of time  mechanism of K-Ras4B, we aimed to develop a synthetic molecular switch for PKA activity. FES can be distilled into the following components Fig. A: 1) a  a 20. WeWe next explored the parameter space of this design to determine how different variables would affect the FES-PKA’s response and localization. The balance between the number of phosphorylation sites and the number and orientation of basic residues may determine the dynamic range of the FES-PKA’s response to PKA stimulation Fig. A. To tesWe next examined if the observed translocation of FES-PKA was due to phosphorylation and not due to perturbation of PKA activity by generating mutants which disrupted phosphorylation. Mutations of both serines in the optimized FES-PKA to alanines yielded little to no response , while having both serines intact led to the most robust response Fig. A,B. Havi24, mutation of these residues to alanines disrupts the phosphorylability of the substrate. For this reason, the serines were mutated to alanines in this experiment. Cells were co-transfected with the mutated FES-PKA and a non-phosphorylable, non-mutated FES-PKA. Mutations in PBR #1 did not appear to disrupt the initial localization, while mutations in PBR #2 caused a substantial enrichment in the intracellular membranes  influx28. This is thought to occur through the binding of calmodulin, independent of phosphorylation. To test this potential effect of Ca2+, we elevated intracellular Ca2+ concentration by treating the cells with 1 μM ionomycin under a condition where the extracellular medium contained 1.8 mM Ca2+. The time-profile shows the translocation of FES-PKA (A-A), which is an unphosphorylable mutant . Both the S–S wild type and the A-A mutant, regardless of the presence of serines, responded similarly to the influx of Ca2+ . To further characterize the response to Ca2+, we used a Ca2+ chelator BAPTA while we monitored FES-PKA redistribution triggered by PKA activation. Despite the greatly suppressed Ca2+ with BAPTA, the extent and kinetics of FSK-IBMX-induced FES-PKA redistribution remained largely intact , suggesting that the observed response of FES-PKA is primarily driven by PKA activity, and the contribution of Ca2+ is marginal.Polybasic targeting sequences in farnesylated proteins including K-Ras4b can be disrupted with calcium  sensor, as well as its reversibility in sensing multiple cycles of activity changes. The fluorescence signal and the FRET signal were measured respectively in real time before and after stimulation with FSK/IBMX  and nuclear localization signal (NLS) that can be modulated by a target kinase activity. Instead, the FES-PKA uses a unique switching mechanism whereby it travels within the membrane systems, potentially allowing for a multiplex usage with other KTRs without competing for cellular translocation machinery. It is also worth noting that the size of previous KTRs ranges from 60 to 400 amino acids which consist of multiple modules such as one for kinase binding, phosphorylation, NLS and NES. In contrast, FES-PKA is concise with only 20 amino acids due to employment of multi-tasking modules. As shown in Fig. S1, however, the FES-PKA responds not only to PKA, but also to Ca2+ as well as potentially other molecules, resulting in a tradeoff in target specificity.We engineered a PKA substrate peptide whose subcellular localization switches between the plasma membrane and the endomembrane depending on the cellular PKA activity. This molecular switch, termed FES-PKA, has further utility in future studies. For example, FES-PKA fused to a fluorescent protein can be used as a kinase activity sensor as demonstrated in Fig. Another application of FES-PKA would be to use it for a molecular actuator that can achieve conditional manipulation of biochemical activity. For example, one may conjugate FES-PKA to an enzyme for post-translational modification. Upon PKA activation, such a molecule could exert the enzymatic reaction due to increased proximity to its substrate as a result of altered subcellular localization. These enzymes include kinases and phosphatases for proteins and membrane lipids, as well as guanine exchange factors for small GTPases. As these molecular actuators could mediate cross-talk between two signal transduction pathways, synthetic operations such as generating a functional output in the face of a normally uncoupled input stimulus may become possible. In conclusion, due to the concise size and modular design principle, FES-PKA represents a potential for utilization in areas of biology and engineering.2. For imaging experiments, cells were seeded at a 30–40% confluence on a #1 coverslip  placed inside 6-wells . Cells were transfected the next day with FugeneHD  at a ratio of 1:1 according to the manufacturer’s protocol, and 50 ng of DNA was added dropwise into each well. Cells were serum-starved with DMEM  without phenol red and supplemented with 2 mM L-glutamine  the morning of the following day. In the afternoon of the same day, cells were imaged by transferring the coverslip to an Attofluor cell chamber .HeLa  cells were routinely passaged and cultured in DMEM  supplemented with 10% FBS  and maintained at 37 °C in 5% CO2 . Images were acquired for 15 min or 25 min, as noted, at 1-min intervals. After 5 min, cells were treated with either 50 µM forskolin  and 100 µM IBMX  cocktail or 1 µM ionomycin , as noted. Images were acquired with a CMOS camera  on a 60 × oil objective . The microscope was controlled with MetaMorph  with motorized stage controller  and filter wheel controller . The sample was illuminated with a LED light source . For FRET experiments, images were acquired by exciting with CFP and detecting in the YFP channel. All experiments shown in a given panel were performed together.Images were acquired on an inverted microscope  with a heated chamber that maintained conditions of 37 °C and 5% COThe signal at the intracellular membranes was quantified by co-expressing in cells an endomembrane marker that consisted of a prenylation sequence with no basic residues. ImageJ  was used to track a 15 × 15 pixel (4.66 pixel = 1 μm) square region that contained the greatest average fluorescence intensity of the endomembrane marker. For fluorescence quantification, the background was subtracted, and the response of the signal was calculated by taking the ratio of signal with the average of the pre-treatment signal at the region of interest determined with the endomembrane marker. For FRET quantification, the background was subtracted, and the CFP-excited YFP emission signal was divided by the CFP-excited CFP emission signal. The reported response is this quantity normalized by the average of the pre-treatment signal for the whole cell.For colocalization analysis, the role of the two polybasic residue clusters was characterized by mutating the positively charged residues to alanines, respectively. Cells were co-transfected with the mutated peptide and an unmutated peptide, both unphosphorylable. The extent of the colocalization between the two peptides was analyzed by first calculating a 20 × 20 pixel median filtered image for each channel and respectively subtracting them from the original images. The two background-subtracted images were correlated using Pearson’s correlation. The average of these Pearson’s correlations from 30 cells is shown in Fig. Paired Student’s t-test was used to test for statistical significance in Fig. DNA constructs were cloned by inserting annealed oligonucleotides into EYFP-C1  and mCherry-C1  at the SacII and BamHI site. The forward sequences of the inserted oligonucleotides with the restriction sites are as follows:Supplementary Information 1.Supplementary Video 1.


It was found that phosphorylated truncated CALP3 with a molecular weight of 60–62 contains p-Tyr, which indicates the possible involvement of protein tyrosine phosphatase in this process.The protein phosphorylation of the membrane-bound mitochondrial proteins has become of interest from the point of view of its regulatory role of the function of the respiratory chain, opening of the mitochondrial permeability transition pore (mPTP), and initiation of apoptosis. Earlier, we noticed that upon phosphorylation of proteins in some proteins, the degree of their phosphorylation increases with the opening of mPTP. Two isoforms of myelin basic protein and cyclic nucleotide phosphodiesterase were identified in rat brain non-synaptic mitochondria and it was concluded that they are involved in mPTP regulation. In the present study, using the mass spectrometry method, the phosphorylated protein was identified as Calpain 3 in rat brain non-synaptic mitochondria. In the present study, the phosphoprotein Calpain-3 (p94) (CAPN3) was identified in the rat brain mitochondria as a phosphorylated truncated form of p60–62 kDa by two-dimensional electrophoresis and mass spectrometry. We showed that the calpain inhibitor, calpeptin, was able to suppress the Ca Phosphorylation of proteins is one of the most common and important post-translational modifications involved in the regulation of many processes in various cellular compartments, including mitochondria . The rev2+-regulated (as a second messenger) and protein kinase-dependent phosphorylation. The level of protein phosphorylation in RBM was found to be altered in the presence of threshold Ca2+ concentration, leading to opening of mPTP. The results showed a clear correlation between mPTP opening and changes in the level of protein phosphorylation in RBM ATP and in the presence of threshold Ca2+-concentrations led to an increase or a decrease in the level of phosphorylation of these proteins , initiating mPTP opening. After that, samples were taken from the chamber for phosphorylation of the mitochondrial proteins. Control samples were taken, as well, before opening of mPTP . Mitochondrial samples  were phosphorylated by [γ-32P]ATP. After exposure with Kodak film the level of phosphorylation of the proteins was evaluated. The typical distribution of mitochondrial phosphoproteins in control mitochondria and when mPTP is open is shown in Previously, we found several membrane-bound proteins with molecular weight of 60–62 kDa, 46–48 kDa, 17–21 kDa, and 3.5 kDa in RBM, which were phosphorylated by ATP , were separated on SDS-PAGE (12.5%) in the Laemmle system . One of them was exposed to X-ray film (Kodak X-Omat AR-5 X-ray film) and after visualization, several phosphorylated protein bands including, 60–62 kDa protein , were revealed on autoradiogram  and anti-phospho-tyrosine (p-Tyr) antibodies.The presence numerous bands on the membrane was discovered, recognized by both antibodies. The phosphor-serine and phosphor-tyrosine residues were detected at the same places on the membrane at level of 60–62 kDa, where CAPN3 domain II was marked. It indicates possible involvement of tyrosine and serine protein kinases in phosphorylation of CAPN3 domain II in RBM. In addition, the levels of p-Ser as well as p-Tyr were found to be higher in RBM with mPTP opened.2+], assuming the participation of CAPN3 in mPTP functioning, we assayed the effects of Calpain inhibitors such as calpeptin and ALLN (cysteine proteinase inhibitor) on induction of mPTP in RBM. Parameters of mPTP opening were determined by simultaneous registration with selective electrodes of O2 consumption, the change of membrane potential and Ca2+ fluxes under threshold [Ca2+] loading . The threshold [Ca2+] was determined experimentally for each isolated sample of RBM. After the first Ca2+ addition the oxygen consumption rate was returned to the resting state and added Ca2+ was almost fully accumulated. Ca2+ efflux and activation of oxygen consumption that indicated initiation of mPTP opening were observed.Since p60–62  was revealed in the presence of the threshold ATP and unlabeled Mg2+-ATP to achieve final concentrations of 2 mM Mg2+, 400 μM ATP and of 5–7 μCi of [γ-32P]ATP. Samples were incubated for 3 min in the presence of oligomycin. The reaction was stopped by addition of solubilizing Laemmle sample buffer and heated in boiling water bath for 3 min at 95 °C.Aliquots of RBM (50–100 μL) were taken from the electrode chamber (1 mL volume) for protein phosphorylation with a mixture of [γ-Polyacrylamide gel electrophoresis under denaturing conditions (SDS-PAGE) was carried out using 4% concentrating and 15% separating polyacrylamide gel [For statistical analysis, relative levels of protein phosphorylation were expressed as mean ±SD from at least 3 to 4 independent experiments with samples being run in duplicate. For statistical analysis, we used one-way ANOVA and a proper post-hoc analysis (Student–Newman–Keuls) .


Caenorhabditis elegans. This in vivo tissue-specific DXB was examined at temperatures from 20 °C to −10 °C for a recombinant ice-binding protein from Antarctomyces psychrotrophicus (AnpIBP) connected with the cells through a transmembrane CD4 protein equipped with a glycine-serine linker. AnpIBP inhibits ice growth at subzero temperatures by binding to ice crystals. We found that the rotational motion of AnpIBP decreases at −10 °C. In contrast, the motion of the AnpIBP mutant, which has a defective ice-binding ability, did not decrease at −10 °C. The twisting and tilting motional speeds of AnpIBPs measured above 5 °C by DXT were always higher than those of the defective AnpIBP mutant. These results suggest that wild-type AnpIBP is highly mobile in solution, and it is halted at subzero temperatures through ice binding. DXB and DXT allow for exploring protein behaviour in live animals with subnano resolution precision.The dynamic properties of protein molecules are involved in the relationship between their structure and function. Time-resolved X-ray observation enables capturing the structures of biomolecules with picometre-scale precision. However, this technique has yet to be implemented in living animals. Here, we examined diffracted X-ray blinking (DXB) and diffracted X-ray tracking (DXT) to observe the dynamics of a protein located on intestinal cells in adult  •in vivo DXB and DXT techniques.Dynamic motions of ice-binding protein (AnpIBP) were analysed in live animals using •The rotational motion of AnpIBP decreases at −10 °C, whereas that of the defective AnpIBP mutant did not decrease at −10 °C.•The twisting and tilting motions of AnpIBPs measured above 5 °C were always higher than those of the defective AnpIBP mutant. Time-resolved X-ray diffraction techniques have the unique potential to measure the dynamic motion of biomolecules at the picometre length scale. Diffracted X-ray tracking (DXT) uses white- or pink-beam X-rays to track X-ray diffraction spots from protein-labelled gold nanocrystals. DXT can detect tilting and twisting motions of protein molecules with angular velocities in the θ and χ directions with milli-radian accuracy , CMS22 lin-15 (n765ts); Ex[elt-2p:AnpIBP:CD4], CMS23 lin-15 (n765ts); Ex[elt-2p:AnpIBP T156Y:CD4].To generate transgenic animals, plasmid DNA was injected into n method . We usedE. coli OP50 at room temperature (∼24 °C).Worms were cultivated on standard nematode growth medium (NGM) plates seeded with 2.3−4 Pa vacuum. The size of the gold nanocrystals is approximately 60–80 nm. The nanocrystals were mixed with phosphate-buffered saline (PBS) and sonicated at approximately 0 °C for 1 h. Adult worms were incubated in PBS with gold nanocrystals for 4 h at room temperature. Transmembrane CD4 is located on intestinal cells. The worms swallow gold nanocrystals during 4 h of incubation. Their intestinal cells contact the gold nanocrystals, and then the gold nanocrystals bind to a thiol site on CD4. After incubation with the gold, the worms were washed with PBS and placed in the sample holder.Gold nanocrystals were fabricated via epitaxial growth on cleaved KCl (100) under a 102.4DXB was performed using a laboratory X-ray source . Time-resolved diffraction images were recorded using a 2D photon-counting detector . The sample temperature was controlled by a temperature-controlled microscope stage .The time-resolved diffraction intensity in Au(111) was analysed at each pixel by the autocorrelation function (ACF),than 1.0 . These cR of a single colloidal sphere with radius r is defined by the Stokes–Einstein–Debye relationship [R, as expressed in the following equation:The rotational diffusion coefficient Dtionship . The ACFθ was calculated by the angular width of the 2θ diagram.The rotational displacement φ2.511 photons/s) were used for the living-worm DXT. Images were captured at a rate of 10 msec/frame. Diffraction spots were tracked by TrackPy , and the trajectories were analysed using custom software written within IGOR Pro . The sample temperature was controlled by a custom-made heating and cooling stage.DXT was performed using the SPring-8 BL40XU beamline. The beam size was adjusted to 50 μm in diameter by inserting a pinhole aperture upstream of the sample, and time-resolved diffraction images from the gold nanocrystals were recorded by an X-ray image intensifier  and a CMOS camera . For each sample, diffractions at several positions  were manually recorded. The distance between the sample and the detector was set to 50 mm. X-rays with an energy bandwidth of 0.1 (15.8 keV in peak energy and photon flux of 10Hundreds of diffraction spots from Au(111) and Au(200) in each trial were tracked and were assigned as θ and χ directional movements. Angular displacement histograms with each temperature condition were fitted by the Gaussian distribution.33.1C. elegans by using gold nanocrystals  [C. elegans. On the other hand, a defective AnpIBP mutant, which has a T156Y mutation in the B-face, did not improve freezing tolerance because this mutation induces a reduction in ice-binding ability [in vivo, has not yet been directly observed. Comparisons between the wild-type and the mutant are useful to understand its structure, dynamics and function. Low X-ray-dose laboratory-DXB can monitor the motion of AnpIBP in living worms over a long time scale.To evaluate the dynamic motion of protein molecules in living worms by our X-ray diffraction techniques, we focused on ice-binding protein from (AnpIBP) . AnpIBP (AnpIBP) . We prev2/s in the θ direction, indicating that DXB spatially detects picometre-scale motion in live animals (Here, we measured the dynamic motion of AnpIBP and the CD4 complex in living worms by DXB b. Blinki animals .3.3in vivo at each low temperature. The individual diffraction spots probably move in the θ and χ directions. However, knowledge of the orientation of AnpIBP movements is limited from the DXB experiments. DXT tracks the movement of the diffraction spots from the gold nanocrystals by using broadband X-ray and can be separately evaluated for the movements of the θ and χ directions in gold nanocrystals as tilting and twisting [in vivo. To observe the temperature-dependent motion of C. elegans AnpIBPs, a heating and cooling stage was equipped with a DXT system (The dynamic motion of AnpIBP differed from that of the AnpIBP mutant twisting ,30 (Fig.T system b. The exθ and Eχ in θ and Eχ. The Eθ and Eχ motions at 5 °C–45 °C in the AnpIBPs seemed to show partially temperature-dependent behaviours (θ and Eχ in the wild-type AnpIBP and the AnpIBP mutant is shown in Hundreds of diffraction spots were tracked and evaluated as angular velocities . For inshaviours e. The re4C. elegans. The rotational motion of transmembrane CD4 and AnpIBPs was observed with picometre precision by DXB. The rotational diffusion coefficients of the AnpIBPs were estimated at approximately 0.1 p.m.2/s in the θ direction. Interestingly, the rotational motions of the wild-type AnpIBP were significantly inhibited at −10 °C, whereas those of the mutant AnpIBP did not decrease (In this study, we applied the DXB and DXT techniques to observe individual membrane proteins in living decrease d. The widecrease f. On theIn this paper, the twisting and tilting motions of AnpIBPs were assigned precisions of approximately 0.4–1.0 mrad and 0.9–2.6 mrad, respectively. We found that the twisting and tilting motional speeds of AnpIBPs measured above 5 °C were consistently higher than those of the defective AnpIBP mutant. Several computational simulations appear to show that IBPs rotate in the χ direction and then bind to ice crystals ,17. Thesin vivo represent tilting and twisting, respectively. The gold nanocrystal markers attached to CD4 on the intestinal cell membrane might be oriented in various directions. Although several improvements will be required in the labelling and measurement methods, we believe that DXT can be used to evaluate the relationship between tilting-twisting motions and ice-binding ability.DXT with a broadband X-ray can obtain the tilting and twisting motions. These motions are related to the ice-binding ability of IBPs. However, DXT measurements below 0 °C were not performed because the generated ice crystals were detected as high-intensity diffraction spots. DXT will provide insight into the IBP-ice interaction at subzero temperatures. The tilting motion probably decreases if AnpIBP-ice complexes are generated at subzero temperatures. The twisting motion also decreases when the protein is bound to ice. Although the twisting motion might have a key role in seeking ice crystals to bind to, it was not clear whether the θ and χ movements of AnpIBPs Choristoneura fumiferana [Tenebrio molitor [in vivo, the behaviour of IBP is very interesting due to its ice-binding ability. Our paper is the first report to observe the dynamic behaviours of IBPs in vivo. A strategy that combines DXB/DXT data and dynamical simulations may be extended to understand IBP dynamics involved in the relationship between structure and function.Computational simulations of IBPs have been performed to understand IBP-ice interactions. Generally, IBP simulations have been performed by assuming an equilibrium state at the ice-water interface. Thus, knowledge regarding how IBPs freely interacts with ice crystals in an actively growing state is limited. Recently, Kuiper et al. reported detailed insight into molecular processes during ice crystal inhibition and modification. When IBP is stably bound to the ice-water interface, the melting temperature of the ice decreases. Thereby, the ice-crystal growth surrounding IBP also dramatically decreases. The molecular dynamics simulations suggest that the motion of the IBP mutant increases at subzero temperatures. The IBP mutant is unable to bind to the ice and might diffuse ahead of the growing ice front. These simulations were performed by using IBPs from the spruce budworm miferana  and from molitor . In a crC. elegans. The ice shape can be analysed from the 2θ diagram, and their size can also be calculated by the Scherrer equation [in vivo are useful to establish optimal cooling and warming methods for cryopreservation in animals.Interestingly, diffractions of ice crystals were also observed under frozen conditions of equation . In addiequation . We beliin vivo techniques described here to observe molecular motion in live animals. The deployment of our metrology techniques has now been expanded from protein and cell to a live animal. The application of DXB and DXT will shed light on the molecular basis of complex biological phenomena in biochemistry, biophysics, pharmacology, pathology, and neuroscience with atomic-scale precision.Finally, we developed the DXB and DXB M.K. and Y.C.S. designed the experiments. M.K., Y.D., Y.S., M.D., K.A., H.S. and K. M. performed the experiments. M.K., Y.D., Y.Y., T.A., and R.O. analysed the data. M.K., S.T. and Y.C.S. wrote the manuscript. All authors discussed the results and contributed to the final manuscript.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.