Here we present the first crystal structure of a HemQ (homopentameric coproheme‐HemQ from Listeria monocytogenes) at 1.69 Å resolution and the conversion of coproheme to heme b followed by UV‐vis and resonance Raman spectroscopy as well as mass spectrometry. The ferric five‐coordinated coproheme iron of HemQ is weakly bound by a neutral proximal histidine H174. In the crystal structure of the resting state, the distal Q187 (conserved in Firmicutes HemQ) is H‐bonded with propionate p2 and the hydrophobic distal cavity lacks solvent water molecules. Two H2O2 molecules are shown to be necessary for decarboxylation of the propionates p2 and p4, thereby forming the corresponding vinyl groups of heme b. The overall reaction is relatively slow (kcat/KM = 1.8 × 102m−1·s−1 at pH 7.0) and occurs in a stepwise manner with a three‐propionate intermediate. We present the noncovalent interactions between coproheme and the protein and propose a two‐step reaction mechanism. Furthermore, the structure of coproheme‐HemQ is compared to that of the phylogenetically related heme b‐containing chlorite dismutases.Heme biosynthesis in Gram‐positive bacteria follows a recently described coproporphyrin‐dependent pathway with HemQ catalyzing the decarboxylation of coproheme to heme 5LOQ.Structural data are available in the PDB under the accession number  Additionally, by UV‐vis and electronic circular dichroism (ECD) spectroscopy as well as mass spectrometry, we demonstrate a clear two‐step kinetics of the conversion of coproheme to heme b as well as a H2O2 to coproheme ratio of 2 : 1. The presence of excess of H2O2 leads to the irreversible formation of heme‐protein linkages and heme bleaching. The data will be discussed with regard to the proposed physiological role of HemQ in heme biosynthesis of Gram‐positive bacteria and possible reaction mechanism(s). In addition, they are compared to the phylogenetically related chlorite dismutases (Clds) and dye‐decolorizing peroxidases (DyPs) Herein we report the first coproheme‐bound HemQ structure at 1.69 Å resolution, which gives valuable information about the interaction of the substrate and redox‐cofactor coproheme with the active site, including coproheme coordination and noncovalent interactions of the four propionates with the protein matrix. Comparison between apo‐LmHemQ and coproheme‐LmHemQ structures (HemQ from L. monocytogenes (LmHemQ) as described previously −1) was crystallized in 0.1 m bicine pH 9.0, 10% w/v PEG6000, and diffracted to a resolution of 1.69 Å. Crystals were pale red.In this work, we heterologously expressed and purified apo‐HemQ from 11, with unit cell dimensions of 77.69 Å × 129.37 Å × 77.91 Å. The final model (PDB code: 5LOQ) consists of 9801 protein atoms, 713 water molecules, has good stereochemistry, and R‐factors  crystallizes in the same oligomeric state and space group with similar unit cell dimensions  with coproheme iron distances between 2.4 and 3.0 Å. Comparison with the structures of the phylogenetically related wild‐type and mutant chlorite dismutases (Clds) shows that the distances between the 74 with cThe amino acids of the distal side of the coproheme‐LmHemQ complex are Q187 , I189, and V202; distances to the heme iron are 5.2 Å (Q187), 4.3 Å (I189), and 6.4 Å (V202). Q187 is oriented toward the protein surface, pointing away from the coproheme iron in coproheme‐LmHemQ  with the protein moiety is shown in Fig. The interaction of p6 and p7  As described above, in the structure of coproheme‐LmHemQ, only in chain A and chain D, a flexible loop between L114 and Y125 could be completely built, because of reliable electron densities due to crystal packing contacts. In the apo‐structure of LmHemQ (PDB code: Staphylococcus aureus (SaHemQ) b‐LmHemQ (produced by addition of hydrogen peroxide to coproheme‐HemQ) shows the Soret maximum at 410 nm and a weak CT1 at 640 nm, typical of a six‐coordinated low‐spin (6cLS) heme with a minor HS component  −1) are evident only by inspection of the difference spectra between heme b‐LmHemQ and coproheme‐LmHemQ. By contrast, the formation of the vinyl substituents can be clearly observed. The spectra in polarized light allowed us to assign the ν(C=C) stretching modes (polarized) at 1621 and 1632 cm−1  vinyl modes are observed as a single band at 418 cm−1  and 5cHS (Soret at 437 nm) species , consistent with the significantly increased amount of LS species. For both proteins, the ν(Fe‐Im) stretching mode is observed at 214 cm−1  is weakly bonded to the heme iron in agreement with the crystal structure and the interatomic distances (2.4–3.0 Å). This finding clearly demonstrates that conversion of p2 and p4 to the respective vinyl groups has no impact on the proximal heme coordination and architecture.The UV‐vis spectrum of ferrous coproheme‐LmHemQ is characteristic of a predominant 5cHS species in the absence of vinyl conjugation (Soret at 423 nm and maximum at 548 nm), whereas ferrous heme b‐LmHemQ. During this reaction, the original spectrum of coproheme‐LmHemQ (Soret maximum: 395 nm) converts to a spectrum with the characteristics of heme b‐HemQ (Soret maximum: 410 nm) with an isosbestic point at 400 nm , the reaction is completed after 140 s  were obtained by monitoring the absorbance increase at 410 nm. The observed kinetic behavior is shown in Fig. KM value for H2O2 was calculated to be 37.1 μm  resulting in a kcat/KM value of approximately 1.8 × 102m−1·s−1   from these studies were plotted against the stoichiometric ratio of H2O2 over LmHemQ. Fitting with a sigmoidal function reveals midpoints of conversion at [H2O2]/LmHemQ ratios between 0.6854 and 0.7761. The reaction is complete after reaching a twofold stoichiometric excess of H2O2 , monovinyl, monopropionate deuteroheme (662.18 Da), and heme b (616.18 Da) are presented in Fig. m H2O2 (ratio of 0.66), coproheme, monovinyl, monopropionate deuteroheme, and heme b are present in fairly equal amounts , whereas after addition of 36 μm H2O2 (ratio of 2.0), heme b is the most abundant species detected (~ 85%) , the knowledge regarding structure–function relationships was limited until now. The catalytic efficiency of the proposed reaction is rather low but this is reasonable in a biological context. The apparent kcat/KM value for HemQ from L. monocytogenes for H2O2 was determined to be 1.8 × 102m−1·s−1, very similar to that reported for HemQ from S. aureus (SaHemQ) In vivo in the Gram‐positive bacterial cell, H2O2 most likely is not present in (high) micromolar concentrations, but is continuously provided by HemY and consumed by coproheme‐HemQ in vivo conditions. This assumption is also supported by the fact that coproheme‐HemQ is very susceptible to irreversible inhibition by modification of the substrate/cofactor and the protein in the presence of a stoichiometric excess of H2O2.It has been recently discovered that HemQ 2O2‐mediated decarboxylation reaction was studied under subequimolar concentrations of H2O2 to minimize side reactions. In this way, it was possible to demonstrate that complete conversion of 1 mol coproheme to 1 mol heme b requires 2 mol of hydrogen peroxide. The reaction occurs in a stepwise manner with the formation of a three‐propionate intermediate ,  or with an amino acid radical (aa•+),  state and converts the propionyl to the vinyl substituent thereby releasing carbon dioxide. To affect the decarboxylation of p2 and p4, two reaction cycles and thus two H2O2 molecules are necessary. The detection of the three‐propionate intermediate, as well as the spectral changes observed during turnover by ECD spectroscopy  suggest that these two decarboxylation steps occur consecutively  shows no electron densities of potential solvent molecules, which is also reflected by temperature‐dependent investigations of the standard reduction potential of the Fe(III)/Fe(II) couple of coproheme‐SaHemQ S°′rc,solv value, which indicates a reduction‐induced increase in solvent ordering, which is typical for a system with a buried metal site and limited solvent accessibility to the distal heme cavity Both the UV‐vis and RR spectra as well as the standard reduction potential of the Fe(III)/Fe(II) couple of coproheme‐LmHemQ of −205 mV 2O2 oxidizes coproheme‐HemQ for production of a redox intermediate that initiates the oxidative decarboxylation reaction is unknown. In contrast to typical heme peroxidases of the peroxidase‐catalase and peroxidase‐cyclooxygenase superfamilies 2O2 and Compound I formation, in coproheme‐HemQ comparable catalytic residues are absent. The distal amino acids within 6 Å distance from the heme iron are Q187, I189, and V202, respectively. Glutamine 187, which aligns with the catalytic arginine in Clds, is fully conserved in HemQs from Firmicutes but is exchanged by alanine in (putative) HemQs from Actinobacteria. In the crystal structure of coproheme‐LmHemQ, Q187 is in the ‘out’ conformation (distance between Fe and amide nitrogen: 5.2 Å) making a hydrogen bond with the carboxyl group of p2. According to MD simulations b‐LmHemQ, Q187 the ‘in’ conformation is possible (due to the absence of p2) which might contribute to the very pronounced LS character of heme b‐LmHemQ compared to coproheme‐LmHemQ.How H2O2, the absence of distal water molecules, and thus of an obvious pathway for proton delivery or elimination, suggest that formation of the initial reaction product  must be extremely slow compared to heme peroxidases or heme catalases and could be the rate‐limiting step of the enzyme turnover. For the subsequent redox reaction, the cleavage of the peroxide bond either follows a heterolytic mechanism [Fe(III)‐O‐O‐H → Fe(IV) = O Por•+ + H2O] or a homolytic cleavage. However, in HemQ, the absence of (a) a distal His‐Arg pair, which supports heterolytic cleavage by acting as proton donating and polarizing catalytic amino acids, and (b) of an anionic proximal histidine, which also promotes heterolytic bond cleavage, suggest a homolytic mechanism [Fe(III)‐O‐O‐H → Fe(IV) = O + •OH]. The hydroxyl radical then could attack either p2 or p4 to form water and the corresponding propionyl radical (p˙). Celis et al. 2O, and p• in a concerted manner without releasing the •OH radical.The hydrophobic nature of the distal heme cavity, the absence of a catalytic base for deprotonation of Hb starts with the oxidation of the resting state by H2O2. Compound I*,  to heme b [Fe(III) Por‐vinyl], two redox cycles have to be passed. In the classic heme biosynthesis pathway of diderm (Gram‐negative) bacteria, HemN decarboxylates coproporphyrinogen III (no iron inocorporated) to protoporphyrinogen IX. It utilizes a [4Fe‐4S] cluster cofactor and SAM‐dependent mechanism to cleave off propionates at positions 2 and 4 2O2 (after complete conversion of p2 and p4 to the respective vinyl substituents) formation of a crosslink between the cofactor  and the protein occurs  Compound I‐like intermediate in this reaction is also supported by the fact that in the presence of an excess of Hurs Fig. E,F. FormL. monocytogenes now allows to critically investigate the environment of these substituents. Interestingly, both p6 and p7 form H‐bonds with the positively charged amino acids K151 and R133  of coproheme are decarboxylated. The first crystal structure of coproheme‐HemQ of b. For the relatively slow and stepwise conversion of coproheme to heme b, two H2O2 molecules are necessary. The heme cavity architecture together with biochemical/physical data suggest homolytic cleavage of hydrogen peroxide and a radical mechanism that includes two one‐electron oxidations of the propionate substituent (p2 and p4). As a consequence of interaction with basic amino acids, the propionates p6 and p7 seem to be protected from oxidation.In conclusion, HemQ is a homopentameric enzyme that uses coproheme as substrate and redox‐cofactor for the conversion of coproheme to heme Escherichia coli Tuner (DE3) cells (Merck/Novagen) and purified via a StrepTrap HP 5 mL column  as described in previously m phosphate buffer, pH 7.0, predissolved in 0.5 m NaOH) to apo‐LmHemQ dissolved in 50 mm phosphate buffer, pH 7.0. In order to determine the extinction coefficient of coproheme, various concentrations of coproheme solutions in 50 mm phosphate buffer, pH 7.0, were prepared and UV‐vis absorption spectra were recorded with an Agilent 8453 diode array spectrophotometer . The absorbance at 390 nm was plotted against the coproheme concentrations and from the slope, the extinction coefficient for coproheme at 390 nm was obtained (128 800 m−1·cm−1).LmHemQ was subcloned into a modified version of the pET21(+) expression vector with an N‐terminal StrepII‐tag, cleavable TEV protease, expressed in b by LmHemQ was followed spectroscopically at 410 nm (ε410 = 76 600 m−1·cm−1) m coproheme‐LmHemQ in 50 mm phosphate buffer, pH 7.0, was used and the reactions were started by the addition of 10–100 μm H2O2 . The H2O2 concentration was checked spectrophotometrically prior to each measurement (ε240 = 39.4 m−1·cm−1) b (μm s−1) were plotted against H2O2 concentrations, and KM and vmax were calculated using a Hanes plot [extraction of catalytic parameters from the slope (1/vmax) and the intercept (KM/vmax)].The conversion of coproheme to heme m H2O2 was added to 5 μm coproheme‐LmHemQ, in 50 mm phosphate buffer, pH 7.0.The activity of LmHemQ was followed spectroscopically between 250 and 700 nm using the cyclic measurement mode . In this experiment, 5–50 μ−1 and allowed simultaneous monitoring of UV‐vis electronic absorption and circular dichroism. Coproheme‐LmHemQ was analyzed in the near UV and visible region . Temperature was controlled by a Peltier element and kept at 25 °C. All measurements were performed in 50 mm phosphate buffer, pH 7.0. During titrations, subequimolar aliquots of H2O2 were added to the enzyme solution under constant stirring.Electronic circular dichroism spectroscopy was performed using Chirascan . The instrument was flushed with a nitrogen flow of 5 L·min2O2 to coproheme, titrations were performed, where small (subequimolar) aliquots of H2O2 were added to coproheme‐LmHemQ. In a typical experiment, H2O2 was added in 2 μm aliquots to 18 μm coproheme‐LmHemQ. To ensure complete reaction of the H2O2, an interval of at least 15 min was set between each peroxide addition. The titrations were performed in a stirred cuvette (1 mL sample volume) at room temperature and monitored by UV‐vis absorption spectroscopy between 250 and 700 nm, using a scanning photometer . About 20 μL of the sample was taken after each addition of H2O2 and analyzed by mass spectrometry.In order to determine the stoichiometry of Hm/z and the instrument was tuned to detect both the rather small, free heme derivatives and intact proteins in a single run. Instrument calibration was performed using ESI calibration mixture . For separation of the analytes, a Thermo ProSwift™ RP‐4H Analytical separation column (250 × 0.2 mm) was used. A gradient from 99% solvent A and 1% solvent B  to 65% B in 11 min was applied, followed by a 2‐min gradient from 65% B to 95% B, at a flow rate of 8 μL min−1 and at 75 °C. A blank run (5 μL H2O) was performed after each sample to minimize carryover effects.For mass spectrometric analysis, 5 μL of each sample was analyzed using a Dionex Ultimate 3000 system directly linked to a QTOF mass spectrometer  equipped with the standard ESI source of the positive ion mode. MS scans were recorded within a range from 300 to 3750 −1) to crystallant were dispensed. Commercially available crystallization screens were used for initial screening. Crystallization plates were stored at 22 °C. Successful trials were obtained using the JCSG‐plus™ from Molecular Dimensions and SaltRx Screen from Hampton Research. Diffracting crystals grew in condition E10 of the JCSG‐plus™ screen .Crystallization experiments were performed using SWISSCI MRC three‐well crystallization plates  adopting the vapor diffusion method. Crystallization drops were set using a Phoenix HT crystallization robot . The reservoir was filled with 40 μL crystallant solution. In the sample wells, ratios of 150 : 200 nL, 200 : 200 nL, and 250 : 200 nL protein .The dataset was processed with m phosphate buffer, pH 7.0, predissolved in 0.5 m NaOH) to apo‐LmHemQ dissolved in 50 mm phosphate buffer, pH 7.0. Ferric heme b‐LmHemQ samples were prepared by adding small aliquots of a concentrated solution of H2O2 in 50 mm phosphate buffer, pH 7.0 to coproheme‐LmHemQ. Ferrous samples were prepared by addition of a freshly prepared sodium dithionite (10 mg·mL−1) solution to the ferric forms previously degassed with nitrogen.Ferric coproheme‐LmHemQ samples were prepared by adding free coproheme (in 50 mm for both coproheme‐LmHemQ and heme b‐LmHemQ. The coproheme‐LmHemQ and heme b‐LmHemQ concentrations were determined using an extinction coefficient (ε) of 68 000 m−1·cm−1 at 395 nm and 76 600 m−1·cm−1 at 410 nm, respectively Sample concentrations were in the range 10–20 μ−1 scan rate) or a 1 cm cuvette (600 nm·min−1 scan rate) at 25 °C by means of a Cary 60 spectrophotometer (Agilent Technologies) with a resolution of 1.5 nm. Absorption spectra were measured both prior and after RR measurements to ensure that no degradation occurred under the experimental conditions used.Electronic absorption measurements were recorded using a 5 mm NMR tube  and with the 441.6 nm line of a He–Cd laser (Kimmon IK4121R‐G). Backscattered light from a slowly rotating NMR tube was collected and focused into a triple spectrometer  working in the subtractive mode, equipped with a liquid nitrogen‐cooled CCD detector. A spectral resolution of 1 cm−1 was calculated theoretically on the basis of the optical properties of the spectrometer for the 3600 grating. The RR spectra were calibrated with indene, n‐pentane, and carbon tetrachloride as standards to an accuracy of 1 cm−1 for intense isolated bands. All RR measurements were repeated several times (about 20 different samples) under the same conditions to ensure reproducibility. No changes have been observed within 30 min of irradiation with 5 mW (ferric) and 10 mW (ferrous) for laser excitation in the Soret band. To improve the signal‐to‐noise ratio, a number of spectra were accumulated and summed only if no spectral differences were noted  spectra were obtained at 25 °C using a 5 mm NMR tube by excitation with the 406.7 nm line of a KrSH, DP, IS, GM performed crystallization experiments. DP, GM refined the structure. SH, IS performed and analyzed activity assays. DM performed mass spectrometry analysis. LM, GS performed and analyzed resonance Raman spectroscopy experiments. The study was designed by SH, GS, PGF, KDC, CO. The paper was written by SH, GM, GS, PGF, KDC, CO. All authors reviewed the results and approved the final version of the manuscript.The authors declare no competing financial interests.


Small angle X-ray scattering (SAXS) and circular dichroism (CD) studies revealed that temperature in the range of 30–40 °C is capable of opening the G1 domain alone, as remaining domains are held together by the Ca2+-sensitive C-tail latch without any loss in the secondary structural content. Full opening of all domains of tail-less gelsolin, and retention of closed shape for G2–G6 gelsolin merely by heating, further substantiated our findings. The Ca2+/pH independent activity of gelsolin near physiological temperature brought out a query: whether gelsolin is always active, and if not, what might deactivate it? Earlier, PIP2 has been reported to render gelsolin inactive with no structural insight. Reduction in shape parameters and modeling revealed that PIP2 reverses the temperature induced extension of g1-g2 linker leading to a compact shape seen for Ca2+-free gelsolin. Similar results for partially activated gelsolin (by low pH or Ca2+ ions below 0.1 μM) imply that inside cells, depolymerization, capping, and nucleation of F-actin by gelsolin is regulated by the culmination of local Ca2+ ion concentration, pH, temperature and PIP2 levels.This is the first report describing temperature based initiation of gelsolin’s F-actin depolymerization activity, even in absence of free Ca Gelsolin is one of the main members of the gelsolin family of proteins capable of depolymerizing F-actin by achieving active dissociation of actin units in assembly and keeping the dissociated actin units capped. Additionally, gelsolin can retard growth rate of F-actin filaments by binding to the growing end. In a seemingly contrasting manner, gelsolin can bind two monomeric or G-actin molecules, and can induce polymerization or nucleation of F-actin. This makes gelsolin as an important regulator of actin assembly inside cells. The plasma form of gelsolin is the fourth most abundant protein in plasma where in presence of 1 mM free Ca2+, plasma gelsolin performs the function of rapidly depolymerizing F-actin released upon cell death or injury, and keeps it from re-polymerizing. Latter ability has been attributed to potential role of gelsolin in different biomedical problems5. Thus, decoding the shape-function relationship of this varied function multi-domain protein has remained exciting to structure biologists. Crystallographic studies, radiolytic foot-printing and SAXS data analysis based models support that in absence of Ca2+ ions, the six homologous domains of this protein are packed tightly in a compact shape, and availability of Ca2+ ions induce systematic opening of the domains away from each other to expose actin binding sites4. Taking a cue from an earlier work which concluded that low pH can override the need for Ca2+ ions, our SAXS experiments revealed that buffer pH~5 can induce the first i.e. G1 domain to open up from other five domains, just enough to allow the actin binding site between the G1 and G2 domain to be available3. Additionally, scattering shape reconstruction of the full length gelsolin and its C-tail truncated version in low pH and/or in presence of Ca2+ ions clearly established that the C-tail latch which held together the G2 and G6 domains was sensitive only to Ca2+ ions and low pH could not open or affect the latch. In the same study, it was shown that addition of substantially less amount of Ca2+ ions to pH 5 activated gelsolin could induce complete opening of this six-domain protein analogous to that seen by 1 mM free Ca2+ ions at pH 8, representing plasma conditions which re-confirmed the Ca2+-specificity of the C-tail latch of gelsolin3. The available biochemical and structural information summarizes that the compactly packed structure/shape represents inactive gelsolin, low pH can open G1 domain away from other domains which makes the protein partially active, and free Ca2+ ions can lead to a completely open structure/shape which can perform all stages of actin assembly regulation.Shape-function studies on the six domain actin-assembly regulating protein, gelsolin has brought forth interesting findings, particularly how the compactly packed domains open up completely upon Ca°C, safely presuming that primary shape-function properties of gelsolin are regulated by only Ca2+ ions or low pH. Additionally, most of the crystal structures of gelsolin and its truncated form(s) +/− actin have been grown either at low pH or in temperature 4–24 °C (PDB ID/Temperature (°C): 1D0N/18, 1P8X/4, 1NPH/20, 1P8Z/20, 1RGI/4, 2FF3/20, 2FH1/4, 3FFK/24, 3FFN/24). Even our SAXS data collection of gelsolin −/+ Ca2+ and/or low pH were done at 10 °C5. In literature, we found only one study which experimentally compared the effect of temperature on functionality of gelsolin, i.e. how much Ca2+ ions are required by gelsolin to exhibit F-actin depolymerization activity6. These authors reported that at 37 °C, Ca2+-gelsolin depolymerization of pyrene labelled F-actin was detectable at 0.5 µM Ca2+ which reached half maximal at 2.2 µM Ca2+ and kept increasing till 0.1 mM Ca2+. In comparison, authors reported that at 24 °C depolymerization activity of gelsolin could be observed only at 10 µM Ca2+ which reached half-maximal 19 µM Ca2+ suggesting need for higher Ca2+ levels at lower temperature. Importantly, their results observed at 24 °C correlated well with previous reports done under similar conditions. This ten-fold difference in Ca2+ requirement at 24 vs. 37 °C clearly indicated that there is a role of increase in temperature in stabilizing the F-actin binding and depolymerizing competent conformations of gelsolin which overrides/complements the Ca2+-induced effects, though the authors mainly connected their findings to the role of Ca2+-sensitive C-tail region of gelsolin in enabling functional shape of full-length gelsolin and its variants.Interestingly, almost all the biophysical studies leading to above conclusions were done at temperatures below 37 7. However, this increase in activity was again attributed to Ca2+ ion sensitive C-tail latch, as the dynamics of tail-less gelsolin matched with adseverin . In current work, while experimentally evaluating influence of temperature on F-actin depolymerization of gelsolin, we found that this protein can depolymerize F-actin when heated to temperatures close to 35 °C even in absence of Ca2+ ions or low pH albeit lesser than Ca2+-induced effects but comparable to influence of low pH. Experiments were repeated to confirm the observations followed by shape analysis using SAXS experiments which brought forward that the essential and minimal step to be depolymerization competent i.e. opening of G1 domain of gelsolin can be achieved by increase in temperature.Interestingly, a comparative study done for gelsolin and adseverin reported that with an increase of mere 10 °C in temperature the actin depolymerisation activity of gelsolin increased by 8 folds2+ ions or low pH can enable gelsolin to depolymerize labelled F-actin which can be recorded as a decrement in pyrene fluorescence8. Yet most of the previous experiments, in presence or absence of Ca2+ ions and pH close to 7.5 or at low pH in absence of Ca2+ ions were done at temperatures close to or below 25 °C, except one study where the depolymerizing activity of Ca2+-gelsolin was also compared at 37 °C6. To test dependence of F-actin depolymerization activity of gelsolin on temperature, heated samples of gelsolin, in buffers having 1 mM free Ca2+ (pH 8)  and pH 5 (middle) and pH 8 (bottom), were added to pyrene-labelled F-actin. In the control assays, only equivalent amounts of buffer were added, and all datasets were normalized to these read-outs from F-actin alone. Results showed that Ca2+-gelsolin heated up to 40 °C retained F-actin depolymerizing activity, but exposure to higher temperatures gradually reduced efficacy of Ca2+-gelsolin with almost complete loss by 60 °C . To the best of our knowledge, these experiments provided first direct indications that temperature alone can somehow allow gelsolin to achieve a shape which can depolymerize F-actin.To our sheer surprise, increasing the temperature of gelsolin in absence of Ca°C before associating into higher order aggregates as seen in the SAXS profiles collected at 60, 70 and 80 °C  is directly proportional to square of the mass of the scattering species, and knowing that protein concentration remained comparable (at least before onset of higher order aggregation), we used I0 values estimated from Guinier approximations to estimate mass of the predominant scattering species in solution at different temperatures  values calculated from the slope of the linear region of the Guinier approximation for the samples at different temperatures have been plotted as a function of the temperature  calculations were done to assess the conformations accessible to proteins in solution Fig. . Against2+ ions, no free Ca2+ ions but pH of 5 and no free Ca2+ ions and pH of 8 to see change in ellipticity values as a function of temperature. In all three conditions, as in SAXS experiments, protein aggregation was visible from 60 °C onwards, and it correlated with earlier reports10. Considering the data prior to initiation of aggregation i.e. below 60 °C, the slow decrement in secondary structural content had a mid-point close to 45 °C for all three conditions  curves from samples (8 mg/ml) at 10, 30 and 40 °C are shown in Fig. °C in buffer having pH 8 and 1 mM EGTA or under Ca2+-free conditions. The dummy atom model computed for 10 and 20 °C compared well with the crystal structure of Ca2+-free gelsolin (PDB ID: 3FFN one chain) (model of 20 °C is not shown)  value for the ten models are mentioned next to each SAXS data based model. NSD values close to 1 support that all individual models resemble each other and can be reliably averaged.Pairwise distance distribution function (PDDF), P(r) is the frequency distribution of interatomic vectors which best-represents the scattering profile emerging from the molecules in solution. In this work, all the PDDF calculations were done in automated manner considering monodisperse globular nature of the scattering species. Probability of finding vectors corresponding to 0 nm and a dimension equal to the longest vector in the scattering shape were considered to be zero. As described above, Iwn) Fig. . The ave°C showed that the gelsolin molecule appears to open from one side  clearly fitted in the extended out volume of the SAXS data based model  the extended away G1 domain and g1–g2 linker exposes the actin binding epitopes. These results further concluded that C-tail latch of gelsolin is specifically sensitive to Ca2+ ions, and explained the surprising F-actin depolymerizing activity of gelsolin in absence of Ca2+ ions upon heating.The model solved for gelsolin at 30 ide Fig.  which op °C Fig. . Being adel Fig. . Differe2+ ions sensitive C-tail latch, we studied temperature dependent SAXS profiles of two additional constructs of gelsolin: (1) ΔCT gelsolin – gelsolin lacking the C-terminal latch (sequence terminated at S728 followed by six Histidine tag), and (2) G2–G6 gelsolin – gelsolin lacking G1 domain (the construct started from L162 preceded by a methionine). Variable temperature SAXS data was acquired on both the proteins at concentrations close to 8 mg/ml, and variations in the RG values were plotted as a function of temperature  in buffer lacking free Ca2+ ions and having pH 8 was heated to different temperatures and then the temperature was brought back to 10 °C, while acquiring SAXS data at different temperatures. Guinier analysis provided the RG values of scattering particles which indicated that gelsolin molecules can reversibly close if they are heated up to 40 °C  did not show decrement in shape parameters upon cooling indicating irreparable or irreversible changes are initiated in the gelsolin proteins at these temperatures. Earlier, we had seen an increase in apparent molecular masses of the molecules at these temperatures which indicated some extent of association. In summary, our data indicated that gelsolin molecules open-up at temperatures close to physiological ones which somewhat correlates with enhanced activity reported earlier6.Quick query was raised if the temperature induced opening of gelsolin is a reversible phenomenon since previous characterizations of gelsolin under Ca °C Fig. . SamplesIf the above observations are true in biology then gelsolin may never be inactive as even in absence of Ca2+ions or low pH, gelsolin can achieve an actin binding shape, and thus interfere in actin assembly process. Situation can get further complicated since there would be a very likely interplay of temperature and available Ca2+ ions or low pH in surroundings of gelsolin molecules. As published before by us, in low pH buffer significantly less amount of Ca2+ ions were required to open up the full gelsolin molecule as the C-tail latch is sensitive to Ca2+ ions only3. In this work, we showed that C-tail latch remains unaffected by temperature, and cutting off C-tail latch allows temperature alone to open-up all domains of gelsolin. We propose that physiological temperature in conjunction with the low levels of Ca2+ ions (below 0.1 μM2) would be able to completely open gelsolin molecules for their actin assembly regulation function. Outside cells, in plasma, large concentration of free Ca2+ ions (~1 mM) would invariably activate gelsolin into a completely open shape11. In other words, considering the fact that gelsolin can be activated by Ca2+ ions, and/or low pH, and/or (now) physiological temperature, it implies that gelsolin would always be constitutively active both inside cells and outside, unless there is a molecule which deactivates it, fully or partially.2) was shown to deactivate gelsolin molecules though no direct structural evidence is available to date13. Gel filtration and intrinsic tryptophan fluorescence experiments provided evidence that gelsolin binds PIP2 and their affinity is increased by the presence of µM levels of free Ca2+ ions and the need for Ca2+ ions is reduced upon lowering of buffer pH14. Biochemical data have shown that PIP2 predominantly binds to the N-terminal half of gelsolin, a portion which is highly conserved amongst the gelsolin superfamily, and to date only one structure (NMR based) is available which shows how the peptide corresponding to residues 150–169 of gelsolin binds to PIP2 (PDB ID: 1SOL)18. The mechanism of action of PIP2 and gelsolin inactivation remains debatable, as one notion is that the PIP2 competes with gelsolin bound actin for binding to g1–g2 linker of gelsolin, which gets challenged since PIP2 binding epitopes are somewhat occluded in bound actin state19. Based on biochemical studies, another mechanism has been composed which suggests that PIP2 binding dislodges Ca2+, leading to release of bound actin to cytoplasm followed by closure of the g1–g2 linker which brings G1 and G2 in proximity of each other20. Furthermore, the cells with increased PIP2 have an altered non-native phenotype similar to that of gelsolin null phenotype which reflects uncontrolled association state of actin inside cells21. In summary, PIP2 is known to bind the residues in the end of the G1 domain and the g1–g2 linker which become available only when the g1–g2 linker opens up from the compact shape of the inactive gelsolin. Since temperature induced activation of gelsolin also involves extension of g1–g2 linker, the known site for PIP2 binding, we decided to explore: (1) if PIP2 can deactivate temperature-activated gelsolin and (2) whether these events can be tracked by SAXS data analysis which may explain vital role of PIP2 in regulating “apparently always” active gelsolin at least inside cells.In literature, phosphatidylinositol 4, 5-bisphosphate  and G2–G6 domains from crystal structure of Ca2+-free gelsolin , could be fitted reasonably well  up to a pCa value of 7.1 or 0.1 µM. For higher concentrations, a decrease for visible but it was insignificant after free Ca2+ concentrations surpassed 10 µM  can induce partial opening of gelsolin where G1 domain moves away from C-tail locked G2–G6 domains. We showed in this work that in absence of these two factors, increase in temperature to 35–40 °C can also open and stabilize G1 domain away from the other five locked domains analogous to that induced by low pH. Based on our previous work and complementary work from other groups, there was a query that in physiology, in absence of Ca2+ ions or low pH, gelsolin adopts an inactive resting shape? Our present shape information in conjunction with results reported earlier indicate that very likely, at physiological temperature, intracellular gelsolin exists in this partially open form and the inactive compact shape may never exist except in availability of PIP2 which binds to g1–g2 linker and induces shape changes which bring G1 domain close to G2 domain. In contrast, the high concentrations of free Ca2+ ions dictate the predominant shape of the gelsolin molecule. These scenarios are possible in plasma where free Ca2+ concentration is close to 1 mM and under injury or stress conditions leading to rise in intracellular Ca2+ concentration. Essentially, the high Ca2+ ion concentration  will lead to the fully active state of gelsolin due to additional factors of low pH or temperature which will enable rapid remodelling of F-actin assembly where the latter is essential for many cellular functions. Another scenario could be the release of Ca2+ ions from the endoplasmic reticulum (ER) membranes, which is released only when a signal is received in the form of inositol triphosphate (IP3) molecule. Interestingly, IP3 molecule is the product of PIP2 hydrolysis by Phospholipase Cγ1 (PLCγ1)24 which suggests a correlation between local PIP2 and Ca2+ levels. Gelsolin and its activation by low pH was discussed by us in view of lowering of pH during apoptosis3. We found one publication which linked apoptosis and IP3-linked mitrochondrial Ca2+ signals25 which indicates that PIP2 and Ca2+ and pH could be interconnected in regulating gelsolin’s function.Shape-function studies in this work brought forth a new physiological activator of gelsolin lue Fig. . Trace a2 is primarily located at the cell membrane as well as perinuclear spaces, however the PIP kinase mediated synthesis of PIP2 in plasma membrane is also reported27. It is also proposed that certain proteins might serve as “buffers” which bind and sequester PIP2 in the plasma, and subsequently concentrate PIP2 in lateral membrane domains26. Gelsolin has been suggested to weakly bind PIP2 which suggests that PIP2 may get released at some point. As of today, it is clear that inactive gelsolin cannot bind PIP2, but there is no data which supports a differential affinity of PIP2 with open vs. closed shape of gelsolin. Thus, the precise mechanism of release of PIP2 remains unclear. For now, we opted to use SAXS data analysis and modeling to interpret the unexpected F-actin depolymerization results as a function of temperature as this technique is not limited by the need for a diffraction quality crystal or extensive timelines for labelling and/or imaging based methods. Moreover, SAXS experiments can aid in tracking shape changes in protein molecules albeit experiments are planned properly and results are supported by orthogonal approaches as we did by developing and studying mutant proteins. Considering the new queries raised and their implications in biology, we intend (and invite other researchers) to extend these findings in cell line based experiments and understand how the shape changes affect the signalling pathways associated/dependent on gelsolin. Thus, temperature plays a key player inside cells in activating shape of gelsolin which in turn regulates multiple functions related to assembly state of actin, and flux of available PIP2 (which in turn is regulated by Phospholipase C) controls active state of gelsolin by specifically closing the g1–g2 linker.Interestingly, PIPhttp://web.expasy.org/protparam/).Different gelsolins used in this work: full-length gelsolin, gelsolin lacking C-tail latch (ΔCT), and gelsolin lacking G1 domain (G2–G6) were expressed in vectors and cells as published before refs 8. Briefly, pyrene labelled G–actin was converted to F–actin by adding 3 mM MgCl2 and 100 mM KCl in presence of gelsolin (in Actin:Gelsolin molar ratio of 500:1) followed by overnight incubation at 20 °C. To measure depolymerization capability, stock of pyrene-F–actin (9.88 µM) was diluted to 100 nM in F–buffer . For activity assays under Ca2+-free conditions, 0.2 mM CaCl2 in F–buffer was replaced with 0.2 mM EGTA. To understand the effect of temperature on the activity of gelsolin, vials containing 50 μl of solution of gelsolin (1.4 mg/ml or 17 μM) was heated at the desired temperature (in the range of 10 to 80 °C) for 30 minutes MyGeneTM Series Peltier Thermal cycler . Subsequently, the protein solution was diluted to 1.8 μg/ml (20 nM) in buffers of respective pH, kept at 25 °C and used for depolymerization assays which were done at 25 °C. It is worth noting here that same gelsolin concentration was used for observing/comparing depolymerization ability of gelsolin as a function of Ca2+ ions or pH in buffer. The fluorescence assays were performed in a 96 well flat bottom FlouroNunc plates. In each well, total reaction volume was close to 200 µL which included gelsolin and F–actin in a molar ratio of 1:10 (Gelsolin: F–actin). Importantly, F–actin was added last in the wells and readings were taken within 15–20 seconds of final addition. For measurements, excitation wavelength was kept at 365 nm and emission was recorded at 407 nm using Tecan plate reader with i-control software . The numbers of flashes were kept at 25 with an integration time of 20 µs. Each sample was assayed in duplicates, and the average of reading of both the samples was taken as final readout.The rate of decrement in fluorescence of pyrene–labelled F–actin in presence of gelsolin was used to determine the ability of gelsolin to depolymerize actin filaments as done before°C, SAXS data was collected on gelsolin solution (about 30 μl) and matched buffer from 10 to 80 °C. Line collimation was used for incident X-rays on sample filled in a quartz capillary of 1 mm diameter for 30 minutes. Scattered X-rays were recorded on a 1D CMOS Mythen detector (Dectris Switzerland). SAXS datasets for sample and buffer were processed using SAXStreat and SAXSquant softwares. Using the beam profile, the data collected on line collimation was desmeared to represent scattering arising from point collimation. Intensity of scattering, I(Q) was obtained as a function of Q, where Q was considered as 4 π sin θ/λ. All processing conditions were identical for all datasets, and I(Q) profile of the respective buffer was subtracted from the I(Q) profile of the solution to obtain SAXS profile arising from the protein molecules in solution. SAXS data profile(s) of gelsolin at different temperatures were analyzed using ATSAS 2.7.1 pipeline of programs to obtain information about scattering size and shape of the protein molecules at that temperature. Briefly, Kratky analysis, Guinier approximations and automated estimations from probability distribution of interatomic vectors were done using the suite of programs.To study the effect of varying temperature on the global shape of gelsolin, SAXS datasets were collected using SAXSpace instrument . At temperature intervals of 5 or 10 G values of the various conformations accessible to the gelsolin molecules at different temperature. This genetic algorithm based program presumes the observed shape profile from the scattering species in solution to be a weighted average of ensemble of conformations accessible to the molecule in solution, and attempts to describe the experimentally acquired SAXS profile as an ensemble of models with varying RG values. Earlier, it has been successfully applied for flexible proteins to map the RG values of the conformations accessible to proteins in solution28. We have applied this protocol to address ensemble of conformations accessible to a well-known inherently disordered protein, Calmodulin29. For this work, against the random pool of structures, optimized ensemble of 5000 conformers were generated by performing 100 independent runs of 50 conformers each. Using the SAXS profiles of the full-length gelsolin at different temperatures, and SAXS data of ΔCT gelsolin and G2–G6 gelsolin at different temperatures, EOM calculations were done to estimate RG values of the conformations in the ensemble.Using the experimental SAXS data as reference and the EOM program in the ATSAS 2.7.1 suite, calculations were done to estimate the R°C, with a temperature ramp of 3 °C/min. From the complete scans, ellipticity values recorded at 222 and 218 nm were plotted to compute melting temperature, Tm or the temperature at which half of the α-helical or β-sheet content was unfolded during the acquisition time of the data.To gain insight into the secondary structural content in gelsolin molecules and their change as a function of temperature, CD experiments were carried out using Jasco spectrophotometer 815 (Tokyo Japan). The temperature for the experiments was controlled with a Peltier type temperature control system, model PTC-424S. A quartz cell with 0.2 cm path length was used and spectra were recorded from 205 to 250 nm at intervals of 1 nm. For each sample and buffer, 5 scans were averaged and final spectral profile of gelsolin was obtained by subtracting profile of the buffer. Temperature scans were done with temperatures starting from 25 to 90 30, albeit with slight modifications. Briefly, a 10% non-denaturing gel was cast (pH 8.8), and this gel was pre-run at 10 V/cm for one hour at 4 °C before loading samples. After pre-run, the electrode buffer was discarded and replaced with fresh buffer. Samples of FPLC purified gelsolin at concentration same as that used for SAXS experiments (8 mg/ml) were individually heated from 10 to 80 °C for 30 minutes and cooled back to 25 °C in a thermal cycler. From these vials 2 μL (16 μg per lane) of protein mixed with 2x non-denaturing gel loading dye (pH 8.8) and loaded in the wells of on the native gel. Post-run, the gel was stained with 0.25% Coomasie Brilliant Blue R – 250, followed by de-staining and image was captured using AlphaImager .The continuous native PAGE was performed as described earlier31. Dummy aspartic amino acid residues equal to mass of the protein molecules were considered to model the shape of gelsolin and its variants. Ten models were generated for each dataset, and they were averaged using DAMAVER suite of programs. Essentially, for each set, the models were superimposed over a reference model by aligning inertial axes using SUPCOMB20 program from ATSAS suite, and their NSD values were calculated. Any models with NSD value more than twice the standard deviation is rejected by the averaging program. In this work, none of the models were rejected being very similar to each other in the sets, except one of the ten for ΔCT gelsolin at 35 °C. The averaged models are presented in the Figures, and were compared with crystal and modelled structures. Open source version of Pymol was used for visual analysis of results and figure generation presented in this publication32.Scattering shapes of gelsolin or versions at different temperature point were reconstructed using chain-like ensemble modeling program GASBOR in reciprocal space using SAXS I(Q) profile and results from its pair wise distribution of interatomic vectors2 was prepared . This mixture was used to acquire SAXS data collection in the temperature range of 10–45 °C to monitor if any shape changes occur to gelsolin pre-mixed with PIP2. Additionally, PIP2 was mixed with gelsolin sample (~3 mg/ml) heated to 40 and 50 °C, respectively, and the sample was cooled back while measuring SAXS data at different temperatures. The SAXS data from these samples were analyzed as described above.For this experiment, 1:1 molar mixture of gelsolin with PIPSupplementary Information


Stephania tetrandra S. Moore, was previously shown to suppress the differentiation of T helper 17 (Th17) cells and consequently ameliorate the collagen‐induced arthritis (CIA) in mice by activating the aryl hydrocarbon receptor (AhR), but its underlying mechanism is incompletely understood. Here, we investigated how tetrandrine suppressed Th17 cell differentiation through the AhR pathway. The naïve CD4+ T cells were stimulated with anti‐CD3/CD28 for 72 hrs in the presence or absence of tetrandrine under the Th17‐polarizing condition. Tetrandrine inhibited the phosphorylation of signal transducer and activator of transcription‐3 (STAT3) and boosted the phosphorylation of STAT5, while it did not alter the expression levels of phospho‐Janus kinase‐1 (p‐JAK1), p‐JAK2, p‐JAK3, and suppressor of cytokine signalling‐3 (SOCS3). The tetrandrine‐mediated inhibition of the Th17 cell differentiation could be diminished by the activator of STAT3 and the inhibitor of STAT5. Meanwhile, the effect of tetrandrine on the either STAT3 or STAT5 phosphorylation was almost completely reversed by the AhR antagonist CH223191 and the AhR knockdown. In CIA mice, tetrandrine decreased p‐STAT3 levels and increased p‐STAT5 levels, which could also be reversed by the AhR antagonist resveratrol administration. Furthermore, tetrandrine promoted the AhR binding to the STAT5, but not to the STAT3. The tetrandrine‐induced inhibition of the STAT3 phosphorylation was diminished by the inhibitor of STAT5. Taken together, tetrandrine suppressed Th17 cell differentiation by reciprocally modulating the activities of STAT3 and STAT5 in an AhR‐dependent manner.Tetrandrine, a bisbenzylisoquinoline alkaloid constituent of the root of  The male DBA/1 mice (6–8 weeks) were purchased from the Laboratory Animal Unit, Academy of the Military Medical Sciences . The mice were housed in specific pathogen‐free facilities and were maintained at 25°C on a 12 hrs/12 hrs dark cycle with food and water available optionally. All of experimental procedures were performed according to the guidelines of the National Institutes of Health Guidelines for the Care and Use of Laboratory Animals.N‐[2‐methyl‐4‐[2‐(2‐methylphenyl)diazenyl]phenyl‐1H‐pyrazole‐5‐carboxamide  was purchased from the Sigma‐Aldrich . The colivelin (an activator of STAT3) was purchased from the Abgent, Inc. . 2‐[(4‐oxo‐4H‐benzopyran‐3‐yl)methylene]hydrazide‐3‐pyridinecarboxylic acid  was purchased from the Cayman Chemical Co. . The cryptotanshinone  was purchased from the MedChem Express LLC . The mouse antibodies against JAK1, phospho‐JAK1 (p‐JAK1), JAK2, p‐JAK2, JAK3, p‐JAK3, STAT1, p‐STAT1, STAT3, p‐STAT3, STAT5, p‐STAT5, suppressor of cytokine signalling‐3 (SOCS3), AhR, and cytochrome P450 1A1 (CYP1A1) were purchased from the Santa Cruz Biotechnology, Inc. . All of other chemicals were of the highest quality available from the commercial vendors.Tetrandrine (purity: more than 98%) was purchased from the Zelang Pharmaceutical Technology Co., Ltd , which was dissolved in 0.1 N HCl and was adjusted to pH 7.2 with 1 N NaOH. It was filtrated with nitrocellulose filter  and was diluted to 10 mM stock solution. The TCDD (purity: 99.9%) was purchased from the AccuStandard, Inc. . The AhR antagonist resveratrol was also purchased from the Zelang Pharmaceutical Technology Co., Ltd . 1‐methyl‐The spleens were collected from the normal C57BL/6 mice, and the excess fat was removed. The T cells were dissociated from the spleens, and the cell suspension was washed. The gradient separation was performed to remove other cells. The cells were collected by the centrifugation and were resuspended in the RPMI‐1640 containing 10% foetal bovine serum for the investigation.+ T cells were isolated from the spleens by the paramagnetic bead enrichment according to the manufacturer's protocol. The splenocytes were incubated with anti‐CD4/CD62L‐coated magnetic beads and were isolated using MACS separation columns . The cell purity more than 98% was confirmed using the flow cytometry assay. The naïve CD4+ T cells were treated with soluble anti‐CD3 (1 μg/ml) and anti‐CD28 (1 μg/ml)  for 72 hrs and were induced to differentiate into the Th17 cells with TGF‐β (2 ng/ml) and IL‐6 (20 ng/ml) in the presence of TCDD (5 nM) and tetrandrine . To investigate whether STAT3 and STAT5 are involved in the tetrandrine‐induced inhibition of the Th17 cell differentiation, the STAT3 activator colivelin (100 pM) + T cells. Furthermore, to investigate whether AhR is involved in the effect of tetrandrine, the AhR antagonist CH223191 (3 μM) was co‐added with tetrandrine (1 μM) into the naïve CD4+ T cells.The naïve CD4+ T cells were harvested and were lysed in the buffer: 1% Nonidet P‐40, 50 mM Tris‐HCl, 250 mM NaCl, 5 mM EDTA, 10 mM Na3VO4, 0.5 mM DTT and containing the protease inhibitor phenylmethanesulfonyl fluoride (1 mM). The homogenate was centrifuged for 10 min by 12,000 g at 4°C.The pre‐treated CD4+ T cells using the reagent kit  as previously described The cytoplasmic and nuclear proteins were extracted from the pre‐treated CD4The proteins were loaded onto the 10% polyacrylamide gels and subjected to the sodium dodecyl sulphate polyacrylamide gel electrophoresis, and then transferred to the nitrocellulose membranes . The membranes were blocked in 5% (w/v) non‐fat milk at 25°C and then incubated with mouse primary antibody overnight at 4°C. Then, the HRP‐conjugated secondary antibody was added. The hybridized bands were detected using the enhanced chemiluminescence reagent kit . These results were determined by the densitometric analysis (Image‐Pro Plus) and then corrected by the GAPDH.The cells were fixed in the 4% paraformaldehyde and permeabilized in the 1% Triton X‐100 at 25°C. Then, the cells were blocked in the 10% normal goat serum and were incubated with mouse antibody against p‐STAT3 overnight at 4°C. The Rhodamine‐conjugated secondary antibody  was used to incubate the cells. The nucleus was stained with the DAPI  for the cell imaging. The fluorescence was visualized using an inverted microscope .+ T cells were washed, and the following mouse antibodies were added for intracellular staining: anti‐CD4‐PE, anti‐IL‐17A‐FITC, anti‐CD25‐FITC and anti‐Foxp3‐APC . The cells were fixed in the 4% paraformaldehyde and were permeabilized in the 1% Triton X‐100 at 25°C. The flow cytometry was performed on a FACS Canto™ II . The events were recorded and then analysed using the FlowJo7.6.1 software .The pre‐treated CD4+ T cells with TRIzol Reagent . The extracted RNAs (1 pg–500 ng) were reversely transcribed into cDNAs using a high‐capacity cDNA synthesis kit . The mRNA expression was determined by the real‐time PCR detection system  using a SYBR Green PCR kit  and the mouse pairs of oligonucleotide primers in Table −ΔΔCt algorithm.The total RNAs were extracted from the pre‐treated CD4+ T cells were inoculated in 6‐well plate at a density of 1 × 106 cells per well and then stimulated with anti‐CD3/CD28 and treated with TGF‐β and IL‐6. The siRNAs for the AhR (siAhR) and the STAT5a/b (siSTAT5), and the non‐target‐specific control siRNA  were transfected into the cells by a transfection reagent Lipofectamine™ 2000 . Thus, the cells were incubated with transfection complexes for 72 hrs in the presence or absence of tetrandrine. The total RNAs and proteins were extracted from the cells for further investigation.The naïve CD4+ T cells which were homogenized in the lysis buffer. The 1 μg of mouse antibody against AhR  was added to the extracted proteins and was rotated overnight at 4°C. Then, the 20 μl of Protein A Dynabeads  was blended in the extracted proteins and then rotated overnight at 4°C. The beads were washed with the lysis buffer, and the immunopurified proteins were eluted by boiling the beads in the 40 μl loading buffer.The proteins were extracted from the pre‐treated CD4The male DBA/1 mice were immunized by an intradermal injection at the base of the tail with 100 μg chicken type II collagen (Sigma‐Aldrich) emulsified in Freund's complete adjuvant (Sigma‐Aldrich) as previously described The immunohistochemical assay was performed as previously described t‐test was used to analyse matched values, and the one‐way ANOVA was used to analyse multiple mean values. A value of P < 0.05 was considered statistically significant.The data were expressed as the means ± SD of the three independent experiments. Statistical analysis was performed using the SPSS version 17.0 software. The Student's + T cells were activated with anti‐CD3/CD28 under the Th17‐polarizing condition, and the phosphorylations of JAK and STAT were detected by the Western blot assay. Similar to TCDD, tetrandrine promoted the expression of the AhR target gene CYP1A1 at protein level, but did not affect the expression of AhR itself , and the effect of tetrandrine on Treg cell differentiation under the Th17‐polarizing condition was observed. Tetrandrine and TCDD did not significantly affect the differentiation of Treg cells  and the HPA were added into the naïve CD4ion Fig. D and E aion Fig. F was lar+ T cells were treated with the CPT (an inhibitor of STAT3) and the HPA in the presence or absence of tetrandrine under the Th17‐polarizing condition. As shown in Fig. To now, little is known about the relation of STAT3 and STAT5 to the AhR. To recognize whether STAT3 and STAT5 are the upstream signallings for the activation of AhR induced by tetrandrine, the naïve CD4+ T cells in the presence or absence of tetrandrine under the Th17‐polarizing condition. Similar to TCDD, tetrandrine inhibited the phosphorylation of STAT3 and enhanced the phosphorylation of STAT5, which were almost completely reversed by CH223191  was orally administered together with tetrandrine for 14 consecutive days from the day 28 after the first immunization of type II collagen. When the mice were sacrificed, the spleens and the MLNs were taken for the examination of p‐STAT3 and p‐STAT5 expression. Figure + T cells were activated with anti‐CD3/CD28 in the presence or absence of tetrandrine and AhR antagonist CH223191 under the Th17‐polarizing condition, and the co‐immunoprecipitation assay was performed to analyse the interaction between AhR, STAT3 and STAT5. Similar to TCDD, tetrandrine could not induce the binding of the AhR to the STAT3 protein, but it promoted the AhR directly binding to the STAT5 protein, which could be reversed by CH223191 (Fig. To further explore how the activation of AhR by tetrandrine regulates the activities of STAT3 and STAT5, the naïve CD4191 Fig. A and B. 191 Fig. C. The re+ T cells in the presence or absence of tetrandrine under the Th17‐polarizing condition for 72 hrs. It was shown that CPT was unable to affect the tetrandrine‐mediated phosphorylation of the STAT5 (Fig. To recognize the relevance between the inhibition of STAT3 activity and the promotion of STAT5 activity by the tetrandrine treatment, CPT and HPA were added into the naïve CD4+ T cell differentiation and inhibits Th17 cell differentiation + T cells The AhR may play an important regulatory role in the T cell differentiation and thereby ameliorate CIA in mice + T cells results in the development of autoimmune diseases which is associated with the overproduction of the cytokine IL‐17 Our previous studies have shown that tetrandrine can ameliorate mouse CIA by suppressing Th17 cell differentiation in a manner dependent of the AhR pathway. The relative activation of STAT3 and STAT5 is closely linked to the Th17 cell differentiation. In this study, tetrandrine and TCDD decreased the STAT3 activity and enhanced the STAT5 activity under the Th17‐polarizing condition, while did not alter the activities of JAK1, JAK2 and JAK3. Meanwhile, tetrandrine and TCDD suppressed the nuclear translocation of the activated STAT3. It is well known that STAT3 plays a pivotal role in the differentiation of Th17 cells and is involved in the development of autoimmune diseases The activation of STAT3 can negatively modulate the differentiation of Treg cells, while the activation of STAT5 appears to be essential for the Treg cell differentiation and sustaining of the expression of the transcription factor Foxp3 + T cells Whatever, the expression of AhR is robustly initiated under the Th17‐polarizing condition in vivo relevance between the regulation of STAT3 and STAT5 activities and the activation of AhR by the tetrandrine treatment was further investigated. In CIA mice, tetrandrine inhibited STAT3 activity and enhanced STAT5 activity through the AhR pathway in the MLNs. Of note, MLNs, a crossroad between the mucosal and the peripheral recirculation pathways, have an important role in the immune modulation and the prevention of autoimmunity Recent studies have shown that the decreased STAT3 activity can attenuate the autoimmune arthritis through reducing the proportion of Th17 cells Concerning on the interaction between the activated AhR and the proteins of STAT3 and STAT5, tetrandrine enhanced the AhR binding to the STAT5 protein similar to TCDD, but not to the STAT3 protein. It was suggested that the activation of AhR by tetrandrine might directly enhance STAT5 activity, which negatively regulated STAT3 activity. Moreover, tetrandrine enhanced the combination of AhR with STAT5 to form a complex, which might account for the promotion of STAT5 activity.via the STAT5 activation. Recent studies have focused on the reciprocal functions of STAT3 and STAT5 in T cells, and it appears that relative activations of STAT3 and STAT5 regulate the balance between Th17 and Treg cells via the AhR pathway might lead to an inhibitory effect on the STAT3 activation.Finally, the relevance between the decreased STAT3 activity and the increased STAT5 activity by tetrandrine was further explored. As a negative regulator in the STAT family, the STAT5 can inhibit STAT3 activation. Tetrandrine suppressed STAT3 activity In conclusion, tetrandrine decreased STAT3 activity and increased STAT5 activity to inhibit Th17 cell differentiation through the AhR pathway. The findings were helpful for understanding the anti‐CIA mechanism of tetrandrine in more detail.The authors confirm that there are no conflict of interests.X. Yuan, Z. Wei and Y. Dai designed the studies; X. Yuan, Y. Dou and X. Wu performed the researches; X. Yuan and Y. Dai analysed the data and wrote the manuscript. All authors reviewed the study.


This paper investigates an improved genetic algorithm on multiple automated guided vehicle (multi-AGV) path planning. The innovations embody in two aspects. First, three-exchange crossover heuristic operators are used to produce more optimal offsprings for getting more information than with the traditional two-exchange crossover heuristic operators in the improved genetic algorithm. Second, double-path constraints of both minimizing the total path distance of all AGVs and minimizing single path distances of each AGV are exerted, gaining the optimal shortest total path distance. The simulation results show that the total path distance of all AGVs and the longest single AGV path distance are shortened by using the improved genetic algorithm. The applications of AGV systems face several important issues: AGVs number determining –27, pathDetermining the optimal numbers of vehicles is the fundamental problem in the management of an AGV system. Several methodologies have been proposed to achieve this goal and their main objective is to attend all tasks on time with a sufficient numbers of vehicles –27, 34. The multi-AGV path planning is most important in ensuring an efficient flow of materials during the production process. The path planning involves three issues in dispatching, scheduling and routing of tasks at the same time. The multi-AGV path planning problem –37 is siThere existing various constraints in multi-AGV path planning, e.g. collision-free constraints –43, timeTraditional genetic algorithms adopted two-exchange crossover operators for crossover operation, that is, using two parent individuals to produce a progeny chromosome –48. ObviThe contributions of this paper lie in the follows:Unlike the traditional path constraint only exerting on the total path distance of all AGVs, this paper exerts double-path restrictions on both the total path distance of all AGVs and single path distances of each AGV. The strategy double shortened total/single AGV path distance and obtained the optimal result.By using three parent individuals other than the traditional method with two parent individuals, to produce a progeny chromosome, this method increases the information of producing the progeny chromosomes, earning the possibility of inheriting the excellent characteristics of the parents and accelerating the searching speed of the improved algorithm.Simulations on multi-AGV path diagrams and the iterative maps of the improved/traditional genetic algorithms verify that the improved genetic algorithm has the shorter total path distance of all AGVs than that of the traditional genetic algorithm.The rest of the paper is organized as follows. Section 2 demonstrates the overview of facility layout. Section 3 investigates an improved genetic algorithm with double-path constraints by using the three-exchange crossover heuristic operators. Section 4 provides the feasibility of the algorithm by simulation. Finally, the concluding remarks are involved in Section 5.M AGVs traversing through N workstations (N > M). For the workstation distribution, the following assumptions are considered for describing the details.A jobshop manufacturing system with multiple AGVs performs material delivering. There are M AGVs traverse through N workstations (N > M).Only one AGV passes through each workstation (except the starting point).Each AGV starts from the same starting point (workstation) and comes back to the starting point.Each AGV travels one route separately with the predefined path and the fixed speed.The total path distance of all AGVs should be minimized;Each single AGV path distance should be minimized.Two constraints are exerted:The schematic diagram is shown in Referring to Indexesi, j—Indexes for two workstations on the ends of an arc, i = 0, 1, 2 …, N, j = 0, 1, 2 …, N.k—Index for AGVs numbers, k = 1, 2 …, M.l—Index for the workstations requires AGVs to delivery, l = 1, 2 …, Lk, 0 < Lk < N.ParametersRij—Arc between two workstations i and j.Cij—Path through the corresponding arc segment Rij.Variablesi = 0, 1, …, N, j = 0, 1, …, N, k = 1, …, M, defineFor Objective functionRequirementswhereRequirement (5) specifies that each AGV starts from the starting workstation 0, all workstations can only be accessed once by an AGV;Requirement (6) shows that any arc starts from the starting workstation;Requirement (7) implies that any arc ends with the starting workstation.The key problem of applying the genetic algorithm to the multi-AGV path planning is to adopt the effective coding and decoding methods. Genetic algorithms repeatedly select, crossover, and mutate the population to produce a new generation population that is more adaptable to the environment than its parents, until satisfying the desired requirements.The step of the genetic algorithm includes: genetic coding, population selection, fitness function, selection action, crossover operation, and matrix decoding. The proposed new genetic algorithm minimizes the total path distance of all AGVs by selecting individuals with big fitness values, and minimizes each AGV path distances by the three-exchange heuristic crossover operator method.N mean the N workstations that need AGVs delivery. We add M − 1 dummy symbols, denoting M − 1 virtual sites, labeled N + 1, …, N + M − 1. They have the same coordinates as the starting site, meaning that every time a dummy symbol appears, the corresponding AGV returns to the starting point. Assume that a gene represents a path that an AGV travels; one chromosome contains all genes, i.e., all paths that all AGVs travel. To avoid frequent sub-paths, we assume that the path distance from the starting point 0 to the starting point 0 is infinite.Symbol 0 indicates the starting workstation (point); symbols 1, 2, …, For example: there are 10 workstations, the code is 0-9, 5 AGVs to complete the task, a random chromosome coding is shown in The paths of the five AGVs are as follows:0 – −6 – −2 – −00 – −7 – −00 – −1 – −8 – −00 – −3 – −4 – −00 – −5 – −9 – −0The virtual symbols are on one end of a chromosomeThe paths of the five AGVs are as follows:0 – −0 – −00 – −2 – −6 – −7 – −00 – −1 – −8 – −00 – −3 – −4 – −00 – −5 – −9 – −0The 0 – −0 – −0 path means the distance is infinite, and can not meet the distance minimizing constraint, so this chromosome will be eliminated.The virtual symbol appears continuously in a chromosomeThe paths of the five AGVs are as follows:0 – −6 – −2 – −00 – −7 – −8 – −1 – −00 – −0 – −00 – −3 – −4 – −00 – −5 – −9 – −0Obviously, the 0 – −0 – −0 path is present on this chromosome, and can not meet the distance minimizing constraint, so this chromosome also will be eliminated.In the iterative process, there may be two kinds of dead solutions as the following Figs N, and the appropriate population size should be controlled between 4N and 6N [The appropriate population size is important for the convergence of the genetic algorithm. If the population size is too small, the genetic algorithm is easy to converge to the local optimal solution; on the contrary, if the population scale is too large, the computing speed of the genetic algorithm will be reduced. The size of the population is related to the variable N and 6N .Z(= Z1+Z2+⋯+Zk) is one of the parent individuals; α and β are arithmetic constants; α determines the coercion of replication, the smaller the value, the greater the replication intensity of the individual with the greatest fitness.In this paper, we use the exponential fitness functions according to . The ideThe selection operation is used to determine the recombination or crossover parent individuals and the number of offspring individuals generating by the candidate population. How to select an operator will directly affect the results of the genetic algorithm. An inappropriate operator will cause the evolution to stop or make the algorithm lose diversity, and produce premature problems .i is equal to the proportion of its fitness value and the sum of the individual population fitness [fi is the fitness value of the individual i. Q is the numbers of selected chromosomes or population size.In this paper, we use the Roulette Wheel Selection  to selec fitness , as the Traditionally, crossover refers to the process in which two chromosomes exchange some genes with each other in a certain way to form one new individuals. After crossover operation, a new generation is produced, and it inherits the father’s basic characteristics.The idea of the three-exchange heuristic crossover operator method is to produce a progeny with three parent individuals. The proposed method increases the information of producing the progeny chromosomes, comparing with the traditional method with two parent individuals. The increased parent chromosomes improve the possibility of inheriting the excellent characteristics of the parents, and accelerate the searching speed of the algorithm. The explanation of the three-exchange heuristic crossover operator method is shown in Taking a task including 10 workstations and 5 AGVs as an example, the process of three-crossover heuristic crossover operator method is described in detail as follows. The distance between the ten workstations is shown in Three individuals were randomly selected as three-crossover heuristic crossover operators:A = 6 2 12 7 11 1 8 10 3 4 13 5 9B = 3 2 12 7 9 11 1 4 13 5 10 6 8C = 5 3 10 8 7 11 2 6 12 1 4 13 9A is 81, the largest distance of the single AGV path is 27;The total distance of route B is 78, the largest distance of the single AGV path is 24;The total distance of route C is 71, the largest distance of the single AGV path is 22.The total distance of route A as a reference, point 6 is the first position of chromosome A. From right to left, cyclically move genes in the chromosomes B and C, and stop when point 6 being the first position, then choose 6 as the first point of progeny S, the results areTaking chromosome A = 6 2 12 7 11 1 8 10 3 4 13 5 9B = 6 8 3 2 12 7 9 11 1 4 13 5 10C = 6 12 1 4 13 9 5 3 10 8 7 11 2S = 6 ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗ ∗From the A = 6 2 12 7 11 1 8 10 3 4 13 5 9B = 6 2 12 7 9 11 1 4 13 5 10 8 3C = 6 2 12 1 4 13 9 5 3 10 8 7 11S in turn. Exerting with the single AGV path distance minimizing constraint, the crossover progeny S of the first crossover step isSimilarly, we can determine the other genes of crossover progeny S = 6 2 12 7 9 11 1 4 13 5 10 8 3S are less than those of original A, B, and C.The above obtained progeny chromosome indicates that the total path distance of all AGVs is 65 and the maximum path distance of a single AGV is 17. Obviously, the total path distance of all AGVs and the maximum single AGV path distance of the obtained Mutation is to exchange genes within the same chromosome, resulting in a new individual. Mutation can determine the local search ability of the genetic algorithm, maintain the diversity of the group, prevent premature convergence of the genetic algorithm .a, b, c (a < b < c), and then insert the intermediate paths a and b (including ab) after c (c refers to the paths associated with it). For example, if the sequence numbers a = 2, b = 5 and c = 10 are randomly generated, the corresponding individual transformations are as follows:This paper adopts the exchanging mutation method . The ideA = 6 2 12 7 11 1 8 10 3 4 13 5 9After the mutation:A = 6 1 8 10 3 4 2 12 7 11 13 5 9Set up a production scene with 10 workstations and 5 AGVs. A random chromosome is shown in The paths of the five AGVs are:0 – −6 – −2 – −00 – −7 – −00 – −1 – −8 – −00 – −3 – −4 – −00 – −5 – −9 – −0D:According to The specific decoding steps are described as follows:(1) Get the reachable matrices of AGVsX1 of AGV1 can be obtained:The travel path of AGV1 is 0 – −6 – −2 – −0, comparing the path with matrix D, value 1 represents the AGV1 through the station, otherwise represented with value 0. So the reachable matrix X2, X3, X4, X5.Similarly, we can get other AGVs reachable Matrices (2) Get the path distance matrices of AGVsXk  with D obtains the path distance matrix Dk  of each AGV.Multiplying the matrix For example, the path distance matrix for AGV1 is(3) Compute the path distance of AGVsThe path distance of AGV1 isIn simulation, we set up the production scene with 5 AGVs and 50 workstations, and meet the requirements listed in the Section 2 and the double-path constraints. Set the population size is 200, applying the proposed new genetic algorithm to perform path optimization.The simulation results for two genetic algorithms are drawn in Figs Figs From the simulation, we can get:(1) The improved genetic algorithm have the shorter total path distance than that of the traditional genetic algorithm.(2) The convergence speed of the improved genetic algorithm is faster than that of the traditional genetic algorithm.We recast the multi-AGV path planning problem into the framework of an genetic algorithm to investigate the improved genetic algorithm on multi-AGV path optimization. In the improved genetic algorithm, by using three-exchange crossover heuristic operators with more information than that of the traditional two-exchange crossover heuristic operators, we get more optimal offsprings. By exerting double-path constraints of both minimizing the total path distance of all AGVs and minimizing each AGV path distance, we gain an optimal shortest total path distance in AGV delivery task. The simulation results show that all AGV path distance and the longest single AGV path distance are shortened by using the improved genetic algorithm.S1 File(ZIP)Click here for additional data file.S2 File(ZIP)Click here for additional data file.