Although the importance of vivianite as a potentialP sink in the global P cycle had previously been recognized, a mechanisticunderstanding of vivianite dissolution at the molecular level, criticalto its potential application, is still elusive. The potential of vivianiteas a P sink or source in natural or engineered systems is directlydependent on its dissolution kinetics under environmentally relevantconditions. To understand the thermodynamic and kinetic controls onbioavailability, the oxidation and dissolution processes of vivianitemust be disentangled. In this study, we conducted controlled batchand flow-through experiments to quantitatively determine the dissolutionrates and mechanisms of vivianite under anoxic conditions as a functionof pH and temperature. Our results demonstrate that vivianite solubilityand dissolution rates strongly decreased with increasing solutionpH. Dissolution was nonstoichiometric at alkaline pH (>7). Therapidinitial dissolution rate of vivianite is related to the solution saturationstate, indicating a thermodynamic rather than a kinetic control. Adefect-driven dissolution mechanism is proposed. Dissolution kineticsover pH 5–9 could be described with a rate law with a singlerate constant and a reaction order of 0.61 with respect to {H+}: Ea = 20.3 kJ mol–1), suggesting hydrogen bridge dissociation as the rate-determiningstep.The iron phosphate mineral vivianite Fe(II) Vivianite is proposed as a recyclableP source, but itsbehavior in environmental settings is not well studied. This studyprovides fundamental knowledge on the vivianite dissolution mechanismand kinetics under environmentally relevant conditions. While P demand is projectedto increase with the growing world population, global P rock reservesare estimated to become depleted within 250–350 years, andsupply chain security is further endangered by geopolitical instabilities,classifying P as a critical raw material in the EU (COM/2020/474).3(PO4)2·8H2O) has recently gainedattention in the contextof P recycling. Vivianite is a common Fe(II)-phosphate mineral foundglobally in marine, freshwater, and terrestrial systems, acting asa substantial P sink.13 The formation of vivianite is restricted to anoxic, reducing environmentsat circumneutral pH with locally high concentrations of dissolvedPO43+ and Fe2+, e.g., resulting frommicrobially mediated organic matter degradation and reductive Fe-(oxyhydr)oxidedissolution. Moreover, vivianite has recently been identified as themain phosphate mineral in sewage sludge of wastewater treatment plants,offering an economically promising P recovery pathway as an alternativeto, e.g., struvite ((NH4)Mg(PO4)·6H2O).21 Pilot studies for efficient vivianite recovery from digested sewagesludge24 and potential application as a fertilizer26 have recently been reported. Vivianite is already used as an Fefertilizer ,29 but it has also beenproposed as a potential P fertilizer.31 However, despiteits global significance for the natural P cycle and its technicaland agricultural significance, a quantitative and mechanistic understandingof Fe and P mobilization from vivianite is still elusive.12The mineral vivianite (FeC2/m space group. It consists of sheetscomprising single (FeI) FeO2(H2O)4 and double (FeII) Fe2O4(H2O)4 octahedral sites that are linked by PO4 tetrahedra . These sheets are only weakly held together by hydrogen bonds betweenthe H2O ligands, explaining the perfect cleavage alongthe 010 plane.33 Under oxic conditions, vivianiteis unstable, and structural Fe(II) oxidizes rapidly to Fe(III), changingthe mineral’s appearance from colorless white to bluish andfurther to deep purple with an increasing degree of oxidation. Theoxidation of Fe(II) impacts the crystal structure, as the additionalpositive charge of Fe(III) needs to be balanced by the release ofH+.34 Nevertheless, the vivianite crystalstructure seems to be stable until an oxidation degree of ∼50%of total Fe.32 Upon further oxidation,vivianite may transform into metavivianite or the amorphous Fe(III)-phosphatemineral santabarbaraite.35 Importantly,amorphous Fe(III)-phosphate minerals of various stoichiometry generallyhave much lower solubilities than vivianite.37Structurally, vivianite belongs to the Ksp = 10–36.38The bioavailability of Fe and P (from vivianite) is stronglyrelatedto their dissolved concentrations, which can be constrained by multiplefactors including vivianite solubility, dissolution rates, and mineraltransformation reactions. The solubility product of vivianite, definedin 43– concentrationin equilibrium with vivianite is much higher than that in equilibriumwith the Fe(III)-phosphate strengite . However, comparedto Ca phosphates such as hydroxyapatite (Ca10(PO4)6OH2, log(Ksp)= −114)39 or common fertilizers, e.g., dicalcium phosphate anhydrous  = −6.7)40 and also compared to struvite  = −13.4),41 the expected dissolved PO43– concentrations of vivianite are 1–3 orders of magnitude lower,depending on the pH . In general,bioavailability is not exclusively thermodynamically but often alsokinetically controlled; nevertheless, dissolution studies of vivianiteare still scarce.44 Thinnappan et al.42 determineda pH-dependent dissolution rate equation for vivianite, with an increasingrate toward basic and acidic pH values and a minimum rate at neutralpH. Protonation and deprotonation of the P–OH group at thevivianite surface result in the weakening of the structural Fe–(PO4) bonds due to polarization and promote Fe and PO4 detachment, respectively. At basic pH, a preferential release ofP was observed, which was attributed to the structural oxidation ofFe. However, the observed dissolution rates for the environmentallyrelevant pH range of 5–9 were extrapolated from the data onlycollected for highly acidic and alkaline conditions.42 Moreover, oxidation of vivianite was not controlled inany previous study, impeding a thorough interpretation of the results.Even oxidation degrees <50% (within the proposed stability of vivianite)will likely lead to local structural changes in the vivianite crystaland influence its dissolution kinetics. Gypser et al.43 and Schütze et al.44 synthesizedvivianite at an elevated temperature (40 °C) without protectionfrom ambient air, while Thinnappan et al.42 obtained a natural vivianite specimen and ground it under atmosphericconditions. However, to gain a quantitative and mechanistic understandingof vivianite dissolution, oxidation and dissolution must be disentangledby ensuring anoxic conditions during the entire experimental procedure, i.e., from mineral synthesis through the actual dissolutionexperiments.Assuming stoichiometric dissolutionin the neutral-to-acidic pHrange, the dissolved POThe aims of the current study were (1) to quantifyvivianite dissolutionrates under anoxic conditions as a function of pH and temperature,(2) to assess whether thermodynamics or kinetics constrains the availabilityof Fe and P from vivianite on time scales relevant for applicationas a fertilizer, and (3) to elucidate the vivianite dissolution mechanism.To this end, a series of controlled batch and flow-through dissolutionexperiments were performed under strictly anoxic conditions.2Rexp) in [mol m–2 h–1] at any time during a batch experiment correspondsto the surface area normalized first derivative of the total dissolvedanalyte concentration (Cdiss) [mol L–1] over time (t) [h]. Surface areanormalization was carried out by dividing the rate in [mol L–1 h–1] by the specific surface area (SSA) [m2 g–1] and the suspension density (SD) [gL–1]. SD corresponds to the added mass (m) [g] of the mineral divided by the suspension volume (V) [m3]  [m3] 22Cdiss) in the reactor until the solid–solution equilibrium is established.Close to equilibrium, the solution saturation state influences Rexp. Therefore, Rexp cannot simply be equated to the forward dissolution rate (Rdiss) of a mineral. However, general rate lawsfor mineral dissolution have been proposed47 that includethe effect of the solution saturation state on dissolution kinetics, and –1). The term R is the gas constant(8.314 J K–1 mol–1), T is temperature [K], and Ksp is the solubilityproduct. For reversible elementary reactions, In batch experiments, dissolution leadsto a continuous increasein dissolved analyte concentration , eq 33.1–1, TOC < 2 ppb) to boil and purging it with pure N2 (purity≥ 99.99%) while cooling down (∼4 h). Unless specifiedotherwise, all experiments and syntheses were performed in anoxicwater.All chemical reagents usedwere ACS grade and used as received. Anoxic water was prepared bybringing ultrapure Milli-Q water  under a N2 environment . Briefly, solutionsof 0.4 M NaH2PO4·H2O as theP source and 0.6 M FeCl2·4H2O as the Fe(II)source were prepared and mixed slowly under constant stirring in astoichiometric ratio of 2:3 (P/Fe). To induce vivianite precipitation,0.5 M NaOH was added into the mixed and agitated Fe–P solutionwith a peristaltic pump at a speed of 10 mL·min–1 until the pH increased from 3.5 to 7.0. A white, slightly bluishprecipitate formed readily , homogenized by a hand pestle and mortar, and stored ina desiccator all inside the N2-filled anoxic chamber untilused in experiments. To ensure consistency and comparability, allexperiments were conducted using vivianite from the same homogenizedbatch, which was thoroughly characterized before use. Prior to experiments,the dried vivianite was suspended in anoxic MQ to obtain a 100 mMstock suspension.Vivianite was synthesized using a modified method ofAl-Borno and Tomson readily 1a. The s3.23.2.1N,N′-diethylpiperazine (DEPP) forpH 5.0 and 9.0, 2-(N-morpholino)ethanesulfonic acid(MES) for pH 6.0, 3-(N-morpholino)propane-1-sulfonicacid (MOPS) for pH 7.0, and piperazine-1,4-bis(propanesulfonic acid)(PIPPS) for pH 8.0.55 The pH was adjustedto the desired value through addition of 1 M HCl or NaOH. The ionicstrength (IS) was increased to 10 mM using 1 M NaCl while accountingfor the contribution of the buffers. For up to 50 h, samples werecollected regularly from the stirred suspensions. One subsample wasfiltered  and stabilized in 1 M HCl andanother subsample remained unfiltered and was digested in 6 M HCl.Both filtered and unfiltered samples were analyzed for total dissolvedP, Fe, and Fe(II). At the end of the experiment, suspensions werecentrifuged, and the remaining solids were collected and stored inthe anoxic chamber for solid-phase analysis.Toinvestigate the dissolution rate and solubility of the synthesizedunoxidized vivianite, batch experiments were performed inside an anoxicchamber at room temperature, using continuously stirred dark brownglass reaction vessels (50 mL) to minimize photo-oxidation. Experimentswere initiated by adding 100 μL of a 100 mM vivianite stocksuspension to 49.90 mL of a solution containing 15 mM buffer, resultingin 0.2 mM vivianite in the experimental suspensions. Noncomplexingbuffers were selected to minimize pH-drift throughout the experiments: 2. The temperature was varied from 5.0 to 75.0 °Cand maintained using a thermostat water bath  andwas also monitored with a thermometer placed inside the reaction vessel.The experiments in the glovebag were started after O2 levelswere below the detection limit of the oxygen sensor . Additionally, the darkbrown glass reaction vessels (50 mL) were continuously purged withN2 throughout the experiment. Vivianite oxidation was determinedby measuring the Fe(II)-to-total Fe ratio at the beginning and theend of the experiment using the Ferrozine method.57 The water bath with the reaction vessel was placed inside the glovebagon a stirring plate to ensure agitation. The experimental setup andanalytical approach were otherwise identical to the batch dissolutionexperiments described above. All temperature-controlled experimentswere conducted at pH 6.0 with 10 mM MES-buffered solution and ranfor 2 h at 5.0, 25.0, 50.0, and 75.0 °C. The pH was adjustedat 25 °C, accounting for the temperature dependency of pH toyield pH 6.0 at the desired temperature.Experiments investigatingthe effect of temperature on the vivianite dissolution rate were performedin a glovebag , which was continuously flushedwith N3.2.258 To prevent O2 diffusionover the experimental duration (∼1 month), experiments wereconducted inside the anoxic chamber. CFSTRs were wrapped in aluminumfoil to prevent photochemical reactions. The reactor outlets werecovered by 0.1 μm membrane filters , allowingonly effluents to escape the reactor, while the solids were retainedinside the reactor. To each reactor, 0.1 g of dried vivianite wasadded, resulting in a solid-to-solution ratio of 1.11 g L–1. Influent solution with IS = 10 mM (NaCl)) was pumped into the reactor using a peristalticpump at rates that accommodated a hydraulic residence time between0.75 and 30 h. Effluent samples (1 mL) were collected at various timeintervals, dependent on the pumping rate. Samples were stabilizedwith 1 M HCl and analyzed for total dissolved Fe and P concentrations.Sporadically, dissolved Fe(II) concentrations were also measured tocheck for possible Fe oxidation. The remaining effluent solution wasused to monitor the pH and the flow rate . At theend of the experiment, outflow filters with remaining solids werecollected and stored in the anoxic chamber for solid-phase analysis.Continuous flow stirred tank reactors (CFSTRs) with a volume of 90mL were used to examine the dissolution rate of unoxidized vivianite;a detailed description of the reactor design is presented in Frazieret al.3.356 using the adapted protocol of Porsch and Kappler.57 In short, for Fe(II), a buffered Ferrozine solution) was added to dissolvedand acidified samples. For Fe(tot), before adding Ferrozine solution,10% (w/v) hydroxylamine in 1 M HCl was added to the sample. Absorbancewas measured at 562 nm with a UV–vis spectrophotometer . The degree of oxidation was calculated using eq Aqueous samplesfrom batch and flow-through experiments were analyzed for pH and subsequentlyacidified in a 1:1 ratio with 1 M HCl to stabilize Fe(II) and preservedissolved species. Solid and suspension samples were completely digestedin 6 M HCl. The chemical composition and elemental ratio were determinedby measuring total Fe and P concentrations by inductively coupledplasma optical emission spectrometry . Fe speciation and the extent of Fe oxidation were determinedwithin 12 h of sampling with the photometric Ferrozine assay,4 concentrationswere determined by an adapted molybdenum blue method,59 where ammonium molybdate and potassium antimonyl tartratereact in an acidic medium with orthophosphate to form phosphomolybdicacid, which is subsequently reduced by ascorbic acid to molybdenumblue. Absorbance was measured spectrophotometrically at 880 nm .Dissolved total PO–1 using an anoxic sample holder witha zero-diffraction silicon base. Mean particle size was determinedby laser obscuration . The specific surfacearea was determined through BET analysis by N2 adsorption at room temperature and degassing undervacuum overnight. Scanning electron microscopy  equipped with an energy-dispersive X-ray detector  was used to examine the particle sizes and morphology of the solidmaterial. Ethanol-suspended samples were deposited on sample holderswith double-sided tape and carbon coating  beforeSEM analysis. Image analysis for particle size measurement was performedusing Fiji software.60 During the samplepreparation for BET and SEM, the exposure to oxygen could not be completelyprevented, but exposure time during weighing, sputter coating, andsample introduction was minimized.The phase purity and secondary mineral formationwere verifiedby X-ray powder diffraction (XRD) analysis  and a monochromator)with 2θ from 10 to 80° with step sizes of 0.06° and0.5° min3.4e.g., pH and electrolyte concentration),were used to model species activities for calculating solubility products.Reducing conditions were simulated by fixing pe at –4. ThepH was fixed to the measured value, while IS was calculated from electrolyteconcentrations in the modeled solutions. The modeled activities wereused to calculate Calculationsof equilibrium speciation were performed using VisualMINTEQ 3.1 andits associated thermodynamic database (thermo.vdb). Measured totaldissolved Fe and P concentrations, along with other solution compositionparameters . The BET specific surface area (SSA: 1.24 m2 g–1) was within the range of previously reported values of 0.2–4.8m2 g–1.42 The particlesize distribution (number based) measured by laser obscuration gavea mean diameter of 9.5 ± 6.8 μm , which reflects crystal sizes previouslyfound in digested sludge.22 The P/Fe ratioin the acid digest was ∼0.67, in accordance with the mineralstoichiometry. The determined percentage of oxidation . All calculated Ksp valuesfor vivianite were within the range of previously reported values,which is relatively broad .4.3Figure S5). At feasiblepumping rates, the dissolution kinetics of vivianite were fast relativeto the average residence time of the solution inside the reactor.Therefore, effluent concentrations and the corresponding calculateddissolution rates were controlled by equilibrium with vivianite andthe flow rate, respectively. Initially, the effluent concentrationsof the CFSTR experiments were comparable to equilibrium concentrationsdetermined in batch experiments. A substantial fraction of the initialvivianite dissolved during the experiment (>50%), resulting ina decreasein mineral surface area in suspension. Additionally, SEM images ofthe solids remaining at the end of the experiment show strong agglomerationof the smaller vivianite particles  dissolution rates.A detailed discussion of the CFSTR experiment is presented in the SI.Duringthe course of the CFSTR experiments, the measured P and Fe effluentconcentrations decreased slowly but constantly over time despite changesin the flow rate S5. At feFigure S7d–f). Therefore,possible effects of agglomeration on the reactive surface area andobserved dissolution rates were not further investigated in this study.The last data point was used as an estimate for the equilibrium concentration(ΔG = 0). 63t is thesurface area at time t, m0 is the initial mass of added vivianite, SSA is the determined specificsurface area of the starting material, and mt is the mass at time t.The value for mt wascalculated from the difference between the total suspension concentrationand the dissolved concentration of vivianite. The dissolved vivianiteconcentration was calculated from the dissolved Fe(tot) and P concentrations,accounting for the mineral stoichiometry. SAt was calculated for each sampling point and used for surfacenormalization. The dissolved vivianite concentrations were fittedto a logarithmic function , contributingto uncertainty in the estimated value for kdiss. In order to test the validity of this approach, we also fittedthe data with kdiss as an additional fittingparameter. This, however, did not improve the quality of the fit significantly,yet the fitted and estimated values of kdiss were in good agreement , thus supportingeach other. The values for the fitting parameters n and m were 0.2 and 4.7, respectively.reaction3a. Howev4.3.1Figure S6, suspension oxidation degree). Eventhough no changes in the XRD patterns were observed for the material, amorphous surface precipitationcannot be completely ruled out. Elemental analysis following aciddigestion of the vivianite stock suspension (100 mM vivianite suspendedin unbuffered MQ) indicated that the molar ratio of P/Fe was 0.67± 0.02, which corresponds to the stoichiometric ratio of initialvivianite. Microscopic examination of the remaining solids did notreveal significant morphological changes . Also, no changes in the P/Fe ratio between bulkand edge particle regions were detected using elemental mapping withEDX. The Fe and P solution concentrations from the dissolution experimentswere used to examine if dissolution was congruent. For the pH rangebetween 5 and 7, this was indeed the case. For pH 8 and 9, however,a preferential release of P was observed, and the dissolved P/Fe ratioincreased strongly with pH . So, especiallyat pH 9, the formation of secondary amorphous Fe(III) precipitatescould not be excluded. Therefore, net dissolution rates as a functionof pH were calculated only from dissolved P concentrations and normalizedto the vivianite stoichiometry. Adsorption of P to Fe(III) precipitateswas assumed negligible due to low Fe(III) concentrations measuredin suspension  and the highP/Fe ratio64 in solution, suggesting thatthe loss of P due to adsorption was marginal in our experiments.Apart from the solution saturation state, the pH alsohad a strong influence on the dissolution rate of vivianite 2. At higkdiss) was derived. Initial dissolution rateswere determined from the change in concentration between t= 0 and the first sampling point (t = 1min), since estimation through linearization was in good agreementwith fitting kdiss, as previously shown.The dissolution rate constants (kdiss)for the various pH values were calculated using G ≪0). The logarithm of the rate constant proved to decrease linearlywith an increasing pH (z (k0 (moln1– m–2 h–1) represents the rate constant at pH 0.An equation to describe the pH dependence of the dissolution rateconstant of vivianite .When applied to the rates measured for pH 5–9,linear regressionto kdiss in terms of pH, we arrived at the following expression, eq Using the fitted parameters to express Rexp), eq The combination of 4.3.2–3 (5 °C)to 1.1 × 10–2 (75 °C) mol m–2 h–1 . Thenatural logarithms of the normalized dissolution rate constants atpH 6, determined far-from-equilibrium conditions, were plotted againstthe reciprocal temperature, resulting in an Arrhenius plot  dissolutionexperiments were performed in order to determine the activation energyof the rate-limiting step of the dissolution reaction. The activationenergy can help us to further understand vivianite dissolution andits high dissolution rates. Initial vivianite dissolution rates increasedwith temperature from 1.9 × 10 m–2 h–1 S8. Thenius plot 1414where55.1Figure S462) cannot be explained by the temperaturedependence of Ksp, since it is negligiblefor vivianite; Ksp increases by only 0.14log units from 5 to 45 °C.54 Instead,variations might result from differences in the particle size anddegree of vivianite crystallinity. The apparent solubility product(Ksp(S)) for small particles, especiallythose smaller than 1 μm or with specific surface areas greaterthan a few m2 g–1, can be estimated fromthe solubility product for infinitely large particles (Ksp(S→0)), the molar surface S [m2 mol–1], and the mean Gibbs free energyof the solid–liquid interface γ̅ [J m–2]39 (eq 15).The variationin reported solubility products among studies (65 computed the γ̅ of the (010) vivianite face to be 0.23J m–2. Additionally, γ̅ was estimatedaccording to the method described by Schindler66 with 0.31 ± 0.03 J m–2. Taking thissurface free energy, the apparent solubility would only substantiallyincrease above a molar surface area of 10000 m2 mol–1, which is approximately 16-fold higher than the measuredsurface area in this study .Pinto et al.Ksp(S) values werealso reported to vary with pH within individual studies that consistentlyused the same starting material. Both in the present study and inSinger,61 the solubility product appearedto increase with increasing pH until pH > 8, where nonstoichiometricdissolution complicates the calculation of Ksp(S). Since Ksp(S) values areby definition pH-independent, first, several databases  were reviewed to ensure correct speciesdistribution calculations and consistency of constants. Second, protonswere included in the Ksp(S) equation.Under the constraints of charge balance and a constant Ksp(S) value within the pH range of 6–8, we optimizedthe stoichiometric coefficients for Fe2+ and H+ in the mineral structure and Ksp(S) byminimizing the deviation of the modeled from the measured dissolvedFe2+, PO43–, and H+ concentrations . Deviations were minimal,and the optimization yielded the following solubility  lead to a locally somewhat different surfacestoichiometry compared to the bulk. With increasing pH, less vivianitedissolved, and defects may have had a more prominent effect on theoverall stoichiometry of dissolved species. Further measurements arerequired to verify this hypothesis. Including a proton term in thesolubility product would also reduce the pH-related variability in Ksp values previously reported for vivianite. Throughout the remainder ofthis study, vivianite stoichiometry was assumed to correspond withthe bulk (P/Fe ratio = 0.67).However, observed 5.2–3 mol m–2 h–1 atpH 6.0, and 8.0 × 10–5 mol m–2 h–1 at pH 9.0) is much higher than that for Fe(III)oxides . This can be explained by the larger bond strength ofFe(III)–O bonds than that of Fe(II)–O bonds, with asmaller Madelung energy, and further by the more dynamic nature ofthe Fe(II) coordination sphere than that of the Fe(III) coordinationsphere.68 Therefore, reductive dissolutionis a common strategy for organisms to increase Fe bioavailability.71 However, the determined vivianite dissolution rate is also highcompared to reported values for other common phosphate minerals inthe environmentally relevant pH range at 25 °C, e.g., ∼2 × 10–7 mol m–2 h–1 for hydroxyapatite (Ca10(PO4)6(OH)2) at pH 5.9–8.45;72 ∼5.7 × 10–8 molm–2 h–1 for fluorapatite (Ca5(PO4)3F) at pH ∼ 9.7;73 ∼2 × 10–8 molm–2 h–1 for variscite (AlPO4·2H2O) at pH 8.99;75 and ∼5 × 10–6 mol m–2 h–1 for struvite (MgNH4PO4·6H2O) at pH 8–11.74 Roncal-Herrero and Oelkers74 stated thatfast struvite dissolution was facilitated by the presence of H-bondsin the structure. H-bonds are relatively weak compared to ionic andcovalent bonds and are absent in the structure of most other phosphatephases. Also, in vivianite, weak H-bonds are present along the 010plane, sustaining the layered structure. However, while struvite dissolutionrates are pH-independent at pH 7.5–11,74 vivianite dissolution rates increase strongly with decreasing pH.The strong increase in solubility and dissolution rate of vivianitewith decreasing pH might be explained by proton-promoted dissolution,as suggested for metal oxides.79 Proton binding weakens critical Fe–O bondswith the underlying lattice by electrophilically attacking metal–oxygen–metalbonds, thus polarizing and imparting surface charge. The proton thuschanges the coordination environment of Fe and facilitates its releasefrom the oxide surface.80 Similarly, Bengtssonand Sjöberg81 demonstrated the formationof protonated phosphate-containing surface sites for apatite, resultingin a proton-promoted dissolution. The most stable surface of vivianiteis the (010) plane terminated by Fe octahedra with H2Oligands .65 Depending on the solution pH, these H2O ligandsare protonated, which promotes the dissolution of the underlying Fe–PO4 sheet, which, in turn, is only weakly connected via hydrogen bonds to the next layer.82The determined dissolution rate for vivianite  oxidation in thepresence of dissolved P, which is close to the stoichiometric P/Feratio of vivianite (0.67). Thus, vivianite oxidation might generateamorphous Fe(III)-phosphate precipitates that could incorporate allreleased PO4. Subsequently, aging effects could lead totransformations of these secondary Fe(III)-phosphate precipitatesand are associated with a loss of oxyanion retention capacity, resultingin the release of initially coprecipitated P.85 However, the short runtime (50 h) of our dissolution experimentsdoes not support aging as the main cause for preferential P release.Moreover, the measured data does not reflect the oxidation of Fe toa substantial degree . Alternatively,amorphous Fe(II)(OH)2 may have precipitated at pH 9, shiftingthe elemental ratio of dissolved P/Fe. Stoichiometric dissolutionup to the measured P concentration would have resulted in oversaturationof Fe(II)(OH)2.Theobserved nonstoichiometric dissolution at alkaline pH (>7),characterized by the preferential release of P, might result from(a limited extent of) Fe oxidation and Fe(III) precipitation, as arguedby Thinnappan et al.5.379 They typically involve exponential factor m and supporting the use of The SEM images of the reacted vivianite show fewer defects andmore rounded shapes than those of the initial dry powder. This indicatesthat dissolution had approached equilibrium, where nucleation of pitsis not energetically favored, and dissolution occurs rather as stepssweep across the crystal surface with new steps only nucleating atcrystal edges. Consequently, surfaces become smoother rather thanmore pitted, and edges become rounded,Ea) we determinedfor vivianite dissolution was only 20.3 ± 3.0 kJ mol–1. This is lower than the reported values for struvite, 37.6–44.8kJ mol–1,90 but higherthan that for the commercial P fertilizer single superphosphate (Ca(H2PO4)2): 14.3 kJ mol–1.91 In general, mineral dissolution reactionswith an activation energy as low as ∼20 kJ mol–1 have been interpreted as rate-limited by diffusion of reaction productsaway from the mineral.79 The low Ea also suggests that the breaking of hydrogen bonds might bethe rate-determining step in vivianite dissolution, similarly as proposedfor struvite dissolution.74 However, vivianitehas a layered structure where weak hydrogen bonds between the H2O ligands of Fe(II) octahedra hold together sheets consistingof ionically bound Fe(II) octahedra and PO4 tetrahedra.92 Accordingly, vivianite dissolution along thisweak (010) surface plane might accelerate the dissolution rates. Inthis sense, a mechanism similar to exfoliation is hypothesized, wherefragments of Fe–PO4 sheets peel off the mineralalong the (101) plane .93The activation energy surfaces.94The proposed mechanism of defect-drivendissolution of vivianitecorresponds to the fitted rate eq to support optimal plant growth (1–60 μM P).96 However, in natural soils, vivianite oxidationand the presence of alternative P sinks may impact the solubility.Furthermore, aging effects and especially oxidation might substantiallychange the properties of vivianite and, consequently, the extent towhich P from vivianite becomes bioavailable in soils. Therefore, alkalinecalcareous soils may be disadvantageous for vivianite applicationdue to the lower dissolution and faster oxidation kinetics of dissolvedFe(II). The effectiveness of vivianite as a P fertilizer is co-determinedby a variety of biogeochemical and hydrological soil processes andconditions. Key processes and conditions include the water flow ratethrough the soil, the presence of organic ligands that form stablecomplexes with Fe, the presence of reactive clay and (oxyhydr)oxidemineral surfaces that adsorb P, the uptake of P by soil organisms,etc. The mechanistic understanding of anaerobic vivianite dissolutiondiscussed in this study can serve as a basis for investigating theaforementioned processes in natural settings. Also, since vivianiteis metastable in oxic environments and most agricultural soils areoxic, the impact of oxidation on the dissolution kinetics and solubilityof vivianite is of particular interest; this issue will be addressedin a follow-up study.Vivianiteoffers a promising way for recovering P from secondarysources such as wastewater sewage sludge, since the efficiency andfeasibility of the recovery process have already been proven.


Schisandra chinensis, can depress the oxidative effect and lipid peroxidation, and protect against liver injury. In this study, C57BL/6J mice were used to estimate a liver fibrosis model by CCl4, and Schizandrin C exerted an anti-hepatic fibrosis effect, as evidenced by decreased alanine aminotransferase, aspartate aminotransferase and total bilirubin activities in serum, lower hydroxyproline content, recuperative structure and less collagen accumulation in the liver. In addition, Schizandrin C reduced the expressions of alpha-smooth muscle actin and type Ι collagen in the liver. In vitro experiments also revealed that Schizandrin C attenuated hepatic stellate cell activation in both LX-2 and HSC-T6 cells. Furthermore, lipidomics and quantitative real-time PCR analysis revealed that Schizandrin C regulated the lipid profile and related metabolic enzymes in the liver. In addition, the mRNA levels of inflammation factors were downregulated by Schizandrin C treatment, accompanied by lower protein levels of IκB-Kinase-β, nuclear factor kappa-B p65, and phospho-nuclear factor kappa-B p65. Finally, Schizandrin C inhibited the phosphorylation of p38 MAP kinase and extracellular signal-regulated protein kinase, which were activated in the CCl4 fibrotic liver. Taken together, Schizandrin C can regulate lipid metabolism and inflammation to ameliorate liver fibrosis by nuclear factor kappa-B and p38/ERK MAPK signaling pathways. These findings supported Schizandrin C as a potential drug for liver fibrosis.Liver fibrosis is considered a sustained wound healing response and metabolic syndrome, and its therapy is of great significance for chronic liver disease. Schizandrin C, as one lignan from hepatic protectant  Liver fibrosis is considered a sustained wound healing response generated from chronic injury, which is accompanied by excessive deposition of extracellular matrix (ECM) . Many faLipids play a vital role in energy metabolism and cell signaling. In addition, lipids serve as the constituent of plasma membranes and lipid particles, including lipoproteins and extracellular vesicles . Since tAs a typical characteristic of chronic hepatic diseases, inflammation participates in and plays a crucial role in the occurrence and development of liver fibrosis . PersistSchisandra chinensis, exerts an antioxidant effect, and inhibits lipid peroxidation and binding of CCl4 metabolites to lipids  at 50 mg/kg was orally administered once a day to the liver fibrosis model mice. The control mice were administered equivalent volumes of peanut oil and 0.5% carboxymethylcellulose solution (CMC-Na). Then, 4 weeks later, the mice were euthanized to obtain blood samples and liver tissues. The structure of Schizandrin C  is presented in Male C57BL/6J mice, which were 6–8 week-old and 18–22 g, were purchased from Vital River Laboratory Animal Technology Co., Ltd. . The mice were raised under controlled conditions with 21°C ± 2°C, 50% ± 10% humidity, and 12 h light–dark cycles. All experimental operating procedures followed the guidelines of the Animal Ethics Committee of Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine . Then, 10 mL/kg 10% CClg for 15 min to obtain serum. The activities of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total bilirubin (TBIL) were analyzed using an automatic biochemical analyzer  as per the manufacturer’s instructions.Blood was centrifugated at 1,000 After acquiring the liver tissues, the liver’s left lobes were separated, fixed in formaldehyde, embedded with paraffin, and sectioned. Then paraffin sections were stained with hematoxylin and eosin (H&E) or Masson’s trichrome staining in accordance with the standard protocol. The staining results were taken using a fluorescence microscope .−ΔΔCT method. The primer sequences are presented in Liver samples were crushed using a TL2020 grinding instrument . Total RNA was isolated by Trizol reagent  as per the standard protocol. Quantitative real-time PCR analysis was performed using One-Step TB GreenTM PrimeScript PLUS RT-PCR Kit  in a LightCycler 480II instrument . The values were analyzed by using the 2After liver tissue sections were deparaffinized, the paraffin sections were blocked with bovine serum albumin (BSA) and incubated with antibodies against alpha-smooth muscle actin (α-SMA) , type Ι collagen (collagen I) , phospho (p)-nuclear factor kappa-B (NF-κB) p65 , p-p38 MAP kinase (p38 MAPK) , and p-extracellular signal-regulated protein kinase (ERK)  overnight at 4°C. Then, the paraffin sections were treated with fluorescence-conjugated secondary antibodies  and counterstained with 40, 6-diamidino-2-phenylindole (DAPI) . The staining results were acquired using a Pannoramic MIDI scanner  and viewed by using CaseViewer 2.4 .Liver total protein was isolated by RIPA buffer and quantified by a BCA protein assay kit  according to the manufacturer’s instructions. Proteins were separated through an SDS-PAGE gel and transferred onto polyvinylidene difluoride (PVDF) membranes and then blocked in 5% skimmed milk. Afterward, the membranes were incubated with the primary antibody against IκB Kinase-β (IKKβ) , NF-κB p65 , p-NF-κB p65 , ERK , p-ERK , p38 , p-p38 , and β-tubulin  at 4°C overnight and then with the corresponding anti-rabbit secondary antibody  or anti-mouse secondary antibody  at room temperature for 1 h. Finally, the bands were determined using a chemiluminescence apparatus  and quantified using the Image J software .First, 100 mg of liver tissues were treated with 0.75 mL of methanol in a glass tube with a Teflon-lined cap. After vortexing, 2.5 mL of methyl tert-butyl ether (MTBE) was added and incubated in a shaker for 1 h at room temperature. Afterward, the samples were added to 0.625 mL of MS-grade water, incubated for 10 min at room temperature, and centrifuged at 1,000 g for 10 min. The upper phase was gathered, and the lower phase was re-extracted using 1 mL of MTBE/methanol/water  for the organic phase. Combined organic phases were dried under nitrogen and re-dissolved in 100 μL of isopropanol for ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) analysis by using a Vanquish UHPLC system  with an Orbitrap Q ExactiveTM HF mass spectrometer  in Novogene Co., Ltd. .A Thermo Accucore C30 column  was used, and the samples were injected with a linear gradient flow rate of 0.35 mL/min for 20 min. The temperature of the column was set at 40°C. Acetonitrile/water (6/4) coupled with 10 mM ammonium acetate and 0.1% formic acid was used as mobile phase buffer A, and acetonitrile/isopropanol (1/9) coupled with 10 mM ammonium acetate and 0.1% formic acid was used as buffer B. The solvent gradient was initially 30% B for 2 min and then 43% B for 5 min, 55% B for 5.1 min, 70% B for 11 min, 99% B for 16 min, and 30% B for 18.1 min.www.metaboanalyst.ca). Potential differential metabolites were picked with variable importance in projection (VIP) > 1 and p < 0.05, or fold change (FC) ≥ 2, or FC ≤ 0.5  for peak alignment, peak picking, and quantitation. Then, peak intensities were normalized to the total spectral intensity and used to calculate the molecular formula on account of additive ions, molecular ion peaks, and fragment ions. The data were matched for accurate qualitative and relative quantitative results using LIPID MAPS, LipidBlast, and HMDB databases. If data were not distributed normally, area normalization was attempted used for normal transformation. Principal components analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were operated using MetaboAnalyst 5.0 (FC ≤ 0.5 .The hepatic hydroxyproline (HYP) content was measured using a hydroxyproline content detection kit .2 at 37°C. Cell Counting Kit-8  was used to screen suitable concentrations of Schizandrin C as per the manufacturer’s instructions, and TGF-β1 at 20 ng/mL was used to activate HSCs.Hepatic stellate cell lines LX-2 (CVCL_5792) and HSC-T6 (CVCL_0315) were acquired from FuHeng Cell Center . Both cell lines were cultured in high glucose Dulbecco’s modified Eagle’s medium (DMEM) with 10% FBS and maintained in an incubator with 5% COpost hoc test. All data were analyzed by GraphPad Prism 8.0 .The values are shown as mean ± SD. Multiple comparisons were conducted with one-way ANOVA, followed by the Student–Newman–Keuls 4 was used to establish a liver fibrosis model , fatty acid synthase (Fasn), sterol regulatory element-binding transcription factor 1 (Srebf1), acetyl-coenzyme A carboxylase alpha (Acaca), carnitine palmitoyltransferase 1a (Cpt1a), long-chain acyl-CoA dehydrogenase (Lcad), lipoprotein lipase (Lpl), microsomal triglyceride transfer protein (Mttp), and apolipoprotein B (Apob) were markedly increased, and treatment with Schizandrin C notably decreased Cd36, Fasn, stearoyl-coenzyme A desaturase 1 (Scd1), Srebf1, Acaca, Cpt1a, acyl-coenzyme A oxidase 1 (Acox1), Lcad, monoglyceride lipase (Mgl), Mttp, and Apob , tumor necrosis factor (Tnfα), and cyclooxygenase-2 (Cox-2) (4 (4 liver (4 mice.As shown in  (Cox-2) . Then, iox-2) (4 . In addiox-2)  signaling pathway is closely associated with lipid metabolism, inflammation, and liver fibrosis, relative protein levels were then detected. Western blot analysis showed that the total protein levels of p38 and ERK were basically unchanged, but phosphorylation levels of ERK and p38 were higher in CClnd p-p38 . The samnd p-p38 . Taken tEvidence has showed that liver fibrosis can cause liver architecture and functional impairment, resulting in cirrhosis and organ failure . If the 4 mice showed a higher level of liver function-related markers in serum, raised hepatic hydroxyproline content, impaired structure, and deposited collagen in the liver, and treatment with Schizandrin C decreased the disturbed serum ALT, AST, and TBIL, reduced hepatic hydroxyproline content, and weakened liver damage and collagen accumulation. Furthermore, the expressions of α-SMA and collagen Ι activated by CCl4 were reduced by Schizandrin C in vivo. The in vitro experiment also indicated that HSC activation was suppressed by Schizandrin C. All these results suggested that Schizandrin C exerts a significant anti-liver fibrosis effect.Almost all chronic liver injuries induced by different etiologies may contribute to liver fibrosis . When a 4 model and normal liver samples, and treatment with Schizandrin C can regulate lipid species in CCl4 liver. Previous studies have displayed that Schizandrin C may inhibit CCl4-activated lipid peroxidation and the combination of CCl4 metabolites and lipids (4 rats decreased markedly, and most PCs and PEs decreased to a great extent (Cd36 associated with lipid uptake, Fasn, Scd1, Srebf1, and Acaca associated with lipid synthesis, Cpt1a, Acox1, Lcad, and Mgl associated with lipid metabolism, and Mttp and Apob associated with TAG transfer. However, treatment with Schizandrin C can reverse most mRNA levels of these enzymes or transporters, further suggesting that Schizandrin C can regulate lipid metabolism in CCl4 fibrotic liver.The liver controls the central processes of lipid homeostasis, and disturbed lipid metabolism can contribute to the occurrence and progression of liver fibrosis . Here, ld lipids . Howevert extent . Here, wt extent . In thist extent . Here, fIL-6 was increased by TGF-β1 stimulation in both LX-2 and HSC-T6 cells and decreased by treatment with Schizandrin C. More importantly, the protein levels of IKKβ, NF-κB p65, and p-NF-κB p65, especially the phosphorylation level of NF-κB p65, were elevated, and inflammatory factors, such as Il-6, Tgfβ-1, Tnfα, and Cox-2, were raised in CCl4 fibrotic liver, but treatment with Schizandrin C can inhibit them, indicating that Schizandrin C can attenuate inflammation and the NF-κB signaling pathway.Recent research studies have reported that TAG metabolism is closely associated with inflammation . Though MAPK pathways, such as p38 MAPK and ERK, are significant for cell growth and differentiation, and closely associated with liver fibrosis . Previou4, which is possibly via the regulation of lipid metabolism and inflammation mediated by NF-κB and p38/ERK MAPK signaling pathways. These results support Schizandrin C as a potential therapeutic drug for liver fibrosis.In conclusion, Schizandrin C can attenuate liver fibrosis induced by CCl


While immensely successful, drugging kinases by active site inhibitors has faced major challenges. Selectivity issues leading to side effects and emergence of resistance mutations rendered treatments targeting active sites ineffective. Double-drugging via active and allosteric sites is a recently developed approach to overcome these obstacles. Using Aurora A and Abelson kinase, we provide a quantitative biophysical evaluation of double-drugging by rationally selecting inhibitor combinations with positive cooperativity. The results shed light on the interplay of kinase conformational equilibria and inhibitor-dose requirements for effective inhibition. Due to our rational selection of a positively cooperative drug combination for Abl, we deliver a fully closed, inactive Abl structure, including regulatory SH3 and SH2 domains. Collectively, this biophysical framework aids future rational double-drug designs. Selective orthosteric inhibition of kinases has been challenging due to the conserved active site architecture of kinases and emergence of resistance mutants. Simultaneous inhibition of distant orthosteric and allosteric sites, which we refer to as “double-drugging”, has recently been shown to be effective in overcoming drug resistance. However, detailed biophysical characterization of the cooperative nature between orthosteric and allosteric modulators has not been undertaken. Here, we provide a quantitative framework for double-drugging of kinases employing isothermal titration calorimetry, Förster resonance energy transfer, coupled-enzyme assays, and X-ray crystallography. We discern positive and negative cooperativity for Aurora A kinase (AurA) and Abelson kinase (Abl) with different combinations of orthosteric and allosteric modulators. We find that a conformational equilibrium shift is the main principle governing cooperativity. Notably, for both kinases, we find a synergistic decrease of the required orthosteric and allosteric drug dosages when used in combination to inhibit kinase activities to clinically relevant inhibition levels. X-ray crystal structures of the double-drugged kinase complexes reveal the molecular principles underlying the cooperative nature of double-drugging AurA and Abl with orthosteric and allosteric inhibitors. Finally, we observe a fully closed conformation of Abl when bound to a pair of positively cooperative orthosteric and allosteric modulators, shedding light on the puzzling abnormality of previously solved closed Abl structures. Collectively, our data provide mechanistic and structural insights into rational design and evaluation of double-drugging strategies. Protein allostery is one of the fundamental regulatory mechanisms involved in various biological processes . SpecifiA recently approved allosteric inhibitor of Abelson kinase (Abl), asciminib, has been highly effective in inhibiting Abl in vitro and in vivo –12. Rema12Herein, we provide the quantitative framework for double-drugging using two targets: Aurora A kinase (AurA) and Abl. Both kinases participate in various cellular pathways, and their dysregulation results in a multitude of cancers, such as breast cancer and leukemia –19. Comm50 = 13 nM, Ki = 0.87 ± 1.44 nM] . Identical Mb1 binding affinities, independent of saturating danusertib concentrations, reveal that the simultaneous binding of Mb1 and danusertib to AurA is possible. Thus, we reason that this 16-fold negative cooperativity for Mb1 binding arises from a conformational equilibrium shift of AurA to the inactive state induced by danusertib.Aligning with our hypothesis, we find that the binding affinity of activating monobody (Mb1) to AurA weakens 16-fold when AurA is presaturated with danusertib B. To tesKeq= 0.67 . Thus, a further increase in positive cooperativity would only be possible if the Mb affinity was tighter to the inactive state of the AurA-danusertib complex than to the inactive state of apo AurA. We indeed observed a threefold positive cooperativity for Mb3 with danusertib  Mb2 is an inhibiting monobody for which we had obtained an X-ray crystal structure in complex with AurA, ii) Mb3 exhibits larger inhibition than Mb2, and iii) AurA-Mb3 complex exists in a monomeric form unlike the dimeric AurA-Mb2 complex . We indeeq= 0.67 ] and assnusertib B. We spenusertib , 28.SI Appendix, Fig. S3).To confirm whether the mechanism of cooperativity between Mbs and danusertib follows a classic allosteric model, we tested binding of Mb6 to the AurA-danusertib complex. Despite high affinity, Mb6 binding does not change AurA’s activity, implying that Mb6 binding does not shift the active/inactive conformational equilibrium of AurA . Indeed,For a reversible two-state allosteric model, the same fold-change of cooperativity must be observed when reversing the order of binding. To measure changes in the affinity of danusertib upon Mb binding, we had to employ competitive replacement ITC with adenosine 5′- diphosphate (AMPCP), since danusertib binds too tightly to AurA for direct measurement. Indeed, the measured cooperativities are matching quantitatively regardless of the binding order C.Next, we probed biological relevance of these observed cooperativities by measuring the inhibition of AurA kinase activity using Lats2 peptide as a substrate with cellular ATP concentrations. Preincubation of inhibiting Mbs resulted in a vastly decreased amount of danusertib required to cause 90% inhibition of AurA activity D. This cSI Appendix, Table S1). The complex of AurA-danusertib-Mb1 . LiSI Appendix, Fig. S1 A–D). We find that the enthalpy for danusertib binding to AurA-Mb1 is reduced by 22.8 kJ/mol compared to AurA-Mb2, which approximates the equivalence of one salt bridge [12.6 to 20.9 kJ/mol . However, in the presence of danusertib, we observe K162 to rather form a hydrogen bond with O-27 of danusertib’s methoxy moiety than with E181 in the MD simulation, which is the state sampled in our crystal structure as well .Our crystal structures and ITC experiments showed that danusertib can bind to both the AurA-Mb2 and AurA-Mb1 complexes. To reveal why danusertib, however, binds with much higher affinity to AurA-Mb2 than AurA-Mb1 (there is no steric hindrance), we scrutinized the thermodynamic parameters of our ITC studies on danusertib binding to different AurA-Mb complexes   Fig. 2  Fig. 2F,64–510) . Abl exists in a conformational equilibrium between open, active, and closed, inactive conformations . Surprisingly, we found that imatinib and asciminib display a twofold negative cooperativity for AblKD . Due to the tight binding of asciminib, its affinity was measured via competitive replacement ITC using N-Myr peptide as a weak-binding ligand  . SKI indeed binds preferentially to the closed conformation of Abl64–510, as seen by the fivefold tighter binding of SKI to Abl64–510 than to AblKD. Furthermore, we observe a modest positive cooperativity between SKI and asciminib binding in AblKD, indicating that SKI binds to the “closing-competent” conformation induced by asciminib. Unexpectedly, we did not find a difference between the binding affinities of SKI to Abl64–510 and Abl64–510-asciminib. We interpret this result as evidence that the conformational equilibrium of apo Abl is already far shifted to the closed conformation. Hence, the binding of asciminib had no effect on this equilibrium. This is, in fact, in agreement with a NMR study by Grzesiek and colleagues reporting overlapping chemical shifts between apo and GNF-5 (a predecessor of asciminib) bound Abl for open/closed equilibrium markers , an orthosteric inhibitor that tightly binds to Src kinase (IC= 44 nM) , 42, bec markers .64–510 at saturating concentration  actually do not inhibit the catalytic activity despite binding to AblKD , 43, 44.ntration A. This v64–510 by the two orthosteric inhibitors imatinib and SKI. In agreement with our affinity measurements . Thus, under our assay condition, we reason that the ATP shifts the conformational equilibrium of Abl64–510 to the open state, which is favored by imatinib over SKI binding.We note that SKI’s ICsciminib A, whereasciminib B–D. We a64–510 kinase activity varying the concentration of both orthosteric and allosteric inhibitors . Surprisingly, this Abl structure adopts a closed conformation with striking differences to previously reported closed structures; Abl in complex with nilotinib and asciminib (PDB-ID: 5MO4), as well as in complex with PD166326 and myristic acid, a groundbreaking structure of full-length Abl in the inhibited state (PDB-ID: 1OPK)  . Second, the α-C helix is adopting the “out” position resulting from this N-lobe twist, since an α-C helix “in position” would clash with strands β4 and β5 , while their DFG-motif is in the “out” position. This highlights i) the importance of the α-C helix conformation and the canonical salt bridge, and not only the DFG-motif, in determining open/closed conformation which is directly correlated to active/inactive states in full-length kinases, and ii) that through binding of SKI and asciminib, we were able to capture the strictly closed and inactive conformation of Abl with regulatory domains. We note, that the orthosteric site is fully occupied by SKI and the twisted N-lobe aids in forming this tightly packed binding pocket . In fact, K290 located on β3 strand is wrapping over SKI burying the inhibitor in Abl’s orthosteric site. Besides extensive van der Waals interactions between SKI and Abl, the quinazoline ring of SKI shares two hydrogen bonds with Abl, one between the side chain hydroxyl of T334 on β-strand 5 and N-2 of SKI as well as between the amide of M337 and N-0 of SKI  . First, 4 and β5 B and C. 0 of SKI C.64–510-SKI-asciminib. Strikingly, S248P was identified as a resistant mutation for GNF-2 and asciminib in cell culture-based screening . This originates from an SKI-induced twist in the N-lobe causing a fully closed conformation, thus, releasing an energetically frustrated conformation observed in other double-drugged Abl complexes, since SKI and asciminib both preferentially bind to the closed state of Abl to cause positive cooperativity. In contrast, double-drugging with an open conformation binder (nilotinib) and a closed conformation binder (asciminib) results in an energetically frustrated Abl structure (PDB-ID: 5MO4). This structural study highlights how understanding of conformational equilibria crucially aids the discovery of further inhibited states. Our finding of the energetically frustrated conformation agrees with previous NMR experiments reporting an opposing binding preference of imatinib and GNF-5 for Abl (Kd >10 µM), and not via binding to its active site (Kd = 15 nM) compared to closed Abl64–510 (Kd = 72.4 nM) and negative cooperativity between imatinib and asciminib buttress Grzesiek’s model where imatinib’s preferential binding to the open conformation of Abl arises from its orthosteric site binding with nanomolar affinity.To combat on-target cancer drug resistance, double-drugging holds promise to be a powerful strategy. The rationale behind is multiplication of individual resistance mutational probabilities for each drug. Impressively, combinations of asciminib and various orthosteric inhibitors, including imatinib, indeed abolish the emergence of Abl resistance mutants and this double-drugging of Abl is currently in clinical trials . Given t for Abl . In cont for Abl . This co for Abl , 34. Ourive site . This isive site , 48. Tig50 of 21 μM  were purified with on-column refolding as described in Zorba et al.  in pET28a and LPP (#79748) from Addgene were cotransformed in BL21(DE3) cells and plated on Kan/Spec LB plate. Expression cultures were grown in TB to OD = 0.6–0.8 and induced with 0.6 mM IPTG for 16 h at 21 °C. Harvested cells were resuspended in 50 mM Tris–HCl, 300 mM NaCl, 20 mM MgCla et al. .64–510  were cloned into pETm41 (GenScript) . Residue numbering follows Abl1b isoform that naturally consists of N-myristoylation. All Abl constructs were cotransformed with phosphatase YOPH (streptomycin-resistance) in BL21(DE3) cells and plated on Kan/Strep LB plate. Expression was performed in TB media and induced at OD = 0.6–0.8 with 0.1 mM (for AblKD) or 0.2 mM IPTG (for Abl64–510) for 16 to 20 h at 18 °C. Harvested cells were resuspended in 50 mM Tris–HCl, 500 mM NaCl, and 1 mM TCEP, pH 8.0 (buffer A). Cells were sonicated in the presence of EDTA-free protease inhibitor cocktail, lysozyme, and DNAse. Clarified lysate was with Ni-NTA columns. The protein was eluted with 100% 50 mM Tris–HCl, 500 mM NaCl, 500 mM imidazole, and 1 mM TCEP, pH 8.0 and combined with TEV and CIP  and dialyzed overnight against buffer A at 4 °C. Cleaved Abl was further purified with Ni-NTA and a Q column . Prior to anion exchange chromatography Abl was dialyzed into 50 mM Tris–HCl, 1 mM TCEP, and 10% glycerol, pH 8.0. Dephosphorylated Abl fractions were polished with 26/600 S75 pg (for AblKD) or 26/600 S200 pg (for Abl64–510) gel filtration column with buffer A. Pure fractions were aliquoted to around 40 μM and stored in −80 °C.AblKD  and AblAll titrations were carried out using Nano ITC (TA Instruments) and analyzed via the NanoAnalyze software either using the independent fit model or competitive replacement model. The first injection of each experiment was discarded according to the software manual.SI Appendix.For AurA, danusertib (Selleckchem #S1107) was reconstituted to 100 mM in 100% DMSO and was diluted to appropriate concentration to match final 5% DMSO (vol/vol) for each experiment. An ADP-analogue, AMPCP, was used for competitive replacement experiments to measure and fitting of the binding of danusertib to AurA. All proteins were dialyzed in 20 mM Tris–HCl, 200 mM NaCl, 10% (vol/vol) glycerol, and 5 mM TCEP, pH 7.5. AMPCP was resuspended with the same buffer and was matched to pH 7.5. DMSO was added prior to each experiment to match 5% between titrant and titrand. Each injection was added in 2 µL increments with 180 s interval at a constant stirring speed of 300 rpm and at 25 °C. Concentrations used for the experiments are noted in SI Appendix.For Abl, N-Myr peptide (Myr-GQQPGKVLGDQR), ordered from GenScript, was used for competitive replacement experiments to measure and fitting of the binding of asciminib to Abl. All proteins were dialyzed in 50 mM Tris–HCl, 500 mM NaCl, and 1 mM TCEP, pH 8.0. Imatinib-mesylate (Sigma #SML-1027) and asciminib (MedKoo #206490) were reconstituted to 10 mM in 100% DMSO and were diluted to appropriate concentration for each experiment. N-Myr peptide was resuspended with the same buffer and was matched to pH 8.0. DMSO was added prior to each experiment to match 5% between titrant and titrand. Each injection was added in 1 to 1.5 µL increments with 180 s interval at a constant stirring speed of 300 rpm and at 25 °C. Concentrations used for the experiments are noted in 50 of danusertib to AurA, ADP-GloTM Max assay (Promega #V7001) was used. 20 nM AurA in the absence or presence of either saturating concentration of Mb1 or Mb2 or Mb3 was incubated with 3 mM Lats2 (ATLARRDSLQKPGLE), 0.6 mg/mL BSA, and varying concentrations of danusertib with final 5% (vol/vol) of DMSO at 25 °C in 20 mM Tris–HCl, 200 mM NaCl, 10% (vol/vol) glycerol, and 5 mM TCEP, pH 7.50. The bolded and underlined residue indicates site of phosphorylation. The reaction was initiated by adding 5 mM ATP, and the final samples were collected after 2 h for AurA-Mb1 complex, 10 h for apo AurA, and 20 h for AurA-Mb2 and AurA-Mb3 complexes. The amount of ADP in the samples was measured by following the manufacturer’s protocol and used to calculate the observed rate.To measure the IC64–510), 2 mM Srctide (EIYGEFKK), 0.6 mg/mL BSA, 20 mM MgCl2, 750 µM NADH, 6 mM PEP, and 2.5 units of PK/LDH (Sigma #P0294). The bolded and underlined residue indicates site of phosphorylation. Oxidation of NADH at A340 was monitored using SpectraMAX by starting the assay with 1 mM ATP. The final volume of the assay was 100 µL. The observed rate (kobs) was calculated following Zorba et al.  in 50 mM Tris–HCl, 500 mM NaCl, and 1 mM TCEP, pH 8.0, supplemented with 20 nM Abl kinase . Both 5 nm of excitation and emission slit width were used. Control experiments  were confirmed that the increase of fluorescence is caused by the fluorescence energy transfer.FluoroMax-4 (Horiba Scientific) with temperature controller (water bath) was used to measure FRET between intrinsic tryptophan fluorescence and SKI. Either 10 nM Abl or 10 nM Abl + 200 nM asciminib was preincubated with varying concentrations of SKI for 40 min at 25 °C before measurements. An increase in the fluorescence was measured when the complex, specifically tryptophan, was excited at 295 nm to emit at 340 nm, which then excites SKI to emit at 460 nm .We simulated curves with tighter 2 with 2 µL reservoir of 0.1 M MES pH 6.5 + 0.2 M ammonium sulfate + 4% (v/v) 1,3-propanediol + 15 to 18% PEG 8,000. Streak seeding was used to obtain bigger crystals. Crystals were grown at 18 °C by hanging drop. The crystals were transferred to a drop of fresh reservoir for 30 s to remove excess nucleotides from the crystal surface. Then, the crystals were transferred to a drop with reservoir with 1 mM danusertib for 16 h of soaking. For cryoprotection, the crystals were transferred into 17.5% PEG 400, 17.5% ethylene glycol, 15% reservoir, and 50% water for a few seconds.Crystals of AurA in complex with Mb1 and danusertib were obtained by combining 2 µL of 300 µM (10 mg/mL) AurA + 315 µM (4 mg/mL) Mb1 + 2 mM AMPPCP + 4 mM MgClCrystals of AurA in complex with Mb2 and danusertib were obtained by combining 0.5 µL of 300 µM (10 mg/mL) AurA + 315 µM (4 mg/mL) Mb2 + 1 mM danusertib with 0.5 µL of 0.1 M BIS–TRIS pH 5.5 + 0.2 M Ammonium acetate + 25% PEG3350. Crystals were grown at 18 °C by sitting drop. Crystals were harvested and subsequently flash frozen.Diffraction data for AurA-danusertib-Mb1 and AurA-danusertib-Mb2 were collected at 100 K Advanced Light Source  at beamlines BL821 and BL501, respectively, and were integrated with XIA2  or XDS . Data we64–510 in complex with SKI and asciminib were obtained by combining 0.3 µL of 600 µM Abl64–510 + 700 µM SKI + 700 µM asciminib (~32 mg/mL) in 5% DMSO with 0.4 µL reservoir of 0.1 M Tris–HCl pH 8 + 1.75 M Ammonium sulfate + 2% (v/v) polypropylene glycol 400 (PPG 400). The final stock of complex was concentrated from 1 µM Abl64–510 with ~1.2 µM SKI/asciminib after incubation at 4 °C for 6 h. Screening around this condition yielded crystals in a transparent diamond-shaped or plate-shaped crystals. Crystals were grown at 18 °C by sitting drop for a few days. The crystals were transferred to a drop of fresh reservoir containing 20% xylitol with matching concentration of inhibitors in 5% DMSO for few seconds for cryoprotection.Crystals of AblSingle crystal X-ray diffraction data were collected at 100 K at Advanced Light Source Berkeley (BL201). Data were integrated with XDS  as well Appendix 01 (PDF)Click here for additional data file.


Ananas comosus bromelain cysteine-protease, (ii) bovine trypsin serine-protease and (iii) Bacillus subtilis neutral metalloendopeptidase. In silico studies were performed with reference ligands and T-2 toxin as control, and in vitro experiments. In silico study results showed that tested toxins interacted near the catalytic triad, similar to how the reference ligands behave in all tested proteases. Likewise, based on the proximity of the amino acids in the most stable poses, the chemical reaction mechanisms for the transformation of OTA were proposed. In vitro experiments showed that while bromelain reduced OTA’s concentration in 7.64% at pH 4.6; trypsin at 10.69% and the neutral metalloendopeptidase in 8.2%, 14.44%, 45.26% at pH 4.6, 5 and 7, respectively (p < 0.05). The less harmful α-ochratoxin was confirmed with trypsin and the metalloendopeptidase. This study is the first attempt to demonstrate that: (i) bromelain and trypsin can hydrolyse OTA in acidic pH conditions with low efficiency and (ii) the metalloendopeptidase was an effective OTA bio-detoxifier. This study confirmed α-ochratoxin as a final product of the enzymatic reactions in real-time practical information on OTA degradation rate, since in vitro experiments simulated the time that food spends in poultry intestines, as well as their natural pH and temperature conditions.Ochratoxin A (OTA) is considered one of the main mycotoxins responsible for health problems and considerable economic losses in the feed industry. The aim was to study OTA’s detoxifying potential of commercial protease enzymes: (i)  About 100,000 fungi species have been identified, and more than 500 mycotoxins with toxigenic effects have been recognised ,3. MycotThe modern direction of mycotoxin decontamination techniques is towards using non-invasive methods, with high specificity, with harmless products and that is environmentally friendly ,12. In tOTA is a potent nephrotoxic, teratogenic, carcinogenic and immunotoxic, amongst others , and conAnanas comosus (cysteine), the bovine trypsin (serine), and a neutral metalloendopeptidase from Bacillus subtilis  with potential to detoxify OTA through biotransformation. While bromelain is easily obtained from the stem and juice of pineapples, and is considered a very resistant enzyme [Seeking practical options of purified proteases as mycotoxin detoxifiers, due to their low cost, wide availability, ease of extraction and high resistance, the aim of this research, was to study the bromelain from t enzyme , it has t enzyme ; the neut enzyme ,43,44; at enzyme , and thet enzyme ,24. Moret enzyme ,32,45, dt enzyme ,33,34,35t enzyme ,46, in tt enzyme ,48 it mit enzyme ,49; (ii)t enzyme , it might enzyme  and  for bromelain was approximately 5.44-fold lower than the reference ligand, indicating a higher affinity for the protein , and its affinity -mediated interactions with amino acid residues of the ligand binding site .iK = 101.78 µM) and binding probability to form a complex  it could function as a possible competitive inhibitor  values when compared to T-2 and the reference ligand, showing that the binding is more spontaneous towards the bromelain binding site among all the evaluated ligands . OTA hadAccording to docking studies, the inactivation mechanism in OTA by bromelain triggers the catalytic action of Cys26 that attacks the carbonyl of the amide group in OTA, resulting in α-ochratoxin and β-phenylalanine as the final products .Molecular dynamics showed that the bromelain-OTA complex maintained stable interactions  within tp ≤ 0.0001; F = 16.87). Sidak’s multiple comparisons tests showed that bromelain reduced OTA concentration by 7.64 (%) at pH 4.6  the final product, α-ochratoxin, suggested in docking was not detected in chromatograms  for trypsin was approximately 272-fold lower, indicating a higher affinity for the reference ligand  compared to T-2, and its affinity . Further, when HPLC–TOF–MS chromatograms were analysed, Both, T-2 and HT-2 corresponding ions were present, 484.25 (m/z) and 442.24 (m/z), for T-2 and HT-2, respectively  for trypsin was approximately 94-fold lower, indicating a higher affinity for the reference ligand  compared to OTA, and its affinity . Sidak’s multiple comparisons tests showed that bromelain reduced OTA concentration by 10.69 (%) at pH 4.6  for neutral metalloendopeptidase was approximately 17-fold higher than the reference ligand, indicating a very low affinity for the protein. T-2 showed hydrogen bond (HB), aliphatic and π–σ–mediated interactions with amino acid residues of the ligand binding site (T-2 toxin showed a similar free binding energy (ΔG) compared to those of the reference ligand DB0763; . Howevering site . Althouging site .iK) when compared to OTA and neutral metalloendopeptidase.OTA’s most negative value (ΔG) value was -8.56, which is very similar to that of the reference ligand (DB07673) when both were calculated by Swiss Dock, which is considered the most precise software when metallic ions are present . ReferenOTA’s interactions with neutral metalloendopeptidase binding site residues are mediated by a hydrogen bond (HB) and aliphatic interactions . OTA’s pThe inactivation mechanism in OTA by neutral metalloendopeptidase triggers the catalytic action of the Zn that attacks the carbonyl of the amide group in OTA, resulting in α-ochratoxin and β-phenylalanine as final products .Molecular dynamics showed that metalloendopeptidase–OTA complex maintained stable interactions throughout the 100 ns; , despitep ≤ 0.0001; F = 464; p ≤ 0.0001; t = 7.07; DF = 12); at pH 5 in 14.44% ; at pH 7 in 45.26% . The final product was identified unequivocally as α-ochratoxin ; however, hydrolysis per cent was low. Since bromelain is a cysteine/thiol-type enzyme containing a Cys–His catalytic dyad, this group of proteases is generally cut from the left side . Thus, cThe results demonstrated that trypsin was effective in hydrolysing OTA at pH 4.6. Since chick’s intestinal pH is acidic, our results suggest that trypsin may be able to hydrolyse OTA in vivo, although OTA’s degradation percentage was below 20%. The only previous study in which OTA hydrolysis using trypsin was evaluated at pH 7.5 and 25 °C, found no OTA hydrolysis . Future Bacillus sutbtillis was able to degrade OTA in acidic and neutral pH conditions. Similar values have been previously reported for other metallopeptidases such as carboxypeptidases, from Bacillus amyloliquefaciens [Bacillus sutbtilis in this study, degraded OTA at pH 5, it was greater at pH 7, which agrees with those found for a carboxypeptidase by Abrunhosa et al. (2006) [Results showed that the neutral metalloendopeptidase from efaciens  and fromefaciens  where OTefaciens ,27. Alteefaciens , in whic. (2006) . This stResults showed that the final OTA metabolite was α-ochratoxin as a product of the reaction in the three tested enzymes. OTA’s enzymatic detoxification could be achieved by the hydrolysis of either: (i) the amide bond to generate α-ochratoxin, and L-phenylalanine by using an amido-hydrolase, or (ii) the lactone ring by using an ochratoxin-lactonase ,19,24. HiK) when compared with the tested ligands (T-2 and OTA). This molecule is an inhibitor by nature, due to its relatively small size, its phenyl and carboxylic acid groups, and the fact that at pH 7 it gets deprotonated. Such traits allow it to easily enter the catalytic site, where its deprotonated carboxylic acid group can perfectly coordinate with the zinc metal ion [Further, the (2S)-2-methyl-3-phenylpropanoic acid DB07673), the chosen reference ligand for the neutral metalloendopeptidase protease docking, had the highest affinity  and chain A was selected. Neutral metalloendopeptidase B (nprB) was modelled by homology using as template, neutral metalloendopeptidase C (Bacillolysin) from Bacillus cereus (PDB ID: 1NPC). Filling missing amino acids and homology modelling were performed in SwissModel® . Homology modelling were performed using enzymes own sequence . Energy minimisation was performed using Chimera 1.16® (https://www.rbvi.ucsf.edu/chimera) [®  and Unipro UGENE v45.0 [The protein structure of the cysteine protease from Ananas comosus  and the serine protease from bovine  were obtained from the Protein Data Bankchimera) . Ramachandex.php . Structu 2022; ® . Multipl 2022; ®  using ClNE v45.0 .Analyses were performed in Autodock Vina ,80, Swis7 iterations was used for Autodock Vina and AutoDock 4.2. [iK) was calculated in Autodock4, where smaller values indicate a higher ligand affinity for the protein. Images were performed in Discovery Studio® [® [Molecular docking was performed by using blind and directed approaches. Blind docking was used to explore binding sites in the whole crystal to identify or discard putative allosteric binding sites using a grid box of 120 × 120 × 120 Å. Directed docking was used to evaluate ligand interactions directly in the ligand binding site of each protein, and a grid-box of 60 × 60 × 60 Å was centred on the site where their reference ligand was removed from the crystallised protein. While a Lamarckian genetic algorithm with an initial population of 100 random individuals and 1 × 10ock 4.2. , an “accock 4.2. . Ligand  Studio®  and PyMOudio® [® . To valiTo perform the equilibrium molecular dynamics (EMD), files from Autodock 4 tool ligand–protein complexes (.pdb) were prepared using Visual Molecular Dynamics software (VMD v.1.9.4). A water box 10 Å spaced from the protein edge was constructed. The potential CHARMM36m was used to represent the molecules’ force field , and theAnanas comosus , trypsin from bovine (Sigma®), or neutral metalloendopeptidase from Bacillus subtilis , OTA pure standard 100  and 150 (mM) phosphate buffer. For all tested enzymes, assays were performed at pH 4.6, 5 and 7, at 41 (°C) and the incubation period lasted 60 (min). Tubes were centrifuged at 18,000× g for 2 (min). T-2 (1000 µg/Kg) was only tested with trypsin under the same experimental conditions as OTA.Control tubes consisted of pure mycotoxin standard 100 (µg/Kg) and phosphate buffer with a final volume of 1 (mL). The OTA detection limit was 14.11 (µg/L), and the quantification limit 23.45 (µg/L). Tested tubes, contained a mixture with a final volume of 1 (mL) containing 20 (mg) of the enzymes, either bromelain from Initial OTA quantification was assessed using a reverse phase with an HPLC (Agilent Technology 1100 series) coupled to a fluorescence detector , at an excitation wavelength of 345 (nm) and an emission wavelength of 455 (nm). A column DISCOVERY C-18  was used at a temperature of 25 (°C). The mobile phase consisted of acetonitrile: 0.25 N phosphoric acid (50:50). The run was isocratic with a constant flow of 1 (mL/min). Data collection was done by FL Winlab . Samples were injected in triplicate and chromatograms were compared with those of their own control.m/z), OTA and α-ochratoxin, respectively. The total range examined was from 100 to 1000 (m/z). Samples were injected in triplicate and data were registered with the acquisition software Mass Hunter Workstation LC/MS Data Acquisition version B.05.01.To identify final metabolites, when the tested enzyme significantly reduced OTA in samples compared with their own control, a reverse phase HPLC–ESI–TOF–MS (High Pressure Liquid Chromatography–Electrospray-Time of Flight–Mass spectrometry) was used, in positive ion mode, using an Agilent 1260 Infinity HPLC system equipped with a C-18 column ; 1.8 Micron  at a temperature of 25 (°C). The mobile phase consisted of water: formic acid (1%) and acetonitrile: formic acid (1%) with a flow rate of 0.15 (mL/min) and an injection volume of 40 (µL). The HPLC was coupled to a TOF/MS (Agilent 66230B) with an electrospray interface . Gas temm/z) and 442.24 (m/z) for HT-2. The total range examined was from 100 to 1000 (m/z). Samples were injected in triplicate. Data were analysed in the Mass Hunter Data Acquisition software for 6200 series  and Qualitative Analysis .T-2 quantification was carried out by reverse phase HPLC–ESI–TOF–MS, in a positive ion mode using an Agilent 1260 Infinity HPLC  system equipped with an RRHD Eclipse Plus C-18 column ; at 25 (°C). The mobile phase consisted of (A) ammonium acetate (10 mM) and (B) HPLC-grade methanol. The gradient started with 80 (%) A and 20 (%) B. Flow rate was set to 0.15 (mL/min) and 40 (µL) for the sample injection volume. The HPLC was coupled to an Agilent 66230B TOF/MS with an electrospray interface. The gas temperature was at 350 (°C), gas flow 6 (L/min) and nebuliser pressure 50 (psig), shredder 105 (V), skimmer 60 (V) and Oct RF 750 (V), capillary voltage 4000 (V). The final precursor ion for T-2 was identified at 484.25 .To determine whether differences in OTA and T-2 concentrations (µg/L) exist between control and tested tubes under different pH and temperature conditions, one-way multiple analysis of variance (ANOVA) was performed, followed by Sidak’s post hoc tests ,91. A p Bacillus sutbtilis neutral metalloendopeptidase has a great effectiveness as an OTA bio detoxifier, confirming α-ochratoxin as a final product of the enzymatic reactions and providing real-time practical information on OTA degradation rate.Overall, this study provides consistent in silico and in vitro evidence, that bromelain and trypsin are capable of hydrolysing OTA in acidic pH conditions at a low efficiency; The


SLC19A3 plays an ill-defined role in the maintenance of tissue thiamine, thiamine monophosphate, and thiamine diphosphate (TDP) levels. To evaluate the impact of THTR2 on tissue thiamine status and metabolism, we expressed the human SLC19A3 transgene in the intestine of total body Slc19a3 knockout (KO) mice. Male and female wildtype (WT) and transgenic (TG) mice were fed either 17 mg/kg (1×) or 85 mg/kg (5×) thiamine hydrochloride diet, while KOs were only fed the 5× diet. Thiamine vitamers in plasma, red blood cells, duodenum, brain, liver, kidney, heart, and adipose tissue were measured. Untargeted metabolomics were performed on the brain tissues of groups with equivalent plasma thiamine. KO mice had ~two- and ~three-fold lower plasma and brain thiamine levels than WT on the 5× diet. Circulating vitamers were sensitive to diet and equivalent in TG and WT mice. However, TG had 60% lower thiamine but normal brain TDP levels regardless of diet, with subtle differences in the heart and liver. The loss of THTR2 reduced levels of nucleic acid and amino acid derivatives in the brain. Therefore, mutation or inhibition of THTR2 may alter the brain metabolome and reduce the thiamine reservoir for TDP biosynthesis.The Thiamine Transporter 2 (THTR2) encoded by  SLC35F3 [SLC19A1 reported to transport TMP and TDP [SLC25A19 [SLC44A4 [SLC19A3 gene product THTR2 on thiamine status in multiple tissues.Thiamine, which is found in meats, grains, beans, and fortified products, is an essential nutrient for cellular functions. In the cell, this vitamin is converted to various derivatives including thiamine monophosphate (TMP) and thiamine diphosphate (TDP). Thiamine and TMP are influenced by recent exposure and are the main forms in plasma available for tissue uptake ,2, whereSLC35F3 , the red and TDP ,21, the SLC25A19 ,23, and [SLC44A4 ,25. Whil[SLC44A4 ,23,26,27[SLC44A4 . THTR2 , we inserted the human THTR2 gene SLC19A3 driven by the villin promoter into the THTR2 knockout  for intestine-specific expression. Murine and human THTR2 have differential affinity for inhibitors. For example, metformin and fedratinib are at least nine times more potent for the human THTR2 than mouse THTR2 [To probe the contribution of THTR2 for thiamine status in various organs, we took advantage of a transgenic mouse model created to explore drug–THTR2 interactions in the gut. For the generation of the transgenic mice  by Tissue lyserII , and total RNA was extracted with RNeasy Mini columns (Qiagen) according to the manufacturer’s instructions. Reverse transcription was performed using a High-Capacity cDNA Reverse Transcription Kit . Quantitative real-time PCR (qPCR) was performed using SYBR Green (Applied Biosystems) on an Applied Biosystems 7300 Real-Time PCR System. g and at 4 °C for 15 min, supernatants were collected, and the protein content was determined by Pierce BCA Protein Assay Kit (Thermo Fisher). Samples of 20 μg of protein were electrophoresed on precast Mini-protean TGX gels with 4–20% polyacrylamide , transferred to a low-fluorescence PVDF membranes (Thermo Scientific), and then blocked in Tris-buffered saline with 0.1% Tween 20 (TBS-T) supplemented with 5% non-fat dry milk at room temperature for 1 h. Membranes were incubated overnight at 4 °C with the 1:1000 dilutions of rabbit anti-SLC19A3 primary antibodies  in TBS-T supplemented with 5% non-fat dry milk, then washed with TBS-T and incubated with 1:2000 dilutions of secondary horse radish peroxidase conjugated goat anti-rabbit IgG . Signals were detected using the enhanced chemiluminescence SuperSignal West Femto Maximum Sensitivity Substrate detection kit (Thermo Fisher).Due to variability of the villin promoter on expression , hTHTR2 n = 12/group; 6 female, 6 male). KO were not viable on the 1× diet and thus the KO mice on that diet were omitted from the study. For 4 weeks, body weight and food intake were monitored weekly and body composition was determined every two weeks. After 2 h of fasting on the last day, mice were anesthetized by isoflurane and euthanized by exsanguination and cervical dislocation. Blood was collected in EDTA-coated tubes and centrifuged at 2000× g and 4 °C for 15 min for RBC and plasma separation. The two fractions were stored at −70 °C until analysis. Duodenum, brain, kidney, liver, heart, and retroperitoneal fat were snap-frozen and kept at −70 °C until analysis. Six animals from each of the five groups were analyzed for thiamine vitamers.The feeding study was conducted at the Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging in accordance with guidelines and regulations approved by the Institutional Animal Care and Use Committee of Tufts University. WT, TG, and KO littermates were cohoused and fed on an AIN93G-based high thiamine diet containing 85 mg/kg thiamine HCl  until 15–16 weeks of age. After a baseline body composition measurement via magnetic resonance imaging , animals were individually housed and randomized into two diet interventions: a standard 17 mg/kg thiamine HCl (1×) or 85 mg/kg thiamine HCl (5×) diets for 5 weeks (n = 11) from Charles River Laboratories . Prior to the intervention, mice were fed a low thiamine diet (5 mg/kg) for one week followed by a thiamine-deficient diet (0 mg/kg) for the second week. The mice were then fasted for 16 h before treatment. On the day of the study, the mice were orally gavaged with either 2 mg/kg thiamine  or a combination of 2 mg/kg thiamine and 61.5 mg/kg trimethoprim . The brains were collected 3 h post intervention for thiamine vitamer analysis.MuriGenics, Inc.  performed a thiamine–trimethoprim interaction study using 9- to 11-week-old (~20–25 g) FVB mice , supernatants were filtered under the same centrifugal force and temperature for 2 min. Filtered samples (10 µL) were then injected on a H-class Acquity UPLC  and separated with a 2 × 150 mm, 3 µm Luna Silica column attached to a 0.5 µm depth × 0.004 in internal diameter in-line KrudKatcher filter  at 35 °C. Mobile phases consisting of 0.1% acetic acid in water (A) and 0.1% acetic acid in acetonitrile (B) were flowed at 0.4 mL/min using the following gradient. The initial conditions of 2%B held for 0.5 min were increased to 13%B at 2.5 min and 100%B at 3.0 min. After a 1.5 min hold, the column was re-equilibrated for 2 min at 2%B. All the solvents and water were LC/MS-grade from Fisher Scientific , while solvent additives were from Sigma-Aldrich. On an API 4000 QTRAP , precursor-product mass transitions for thiamine (265.0 > 122.1 m/z) and thiamine-d3 (268.0 > 125.0 m/z) were monitored in positive mode. The temperature, ion spray voltage, gas1, and gas2 were set at 550 °C, 4500 V, 40 psi, and 40 psi, respectively. Thiamine was quantified in MultiQuant 3.02 (Sciex) using peak area ratios against a minimum 9-point calibration curve. The lowest calibration point contained thiamine-d3 to correct for background impurities. Two method blanks, three pooled mouse plasma, and three pooled human plasma were processed with experimental samples. Plasma thiamine was quantified using ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Briefly, in 1 mL polypropylene 96-well plates , plasma (10 µL) was spiked with 10 µL of 1 µM thiamine-d3  as an internal standard (ISTD) and diluted with 80 µL of chilled acetonitrile containing 0.1% acetic acid and 0.55 mM ammonium acetate. The plates were shaken for 1 min and centrifuged at 2247× 13C3 thiamine , and TDP-d3 . For the THTR2 inhibition study, only 30 mg of brain was used. Methanol (200 µL) was added for protein precipitation before homogenization on a 2010 Geno/Grinder vertical ball mill  for 1 min at 1300 rpm using a stainless-steel bead. The samples were centrifuged at 20,000× g and 4 °C for 15 min, and the resulting supernatants were dried under vacuum. After reconstitution in 0.5% aqueous formic acid, the extracts were filtered through 0.2 µm PVDF filter plates (Agilent Technologies) by centrifugation at 2247× g for 2 min. Brain, liver, heart, duodenum, and kidney samples were diluted 5-fold with 0.5% aqueous formic acid to capture analytes within their analytical curves. Ten microliters of extracts were injected on a Waters H-class Acquity UPLC connected to an API 4000 QTRAP (Sciex) mass spectrometer. Using a modified published method [m/z), TMP (345.0 > 122.1), and TDP (425.1 > 122.2), and their internal standards 13C3-thiamine (268.0 > 122.0 m/z) and TDP-d3 (428.1 > 125.2 m/z). For source parameters, temperature, ion spray voltage, gas1, and gas2 were set at 650 °C, 2000 V, 40 psi, and 40 psi, respectively. Quantification was performed using internal standard methodology and 9-pt calibration curves prepared daily with samples by serial dilution of primary stocks stored at −80 °C. A master mix containing 100 µM thiamine , TMP chloride dihydrate , and TDP (Sigma-Aldrich) in methanol and a ISTD mix containing 13C3-thiamine and TDP-d3 in water was diluted with 0.5% formic acid to result 2500 nM analytes, 30 nM 13C3-thiamine, and 400 nM TDP-d3 for diluted samples or 2500 nM analytes and 150 nM 13C3-thiamine and 2000 nM TDP-d3 for undiluted samples. The mix was then serially diluted 2–5x fold per step with ISTD in 0.5% formic acid to result the linear range of 0.5–2500 nM. A calibration solution containing only ISTDs was used as a zero point to correct for any native background in isotopically labeled compounds. Since isotopically labeled TMP was not commercially available, we evaluated TMP correction using either 13C-thiamine or TDP-d3. Using 13C-thiamine-based corrections yielded vitamer ratios more similar to reported fluorometric-based methods and were selected for reporting. Our vitamer values for plasma and tissue levels in WT mice were comparable to a prior study on total vitamers [For the feeding study, thiamine, TMP, and TDP in RBCs, brain, liver, heart, retroperitoneal fat, duodenum, and kidney were measured by UPLC-MS/MS. Briefly, ~15 mg RBCs, ~75 mg brain, ~35 mg fat, ~40 mg liver, ~25 mg heart, ~25 mg duodenum, or ~25 mg kidney, were enriched with 10 µL of a water containing d method , the ana 345.0 > 2.1, and To further investigate the effects of genotype on brain thiamine metabolism, we performed untargeted metabolomic analyses on brain samples from mice with similar circulating thiamine vitamer levels, namely WT and TG fed the 1× diet and KO mice fed the 5× diet. Brain cortices of 12 mice/group  were analyzed at the UC Davis West Coast Metabolomics Center . The samples were processed via established methods  using gav/v) acetonitrile: water. After centrifugation, the supernatant was dried under vacuum and stored at 20 °C until further processing. For GCMS on the day of analysis, residues were mixed with methoxyamine HCl in pyridine followed by treatment with N-methyl-N-trimethylsilyl-trifluoroacetamide and spiked with fatty acid methyl esters as a retention time reference. Metabolites were separated on a Restek Rtx-5Sil MS w/Integra-Guard column  in an Agilent Technologies 7890A GC, interfaced with a Leco Pegasus IV time of flight . For LCMS on the day of analysis, residues were reconstituted in 20% acetonitrile (100 µL) containing 35 deuterated ISTDs and 1-cyclohexyl-ureido, 3-dodecanoic acid (Sigma-Aldrich). Metabolites were separated on 1260 Infinity HPLC (Agilent Technologies) using a 2.1 × 150 mm, 1.7 µm Acquity UPLC BEH amide column (Waters Corp) attached to a 2.1 × 5 mm, 1.7 µm Acquity BEH amide guard column, interfaced with a QTOF 6600 (Sciex) mass spectrometer. Briefly, 4 mg brain cortex was ground, and proteins were removed via protein precipitation. Supernatants were split into aliquots for GCMS and LCMS analyses and dried under vacuum. Residues were reconstituted in 50:50  were performed in JMP Pro 16 . Random Forest (RF) analyses were performed in R version 4.2.2.Body weight, food intake, fat mass, and fat mass percentage were evaluated by sex using mixed model regressions with group and week by sex. Tissue weights of the liver, heart, kidneys, fat, and brain were compared separately by sex using ANOVA and Tukey’s Honest Significant Difference post hoc tests.p > 0.05). To test the impact of diet on tissue vitamer status, least square regressions were repeated, replacing plasma thiamine with diet as a categorical variable.Of the samples analyzed, one plasma sample from a 5× WT male mouse diet failed during extraction and was excluded from the group comparisons. Outliers identified in untransformed data by a robust fit outliers quartile test were treated as missing. Data normality was evaluated by Shapiro–Wilk tests and Log or Johnson transformed if required. Two data points, the above-mentioned plasma thiamine, and a single kidney TMP outlier from a 1× TG female mouse, were imputed using multivariate imputations. To compare the vitamers among the five groups, ANOVA and post hoc Tukey’s tests were performed. To evaluate variables affecting thiamine status between WT and TG mice, linear regressions were performed with genotype, sex, and plasma thiamine concentration and their interactions as fixed effects. Models were simplified in a stepwise fashion removing variables if the coefficients were not significant  were combined and analyzed in aggregate. Of the 1430 features found, 406 were annotated by library matches and separated from unknowns. Of 14,616 data points, 172 outliers (0.012%) were detected by robust fit Huber’s test and treated as missing in the annotated dataset. For each metabolite, data normality was assessed using Shapiro’s test for untransformed, log-, square root-, and Johnson- transformed data. If normality was not achieved, Box–Cox transformation was also attempted. Normality was achieved for 97% of the metabolites. Sixty-six duplicate metabolites with the higher %CV in pooled samples were removed resulting in a final dataset of 340 unique known metabolites. Data were then mean centered and scaled to achieve normal distribution with a mean of 0 and variance of 1. Prior to modeling, missing values were imputed via the singular variable decomposition method in JMP.p-values from the beta coefficients for genotype effect from regression models as well as fold changes of raw peak heights as input variables [To evaluate enrichment of chemical classes, ChemRICH was used to classify metabolites and to cluster them by chemical class using ariables .2 > 0.4 was considered to indicate full group discrimination, and variable importance in projection (VIP) scores >1.0 indicated discriminating variables. In addition, variable selection via random forest (RF) was performed using R package ranger to build 5000 trees without sample replacement [tuneRanger was used to determine the hyperparameters including minimum node size, number of variables considered at splitting points (mtry), and the sample fraction used to build the trees [p-values from 100 permutations were collected. A PLSDA-RF ensemble scoring system was created combining the two variable selection methods to identify top differentiating candidate metabolites as follows: (1) PLSDA VIP scores <1, 1–1.249, 1.25–1.49, 1.5–1.749, and >1.75 were assigned 0, 0.25, 0.5, 0.75, and 1, respectively; (2) permuted RF p-values <0.05, 0.051–0.1, 0.101–0.15, 0.151–0.2, and >0.2 were scored as 1, 0.75, 0.5, 0.25, and 0, respectively. If the importance value was 0 or negative, then the RF score was automatically made 0; (3) the PLSDA and RF scores were summed for a total score between 0 and 2.Metabolites differing between experimental groups were identified, and discriminating variables were scored using PLSDA and RF. To find differentiating metabolites between the three comparisons , PLSDA was performed using leave-one-out cross validation. A cumulative Qlacement ,43. Packhe trees . ImportaEvidence of THTR2 ablation, intestine-specific human THTR2 expression, and mouse THTR1 responses to genetic manipulation was obtained. qPCR showed that TG and KO had absent or lower expression of THTR2 in the brain and jejunum compared to WT . There wp = 0.051) and Tukey post hoc analysis indicated that the 5× WT were heavier than the 5× KO mice. However, this weight difference was not substantial as KO/WT ratios were 0.89 at week 0 and 0.89 prior to euthanasia. In addition, female WT in the 1× diet had greater %fat compared to the 1× TG and 5× KO mice. The (1× TG)/(1× WT) and (5× KO)/(1× WT) %fat ratios were ~0.67 and ~0.58. However, further analysis using 33 WT, 36 TG, and 18 KO mice under the 5× diet since birth showed no difference in body weight and body composition.For males, there were no differences in body weight, food intake, body composition, and the tissue weights of the liver, heart, kidney, retroperitoneal fat, and brain among the five groups of mice . In femaThe KO mice did not survive on the 1× diet. Plasma collected from a single deceased KO had 8.3 nM thiamine, ~25× lower than the WT on the same diet. Thiamine vitamers measured in plasma, RBCs, duodenum, brain, liver, kidney, heart, and retroperitoneal fat are reported in p < 0.0001; To determine the effect of the transgene expressed in the intestine, vitamers were compared in the duodenum and circulation. The TG mice were comparable to the WT mice for all three vitamers in the gut A, with tp < 0.0001) and KO  groups compared to the WT group (0.63 ± 0.07 nmol/g). Notably, the 5× diet did not rescue the brain thiamine levels in the absence of THTR2 expression. WT and TG brain thiamine vitamer concentrations were not influenced by dietary thiamine (p = 0.038) in the brain but had no effects on TMP and TDP  in WT and TG mice. While the diet did not change renal TDP in the WT groups, the TG group had 1.5× higher TDP in the 5× diet (34.88 ± 2.53 nmol/g) than the 1× diet . KO mice had lower renal thiamine, TMP, and TDP compared to the WT on the 5× diet and were comparable to the WT and TG on the 1× diet.In contrast to the brain, renal thiamine was strongly influenced by diet F. Specifp = 0.0058), while no differences were observed on the 1× diet . For WT vs. TG and WT vs. KO comparisons, metabolites with RF p-values < 0.05 had VIP score > 1.25. Variable selection outputs of PLSDA and RF for each of the comparisons are shown in In general, strong discriminating variables in RF were also identified as top hits by PLSDA, with RF Slc19a3−/− (KO) and Slc19a3SLC19A3int−/−-;  (TG) mouse models to probe thiamine status in various tissues. Since the TG model expresses the human THTR2 only in the intestine and maintains normal circulating thiamine, the model presents an opportunity to examine the influence of THTR2 on thiamine status in multiple organs of the mouse.Drug–nutrient interactions on thiamine status could be an important consideration when prescribing drugs that are inhibitors of thiamine transporters, such as trimethoprim and fedratinib ,32. WhilSLC19A3 expression rescued the low plasma thiamine levels found in KO mice under the standard thiamine diet. As previously reported [SLC19A3, the TG mice survived on a standard thiamine diet and had normal plasma thiamine.Intestinal reported , the KO reported . With thThe THTR2 deficiency had either no discernible or mild effects on several tissues. Among the tissues measured, retroperitoneal fat had the lowest concentrations for all three thiamine vitamers, and no difference among the five experimental groups. While THTR2 mRNA is high in fat , the HumIn the current study, the TG mice on the 5× diet had slightly lower hepatic thiamine compared to WT but no difference between groups on the 1× diet. The role of THTR2 in maintaining hepatic thiamine status appears to be minor as compensation by other transporters largely overcame its deficit in the current mouse model. The nonspecific cation transporter OCT1 is highly expressed in the liver and may account for this protection . HoweverAmong the investigated organs, the brain was the most impacted by the loss of THTR2. As brain thiamine uptake and turnover rates are similar, the organ has a low thiamine reserve in the case of inadequacy . Comparep = 0.067) [Similar to THTR2 ablation, administration of the THTR2 inhibitor trimethoprim also reduced brain thiamine. Our recent study investigating the impact of trimethoprim on thiamine disposition showed that elevations in plasma thiamine was accompanied by a decline in hepatic thiamine (= 0.067) , likely = 0.067) ,55 as TD= 0.067) ,56.To probe the impact of THTR2 loss on brain metabolism, we compared metabolomic profiles from the cerebral cortex of WT, TG, and KO mice with equivalent plasma thiamine concentrations. The results showed reduced nucleic acid and amino acid derivatives, possibly due to various mechanisms including TDP-independent functions of thiamine or its derivatives, as well as other metabolic consequences resulting from alterations in endogenous THTR2 substrate concentrations. Though the metabolic functions of some thiamine derivatives, such as thiamine triphosphate (TTP) and adenosine TTP, are poorly characterized, changes in these thiamine products are unlikely to explain the observed metabolite profile changes as they are derived from TDP . In addiSLC19A3 results in the rare biotin–thiamine-responsive basal ganglia disease. This disorder is distinguished by stress-triggered episodic encephalopathy, dystonia, ophthalmoplegia, and seizures, which can prove fatal without improvement [Future studies should consider the benefits and drawbacks of utilizing this novel TG model. Although this model can be used to examine the impact of oral THTR2 inhibitors on intestinal thiamine absorption, it may not be optimal for evaluating the effects of these drugs on tissue status beyond the intestines. Additionally, the ramifications of the low brain thiamine levels should be investigated in the TG mouse subjected to physical, psychological, and/or hypermetabolic states. Since higher metabolic states increase thiamine demand, these animals may be less resilient during metabolic stress. Notably, clinical THTR2 dysfunction from various mutations in rovement . While trovement . FurtherOur study has a few limitations. The brains of the TG mice were profiled at ~21 weeks and the mice themselves were kept no longer than 8 months so developmental and long-term effects of reduced brain thiamine in the TG model are unknown and may include compensatory mechanisms or a health deterioration over time. While previous investigation on the KO model showed premature death at one year , it is uIn conclusion, our findings suggest that THTR2 is irreplaceable for maintaining brain thiamine levels. As a significant transporter for thiamine distribution, THTR2 should be taken into consideration for drug–nutrient interactions, not only for gut absorption and renal elimination, but also uptake into tissues, especially the brain where inhibition can lead to localized deficiency and altered metabolism.