Trypsin-like proteases are synthesized as zymogens and activated through a mechanism that folds the active site for efficient binding and catalysis. Ligand binding to the active site is therefore a valuable source of information on the changes that accompany zymogen activation. Using the physiologically relevant transition of the clotting zymogen prothrombin to the mature protease thrombin, we show that the mechanism of ligand recognition follows selection within a pre-existing ensemble of conformations with the active site accessible (E) or inaccessible (E*) to binding. Prothrombin exists mainly in the E* conformational ensemble and conversion to thrombin produces two dominant changes: a progressive shift toward the E conformational ensemble triggered by removal of the auxiliary domains upon cleavage at R271 and a drastic drop of the rate of ligand dissociation from the active site triggered by cleavage at R320. Together, these effects produce a significant (700-fold) increase in binding affinity. Limited proteolysis reveals how the E*-E equilibrium shifts during prothrombin activation and influences exposure of the sites of cleavage at R271 and R320. These new findings on the molecular underpinnings of prothrombin activation are relevant to other zymogens with modular assembly involved in blood coagulation, complement and fibrinolysis. Members of this family participate in physiological processes such as digestion, blood coagulation, fibrinolysis, development, fertilization, apoptosis and immunity2. Nearly all of them are expressed as inactive zymogens that are irreversibly converted to the mature protease by proteolytic cleavage at an Arg residue in the activation domain3. The cleavage generates a new N-terminus that inserts into the protein and H-bonds to the side chain of the highly conserved D194 (chymotrypsinogen numbering). This interaction organizes the architecture of the entire active site, especially residue G193 in the oxyanion hole and the catalytic S195, and prepares the enzyme for substrate binding and catalysis5. The Huber-Bode mechanism of zymogen activation in the trypsin family described above is one of the most enduring paradigms in protease biology3. It rationalizes the onset of biological activity and is particularly useful in the interpretation of the initiation, progression and amplification of enzyme cascades7. The paradigm has also fostered the notion that activity associates with the protease (or protease-like states) and inactivity with the zymogen (or zymogen-like states)5. Yet, a number of zymogens spontaneously autoactivate11 or can be engineered to do so13 and a number of proteases are inactive unless bound to cofactors15. The zymogen may therefore access states featuring some level of activity, or protease-like, and the protease may assume conformations that are poorly active, or zymogen-like. These observations suggest that zymogen and protease are best described as points along a trajectory that connects active and inactive states within an ensemble of possible conformations. The exact active:inactive distribution along the trajectory describes the properties of zymogen and protease depending on biological context.The trypsin family of proteases is widely distributed in nature and constitutes a significant component of a typical genome5. A survey of high resolution (<3 Å) structures of proteases and zymogens currently deposited in the Protein Data Bank (PDB) documents multiple conformations for this segment, even in the same crystal18, that directly influence access to the active site20. Specifically, the Cα-Cα distance between the highly conserved residues G193 in the oxyanion hole and G216 in the 215–217 segment spans the range 7–13 Å and defines the aperture to the primary specificity pocket that requires >8 Å to ensure ligand binding to the active site. The structures in the PDB likely are snapshots of the active site region as it assumes conformations within the ensemble that either allow (E) or disallow (E*) binding as a necessary step for catalysis19. Structural evidence from the PDB is compelling but provides no proof that alternative conformations of the active site do exist in solution, nor it quantifies the E*-E distribution which remains a challenging task for both protease and zymogen. NMR measurements are ideally suited to address this task, but have so far been limited to the more rigid bound forms of the protease24 and only offered speculations about the free forms. Recent theoretical investigations of ligand binding mechanisms27 have renewed interest in rapid kinetics as a strategy to detect conformational transitions and whether they precede and/or follow the binding step. Rapid kinetic measurements of ligand binding to the active site of the protease28 support a mechanism through which optimal conformations are selected from a pre-existing ensemble, which is consistent with the PDB scenario. Whether the same mechanism applies to the zymogen precursor of the protease remains to be established.The plasticity of the trypsin fold within the ensemble is supported first and foremost by X-ray structural biology. The 215–217 segment defines the west wall of the active site and provides anchor points for substrate residues immediately upstream of the peptide bond to be cleaved by the protease29. We take advantage of the modular architecture of prothrombin6 to explore how its auxiliary Gla domain and kringles influence long range the properties of the active site in the protease domain. The results define a strategy of general applicability to other trypsin-like proteases and zymogens involved in blood coagulation, complement and fibrinolysis.In this study we extend our recent investigation of ligand binding to the active site of thrombin by studying its zymogen precursor prothrombin and elucidate the contribution of the E*-E pre-existing equilibrium as the zymogen transitions to the protease along its two possible pathways of activation30. The Gla-domain confers the ability to bind to phospholipids on platelets, red blood cells and the endothelium, thereby localizing and enhancing activation of the zymogen for biological response. The kringles provide additional surface for interaction with the protein components of prothrombinase  when prothrombin is converted to the active protease thrombin in the penultimate step of the coagulation cascade. The conversion involves two proteolytic cleavages at R271 and R320 that shed the Gla domain and two kringles and generate thrombin as a free protease domain. Cleavage at R271 sheds the Gla domain and both kringles to generate prethrombin-2, a direct zymogen precursor of thrombin from which it differs only in the intact activation domain. Cleavage at R320 generates the active intermediate meizothrombin that retains the modular organization of prothrombin but with the active site folded for catalysis as described by the Huber-Bode mechanism. The conversion of prethrombin-2 to thrombin involves only the protease domain. The conversion of prothrombin to meizothrombin involves the entire modular assembly. Analysis of these reactions by rapid kinetics of ligand binding to the active site affords a unique opportunity to explore the role of the pre-existing E*-E equilibrium during zymogen activation, with or without the presence of auxiliary domains.Prothrombin, or coagulation factor II, is composed of 579 residues and has a modular assembly Fig.  that com1) and hyperbolically (α2) with the ligand concentration. In principle, this kinetic profile is consistent with the scheme in eq. 27. However, measurements with excess macromolecule28 have already resolved this potential ambiguity in favor of the scheme in eq. k12 = 16 ± 1 s−1 and k21 = 3.8 ± 0.8 s−1, with a resulting E*:E ratio of 1:4  = 45 ± 5 s−1, defining the smaller between koff or the sum k12 + k21, and −1, with a resulting E*:E ratio ≥6:1 (Table k21being ≥10-fold higher in the zymogen. Access to the active site opens at the same rate (k12) in prothrombin and thrombin, but closes at a ≥10-fold faster rate (k21) in the zymogen. Ligand dissociation from the active site is ≥75-fold faster in prothrombin compared to thrombin. A lower estimate of the rate of ligand association is derived from analysis of FPR binding at equilibrium  for prethrombin-1 and ≥1:2 (k21 ≥ 100 ± 10 s−1) for prethrombin-2  or R320 (meizothrombin pathway). Consequently, the auxiliary domains of prothrombin control the E*-E equilibrium in the zymogen but play little role upon activation. The value of ligand dissociation drops drastically upon activation and is influenced little by the presence of auxiliary domain.Activation of prothrombin to thrombin organizes the active site region and promotes catalysis. The changes envisioned by the Huber-Bode mechanism of activationion Fig. . Togethe32. The rate of proteolytic digestion of prothrombin by subtilisin is significantly enhanced in the presence of the active site inhibitor argatroban , which houses the cleavage site at R155 for generation of prethrombin-129, has different exposure to solvent in the E* and E conformations. The observation confirms the role of the flexible Lnk2 in making the overall structure of prothrombin very dynamic with kringle-1 and the protease domain coming into transient intramolecular interaction, as unraveled recently by X-ray crystallography and single molecule spectroscopy35. The effect of argatroban on subtilisin digestion of prethrombin-2 is much less pronounced than that of prothrombin and practically absent in thrombin  used as active site ligand. FPR was purchased from Bachem.Prothrombin wild-type and mutants R271W and R320W, prethrombin-1, prethrombin-2, meizothrombin and thrombin were expressed as previously describedBacillus licheniformis (Sigma) at 1:1000 (w/w) ratio, in 10 mM Tris, 145 mM NaCl, 5 mM CaCl2, pH 7.4 at 37 °C, in the absence or presence of the active site inhibitor argatroban (500 μM). Aliquots of proteolysis mixtures were quenched whit NuPAGE LDS buffer and analyzed by non-reducing SDS-PAGE (4–12% acrylamide). None of the gels were cropped and originals are available in the Supplementary Information. The relative intensity of intact protein gel bands, after Coomassie staining, was estimated by densitometric analysis and fit to single exponential decay over time.Proteins (0.1 mg/ml) were reacted with sequencing grade chymotrypsin (Promega) at 1:50 (w/w) ratio or with subtilisin from 2Cl, for which detailed structural information exists on its interaction with the active site of thrombin61. Rapid kinetics of FPR binding were studied using an excitation of 295 nm and a cutoff filter at 320 nm. Baselines were measured by mixing the protein into buffer in the absence of ligand. Each kinetic trace for a given ligand concentration was taken as the average of a minimum of six determinations. Traces were fit to single or double exponentials based on the analysis of residuals using software supplied by Applied Photophysics.Rapid kinetic experiments were conducted on an Applied Photophysics SX20 stopped-flow spectrometer under conditions of excess ligand. The dead time of the mixing cell for this instrument is 0.5–1 ms. Final concentrations of 50–75 nM of thrombin and meizothrombin, or 200–400 nM of prothrombin, prethrombin-1 and prethrombin-2 were used in a buffer containing 400 mM ChCl, 50 mM Tris, 0.1% PEG8000, pH 8.0, at 15 °C. The solution containing the protein was mixed 1:1 with 60 µL solutions of FPR in the same buffer. FPR is the cleavable analog of the irreversible active site inhibitor H-D-Phe-Pro-Arg-CH27. and is briefly summarized below for the sake of completeness. The relevant kinetic scheme for ligand binding to the active site of a trypsin-like protease or zymogen iskon. Under conditions where L is in large excess over the macromolecule, the reaction scheme in eq. A detailed discussion of ligand binding mechanisms established by rapid kinetics is given elsewhereα1, always increases and eventually grows linearly with [L]. Depending on the sign of the expression α2 hyperbolically decreases  (Table α2 increases hyperbolically with [L], as seen for prethrombin-2 (Fig. koff and the upper limit, k12. When α2 is independent of [L], as seen for prethrombin-1 (Fig. α2 is accessible to experimental measurements, estimation of the E*:E ratio requires additional information from the apparent equilibrium dissociation constantResolution of all four independent rate constants in the reaction scheme in eq. n-2 Fig. , only a bin Fig. , the E*:n-2 Fig. , the lown-1 Fig. , then \dKd, and the E*:E ratio Kd,app can be obtained by fluorescence titrations under the same experimental conditions used for stopped-flow measurements. The definition of Kd,app in eq. α2 decreases hyperbolically with [L] as in the case of prothrombin (Fig. α2 increases hyperbolically with [L] as in the case of prethrombin-2 (Fig. α2 is independent of [L] as in the case of prethrombin-1 (Fig. kon from which the value of k21 and the E*:E ratio can be arrived at with the help of eq. kon to arrive at the value of k21. In both cases, a lower limit for kon is estimated as defined in terms of the intrinsic equilibrium dissociation constant, bin Fig. ,5\documen-2 Fig. , and6\don-1 Fig. . The expRecombinant reagents and data presented in this study are available from the corresponding author upon reasonable request.Supplementary Information


The symptoms of their toxicity to insects and the rapid knockdown effect suggest neurotoxic action, but the precise mode of action and the molecular targets for decaleside action are not known. We have presented experimental evidence for the involvement of sodium pump inhibition in the insecticidal action of decaleside in the cockroach and housefly. The knockdown effect of decaleside is concomitant with the in vivo inhibition of Na+, K+ -ATPase in the head and thorax. The lack of insecticidal action by experimental ablation of tarsi or blocking the tarsal sites with paraffin correlated with lack of inhibition of Na+- K+ ATPase in vivo. Maltotriose, a trisaccharide, partially rescued the toxic action of decaleside as well as inhibition of the enzyme, suggesting the possible involvement of gustatory sugar receptors. In vitro studies with crude insect enzyme preparation and purified porcine Na+, K+ -ATPase showed that decaleside competitively inhibited the enzyme involving the ATP binding site. Our study shows that the insecticidal action of decaleside via the tarsal gustatory sites is causally linked to the inhibition of sodium pump which represents a unique mode of action. The precise target(s) for decaleside in the tarsal chemosensilla and the pathway linked to inhibition of sodium pump and the insecticidal action remain to be understood.Decalesides are a new class of natural insecticides which are toxic to insects by contact  In view of the environmental and ecological concerns, human health hazards, and increasing insect resistance, many insecticides have been banned or replaced by newer chemicals . Mode ofDecalepis hamiltonii (Wight and Arn.) that are toxic to several insect species by contact with the tarsal gustatory sites but not toxic by oral or topical application [Drosophila [Recent addition to the natural insecticides are decaleside I and II, novel trisaccharides isolated from the roots of lication –21. Thislication . In inseosophila –24. Ther+, K+ -ATPase, or sodium pump, is a transmembrane ion motive enzyme most important in cellular ion regulation and maintenance of membrane potential by regulating the movement of Na+ and K+ ions across the cell membrane [+, K+ -ATPase, a highly conserved heterodimeric protein consisting of alpha and beta subunits with a transmembrane segment and the subunits combine to give tissue specific isoforms of the enzyme [+ efflux, Na+ influx and membrane depolarisation [Chondria armata was extremely toxic to cockroach when injected [in vivo inhibition of Na+, K+ -ATPase in decaleside-treated insects, which led to the present study wherein we present experimental evidence that Na+, K+ -ATPase (sodium pump) is involved in the insecticidal action of decaleside in insects, which leads us to postulate novel mode of action for these unique natural insecticides.Namembrane –28 whiche enzyme –30. The risation –35. Receinjected  suggestiDecalepis hamiltonii as reported earlier [The purified enzyme, sodium potassium adenosine triphosphatase , adenosine triphosphate (ATP), bovine serum albumin (BSA) and Ouabain were purchased from Sigma chemical Co., . Other chemicals were purchased from Sisco Research Laboratory Mumbai, India. Decaleside I and II were isolated and characterized  from the roots of  earlier .Musca domestica) were reared in a mixture of sterilized bran, milk powder and water, and the adults were allowed free access to water and thick paste of condensed milk and milk powder [Blatella germanica) was reared in plastic tubes with harborages, with dry food (biscuits) and water provided ad libitum [. Insect cultures were maintained at 25.0 ± 2.5°C and 70% RH with a photoperiod of 12:12 (L: D).Housefly  were determined from the dose-response data using probit regression analysis [Knockdown effect, defined as the state of intoxication and partial paralysis with lack of movement which usually precedes death by exposure to decaleside I and II, was investigated in contact bioassays using adults of the cockroach and housefly. A 1 ml solution (in methanol) each of the decalesides containing known concentration of the compounds was applied on Whatman No.1 (9cm) filter paper and placed in a glass Petri dish and the solvent was allowed to evaporate for 10 min under airflow with a fan, followed by the release of 10 adult cockroaches or 20 houseflies into each dish. The control filter paper discs were treated with the solvent only. Methanol as solvent was chosen for the ease of evaporation. Each treatment consisted of four replicates. The knockdown of insects was recorded after 45 min exposure. The dosages ranged from 0.004 to 0.272 mg/cmanalysis .2) solutions (1ml) were sprayed on to filter paper and the control groups received only the solvent as described earlier. The solvent was allowed to evaporate for 10 min followed by the release of 10 unsexed adults of B. germanica and M. domestica separately into glass petri dishes (9cm diameter) at 25.0 ± 2.5°C. Four replicates were used for each dosage. Effective dosage for 50% knockdown effect (KD50)  was determined from the dose-response data using probit regression analysis [Decaleside I and II . The number of insects knocked-down was recorded for 0–60 min exposure.Cockroaches or houseflies (10 per replicate) were released into Petri dish containing decaleside treated filter paper at KD25, KD50, and KD90 doses of decaleside I and II were determined by exposing the insects (cockroach and housefly) for 45 min in contact bioassay. In the case of houseflies, the head and thorax were frozen for the enzyme assay, whereas, for cockroaches, the brain  and the coxal muscle were dissected out and used.Dose-response study: The KD50 dose of decalesides in the contact bioassay and removed at various exposure time intervals . The tissues of the insects were dissected and assayed as described above.Time-course study: Insects were exposed to the KD+, K+–ATPase [2 (3mM), ethylenediamine tetra-acetic acid , to which the enzyme (50μl) was added with or without 1mM ouabain in a final volume of 1ml and pre-incubated at 37°C for 10 min. The reaction was started by adding 50μl of ATP (1.5mM), incubated for 30 min at 37°C and the reaction was stopped by the addition of 0.5ml of ice-cold 10% trichloroacetic acid and centrifuged at 5000 rpm for 10 min and the phosphate content (Pi) in the supernatant was estimated [The tissues were homogenised in 0.1M tris-HCl buffer (pH 7.4), and centrifuged at 10, 000 x g for 15 min at 4°C and the supernatant was used for the assay of Na+–ATPase . The reastimated . The enzRequirement of direct contact of decaleside with the tarsi in the legs for the insecticidal action has been experimentally demonstrated by surgical ablation of the tarsi or blocking by molten wax, as reported earlier . In ordeChemical and enzymatic hydrolysis of decaleside and its effect on insect toxicity has been described earlier . In thisSince some sugars interfere with the insect toxicity of decaleside, we undertook to study if it involves sodium pump inhibition. The contact bioassay procedures with or without sugars on the toxicity have been described earlier . The actIn vitro inhibition of the enzyme, Na+, K+ -ATPase by decalesides in the tissues of houseflies, cockroaches (crude preparation) and the purified enzyme  was studied. The enzyme was pre incubated with decaleside I and II (10μm– 1mM) at 37°C for 30 min, followed by the addition of 50μl of ATP (1.5mM), and incubated for 30 min at 37°C. The reaction was stopped by the addition of 1ml of ice-cold 10% trichloroacetic acid and centrifuged. Phosphate content in the supernatant was estimated [+, K+ -ATPase was determined. IC50 were calculated by regression analysis.stimated . The enzProtein content was measured by the method of Lowry et al.  using BS50 [The data was analysed using one-way Anova (p < 0.05) using Statplus 2007 software. The data was expressed as means ± SE. Probit analysis was used for calculating KD50 .+, K+ -ATPase activities in insects exposed to KD25, KD50 and KD90 doses of decaleside I and II was markedly inhibited in a dose-dependent manner in the housefly (head and thorax) (in vivo enzyme inhibition was dose-dependent and correlated with the knockdown effect measured at 45 min of exposure in the contact bioassay.Na thorax)  and cock thorax) . The in +, K+ -ATPase markedly increased with time in insects exposed to KD50 dose of decalesides , and closely correlated with the knockdown effect .Direct application of decaleside to the tarsi of the first pair of legs induced knockdown effect and caused enzyme inhibition in the cockroaches, whereas wax application on the tarsi protected against the toxicity and, there was no enzyme inhibition ..50 concentration of the hydrolyzed  decaleside II, there was no toxicity as evident from the absence of knock down. Also, there was no inhibition of Na+, K+ -ATPase in the brain of cockroaches showing correlation with lack of toxicity of the hydrolyzed sample of decaleside II  had no effect on the knockdown effect of decaleside II, which correlated with the lack of Na+, K+ -ATPase inhibition  of decaleside II correlated with inhibition of Na+, K+ -ATPase in the brain in vivo  shifted with the increased concentration of the inhibitors indicating that the inhibition was competitive as evident from the Lineweaver-Burk plot  exposed to decaleside I and II in the contact bioassay. The in vivo inhibition closely correlated (r = >0.9) with the knockdown effect of decaleside I and II in dose-response and time-course studies. The in vivo inhibition was seen in both head and thorax in the case of house fly and the nervous (ganglion) and muscle tissue in cockroaches exposed to decaleside. Further, experimental evidence shows that the inhibition of Na+, K+ -ATPase requires contact of the insect leg (tarsi) with insecticide treated surface, since no inhibition was seen in insects with tarsi ablated. The same was demonstrated with the application of wax on the tarsi, wherein toxic action of decaleside was abolished. In these experiments in which contact with tarsi for the insecticidal action of decaleside is required, also show concomitant inhibition of Na+, K+ -ATPase in vivo. The results lead us to conclude that tarsi-mediated insect toxicity of decaleside involves Na+, K+ -ATPase inhibition. Our results are the first report of a natural insecticide (novel trisaccharides) showing Na+, K+ -ATPase as the target in its mode of action. The molecular mechanisms involved in the insecticidal action of decaleside via the gustatory chemosensilla that lead to the knock-down effect, the toxic outcome finally leading to mortality, are not clear at present. Our results show that the insects exposed to decaleside, are initially hyperactive indicating neural excitation, which is followed by knockdown effect, symptoms somewhat similar to that of pyrethoids, suggesting a neurotoxic effect [+ concentration (step III) finally leading to knockdown effect and mortality. Electrophysiological evidence is needed to support this hypothesis.Our study has demonstrated that Nac effect –44. The c effect –47. In tin vivo. Whether specific gustatory receptor neurons mediate the action of decaleside action needs to be investigated.Our study shows that some of the sugars particularly maltotriose, a trisaccharide, interferes with the insecticidal activity of decaleside implying the involvement of sugar receptors in the gustatory chemosensilla which is also concomitant with the Na+, K+ -ATPase inhibition in vitro studies of Na+, K+ -ATPase from the insect tissues as well as the purified enzyme indicate that the inhibition is competitive type which suggests that decaleside is interacting with the ATP binding site of the enzyme. It is known that the ATP binding site of Na+, K+ -ATPase in the plasma membrane is interior to the cell unlike the ouabain binding site which is to the exterior [50 values for the in vitro inhibition of the insect enzyme versus the purified enzyme could be attributed to the crude enzyme preparation from insect tissue and it is not clear if the binding sites for decaleside on the enzyme are different. Future investigations on insecticidal action of decalesides targeting the gustatory (sugar) receptors and the neurons will open up a new field for scientific inquiry in order to unravel the mechanisms involved in their toxic action in insects. Decalesides, therefore, represent novel natural insecticidal molecules with a unique mode of action.Our exterior , 48–49. S1 FigA: % Knockdown. B: Dose-dependent in vivo inhibition of Na+, K+-ATPase in the cockroach by Decaleside II .(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 FigA) % Knockdown, B) Na+, K+ ATPase activity of decaleside II in Blatella germanica exposure at 1mg/leg (fore legs) by topical application . C) % Knockdown, D) Na+, K+ ATPase activity of decaleside II in Blatella germanica exposure at KD50 (0.07 mg/cm2) by contact bioassay .(TIF)Click here for additional data file.S4 FigA) Recovery from knockdown of decaleside I;B) Recovery of Na+, K+-ATPase inhibition . C) Recovery from knockdown of decaleside II;D) Recovery of Na+, K+-ATPase inhibition .(TIF)Click here for additional data file.S5 FigI) Control (no wax), II) Control (no wax) + decaleside II (1mg/insect), III) wax treated on tarsi (+ solvent), IV) with wax treated tarsi + decaleside II (1mg/insect) , One-way ANOVA, ***P < 0.001.(TIF)Click here for additional data file.S6 FigBrain: A, Decaleside I; B, Decaleside II. Coxal muscle: C, Decaleside I; D, Decaleside II.(TIF)Click here for additional data file.S7 FigA) Decaleside I; B) Decaleside II.(TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.


Following inflammatory stimuli, GSK3 inhibition functions as a hub with pleiotropic effects leading to cartilage degradation. However, little is known about the effects triggered by its direct inhibition as well as the effects on mitochondrial pathology, that contributes to osteoarthritis pathogenesis. To this aim we assessed the molecular mechanisms triggered by GSK3β inactivating stimuli on 3-D (micromass) cultures of human articular chondrocytes. Stimuli were delivered either at micromass seeding (long term) or after maturation (short term) to explore “late” effects on terminal differentiation or “early” mitochondrial effects, respectively. GSK3β inhibition significantly enhanced mitochondrial oxidative stress and damage and endochondral ossification based on increased nuclear translocation of Runx-2 and β-catenin, calcium deposition, cell death and enhanced remodelling of the extracellular matrix as demonstrated by the increased collagenolytic activity of supernatants, despite unmodified (MMP-1) or even reduced (MMP-13) collagenase gene/protein expression. Molecular dissection of the underlying mechanisms showed that GSK3β inhibition achieved with pharmacological/silencing strategies impacted on the control of collagenolytic activity, via both decreased inhibition (reduced TIMP-3) and increased activation (increased MMP-10 and MMP-14). To conclude, the inhibition of GSK3β enhances terminal differentiation via concerted effects on ECM and therefore its activity represents a tool to keep articular cartilage homeostasis. An intact ECM delivers survival signal to chondrocytes4 preventing β-catenin activation (dephosphorylation), its nuclear translocation and subsequent transcriptional activation of TCF/LEF complex.GSK3 is among the molecular constraints that keep chondrocytes in a “maturational arrested state”5. On the other hand, conditional complete ablation of β-catenin signaling pathway has been associated with cartilage degeneration in transgenic mice6, but due to a significant increase in articular chondrocyte apoptosis. Therefore, healthy articular cartilage requires an “housekeeping“ level of β-catenin signaling maintained via fine tuning of GSK34.The relevance of this mechanism in OA development has been pointed out by conditional activation of β-catenin in mouse articular chondrocytes, that led to cartilage destruction and accelerated progression towards terminal differentiation7 and signaling8 specific roles in the cells. Although both isoforms contribute to skeleton formation, GSK3β is the only GSK3 protein expressed in articular chondrocytes in healthy cartilage9. Moreover, findings of functional genomics studies on global knockout mice indicate that GSK3β10 plays a more important role in skeletal development compared to GSK3α11.There are two GSK3 isoforms, α and β, that despite some redundancy exert tissue12. In endochondral ossification, a number of different regulatory kinases affect GSK3β phosphorylation status and drive the process towards hypertrophy and terminal differentiation. Akt has been reported to regulate skeletal development through GSK3, mTOR and FoxOs13. In growth plate undergoing endochondral ossification, the inactivating GSK3β phosphorylation is instead due to cGMP dependent protein kinase II responsible for chondrocyte hypertrophic differentiation14.Inhibition of GSK3α/β via serine 21/9 phosphorylation and subsequent β-catenin activation is a key event in chondrocyte differentiation in the context of endochondral ossification, a process that is recapitulated in OA. Indeed, Miclea and coworkers showed that, in rats, intra-articular injection of a selective GSK3 inhibitor induces OA changes in articular cartilage15. This enhanced ECM catabolism is likely due to increased activation/decreased inhibition of matrix degrading enzymes, despite differential effects on MMP gene and protein expression. In this context, the effects of inflammatory cytokines on ECM catabolism were worsened by the delivery of GSK3 inhibitors which conversely had been previously proposed as a potential therapeutic tool in OA18 because of their anti-NF-κB or p38 inhibiting activity18. Moreover, recent findings have pointed at a role of inhibition of “mitochondrial GSK3” in reactive oxygen species (ROS) generation, DNA damage and cell senescence in exponentially growing cells20. In this setting we had recently shown that GSK3 inhibition links oxidative damage, hypertrophy and senescence, mimicking the status of chondrocytes in cartilage of obese OA patients20.Recently, Litherland and co-workers have established that GSK3 inhibition, at the cross of several inflammatory networks, occurs following different inflammatory stimuli and is responsible for enhanced cartilage destruction in a murine DMM model21. Grown in micromasses, chondrocytes recover a healthy articular phenotype in few days and become surrounded by their native ECM22. Moreover, 3-D culture appears as a convenient surrogate for chondrocyte “maturation” that reproduces dynamically23 and is therefore suitable to evaluate the effects on cells and matrix protein of key signalling intermediates or culture conditions27. At first, we checked the differential expression of the α and the β isoforms in human articular chondrocytes grown in 3-D culture, since previous studies carried out with exponentially growing monolayer indicated the presence of both isoforms, almost equally expressed15. We then analyzed the effects of different GSK3β inhibitors on mitochondrial health , nuclear translocation of transcription factors pivotal for endochondral ossification, cell viability and global reprogramming of matrix degrading enzymes at transcriptional, translational and post translational level. Particularly we focused on the control of activation/inhibition of matrix degrading enzymes that ultimately drives endochondral ossification and its recapitulation in OA.Since GSK3β inhibition has been linked to ECM remodelling we aimed at analyzing its effects on several aspects of terminal differentiation using primary knee OA chondrocytes cultured in 3-D (micromasses) in order to improve the biological relevance of the findingsWe conclude that GSK3β activity is a requirement for a healthy articular cartilage since it impacts on chondrocyte viability, mitochondrial function and ECM integrity and therefore is a fundamental factor for “maturational arrest” maintenance.All methods and experiments were performed in accordance with the relevant guidelines and regulations.20.GSK3 inhibition was achieved with 5 mM LiCl or 10 µM SB216763 or 33 nM insulin. Moreover, confirmation of the specificity of the effects was also obtained with small interfering RNA-mediated gene silencing of GSK3β, as in24. The GSK3β inactivating stimuli were either delivered “long term”  to test the effects on chondrocyte hypertrophy and terminal differentiation or “short term”  after micromass maturation to evaluate early effects. Micromasses were then used for immunohistochemistry or immunofluorescence, western blot or real time PCR or mineralization assays essentially as described in24. Some samples were instead employed for live sample imaging as described below. Supernatants were collected either in regular medium or after an overnight starvation in order to avoid serum interference on electrophoresis and/or enzymatic activity assessment.After approval of the Ethics Committee of Rizzoli Orthopaedic Institute and patients’ informed consent, primary chondrocytes isolated with sequential enzymatic digestion were obtained from 20 OA patients undergoing knee arthroplasty, and seeded in 3-D (micromass) culture essentially as described in28. Signals were revealed with ECL Select kit  as in20. Moreover, we tested the effect of the GSK3β inactivating stimuli on both isoforms using the anti-phosphoGSK3α/β antibody . In some experiments GSK3β phosphorylation was also assessed by mean of an anti-phosphoGSK3β rabbit monoclonal antibody  used as in20. Anti-GAPDH  served as loading control.The expression pattern of the two GSK3 isoforms was investigated by means of western blot analysis using an anti-GSK3α/β antibody . Protein lysates corresponding to half micromass or 150000 cells of exponentially growing monolayer were loaded and processed as described in29. Change in MitoTracker staining was investigated exploiting the use of Light Sheet technology (Zeiss) that allows for “live” sample imaging of almost the entire samples30. Hoechst 33342 was used as general counterstaining, while nuclei of dead cells, unable to exclude the dye, were stained by mean of Sytox Green.A first investigation was performed using MitoTracker dye , applied at 200 nM in serum-free medium (30 min at 37 °C) to viable micromasses established with cells of two different patients and treated with GSK3β inhibiting stimuli. The staining intensity of this probe has been shown to sensibly and reliably evidence changes in transmembrane potential as well as increased generation of ROSROS generation was assessed by using MitoSox probe for superoxide (Invitrogen), essentially as indicated by the manufacturer and exploiting flow cytometric detection with a FACSCanto II (Becton Dickinson). Live cells were obtained by mild enzymatic digestion of micromasses treated with GSK3β inactivating stimuli for 16 hours. Each condition was carried out in triplicate and the experiments were run with cells from three different patients. Half of the cells derived from each micromass were used as a background fluorescence control and subtracted from MitoSox fluorescence to obtain the Mean channel of Fluorescence intensity Increment (MCFI).31.Overlapped signals of MitoTracker Orange CMTMRos and LysoTracker Green (Invitrogen) were evaluated by Light Sheet technology in live micromass samples to assess occurrence of mitophagy32, in conjunction with the dead cell staining ethidium homodimer.A confirmation of ROS generation leading to cell damage and death was obtained by staining the samples with 30 µM 2′,7′-Dichlorofluorescein diacetate (DCHF-DA), a robust indicator of generalized oxidative stress33. The extent of mitochondrial oxidative damage at 16 hours stimulation was investigated by mean of staining of 8-oxo-dG (Trevigen), a well known oxidative damage marker34, performed by immunohistochemistry and image analysis of the samples, essentially as described in35. Mitochondrial localization of 8-oxo-dG was confirmed by combining the immunofluorescent staining of 8-oxo-dG (detected by an Anti-Mouse Alexa Fluor 555) with that of the mitochondrial marker Tom20 , thus yielding an orange signal. A 3-D reconstruction of one representative cell for each condition was undertaken and a quantitative colocalization analysis carried out using the overlap coefficient K2, in order to compare the different culture conditions.MitoTracker was also applied to micromass sections, exploiting its ability to bind heat shock proteins that increase after mitochondrial activation20. 2 µl of the extract were diluted with PBS to the volume of 75 µl, joined to the same volume of substrate and left to incubate for 30 min. Then the luminescent signal was detected with a Tecan M200 luminometer.The consequences of mitochondrial oxidative stress following GSK3β inhibition achieved by either pharmacologic or silencing strategies were investigated by mean of the luminescent assessment of increased activity of major initiator (caspase 8 and 9) and effector (3 and 6) caspases by using caspase-Glo reagents (Promega). To evaluate the extent of caspase activation, micromasses were lysed with 20 µl of RIPA bufferConfocal microscopy analysis of Runx-2 and β-catenin nuclear localization28. β-catenin translocation was also assessed after SB216763.Nuclear translocation of pivotal transcription factors (Runx-2 or β-catenin) following LiCl delivery was evaluated in 3 different experiments by confocal microscopy in 4% paraformaldehyde fixed 5 µm micromass sections, essentially as described inMineralization assays28. Micromasses were also scored for mineralized areas by alizarin red staining as previously described36.Changes in mineralization following either LiCl or SB216763 were quantified by mean of the Quantichrom DICA-500 assay (Bioassay Systems) as previously describedViability assayThe effects on terminal differentiation and viability of chondrocytes were evaluated with the Live & Dead viability cytotoxicity kit (Invitrogen), according to manufacturer’s instructions. Three different experiments of long term GSK3β inhibition were evaluated with NIKON confocal microscope system A1 with a z height of nearly 50 µm, while three additional experiments with micromasses exposed either short term or long term to GSK-3β inhibiting stimuli were analyzed with the ZEISS Light Sheet system. Nuclei were stained with Hoechst 33342.in situ with imunohistochemistry  coupled with image analysis as previously described35 since it corresponds to a membrane type MMP and therefore not released in the supernatant until lately. TIMP-3 was also assessed in situ , since it is the only TIMP to be sequestered to the extracellular matrix37.Supernatants of micromasses exposed to GSK3 inactivating stimuli were used to test the global effect of this treatment on the expression and activity of major collagenases. To this end we used the Human MMP panel 5-PLEX (Biorad) multiplex bead based sandwich immunoassay kit to simultaneously evaluate 5 different MMPs: the three collagenases MMP-1, MMP-8, MMP-13 and the two stromelysins MMP-3 and MMP-10. A further collagenase activator  was instead analyzed 20. Primers were as follows, with details of GenBank entries and primer pairing positions: GAPDH, NM_002046: forward 579–598 and reverse 701–683; MMP-1, NM_002021.3: forward 136–155 and reverse 304–285; MMP-8, transcript variant 1, NM_002424.2: forward 141–160 and reverse 329–310; transcript variant 2, NM_001304441: forward 141–160 and reverse 420–401 and transcript variant 3, NM_001304442: forward 141–160 and reverse 417–398; MMP-13, NM_002427: forward 496–511 and reverse 772–756; MMP-10, NM_002425.2, forward 1278–1298 and reverse 1472–1449; MMP-14, NM_004995: forward 3174–3193 and reverse 3375–3356 and TIMP-3, NM_000362: forward 1193–1210 and reverse 1313–1294.To detect the effects of GSK3β inhibition on global gene reprogramming targeted to ECM remodelling, micromasses underwent RNA extraction with Trizol (Invitrogen), reverse transcription and real time PCR analysis to evaluate change in gene expression of MMPs and TIMPs essentially as described inWestern blotting28. Signals were revealed with ECL Select kit  as in20.Western blot analysis was performed to detect MMP proteolytic processing. Protein lysates corresponding to half micromass were loaded and processed as described inMMP-13 was detected by a goat polyclonal antiserum (R&D) able to recognize the 60 kDa pro-enzyme, the 50 kDa intermediate active and the 48 kDa finally active form.At least 4 different experiments were carried out for each analysis. Anti-GAPDH  served as loading control.Collagen zimography38 using SDS-PAGE and 10% acrylamide gels containing either gelatin or collagen 1 or 2, to better characterize the type of proteolytic activity. 20 µl supernatant were loaded along with suitable molecular weight markers. Digestion time was 16 hours.Supernatants obtained in serum free conditions were tested by zymographyC1,2C immunohistochemistry35, carried out on samples from three different patients.Collagenase activation was also analysed by mean of immunohistochemistry of C1,2C  collagen neoepitopes coupled with image analysis20.To confirm the specificity of the effects observed following GSK3β pharmacological inhibition, experiments were also carried out using RNA interference (RNAi), as in48 hours after siRNA  delivery, chondrocytes were collected for evaluation of GSK3β knockdown (KD) and for micromass seeding. To confirm the findings obtained with wild type chondrocytes, control siRNA transfected chondrocytes were also stimulated with GSK3 inactivating stimuli at both short or long term.Immunohistochemistry coupled with image analysis was carried out to detect the effects on selected markers: 8-oxo-dG, MMP-10 , MMP-14, TIMP-3 and C1,2C.Parallel micromass samples were also dedicated for caspase activity analysis.All experiments were run at least three times or otherwise indicated.The graphs represent the cumulative analysis of experiments performed with cells from at least three different patients. All data are presented as mean ± standard error of the mean (SEM), analyzed and graphed using GraphPad Prism version 5.00 for Windows (GraphPad Software).Since comparisons were always carried out in order to compare each GSK3β inhibiting stimulus with the unstimulated condition we did not use statistical tests for multiple groups. Means of groups were compared with Student’s t test as detailed in the legend and considered significant when P < 0.05, with *P < 0.05; **P < 0.01; ***P < 0.001. Two tailed Student’s t test was used throughout. Correlation was tested by Pearson’s r.15. Indeed chondrocytes within 1 week micromasses almost only express the GSK3β isoform  with GSK3β inactivating stimuli showed markedly increased signal of MitoTracker Fig. , a probenal Fig. .Figure 139, and therefore expression of compensatory activities of the cells to protect themselves from oxidative stress following GSK3β inhibition.MitoTracker staining applied to micromass sections confirmed a higher staining with GSK3β inactivating stimuli, particularly in samples treated with SB216763 Fig. . As also41. A 3-D reconstruction of single cells showed that 8-oxo-dG signal was exclusively localized in the mitochondrial and not in the genomic DNA.The increased ROS production led to mitochondrial damage that activates mitophagy Fig.  as a comMoreover, a quantitative comparison of the intensity of colocalized pixels  and of caspase 8. The analysis was affected by a certain degree of variability, possibly due to the different extent of chondrocyte viability in the 3-D constructs. Yet, the cumulative analysis of the activities of the four caspases (21 samples) showed a very high level of correlation among CP6, 8 and 9  suggesting their interdependent activation downstream GSK3β inhibition. Although not significantly different, the GSK3β specific inhibitor SB216763 was the more effective stimulus for caspase activation see Fig. . The low3-D cultures were used to evaluate the effect of “long term” GSK3β inhibition on chondrocyte maturation across the chondrogenesis process to terminal differentiation.Confocal analysis indicated that nuclear localization of the hypertrophy marker and regulator Runx-2 was much higher in 5 mM LiCl treated micromasses. This led to increased nuclear translocation and therefore transcriptional activation of β-catenin. Comparable results were obtained with SB216763 .However, a strong activation of both MMP-10 and MMP-14 protein expression  was observed following both LiCl and SB216763 Fig. . MMP-104P-3 Fig. , the maj51, within the 3-D construct. The representative example in Fig. 25. However, only at 1 week the increased MMP-13 proteolytic processing was markedly associated to a strong increase in GSK3β phosphorylation in LiCl stimulated samples. GSK3α phosphorylation was only evident at 3 weeks but independently of the stimuli and rather indicating a progression in differentiation  and decrease in the major collagenase inhibitor (TIMP-3) thus leading to increased C1,2C accumulation Fig. .Micromass lysates were tested for the activity of major caspases. Specific silencing of GSK3β led to increased activity of all caspases tested Fig. .18 worsens murine OA15. Moreover, GSK3 inhibition is an event placed downstream many inflammatory stimuli15 or growth factors that signals via PI3K/Akt to inhibit GSK3 such as insulin, increased in insulin resistance and recognized as a major determinant of metabolic OA53 and mitochondrial dysfunction54. Noteworthy, fractionation studies indicated that GSK3 localizes in the cytosolic, mitochondrial and nuclear fraction, with different proportion depending on the cell type19. Inhibition of “mitochondrial GSK3” is responsible for increased ROS production and downstream effects on cellular senescence, as the result of mitochondrial complex IV defect19.Litherland and co-workers had recently pointed out that GSK3 inhibition, rather than being protective as previously suggested56 since ROS produced by dysfunctional mitochondria are able to boost cellular signalling and matrix catabolism55 thus leading to tissue derangement.Mitochondrial pathology has been recently recognized as having a pivotal role in OA20. Concerning articular cartilage, data derived from the different phenotypes of global GSK3-α or β knockout indicate a more pivotal role for GSK3β that is also selectively expressed in articular chondrocytes14. To approach in vitro the closest as possible the phenotype of articular chondrocytes in vivo we selected a 3-D culture model (micromass or pellet cultures)22 that more closely mimic the complex scenario of chondrocytes embedded in their native ECM57. In micromasses, chondrocytes recover in 1 week time a correct “healthy articular chondrocyte” phenotype. Indeed, the analyses carried out in these settings confirmed that the β isoform accounts for most of GSK3 expression and phosphorylation.We had already shown that mitochondrial activation and ROS production occur after GSK3β inhibition in primary chondrocytes cultured in “monolayer”, reproducing the phenotype observed in cartilage of obese patients where GSK3β phosphorylation overlaps with mitochondrial DNA damage, hypertrophy and senescence“per se” achieved with different stimuli and independently of other upstream inflammatory stimuli is sufficient to elicit mitochondrial activation, superoxide production and oxidative damage (8-oxo-dG staining) to mitochondrial DNA in 3-D culture of primary chondrocytes. This results in activation of initiator caspases 8 and 9 and effector caspase 6 and 3/7. These events are sufficient to increase nuclear localization of transcription factors  responsible for enhanced chondrocyte differentiation towards “endochondral ossification”. Indeed, we described an increased calcium deposition and “terminal differentiation” of chondrocytes as indicated by live and dead experiments carried out with Light Sheet technology, an advanced method of fluorescence microscopy, specifically developed for 3-D structure mapping of large samples58, a challenge that could allow to drive more relevant conclusions compared to conventional studies carried out in monolayer. These experiments indicate reduced viability at both “short term” and “long term” GSK3β inhibition.Then we tested the effect of GSK3β inhibition on chondrocyte differentiation using 3-D cultures of chondrocytes. GSK3β inhibition was achieved by mean of both pharmacological and RNAi approach. We provide evidence that GSK3β inhibition 2. Noteworthy, at the same time GSK3β inhibition increases the protein expression of major collagenase activators (MMP-10 and MMP-14) and reduces the expression of TIMP-3, the only one inhibitor that is effective on both aggrecanases and MMPs. Notably, functional genomic studies in KO mice had previously indicated the role of TIMP-3 in OA progression49.We also dissected the mechanisms whereby GSK3β inhibition leads to ECM remodelling. Overall, GSK3β inhibition achieved with either pharmacological or RNAi approach consistently impacts on the regulation of collagenase activity as shown by zymography or accumulation of the C1,2C neoepitope, a bioactive peptide able to further boost chondrocyte progression towards hypertrophy and endochondral ossificationThe concerted effect on collagenase activity observed with pharmacological inhibition of GSK3β using either specific (SB216763) or aspecific drugs  were fully reproduced by a RNAi approach, thus confirming that GSK3β is one of the molecular constraints that prevent the progression of articular chondrocytes towards terminal differentiation.In conclusion exploiting 3-D culture of primary chondrocytes we here demonstrate that GSK3β inhibition leads to a highly catabolic shift in protein expression and posttranslational processing, that through accumulation of bioactive collagen peptides boosts chondrocyte progression towards terminal differentiation, further sustained by accumulation of mitochondrial damage.Supplementary Figures


Animals living in complex environments experience differing risks of predation depending upon their location within the landscape. An animal could reduce the risk it experiences by remaining in a refuge site, but it may need to emerge from its refuge and enter more dangerous sites for feeding and other activities. Here, I consider the actions of an animal choosing to travel a short distance between a safe refuge and a dangerous foraging site, such as a bird leaving cover to visit a feeder. Although much work has been conducted examining the choice between a refuge and a foraging site when faced with a trade-off between starvation and predation risk, the work presented here is the first to consider the travel behaviour between these locations. Using state-dependent stochastic dynamic programming, I illustrate that there are several forms of optimal behaviour that can emerge. In some situations, the animal should choose to travel without stopping between sites, but in other cases, it is optimal for the animal to travel hesitantly towards the food, and to stop its travel at a point before it reaches the refuge. I discuss how this hesitant ‘dawdling’ behaviour may be optimal, and suggest further work to test these predictions. AnimaMany environments are heterogeneous, and an animal will experience differing feeding opportunities and levels of predation risk as it moves through the landscape –10. In sContinuously travelling back and forth means that an animal is spending periods of time neither in the safety of its refuge nor at a foraging site where it is able to replenish its diminishing energy reserves. The exposed region between the two sites is itself unlikely to be homogeneous in the risks that the animal will be exposed to ,9. Even I explore the decisions an animal makes during this travel period using stochastic dynamic programming –21, a te2.2.1.D units away from a safe refuge, separated by D − 1 exposed intermediate points. At any given moment in time t, the animal is found at location d (one of these D + 1 locations). Any changes to the environment or the animal occur at discrete time-steps. If the animal is in its refuge, it is presumed to be safe from predators, but if it is outside the refuge, there is a probability α that a predator appears during a time-step. If a predator has appeared, the animal is killed with probability π per time-step. If a predator appears, it is assumed that it will immediately pursue the animal until it has either escaped or been captured. The animal is therefore assumed to start to flee homeward in the next time period, moving one step closer to the refuge at each decision period until it has entered the refuge. The predator remains present in the environment until the animal has returned home, meaning that an animal that encounters a predator close to the refuge suffers fewer periods with the risk of being predated, when compared with an animal closer to the foraging site. Once the animal has returned home, the predator immediately departs. I note here that I am not considering predation risk as being different for a foraging animal and for a travelling animal . I also note here that because I am not explicitly modelling predator spatial location, I am therefore ignoring considerations about flight initiation distance [σ. A larger value of σ implies a higher risk of being predated with large energy reserves. So, if a predator is present, I consider the probability of an exposed individual being killed during a period to be π + σx2.An animal is assumed to exist in an environment consisting of a foraging site located distance –32. I dodistance , where idistance ), multipu, the distance moved towards the foraging patch): move one step towards the foraging patch; remain in its current location; or move one step back towards the refuge at d = 0. For most locations, all three of these behaviours are possible. However, if the individual is at the home location, it can only choose between u = 0 or +1, whereas if it is at the foraging patch, it can only choose between u = −1 and 0.If no predator is present in the environment during a time period (or no predator has yet appeared), the animal can choose between three options  of finding 0, 1 or 2 energy units of food when it is foraging). Because the model considers an individual that is assumed to be active within the environment, I assume here that it is metabolically active in this model regardless of whether it is moving or not, and it is assumed to have a mean metabolic rate κ0, κ1, κ2) of losing 0, 1 or 2 energy units in a period).The individual can only increase its energy reserves when it is at the foraging site, where it gains energy at a mean rate Given these assumptions, optimal policies were calculated using stochastic dynamic programming –21. Full2.2.t = 0 in the refuge d = 0, with initial energy reserves sampled from a uniform distribution of  energy units. The period's decision was taken from the optimal policy, and metabolic expenditure (and energy gain if appropriate) were randomly generated according to the parameters that generated the policy. In the forward simulations, predation did not occur, and so the forward simulations solely consider the behaviour of an animal following an optimal policy in a risky environment. Any deaths occurring are therefore due to the animal starving to death. The parameter space chosen was sufficient to ensure that most  of the individuals within each simulation set survived through to the end of their forward runs.For each optimal policy generated, sets of 1000 individuals were run independently through each policy for 20 000 time-steps. Each individual within a set started at Summary statistics were then calculated as the mean value of the following measures for each set of those individuals who were still alive at the end of a forward run. The two state values of each individual were tracked over time to calculate its mean energy reserves and proportional mean distance from the refuge, and its initial departure time was recorded as the period that it first moved away from the refuge. Once an individual had left the refuge for the first time, the time spent in the refuge after its initial departure was recorded for the remaining periods, as well as the number of visits made to the refuge and the length of each visit. Also recorded were the time spent foraging, the number of visits to the foraging site and the length of foraging episode , the time spent static when at an exposed location in between the refuge and foraging site, and the number of stays at exposed turning points . If an individual was static during the last (20 000th) period of a simulation, additional periods were calculated solely to assess whether this was a minimum turning point or not—these additional periods did not contribute to any of the other metrics calculated.Individuals that are not at either the home site or the foraging site during a period are considered to be moving either outwards or homewards. An individual is classified as moving outwards if its last non-zero movement was towards the foraging site, and homewards if its last non-zero movement was towards the home site. These two classifications mean that individuals that have been static for one or more periods are still considered to be in directed transit, based on their last movement. The speed when moving towards and away from the foraging site of an individual are the proportion of those periods where the individual is classified as moving in a given direction where its location changes between consecutive time-steps.2.3.In total, 50 000 policies were calculated for independently generated parameter sets, as detailed in appendix B, keeping the foraging site at 80 units from the refuge. Models were coded in C++, using a Mersenne twister algorithm for random number generation.To examine the effects of distance, 5000 parameter sets were also generated, and policies were calculated for these while systematically altering the distance of the foraging site to be 20, 40, 60, 80 and 100 units from the refuge.ggplot2 [Fobs was calculated as the standard F-value from one-way ANOVA . Corresponding F-values were calculated for 10 000 complete permutations of the entire dataset, and from these sets the largest value was identified, denoted ‘F’max, corresponding to significance levels of α = 0.0001. Sensitivity analyses were also conducted exploring the interaction between the policy classifications and parameter values. The results of these are presented in the electronic supplementary material, figures S1–S11, but are not discussed in any detail here as the focus of this work is on the policy forms generated by the model.Using the three policy classifications described in the results section , summary statistics were explored and visualized using ggplot2  within Rggplot2 . To explggplot2 ,38. For 3.Optimal policies were generated when exploring the parameter space described. In all the policies , the ania), labelled a decreasing policy, the threshold describing the switch between behaviours falls monotonically as distance from the refuge increases. In the second (b), labelled an increasing policy, the threshold increases monotonically as distance from the refuge increases. Note that the example shown in figure 1b is an extreme example—not all increasing policies rise such that the threshold at foraging site is the maximum energy reserves. The final policy form, labelled an intermediate policy (figure 1c), has a non-monotonic threshold that falls and then rises again as distance from the refuge increases, giving an intermediate location where the threshold is lowest.Three forms of policy emerged from parameter exploration. In the first a, labelle second b, labella). This means that once the animal has reached the foraging site, it should build its energy reserves by staying for a number of periods before it moves off.In all the policy types shown, the animal should remain in the refuge if its energy reserves are above the threshold (shown by the yellow bar on the left side of each diagram). When the animal is at the foraging site, it should stay if its reserves are below the threshold, but it should be noted that for the decreasing policies, this switching threshold at the foraging site can be higher than the switching threshold at the location immediately before the foraging site , policies tended to be increasing . As environmental risk decreased, intermediate policies became more common , showing a peak in the proportion of policies produced at intermediate environmental risk levels. Although decreasing policies were never the most common policy in the parameter set explored, they did become gradually more common as risk was reduced .The form of policy seen was influenced strongly by the environmental predation risk, crosses, a. As envb), while increasing the mean cost c). The risk of being killed when a predator was present π had a subtler effect, with an intermediate maximum in the proportion of intermediate policies and an intermediate minimum in the proportion of decreasing policies at an intermediate value of π (d). Increasing the mass-dependent predation scalar σ led to an increase in the proportion of decreasing policies and a reduction in the proportion of intermediate policies (e). The proportion of increasing policies seen were little affected by changes in gain, cost or mass-dependent predation scalar , but showed a gradual increase with an increase in the risk of being killed when a predator was present (d).The other parameters explored had less pronounced effects on the proportion of each policy type seen. Increasing the mean gain policies b, while e effect c. The rilue of π d. Increapolicies e. The prn scalar b,c,e, bu present d.Fobs values obtained from resampling were much greater than the ‘F’max values from the sampled distribution , suggesting that policy type can have large effects on the behaviours being measured.For all the statistics calculated, the Animals following decreasing policies tended to spend a longer time at home before their initial departure, when compared to animals following increasing or intermediate policies , becauseIn comparison, animals following increasing policies showed much more time at the refuge, with all individuals returning at some point during the simulations, and spending a much longer time in the refuge per visit than returning individuals following decreasing policies . They spAnimals following an intermediate policy tended to show behavioural statistics intermediate between the decreasing and increasing policy behaviours, with their overall behaviour more closely matching the form of individuals following decreasing policies , with inD) meant animals tended to spend more time in the refuge during a visit (unless following a decreasing policy with a close foraging site), and tended to spend longer at the foraging site during a visit . Animals tended to stop less when travelling towards the foraging site .Changing the distance to the foraging site affected behaviour. 4.The model described here demonstrates that when we are observing the behaviour of an animal choosing to move between a refuge and a close foraging site, it may be optimal for an animal to be making decisions about its behaviour while travelling between these two locations. Dependent upon the form of policy followed, the animal may also show slow ‘dawdling’ behaviour on its way towards the foraging site , as is seen when policies show decreasing or intermediate forms. For the sake of describing the different forms of behaviour seen, I arbitrarily divided policies into three forms, but it may be more correct that they are seen as a continuum, where intermediate policies are similar to decreasing ones, as is evident from the similarity of the report statistics in The model suggests that in some cases (particularly for decreasing policies) it might be advantageous to remain part-way between the foraging site and the refuge, rather than returning completely to cover. Showing exposed turning points means that an individual does not have to travel the full distance between the foraging site and the refuge each time (saving time and energy), while keeping its minimum distance to the refuge suitably small to reduce its overall probability of being captured by a predator if one appears. Within the model, when the animal initially heads homewards after leaving the foraging site, it does not stop until it reaches a turning point. Because the optimal policy is fixed for an individual, the location of the turning point will depend upon both immediate metabolic expenditure and the energy gained in the previous foraging episode, both of which are stochastic. Empirically, this translates to uncertainty in both food supply and metabolic processes, and should be interpreted as an individual being expected to stop at some intermediate exposed location, rather than as an exact prediction about location (and the stuttering stop–start behaviour when moving back to the foraging location should be interpreted similarly). Furthermore, it is likely that stopping points will be heavily influenced by local environmental features . An animal in the wild may therefore be likely to follow a simpler heuristic than its optimal policy , such asDespite the potential ease of observing travel to a close foraging site, and the number of studies exploring this form of foraging behaviour . DirectThe model presented here considers a single forager in a simple environment where the forager is unable to influence how it detects and responds to the predator. The forager could show vigilance ,50, whicHere, I have described an optimal behaviour akin to latent approach behaviour as an optimal foraging strategy under the risk of predation. Similar patterns are seen in the cognitive sciences in response to a fitness-reducing factor. A slow approach behaviour could be construed as ‘wariness’ or ‘fearfulness’ by an observer ,60, and


Necroptosis, a regulated necrosis pathway mediated by the receptor-interacting protein kinases 1 and 3 (RIPK1 and RIPK3), is induced following spinal cord injury (SCI) and thought to contribute to neuronal and glial cell death. However, mechanisms leading to activation of necroptosis after SCI remain unclear. We have previously shown that autophagy, a catabolic pathway facilitating degradation of cytoplasmic proteins and organelles in a lysosome-dependent manner, is inhibited following SCI in rats. Our current data confirm that inhibition of autophagy also occurs after thoracic contusive SCI in the mouse model, as indicated by accumulation of both the autophagosome marker, LC3-II and autophagy cargo protein, p62/SQSTM1. This was most pronounced in the ventral horn neurons and was caused by rapid inhibition of lysosomal function after SCI. Interestingly, RIPK1, RIPK3, and the necroptosis effector protein MLKL also rapidly accumulated after SCI and localized to neurons with disrupted autophagy, suggesting that these events may be related. To determine if lysosomal dysfunction could contribute to induction of necroptosis, we treated PC12 cells and primary rat cortical neurons with lysosomal inhibitors. This led to rapid accumulation of RIPK1 and RIPK3, confirming that they are normally degraded by the lysosomal pathway. In PC12 cells lysosomal inhibition also sensitized cells to necroptosis induced by tumor necrosis factor α (TNFα) and caspase inhibitor. Imaging studies confirmed that RIPK1 partially localized to lysosomes in both untreated and lysosomal inhibitor treated cells. Similarly, we detected presence of RIPK1, RIPK3 and MLKL in both cytosol and at lysosomes after SCI in vivo. Furthermore, stimulation of autophagy and lysosomal function with rapamycin treatment led to decreased accumulation of RIPK1 and attenuated cell death after SCI. These data suggest that lysosomal dysfunction after SCI may contribute to both inhibition of autophagy and sensitize cells to necroptosis by promoting RIPK1 and RIPK3 accumulation. Because many pathways are involved, attempts at improving SCI outcomes by inhibiting specific types of cell death have been largely unsuccessful2. This has led to more recent proposals for use of drugs that target upstream changes involved in the initiation of multiple cell death pathways. This, however, will require identification and characterization of the upstream cellular events involved in control of multiple pro-death pathways during SCI secondary injury.One of the features of secondary injury following traumatic spinal cord injury (SCI) is progressive neuronal cell death. The mechanisms of this death are diverse and include necrosis, classical apoptosis, as well as caspase-independent regulated cell death pathways4. The upstream mediator of necroptosis, RIPK1, is a key regulator of the innate immune responses involved in both inflammation and cell death, thus may represent an ideal target for reducing both cell death and inflammation in the central nervous system (CNS)5. Activation of necroptosis has been shown to contribute to cell loss and tissue damage in neurodegenerative diseases affecting the spinal cord, such as amyotrophic lateral sclerosis and multiple sclerosis7. Recent data also demonstrate involvement of necroptosis in neuronal and glial cell death after SCI10, and that its inhibition can improve functional recovery in animal models of SCI11. However, the mechanisms leading to activation of necroptosis after SCI and its relationship to other cellular pathways in this context remain unknown.Necroptosis is a form of regulated necrosis activated downstream of the tumor necrosis factor receptor 1 (TNFR1), dependent on the activity of the receptor-interacting protein kinase 1 (RIPK1) and 3 (RIPK3) and mediated by the mixed lineage pseudo-kinase MLKL12. Inhibition of autophagy after SCI is particularly pronounced in the ventral horn motor neurons and contributes to endoplasmic reticulum (ER) stress induced apoptosis in these cells. Here we demonstrate that autophagy is similarly inhibited after SCI in a mouse model. Inhibition of autophagy flux is caused by a rapid decline in lysosomal function after injury, leading to accumulation of dysfunctional autophagosomes. Surprisingly, our data demonstrate that inhibition of lysosomal function also causes rapid accumulation of necroptosis mediators, RIPK1, RIPK3, and MLKL in neurons both in vitro and in vivo after SCI. These proteins accumulate both in the cytosol and at the lysosomes and can lead to cellular sensitization to necroptosis. Conversely, increasing function of the autophagy-lysosomal pathway in vivo can decrease necroptosis and general cell damage after SCI. These data point to a previously unexplored link between inhibition of the autophagy-lysosomal pathway and induction of neuronal necroptosis after SCI, and suggest improving lysosomal function as a potential multi-functional treatment after SCI.We recently demonstrated that contusive SCI in a rat model leads to inhibition of autophagy, a lysosome-dependent protein degradation pathway12. To determine whether this is also the case in mice, we assessed accumulation of autophagosomes and autophagy flux after thoracic (T10) contusive injury13. Western blot data demonstrated progressive accumulation of the autophagy marker microtubule-associated protein 1A/1B light chain 3-II (LC3-II) in the spinal cord tissue surrounding the injury site starting by 6 h  dramatically increased at late time points after injury (days 3 and 7). This reflects activation and proliferation of microglia and infiltrating macrophages after injury (data not shown)18. However, at early time points (1 and 6 h) after SCI we observed a slight decrease in levels of CTSD, indicating possible injury-induced decrease in lysosomal function 14. Four hour treatment led to inhibition of lysosomal function and autophagy flux and accumulation of both RIPK1 and RIPK3 proteins 23, we observed increased phosphorylation of mTOR target, the ribosomal protein S6, in the spinal cord tissue after SCI. Phospho-S6 was decreased in rapamycin-treated mice, confirming inhibition of mTOR  expression of RIPK1 occurred primarily in neurons, at later time points it localized to cells with activated microglia/macrophage morphology (data not shown). On the other hand, while RIPK3 and MLKL are required together with RIPK1 for necrosome formation and induction of necroptosis19, they are not involved in complex I/RIPK1 dependent NFκB signaling. Consistent with a function in neuronal necroptosis after SCI, both RIPK3 and MLKL accumulate rapidly in neurons and peak by day 1, the time of maximum cell death. Their levels decline by day 3. This is also consistent with the timing of lysosomal and autophagy dysfunction after SCI, which declines by day 3 and largely resolves within a week after injury.Consistent with the notion that lysosomal damage may specifically contribute to multiple mechanisms of neuronal cell death after SCI, in addition to the previously reported ER stress and apoptosis10 and that treatment with RIPK1 kinase inhibitor, necrostatin 1 (nec1), can improve cell survival and functional outcomes after injury11. However, the mechanisms leading to activation of necroptosis after SCI and its relationship to other cellular pathways are not clear. In particular, while accumulation of RIPK1, RIPK3, and MLKL after SCI has been noted and used as a marker of necroptosis8, the reasons and timing for the buildup of these proteins remained unknown. Necroptosis is activated following ligation of the TNFR1 receptor by TNFα and requires activation of RIPK1 and RIPK3 kinase activity and recruitment of MLKL to form necrosome19. No protein synthesis is necessary, and in fact, in many cell types necroptosis is specifically induced under conditions where protein translation is inhibited in order to suppress pro-survival function of NFκB3. Instead, RIPK1 protein recruitment to complex I versus complex II and necrosome is regulated by ubiquitination5. Ubiquitination also affects RIPK1 protein stability, which until recently has been thought to depend exclusively on proteasomal degradation. However, a recent report indicated that under at least some circumstances ubiquitinated RIPK1 and RIPK3 may be also degraded via lysosome-dependent pathway20. Consistent with the importance of this pathway in the CNS, our data suggest that lysosomal inhibition in vitro and in vivo specifically causes rapid accumulation of necroptosis mediators in neurons. Confirming the function of lysosomes in their degradation, RIPK1, RIPK3, and MLKL accumulate both in the cytosol and at the lysosomes. Therefore, our data support a model where under basal conditions lysosomal degradation keeps the levels of necroptosis mediators in neuronal cells low. When lysosomal function is impaired, such as after SCI, RIPK1, RIPK3, and MLKL accumulate, making the cells more sensitive to necroptosis.It has been previously demonstrated that activation of necroptosis contributes to neuronal and glial cell death after SCI27. However, we were not able to detect interaction of necrosome components with ATG5 either in vitro or in vivo (data not shown). Furthermore, our in vitro IF experiments indicated that RIPK1 colocalized primarily with LAMP1-positive lysosomes rather than with autophagosomes (data not shown). However, we cannot exclude the possibility that in addition to directly leading to accumulation of necroptosis proteins, lysosomal dysfunction after SCI can further potentiate necroptosis after SCI by causing accumulation of autophagosomes and thus providing additional platform for necrosome assembly. These mechanisms are not mutually exclusive and further experiments will be necessary to clarify their respective contribution.Our in vitro experiments indicate that lysosomal inhibition can lead to induction of necroptosis even in the absence of TNFα. Therefore, it is possible, that following lysosomal inhibition accumulation of RIPK1, RIPK3 and MLKL per se can lead to the formation of necrosome and initiation of necroptosis. It has been previously suggested that under some circumstances formation of necrosomes can occur on the surface of dysfunctional autophagosomes through interaction with the autophagy protein, ATG528. However, the mechanisms of this protection remained unclear. Interestingly, combined inhibition of mTOR and AKT but not either treatment alone, has been shown to suppress necroptosis in cultured cortical neurons29 and provide neuroprotection in a mouse model of traumatic brain injury (TBI)23. Our data indicate that inhibition of mTOR is sufficient to at least partially attenuate necroptosis after SCI. In addition to being directly involved in necrosome formation, RIPK1 has been implicated in regulation of autocrine production of TNFα through the Akt/mTOR/JNK pathway26. We did not observe any changes in either AKT or JNK activation following treatment with only rapamycin. Therefore, similar to TBI, inhibition of both AKT and mTOR may be necessary to cause downregulation of JNK and autocrine production of TNFα. We hypothesize that combination of Akt inhibitor and rapamycin treatment after neurotrauma may affect necroptosis by both suppressing accumulation of RIPK1 and other necrosome components, and by decreasing autocrine TNFα production and activation of necrosome assembly downstream of TNFR1 ligation.Our data point to the crucial role of lysosomal dysfunction as an early event contributing to propagation of secondary injury through induction of apoptosis and necroptosis. Consistently with the causative role of lysosomal dysfunction, treatment of SCI mice with the mTOR inhibitor and inducer of autophagy and lysosomal biogenesis, rapamycin, attenuated both inhibition of autophagy flux and accumulation of RIPK1. Treatment with rapamycin has been previously shown to confer neuroprotection and improve functional outcomes in rodent models of SCI28. Inhibition of autophagy/lysosomal pathway and activation of necroptosis have been shown to contribute to cell loss and tissue damage in other CNS trauma models, including traumatic brain injury31. Necroptosis is also involved in neurodegenerative diseases affecting the spinal cord, such as amyotrophic lateral sclerosis and multiple sclerosis7. As most neurodegenerative disorders, these diseases are also associated with defects in the lysosomal/autophagy pathway. Therefore, lysosomal dysfunction may contribute to induction and/or sensitization to necroptosis also in these diseases.Together our data suggest that, lysosomal function may be an important upstream cellular event involved in control of multiple pro-death pathways during SCI secondary injury, including inhibition of autophagy flux, activation of ER stress dependent apoptosis and sensitization to necroptosis. Thus, restoring or enhancing lysosomal function may represent an interesting intervention avenueGFP-LC3 autophagy reporter transgenic male mice15 were anesthetized with isoflurane and received T10 spinal contusions using the Infinite Horizon Spinal Cord Impactor (Precision Systems and Instrumentation) with a force of 60 kdyn, a moderate injury32. Bladders were manually expressed twice daily until a reflex bladder was established (7–14 d after SCI). The number of mice at various time points in each study is indicated in the figure legends. All procedures were performed under protocols approved by the University of Maryland School of Medicine Institutional Animal Care and Use Committee (IACUC).Adult male C57BL/6J mice  or n = 6) at a dose of 5 mg/kg based on prior investigation16. Mice of the control group (n = 6) were injected with the equivalent volume of vehicle. Animals were anesthetized and processed for western blot at 24 h after injury.Sham and SCI mice were assigned to a treatment group according to a randomized block experimental design. Rapamycin  was dissolved in DMSO and then diluted in vehicle containing 0.25% PEG400 and 0.25% Tween 80. The final concentration of DMSO was adjusted to 0.1%. Rapamycin was injected twice (5 min and 4 h post injury) intraperitoneally in treatment group . Samples were run on 4–20% SDS–PAGE , and transferred to PVDF membrane (Bio-Rad). Membranes were incubated with primary antibodies overnight, with HRP-conjugated secondary antibodies for 1 h, visualized using SuperSignal West Dura Extended Duration Substrate (ThermoFisher), and imaged with ChemIDoc TM MP system (Bio-Rad). The signal  was quantified by Image Lab software (Bio-Rad). Primary antibodies: LC3 , p62/SQSTM1 , CTSD , RIPK1 , RIPK3 , MLKL , β-Actin , Fordin/SPTAN1 , GAPDH , LAMP1 . Expression levels of the target protein bands were normalized to β-actin, GAPDH or LAMP1 , and expressed as a fold of sham control.Mouse spinal cord tissue (5 mm) centered on the injury site was lysed and homogenized in RIPA buffer (Sigma-Aldrich) supplemented with 1 × protease inhibitor cocktail (Sigma-Aldrich) and phosphatase inhibitor cocktail II and III (Sigma-Aldrich), sonicated and centrifuged at 20,000 × g for 10 min at 4 °C to pellet down the nuclei. Supernatants were sequentially centrifuged at 20,000 × g for 20 min at 4 °C to pellet the heavy membrane/crude lysosomal fractions and at 100,000 × g for 1 h at 4 °C to pellet light membrane fractions16. Both supernatant and suspended pellet fractions were re-centrifuged to minimize cross contamination from the different subcellular fractions. All pellets were re-suspended in homogenization buffer. Protein concentration was estimated using BCA reagent; samples were analyzed by western blot.Around 5-mm fragments of spinal cord tissue centered on the injury site or corresponding site in sham animals were collected from sham mice, and at 2 or 24 h after injury and homogenized in ice-cold buffered solution containing 0.32 M Sucrose, 10 mM Hepes and protease and phosphatase inhibitors. Homogenates were centrifuged at 800 × g for 5 min at 4 °C. Protein concentration was estimated by the BCA method; 50 ng of protein was used per assay. The CTSD and NAG assays were performed using a fluorometric assay kits  as per the manufacturer’s instructions16. Fluorescence released from the synthetic substrate was measured using fluorescent plate reader  at Ex/Em = 328/460 nm.Mice were anesthetized, perfused with ice-cold saline, and 5-mm spinal cord tissue surrounding the site of injury was dissected, homogenized in ice cold cell lysis buffer and centrifuged at 15,000 × 33. A 1.0-cm segment of spinal cord centered at the injury epicenter was sectioned at 20 µm thickness and thaw-mounted onto Superfrost Plus slides (ThermoFisher). Sections were blocked in 5% goat or donkey serum in PBS/0.025% Triton X-100, incubated with primary antibodies overnight and with secondary antibodies for 1 h. Cell nuclei were labeled with 4′,6-diamidino-2-phenylindole , slides were cover-slipped with an anti-fading medium . Primary antibodies: LC3 , p62/SQSTM1 , CTSD , RIPK1 , RIPK3 , MLKL , NeuN/RBFOX3 . Secondary antibodies: alexa fluor 488 goat anti-rabbit (Cat. No. A11034), alexa fluor 546 goat anti-mouse (Cat. No. A11030), alexa fluor 568 goat anti-guinea pig (Cat. No. A11075), alexa fluor 633 goat anti-mouse (Cat. No. A21052) and alexa fluor 546 donkey anti-goat .Animals were intracardially perfused with PBS, then with 4% paraformaldehyde33. Images from ventral horns of gray matter were acquired using a fluorescent Nikon Ti-E inverted or Nikon Ni-E upright microscope, at ×20 (CFI Plan APO VC 20 × NA 0.75 WD 1 mm) or ×60 (CFI Plan APO VC 60 × NA 1.4 Oil) magnification16. All images for each data set were acquired using the same parameters . All ×60 images were acquired as z-stacks and focused using Extended Depth of Focus (EDF) module of Elements software (Nikon). The background of each image was subtracted using background region of interest (ROI). All images were quantified in unbiased automated manner using custom macros in Elements: nuclei were identified using Spot Detection algorithm; cells positive for any of the immunofluorescence markers were identified using Detect Regional Maxima algorithm, followed by global thresholding. Number of positive cells was normalized to the total imaged ventral horn area (mm2). Intracellular puncta were detected using Spot Detection and normalized to the number of cells imaged. For each experiment data from all images from same region in each mouse was summed up and used for final statistical analysis. At least 500–1000 cells were quantified per mouse per experiment. All quantification was performed on original unedited images. For visualization purposes in figures only brightness and contrast were adjusted; all adjustments were applied to entire image area and equally to all panels in the same figure. In multi-color overlay images brightness of the DAPI channel was selectively decreased to allow better visualization of other channels.All images were acquired 0.5–1 mm rostral to the epicenter34. Rat embryonic neurons were extracted from embryo of female spraque-dawley rats  as described35. Neurons were maintained in neurobasal medium  with B-27, L-glutamine, penicillin and streptomycin and allowed to differentiate for 1 week prior to experiments. For western blot analysis, PC12 cells were seeded in 24-well plates at a density of 5 × 104 cells/well. After reaching 80% confluence (PC12 cells) or 1 week differentiation (neurons), cells were incubated with or without 100 μM chloroquine  or 100 nM bafilomycin A  for 4 h14, lysed in homogenizing buffer and analyzed by western blot. For immunofluorescence (IF) imaging cells were seeded on cover slips, treated as above, then fixed in 2% paraformaldehyde. Coverslips were blocked in 5% goat or donkey serum in PBS/0.025% Triton X-100, incubated with primary antibodies (same as for IHC) overnight and with secondary antibodies for 1 h. Cell nuclei were labeled with DAPI. Coverslips were mounted on slides with an anti-fading medium , then imaged and analyzed as IHC above12. For cell viability assay, PC12 cells were seeded in 96-well plates at a density of 5 × 103 cells/well. After reaching 80% confluence, cells were incubated with or without 50 μM Boc-D-FMK , 30 mM necrostatin-1 3, 20μg/ml cycloheximide , 100 μM chloroquine, 100 nM bafilomycin A, and recombinant rat TNFα  for 18 h. Cell viability was analyzed by CellTiter-Glo Luminescnet Cell Viability Assay kit  following the manufacturer protocol36.Rat pheochromocytoma PC12 cells  were maintained in F-12K nutrient mixture (1 × ) Kaighn’s modification with 5% fetal bovine serum , 10% horse serum (Gibco), penicillin, and streptomycinn” is the number of individual animals per group. The number of animals in all studies was determined by power analysis . Key experiments were repeated with independent groups of animals to ensure reproducibility. For in vitro cell based assays results are expressed as mean ± SD; “n” is the number of total replicates from at least three independent experiments. All statistical analyses were conducted using SigmaPlot, Version 12  or GraphPad Prism, Version 3.02 for Windows . One-way or two-way (cell death assay and in vivo rapamycin treatment) ANOVA followed by Bonferroni, Tukey’s or SNK t-test post-hoc test was used for parametric data. Kruskal–Wallis ANOVA based on ranks and Dunn’s post-hoc test was used for non-parametric data. For experiments with only two groups two-tailed unpaired Student’s t-test (parametric) was performed. A p value ≤ 0.05 was considered significant16.Unless indicated otherwise, all in vivo results are expressed as mean ± SEM, where “Supplementary Figures


Breeding dispersal is a key process of population structure and dynamics and is often triggered by an individual's breeding failure. In both colonial and territorial birds, reproductive success of conspecifics (RSc) can also lead individuals to change breeding sites after a failure on a site. Yet, few studies have simultaneously investigated the independent contribution of individual reproductive success (RSi) and of RSc on dispersal decision. Here, we develop a modeling framework to disentangle the effects of RSi and RSc on demographic parameters, while accounting for imperfect individual detection and other confounding factors such as age or dispersal behavior in the previous year. Using a 10‐year capture–recapture dataset composed of 1,595 banded tree swallows, we assessed the effects of nonmanipulated RSi and RSc on female breeding dispersal in this semicolonial passerine. Dispersal was strongly driven by RSi, but not by RSc. Unsuccessful females were 9.5–2.5 times more likely to disperse than successful ones, depending if they had dispersed or not in the previous year, respectively. Unsuccessful females were also three times less likely to be detected than successful ones. Contrary to theoretical and empirical studies, RSc did not drive the decision to disperse but influenced the selection of the following breeding site once dispersal had been initiated. Because detection of individuals was driven by RSi, which was positively correlated to RSc, assuming a perfect detection as in previous studies may have lead us to conclude that RSc affected dispersal patterns, yet our approach corrected for this bias. Overall, our results suggest that the value and use of RSc as public information to guide dispersal decisions are likely dictated by multiple ecological determinants, such as landscape structure and extent, if this cue is indeed used. We have been monitoring closely the breeding activities of tree swallows on the 40 sites since 2004 and had banded 1595 breeding females by 2012. In this article, we included birds recaptured until 2013. Each site comprised 10 nest boxes aligned along a single field margin and spaced by 50 m to prevent territorial competition. The first and last nest boxes were thus separated by 450 m, the approximate distance up to which tree swallows are assumed to forage during the chick‐rearing period  distributed within a 10,200‐km² gradient of agricultural intensification in southern Québec, Canada  of females annually) or produced an average of 4.23 ± 1.41 fledglings per year between 2004 and 2013  or to have dispersed (to change of site between two breeding seasons) even though an individual was not captured over two consecutive years , fidelity (F), transition between RSc (C), transition between RSi (I), and recapture (R). Although the ultimate parameter of interest was F, the other “nuisance” parameters were considered in the model because they could indirectly affect the estimates of F. The matrix for each type of parameters is detailed in Appendix t, it can return at t + 1 to the same site it occupied at t with probability (F), or disperse to another site with probability (1 − F). The model then estimates the probability (C) that an individual experiences different RSc between t and t + 1, or the same RSc between these two breeding occasions (1 − C). Note that C is independent of F because an individual can be faithful to a given site between two consecutive years while the RSc of that site can change. Similarly, the model goes on to estimate the probability (I) that an individual obtains a different RSi between t and t + 1, or the same RSi between the two breeding occasions (1 − I). In the last step of the transition between t and t + 1, the probability of being captured (R) or not (1 − R) at t + 1  tests to assess the potential nonindependence of capture events for each individual in our dataset . The overall lack of fit can be corrected in modeling, using the coefficient of overdispersion ĉ following Burnham and Anderson . Standarc; Burnham & Anderson, i (wi) having a structure already determined for all parameters  based on the QAICc and wi (≥0.01) of candidate models , RSi, RSc, or a combination of those as main effects or interactions, as well as the effects of time or age as main effects Appendix . For ins3SD) of 4.61 ± 0.78 nest boxes per site produced at least one fledgling on a yearly basis and between 38% and 53% of sites showed a bad RSc depending on year. RSc was strongly and positively autocorrelated across years (r = .70 ± 0.06). This result supports the assumption that RSc was predictable in space and time and thus could potentially act as a determinant of dispersal decisions in our system.Between 2004 and 2013, an average . Although no trap dependence was detected, a transience effect was found, especially for SY females . Because apparent survival was lower for SY than for ASY females , SY females were less likely to be recaptured than ASY ones. We corrected for the overall lack of fit by using a variance inflation factor ĉ = 1.94.Goodness‐of‐fit tests indicated a lack of fit of the general model that considered all transitions possible between states over time when fitted to the data  effect on F, and no time or age effects (Appendix 3.2.114) showed a QAICc 52.7 points lower than the constant model (model11). As expected, a female with a good RSi was recaptured with a higher probability (0.99 ± 0.00) than a female with a bad RSi (0.32 ± 0.06). These probabilities appeared constant across years (∆QAICc for model18 vs. model14 = 4.68).The model including an RSi effect (modelc for model22 vs. model20 = 12.26).The probability that an individual experienced a good RSc after having experienced a good RSc in the previous breeding seasons was (0.81 ± 0.03), which is nearly twice as high as the probability that it experienced a bad RSc given that it had experienced a bad RSc in the previous breeding seasons (0.44 ± 0.06). Time had no effect on this parameter . None of the models considered in that second round performed better than model55 (w55 = 0.36), thereby lending support to the parameter structure obtained for F in the first round. Few models obtained an empirical support equivalent  to that of model55  than faithful ones . On the other hand, when they had a bad RSi, they survived equally well  whether they had dispersed in the previous year or not . Although a time effect was included in a model selected for model averaging  than females with a bad RSi Figure . Althoug53) in the multimodel inference provided support for the hypothesis that dispersal probabilities are affected by RSi and that this effect depends upon the dispersal behavior of the female in the previous year  to 9.5 (=0.19/0.02) times more likely to disperse than females that succeeded at fledging at least one young, depending on whether they dispersed or not in the previous year, respectively . This definition can be an indicator of expected number of potential sexual partners and reproductive success, inasmuch as dominant or healthy individuals should tend to gather in good sites, but also provides information about expected levels of competition or other detrimental effects such as parasitism , and the distance to the nearest site averaged 7.3 ± 3.5 km, with potentially few alternative, natural or artificial breeding sites surrounding those provided by our nest box network . Moreover, the probability that a female bred on a good site then on a bad one in subsequent years was lower than the probability it consecutively bred on a good site . Analogously, the probability that a female bred on a bad site then on a good one was higher than the probability it consecutively bred on a bad site (0.56 vs. 0.44 ± 0.06). Also, females that settled on a site where conspecifics experienced a good success were twice as likely to have a good RSi as females that settled on a bad site. Such settlement patterns toward sites that produce the greater numbers of fledglings have been observed in other passerines . Dany Garant, Fanie Pelletier, and Marc Bélisle provided the financial support for field work and data collection. Blandine Doligez, Dany Garant, and Fanie Pelletier contributed to write the article. Click here for additional data file.