Promastigote forms of L. amazonensis were incubated with OA and UA for 24h, and effective concentration 50% (EC50) was estimated. Ultraestructural alterations in Leishmania amazonensis promastigotes after UA treatment were evaluated by transmission electron microscopy, and the possible mode of action was assayed through Annexin V and propidium iodide staining, caspase 3/7 activity, DNA fragmentation and transmembrane mitochondrial potential. The UA potential was evaluated in intracellular amastigotes, and its therapeutic potential was evaluated in L. amazonensis infected BALB/c mice. UA eliminated L. amazonensis promastigotes with an EC50 of 6.4 μg/mL, comparable with miltefosine, while OA presented only a marginal effect on promastigote forms at 100 μg/mL. The possible mechanism by which promastigotes were eliminated by UA was programmed cell death, independent of caspase 3/7, but it was highly dependent on mitochondria activity. UA was not toxic for peritoneal macrophages from BALB/c mice, and it was able to eliminate intracellular amastigotes, associated with nitric oxide (NO) production. OA did not eliminate amastigotes nor trigger NO. L. amazonensis infected BALB/c mice submitted to UA treatment presented lesser lesion size and parasitism compared to control. This study showed, for the first time, that UA eliminate promastigote forms through a mechanism associated with programed cell death, and importantly, was effective in vivo. Therefore, UA can be considered an interesting candidate for future tests as a prototype drug for the treatment of cutaneous leishmaniasis.Among neglected tropical diseases, leishmaniasis is one of the most important ones, affecting more than 12 million people worldwide. The available treatments are not well tolerated, and present diverse side effects, justifying the search for new therapeutic compounds. In the present study, the activity of ursolic acid (UA) and oleanolic acid (OA) were assayed in experimental cutaneous leishmaniasis ( Leishmania genus (Kinetoplastida: Trypanosomatidae) and transmitted to humans through the bite of insect vectors, such as Lutzomyia sp. and Phlebotomus sp. [Leishmania species, therefore a spectrum of clinical signs can be recorded, ranging from a single localized skin lesion, that can heal spontaneously, to multiple ulcerated or non-ulcerated lesions affecting skin and/or mucosa, and these types of lesions frequently require a more complex treatment [Leishmaniasis is an infectious disease caused by a protozoan belonging to the omus sp. . In the omus sp. . The cutreatment . Howeverreatment .V) are the first choice of treatment for leishmaniasis and were first introduced as trivalent antimonial (SbIII) [V shows milder effects [III is better known. So far, the most accepted hypothesis is that SbV acts as a pro-drug and upon administration in humans, a considerable fraction is reduced to its more toxic counterpart SbIII, thus causing parasite death. How this reduction occurs is unknown, however, it can be caused through enzymatic reaction or even mediated by plasma or cellular thiols present on the host’s cell phagosomes [Pentavalent antimonials (Sb (SbIII) . Althoug effects . Despiteagosomes .V treatments [Resistance to antimonial drugs was first observed in regions of Bihar—India , where reatments . The prieatments .Streptomyces nodosus. Amp B has replaced antimony treatment in some parts of India due to parasite resistance to antimonial. The treatment with Amp B is effective, since 99.5% of treated patients show no signs of parasites, moreover parasites from relapsing patients did not show resistance to Amp B [Amphotericin B (Amp B) is a polyene antibiotic first isolated in 1955 from to Amp B . In cellto Amp B . This into Amp B . As an ato Amp B . In the to Amp B . Based oLeishmania (Leishmania) major, L. (L.) donovani, L. (L.) infantum, L. (L.) amazonensis, L. (Viannia) braziliensis, L. (L.) mexicana and L. (V.) panamensis, suggesting that these classes of compounds present strong leishmanicidal activity [Plants possess different compounds known as secondary metabolites. These compounds are classified according to their biosynthetic origin, as terpenes, phenolics, and alkaloids, that plants produced in order to facilitate their interaction with the biotic environment . These cactivity , 26, 27.activity . These tL. donovani, L. major [L. (L.) amazonensis [L. (V.) braziliensis [Leishmania sp. In spite of that, there are not works dealing with their possible action mechanisms on Leishmania sp., and there is only one study assessing the leishmanicidal effect in vivo of a fraction enriched with OA and UA isolated from Baccharis uncinella [Leishmania sp. and the absence of studies assessing the therapeutical potential of OA and UA, the present manuscript aimed at analyzing the effect of these triterpenes on L. (L.) amazonensis cultured promastigote and amastigote forms, the mechanism of action of UA on L. (L.) amazonensis as well as the therapeutical effect of UA using the murine model of cutaneous leishmaniasis.The leishmanicidal effects of OA and UA already were evaluated against promastigote and/or intracellular amastigotes of the following species: L. major , 22, L. zonensis , L. (V.)iliensis , and thencinella . ConsideLeishmania (Leishmania) amazonensis (MHOM/BR/73/M2269) was kindly donated by Prof. Fernando Tobias Silveira, Evandro Chagas Institute, Pará, Brazil. This parasite was maintained as amastigotes in BALB/c mice, acquired from Medical School of São Paulo University, Brazil, that were maintained in appropriated conditions. Animal experiments were carried out using protocols approved by the Ethics Committee for Animal Experimentation of São Paulo University under the number CEP 067/14.All necessary permits were obtained for the described field studies. The State of São Paulo Research Support Foundation (FAPESP), Brazil, and the Brazilian National Research Council (CNPq) provided permits to collect plant material. The site of plant collection is privately owned by São Paulo University, where the authors carried out the plant collection. Procedures involving plant material were in accordance with proper guideline and the field studies did not involve endangered or protected species. 1H and 13C NMR spectra were recorded, respectively, at 300 and 75 MHz in a Bruker Avance III spectrometer using CDCl3 and DMSO-d6 (Aldrich) as solvent and internal standard. Silica gel  and Sephadex LH-20 (Aldrich) were used for column chromatographic separation, while silica gel 60 PF254 (Merck) was used for analytical TLC (0.25 mm). Amphotericin B  and Glucantime  were solubilized in sodium chloride 0.9% (w/v).Petiveria alliaceae (Phytolaccaceae) were collected in the city of São Paulo, SP, Brazil, in July/2013 and were identified by Dr. Euder G. A. Martins (IB-USP). Voucher specimen has been deposited at Herbarium of Instituto de Botânica-SEMA, São Paulo, SP, Brazil; under reference number PMSP8983.Leaves of P. alliaceae (18 g) were exhaustively extracted with hexane (10 X 200 mL) at room temperature. The combined organic fractions afforded, after removal of solvent under reduced pressure, 4.6 g of crude hexane extract. Part of this extract (3.2 g) was subjected to column chromatography (SiO2 gel) eluted with a crude solvent gradient of hexane/EtOAc (starting with pure hexane and finishing with pure EtOAc). Using this approach, were obtained 14 fractions (A–N). As fraction D (412 mg) displayed in vitro antileishmanial activity, this material was purified by column chromatography over Sephadex LH-20 with MeOH as the eluent. This second purification step afforded 111 mg of a mixture of triterpene acids. Purification by semi-preparative RP-18 HPLC, eluted with MeOH:H2O 95:5 (flow rate at 5 mL/min and detector at λ = 218 nm) yielded ursolic (31 mg) and oleanolic (45 mg) acids.Dried and powdered leaves samples of 1H NMR  δH: 4.89 , 4.06 , 1.87 , 1.68 , 1.61 , 1.52 , 1.31 , 0.80 , 0.63 , 0.58 . 13C NMR  δC: 178.7 (C-28), 138.6 (C-13), 125.0 (C-12), 77.3 (C-3), 55.4 (C-5), 53.0 (C-18), 47.3 (C-9), 47.5 (C-17), 42.1 (C-14), 40.5 (C-8), 40.2 (C-19), 40.0 (C-10), 39.7 (C-22), 39.6 (C-7), 39.5 (C-21), 39.4 (C-23), 38.8 (C-15), 36.8 (C-1), 30.7 (C-4), 33.2 (C-20), 28.7 (C-2), 28.0 (C-29), 27.4 (C-16), 24.3 (C-27), 23.7 (C-11), 21.6 (C-30), 17.5 (C-6), 17.3 (C-26), 16.5 (C-25), 15.7 (C-24).Ursolic acid (99.4% of purity determined by HPLC). 1H NMR  δH: 5.16 , 3.07 , 2.73 , 1.47 , 1.22 , 0.88 , 0.69 , 1.03 , 0.82 , 0.78 . 13C NMR  δC: 180.0 (C-28), 143.8 (C-13), 121.9 (C-12), 78.0 (C-3), 55.1 (C-5), 47.4 (C-9), 46.0 (C-19 and C-17), 41.6 (C-14), 41.0 (C-18), 39.2 (C-8), 38.6 (C-4), 38.4 (C-1), 36.8 (C-10), 33.8 (C-21), 33.0 (C-29), 32.6 (C-7), 32.3 (C-22), 30.6 (C-20), 28.1 (C-23), 27.5 (C-15), 27.0 (C-2), 25.8 (C-27), 23.5 (C-30), 23.2 (C-16), 22.9 (C-11), 18.2 (C-6), 16.9 (C-26), 15.7 (C-24), 15.2 (C-25).Oleanolic acid (99.9% of purity determined by HPLC). L. (L.) amazonensis parasite (MHOM/BR/73/M2269) was kindly provided by Prof. Dr. Fernando T. Silveira from the criobank of “Leishmaniasis Laboratory Prof. Dr. Ralph Laison”, Department of Parasitology, Evandro Chagas Institute, Ministry of Health, Belém, Pará, Brazil. The parasite was identified using monoclonal antibodies and isoenzyme electrophoretic profiles at the Leishmaniasis Laboratory of the Evandro Chagas Institute . This parasite was grown in Roswell Park Memorial Institute-1640 medium—RPMI 1640 , supplemented with 10% heat-inactivated fetal bovine serum, 10 μg/mL of gentamicin, and 1,000 U/mL of penicillin (R10) at 25°C. Promastigote forms in the stationary phase were used.http://www.cobea.org.br). The protocol was approved by the Committee on the Ethics of Animal Experiments of the Institutional Animal Care and Use Committee at the Medical School of São Paulo University (CEP 322/12). For all experimental procedure mice were anaesthetized with tiopental (1mg/200 μL).Six to eight weeks old female BALB/c mice were obtained from Medical School of São Paulo University. This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the Brazilian National Council of Animal Experimentation (L. (L.) amazonensis (2x107 promastigotes/mL) were incubated in 96-well culture plate in R10 medium with OA or UA in a range of 100 to 4x10-1 μg/mL. The standard drug Amp B was added in culture in the range of 1.0 to 4x10-3 μg/mL and Miltefosine in the range of 100 to 4x10-1 μg/mL. Negative control group was cultivated in medium and DMSO as vehicle solution (never exceeding 1% v/v). The parasites were incubated for 24h at 25°C. Then, the plate was washed with 200 μL of sodium chloride 0.9% (w/v) three times with centrifugation at 3000 rpm, 10 min at 4°C, followed by addition of MTT -2,5-diphenyltetrazolium bromide) (4 mg/mL). Four hours later, 50 μL of 10% sodium dodecyl sulfate (SDS) was added to each well. The plates were further incubated for 18h and read in ELISA reader at 595 nm. Effective concentration 50% (EC50) was estimated using Graph Pad Prism 5.0 software.Promastigote forms of 5 peritoneal macrophages from BALB/c mice were cultured in R10 medium with UA or amphotericin B (100.00 to 0.01 μg/mL). As negative control, macrophages were cultivated in medium and DMSO as vehicle solution (never exceeding 1% v/v). After 24h, cell viability was analyzed by MTT method. Cytotoxic concentration 50% (CC50) was estimated with Graph Pad Prism 5.0 software was used for plotting and statistic analysis. The index of selectivity was obtained through the expression:Approximately 2x10L. (L.) amazonensis (2x107 promastigotes/mL) were incubated in 96-well culture plate in R10 medium with the EC50 of UA for 24h, at 25°C. Control group was cultivated with medium and vehicle solution DMSO (never exceeding 1% v/v). The plate was centrifuged at 3000 rpm, 4°C, 10 min and washed three times with 200 μL of sodium chloride 0.9%. Then the pellets were ressuspended in glutaraldehyde 2% and incubated at 4°C, during 60 min. Parasites were post-fixed in 1% osmium tetroxide, and these materials were stained and block staining in 1% aqueous uranyl acetate overnight, dehydrated using alcohol. Then, samples were embedded in a polyester resin, thin sectioned with a LKB ultratome, double-stained by uranyl acetate and lead citrate (Ladd Research Industries), and examined with a Jeol 1010  transmission electron microscope (TEM).Promastigote forms of L. (L.) amazonensis (2x107 promastigotes/mL) were incubated in 96-well culture plate in R10 medium with the EC50 of UA for 24h, at 25°C. In addition, promastigote forms of L. (L.) amazonensis were also incubated with EC50 of hydrogen peroxide (5.8 μM) as an apoptosis inducer [In order to evaluate the pathway of programed cell death triggered by UA, modification in the pattern of phosphatidylserine, caspase 3/7 protease activity, genomic DNA fragmentation, and mitochondrial membrane potential were evaluated. To perform all these sets of experiments, promastigote forms of  inducer . ControlL. (L.) amazonensis promastigotes treated with EC50 of H2O2 were single stained with Anexin V (FITC) or PI and were used for cytometer adjusts. The samples were acquired in Fortessa II cytometer, and around 106 events were recorded. The data were analyzed in FlowJo 10, and parasites were characterized: 1) viable: Annexin V-/Pi-; 2) early stages of apoptosis: Annexin V+/Pi-; 3) late stages of apoptosis: Annexin V+/Pi+ and 4) other type of cell death: Annexin V-/Pi+.To analyze exposure of phosphatidylserine on membrane, parasites were stained with Annexin V (FITC) and PI according to manufacturer’s instructions (LifeTech). To analyze the involvement of caspase in cell death, caspase-3/7 protease activity was measured using the Apo-1 homogenous caspase-3/7 activity assay kit . The assay was done according to the manufacturer’s instructions. In this set of experiment, parasites were incubated with caspase substrate for 120 min and increase in the fluorescence was an indicative of substrate cleavage. Plates were fluorometrically read at excitation and emission wavelengths of 485 and 530 nm, respectively.To analyze the pattern of DNA fragmentation genomic material from pellets of treated and control parasites was purified using commercial kits (LifeTechnologies). The amount of DNA was quantified, adjusted to 50ng and applied into 1.5% agarose gel plus 0.001% of gel red . DNAs were subjected to electrophoresis in Tris-Borate-EDTA buffer for 2 h at 100V. DNA was then visualized under UV light.The mitochondrial membrane potential of treated and non-treated promastigotes was investigated using the JC-1  marker, according to the manufacturer´s instruction . Treated and control parasites were incubated with JC-1 and Hoeschst solutions for 15min, 25°C. Parasites were analyzed by High Content Analysis ImageXpress Micro high content screening system , and at least nine sites per well and three wells per treatment were acquired. The presence of JC-1 aggregates was determined using the transfluor MetaXpress software.5 macrophage) were cultivated in round cover slips in 24-well plate, followed by infection with L. (L.) amazonensis promastigotes at a ratio of 10 parasites per 1 peritoneal macrophage. Plates were incubated at 5% CO2 at 35°C. After 24h of culture, UA  and amphotericin B (0.1 μg/mL) were added. After 24 and 72h supernatants were collected and stored at −80°C for nitric oxide  and IL-10, IL-12 and TNF-α  quantifications, according to manufacturer’s instructions. Round cover slips from each experimental time-point were dried at room temperature, fixed in methanol, and stained by Giemsa. The Infection Index (II) was then estimated according to Passero et al 2015 [Peritoneal macrophages from BALB/c mice  amazonensis and five BALB/c mice received only sodium chloride 0.9% (w/v) under the same route . Twenty days after infection, L. (L.) amazonensis-infected BALB/c mice were divided into four groups: group # 1 was injected with the dose of 1.0 mg of UA by kg of body weight (mg/kg); group # 2 was injected with 2.0 mg/kg of UA, group # 3 was injected with 100.0 mg/kg of Glucantime [Twenty male BALB/c mice were subcutaneously infected into the right hind footpad with 10ucantime , groups The development of lesions in infected and treated groups was measured weekly after infection. The size of lesion was obtained from the difference between infected and uninfected footpads.The parasite load in the skin was determined using the quantitative limiting-dilution assay, as previously described . BrieflyThe results were expressed as the mean ± standard deviation of three independent experiments and the nonparametric Mann-Whitney U test was used to compare results among groups. Differences were considered statistically significant at 5% significance level (p<0.05). GraphPad Prism 5  was used to analyze the results.1H NMR spectra of purified compound displayed signals of olefin and carbinol hydrogens, respectively, at δ 5.16/4.89 (H-12) and 3.07/4.06 (H-3). These signals, associated with the presence of doublets at δ 2.73 (J = 4.0 Hz) and 1.87 (J = 3.4 Hz) are characteristic of H-18 of oleanane and ursane triterpenoid, respectively [13C NMR spectra showed signals attributed to olefin carbons at δ 121.9/125.0 (C-12), 143.8/138.6 (C-13), 78.0/77.3 (C-3) and 180.0/178.7 (C-28). The presence of these signals associated to those attributed to the methyl groups C-23 (δ 28.1/39.4), C-24 (both at δ 15.7), C-25 (δ 15.2/16.5), C-27 (δ 24.3), C-29 (δ 33.0/28.0), and C-30 (δ 23.5/21.6), allowed the identification of oleanolic and ursolic acids [Analysis of ectively . 13C NMRic acids , as indiL. (L.) amazonensis were treated with UA and OA as well as two standard drugs, amphotericin B and Miltefosine (L. (L.) amazonensis promastigote in a dose-dependent manner, showing an EC50 of 6.2 ± 1.8 μg/mL; on the other hand, OA presented only a marginal effect on promastigote forms, eliminating around 14% of parasites with 100 μg/mL. Both Amp B and Miltefosine eliminated promastigote forms in a dose-dependent manner, and the EC50 were 1.5 ± 0.5 μg/mL and 5.9 ± 1.8 μg/mL, respectively  amazonensis were treated with UA EC50 and H2O2 (positive control of apoptosis) and 24h later the mechanisms of cell death were evaluated. Control promastigotes , a small frequency of parasites was dead, being 5.4% of the parasites in early apoptosis , 0.087% in late apoptosis  and 0.9% were necrotic . In contrast, L. (L.) amazonensis treated with UA EC50 . A significant population of UA—treated promastigotes was in early apoptosis , 3.7% of parasite population was in late apoptosis  and 9.7% of the parasite was necrotic  (p < 0.05). After treatment with H2O2, the majority of the parasites were viable , however the frequency of Annexin V+/PI+ population (9.30% in Q2) was two times higher than control parasites (p < 0.05). In addition, 0.58% of parasites were in late apoptosis  and 0.80% was necrotic .Promastigote forms of stigotes  presente UA EC50  showed a2O2 –treated parasites presented high activity for caspase 3/7 compared to control and UA—treated parasites (2O2 –treated parasites (p < 0.05).arasites , and DNAarasites , lane 4.After 24h and 72h of UA treatment, alterations in the Infection Index (II) were observed. Infected peritoneal macrophage treated with 0.1 and 1.0 μg/mL of UA decreased significantly (p<0.05) the II in comparison with their respective control , in addiAt 24 and 72h of treatment , levels Animals treated with UA (1.0 and 2.0 mg/kg) or Glucantime (100.0 mg/kg) presented decreased lesion size in comparison to infected control (p<0.05) from 2 to 5 weeks post infection, as indicated in Regarding skin parasitism, BALB/c mice treated with 1.0 and 2.0 mg/kg of UA showed lesser skin parasitism in comparison with infected control (p<0.05), representing a decreasing of parasitism of 91 and 98%, respectively. Glucantime eliminated 99.9% parasites . The effL. (L.) amazonensis-infected BALB/c mice, treated with 1.0 mg/kg of UA also presented vacuolized macrophages with less intracellular amastigotes when compared to control mice (L. (L.) amazonensis-infected BALB/c mice, treated with 2.0 mg/kg of UA showed more preserved epidermis and dermis, and few parasitized macrophages were found  amazonensis promastigotes with an EC50 of 5.0 μg/mL [Baccharis dracunculifolia was effective against L. donovani promastigotes with an EC50 of 3.7 μg/mL. In the present study, purified UA was active against L. (L.) amazonensis promastigotes, presenting an EC50 of 6.2 μg/mL, by the other side, its isomer presented only a marginal leishmanicidal effect at 100 μg/mL (~14% of parasite inhibition), as also shown by Tan and collaborators [L. (L.) amazonensis promastigotes, and this activity was similar to that induced by the standard drug Miltefosine. In addition, the cytotoxicity induced by UA was similar to amphotericin B and higher than Miltefosine, that in turn correlated with the selectivity indexes, demonstrating that UA presented a marginal cytotoxic effect. In fact it was comparable with amphotericin B and similar to Miltefosine, suggesting that UA can be considered as a prototype drug. Furthermore, studies have demonstrated that promastigote sensitivity and cell toxicity to new compounds frequently indicate how specific a given molecule attacks the parasites and not host cells, as indicated in in vitro, amphotericin B was more effective.Classic drugs used to treat leishmaniasis, such as antimonials and amphotericin B, are considered obsoletes and most importantly toxic to patients, justifying the rational search for new anti-leishmanial compounds. In this regard, plant extracts, fractions and purified compounds have been extensively assayed in different types of experiments targeting to find more effective and lesser toxic drugs . Some ststigotes . Pouroum.0 μg/mL . Moreoveborators . These dLeishmania sp. parasites. The ultra-structural study revealed that UA caused parasite morphological alteration, which can be associated with apoptosis or even autophagy process [L. (L.) amazonensis, suggesting that, at least one of the possible mechanism of action triggered by UA is programed cell death. Besides ultra-structural alterations of UA-treated promastigotes, detected by TEM, other phenotypic changes can be associated to programmed cell death in parasites, as is the case of phosphatidylserine exposure from the inner side to the outer layer of the plasma membrane stained by Annexin V [L. (L.) amazonensis promastigotes presented morphology associated to a process of apoptosis-like, that was confirmed trough the detection of two populations by flow cytometry, one Annexin V+/PI- (early apoptosis) and the other was Annexin V+/PI+ (late apoptosis), suggesting that UA triggered programmed cell death in L. (L.) amazonensis promastigotes. Studies conducted with other types of natural compounds, such as saponin racemoside A [L. (L.) donovani, L. (L.) chagasi and L. (L.) amazonensis promastigotes. In the present study, in the UA-treated L. (L.) amazonensis group, approximately 36% of the parasites underwent apoptosis and a minor population (~10%) was PI+, suggesting that this parasite population also presented loss of membrane integrity, leading to a process of death associated to necrosis [Although UA represents a prototype drug, studies did not reveal the action mechanism of this triterpene on  process . Studies process  and SW48 process  tumoral nnexin V . As statmoside A , polyphemoside A , lignan moside A , also innecrosis , 50.2O2, a positive control for apoptosis, it could be even considered basal. In addition, the activity of caspase from UA-treated parasites was not enough to fragment genomic DNA as caspases from H2O2-treated parasites did. Considering these findings, programed cell death triggered by UA in L. (L.) amazonensis parasites can be considered independent of caspase. In fact, the majority of promastigote forms treated with UA were in early stage of programmed cell death, that can be firstly characterized by alterations in mitochondria physiology. In Jurkat cell lineage and lymphocytes, an elevation of mitochondrial membrane potential occurs before activation of caspases, and this fact appears to be the earliest change associated with apoptosis pathways . Indeed, UA-treated promastigotes showed an increasing in JC-1 aggregates that can be associated to a hyperpolarized state of mitochondria [L. (L.) amazonensis and this fact was associated with a hyperpolarized state of mitochondria rather than caspase 3/7 activity.In order to evaluate if apoptosis was dependent or independent of capases, enzymatic reactions were carried out using caspase 3/7 substrates. These enzymes are considered to be an executioner caspases , and forchondria , 53, reiL. (L.) amazonensis infection [Baccharis uncinella leaves that was enriched in UA [L. (L.) amazonensis-infected peritoneal macrophages produced high levels of NO that could account for UA leishmanicidal activity. Taken together, in this study UA was active against intracellular amastigote and triggered NO production in infected peritoneal macrophages.Some evidences have shown that nitric oxide is the major antileishmanial compound produced by macrophages to eliminate intracellular amastigotes of nfection , 55, 56.nfection . In the nfection  reporteded in UA . Thus, Uin vitro assays conducted with the triterpenes, in vivo experiments have been successfullly performed with this class of secondary metabolites. Studies conducted by Germonprez and coauthors [Maesa balansae were able to reduce liver parasitism in L. (L.) infantum-infected BALB/c mice. In L. donovani-infected hamster the therapeutic potential of the triterpene saponin maesabalide III was comparable with liposomal amphotericin B [Baccharis uncinnela leaves was therapeutic for L. (L.) amazonensis-infected BALB/c mice, and did not present toxicity for internal organs of mice [L. (L.) amazonensis—infected BALB/c mice submitted to UA treatment presented lesser lesion size and skin parasitism compared to control-infected mice. Although UA presented therapeutic effect in infected BALB/c mice, Glucantime treatment presented a slight efficacy in experimental disease compared to UA, being able to eliminate around 99.9% of parasite with a total of 10.0 mg administrated via intralesional route, while the treatment with 2.0 mg/kg of UA eliminated around 98% of parasites with a total of 176 μg of UA injected intralesionally. In fact, this is a significant difference between drugs requirement to eliminate intracellular parasites, therefore, it was necessary around 57 times more antimony than UA to eliminate a similar amount of parasites. Interestingly, in the site of parasite inoculation, this decrease in parasitism was also observed by histology, since UA- and Glucantime- treated animals presented lesser vacuolized and infected macrophages, confirming the efficacy of natural and standard drugs. These findings suggest that UA presents a superior efficacy in the experimental treatment of leishmaniasis in comparison with glucantime. Noteworthy, the standard drug Glucantime presents serious side effects for patients, such as fever, gastrointestinal toxicity  and in more severe cases, cardiotoxicity. By the other side, studies already showed that UA presents low/tolerable or even absent toxicity for different experimental models, and for this reason, it has been used for different clinical applications, including cosmetic industry [In addition to oauthors  demonstrericin B . A fract of mice . Similarindustry , 62.L. (L.) amazonensis-infected BALB/c mice, suggesting that this triterpene can be considered an interesting candidate for future tests as a prototype drug for the treatment of cutaneous leishmaniasis.In overall the present showed for the first time, that the action mechanism of UA was related to programmed cell death, as evaluated through morphological and biochemical studies; and importantly UA presented therapeutic effect for S1 File(XLSX)Click here for additional data file.


Drosophila and mammals have established the Hippo signaling pathway as an important modulator of organ size and tumorigenesis. Upon activation, this kinase cascade modulates gene expression through the phosphorylation and inhibition of transcription co-activators that are involved in cell proliferation, differentiation, growth and apoptosis. Hippo signaling serves to limit organ size and suppress malignancies, and has been implicated in tissue regeneration following injury. These outcomes highlight the important role that Hippo signaling plays in regulating both physiologic and pathologic processes. In this review, an overview of the signaling pathway will be discussed as well as recent work that has investigated its role in cardiac development, regeneration and disease.Control of cell number and organ size is critical for appropriate development and tissue homeostasis. Studies in both The online version of this article (doi:10.1186/s40169-014-0027-0) contains supplementary material, which is available to authorized users. Myocardial infarction (MI), or insufficient blood flow to the heart muscle, promotes thedeath and loss of cardiomyocytes resulting in heart damage and impaired cardiacfunction. While patient survival following MI has improved, the prognosis is typicallypoor and can eventually progress to heart failure, a leading cause of morbidity andmortality . BecauseDrosophila melanogaster shed new light on this question and identified the core components of what is now known as the Hippo signaling pathway, appropriately named after Hippo kinase. Mutant flies genetically deficient for a functional Hippo (Hpo) [Determining how multicellular organisms attain and maintain appropriate organ size has plagued researchers and remains a major quest. Studies employing genetic mosaic screens in po (Hpo) -5], Sal, SalDrospo (Hpo) ,7] or W or WDrospo (Hpo) ,9] exhi exhiDrospo (Hpo) . A fourtpo (Hpo) ,11]. Th. ThDrosoIn 2005, work from Pan and colleagues provided the critical link between the Hippo cascade and gene expression. Using a yeast two-hybrid approach with Warts as bait, they were able to identify the transcription co-activator Yorkie (Yki) as a downstream target of Hippo signaling . SubsequDrosophila and mammals. Similar to the fly, mammalian Hippo signaling involves the activation of a conserved kinase cascade that ultimately phosphorylates the transcription co-activator Yap (Yes-associated protein) and its paralog TAZ , thereby regulating downstream gene expression, cell proliferation and organ growth  and Lats1/2 , as well as the adapter proteins Salvador  and Mob1 ). T). TDrosoila Mats). Analogoila Mats). Mst1/2  mammals . Further mammals .Drosophila, including cyclin E, diap1, and the microRNA bantam, which may modulate cell proliferation and survival ,,-17]. Se. Se17]. survival ,14],. In. InDroso Yap/TAZ , ErbB-4  Yap/TAZ , Runx , Fo, FoDroso Yap/TAZ , Tbx5 [5 Yap/TAZ  and Smad Yap/TAZ -53]; ho; hoDrosoYap has been the focus of intense research since it was discovered to be the link between Hippo signaling and gene expression. Yap contains five potential Lats phosphorylation sites (HXRXXS) and mutation of one of these sites, a serine to alanine substitution at residue 127, was shown to attenuate Yap phosphorylation by Lats2 and modulate its subcellular distribution from cytosolic to nuclear prevalence ,[27],5454,55]. . 55]. SeYap activity is also regulated by multiple upstream signaling pathways that are independent of Hippo signaling. Yap was originally discovered as a WW-domain-containing protein that interacted with Yes, a member of the Src family of tyrosine kinases . SubsequDrosophila, a number of potential upstream components have been identified as important pathway regulators. Genetic screens identified the FERM domain family members Merlin (Mer) and Expanded (Ex). Mutations in either of these genes led to an attenuation of Hippo signaling in flies . Th. ThDrosoin flies . Additiod Yorkie -72]. Fa. FaDrosod Yorkie -77]. Fa. FaDrosod Yorkie -75]. Fu. FuDrosod Yorkie . Crumbs,ignaling ,79],. It. ItDrosoignaling ,84]. Re. ReDrosoignaling . The Sikignaling ,87]. Gi. GiDrosoignaling ,88]-,. RA. RADrosonstrated , therebynstrated ,98]. It. ItDrosooma (HCC),100]. I. IDrosopathology . On the e to HCC . While te to HCC . Taken tThe ability to sense and transduce extracellular signals and/or cues from the surrounding environment into the cell is a hallmark of traditional signaling pathways. Along these lines, work from Guan and colleagues demonstrated that cell density regulates the activation status of Hippo signaling . Cell-toIn a landmark study, the Guan group was the first to demonstrate that extracellular receptors, in this case GPCRs (G-protein-coupled receptors), could modulate Hippo signaling . LigandsAdditional groundbreaking studies from the Piccolo lab have shown that extracellular matrix (ECM) stiffness and mechanotransduction systems can also modulate the activity of Yap/TAZ . This woThe mammalian heart develops from mesodermal tissues, first forming a heart tube, which then loops and gives rise to atrial and ventricular components and an outflow tract. These complex processes require finely orchestrated spatial-temporal signaling events between multiple cell types to give rise to a normal, healthy heart . Tbx5 isSav1, Mst1/2 or Lats2 in the heart revealed the importance of these Hippo components for proper organ development . I. ISav1, Embryonic heart growth occurs mainly through proliferation of cardiomyocytes, whereas shortly after birth these cells experience a dramatic reduction in their ability to divide. Thus, further organ growth is almost exclusively mediated through the enlargement of existing cardiomyocytes. Around this same time, the ability of the mammalian heart to regenerate following injury drastically declines. It should be noted, however, that low-level cardiomyocyte turnover seems to occur throughout adult mammalian life ,117] an an117] ain vivo also caused increased cardiomyocyte proliferation, indicating that this observation is not limited or specific to neonatal cells ,,. Ectopical cells ,124]. S. Sin vivferation , providiferation . To deted normal , suggestd normal . ConditiMst1 was first cloned and characterized nearly 20 years ago and was later identified as a Hippo ortholog and a core component of the mammalian Hippo signaling pathway . Mst1 isSimilar to Mst1, increased expression of Lats2 promotes, while expression of DN-Lats2 attenuates, apoptosis of cultured cardiomyocytes . InteresRASSF1A associates with Mst1/2 and promotes mammalian Hippo signaling -98]. In. In98]. Yap results in embryonic lethality at day E8.5 -[1-[1138]-, yet itsday E8.5 ,146]. S. SYap reabeculae . These fabeculae . Myocards of age ,123]. Y. YYap res of age . TAZ CKOrol mice . Howeverrol mice . Conversrol mice . Increasrol mice . These frol mice . Taken ain vivo,,, 2) promin vivo,122]-, H, Hin vivin vivo.The Hippo signaling pathway has risen to prominence and is regarded as an important transduction mechanism that regulates cell growth, proliferation and survival. It has important implications for physiology and pathology that are the focus of intense ongoing research. Studies to elucidate the importance of Hippo signaling in cardiovascular biology and disease continue to shed light and reveal further complexity of this cascade in the mammalian heart. Future work may focus on the following points of outstanding interest: 1) the underlying mechanism explaining how Yap promotes cardiomyocyte proliferation; 2) upstream regulation of Hippo and how various stresses modulate the pathway; 3) possible crosstalk between additional established signaling networks that impact the heart; and 4) targeting Hippo components using small molecules to influence signaling and outcomes.


The immunopathogenic mechanisms responsible for debilitating neurodegenerative and oncologic diseases associated with human T-cell leukemia virus type 1 (HTLV-1) are not fully understood. In this respect, a patient cohort from HTLV-1 endemic region that included seronegative controls (controls), asymptomatic carriers (ACs), and patients with adult T-cell leukemia (ATL) or HTLV-associated myelopathy/tropical spastic paraparesis (HAM/TSP) was analyzed for CD8+ T cells functionality in response to the viral antigen Tax and a superantigen SEB. Overall, there was a poor recall response to Tax and less polyfunctionality in cells from ATL and HAM/TSP patients but not in ACs explaining why these cells remain ineffective in limiting viral burden and controlling disease progression. On the other hand, response to superantigen SEB was similar in all the groups, suggesting that the observed defects in CD8+ T cells are not generalized but rather HTLV-specific. As an underlying mechanism, programmed death-1 (PD-1) receptor was found to be highly unregulated in Tax-responsive cells from ATL and HAM/TSP but not from ACs and directly correlated with the lack of polyfunctionality in these individuals. Further, an opposite dynamic was observed between PD-1 and MIP-1α with proviral loads revealing new avenues of understanding the immunopathogenesis of human chronic viral infections. Additionally, we identified key cytokine signatures defining the immune activation status of clinical samples by the luminex analyses. Collectively, our findings suggest that reconstitution of fully functional CTLs, stimulation of MIP-1α expression, and/or blockade of the PD-1 pathway as potential approaches for immunotherapy and therapeutic vaccine against HTLV-mediated diseases.


The Ras-superfamily GTPases are central controllers of cell proliferation and morphology. Ras signaling is mediated by a system of interacting molecules: upstream enzymes (GEF/GAP) regulate Ras’s ability to recruit multiple competing downstream effectors. We developed a multiplexed, multi-turnover assay for measuring the dynamic signaling behavior of in vitro reconstituted H-Ras signaling systems. By including both upstream regulators and downstream effectors, we can systematically map how different network configurations shape the dynamic system response. The concentration and identity of both upstream and downstream signaling components strongly impacted the timing, duration, shape, and amplitude of effector outputs. The distorted output of oncogenic alleles of Ras was highly dependent on the balance of positive (GAP) and negative (GEF) regulators in the system. We found that different effectors interpreted the same inputs with distinct output dynamics, enabling a Ras system to encode multiple unique temporal outputs in response to a single input. We also found that different Ras-to-GEF positive feedback mechanisms could reshape output dynamics in distinct ways, such as signal amplification or overshoot minimization. Mapping of the space of output behaviors accessible to Ras provides a design manual for programming Ras circuits, and reveals how these systems are readily adapted to produce an array of dynamic signaling behaviors. Nonetheless, this versatility comes with a trade-off of fragility, as there exist numerous paths to altered signaling behaviors that could cause disease.DOI:http://dx.doi.org/10.7554/eLife.12435.001 Cells sense and respond to the world around them using signaling “circuits” made of proteins and other molecules, and when an important cell circuit breaks, diseases like cancer may arise. Much like with electrical circuits, a given set of molecular components can be used to build different signaling circuits that behave in different ways. However, unlike for electrical circuits we generally do not have design manuals that allow us to work out how a signaling circuit behaves based on the components it includes. Doing this would involve identifying all the molecular parts of a circuit, using them to build every possible circuit, and carefully measuring the associated behavior.A group of proteins called the Ras-superfamily GTPases are important controllers of cell behavior. To investigate the behavior of Ras GTPase signaling circuits, Coyle and Lim built up different circuits from their components and “watched” their behavior with a microscope. Analyzing these behaviors provided the information needed to produce a ‘design manual’ for programming Ras circuits.Coyle and Lim found that the makeup of a Ras signaling circuit strongly affects the timing, duration, shape and size of its output. This means that different cells can use the same core components in different ways to build circuits customized to their specific needs. Nonetheless, this versatility comes with a trade-off: the circuits are fragile, and can break in many different ways to cause disease.In the future Coyle and Lim aim to build other types of important cellular signaling circuits from their component parts. Only by building these systems, turning them on and watching them run can we begin to understand how they actually perform and what they are capable of.DOI:http://dx.doi.org/10.7554/eLife.12435.002 Many dynamic processes in the cell such as proliferation, differentiation, or morphological change are regulated by signaling through members of the Ras superfamily of small GTPases . Mutatioi, and releasing product to complete the catalytic cycle on their own, but, in practice, the GTPase is incredibly slow at each stage of this cycle except for the initial binding of nucleotide (i (ON->OFF transition)   (Boguskinsition) . How Rasnsition) .Our biochemical view of Ras and Ras-associated proteins, however, is largely focused on individual molecules, rather than the system of molecules. Considerable work in vitro over several decades has provided structural and biochemical insights into how individual GEFs, GAPs and effectors function, as well as how their activity can be controlled through mechanisms like autoinhibition and allostery . These sBy comparison, cell-based investigations of signaling are inherently multi-component and multi-turnover with respect to Ras, but provide far less control over the internal system parameters. In vivo assays usually contain fewer observables that are often far removed from the proximal signaling events. A variety of ingenious experiments have aimed to directly probe Ras activation during signaling in cells using fluorescent reporter molecules or super-resolution microscopy . Howeversystems reconstitution of Ras signaling – methodically exploring in vitro how the multiple activities that regulate Ras work together to dynamically cycle Ras and control the assembly of competing effectors on activated Ras during signal processing. As such, we know little about how the concentration and identity of the components within a Ras system define its signaling properties. Understanding how these systems-level parameters shape behavior is critical, given that different cell types can harbor different configurations of network components (both in identity and expression levels) and also because distinct receptors may differentially activate key network components. In addition, the fact that many diseases are associated with perturbations to Ras and its associated regulators suggests that a systems level reconstitution of Ras signaling systems could be highly informative as to types of outputs and behaviors that these systems are capable of, as well as how these systems respond to perturbations such as mutation.To date, there has been little Here, to address this problem of systems reconstitution, we develop a new microscopy-based bead reconstitution assay of dynamic signal processing by human H-Ras, a canonical member of the Ras subfamily of GTPases. Our system includes both upstream regulators of Ras activity as well as multiple downstream effectors that bind to and perceive Ras•GTP signals. This allows us to follow multiple cycles of Ras turnover in real-time using the bead recruitment of fluorescently tagged effectors on Ras as the measured output – precisely analogous to the way cells measure and couple Ras•GTP levels to signaling outputs. In addition to giving an output that reflects a critical biological function (effector recruitment), this system allows us to precisely control the components and their concentration.Using this system, we have explored how Ras signaling changes in response to network changes. We explore how oncogenic substitutions in Ras impact output behavior. We have scanned how the concentration of each type of network component sculpts effector outputs in response to a simple step input of GEF activity, how systems that contain multiple competing effector molecules behave, and how different mechanisms for implementing positive feedback reshape the landscape of output behaviors. More generally, the methods we develop herein provide a framework for studying the dynamics of other assembly driven signaling systems or more complex systems that incorporate multiple interconnected signaling nodes. This kind of analysis provides an overall design manual for Ras circuits, including those that could have originated through evolution or disease perturbation.To gain insight into the dynamics of how Ras transmits signals to downstream effectors under different network configurations or perturbations, we sought a dynamic in vitro reconstitution of Ras signal processing that would allow us to track effector outputs across multiple Ras turnovers. We reasoned that a microsphere surface charged with Ras could serve as a platform for the assembly and disassembly of fluorescent effector molecules from solution in response to inputs, much like the native Ras system (bound to the plasma membrane) functions in cells . SignaliDK) of a model effector: a fluorescently tagged Ras-binding domain (RBD) from the C-Raf kinase . For our initial studies, we chose to use the catalytic domain from the RasGRF GEF, which is constitutively active and, unlike other GEFs, contains no allosteric feedback sites . Ni-NTA f kinase . Under tf kinase . This amf kinase .quantitative differences in the system’s output behavior when different amounts of GEF activity were used as inputs. When identically loaded beads were stimulated with increasing amounts of RasGRF, we observed both faster rates of effector translocation and higher steady state amplitudes of effector output , incubated them with a saturating excess amount of C-Raf RBD effector , and monitored the loss of effector signal from the bead over time  are frequently associated with cancer or other diseases . These aUsing our dynamic, multi-turnover reconstitution of Ras signal processing, we examined how signaling networks bearing the G12V allele of the Ras GTPase distorted effector outputs relative to the wild-type Ras GTPase. By labeling wild type and G12V Ras GTPases with different fluorophores, we could distinguish beads loaded with each variant in a common solution of network components to see differences in effector outputs from each system side-by-side.amplitude and the shape of the output response, and (2) we show the responses after normalizing to the maximum value of the response, which conveys information only about the shape or dynamic profile of the output. The latter is particularly useful for seeing how the shape of two responses differs when the amplitudes are substantially different.For these and future experiments, we display the output response data in two ways: (1) we show the absolute response, which conveys information about both the without GAP activity in response to a step input of 2 μM of the GEF RasGRF  but in networks that now included 1 μM basal NF1-GAP , Video 2bona fide activating signals.Together these data and model imply that the balance of positive and negative regulatory activities in a signaling network impacts the severity by which Ras-G12V distorts signals. Similar results were also observed for G12C and Q61L alleles . To deteThe transient response of the wild-type GTPase in the high-GAP network context was unanticipated, as this phenomenon cannot be explained by the simplest model of effector/GTPase binding in which the GTPase toggles ON and OFF with rates directly proportional to [GAP] and [GEF] . Indeed,We found that extending the two-state model to include competition could produce overshoot, but this required higher concentrations of the Raf-RBD effector than the GAP and tighter binding of GAP to GTPase than Raf-RBD to GTPase, neither of which are consistent with the known parameters of the system . MoreoveIn contrast, the introduction of a refractory GTPase state to the model produced overshoot that captured the key features of the observed data within physiological parameters: a monotonic response to inputs in low-GAP networks but a transient response in high-GAP networks . It also2, 50 nM C-Raf effector, no GAP activity) with an associated output response, asked how titration of individual system components modulated the effector output.Our comparison of wild type and G12V Ras signaling systems and our associated model illustrated the importance of the network composition in shaping signal processing outputs. Each individual network component is, in essence, a separate 'dial' of the Ras signaling system that can be turned by adjusting the concentration of that component . BecauseMK for Ras (0.3 μM) and modest catk (1.4 s-1) (MK (9.7 μM) for Ras, but also a higher catk (19 s-1), and shows a much more ubiquitous expression profile  . In cont profile .dynamics of approach to steady state significantly: while GAP-free networks approached steady state from below, networks containing NF1-GAP showed transient overshoot that decayed back down to the steady state from above, creating an initial pulse of strong output followed by weaker levels of output in the long term. The pulse-width and peak-time of effector outputs were inversely correlated with the concentration of the NF1-GAP , the system output showed the typical monotonic approach to a sustained steady-state.When we measured the system step-response in the presence of increasing amounts of effector in the network, dramatic changes in the both the amplitude and dynamics of output were observed . At an e20 times that of the 50 nM effector system (measured at 120 min) at that time, before decaying down to its final steady state level. At even higher effector concentrations , system output peaked quickly within 20 min and then decayed monotonically over several hours to the final steady state level. These data demonstrate that higher effector concentrations not only increase output amplitudes but also enable the output to capture more transient features of the upstream Ras•GTP signal. This idea is supported by our kinetic model  and measured system output from different Ras densities, p120GAP concentrations, and input strengths ([GEF]). In total, we experimentally measured output responses for 96 configurations corresponding to four different input strengths, four different GAP concentrations, and six different Ras densities  and higher  affinities for Ras•GTP than C-Raf , respectively  but less so in the long-term (equilibrium-determined phase) . ApproprWe then performed a similar analysis for two-effector systems containing equivalent, physiological amounts of C-Raf and A-Raf RBDs, where A-Raf has a weaker affinity for Ras•GTP and higher off-rate from the GTPase than C-Raf . In GAP-N64A point mutant that has decreased affinity for Ras•GTP  of the C-Raf RBD and the C-Raf Ras•GTP . Differe Ras•GTP  and high Ras•GTP  networks Ras•GTP . This shTaken together, this analysis shows that distinct effector molecules can perceive the same input to a Ras signaling system with different dynamics and amplitudes depending on their affinities and biochemical properties. Consequently, a single-step input can be in principle be used encode multiple classes of temporally distinct outputs that peak and decline out of phase with one another, allowing for a sequence of different activities to be organized during signal processing. For example, we were able to produce a three-wave activation response of three distinct effectors in our kinetic model by simply modifying concentrations and off-rates . FurtherThe signaling networks we have examined thus far are solely the product of constitutive enzymatic activities and effector assembly processes unfolding in the simplest possible Ras GTPase signaling circuit. Our analysis found that in high-GAP systems, the 'ground state' output for a step-response will transiently overshoot the final steady state. In some instances, this behavior could be useful for the cell, for example to create an adaptive response or to produce distinct temporal phases in multiple downstream effector outputs; in other instances this overshoot behavior could prove undesirable, for example if the overshoot provoked a proliferative response to non-proliferative level of input.Many cellular circuits modulate intrinsic behaviors of a signaling system by including additional layers of regulation and feedback control that could alter the signaling properties of the system. To gain insight into how such regulation might alter the ground state signaling behavior of Ras GTPase systems, we examined the effect of introducing two different modes of GTPase→GEF positive feedback (defined as active Ras promoting more activation of Ras) on system signaling behavior.One common mode of generating positive feedback in signaling is through recruitment. For example, in yeast, the GTPase Cdc42, when activated, recruits its own GEF Cdc24 (via the scaffold Bem1), thus leading to further Cdc42 activation . SimilarThe inclusion of recruitment-based positive feedback in the system had considerable consequence for both the dynamics and amplitude of the effector output’s we observed. For example, in high GEF / high GAP regimes, multiple local maxima in the output dynamics were observed . InteresHow do these differences alter the signaling properties of the system compared to not having this feedback present? Manual inspection of the curves from the system with or without feedback suggested that recruitment-feedback was particularly effective at increasing output in high GAP network contexts. For example, high GEF / low GAP system configurations produced similar responses with or without feedback , but feeamplifying signals arising from weak inputs in a high turnover background.These data imply that this type of feedback mechanism can produce strong effects in certain network configurations but have little to no effect in other configurations. In particular, networks that contained high amounts of basal GAP-activity but only small amounts of input GEF showed the strongest differences in signal. These correspond to regimes in which the amount of GAP activity in the system dominates the small amount of intrinsic catalytic activity of the GEF, but does not overcome the small amount of localized GEF activity arising from the RasGRF-RBD feedback GEF . In contFor the second feedback mode, we replaced the RasGRF GEF with SOScat, the catalytic domain from the Son of Sevenless GEF. SOScat has an intrinsic feedback mechanism built in, such that the molecule has very low GEF activity in the absence of Ras•GTP, but Ras•GTP binding to a distal site on SOScat allosterically stimulates GEF activity to very high levels . Thus, iThese data show a very different effect of the allosteric SOScat feedback on signaling outcomes than was observed for the recruitment-based feedback of the RasGRF-RBD fusion. Unlike with recruitment-based feedback, allosteric-feedback did not provide large gains in output amplitudes in any of the regimes we looked like. However, we did observe that transient overshoot behavior was almost completely absent in the output responses of the SOScat system, even in the highest p120GAP condition we inspected. Indeed, the output dynamics from allosteric-feedback networks appeared much more stable and monotonic than those from RasGRF networks that contained no feedback. These effects were most dramatic in high GAP network contexts in which RasGRF produced a large transient overshoot phase, whereas SOScat produced a monotonic approach to the steady state . Howeverramp-input in terms of protein activity because it takes multiple rounds of GEF activity to produce enough Ras•GTP for SOScat to achieve significant activity 3x-6xHis) fusion proteins using custom expression plasmids (see plasmids table). The SNAP-tag facilitated labeling with high-performance inorganic dyes for imaging, and the DoubleHisTag on the C-terminus allowed Ni-NTA supports to be loaded stably (t1/2 >24 hr) with GTPase in a configuration resembling the native C-terminal attachment mode.Full-length H-Ras, H-Ras(G12V), H-Ras (G12C), and H-Ras(Q61L) were expressed as N-terminal SNAPtag-(GAGS)E. coli cells were grown to an OD of 0.4 from a fresh transformation, chilled to 18°C, induced with 0.8 mM IPTG, and allowed to express overnight. The proteins were purified by Ni-NTA affinity chromatography following the manufacturer’s instructions but were eluted in the presence of 1M Imidazole to facilitate elution of the DoubleHisTag. Proteins were subsequently purified by amylose affinity chromatography per the manufacturer’s guidelines. The protein was then concentrated to ~0.5 mL and purified by gel-filtration chromatography on a Superdex S200 10/300 equilibrated in Nucleotide Exchange Buffer  to remove any bound nucleotide from the GTPase.To express protein, BL21(T1R) Labeling of the SNAPtag on the GTPases was performed per the manufacturer’s instructions. Briefly, samples were buffer-exchanged into a labeling buffer  using a zebra desalting column. Following 20-min incubation with 5 mM DTT at 37°C, SNAP-Cell 430 substrate was added at a 1.1:1 dye:protein molar ratio and incubated for 1 hr at 37°C or overnight at 4°C. Unlabeled dye was removed by passing the sample through four zebra desalting columns.2 to 10 mM. Unloaded nucleotide was removed by passing the sample through 4 zebra desalting columns. Samples were finally exchanged into GTPase storage buffer , concentrated to ~100 μM, alliquotted, flash-frozen, and stored at -80°C.The labeled GTPases were loaded with nucleotide using established protocols . Briefly2x-MBP C-terminal Strep-II tag fusions. The SNAP-tag facilitated labeling with high-performance inorganic dyes for imaging, and the Strep-II tag provided a handle for affinity chromatography that did not interact with Ni-NTA supports.The RBD effector domains of A-Raf, B-Raf, C-Raf, and any associated mutants were expressed as N-terminal SNAPtag-(GAGS)E. coli cells were grown to an OD of 0.8 from a fresh transformation, chilled to 18°C, induced with 0.8 mM IPTG, and allowed to express overnight. The proteins were purified by Streptactin affinity chromatography and then amylose affinity chromatography, per the manufacturer’s instructions. Proteins were concentrated to ~1 mL and further purified by gel-filtration chromatography on a Superdex S75 16/60 equilibrated in standard protein buffer .To express protein BL21(T1R) Labeling of the SNAPtag on the effectors was performed per the manufacturer’s instructions. Briefly, samples were incubated with 5 mM DTT at 37°C for 20 min. SNAP-Surface 488 or SNAP-Surface 549 were added at a 1.1:1 dye:protein molar ratio and incubated for 1 hr at 37°C or overnight at 4°C. Unlabeled dye was removed by passing the sample through 4 zebra desalting columns. Samples were concentrated to 100 μM, exchanged into storage buffer , aliquotted, flash frozen, and stored at -80°C.The catalytic domains of RasGRF, p120GAP, NF1-GAP, SOS, and RBD-RasGRF were expressed as N-terminal MBP C-terminal Strep-II tag fusions. The Strep-II tag provided a handle for affinity chromatography that did not interact with Ni-NTA supports.E. coli cells were grown to an OD of 0.4 from a fresh transformation, chilled to 18°C, induced with 0.8 mM IPTG, and allowed to express overnight. The proteins were purified by Streptactin-affinity chromatography and then amylose-affinity chromatography, per the manufacturer’s instructions. Proteins were concentrated to ~0.5 mL and purified by gel-filtration chromatography on a Superdex S200 10/300 equilibrated in standard protein storage buffer . Proteins were concentrated, aliquotted, flash frozen, and stored at -80°CTo express protein BL21(T1R) 2, 30 mM Imidazole), and resuspended in a final volume of 1 mL GAB. To load the beads, 7.5 μL of this bead slurry was mixed with 7.5 μL of GTPase in a PCR tube and incubated on ice for 1 hr with occasional flicking. The amount of GTPase used to load the beads depending on the desired density for the specific experiments being performed downstream, but a typical bead-loading used 7.5 μL of 30 μM GTPase and typically resulted in Ras densities crudely estimated at 2500 molecules × μm-2 . Following incubation, the beads were spun in a table-top minifuge, the supernatant removed, and washed thrice with GAB. The washed beads were resuspended in ~100 μL GAB, transferred to an Eppendorf tube, shielded from light, and stored on ice. The exact amount of final GAB the beads were in was adjusted for any particular experiment such that 2 μL of bead slurry contained roughly 25–100 total beads when placed in a 384-well microscopy plate.Here, 50 μL of NiSepharose High-Performance beads  were washed twice with 1 mL water, twice with GTPase assay buffer  and beads in GAB. It should be noted that the inclusion of 20 mM Imidazole was critical for eliminating non-specific background effector staining on the bead surface and improved reproducibility dramatically. A 20 μL volume of this bead mix was dispensed into the wells of a 384-well Costar microscopy plate. Second, an 'initiation-mix' was prepared that contained fluorescent effector at the desired concentration, 5 mM GTP (or other nucleotide if used) and GEFs and GAPs at the desired concentration, all in GAB. 10 μl of this reaction mix was gently added to the 20 μL bead mix in the 384-well plate to initiate reaction. The large volume of the initiation mix was critical for getting sufficient mixing without the need to pipette up and down and disrupt the beads and improved reproducibility. Once signal processing reactions were initiated, they wells were sealed with PCR plate sealant to prevent evaporation.All data were collected using a Nikon Eclipse TI inverted microscope equipped with a Yokogawa CSU-X1 spinning disk confocal using a 20x PlanAPO 0.75 NA objective and an electron microscopy charge-coupled device (EM-CCD) camera . Depending on the experiment, 405 nm, 488 nm, and/or 561 nm wavelength laser light  were used for excitation.For typical experiments, 5–10 x-y positions within a given well were used to collect signal processing behaviors from 20–100 individual beads. Timepoints varied depending on the experiment, but for typical large matrix experiments of 24–60 different GEF/GAP/effector conditions, we typically imaged every 15 min for 6–12 hr. MicroManager software was used to design the imaging protocols and collect the actual data.A combination of standard and custom ImageJ macros were used to prepare the primary image data for further analysis. First, drift in the stage was corrected using a macro based around the MultiStackReg plugin. Two or three color multi-tiff timecourses were split into separate channels. Matrix transformations to register timecourses were obtained using the constant GTPase fluorescence on every bead from the blue channel. These matrices were then used to register the timecourses of the red or green channels. The three channels were then recombined to produce the properly registered multi-tiff used for analysis of the beads. The ImageJ macro code was tweaked depending on the particular experiment, but a representative example of the code is shown below:matrix path= "C:\Users\scoyl_000\Google Drive\MICROSCOPY\150403\matrix\";inputpath = "C:\Users\scoyl_000\Google Drive\MICROSCOPY\150403\raw\";outputpath = "C:\Users\scoyl_000\Google Drive\MICROSCOPY\150403\processed\";function scott_register{open(input+filename);run("Split Channels");run;run;run;run;}list = getFileList(inputpath);for scott_register;We then corrected for uneven sample illumination or background artifacts using a rolling ball background substraction of 50 pixels. These processed images were subsequently used to analyze the signaling behavior of each bead.To analyze the images, beads were either identified and stored as regions-of-interest (ROIs) automatically from the GTPase fluorescent signal on beads using a custom macro that makes use of ImageJ’s 'find particles' function, or in the case of experiments with beads that deliberately contain differing levels of Ras density, beads were identified and stored as ROIs by hand. The particular parameters of the automated bead finding varied depending on the particular experiment, but a representative ImageJ macro is shown below:inputpath = "C:\Users\scoyl_000\Google Drive\MICROSCOPY\150403\processed\";outputpath = "C:\Users\scoyl_000\Google Drive\MICROSCOPY\150403\beads\";function scott_findbeads{open(input+filename);run("Split Channels");selectWindow("C3-" + filename);run;//set threshold and find particlesStack.setPosition;setSlice(20);setThreshold;run;//close any and all open windowsclose;close;close;//reopen original fileopen(input+filename);//transfer ROIs to overlay and saverun("From ROI Manager");saveAs;//clear managerroiManager("Delete");close;}list = getFileList(inputpath);for scott_findbeads;Once beads were identified and stored as ROIs, a variety of measurements were made for each bead using a custom macro. We measured the average total Ras fluorescence in the ROI, and the average fluorescent effector signal in the ROI at every timepoint in the experiment. We also measured the area and perimeter of the bead. As with other macros, the exact details of the code varied depending on the number of effectors we were simultaneously examining or other aspects of the setup, but a representative ImageJ macro is shown below:inputpath = "C:\Users\scoyl_000\Google Drive\MICROSCOPY\150318\one_shot_processed\";outputpath = "C:\Users\scoyl_000\Google Drive\MICROSCOPY\150318\one_shot_data\";setBatchMode(true);list = getFileList(inputpath);for crunchimage;setBatchMode;//The Functions that are used in the macro are belowfunction crunchimage{//open the imageopen(input+filename);//clear log file and reulsts tablerun("Clear Results");print("\Clear");//import ROIs from overlayrun("To ROI Manager");//count ROiscount=roiManager("count");//record Ras AMPS and RBD timecourse for each ROIfor{// first record the AMP for the Ras field;recordAMP(i);// next calculate the time series for the datarecordTimecourse(i);// print newline markerprint("!");}selectWindow("Log");saveAs;close;}function recordAMP(index){//function that reports area, mean intensity, and perimieter// of an ROI used to get everything EXCEPT the timecourse datarun("Clear Results");roiManager;// select channel 2 and select the midpoint of hte stackStack.setPosition;// make measurementsrun("Measure");BeadArea=getResult;BeadMean=getResult;BeadPerim=getResult;print;}function recordTimecourse(index){run("Clear Results");roiManager;sliceCount=nSlices/2;// print(sliceCount);for{Stack.setPosition;run("Measure");timepointK=getResult;print;}}The output of this macro is a file that contains a list of every single bead trace in the multi-tiff image. Each trace begins with the area measurement of the bead, the mean total Ras intensity of the bead, and the perimeter measurement of the bead, followed by the effector measurement of the bead at every timepoint. Each measurement ends with a ',' and is on a newline. At the end of each bead trace, a stop marker '!' is printed. These data are then transformed by GREP and shell script into a CSV where each line contains all the relevant information about each single bead’s signaling trace. These data can then be loaded into either Matlab or Excel for further analysis.2, 300 molecules / μm2, 600 molecules / μm2, 1200 molecules / μm2, 2500 molecules / μm2, 10,000 molecules / μm2. The individual bead traces within a given bin were then averaged together to produce an average response for the associated density bin and network configuration. Each trace was typically the average of 15–80 beads from the combination of two independent experiments. The standard error of the mean for a given trace was typically <15%.Once in Excel, data were typically further analyzed as follows: (i) intensity measurements were normalized to perimeter instead of area, (ii) the time-series data for a given bead was normalized such that the time-zero effector measurement was zero, and (iii) single bead traces were binned based on total GTPase levels to obtain statistics on the signaling behavior. Beads were assigned to the nearest of the 6 Ras density beads: 150 molecules / μm-2 in the following manner. First, we determined the correspondence between the concentration of labeled Ras and its fluorescence intensity by imaging serial dilutions of known concentrations of SNAP-Cell 430 labeled Ras in solution. From this, we could associate a particular fluorescence intensity with a three-dimensional concentration in μM. For our imaging conditions, this relationships was:We estimated the approximate Ras density of a bead in molecules × μm-1) × Intensity (AU)Concentration (μM) = 4.287 (μM × AUh (h obtained from previously published work on EGFR kinases tethered by His-tags to a DGS-NTA(Ni) charged vesicle surface, which assumed a radius of confinement of 55 nm  * 0.055 μm = 33.1 molecules μm-21 μM × (602 [molecules × μm-2) =⇒ 2-D Concentration (molecules × μm2] x μM-1)3-D concentration (μM) * 33.1  parameters:The third model was a three-state GTPase model that included an additional post-hydrolysis GTPase state (GI) which was refractory to GEF activation. This state converts to the GDP form on a slow timescale. This was modeled in Kintek as:The third model was the best at explaining the transient behaviors of the system that we observed as well as the differences between WT and G12V Ras, and thus was used as the basis of all subsequent modeling and simulations. For any given simulation in the text, the initial conditions and any changes to associated rate-constants are indicated in the figure legend.Relative log-transformed expression levels for p120GAP, C-Raf, and H-Ras across a variety of cell-types and tissue-types were obtained from data contained within the Genevestigator software package  and Tony Hunter as the Senior Editor.Thank you for submitting your work entitled "Mapping functional versatility and fragility of Ras GTPase signaling circuits through in vitro network reconstitution" for consideration by The reviewers  have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:eLife. However, it is recommended that several issues be addressed.The authors present an ingenious study of signal processing down the Ras pathway. These investigators develop an exceedingly simple yet powerful system: measure the recruitment in vitro to Ras-coated microbeads of fluorescently tagged Ras binding domains (RBDs) of various effectors to quantify the amplitude and kinetics of Ras signaling. By manipulating the density, mutational or GTP-binding state of the bound Ras along with the concentrations of single or multiple GEFs, GAPs and effectors, the investigators are able to observe a wide variety of signal outputs. Among the most compelling results is the dependence on GAP concentrations of the difference in signal output between wt and activated Ras . This tyEssential revisions:1) The manuscript would be deeper and ultimately more satisfying if the phenomena could be explained in terms of the biochemical properties of the component species . It might be said that the majority of observations from 2) While no new experiments are requested on this point, discussion is needed on how the absence of membranes in this system may alter the interpretation of the results. Ras proteins are peripheral membrane proteins that, although they appear to stably associate with membranes at steady state, are, in fact, in a dynamic equilibrium both in terms of association with the membrane per se (see PMID 16236799) and within membrane microdomains (see PMID: 17618274). The behavior of the stationary Ras proteins affixed to the inert microbeads is likely quite different from their membrane-asociated counterparts in an in vivo system. The lack of membrane also confounds other aspects of interpreting the results. For example, in their analysis the authors equate recruitment of the RBD of an effector to the microbead as a readout of signaling. But this is simplistic. Raf-1 is a kinase that is the first node in a cascade of kinases. The sine qua non of Raf-1 signaling involves stimulation of the kinase activity of Raf-1. Yet the interaction of Raf-1 with GTP-loaded Ras does not stimulate kinase activity in the absence of a cellular membrane . Indeed, the membrane acts upon the Raf-1 kinase in a manner that involves the cysteine-rich domain and initiates a poorly understood activation sequence, which may include dimerization. Importantly, Raf-1 sent to the membrane via a CAAX sequence does not require GTP•Ras at all for full activation  demonstrating that it is membrane not Ras that activates the kinase. Likewise GEFs for Ras and other small GTPases require biological membranes for activation. Indeed, the way GEFs like SOS and RasGRPs are regulated is by modulation of their affinity for membranes utilizing domains like SH2 (on Grb2), PH and C1 for membrane binding. Although the catalytic domain of SOS will have exchange activity toward Ras in solution, in vivo the histone, PH and DH domains are required for productive associate with membranes (PMID: 20133692).3) We could not find information about sample size and statistical analysis of data. This needs to be laid out clearly. The manuscript would be deeper and ultimately more satisfying if the phenomena could be explained in terms of the biochemical properties of the component species . It might be said that the majority of observations from and a refractory intermediate GTPase state produced a model that captured the main observations as to how system output was affected by GAP, Ras density, effector concentrations, mutational state and multiple effectors. The exact molecular nature of this intermediate GTPase state will be the subject of additional work but at present is outside the scope of this systems-oriented manuscript. We have included an extensive discussion of this modeling in the main text, and have included 3 new associated supplemental figures that contain this modeling data and articulate how it connects to our empirical observations.This was a very informative suggestion. We have now explored a number of kinetic models and included figures about their associated simulations in the manuscript. An important result from this modeling was the observation that the simplest model (as was suggested by the reviewers above) was unable to produce the types of transient overshoot behaviors that we observed in our data. Indeed, the fact that we could not produce overshoot from the simplest model is consistent with theoretical work on n-state Markov systems, which argue that this type of behavior is only possible for systems with at least three states. We found that overshoot could be introduced in the system by either (i) including competition between GAP and effector for the GTPase and/or (ii) including a post-hydrolysis intermediate GTPase state that is refractory to nucleotide reloading. While (i) could formally produce overshoot behavior, it could only do so in non-physiologic parameter regimes for GAP and was unable to explain the lack of overshoot in G12V compared to WT (the model predicted overshoot in both scenarios). In contrast, including both competition While no new experiments are requested on this point, discussion is needed on how the absence of membranes in this system may alter the interpretation of the results. Ras proteins are peripheral membrane proteins that, although they appear to stably associate with membranes at steady state, are, in fact, in a dynamic equilibrium both in terms of association with the membrane per se (see PMID 16236799) and within membrane microdomains (see PMID: 17618274). The behavior of the stationary Ras proteins affixed to the inert microbeads is likely quite different from their membrane-asociated counterparts in an in vivo system. The lack of membrane also confounds other aspects of interpreting the results. For example, in their analysis the authors equate recruitment of the RBD of an effector to the microbead as a readout of signaling. But this is simplistic. Raf-1 is a kinase that is the first node in a cascade of kinases. The sine qua non of Raf-1 signaling involves stimulation of the kinase activity of Raf-1. Yet the interaction of Raf-1 with GTP-loaded Ras does not stimulate kinase activity in the absence of a cellular membrane . Indeed, the membrane acts upon the Raf-1 kinase in a manner that involves the cysteine-rich domain and initiates a poorly understood activation sequence, which may include dimerization. Importantly, Raf-1 sent to the membrane via a CAAX sequence does not require GTP•Ras at all for full activation  demonstrating that it is membrane not Ras that activates the kinase. Likewise GEFs for Ras and other small GTPases require biological membranes for activation. Indeed, the way GEFs like SOS and RasGRPs are regulated is by modulation of their affinity for membranes utilizing domains like SH2 (on Grb2), PH and C1 for membrane binding. Although the catalytic domain of SOS will have exchange activity toward Ras in solution, in vivo the histone, PH and DH domains are required for productive associate with membranes (PMID: 20133692).in general is affected by network configurations and effector properties. The complex effector binding dynamics that we observe are now discussed as the background and context in which other molecule-specific signaling mechanisms like dimerization or lipid interactions take place. Extending our in vitro reconstitution to lipid supports and post-binding readouts is something we are currently exploring in ongoing work and we look forward to seeing how molecule-specific phenomenon interface with the complex binding dynamics we observed in this work.This is an outstanding point and clarification of what we are measuring (binding) and how that is reflected in ‘signaling outputs’ has been incorporated into the manuscript. We emphasize that it was not our intent to suggest that other critical components of Raf activation  were not important in signal processing. Instead, we were primarily focused in how effector binding to GTPases  We could not find information about sample size and statistical analysis of data. This needs to be laid out clearly.We have extended our methods discussion to clearly indicate this information.


We present a simple method and its experimental implementation to determine the pulse durations and linear chirps of the pump-and-probe pulse and the Stokes pulse in a coherent anti-Stokes Raman scattering microscope at sample level without additional autocorrelators. Our approach exploits the delay line, ubiquitous in such microscopes, to perform a convolution of the pump-and-probe and Stokes pulses as a function of their relative delay and it is based on the detection of the photons emitted from an appropriate non-linear sample. The analysis of the non-resonant four-wave-mixing and sum-frequency-generation signals allows for the direct retrieval of the pulse duration on the sample and the linear chirp of each pulse. This knowledge is crucial in maximizing the spectral-resolution and contrast in CARS imaging. In the coherent-anti-Stokes-Raman-scattering (CARS) process a pair of photons (“pump” and “Stokes”) is exploited to excite selected vibrational levels of a sample by choosing them so that their frequency difference matches the vibrational frequencies of interest. A third photon, from the same source as the pump in the so-called two-color CARS implementations, coherently probes the phonon population of the vibrational mode generating strong anti-Stokes emission . This apPulses are routinely characterized by means of autocorrelators, where a time-delayed fraction of a pulse interferes on an object having a non-linear optical response with the non-delayed remaining of the same pulse. Second-order processes are recorded as a function of the time delay yielding the beam autocorrelation function and–when the spectral bandwidth and pulse-envelope shape are known–the pulse duration and chirp. Anyway, this characterization cannot be easily performed at the focal plane of the microscope objective and the additional contributions to the total group delay dispersion (GDD) are typically only estimated. The approach proposed here leads to distinctive advantages even when the contribution of the objective to the total GDD is small with respect to the other optical components in the microscope (or if it can be estimated). In this case the pulse characteristics could be determined with an external autocorrelator by removing the objective and the condenser but this process is cumbersome and can lead to misalignments in the optical path. It should also be noted that optimization strategies common for example in two-photon-excited-fluorescence microscopy, based on maximizing the signal by tuning a pre-chirp device, cannot be applied here. Indeed, the setting that would lead to maximum signal would likely be different to that leading to optimal spectral resolution due to the presence of non-resonant background.More sophisticated and precise laser-pulse-characterization techniques exist , e. g. bAnyway, while the DBFROG technique and similar approaches are extremely powerful in the determination of unknown arbitrary pulses, they require complex iterative pulse retrieval algorithms. In the case of CARS microscopes, where one starts with known pulses and is interested in determining the additional linear chirp introduced to achieve spectral focusing and the total pulse duration at the sample, a simpler method would be desirable. In fact, simplified implementations are often used: in Ref.  XFROG SFδt, the pulse durations at the sample level can be straightforwardly measured. Differently from conventional FROG-based approaches, this step does not even require to frequency resolve the emitted signal signals. Measuring the signal intensity with a PMT (a pair of filters to isolate the FWM and SFG will be needed) as a function of δt is enough to determine both pulse durations. If the pulse characteristics at the laser output are known, then it is also easy to calculate the GDDs at sample level. If the emitted signals can be spectrally analyzed, the GDD of each pulse can also be determined experimentally. The only assumptions behind this approach are that: i) the non-linear responses of the chosen medium are only weakly dependent on the wavelength of the excitation photons, at least within the bandwidths of the pulses, which can be easily verified experimentally. ii) Pump and Stokes beam powers are chosen in order to avoid pump depletion. Also this can be checked for experimentally  and sum-frequency-generation (SFG) signals as a function of their relative delay τ, amplitude A1/2, and centered around an angular frequency ω can be described as:The electric field of a Fourier-limited Gaussian pulse having duration a. Neglecting third-order dispersion (TOD) terms and higher  from the pump pulses and from the Stokes pulses will also be generated. Since these obviously do not depend on ASFG and AFWM provide their spectra:The squared moduli of the Fourier transforms of The explicit expressions of the coefficients in δt, the spectra are Gaussian curves with amplitudes (ISFG and IFWM) and centers  depending on δt. The amplitudes of the Gaussian curves as a function of δt are:βpump and βStokes are defined in W) are:From ISFG and IFWM while moving the delay line. Inverting τout,pump and τout,Stokes:The FWHMs can be straightforwardly determined experimentally by monitoring δt with rates (S):If the pulse durations are known, then the inversion of τout,pump and τout,Stokes, yields the values of αpump and αStokes:τpump, τStokes, apump, and aStokes:Inversion of Lpump (LStokes) the length of the glass blocks placed in the pump (Stokes) path. Before the dichroic mirror D, the Stokes pulses are delayed by means of a motorized delay line. Photons reach and overfill the pupil of the microscope objective after being reflected by a pair of galvanometric mirrors and after propagating through a scan lens and a tube lens. Pump (Stokes) beam power measured after the objective is 20 mW (10 mW). Signals generated from the sample are collected by the microscope condenser, spectrally filtered to remove pump and Stokes photons, and analyzed by a spectrometer.In the following, we shall show the validity of our approach by reporting the pulse characteristics of a CARS setup, schematically shown in 3/Au nanoparticles, (NPs), with an average diameter of 300 nm owing to their strong non-linear optical properties. A scanning-electron-microscope image of some NPs deposited on a microscope glass slide is shown in As a sample material for the experiments, we chose core/shell BaTiOLpump = LStokes = 0) to evaluate the contribution of the set-up optics and sources alone to the total GDDs. The measured spectra as a function of the delay are reported in WSFG and WFWM. Linear fits of the center wavelengths as a function of the delay in turns gives SSFG and SFWM. Eqs  an anLpump FWM. Eqs  finally Lpump = LStokes = 0 and for the other configurations tested, averaged over 20 repetitions of each experiment, are reported in Lpump = LStokes = 0) even if both pulses cross similar amounts of glass in the setup, they reach the sample with a difference in GDD ~10000 fs2. This is quite likely due to a setting of the OPO cavity introducing a negative chirp in the Stokes beam that compensates the positive one introduced by the additional optics.The parameters calculated for Lpump = 10 cm and LStokes = 15 cm blocks of SF6 glass. The lengths were calculated in order to introduce approximately the same GDD for both the pump and Stokes beams, which is what one would be tempted to choose without knowing the real characteristics of the pulses. Calculating the refractive index of the SF6 glass by means of the Sellmeier equation , the additional dispersions can be determined to be 19643 fs2 and 19746 fs2 for the pump and Stokes pulses respectively. The characterization of SFG and FWM, shown in Lpump = 0 and LStokes = 0, increased by the calculated GDDs introduced by the glass. Similarly consistent parameters were obtained for Lpump = 0 cm and LStokes = 15 cm.We repeated the procedure after introducing Lpump = 10 cm and LStokes = 25 cm, was determined following the characterization in the other configurations in order to yield similar GDDs (~30000 fs2) for both pulses at the sample level. The increase in spectral resolution with the latter choice of glass lengths was demonstrated by measuring the spectrum of liquid methanol in the C-H stretch region  or in the Stokes path (right column) to allow an easy comparison among the data. Error bars show the standard deviation calculated over 20 repetition of the acquisition.(EPS)Click here for additional data file.S2 FigWFWM were observed. In the case of probe-induced pump depletion, at large ratios a reduction of WFWM is expected.Within the measurement uncertainties, no variations of (EPS)Click here for additional data file.S3 Figδt with a 10-cm SF6 glass block in the Stokes-beam path. The red line shows the best Gaussian fit to the data (FWHM = 478 ± 3 fs) and the crosses displays the fit residuals. Crosses show the residuals, demonstrating the quality of the fit. Similarly, the pump beam was tested with analogous results.In order to verify the assumption of Gaussian beams, one of the beams was stretched with a block of glass and its temporal profile determined using the other pulse as a much narrower optical gate. The plot shows FWM intensities (open circles) as a function of (EPS)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableErrors represent the standard deviation calculated over 20 repetition of the acquisition.(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.


Targeting oncogenic HH/GLI signaling with small molecule inhibitors of the essential pathway effector Smoothened (SMO) has shown remarkable therapeutic effects in patients with advanced and metastatic basal cell carcinoma. However, acquired and Here we report on the identification of the Dual-Specificity-Tyrosine-Phosphorylation-Regulated Kinase 1B (DYRK1B) as critical positive regulator of HH/GLI signaling downstream of SMO. Genetic and chemical inhibition of DYRK1B in human and mouse cancer cells resulted in marked repression of HH signaling and GLI1 expression, respectively. Importantly, DYRK1B inhibition profoundly impaired GLI1 expression in both SMO-inhibitor sensitive and resistant settings. We further introduce a novel small molecule DYRK1B inhibitor, DYRKi, with suitable pharmacologic properties to impair SMO-dependent and SMO-independent oncogenic GLI activity. The results support the use of DYRK1B antagonists for the treatment of HH/GLI-associated cancers where SMO inhibitors fail to demonstrate therapeutic efficacy. The Hedgehog (HH)/GLI pathway plays a central role in the control of vertebrate development and tissue homeostasis of adult mammalian organisms, while its uncontrolled activation or inefficient termination has been implicated in a number of human malignancies including cancers of the skin, brain, hematopoietic system, lung, ovary and of the gastrointestinal tract . TargetiPrecise control of canonical HH/GLI signaling is an intricate process involving numerous regulatory processes. Briefly, in the absence of HH ligand, the twelve-transmembrane protein Patched (PTCH) represses HH signaling by preventing the G-protein coupled receptor-like protein Smoothened (SMO) to translocate to the primary cilium, an antenna-like compartment central to the activation of canonical HH/GLI signaling. Binding of HH to its receptor PTCH revokes the repressive effect of PTCH thereby allowing SMO to enter the primary cilium and initiate signaling. In the cilium, SMO activates the GLI zinc finger transcription factors GLI2/3 by preventing the formation of GLI repressor forms and by releasing GLIs from their negative regulator Suppressor of Fused (SUFU). Translocation of GLI2/3 activator forms to the nucleus induces HH/GLI target gene expression, including the potent transcriptional activator and oncogene GLI1 (for detailed reviews see -7).de novo drug resistance . As. As41]. Ptch or Sufu. In line with Dyrk1b acting downstream of Smo, Dyrk1b inhibition by harmine treatment reduced Gli1 expression in −/−Ptch and −/−Sufu MEF .We confirmed the role of Dyrk1b in the regulation of Gli1 using mouse embryonic fibroblasts (MEF) deficient in either F Figure , while vde novo resistance to SMO targeting . The compound was shown to be nontoxic, and demonstrated favorable selectivity against other kinases in the DiscoveRX KINOMEScan (selectivity factor S (35)=0.078) =0.078) . DYRKi dy dosage .50 concentrations of 1.16 μM and 1.04 μM, respectively  and untreated SUFU-depleted (ΔSufu MB) human medulloblastoma cells prevented GLI1 mRNA expression at comparable ICy Figure . By conty Figure . DYRKi-ty Figure . Furthery Figure . Analysiy Figure  and Sufuy Figure  further y Figure , suggestin vitro and impaired in vivo tumor growth imidazol-2-amine , 2-(1H-benzotriazole-1-yl)-1,1,3,3-tetramethyluronium hexafluorophosphate (HBTU) , 4-dimethylaminopyridine  and N,N-diisopropylethylamine  were added. The reaction mixture was stirred for 72 h at room temperature, poured into ice water and the formed precipitate dried and purified by flash column chromatography (DCM/MeOH 95:5 to 0:100). The crude product was suspended in Et2O, filtered and dried. The product was obtained as a white solid . mp: 232.5; 1H NMR  d 12.51 , 11.81 , 8.50 , 8.04 , 7.85 , 7.77 , 7.62 , 7.40 , 4.57 , 3.16-3.30 ; 13C NMR  d 168.0, 162.1, 159.9, 148.4, 148.2, 128.6, 127.4, 126.9, 125.8, 125.1, 123.7, 123.3, 122.1, 121.7, 118.0, 118.0, 117.9, 109.2, 71.7, 28.5; analysis : C , H , F , N , S ; LC/MS [M+H]+: 431.0.Synthesis of DYRKi was done as follows: to a solution of 2--1,3-thiazole-4-carboxylic acid (1.00 g. 4.04 mmol) in 20 ml in vivo tumor growth studies 1 × 106 PANC-1 or 1 × 105 L3.6pl pancreatic cancer cells in 25% Matrigel (BD Biosciences) were injected subcutaneously into the lower flanks of Foxn1nu nude mice . For in vivo treatment, DYRKi was dissolved in sun flower oil and administered at 100mg/kg/d by oral gavage. Tumor volume was measured with a caliper and calculated according to the formula [4/3 × π × (length/2) × (width/2) × (height/2)].For