Galleria mellonella larvae infected with MDR strains of P. aeruginosa. Carbapenem-resistant P. aeruginosa NCTC 13437 and an unrelated clinical isolate were used to infect G. mellonella larvae and the efficacy of twenty-eight dual β-lactam combination therapies were compared to their constituent monotherapies. For the most potent combinations identified, penicillin-binding protein (PBP) inhibition profiles were measured and compared with each constituent antibiotic. Five of the dual β-lactam combinations resulted in greater than 70% survival of infected G. mellonella. Two combinations showed potent, enhanced efficacy versus both strains − ceftazidime + meropenem and aztreonam + meropenem. Comparison of PBP inhibition profiles revealed that the enhanced efficacy of these two dual β-lactam combinations could not be explained by more potent inhibition of PBPs or inhibition of a broader range of PBPs. A possible contribution to the enhanced efficacy of the combinations could be stimulation of innate immunity via increased haemocyte numbers compared to their constituent monotherapies. Combinations of β-lactam antibiotics show promise in overcoming MDR P. aeruginosa and are worthy of additional study and development.The aim of the study was to determine the efficacy of dual β-lactam combination treatments derived from eight approved drugs against  Pseudomonas aeruginosa infections in healthcare settings include pneumonia, urinary tract infections and surgical site infections. Risk factors include immunosuppression, prior antibiotic exposure, catheterisation and mechanical ventilation. Infections due to P. aeruginosa can result in bacteraemia and are associated with high mortality1. Effective treatment of P. aeruginosa infections can be problematic because the organism is intrinsically resistant, and readily acquires resistance, to multiple antibiotics. The incidence of isolation of multi-drug resistant (MDR) strains (defined as resistant to three or more classes of antibiotics) is increasing2.P. aeruginosa infections. Resistant phenotypes often emerge during treatment via the selection of various complex chromosomal mutations. Frequently reported mutations include those leading to inactivation of the porin OprD, which decreases the drug permeability of the bacterial membrane, or those leading to de-repression of the intrinsic AmpC enzyme, a β-lactamase capable of hydrolysing penicillins and cephalosporins3. Other resistance-conferring mutations include those leading to up-regulation of drug efflux pumps4. Resistance can also result from the acquisition of transferable resistance genes such as those encoding extended-spectrum β-lactamases (ESBLs) or carbapenemases. In recent years, an increasing number of carbapenemase-producing P. aeruginosa outbreaks have been reported6. Worryingly, several of these have included metallo-β-lactamase (MBL) producing strains that are capable of rapidly hydrolysing carbapenems, a ‘last-resort’ treatment option for MDR Gram-negative infections10. MBL production is associated with higher mortality rates for P. aeruginosa infections11.Many antipseudomonal drugs belong to the β-lactam class of antibiotics and antipseudomonal β-lactams are essential for the successful treatment of P. aeruginosa infections are treated with dual combinations of antibiotics. The reasoning being that the simultaneous administration of two antibiotics with different modes of action increases the likelihood that the pathogen will be inhibited by at least one of the component drugs12. Receiving inappropriate initial antibiotic therapy correlates with patient mortality13, meaning that combination therapy can potentially improve initial therapy. Indeed, the use of combination therapy as an initial treatment has been shown in some cases to improve mortality rates for P. aeruginosa bacteraemia and pneumonia14.Traditionally, antipseudomonal combination therapy consists of a β-lactam plus a quinolone or an aminoglycoside. Clinical data supporting the use of β-lactams in combination with quinolones is lacking as most studies have found no difference in treatment outcomes between monotherapy and combination therapy12. There is more data to support the efficacy of β-lactams and aminoglycosides15, however this combination is associated with toxic side effects16 such as kidney damage17. The evidence for combination therapy providing real therapeutic benefit for P. aeruginosa infections remains contentious and data from a number of studies are conflicting (reviewed in18).To try to circumvent this problem, many resistant P. aeruginosa are required urgently as no new anti-pseudomonal antibiotics are likely to become available in the near future. Therefore, making optimal use of the antibiotics that are currently available in the form of novel combinations remains a realistic solution. Dual β-lactam therapy is an underexplored treatment option for MDR P. aeruginosa infections. Many in vitro studies were published in the 1980s that revealed extensive synergies between many different β-lactams against P. aeruginosa. In vivo studies, either in animal models or with human patients, were fewer but some also showed promise (extensively reviewed in19). None of these dual β-lactam combinations were developed further because at this time there was little clinical need due to lower incidence of MDR pathogens and the successful administration of antibiotic monotherapies. However, in light of the current aforementioned problems with treating MDR P. aeruginosa, re-exploring the potential of β-lactam combinations could prove beneficial.It is clear that novel treatments for MDR in vivo was compared with their constituent monotherapies against Galleria mellonella larvae infected with antibiotic-resistant strains of P. aeruginosa to identify combinations that could provide realistic future therapeutic options. For the most potent combinations identified, inhibition of penicillin-binding proteins (PBP) was compared to monotherapies to better understand the inhibitory action.The aim of this study was to evaluate the efficacy of twenty-eight dual β-lactam combinations derived from eight approved drugs that each represented a major class of the β-lactams. Efficacy of each combination therapy P. aeruginosa NCTC13437, a characterised MDR strain (carrying the VEB-1 ESBL and VIM-10 MBL), that is resistant to carbapenems and other β-lactam antibiotics and also quinolones and aminoglycosides by unknown mechanisms20. A clinical strain of P. aeruginosa isolated from the sputum of a patient in intensive care with a hospital-acquired pneumonia that did not respond to meropenem therapy. The strain is resistant to ceftazidime, imipenem and piperacillin-tazobactam and displays intermediate resistance to meropenem and aztreonam. The isolate was positive for the modified carbapenemase inhibition test and the carbapenem inactivation method by the Scottish AMR Satellite Reference Laboratory, Glasgow21. It was not found to possess any known carbapenemase enzymes at the Antimicrobial Resistance and Healthcare Associated Infections Reference Unit (AMRHAI), Public Health England, Colindale, and the antibiotic resistance profile was consistent with loss of the OprD porin and enhanced drug efflux. Finally, P. aeruginosa PA01 was provided by Dr. Olga Lomovskaya, Rempex Pharmaceuticals, USA. All strains were grown to stationary phase in Mueller–Hinton broth  at 37 °C with shaking (at 200 rpm) overnight to prepare inocula for antibiotic efficacy testing in vivo.Three strains were used: G. mellonella larvae were obtained from UK Waxworms Ltd. .All antibiotics were purchased from Sigma–Aldrich Ltd . Stock solutions of antibiotics were prepared in sterile deionized water. P. aeruginosa strains were determined in 96-well microplates as previously described22. Briefly, doubling dilutions of each antibiotic were prepared in MHB and subsequently inoculated with 1.0 × 106 cfu/mL of P. aeruginosa. Microplates were incubated at 37 °C and the MIC was defined as the concentration(s) present in the first optically clear well after 24 h.Minimum inhibitory concentrations (MICs) of antibiotics against each of the G. mellonella at their final instar larval stage were kept at room temperature in darkness. Larvae weighing within the range of 250 to 350 mg were selected for each experiment to ensure consistency in subsequent drug administration and were used within 1 week of receipt.G. mellonella larvae infected with the P. aeruginosa strains was carried out exactly as described previously24. Briefly, groups of 15 larvae were infected with an inoculum of 2.5 × 103 cfu/mL of P. aeruginosa cells (unless otherwise stated). Treatment with a single dose of each antibiotic alone, or dual combinations of these antibiotics, were administered 2 h post-infection. The experiments were repeated in duplicate using larvae from a different batch and the data from these replicate experiments were pooled to give n = 30. Survival data were plotted using the Kaplan–Meier method25 and comparisons made between groups using the log-rank test26. In all comparisons with the negative control it was the uninfected control (rather than the unmanipulated control) that was used. Holm’s correction was applied to account for multiple comparisons in all tests and P ≤ 0.05 was considered significant27.Efficacy of antibiotics alone or in combination versus 28. P. aeruginosa PAO1 cells from 1.5 ml of an overnight culture were harvested by centrifugation at 8,000 × g for 3 minutes at room temperature, washed in 1 mL of phosphate buffered saline (PBS), harvested, and resuspended in 80 μL of PBS containing 0.0001–1000 mg/L of aztreonam, ceftazidime or meropenem alone, or 0.0002–2000 mg/L of aztreonam + meropenem or ceftazidime + meropenem. A reference sample was resuspended in 80 μl of PBS alone. The cells were incubated at 37 °C for 40 mins prior to harvesting and washing in PBS, harvesting and resuspension in 50 μL of PBS containing 30 μg/mL of BOCILLIN™ FL penicillin, sodium salt (Boc-FL), a fluorescent analogue of penicillin V coupled with the fluorophore BODIPY FL, used to detect and label PBPs . The cells were incubated at 37 °C for 30 mins, prior to harvesting and washing and final resuspension in 100 μL of PBS, and then sonicated (Hielscher Ultrasonic Processor (UPS200S)) for 4 × 10 second intervals  with 10 seconds cooling between each round. Following sonication, any remaining un-lysed cells were harvested  and the supernatant collected. The protein content was measured  and all samples were adjusted to 8 mg/mL via dilution with PBS. Next, 51 μL of each protein sample was mixed with 17 μL of 4 × Laemmli sample buffer  supplemented with β-mercaptoethanol  as described in the manufacturer instructions, and de-natured at 95 °C for 5 mins before loading 20 μL onto a 10% Tris-HCl polyacrylamide gel . Proteins were separated via gel-electrophoresis for 1 hr 45 min at 120 V. The gels were then rinsed repeatedly with deionised water and imaged (excitation at 473 nm with a 520 nm emission filter at 50-μm pixel resolution) using a Typhoon FLA 7000 scanner .PBP detection and β-lactam titration were carried out as previously described with several minor alterations50 values were determined as described previously28. Briefly, gel images were imported into Image J software (https://imagej.nih.gov/ij/download.html) and the brightness and contrast levels were adjusted to optimise the signal to noise ratio. The background was subtracted , and dark noise outliers were removed  to reduce the appearance of blemishes on the Typhoon scanner stage. The density of Boc-FL labelling in each protein band was quantified relative to the no-antibiotic reference sample using the Analyse Gels function . Relative Boc-FL labelling values from two independent experiments were averaged and GraphPad Prism  was used to create graphs showing relative % Boc-FL labelling versus β-lactam concentration. The binding affinity of each PBP for each antibiotic was determined by fitting a log10(inhibitor) vs. response – variable slope (four-parameter) curve to the % inhibition data from two independent experiments. IC50 values were determined using a 4-parameter logistic regression equation using GraFit 5.0 .Antibiotic PBP affinity profiles and ICGalleria saline29 at 5, 20.5 and 24 hours post-infection and haemolymph was bled into individual sterile reaction tubes and 10 µL was loaded onto an improved Neubauer haemocytometer and the haemocytes counted with duplicates for each sample. This experiment was performed in triplicate to give n = 9 for each experimental condition.Groups of 15 larvae per condition were injected with 10 µL of PBS followed 2 h later with either PBS, aztreonam (50 mg/kg), ceftazidime (5 mg/kg) or meropenem (2.5 mg/kg) or aztreonam + meropenem (50 + 2.5 mg/kg) or ceftazidime + meropenem (5 + 2.5 mg/kg) to assess the effects of these antibiotic treatments on circulating haemocyte numbers. Unmanipulated controls were also included. Three larvae were randomly selected and injected with 75 µL in vivo efficacy in dual combinations . G. mellonella larvae were infected with P. aeruginosa NCTC13437 because it is a characterised MDR strain that has been used successfully to infect G. mellonella in previous studies24. Initial pilot experiments determined the efficacy of monotherapy ) with each of the β-lactam antibiotics listed above on G. mellonella larvae infected with a lethal dose (2.5 × 103 cells/mL) of P. aeruginosa NCTC13437. Four of the β-lactams administered  resulted in minimal therapeutic benefit to infected larvae at the highest dose tested (100 mg/kg). This result is consistent with the fact that these β-lactams have minimal anti-pseudomonal activity. In contrast, PIP, CAZ, ATM and MEM each resulted in enhanced survival of infected larvae in a dose dependent manner (data not shown). These initial experiments allowed the selection of doses of each individual antibiotic for subsequent study of the effect of dual combinations - doses of each constituent antibiotic that had minimal therapeutic benefit as monotherapies were selected. This approach allowed optimal identification of combinations that offer enhanced efficacy compared to the constituent monotherapies.A group of eight β-lactam antibiotics  that each represent a common class of this group of drugs were selected for screening of G. mellonella larvae infected with a lethal dose of P. aeruginosa NCTC13437 (2.5 × 103 cells/mL) is shown in Table The effect of the 28 possible dual β-lactam combinations on survival of G. mellonella larvae infected with increasing inoculum sizes of P. aeruginosa NCTC13437 , 100-fold (2.5 × 105 c.f.u/mL) or 1000-fold (2.5 × 106 c.f.u/mL) resulted in an inoculum-dependent reduction in survival for all combinations tested. Notably, all four combinations still had some therapeutic benefit 96 h p.i with 2.5 × 105 c.f.u/mL and treatment with ATM + MEM resulting in some survival after infection with the highest inoculum tested - 2.5 × 106 c.f.u/mL . The same dual combinations of β-lactams administered to P. aeruginosa NCTC13437 , a fluorescent analogue of penicillin V, to measure antibiotic-dependent inhibition of PBPs.A primary hypothesis explaining why β-lactam combinations can offer enhanced efficacy is the broadened spectrum of PBPs that could be inhibited by administering multiple drugs with different PBP affinities [reviewed inP. aeruginosa33. Live P. aeruginosa PA01 cells were incubated with increasing concentrations of CAZ, MEM or ATM and the dual combinations of MEM + CAZ or ATM + MEM. After incubation, PBPs that had not been bound by the single antibiotics or combinations were labelled using Boc-FL. The PBPs were separated by SDS-PAGE and the affinity of the β-lactams or the combinations for each PBP was quantified by measuring Boc-FL labelling relative to an unexposed control. Experiments were run in duplicate and an example gel image for each of the drug treatments and their effect on PBP labelling by Boc-FL is shown in Fig. P. aeruginosa PA01 PBPs was based on molecular weight and comparison of the electrophoretic pattern with previously published studies33.Boc-FL has been used to study the PBPs of a range of bacteria, including −3 mg/L of MEM that is not seen with either ATM or CAZ at the same concentration  values were determined and are shown in Table 50 values calculated. The IC50 values provide insight into the preferential PBP targets for each of the treatments and relating the IC50 concentration with the MIC of P. aeruginosa PA01 also indicates if the PBP inhibition is likely to contribute to the antibacterial effect of the drug. The MIC values (mg/L) for P. aeruginosa PA01 were: ATM (1–2); CAZ (0.5–1) and MEM (1). Thus, ATM was selective for PBP1a and PBP1b and the IC50 values for both PBPs were less than the MIC for this drug. CAZ was selective for PBP1a and PBP2 and IC50 values for both PBPs were lower than the MIC, particularly that for PBP2. MEM was clearly the most potent β-lactam tested in terms of PBP affinity, showing selectivity for PBP1b and PBP4 but the IC50 values for PBP1a, 1b, 2, 4 and 5 were all lower than the MIC. Remarkably, none of the PBP IC50 values for the dual β-lactam combinations, both of which contained MEM, were lower than those obtained for MEM alone. With the exception of PBP4, the IC50 values were all higher than those calculated for MEM. From the dose-response curves, the % inhibition of each PBP by each individual antibiotic at their MIC was calculated and is shown in Table To describe the PBP affinity profile of each of the β-lactam treatments, half maximal inhibitory concentration . However, the rise in problematic MDR Gram-negative infections with few treatment options means that β -lactam combinations could be a potential solution. This study presents evidence that dual combinations of β-lactams offer enhanced efficacy against infections caused by MDR P. aeruginosa in an invertebrate model of systemic infection. The two most potent dual combinations identified in this study (meropenem with aztreonam or ceftazidime) have not been reported previously. The presence of a carbapenem (meropenem) in these effective combinations is notable because much of the past research on β-lactam combinations was carried out in the 1980’s and data is lacking on the use of carbapenems in combinations versus P. aeruginosa, particularly in vivo. Furthermore, the majority of the previous studies on the efficacy of β-lactam combinations were not carried out on MDR strains of P. aeruginosa19. Thus, the effective combinations reported here could represent real options for therapeutic intervention against resistant P. aeruginosa and merit further investigation in mammalian infection models and ultimately patients. This conclusion is supported by a number of studies that have highlighted successful application of dual β-lactam combinations to treat patients infected with MDR, and carbapenemase carrying, strains of Klebsiella pneumoniae38.Effective β-lactam combinations that target in vitro studies that report significant synergy versus P. aeruginosa between aztreonam and third or fourth generation cephalosporins, such as ceftazidime and cefepime39. The inclusion of aztreonam in dual combinations versus MDR Gram-negative bacteria that possess carbapenemases is logical because the drug is not hydrolysed by MBLs. However, aztreonam is susceptible to hydrolysis by most serine ESBLs and because many MDR pathogens carrying an MBL also possess ESBLs, aztreonam will need to be administered in combination with the novel β-lactamase inhibitor avibactam (reviewed in40). Unfortunately, avibactam is only a weak inhibitor of Ambler class B MBLs such as VIM-10 that is carried by P. aeruginosa NCTC 13437 used in this study and is thus unlikely to be part of an effective therapy41.Many of the potent β-lactam combinations that were identified in this study included the synthetic, monocyclic β-lactam, aztreonam. This observation is supported by many in vivo19. Adding to this, an alternative ‘shielding’ hypothesis potentially explains why dual β-lactams are more effective against resistant strains possessing ESBLs or MBLs - one of the component β-lactams could bind preferentially, or with higher affinity, to the β-lactamase enzyme, thus sequestering the hydrolytic capacity of the enzyme, and allowing the other component β-lactam to bind to its target PBP(s) more effectively. For example, Lister et al.42. revealed that aztreonam enhanced the activity of cefepime versus P. aeruginosa strains expressing chromosomal AmpC β-lactamases. A possible explanation for this was the high affinity aztreonam has for the active site of some β-lactamases, such as AmpC enzymes, meaning that it could also act as an inhibitor thus permitting cefepime to act unhindered43.Definitive studies on the actual mechanism underpinning β-lactam synergy are lacking. However, the principal hypothesis is that a broader spectrum of PBPs can be inhibited by combining β-lactams with different PBP affinity profiles. While β-lactams confer their antibiotic activity through PBP inhibition, individual antibiotics differ in their affinities for each of the bacterial PBPs. Therefore, a combination treatment with two β-lactams each with differing PBP binding profiles could provide broader PBP inhibition and thus collectively enhance their inhibitory effect and efficacy Escherichia coli PBPs was applied to P. aeruginosa28. This method uses Boc-FL to label PBPs in living cells rather than purified membranes with the advantage of avoiding any negative effects membrane preparation could have on PBP activity44. Using this method, all P. aeruginosa PBPs were identified with the exception of PBP3. PBP3 was not seen because stationary-phase cells were used in these experiments. PBP3 is expressed during the exponential-phase of growth and is down-regulated upon entry to stationary phase when cells switch to PBP3a expression45. Stationary phase cells were used to be consistent with the earlier experiments measuring efficacy of the various β-lactam treatments on G. mellonella larvae that were infected with stationary phase cells. PBP3 is essential for growth of P. aeruginosa, while the other PBPs can be individually deleted46. Many antipseudomonal β-lactams have been reported to preferentially bind to PBP3 including the drugs used in this study – aztreonam, ceftazidime and meropenem30. Unfortunately, because PBP3 was not detected here, any differences between the inhibition of PBP3 by the individual β-lactams and the dual combinations were not compared. However, if the previous studies are correct, and aztreonam, ceftazidime and meropenem all have high affinity for PBP3, it could be argued that combinations of these drugs would be unlikely to result in further significant inhibition that could explain the enhanced efficacy of the combinations observed in vivo.In this work, a novel method first used to study 46. The low molecular weight (LMW) PBPs are not considered to be important targets of the β-lactams since simultaneous deletion of PBP4, PBP5 and PBP7 has no significant effect on growth rate or cell morphology47.PBP1a and PBP2 are thought to be relevant β-lactam targets as simultaneous mutation of their transpeptidase domain results in cells that show reduced fitness19. For example, ceftazidime was observed to inhibit PBP2 unlike previous studies31. Also, meropenem inhibited PBP5, and particularly PBP4, with high affinity and was also a more potent inhibitor of PBP1b than reported previously30. These discrepancies could be due to the use of different PBP labelling methods between this and previous studies as discussed above. Meropenem was found to inhibit multiple PBPs unlike aztreonam or ceftazidime. In addition, comparison of PBP inhibition at the MIC of all three drugs revealed that meropenem was also a more potent inhibitor of the PBPs that were preferentially targeted by either aztreonam or ceftazidime. This broad-spectrum of coverage of PBPs could explain why meropenem is the more potent antibiotic than the other drugs investigated when employed as a monotherapy.The calculated PBP affinities of the β-lactams used in this work with those reported previously were generally consistent but with some notable exceptions50 values below those that were calculated for meropenem alone. In fact, the combinations had increased IC50 values for all the PBPs compared with meropenem. Similarly, neither of the combinations resulted in broader coverage of overall PBPs inhibited compared to meropenem. Thus, the hypothesis that a broader spectrum of PBPs are inhibited by combining β-lactams with different PBP affinity profiles can be discounted as an explanation for the enhanced efficacy of these particular β-lactam combinations in vivo. Perhaps the ‘shielding’ hypothesis discussed previously offers the more likely explanation why PBP-inhibiting drug combinations show enhanced efficacy in vivo against β-lactamase carrying MDR strains of P. aeruginosa and additional studies will be required to test this hypothesis.The dual combinations of meropenem with either aztreonam or ceftazidime did not decrease the ICin vivo is the increase in haemocyte numbers that was induced in response to exposure to the antibiotic combinations compared to the monotherapies. Notably, a direct correlation between increased numbers of circulating haemocytes and enhanced survival of G. mellonella larvae infected with fungal pathogens has been observed48. The immunomodulatory effects of antibiotics on human phagocytes can include both enhancement and suppression of phagocytosis (reviewed in49). β-lactams were previously shown to have pro-inflammatory properties by upregulating interleukin expression in murine macrophages50 and by stimulating macrophage phagocytosis51. Supporting the antibiotic-mediated increase in circulating haemocytes reported here, a similar immune-priming effect upon exposure to different antimicrobials has been shown in G. mellonella larvae previously53.A further possible mechanism that could partly explain the enhanced efficacy of the β-lactam combinations P. aeruginosa and are worthy of additional study and development. Before dual β-lactam therapy can be optimised for MDR P. aeruginosa infections, it will be important to undertake additional studies to determine the contributing mode(s) of action in order to maximise bactericidal activity and prevent resistance development.Irrespective of the precise inhibitory action, it is clear that combinations of PBP-inhibiting drugs show great promise in overcoming MDR Supplementary Information


GSK3α has been identified as a new target in the treatment of acute myeloid leukemia (AML). However, most GSK3 inhibitors lack specificity for GSK3α over GSK3β and other kinases. We have previously shown in lung cancer cells that GSK3α and to a lesser extent GSK3β are inhibited by the advanced clinical candidate tivantinib (ARQ197), which was designed as a MET inhibitor. Thus, we hypothesized that tivantinib would be an effective therapy for the treatment of AML. Here, we show that tivantinib has potent anticancer activity across several AML cell lines and primary patient cells. Tivantinib strongly induced apoptosis, differentiation and G2/M cell cycle arrest and caused less undesirable stabilization of β-catenin compared to the pan-GSK3 inhibitor LiCl. Subsequent drug combination studies identified the BCL-2 inhibitor ABT-199 to synergize with tivantinib while cytarabine combination with tivantinib was antagonistic. Interestingly, the addition of ABT-199 to tivantinib completely abrogated tivantinib induced β-catenin stabilization. Tivantinib alone, or in combination with ABT-199, downregulated anti-apoptotic MCL-1 and BCL-XL levels, which likely contribute to the observed synergy. Importantly, tivantinib as single agent or in combination with ABT-199 significantly inhibited the colony forming capacity of primary patient AML bone marrow mononuclear cells. In summary, tivantinib is a novel GSK3α/β inhibitor that potently kills AML cells and tivantinib single agent or combination therapy with ABT-199 may represent attractive new therapeutic opportunities for AML. Only a small percentage of genetically defined AML patients exhibit durable long-term responses with current therapy. For instance, identification of the FLT3 internal tandem duplication mutation in 13–36% of AML (depending on the subgroup)2 has led to the development of the FLT3 inhibitors quizartinib and midostaurin3, the latter of which has recently received FDA approval in combination with standard cytarabine and daunorubicin. However, the 5-year overall survival rates of the majority of AML cases ranges from 5–15% in older patients to 30% in young adults4. This lack of improvement in patient survival rates is primarily attributed to the limited efficacy of currently available therapies in AML and the need for new targeted drugs. Although a number of promising drug candidates are being tested, such as the above mentioned FLT3 inhibitors, combination chemotherapy remains the standard of care3. Thus, there persists a clear unmet need for new drugs for the treatment of AML.Despite significant advances in targeted therapy development and a growing repertoire of drugs being tested in the treatment of acute myeloid leukemia (AML)5. In contrast to the more established role of GSK3α/β as a tumor suppressor pair, which inhibits Wnt signaling via β-catenin phosphorylation and subsequent degradation6, it has been shown that GSK3α plays an important role in maintaining an undifferentiated leukemic state of AML blasts and therefore selective targeting of GSK3α, which avoids concomitant inhibition of GSK3β and β-catenin stabilization, could represent a viable therapeutic strategy in AML5. Currently, the only FDA-approved GSK3 inhibitor is lithium chloride (LiCl), which is approved for the treatment of epilepsy and bipolar disorder8. However, given the narrow therapeutic index of LiCl, the lack of GSK3α specificity, and its limited kinome-wide selectivity10, its utility as an AML therapy is questionable. There are a number of GSK3 inhibitors in development, but current compounds are either highly unselective featuring various off-targets in addition to GSK3α/β, lack isoform selectivity or have not yet advanced to clinical studies12. We have previously identified GSK3α/β as novel targets of tivantinib (ARQ197)13, an advanced clinical drug candidate, which was initially thought to be a highly specific MET inhibitor14. We observed that tivantinib, compared to other GSK3 inhibitors, has remarkable kinome-wide selectivity for GSK3α/β, as well as a slight preference for GSK3α over GSK3β. Considering the identification of GSK3α as a potential pro-tumorigenic signaling protein, we hypothesized that tivantinib may be an effective, novel therapeutic option for AML. In the current study, we therefore characterized tivantinib’s anticancer activity in AML cell lines, identified a synergistic drug combination with the BCL-2 inhibitor ABT-199, and demonstrated its efficacy in primary AML samples. The results presented herein suggest that tivantinib, either as a single agent or in combination with ABT-199, may be a novel and attractive targeted therapy option for AML.Through the combination of chemical and RNAi screens, it has been suggested that GSK3α is a novel target in AML2O .HL60 cells were kindly provided by Dr. G. Reuther  and were cultured in IMDM (20% FBS). U937 cells were a kind gift from Dr. G. Superti-Furga  and were cultured in RPMI 1640 (10% FBS). Cell line authentication was done by short-tandem repeat (STR) analysis. Tivantinib (Moffitt Chemistry Core and ChemieTek), ABT-199 (ChemieTek), PF-04217903 (Selleckchem) and 6-bromoindirubin-3′-oxime  were dissolved in DMSO (10 mM) and LiCl and NaCl (Sigma-Aldrich) were dissolved in sterile diH2, 100 mM NaCl lysis buffer containing Phosphatase Inhibitor Cocktail 2  and cOmplete Protease Inhibitor Cocktail . Lysates were resolved by SDS-PAGE and incubated with primary antibodies. Antibodies used were against actin  and pGSK3 (Y279/216) . Antibodies against β-catenin (sc-7199), Bak (sc-832), and MCL-1 (sc-819) were from Santa Cruz. Antibodies against GSK3α (#4337), GSK3β (#9315), pSer10 Histone H3 (#3377), Cleaved Caspase 3 (#9661), PARP-1 (#9542), and BCL-XL (#2764) were from Cell Signaling. Secondary antibodies were HRP-conjugated α-rabbit or α-mouse .Cells were lyzed using 0.20% NP40, 50 mM Tris pH 7.5, 5% Glycerol, 1.5 mM MgCl50 estimation using R. For the synergy screen, tivantinib was plated at 0 µM and 0.25 µM, respectively. Each library drug was tested at 0.5 µM and 2.5 µM, respectively. Subsequent drug combination effects were evaluated by the Bliss method.Cell viability assays were conducted according to manufacturer’s specifications for CellTiter-Glo Luminescent Cell Viability Assay (Promega). Cells were seeded at 1000 or 3000 cells/well in a 384 well microtiter plate and treated after 24 hours with drug diluted in the respective culture medium at the indicated concentrations. Cells were treated for 72 hours before the addition of CellTiter-Glo reagent and read on a M5 Spectramax plate reader (Molecular Devices). Raw data was normalized to DMSO controls and a three-parameter log-logistic function was fit to the data for an ICCells were treated as indicated with DMSO, NaCl, LiCl, or tivantinib. For cell cycle experiments, cells were harvested following incubation, fixed with 70% cold ethanol and stored at −20 °C until analyzed. Cells were washed with PBS and cell cycle was determined by incubating in a 1 μg/mL DAPI /0.1% Triton X-100/PBS solution. For apoptosis experiments, treated cells were stained with Annexin V–APC (BD Biosciences) and 100 ng/mL DAPI according to the manufacturer’s instructions. PE Mouse Anti-Human CD11b/Mac-1 (BD Biosciences) was used to monitor cell differentiation. Analyses were conducted using a FACSCanto II benchtop analyzer (BD Biosciences). Cell cycle was analyzed using ModFitLT V3.2.1 (Verity Software House). Apoptosis and differentiation data was analyzed using Flowjo . Analyses represent data for singlet cells using a standard aggregate gating strategy.AML patient bone marrow mononuclear cells (BMNCs) were seeded into 6-well plates and treated overnight at the indicated concentrations of drug using IMDM (10% FBS) as the diluent. Treated cells were then collected and suspended in MethoCult™ H4034 Optimum methylcellulose medium (StemCell Technologies) containing additional drug, split into technical duplicates  and plated in 30 mm cell culture dishes. A colony was defined as a cell cluster containing >30 cells. Colonies were counted manually following 14 days of growth. Select samples were chosen for an additional readout after 19 days. Average colonies and standard deviation were calculated for each treatment. Samples for this project were archived and retrieved under both SRC and IRB approval for the Total Cancer Care® and Moffitt Cancer Center pilot protocol.15, which provides gene expression profiles of a number of mouse/human hematopoietic cells .GSK3α and GSK3β expression levels across different human myeloid lineages were queried using the Bloodpool aggregation of hematopoietic expression profiles from numerous studies catalogued in the manually curated BloodSpot databasehttps://oncologynibr.shinyapps.io/drive/)16 and imported into python for analysis. The redundant siRNA activity (RSA) score was used as the sensitivity measurement as the RSA sensitivity is calculated using all shRNA reagents against a given gene to determine a score17.shGSK3α and shGSK3β sensitivity data was downloaded from the Project DRIVE database (18. Data was split into training (0.75) and test sets (0.25). Let n is the number of cell lines included in the training set and p is the number of features. Let y) or by solving the following:In order to predict sensitivity of AML cell lines to tivantinib, we built a regularized linear regression model (elastic net) to select gene features that can predict a tivantinib response vector. Elastic net regularization is a machine learning algorithm that is specially suited for the case of many more input features (genes) than samples (cell lines). Candidate predictive features were selected from 18989 genes with normalized measures of gene expression in CCLE for cell lines that have tivantinib sensitivity data in CTRPv2 (n = 297)13. Briefly, c-(−)-tivantinib, c-(+)-tivantinib, and ampicillin were immobilized on NHS-activated Sepharose for Fast Flow resin . Non-coupled resin (blocked beads) and coupled resin were then blocked with ethanolamine for 4 hours. HL60 and U937 cells were lyzed and total cell lysate containing 10 mg of protein were added to the affinity matrix for 6 hours. Competition experiments were conducted by incubating total cell lysates with 20 μM BIO for 2 hours prior to affinity chromatography. Blocked beads were incubated with lysate without immobilized compound.Drug affinity chromatography experiments were conducted essentially as described previously19. Two trypsin missed cleavages were allowed, the precursor mass tolerance was 10 ppm. MS/MS mass tolerance was 0.05 Da. Dynamic modifications included carbamidomethylation (Cys) and oxidation (Met). Mascot search results were summarized in Scaffold 4.3.A nanoflow ultra high performance liquid chromatograph  coupled to an electrospray bench top orbitrap mass spectrometer  was used for tandem mass spectrometry peptide sequencing experiments. Samples were first loaded onto a pre-column  and washed for 8 minutes with aqueous 2% acetonitrile (ACN) and 0.04% trifluoroacetic acid. The trapped peptides were eluted onto the analytical column, . The 120-minute gradient was programmed as: 95% solvent A (2% ACN + 0.1% formic acid) for 8 minutes, solvent B (90% ACN + 0.1% formic acid) from 5% to 50% in 90 minutes, then solvent B from 50% to 90% B in 7 minutes and held at 90% for 5 minutes, followed by solvent B from 90% to 5% in 1 minute and re-equilibrate for 10 minutes. The flow rate on the analytical column was 300 nl/min. Sixteen tandem mass spectra were collected in a data-dependent manner following each survey scan. Both MS and MS/MS scans were performed in the Orbitrap to obtain accurate mass measurements using 60 second exclusion for previously sampled peptide peaks. Mascot searches were performed against the Swiss-Prot human database downloaded on June 12, 201421. Data was formatted into inter, prey and bait files using total spectral counts as a measure of abundance and ampicillin drug affinity chromatography experiments as negative controls. Data was then analyzed by SAINTexpress and the CRAPome within APOSTL to determine the probability of selective interactions of proteins with tivantinib23. The resulting files were merged and summarized in APOSTL’s interactive environment for analysis and visualization  revealed that GSK3α is overexpressed across multiple AML subtypes as compared to normal hematopoietic lineages  to GSK3α silencing as compared to GSK3β gene silencing 18. Therefore, to evaluate tivantinib’s efficacy across all AML cell lines in the Cancer Cell Line Encyclopedia (CCLE)24, we trained an elastic net regularized regression model to predict the area under the curve (AUC) sensitivity values of all cell lines with tivantinib sensitivity data in CTRPv2 (which does not include tivantinib sensitivity information for AML cell lines) using the gene expression profiles of these cell lines (CCLE) as features. Our model had good accordance between predicted and experimental values  which is comparable to similar models 26, such as the TCF7 cofactor MLLT11, which had the most highly weighted coefficient -tivantinib, but not (+)-tivantinib, displayed nanomolar efficacy in HL60 and U937 cell lines  while the potent and selective MET-inhibitor PF-04217903 was essentially inactive suggesting that GSK3, not MET, inhibition is responsible for tivantinib’s activity in AML cells , SGX253 (MET inhibitor), and ML320 (highly selective GSK3 inhibitor) sensitivity across cell lines present in CTRPv2. We then applied these models to predict AML sensitivity, and performed pairwise comparisons (Spearman) of the model predictions. As expected, tivantinib’s sensitivity profile was uncorrelated with SGX253 further supporting that MET is not involved in tivantinib’s mechanism in these cells. Interestingly, whereas tivantinib was only weakly correlated with paclitaxel, it was highly correlated with ML320 suggesting the GSK3 inhibition is the primary mechanism in which tivantinib elicits activity in these cells -tivantinib, which is currently in advanced clinical development, its enantiomer (+)-tivantinib, which is a much weaker GSK3 inhibitor, the nes Fig. . This islls Fig. . Since tlls Fig. . In summ13. Pulldowns were of high quality with good reproducibility between biological replicates 32, respectively. In addition, we filtered the data set for common binders using the Contaminant Repository of Affinity Purification-Mass Spectrometry Data (CRAPome)22. We prioritized targets with a SAINTScore ≥ 0.95, a CRAPomePCT ≥ 0.95 and an –ln(NSAF) ≥ −7 -tivantinib analog as previously described Fig. 13. Pulldtes Fig. . To iden −7 Fig. . These c −7 Fig. . Tivanti −7 Fig. . MET pro33. Furthermore, upon treatment with tivantinib we observed an increase in total β-catenin levels, which is characteristic for GSK3 inhibitors6. A larger and more prolonged increase in β-catenin was observed with LiCl than with tivantinib  as a potentially synergistic drug   were in clinical development so that identification of a drug that synergizes with tivantinib would have the potential for clinical translation. The data was highly reproducible with good correlations between biological replicates Fig. . One of rug Fig. 36. We po-C) Fig. .Figure 440, we next hypothesized that the observed synergy with tivantinib was a result of altered MCL-1 and BCL-XL protein levels. Interestingly tivantinib single agent and, more pronouncedly, ABT-199 combination caused a loss of anti-apoptotic MCL-1 and BCL-XL protein levels while maintaining pro-apoptotic Bak levels  to strong synergy (patients 3 and 4) values  as a single agent, as well as in combination with ABT-199. Using several different primary AML patient samples, tivantinib displayed a strong ability to inhibit colony formation at the clinically relevant concentration of 5 μM across all patients with only a few colonies remaining Figs , S7. Sins Figure , tivantis Figure  although41. In the context of cancer, GSK3 is best known in its function as a tumor suppressor, which is deactivated by AKT or Wnt signaling41. However, most studies have focused on GSK3β, whereas significantly less is known about GSK3α. Moreover, it is increasingly appreciated that GSK3 signaling is context-dependent. For instance, there have been several reports that describe tumor supporting roles of GSK3α in glioblastoma, pancreatic cancer, multiple myeloma, and MLL-rearranged leukemia44.GSK3 plays a central role in a broad range of cellular processes, including glycogen metabolism, insulin signaling, apoptosis and microtubule function. Accordingly, it is under investigation as a potential target in Alzheimer’s disease and diabeteset al. through a functional genomic screen as a promising target in AML5. However, targeting GSK3 in hematological malignancies does have theoretical challenges in that GSK3 is known to phosphorylate β-catenin thereby marking it for subsequent proteasomal degradation. Upon GSK3 inhibition, β-catenin accumulates, translocates to the nucleus and activates transcriptional pathways45. Such increased β-catenin signaling has been implicated in a number of leukemogenic effects, such as self-renewal of leukemic stem cells46. As β-catenin stabilization requires inhibition of both kinases and most GSK3 inhibitors target GSK3α and GSK3β with similar potency34, these compounds may possess some significant limitations. Accordingly, the nonspecific pan-GSK3 inhibitor LiCl, which is currently FDA approved for the treatment of epilepsy and bipolar disorder8, has met limited success in clinical studies of AML49. In addition to isoform selectivity, various other aspects, such as the binding mode, magnitude of inhibition, and kinome-wide target specificity influence the overall cellular outcome of inhibiting GSK3α. For this reason, not all GSK3 inhibitors should be treated equally.GSK3α has been identified by Banerji 14, but its target selectivity and mechanism of action has been a controversial subject. We and other groups have suggested that MET is actually not a significant target of tivantinib in many cancer cells50. We have previously observed that tivantinib, although being indeed a weak MET inhibitor, much more prominently targets GSK3α and GSK3β in NSCLC cells and that inhibition of these targets can explain its potent anticancer activity in NSCLC13. Importantly, we also noted remarkable kinome-wide specificity and some moderate selectivity of tivantinib for GSK3α over GSK3β, which are unique features among clinical GSK3 inhibitors12. It has also been suggested that tivantinib binds tubulin and inhibits microtubule dynamics resulting in anticancer activity50. While these observations are compelling, our results suggest that the sensitivity profile of tivantinib in AML cells more closely matches that of a GSK3 inhibitor. Furthermore, we show that pharmacological inhibition of GSK3 by LiCl largely mimics tivantinib’s effects in these cells with regard to viability, apoptosis, cell cycle arrest and differentiation. However, as GSK3α/β have well described roles in microtubule regulation through phosphorylation of Tau (MAPT)52 and other microtubule associated proteins, such as MAP2C53, it would be difficult to precisely identify the contributions to tivantinib’s overall cellular effects that stem from targeting tubulin in addition to GSK3, particularly as histone H3 phosphorylation is induced rapidly, which could indicate further crosstalk between GSK3 and the cell cycle regulation pathway54. Impairment of microtubule polymerization however may be translationally beneficial as it may result in synergistic anticancer activity in the context of dual GSK3 and BCL-2 inhibition as has been previously observed in breast cancer55. However, additional studies are necessary to elucidate the complex interplay between these pathways in AML.Tivantinib was originally developed as an inhibitor of the receptor tyrosine kinase MET5, analysis of publically available datasets showed that GSK3α is overexpressed in AML and that knockdown of GSK3α has strong effects on the viability of AML cell lines. We also show that tivantinib interacts with and inhibits GSK3α/β in AML cells and that it potently kills these cells by inducing apoptosis. Interaction of tivantinib with its intended target MET, which was observed to a minor extent in NSCLC cells13, was not detectable in AML cells. While tivantinib does target both GSK3α and GSK3β, its effects on β-catenin levels were somewhat less pronounced than with LiCl. This was consistent with our previous observation that tivantinib is more selectively targeting GSK3α13. Also, β-catenin stabilization was more transient with tivantinib, whereas it is sustained for a longer period of time upon LiCl treatment. Tivantinib may therefore provide an important therapeutic advantage over pan-GSK3 inhibitors, such as LiCl. Banerji et al. have shown that LiCl readily causes differentiation of AML blasts at relatively low concentrations5. Our results confirmed these observations and showed that tivantinib also induces differentiation. However, tivantinib was a much stronger inducer of apoptosis than of differentiation; and although LiCl also induces apoptosis, tivantinib is markedly more potent than LiCl in this regard, which might be due to additional effects of tivantinib on microtubules.In light of the suggested role of GSK3α in AML, we investigated the potential for repurposing tivantinib for the treatment of AML, which to the best of our knowledge has not been reported. Consistent with previous reports39, synergizes with tivantinib by further enhancing tivantinib’s already potent ability to inhibit cell viability and induce apoptosis. MCL-1 and BCL-XL expression have previously been associated with ABT-199 resistance40, and it is noteworthy that we observed a dose-dependent decrease in MCL-1 and BCL-XL levels following tivantinib treatment, which was enhanced in combination with ABT-199. This is consistent with previous reports showing that tivantinib downregulates these proteins in hepatocellular carcinoma56. It is also known that GSK3 transcriptionally regulates BCL-XL expression and that GSK3 inhibition by BIO or SB-415286 leads to a reduction in BCL-XL levels58. Interestingly, while BIO similarly downregulated BCL-XL in breast cancer cells, it also reduced MCL-1 expression, not via transcriptional control, but through a proteasome-dependent mechanism57. This downregulation of MCL-1 and BCL-XL expression likely contributes to the synergy observed between tivantinib and ABT-199. By downregulating anti-apoptotic MCL-1 and BCL-XL that cause ABT-199 resistance, tivantinib is amplifying the relative apoptotic effect of ABT-199. This synergy is in excellent agreement with a previous study that described cancer cells with increased β-catenin levels, for instance as the consequence of GSK3 inhibition, to be particularly sensitive to inhibition of BCL-2 by the ABT-199 analogue navitoclax35. Interestingly, in addition to modulation of anti-apoptotic proteins we observed that the tivantinib/ABT-199 combination completely abrogated β-catenin stabilization seen with tivantinib single drug treatment. This was apparent already after 4 hours and is therefore likely due to cross-talk between the GSK3 and BCL-2 pathways that is independent of altered transcription. This pronounced reduction of β-catenin persisted for 24 hours and could possibly help prevent some of the leukemogenic effects previously associated with β-catenin signaling in AML46. Thus by modulating tivantinib’s effects on β-catenin levels in conjunction with the amplification of apoptotic signaling, this suggests a superior therapeutic potential of this drug combination in AML.In addition to tivantinib exhibiting potent single agent activity in AML, we observed that the BCL-2 inhibitor ABT-199, which displays activity and is in clinical trials in AML11q23 MLL-rearranged leukemia, which has previously been shown to be sensitive to GSK3 inhibition28. Interestingly, high expression of GSK3 and BCL-XL has previously been suggested to correlate with poor prognosis in AML59. However, a more thorough investigation of GSK3α expression and signaling in AML is necessary to make detailed conclusions. Although tivantinib has been described to cause myelosuppression61, this is readily managed in most cases and tivantinib is generally considered a well-tolerated compound61, which has been evaluated in more than 40 clinical studies, including phase III. Considering also that the concentrations required for its activity in AML cells are well within the therapeutically achievable levels and could be potentially even further reduced in combination with ABT-19962, repurposing tivantinib provides a tangible opportunity for clinical translation into AML.In this context, it is important to note that tivantinib, as a single drug and even stronger in combination with ABT-199, showed potent anti-leukemic activity in AML patient-derived samples within clinically relevant concentrations. This appears to be independent of the mutational status of common prognostic genes although our sample size was too small to allow broader conclusions. A potential correlation with tivantinib sensitivity could be amplification of GSK3α expression levels as GSK3α is more highly expressed in several different subtypes of AML, including In summary, repurposing the advanced clinical drug candidate tivantinib based on its off-target GSK3α identified it as a highly potent agent in AML cells. Combination with the BCL-2 inhibitor ABT-199, which is already under clinical investigation for AML, further enhanced tivantinib’s potency and eliminated undesirable β-catenin activation. Together, these findings suggest that tivantinib, either as a single agent or in combination with ABT-199, represents a novel and promising therapeutic option for AML, a disease, which is still in high need for new therapies.Supplementary InformationSupplementary Table S1Supplementary Table S2


Comparative [Ca2+]-dependent fluorescence spectroscopy revealed that the native granules in Cupriavidus necator H16 act as a Ca2+ storage system, presumably for the regulation of its cytosolic Ca2+ level, but those from recombinant Escherichia coli do not. This study reveals intimate links between Ca2+ and native granule formation, and establishes a novel mechanism that intracellular PHB granules function as Ca2+ storage in order to relieve soil bacteria from Ca2+ stress.Soil bacteria accumulate polyesters , in which one end of the chain terminates with a carboxyl group) in the form of hydrated, amorphous nanogranules in cells. However, it is not clear what drives the structure of these biomaterials inside bacterial cells. Here, we determined that calcium guides intracellular formation of PHB nanogranules. Our systematic study using the surface zeta potential measurement and the carboxyl-specific SYTO-62 dye binding assay showed that the terminal carboxyl is not exposed to the granule surface but is buried inside native “unit-granules” comprising the mature granule. Extracellular Ca The most abundant PHA is poly([R]-3-hydroxybutyrate) (PHB). About 30 years after its discovery in the 1920s, PHB was recognized as the prototypical biodegradable thermoplastic with the potential to solve the challenge of waste disposal3. Since then, there have been remarkable advances in our understanding of PHA metabolism in cells3, and its application has been extended to the area of specialty materials, such as nanobeads and nanobiomaterials for drug delivery7.Polyhydroxyalkanoic acids (PHAs) are important biomaterials accumulated in the form of discrete cytoplasmic, nanogranular inclusions inside many bacteria and have been suggested to serve as carbon and energy reserves4. Various techniques, such as electron microscopy, wide-angle X-ray scattering, NMR spectroscopy and confocal microscopy, have been used to investigate the structure of PHA granules. In vivo NMR spectroscopy8 and X-ray analysis1 have shown that PHA in native granules is amorphous, even after isolation. From the crystallization kinetics analysis of medium-chain-length PHA, it was suggested that the polymer is more highly organized in native granules than in organic solvent-reshuffled artificial granules9. Analysis of PHA granules by atomic force microscopy (AFM) has shown porin-like structures in the surrounding membrane that are suggested to provide a portal to the amorphous polymer core and to act as sites of PHA metabolism and depolymerization10. The studies reported thus far have not provided any specific information about the structure (chain orientation or folding) of the polymer chains in the granules. The polymer chains in native granules have long been assumed to adopt randomly folded (entangled) conformations in an amorphous state of hydrated meta-stable structures11. The characterization of the amorphous structures of water-plasticized, gel-like PHA materials at the molecular or atomic level have long thus been being a challenging problem.However, little is known about the structure and assembly of PHA nanogranules in cells2+]-dependent fluorescence spectroscopy. The surface characterization investigated in this work revealed that the terminal carboxyl groups of PHB chains are not exposed to the surfaces of intracellular PHB granules in Cupriavidus necator H16. The [Ca2+]-dependent fluorescence spectroscopic data demonstrated that the directional PHB chain orientation may be essential for the calcium storage system in PHB-accumulating soil bacteria that harbor an innate pha gene locus12, which is described in the Results section. For comparison, we also investigated the polymer chain topography of native PHB granules from a recombinant Escherichia coli harboring the phbCAB operon responsible for PHB synthesis but not phasin gene (phaP). The single operon which regulates the three genes i.e phbCAB, encode the enzyme PHB synthase (PhbC), β-ketothiolase (PhbA) and NADPH-dependent acetoacetyl-CoA reductase (PhbB), respectively, is involved in the synthesis of PHB inside bacterial cell. PhbC is the key enzyme for PHB biosynthesis, which polymerizes (R)-3-hydroxybutyl-CoA thioester monomers into polymers. PHB can be degraded by depolymerases (PhaZ) intracellularly or extracellularly. PhaP is an amphiphilic protein localized in the interfacial region between cytosolic water and hydrophobic PHB inclusion body and responsible for the regulation of the size and number of PHB granule12. However, the mechanism of the involvement of phasin protein in the self-assembled formation of PHA granules in the cells is hitherto unknown.In the present report, we investigated the polymer chain topography in both native and artificial PHB granules using the surface zeta potential, the carboxyl-specific SYTO-62 dye binding assay, divalent cation sorption, and comparative ex. To identify the probable functional role of external Ca2+ in the enhancement of PHB accumulation, we measured the [Ca2+]ex-dependent expression of the PHB synthase phbC gene, which is responsible for PHB chain elongation, at the growth times of 24 and 40 h, which correspond to the start and mid-exponential phase of PHB accumulation, respectively  Fig. . For allium Fig. . Furtherles Fig. . These oely Fig. . The rea2+ added to the medium, we determined the amounts of Ca2+ stored in native PHB granules and that taken up by H16 WT cells grown on fructose , which ranged between 4.2 and 6.8 mg/g PHB. The experimentally measured values are rather low compared with the calculated values but both depending on [Ca2+]ex,, suggesting that significant amounts of the uptaken Ca2+ ions are encapsulated in PHB granules. The cells with higher levels of PHB accumulation demonstrated a gradual decrease in calcium uptake (%) with increasing [Ca2+]ex  exposed small granules sized approximately 20 to 30 nm in diameter with clear phase boundaries among the small granules, referred to as “unit-granules” in this study  surface morphology image analysis revealed that acetone washing of hypochlorite-processed udy Fig. . Howeverudy Fig.  or nativles Fig.  in this 11. However, the randomly folded conformation could not explain all our above results well. Besides, the adsorption of small molecules into large macromolecules usually depends on the geometry of the sorption sites. Therefore, it was speculated that the polymer chains in native granules are assembled in orderly folded conformations. To verify the hypothesis, we performed calcium absorption experiments against all the types of PHB granules. Compared with the Ca2+ content of the H16 native granules, the amount of Ca2+ adsorbed was very low. Only 1–130 μg of Ca2+ per g of PHB was adsorbed depending on the external Ca2+ concentration in the range of 1–100 μM. The amount of Ca2+ present in the isolated native granules was several hundred-fold higher than that adsorbed in vitro . Thus, the sorption mostly occurs nonspecifically and electrostatically. The ester groups of polyester chains could be electrostatic coordination sites of the cations. C. necator H16 and E. coli native granules showed quite similar sorption capacity whereas the artificial granules displayed significantly lowered sorption compared to the native granules. The four metal ions Mg2+, Ni2+, Cd2+ and Zn2+ exhibited more similar and stronger sorption than Ca2+. The 3 to 5 times lower sorption capacity of Ca2+ than the other four cations , but little spectral intensity changes were observed. Thus, the Ca2+ adsorption in the granules with randomly oriented chains must be mostly nonspecific. The fluorescence emission spectra also showed similar [Ca2+]-dependent changes, particularly at ~310 nm, for the native and artificial granules  or unidentified calcium channel if any.It is worth noting that the little spectral intensity changes of H16 artificial and 2. However, PHA accumulates mostly under unbalanced, nutrient-poor conditions in the presence of an excess carbon source2. Thus, [Ca2+]ex-dependent PHB accumulation and Ca2+ uptake may have implications for physiological roles that differ from those suggested in the literature. To survive harsh, nutrient-poor environments, soil bacteria may require a special survival kit, particularly in Ca2+-rich environments. The different growth characteristics of H16 WT and the ΔphbC mutant cells in nutrient-rich medium and nutrient-limited M1 medium  and M1 medium in the presence of various amounts of extracellular Ca2+ clarified the role of PHB nanogranules, as their viable cell counts were [Ca2+]ex-dependent when grown with fructose . FE-SEM analysis of the cells grown on crotonate 5 g/L and citrate 5 g/L further confirmed the suggestion . In addition, the additional Ca2+ did not induce significant effect on PHB accumulation (12~15 wt% in cell dry mass) in WT cells as well as the growth of WT and phbC mutant cells in NB medium. Thus, the extracellular Ca2+ was effective only in nutrient limited M1 medium, not in nutrient rich medium.Calls Fig. . Thus, ales Fig. . Howeverin vivo suggested that the bulk of PHB in native granules are in a hydrated amorphous meta-stable state most likely because of the plasticizing action of water8. Water may either hydrogen bond or form dipole-dipole interactions with the ester groups, thereby inhibiting chain-chain proximity, and localized pockets of water may exist. However, our results shed new light in this regard: the hydrated meta-stable state may be further stabilized by Ca2+-coordinated organization, as shown in our [Ca2+]-dependent fluorescence quenching experiments. Ca2+ is believed to play a role in the stabilization of the meta-stable state of the polymer, but the detailed architecture of the Ca2+-containing carboxyl end-group region in a particular conformational state, if any, remains to be identified in terms of a probable Ca2+ coordination geometry. Nevertheless, no significant differences in the X-ray diffraction pattern or FTIR spectral bands were observed between the dehydrated samples of native and artificial granules independent of their Ca2+ content, suggesting the localization of Ca2+ in the carboxyl end-group region so that the Ca2+ ions coordination do not significantly affect the overall dimension of the polymer chain folding in the dried state  widely found in both prokaryotes and eukaryotes, where Ca2+ is known to be complexed with polyphosphate25. In E. coli, it acts as voltage-gated Ca2+ channels with complex gating kinetics, their activity being implicated in the phase of growth-dependent control of cytosolic Ca2+ levels26. E. coli do not harbor the PHB synthesis genes such as phaC, phaP, phaZ, phaR, etc. but recently, a periplasmic protein, YdcS has been reported to exhibit short-chain PHB synthase activity27. On the contrary, in the case of granular PHB in C. necator H16, Ca2+ is considered to be complexed to the terminal carboxyl groups if we assume there is no other chelating agent such as cyclized 3HB dimer .As shown in the comparison of cell viability between H16 WT and 31. UgtP which localizes to the division site in a nutrient-dependent manner directly inhibits FtsZ assembly31. Moreover, uridine-5′-diphosphoglucose (UDP-glucose) is the substrate of UgtP. It is likely that changes in UgtP activity could be caused by the higher levels of UDP-glucose resulting from the use of sugars such as fructose as carbon source in the cultivation of H16 strains. Thus, cell elongation of H16 WT and phaC mutant grown on nutrient rich or fructose fed M1 medium may result from the inhibition of FtsZ polymerization by UgtP. But the cell elongation of WT grown on crotonate containing nutrient limited medium is believed to be caused by Ca2+ level regulation by PHB nanogranules because phaC mutant did not elongate. In vitro studies showed that Ca2+ stimulates FtsZ polymerization in vitro32. PHB granules from crotonate-grown cells contained much more significant amounts of Ca2+ (up to ~50 mg/g PHB), probably causing more significantly lowering cytosol Ca2+ level and eventually inhibiting cell division. Thus, intracellular PHB nanogranules may control the cytosol Ca2+, affecting cell division.During bacterial cell division, FtsZ undergoes guanosine 5′-triphosphate (GTP)-dependent polymerization to form the Z ring at the mid-cell2+ controlled manner in order that the water insoluble hydrophobic polymer chains do not perturb the other cellular system during the formation of unit-granules. The revealed structural difference between native and artificial granules explains the reason why they exhibit very different susceptibility to enzymatic hydrolysis. The Ca2+ storage is believed to relieve the cell from Ca2+ stress, especially in soil bacteria for survival in nutrient-poor ecological niches in nature. Thus, on the basis of the findings in this study, the role of intracellular PHB granules should be reassessed in terms of cell viability of soil bacteria in Ca2+ rich natural environment from the ecological point of view. The authors assure that the Ca2+ related results could be exploited in the application studies such as high PHB production in bacterial and plant cells as well as in an enzyme reactor and the design and preparation of novel PHB based nanoparticles and drug implants for biomedical applications with Ca2+ controlled polymer chain orientation. The isolated native PHA granules can be used as a storage/transport vehicle for calcium (PCT patented). In addition, ester capping of the carboxyl end group in PHA could be a means to control the degradation rate of PHA bioplastics in nature (US patent application).Calcium plays a pivotal role in numerous biological processes. The regulation of cytosolic concentrations of calcium is essential for the survival of an organism. We infer that the directional PHB chain organization occurs in a limited cytosol space in Ca2HPO4·12H2O, 0.24 g/L KH2PO4, pH 7.4) and lysed with 6% (w/v) of sodium hypochlorite solution  for 8 h under rapid stirring at 4 °C cold chamber. White granules were harvested by centrifugation  and washed twice with cold PBS buffer. Granules were suspended in deionized distilled water and then dialyzed with 12~14 kDa CelluSep  T4 molecular weight cut off (MWCO) cellulose tubing membrane for 2 days against at least 3 times change of deionized distilled water. The recovered PHA granules were stored at 4 °C. The 6% (w/v) hypochlorite solution contained 0.015 mg/L Ca2+. The ICP detected Ca2+ in the stripping medium(5 mL) was calculated to occupy only 1/1000~1/10000 of the amounts of Ca2+ detected in PHB granules recovered, negligible to our analysis purpose.PHA-accumulated cells were harvested by centrifugation , 15 g of wet cells were suspended in 100 mL of cold PBS buffer , solubilized in 1 mL of chloroform was added to 5 mL of aqueous solution of 0.05% (w/v) sodium deoxycholate. The mixtures were emulsified by sonication and the chloroform solvent of emulsified mixtures was removed by centrifugation  and subsequent stirring in the fume hood for 1 h. After removal of the solvent, the stable artificial PHA granules were obtained.Artificial PHA granules were prepared by a previously described methodPseudomonas stutzeri BM190, isolated in author’s lab, was used as source strains for PHB depolymerases as described in the Supplementary materials and methods.The activity of PHB depolymerase was assayed spectrophotometrically by measuring the initial decrease in the optical density (O.D.) of the PHA granules at 660 nm as detailed in the Supplementary materials and methods.C. necator H16 phaC gene was cloned into the kanamycin-resistant plasmid pVIK112 and introduced into E. coli S17-1 λ-pir by electroporation34. Conjugation was performed by filter mating with E. coli S17-1 λ-pir (pVIK112-phaC) and C. necator H16 as donor and recipient, respectively. The transconjugant (C. necator H16 pVIK112-phaC) was selected on LB medium containing kanamycin at 30 °C. The other mutants were prepared similarly. All primers’ sequences were provided in the Supplementary Table Amplified internal fragments from the C. necator H16 cells were fixed and dehydrated as described previously35. Hypochlorite treated PHB granules, isolated from C. necator H16 cells, were soaked in pure acetone for 1 h and the isolated granules were washed with fresh acetone. All the samples were coated with gold and observed through Philips XL30 S FEG field emission scanning electron microscopy .C. necator H16 wild-type cultures grown on PHA synthesis medium were harvested by centrifugation  and cells were prefixed in a 2.5% glutaraldehyde solution for 2 h. The samples were washed twice with 0.2 M PBS buffer (pH 7.2) and then postfixed in 1% osmium tetraoxide (OsO4) for 1 h. They were washed twice with PBS and dehydrated by exchange with a graded series of ethanol solutions, followed by propylene oxide. Pellets were infiltrated in a 3:7, 5:5, and 7:3 ratios of epoxy resin mixture and propylene oxide each for 1 h and finally embedded in fresh epoxy resin mixture overnight and then polymerized for 48 h at 50 °C. The polymerized blocks were sectioned with ultramicrotome (LEICA EM UC6). The thin sections were stained with uranyl acetate and lead citrate solutions, followed by imaging in a model Tecnai 12 transmission electron microscope  operated at 120 kV in the bright field mode.λ = 1.54056 Å) radiation was utilized for all X-ray experiments scanned from 5 to 80° (2 Å) with a step length of 0.05°.The X-ray analysis of artificial and native, granule suspensions was performed as wet state by using glass capillary. WAXD patterns of the PHA granules were recorded in a General Area Detector X-ray Diffraction System  equipped with a collimator having the diameter of 0.2–0.5 mm. Cu Kα  at a scattering angle of 20°. Native PHB granules were washed to remove any lipid impurities via immersion in acetone for 30 min at room temperature, followed by washing three times with water. Artificial PHB granules and PHB-1-octadecanol granules for zeta potential measurement were prepared under detergent-free conditions. The mean zeta potential of the PHA granules was determined in duplicate, and the average values were calculated.The carboxyl groups on the surface of PHA granules were characterized by fluorescence dye adsorption assay using SYTO-62  and F-7000 fluorescence Spectrometer . The native PHB granule was washed with acetone to remove lipid impurities by immersion for 30 min at room temperature, followed by water washing three times. Artificial PHB granule was prepared under detergent free condition. PHA granules and SYTO-62 dye were reacted in deionized water at room temperature for 1 h and then analyzed. The OD value (at 660 nm) of the two granule suspension was 0.6 where the granule size and the amount of PHB were similar. The dye concentrations were 0.65, 1.25, 2.5, and 5.0 μM. The fluorescence run conditions were as follows: excitation wavelength, 649 nm; emission start wavelength, 650 nm; emission end wavelength, 800 nm; scan speed, 240 nm/min; excitation slit, 5 nm; emission slit, 5 nm.C. necator H16 cells, native PHB granules, and chloroform-extracted PHB homopolymers was determined after acid hydrolysis. Each 100 mg of the freeze-dried C. necator H16 cells or 80 mg of the native PHB granules and chloroform-extracted PHB homopolymers was hydrolyzed with 10 mL of 6 N HCl  for 6 h at 100 °C. Blank aqueous 6 N HCl solution (HPLC grade) was used as a control. Ultra-pure water, 18 MΩ·cm deionized, was used in all experimental steps including cell washing. The concentration of each ion in each aliquot was then determined by inductively coupled plasma-atomic emission spectrometer (ICP-AES)  analysis. All experiments were performed in triplicate.The amount of divalent cations present in the freeze-dried C. necator H16 wild-type cells grown on PHA synthesis medium containing 20 g/L of fructose as the sole carbon source and 0 ~25 mM CaCl2 were harvested after 24 and 40 h. RNA isolation was performed by using the RNeasy mini kit  according to the manufacturer’s protocol. RNA molecules were incubated with DNase I to remove genomic DNA. One-step RT PCR was performed by using Rotor-Gene SYBR Green RT-PCR kit  according to the manufacture’s protocol. 16 S rRNA was used as an internal standard to estimate the relative expression level of the target gene by 2−ΔΔCT method36. All experiments were performed in triplicate.E. coli native granule (184.6 mg/Ll−1) solutions containing 100 μM, 10 μM, and 1 μM of either Ca2+ (as CaCl2), Mg2+ (as MgCl2), Zn2+ (as ZnSO4), Ni2+ (as NiCl2) or Cd2+ (as CdCl2) was incubated at 30 °C, 100 rpm for 5 h. Native PHB granules were washed with acetone to remove lipid and lipophilic impurities by immersion for 30 min at room temperature, followed by water washing three times. Artificial PHB granule was prepared under detergent free condition. After reaction, PHB granules were removed by centrifugation and the concentration of the remaining ion in each clear supernatant solution was then determined by inductively coupled plasma-atomic emission spectrometer (ICP-AES)  analysis. All experiments were performed in duplicate.o and Ce are the initial and remaining concentration of metal ions in solution.To evaluate the metal ion binding capacity of PHB granules each 10 mL of native granule (185.6 mg/L) and artificial granule (188.2 mg/L), E. coli native granule (184.6 mg/L), and PHB-1-octadecanol granule (186.4 mg/L) solutions containing 100 μM, 10 μM, or 1 μM of Ca2+ (as CaCl2) was shaken at 30 °C, 100 rpm for 5 h. Fluorescence impurities in the deionized water were removed by the treatment of charcoal. Emission and excitation of Ca2+ treated PHB granule suspensions were determined by F-7000 FL fluorescence spectrometer  analysis. The excitation spectra were obtained in the scan range between 200 and 360 nm with the emission at 370 nm, and the emission spectra between 275 and 520 nm with the excitation at 267 nm. The excitation and emission slit widths were set to 5 nm.Each 10 mL of native granule (185.6 mg/L), artificial granule (188.2 mg/L), C. necator H16 wild-type and phaC mutant cultures grown on nutrient-rich (NR) or PHB synthesis media were taken at the sampling times of 20, 40, 60, 84 and 108 h, gradient diluted with 0.85% NaCl and subsequently plated onto NR agar plates. All agar plates were incubated at 30 °C, and colony-forming units (CFU) were counted at 36 h. All experiments were performed in triplicate. The PHB synthesis medium contained 37 mM phosphate. The final pH of the cultures grown on fructose was 6.2–6.5 for 0–10 mM Ca2+ and 6.0 for 25 mM Ca2+, where the initial pH was 7.0.Aliquots of Pseudomonas stutzeri BM190 sequence is EU887946 and C. necator H16 phaC gene is NC008313.The GenBank accession number for the PHB depolymerases of Supplementary Information


In this fashion, astrocytic Ca2+ signaling is regarded as a processor of neural network activity by means of complex spatial and temporal Ca2+ dynamics. Accordingly, a key step is to understand how different patterns of neural activity translate into spatiotemporal dynamics of intracellular Ca2+ in astrocytes. Here, we introduce a minimal compartmental model for astrocytes that can qualitatively reproduce essential hierarchical features of spatiotemporal Ca2+ dynamics in astrocytes. We find that the rate of neuronal firing determines the rate of Ca2+ spikes in single individual processes as well as in the soma of the cell, while correlations of incoming neuronal activity are important in determining the rate of “global” Ca2+ spikes that can engulf soma and the majority of processes. Significantly, our model predicts that whether the endoplasmic reticulum is shared between soma and processes or not determines the relationship between the firing rate of somatic Ca2+ events and the rate of neural network activity. Together these results provide intuition about how neural activity in combination with inherent cellular properties shapes spatiotemporal astrocytic Ca2+ dynamics, and provide experimentally testable predictions.Intracellular Ca These can be triggered by neuronal activity and the subsequent release of neurotransmitters and increase in extracellular K+. Following Ca2+ activity, astrocytes can release gliotransmitters that act at the synaptic or perisynaptic level to strengthen or weaken synapses, or to change neuronal activity. This fueled a number of modeling studies that investigated the mechanisms through which synaptic activity triggers Ca2+ spikes in astrocytes and how, in turn, the astrocyte response affects the synapses   and the larger events occuring in the astrocyte core (soma and major processes). Of those larger events, a much greater fraction occured in major processes than in the soma. Occasionally, global events that invaded most of the core were observed. These events were not sweeping waves, but were triggered by the simultaneous occurence of Ca2+ events in multiple loci, generally in the gliopil, and presumably due to synchronous neuronal activity.These spatiotemporal events interact in complex ways with governing rules that are important to clarify  is expressed in terms of its concentrations i, and 2+ between the soma and the process is proportional to the difference in Ca2+ concentration between the two compartments.We model the astrocyte as a soma with five major processes . This fluctuating Ca2+ term is due in part to the Na+/Ca2+ exchanger (NCX), which is co-localized with Na+-dependent glutamate transporters, as well as neurotransmitter-gated Ca2+-permeable ion channels such as AMPA, NMDA, or P2X receptors  from internal stores. This work utilizes a representation of IPR flux taken from  are solved numerically using a first order Euler-Maruyama method , we first compute the correlation matrix Σ such that Σij = (1−δij)ρ+δij (where δij is the Kronecker Delta) and perform a Cholesky factorization Σ = LLT  . We explore how this leads to CICR-driven spikes in processes and soma. In general, nearby neurons can be correlated  is initially set to σ = 0.2 . One of the soma spikes is identified as a global event, defined when at least four of five processes spike within a period of 12.5 time units from the soma spike. Thus our model covers the three scales of Ca2+ activity observed experimentally , an intermediate timescale set by the process spikes , and the large scale of global events . The interval between successive spikes in a given process follows a sharp, approximately log-normal distribution  degree of correlation  with pairwise correlation ρ. We then compute the activity in the processes and soma as a function of σ for different values of ρ. Frequency curves are shown in Figure The amplitude of inputs is not the only factor that affects astrocyte Ca2+ influx signals decreases the threshold σ necessary for the soma to spike. In Figure We also find that higher correlation between CaFinally, we show in Figure 2+ due to neuronal activity. However, our model provides the ability to stagger the level of Ca2+ input between processes. We wish to better understand whether neuronal inputs should be distributed over many processes to effectively evoke somatic Ca2+ spikes.Up until this point, we have assumed a uniform distribution of Ca3, and in the third case, a single process is active, with neuronal activity σ1. We choose the levels σ1 and σ3 to ensure that in each case the sum of all active signals has identical variance.To gain some insight into this question, we perform three experiments in which we vary the number of processes subject to neuronal input Figure . In the Sm of m signals si with pairwise correlation ρ and variance σ2. It can easily be shown that the standard deviation of Sm is given byMore generally, consider the sum With the help of Equation 14, we obtain relationships that ensure comparative total input between the standard deviations of the process neuronal input when one and three processes are active:We find that concentrating inputs onto fewer processes slightly increases spiking frequency in the soma, and decreases the threshold σ required to evoke soma spiking Figure . At highJI, d) or through the ER . Accordingly, we set out to investigate how variations of diffusion coefficients DI and DE affect somatic spiking.Calcium gradients across neighboring cell regions are accounted for in our model by diffusion fluxes between adjacent processes, either through the cytosol . Increasing DI also slightly decreases the threshold value of σ for soma spikes. To determine how the rate of diffusive Ca2+ transfer impacts the relationship between process and soma spiking, we plot the average spike-triggered average of processes Ca2+ conditioned on soma spikes for different values of DI in Figure DI, the STA of process activity narrows and moves closer to the soma spike, suggesting that for higher values of DI fewer process spikes occurring within a short time frame are needed to elicit a soma spike. To confirm this, we plot the likelihood of different process spike counts preceding a soma spike for several values of cytosolic diffusion. This information is summarized in Figure DI = 0.05 or less, most soma spikes are triggered only once two or three process spikes occur close to each other. Thus, soma spikes occur less frequently and less regularly than process spikes, explaining the wider distribution of ISI for soma spikes To explain why the soma spikes at a lower rate at high σ, we note that two opposite factors shape the relationship between the rate of spikes in the soma and the neuronal input intensity. As σ increases initially, the spike rate in the processes rises, which leads to more spikes in the soma. Accordingly, the first part of the curves in Figure 2+ lowers soma excitability so much that soma spike rate decreases with σ.To summarize, at low σ, the spike rate increases as the slope of frequency vs σ is quite large. On the other hand, as σ increases, the higher spike rate due to higher excitation slows down, while the soma ER gets further depleted with increased process spike frequency. Around σ = 0.1, this depletion of soma ER Ca2+ for 2+ does not vary significantly over the range of DE considered. At higher values of σ  fast transients due to neuronal activity onto each process; (2) process spikes; (3) soma spikes; and (4) global events that involve spikes in soma and several processes within a short time window. Fast transients (1) are always produced as long as there is neuronal activity (σ > 0). Astrocyte processes integrate fast Ca2+ transients caused by neuronal inputs, leading to process spikes. The soma Ca2+ rises due to process spikes. We have not observed soma spikes (3) without process spikes (2) and rarely observed global events (4) without soma spikes (3). Thus the chain (1)-(4) of observable Ca2+ events defines a hierarchy, whereby an event high in the hierarchy only occurs when preceding events in the hierarchy have already been reached.The model generates four types of Ca2+ events (1)-(4) observed in the hierarchy depend on the parameters σ and ρ, which respectively describe neuronal activity and input correlation. At very low σ, we do not observe spikes in either processes or soma: only fast Ca2+ transients (1) occur in the processes. At higher σ, processes begin to spike (2) and their spike rate increases with σ. The spiking frequency in the process reproduces the behavior of the spiking rate in a single compartment model with identical σ . In turn, this affects synapses under its control, active or not. Finally, synaptic activity occurring in more than one process may evoke somatic spikes and global events, (3) and (4), depending on the degree of synchrony of synaptic activation. These events in turn may lead to synaptic plasticity in all synapses covered by the astrocyte. Araque's hypothesis only holds if a hierarchy of Ca2+ events results from a hierarchy of network synaptic activity. Our results support this hypothesis by demonstrating that the different types of astrocyte Ca2+ events follow such a hierarchy. The higher in the hierarchy, the more synapses over a larger area may be affected synchronously by astrocyte signaling.In addition to many roles played by astrocytes as neuron support cells and regulators of blood flow, there is growing evidence that astrocytes also modulate the activity of neural circuits by acting on neuronal excitability and on synaptic activity and plasticity. It has been suggested that the spatiotemporal distribution of neuronal activity determines the profile of CaOur results may also explain why astrocytes in the visual cortex maps have sharper tuning curves than do neurons. Schummers et al.  measured2+, plays an important role in these Ca2+ events. Spiking in the soma occurs as a response to increased levels of neuronal activity when the ERs in the soma and processes connect through diffusion. Setting DE to a non-zero value resulted in a qualitative change in the relationship between the amount of neural activity and the soma spike frequency. More specifically, the graph of average frequency vs. σ becomes non-monotonic, initially increasing at low values of σ, then decreasing back toward 0. During a process spike ER, Ca2+ in the process becomes depleted, which leads to diffusion of Ca2+ from the soma ER to the ER in the processes. Since the processes spike more frequently than the soma, the net result is a decrease of Ca2+ in the soma ER and lower soma excitability.CICR generates spikes while somatic and global events rely on diffusion between processes and the soma. Therefore the ER, which is the main store of astrocytic Ca2+ excitability, Ca2+ in ER plays the role of the recovery variable. Thus, the loss of Ca2+ by the soma ER engenders a decrease in soma excitability as σ increases from the lower levels. With a different model with de-inactivation of IP3R channels by Ca2+ as the recovery variable, we may not see the drop in soma spike frequency as some ER Ca2+ becomes depleted, but rather a drop in soma spike amplitude.We note that in this model of Ca2+ channels. Store-operated Ca2+ entry would activate once the ER Ca2+ reaches a low level, potentially resulting in an influx of Ca2+ through the cytoplasm. This could prevent the decrease in soma excitability at high σ. Thus, a modification in the parametrization of Ca2+ excitability in the model might impact cause and effect between processes and soma ER.Our model does take into account the effect of store-operated Ca2+ activity in several forms of neurodegenerative disease , β-amyloid buildup has been shown to initiate reactivity in astrocytes (Alberdi et al., 2+ influx, on Ca2+ spiking and global events.Prior to the development of β-amyloid plaques, astrocytes undergo atrophy as a result of reactive gliosis (Verkhratsky et al., 2+ events observed in astrocytes. A parametric study conducted with respect to Ca2+ influx intensity and pairwise correlation, DI, and DE, suggests that the variability of neuronal activity seen by the astrocyte sets the spiking frequency in both the processes and in the soma. The correlation between the neuronal activity in the different processes controls the number of global events. Our calculations also suggest that diffusion between the ER of the soma and of the major processes has an important effect on the dynamics of Ca2+ events in astrocytes. A detailed look at the mechanics behind the global events and the conditions under which synchronization occurs remains a subject of future investigation.We have demonstrated that a functional compartmental model can answer questions about the rules that govern the generation of CaAll authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.