Aberrant PI3K/AKT/mTOR signaling has been linked to oncogenesis and therapy resistance in various malignancies including leukemias. In Philadelphia chromosome (Ph) positive leukemias, activation of PI3K by dysregulated BCR-ABL tyrosine kinase (TK) contributes to the pathogenesis and development of resistance to ABL-TK inhibitors (TKI). The PI3K pathway thus is an attractive therapeutic target in BCR-ABL positive leukemias, but its role in BCR-ABL negative ALL is conjectural. Moreover, the functional contribution of individual components of the PI3K pathway in ALL has not been established.We compared the activity of the ATP-competitive pan-PI3K inhibitor NVP-BKM120, the allosteric mTORC1 inhibitor RAD001, the ATP-competitive dual PI3K/mTORC1/C2 inhibitors NVP-BEZ235 and NVP-BGT226 and the combined mTORC1 and mTORC2 inhibitors Torin 1, PP242 and KU-0063794 using long-term cultures of ALL cells (ALL-LTC) from patients with B-precursor ALL that expressed the BCR-ABL or TEL-ABL oncoproteins or were BCR-ABL negative.Dual PI3K/mTOR inhibitors profoundly inhibited growth and survival of ALL cells irrespective of their genetic subtype and their responsiveness to ABL-TKI. Combined suppression of PI3K, mTORC1 and mTORC2 displayed greater antileukemic activity than selective inhibitors of PI3K, mTORC1 or mTORC1 and mTORC2.Inhibition of the PI3K/mTOR pathway is a promising therapeutic approach in patients with ALL. Greater antileukemic activity of dual PI3K/mTORC1/C2 inhibitors appears to be due to the redundant function of PI3K and mTOR. Clinical trials examining dual PI3K/mTORC1/C2 inhibitors in patients with B-precursor ALL are warranted, and should not be restricted to particular genetic subtypes. The Phosphatidylinositol 3-kinase (PI3K) signaling pathway plays an important role in many physiological functions, including cell cycle progression, differentiation, survival, apoptosis and protein synthesis ,2. DysreActivation of PI3K leads to the phosphorylation of AKT on Thr308, which in turn induces activation of mammalian target of rapamycin (mTOR), a distal element of the PI3K/AKT/mTOR pathway ,17,18. mThe relative contributions of the individual components of the PI3K/AKT/mTOR signaling pathway for proliferation and survival in the cellular context of ALL remain to be resolved. Combined inhibition of PI3K and the mTOR complexes 1 and 2 may have the advantage to inhibit feedback loops and may be more efficient than targeting PI3K and mTORC1 alone. in vitro and in vivo, with slowing of tumor growth and delayed progression, but are poor inducers of apoptosis. One reason for this appears to be the simultaneous activation of feedback loops in conjunction with inhibition of mTORC1, resulting in survival of cells [A number of inhibitors of PI3K/AKT/mTOR signaling have been developed that selectively interfere with different components of this pathway, and thus differ in their biological effects. The allosteric mTORC1 inhibitors rapamycin and RAD001 display primarily antiproliferative effects of cells –33. As PI3K signaling is considered to be one of the decisive pathways for the transformation potential of BCR-ABL, and may play a role in causing imatinib-resistance, we investigated the antileukemic effects of PI3K, mTORC1 and combined PI3K, mTORC1 and mTORC2 inhibition in BCR-ABL/TEL-ABL positive and negative LTCs. We utilized several inhibitors that are currently in clinical testing, including the ATP-competitive selective pan-PI3K inhibitor NVP-BKM120, the dual PI3K and mTOR inhibitors NVP-BEZ235 and NVP-BGT226, and the allosteric mTORC1 inhibitor RAD001–37. We e6 cells/ml. After an initial lag phase, proliferation ensued resulting in prolonged expansion of cultured cells. For all functional assays described herein, only cells that had been passaged for less than 6 months were used. All other ALL-LTCs from patients with BCR-ABL/TEL-ABL positive and negative B-precursor ALL have been described previously [Initiation of a LTC from a BCR-ABL positive ALL patient harboring the T315I mutation was performed essentially as previously described . Brieflyeviously ,39. The 6 cells/ml, and proliferation was measured on day 4. Cell division of the LTC KÖ was determined by trypan blue dye exclusion assay using a Countess® Cell Counter (Invitrogen). Cell proliferation was assessed using the Cell Proliferation Kit II (XTT)  according to the manufacturer´s instructions. Cells were seeded at a concentration of 0.5x106 cells/ml and cell death was measured on day 4. Cell death was defined as positive staining for Annexin-V and/or propidium iodide by flow cytometry. Cell death was quantified using the Annexin-V-FLUOS Staining Kit  according to the manufacturer´s instructions. Cells were seeded at a concentration of 0.5x10Western blot analyses were performed using the NuPage Western blotting system (Invitrogen) according to the manufacturer´s instructions. The following antibodies were used: anti-phosphorylated AKT specific for the phosphorylated serine residue 473 (p-AKT-S473), anti-AKT (AKT), anti-phosphorylated S6 protein specific for the phosphorylated serine residues 235/236 (p-S6-S235/236) and 240/244 (p-S6-240/244) anti-S6 (S6), anti-phosphorylated 4E-BP1, specific for the phosphorylated threonine residues Thr37/46 (p-4EB-P1-Thr37/46), anti-4E-BP1 (4E-BP1) and anti-β-Actin (β-Actin). All antibodies were obtained from Cell Signaling Technology, Danvers, MA. Membrane blocking and antibody incubation were performed in 5% low-fat dry milk and 5% BSA, respectively, and the membranes were washed in Tris-buffered saline (TBS)  containing 0.1% Tween-20 (TBST). The antibodies were diluted in 5% BSA and 5% low-fat dry milk, respectively. Differences in response rate of BCR-ABL+/TEL-ABL+ versus BCR-ABL- LTCs towards the same concentration of single inhibitors were analyzed by Student's t-test. Statistical analyses were performed using the GraphPad Prism  software package. After the initial lag period, blast cells in the ALL-LTC KÖ had a doubling time of approximately 3 days. Surface marker expression demonstrated expression of CD19, CD79a, CD22, CD20, CD10, CD34, HLA-DR, TdT and CD13 (data not shown). Cytogenetic analysis at diagnosis revealed the following complex karyotype: 53,XX,del(1)(q25),+der(2)t,+6,der(9)tt,+14,+ der(18)t,+21+21,der(22)t,der(22)t. Mutation analysis of leukemic cells prior to and during culture demonstrated the presence of the BCR-ABL TKD gatekeeper mutation T315I. As expected, KÖ cells were unresponsive to imatinib, dasatinib and nilotinib when used at clinically achievable concentrations, known to inhibit proliferation and induce cell death in non-resistant BCR-ABL+ cells. The BCR-ABL+ LTC PH served as positive control .in vitro analyses of mutational and non-mutational TKI-resistance of BCR-ABL+ ALL have relied on leukemic cell lines, given the lack of cell culture models using primary ALL cells. We employed the 6 ALL-LTC without TKD mutations described above to determine whether the cells differed in their innate responsiveness to the clinically available TKI imatinib, dasatinib and nilotinib, facilitating further studies of non-mutational resistance. Five of the 7 LTCs, demonstrated a dose–dependent but variable responsiveness to the TKI, one LTC (BV) was resistant despite no evidence of a TKD mutation , and that the extent of imatinib-induced S6 dephosphorylation does not correlate with the sensitivity of the BCR-ABL+ ALL-LTCs to imatinib, point to an unexpected heterogeneity in mechanisms of TKI-induced inhibition. The commonly accepted role of PI3K/AKT/mTOR as a major downstream signaling pathway of BCR-ABL and TEL-ABL suggested that cells harboring an ABL-translocation might be more sensitive to inhibition of this pathway than BCR-ABL negative cells. In addition, we were interested whether the variable sensitivity of the BCR-ABL+ LTCs to ABL-directed TKI was associated with a differential responsiveness to inhibition of the PI3K/AKT/mTOR pathway.50, LY294002 and NVP-BKM120 inhibited proliferation by a median of 30% in ALL with an ABL-translocation (BCR-ABL+/TEL-ABL+) and by 50% and 55% in BCR-ABL negative cells (p=0.022 for NVP-BKM120)  . Induction of cell death of ALL cells by both PI3K inhibitors was likewise dose-dependent. BCR-ABL/TEL-ABL+ ALL cells were more sensitive to induction of cell death than cells without an ABL-translocation, with median of 39% vs. 20% cell death in response to LY294002 (p=0.013) and 60% vs. 40% with NVP-BKM120 . The antUnexpectedly, inhibition of PI3K by LY294002 and NVP-BKM120 was not associated with dephosphorylation of AKT at Ser473, a surrogate marker for inhibition of PI3K activity, in the majority of the ALL-LTCs, whereas AKT dephosphorylation was observed in the control Jurkat cells. To determine whether selective inhibition of PI3K had an effect on more distal components of this pathway, we examined the phosphorylation status of S6 and 4E-BP1, two targets of mTORC1 which are downstream of AKT. In the majority of ALL-LTCs and in the control Jurkat cells, S6 phosphorylation was reduced in dose-dependent manner in response to both LY294002 and NVP-BKM120, indicating that PI3K inhibition indeed inhibited mTORC1. In contrast, when ALL-LTCs were treated with these PI3K inhibitors, 4E-BP1 was not dephosphorylated . Thus, in ALL-LTCs, the magnitude of the antiproliferative and proapoptotic effects of selective PI3K inhibition is independent of the presence of an ABL translocation. This is consistent with the observation that the effect of PI3K inhibition on the phosphorylation status of more distal components of the PI3K pathway was also independent of an ABL-translocation. Among BCR-ABL positive ALL-LTC, their sensitivity to ABL-directed TKI did not correlate with responsiveness to PI3K inhibition. The variable sensitivity of the LTCs to PI3K inhibition could not be attributed to differences in the phosphorylation of AKT, S6 protein and 4E-BP1.The antiproliferative and proapoptotic effect of PI3K inhibition occurred in conjunction with dephosphorylation of the S6 protein, a downstream target of mTORC1. We therefore investigated whether selective inhibition of mTORC1 by RAD001 likewise resulted in suppression of proliferation and induction of cell death in ALL cells. RAD001 strongly inhibited phosphorylation of the S6 protein in the majority of ALL LTCs and Jurkat cells, but not of 4E-BP1 . This waMoreover, the different sensitivity of the individual ALL-LTCs to mTORC1 inhibition does not correlate with the phosphorylation pattern of the pathway components as determined by Western blotting. 50 values within the nanomolar range, both NVP-BGT226 and NVP-BEZ235 were more potent in terms of growth inhibition and induction of cell death than the selective inhibitors of PI3K and mTORC1 respectively , inhibited proliferation of BCR-ABL negative LTCs more potently than that of BCR-ABL/TEL-ABL positive cells, although this was significant only for NVP-BGT226 (p=0.0283 10nM) (50 (Treatment with NVP-BGT226 and NVP-BEZ235 at concentrations close to the IC83 10nM) . No diff0nM) 50  and S1B.0nM) (50 . The sam0nM)  and selective inhibitors  in the majority of ALL cells examined. In contrast, dephosphorylation of 4E-BP1, likewise downstream of AKT, was observed in response to ATP-competitive PI3K/mTOR and mTORC1/C2 inhibitors  but not Together, these data suggest that inhibition of both mTORC1 and mTORC2 by ATP-competitive inhibitors contributes to the antiproliferative and proapoptotic effects of the dual inhibitors. At inhibitor concentrations that induce cell death and dephosphorylation of 4EBP1, Ser473 AKT does not appear to be involved, suggesting a role of other PI3K-related kinases such as SGK .The greater antiproliferative and proapoptotic activity of dual (ATP-competitive) inhibitors of PI3K and mTOR, in conjunction with the exclusively antiproliferative effects of allosteric mTORC1 inhibition, raised the possibility of a contributory role of mTORC2. To determine whether mTORC2 inhibition indeed contributes to the antileukemic effect of the dual inhibitors NVP-BGT226 and NVP-BEZ235, we compared the antileukemic activity of these compounds with that of the selective inhibitors alone and in combination. As shown in To analyze whether inhibition of mTORC2 affects the phosphorylation level of the S6 protein and 4E-BP1, we performed western blot analysis after exposure of the different drug combinations described above. As shown in Taken together, these data indicate that the roles of mTORC1 and mTORC2 in regulating proliferation and survival of B-ALL cells are independent of an ABL-translocation. Furthermore, these data are consistent with a contribution of mTORC1 and/or mTORC2 to regulation of 4E-BP1 phosphorylation. PIK3CA and screened for the E17K mutation in the AKT1 gene, confirming that no mutations are present in any of the 13 ALL-LTCs (data not shown). Mutations or epigenetic silencing of PTEN occur in many tumor types including Ph+ ALL [3. We found no evidence of decreased PTEN expression in our ALL cells, indicating that diminished PTEN activity is not the cause of AKT activation. Functional studies involving primary ALL cells are hampered by the well-known inability to maintain human ALL blasts in short-term culture and the high initial rate of cell death. We have previously reported a unique cell culture system enabling long-term culture of leukemic lymphoblasts obtained from patients with ALL. These cultures represent different genetically defined ALL subtypes, i.e. leukemias harboring the BCR-ABL, TEL-ABL or E2A-PBX1 translocation, or no recurring genetic abnormality ,39. Our  Ph+ ALL , resultiOur results raise the question which of the individual components of the PI3K/AKT/mTOR pathway are most relevant for supporting leukemic cell growth and thus are the most attractive targets for therapeutic intervention. To dissect the relative contributions of PI3K and the mTORC1 and mTORC2 complexes, we exposed ALL-LTCs to the allosteric mTORC1 inhibitor RAD001 and the selective panPI3K inhibitor NVP-BKM120, both of which are being evaluated for anti-neoplastic activity in clinical trials. Blocking only mTORC1 by RAD001 failed to induce cell death in any of the ALL cells, and had a moderate antiproliferative effect, which was most conspicuous in the TEL-ABL expressing ALL cells. These findings are in line with numerous preclinical studies of various disease entities, which demonstrate that RAD001 has primarily antiproliferative effects ,27,32. TBCR-ABL transformed murine pro/pre-B cells, despite these cell´s dependency on PI3K signaling [We did not specifically examine and compare the impact of selective AKT inhibition on leukemic cell growth and cell death. By Western blotting, AKT showed only a minimal degree of phosphorylation at position Ser473 in the ALL-LTC compared to the Jurkat cell line. This is similar to published data showing weak AKT phosphorylation in p190ignaling . More imignaling , suggestignaling  recentlyignaling  demonstrIn conclusion, simultaneous inhibition of PI3K, mTORC1 and mTORC2 by the dual inhibitors NVP-BEZ235 and NVP-BGT226 exerts profound antileukemic activity against a broad spectrum of B-precursor ALL, irrespective of genetic subtype and – in the case of BCR-ABL positive ALL – their degree of responsiveness or resistance to clinically established ABL-kinase inhibitors. Combined inhibition of PI3K, mTORC1 and mTORC2 enhances the induction of cell death in a subset of these leukemias. In the cellular context of ALL, dephosphorylation of 4E-BP1 is observed in response to inhibition of both mTORC1 and mTORC2, but is not necessarily associated with induction of cell death. Our data provide a strong preclinical rationale for clinical studies exploring these compounds as treatment for ALL, but suggest that 4E-BP1 or S6 phosphorylation may not be robust biomarkers in clinical trials of PI3K pathway inhibitors in ALL. Figure S1The impact of combined mTORC1 and mTORC2 inhibition in B-ALL is independent of the presence of an ABL translocation. BCR-ABL+ , TEL-ABL+ (VG) and BCR-ABL-  LTCs were exposed to increasing concentrations of the mTORC1/C2 inhibitors KU-0063794, PP242 und Torin 1. (A) Proliferation was measured after 4 days of drug treatment. The proliferation rate of the ABL-translocated cells (BCR-ABL+/TEL-ABL+) and the BCR-ABL- cells did not differ in their response to treatment with KU-0063794, PP242 and Torin 1 at 1µM or 0.1µM, respectively (corresponding approximately to the IC50). 50). Treatment with 5µM PP242 or 0.1µM Torin 1 showed no difference between ABL-translocated cells (BCR-ABL+/TEL-ABL+) and the BCR-ABL- cells in terms of cell death induction.  Cell proliferation was assessed by XTT assay, induction of cell death was measured by Annexin-V/propidium iodide staining. The data shown represent the means + SD of 3 experimental replicates from one representative experiment out of 2 performed. (B) Cell death was measured after 4 days of drug treatment. The rate of cell death of the ABL-translocated cells (BCR-ABL+/TEL-ABL+) was significantly higher than of BCR-ABL negative ALL (p=0.0209 (*)) after exposure of 5µM KU-0063794 (corresponding approximately to the IC(TIF)Click here for additional data file.Figure S2The impact of combined mTORC1 and mTORC2 inhibition in B-ALL on AKT, S6 and 4E-BP1 phosphorylation. BCR-ABL+  and Jurkat cells were treated with increasing concentrations of KU-0063794, PP242, Torin 1 for 2h. Lysates of these cells were used for the detection of phosphorylated and total AKT, S6 and 4E-BP1 by Western blotting. Lysates of untreated Jurkat cells were used as positive controls and those of cells treated for 2h with 1µM Wortmannin (WM) served as negative controls. β-Actin was used as loading control. d = DMSO control. (TIF)Click here for additional data file.


Fibrillar deposits of highly phosphorylated tau are a key pathological feature of several neurodegenerative tauopathies including Alzheimer’s disease (AD) and some frontotemporal dementias. Increasing evidence suggests that the presence of these end-stage neurofibrillary lesions do not cause neuronal loss, but rather that alterations to soluble tau proteins induce neurodegeneration. In particular, aberrant tau phosphorylation is acknowledged to be a key disease process, influencing tau structure, distribution, and function in neurons. Although typically described as a cytosolic protein that associates with microtubules and regulates axonal transport, several additional functions of tau have recently been demonstrated, including roles in DNA stabilization, and synaptic function. Most recently, studies examining the trans-synaptic spread of tau pathology in disease models have suggested a potential role for extracellular tau in cell signaling pathways intrinsic to neurodegeneration. Here we review the evidence showing that tau phosphorylation plays a key role in neurodegenerative tauopathies. We also comment on the tractability of altering phosphorylation-dependent tau functions for therapeutic intervention in AD and related disorders. Characteristic accumulations of highly phosphorylated tau protein aggregates are found in several neurodegenerative tauopathies including Alzheimer’s disease (AD), progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), and some forms of frontotemporal lobar dementia (FTLD-tau). It was assumed that these pathological tau aggregates are the toxic form of tau. However, recent studies indicate that soluble and highly phosphorylated tau species are more closely associated with synaptic dysfunction and cell loss –4.Tau is normally a highly soluble protein found predominantly in neurons. A total of six different isoforms of tau are expressed in the adult human CNS via alternative splicing of the MAPT gene, which comprises 16 exons and is found on chromosome 17q21.3. Regulated inclusion of exons 2 and 3 gives rise to tau isoforms with 0, 1, or 2 N-terminal inserts, whereas exclusion or inclusion of exon 10 leads to expression of tau isoforms with three (3R) or four (4R) microtubule-binding repeats Figure –9.Tau is a phosphorylated protein, containing 85 potential serine (S), threonine (T), and tyrosine (Y) phosphorylation sites. Many of the phosphorylated residues on tau are found in the proline-rich domain of tau, flanking the microtubule-binding domain Figure B. Both tDespite the significant heterogeneity that exists between and within the various tauopathies, the deposited tau in pathological lesions is invariably highly phosphorylated. Mass spectrometric analysis, combined with Edman sequencing and specific antibody reactivity, shows that approximately ten phosphorylation sites can be detected on soluble tau purified from normal brain . In contThe proline-directed kinases glycogen synthase kinase-3 (GSK-3) –22, cyclNon-proline-directed kinases, such as casein kinase 1 (CK1) , microtuTyrosine kinases including Fyn , 36, AblA large number of different kinases and phosphatases have been shown to regulate tau phosphorylation, and an imbalance in tau kinase and phosphatase activity is believed to result in tau hyperphosphorylation in disease. Tau kinases include:In addition, several phosphatases dephosphorylate tau, including protein phosphatase-1, -2A, and -5   in models of AD , 41–43. O-GlcNAcylation, aggregation, and filament formation  residue 421 , and N-tin vivo  which is detected in late-stage AD . Alteredin vivo , and abnin vivo , 58. ThuDrosophila model of tauopathy, the suppression of tau-induced neurodegeneration is associated with clearance of ubiquitinated and phosphorylated low molecular weight (<250 kDa) tau oligomers, concomitant with increases in ubiquitinated tau monomers and high molecular weight (>250 kDa) tau oligomers  receptor subunit 2 phosphorylation and interactions between NMDA receptors and the post-synaptic density protein PSD-95  is a non-ATP competitive inhibitor of GSK3 that has entered clinical trials. Tideglusib has disease-modifying effects when administered to transgenic mice that develop both tau and amyloid pathology . Pilot tKinase inhibitors have entered clinical use for conditions unrelated to neurodegeneration . HoweverFinally, biomarkers are increasingly used to follow the progression of AD, and in some cases to support early diagnosis of the disease . HoweverThe 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.


Saccharomyces cerevisiae. The pheromone pathway includes a mitogen activated protein kinase (MAPK) cascade activated by a G-protein coupled receptor (GPCR). We used published mass spectrometry-based proteomics data to identify putative sites of phosphorylation on pheromone pathway components, and we used evolutionary conservation to assign priority to a list of candidate MAPK regulatory sites. We made targeted alterations in those sites, and measured the effects of the mutations on pheromone pathway output in single cells. Our work identified six new sites that quantitatively tuned system output. We developed simple computational models to find system architectures that recapitulated the quantitative phenotypes of the mutants. Our results identify a number of putative phosphorylation events that contribute to adjust the input-output relationship of this model eukaryotic signaling system. We believe this combined approach constitutes a general means not only to reveal modification sites required to turn a pathway on and off, but also those required for more subtle quantitative effects that tune pathway output. Our results suggest that relatively small quantitative influences from individual phosphorylation events endow signaling systems with plasticity that evolution may exploit to quantitatively tailor signaling outcomes.Cell signaling systems transmit information by post-translationally modifying signaling proteins, often via phosphorylation. While thousands of sites of phosphorylation have been identified in proteomic studies, the vast majority of sites have no known function. Assigning functional roles to the catalog of uncharacterized phosphorylation sites is a key research challenge. Here we present a general approach to address this challenge and apply it to a prototypical signaling pathway, the pheromone response pathway in  In response to stimuli sensed at the cell surface by receptors, eukaryotic cells propagate signal to the nucleus via intracellular signaling pathways. Such pathways inform decisions about cell fate, cell polarity, migration, cell-cycle regulation, cell proliferation and programmed cell death In organisms as diverse as mammals, invertebrates and yeast, researchers have used mass spectrometry based proteomics to identify thousands of sites of phosphorylation on proteins in cell signaling pathways. Some sites of phosphorylation serve as molecular switches that activate an enzyme , determine a protein’s subcellular localization , or target a protein for degradation  Saccharomyces cerevisiae – a well-developed system for studying eukaryotic cell signaling. In this system we can sensitively and accurately quantify pathway input, signal flow and pathway output in vivo in single cells We focused on the pheromone response system in the budding yeast The pheromone signaling system is stimulated by binding of a 13 amino acid peptide pheromone to a 7-transmembrane spanning G protein-coupled receptor (GPCR), activating a mitogen-activated protein kinase (MAPK) cascade and triggering downstream cellular events including gene transcription, cell cycle arrest, cell fusion and mating  [15]. UpHere, we mined mass spectrometry based proteomics data to identify phosphorylation sites with no known function on components of the pheromone pathway. We then prioritized for further examination phosphopeptides that contained conserved consensus sequences (associated with MAPKs) in regions of system proteins that contained no known or predicted structural domains. Finally we combined mutations, quantitative single-cell experiments and computational modeling to define novel quantitative roles for six phosphorylation events on three pathway proteins in regulating pheromone signaling. While more detailed and mechanistic computational models of the pathway have been published before, the simple models used here are course-grained in order to be generic and broadly applicable We found that mutation of three of the six sites decreases system output, mutation of two other sites increases system output, and mutation of the final site removes a negative feedback loop that conditionally diminishes system output when signal is low. We believe that a similar combination of approaches will allow researchers to characterize functional roles for phosphorylation events that contribute to the dynamic quantitative regulation of many signaling systems.S. cerevisae to at least S. bayanus (∼20 million years); (3) the chosen peptides lie outside of evolutionarily conserved predicted structural domains  Ste12, Ste50 and Dig1 function at different points in the pheromone response system upstream and downstream of the protein kinase cascade . We chosSTE12, STE50 or DIG1 with a mutant allele encoding the protein to be tested under the control of its native promoter at its endogenous locus (PRM1 promoter fused to a fluorescent protein (either YFP or mCherry), and used previously described fluorescence microscopy and flow cytometry-based single cell assays to measure fluorescence after treatment with different concentrations of pheromone We made individual haploid yeast strains in which we replaced wild type us locus . We mutaTo begin to elucidate the quantitative role of phosphorylation in the pheromone pathway, we focused on two tryptic peptides on the transcriptional activator Ste12  [32], .dig1? background  was indistinguishable from reference cells  was severely diminished, similar to the dig1? strain  in which all phosphorylation was induced by pheromone; 2) in which all sites were initially phosphorylated and dephosphorylation was pheromone-dependent; 3) in which T280 was phosphorylated in response to pheromone while T277/S279 were dephosphorylated in response to pheromone; and 4) in which all phosphorylation was constitutive and independent of pheromone . We studSaccharomyces cerevisiae.While many sites of phosphorylation have been mapped in proteomic studies from mammals, invertebrates and yeast, the vast majority of sites have no known function. We hypothesized that many of these sites are likely to exert dynamic regulatory roles in signaling pathways, the effects of which can only be revealed with quantitative assays in the context of the specific stimulus about which they convey information. We therefore developed a systematic, general approach to prioritize the study of individual phosphorylation events and their potential functions in signaling networks, and demonstrated the utility of our approach on components of the pheromone response system in the budding yeast Since the approach described here requires targeted mutagenesis of genomic DNA, which is straightforward to accomplish in genetically tractable model organisms like yeast, we acknowledge that this methodology is more challenging to implement in other organisms. However with recent advances in tools like zinc finger nucleases and TALENs it will become increasingly possible to target mutations in many diverse organisms and cell types We focused on three non-kinase proteins with distinct signaling roles upstream and downstream of the protein kinase cascade : 1) Ste1In strains expressing a protein with phosphorylation site point mutations, no cell will have the mutated site phosphorylated. In the reference strain in any given single cell, the fraction of the population of molecules of the protein with the site phosphorylated is unknown. We can thus expect that the effect of any phosphorylation site on signaling pathway output will be incompletely penetrant. The quantitative phenotypes we measured in the mutant strains – measurements made comparing the population of mutant cells to the heterogenous reference cells – may therefore underestimate the effect that these phosphorylation sites exert on the activity of the proteins they modify.On Ste12, we identified 2 putative phosphorylation sites, S400 and T525, that each contribute ∼25% to the transcriptional activity of Ste12 across a dose response of pheromone . Based oThe adaptor protein Ste50 links the MAP3K Ste11 to active Cdc42 and Ste20, thereby localizing Ste11 to its upstream activators at the plasma membrane. Ste11 then signals through different MAPK cascades via its association with different scaffold proteins: Ste5 directs signaling to the pheromone pathway, while Pbs2 directs signaling to the hyper-osmotic stress pathway. Several groups have suggested that phosphorylation of Ste50, possibly on S202, may help determine how much signal from active Ste11 goes to the pheromone pathway, and how much goes to the hyper-osmotic stress pathway T280A displayed a severely diminished transcriptional response, phenocopying the full deletion of Dig1. Strikingly, the closely situated residues T277 and S279 had the opposite effect in that they inhibit signal output: mutation of either residue leads to an increased pheromone response. Since these sites lack consensus MAPK sequence context, the mechanistic and architectural details of how they might exert their effects could be constrained through computational modeling, but not determined unequivocally. Similarly, since in this sensitized strain background, CFP-Ste12 required Dig1-YFP for full activity, the significance of the phenotypes of the Dig1 mutations for the native pheromone pathway remains to be determined. However, our current findings that closely situated mutations exert opposite effects are sufficient to suggest that multiple layers of post-translational regulation can be superimposed to fine-tune quantitative signal output.For the redundant repressor protein Dig1, we utilized a sensitized genetic background in which CFP-tagged Ste12 requires Dig1 for its full activity to increase the likelihood of revealing functional roles for Dig1 mutants without having to delete the paralogous repressor Dig2. We identified 3 putative sites on Dig1 that alter the pheromone response. T280 is required for Dig1-mediated Ste12 activity: cells expressing Dig1-YFPOur results indicate that many putative sites of phosphorylation contribute to and adjust the input-output relationship of this model eukaryotic signaling system. We propose that multiple small influences of such individual phosphorylation events can endow signaling systems with plasticity and evolvability. Consistent with this view, in the motifs that we studied on Ste12  and Ste50 (S202), the presence of a minimum consensus requirement for a MAPK substrate (serine or threonine preceded by a proline residue) arose relatively recently and is conserved in closely related yeast species but not in more distantly related yeast species  and 3A. In conclusion, we suggest that new layers of post-translational regulation can be gained and lost to rapidly adapt quantitative system output in the face of changing selective pressure without compromising the core structural and functional integrity of key signaling proteins. We note that this idea suggests means to systematically design and alter signaling pathway components to introduce novel regulatory loops or sever existing ones, and to confer new regulatory properties to pathway specific kinases and phosphatases. An approach based on iterating the design and construction of such re-engineered signaling pathways guided by quantitative experimentation and interpreted via appropriate models, should facilitate design-based alteration of signaling systems to bring about desired cellular behaviors.1). Strains were grown on YAPD plates  and/or YAPD liquid  media. Yeast deletions were selected on YAPD/HygB or YAPD/Kan plates. Mutant strains were grown on SD plates and/or SD liquid media .Routine growth of yeast strains was performed as described  was ordered from and synthesized at the W.M. Keck Foundation Biotechnology Resource Laboratory . We made a 1 mM stock solution and stored it in aliquots at -80°C.For large-scale cell growth cells were treated with 1 µM pheromone for the time indicated. For both microscopic and flow cytometric studies cells were treated with 1-20 nM pheromone as indicated for the described time.600 = 1.0. On each of the four plates we spotted 10, 100 and 1000 cells of each strain and incubated the plates 30°C for 20 hrs, following which the growth of cells was recorded.We qualitatively tested the pheromone sensitivity of all reference strains, deletion strains and phosphorylation site mutants. We prepared YAPD plates with 10-fold dilutions of pheromone, ranging from 1 µM to 1 nM. We diluted saturated overnight cultures of strains to OD2).We monitored phosphorylation of the MAPKs (Fus3 and Kss1) in populations of cells by Western blot analysis with rabbit anti-phospho-p44/42 antibodies . We monitored the appearance of fluorescent protein fusion proteins by Western blot analysis using mouse monoclonal anti-GFP antibodies (JL-8) . We verified the relative abundance of cell extract per gel lane by Western blot analysis using a mouse monoclonal antibody against the reference protein, GAPDH .We used one of two fluorescently-labeled secondary antibodies to visualize all results on Westerns .We used custom rabbit polyclonal antibodies against pheromone pathway proteins  with the pFA6a-kanMX6 template (3) and primer pair STE12KOf/STE12KOr, creating D12. We verified the deletion by PCR and Western blot analysis. Subsequently, we replaced the PRM1 ORF in D12 with a PCR product containing the mCHERRY coding sequence, the ADH1 terminator and the hph gene from pAG32-hphMX6 (4), creating DPY112. DIG1: We deleted DIG1 by one-step excision of ura3-marked DIG1-YFP from RCY1130 using 5-FOA (1) to select for excision products, creating RCY2005. We verified the deletion using epifluorescent microscopy and Western blot analysis. Subsequently, we replaced the PRM1 ORF in RCY2005 with a PCR product containing the mCHERRY coding sequence, the ADH1 terminator and the hph gene from pAG32-hphMX6 (4) creating RCY2005pch. STE50: We deleted STE50 from TCY3154 using PCR-mediated one-step replacement (1) with the pAG32-hphMX6 (4) template and primer pair STE50KOf/STE50KOr, creating DPY250. We verified the deletion by PCR and Western blot analysis.We created yeast strains lacking the ORFs STE12, DIG1-YFP and STE50. To make the mutant STE12 strains, we amplified the wild type STE12 gene  from W303a genomic DNA and cloned this PCR product into pRS406 at XhoI and EcoRI sites, creating pSTE12-406. We performed site-directed mutagenesis with the GeneTailor™ site directed mutagenesis kit  using the following primer pairs: STE12M3f/STE12M3r, STE12-s400a-f/STE12-s400a-r, STE12-s402a-f/STE12-s402a-r, STE12-t405a-f/STE12-t405a-r, STE12-s406a-f/STE12-s406a-r and STE12M4f/STE12M4r and methylated pSTE12-406 as the template, creating pSTE12m3-406, pSTE12s400a-406, pSTE12s402a-406, pSTE12t405a-406, pSTE12s406a-406, and pSTE12m4-406. The sequences of the mutated plasmids were verified . We linearized the mutant plasmids in the STE12 promoter region with BsiWI , and individually transformed them into DPY112 and plated on SD plates lacking uracil, creating DPY1203, CRY1004, CRY1005, CRY1006, CRY1007 and DPY1204. We verified the presence of and normal abundance of Ste12S400A,S402A,T405A,S406A, Ste12S400A, Ste12S402A, Ste12T405A, Ste12S406A, and Ste12T525A proteins using Western blot analysis and the absence of the Ste12 protein in the Ste12D reference strain.We created yeast strains with mutant alleles of DIG1-YFP mutant strains, we performed site-directed mutagenesis and sent for sequencing as above, using primer pairs DIG1M1f/DIG1M1r, DIG1M3f/DIG1M3r, Dig1-t277a-f/Dig1-t277a-r, Dig1-s279a-f/Dig1-s279a-r, and Dig1-t280a-f/Dig1-t280a-r and methylated pDIG1YFP-406 (3) template, creating pDIG1m1YFP-406, pDIG1m3YFP-406, pDIG1t277aYFP-406, pDIG1s279aYFP-406, and pDIG1t280aYFP-406. We linearized the mutant plasmids in the DIG1 promoter region with BstEII , individually transformed them into RCY2005pch and plated on SD plates lacking uracil, creating DPY1001, DPY1003, TCY3328, TCY3329, and TCY3330. We verified both the presence and normal abundance of Dig1S126A,S127A,S129A, Dig1T277A,S279A,T280A-YFP, Dig1T277A-YFP, Dig1S279A-YFP, and Dig1T280A-YFP proteins by Western blot analysis and the absence of the Dig1 protein in the Dig1D reference strain. We additionally verified that the Dig1-YFP proteins localized to the nucleus using epifluorescent microscopy.To make the STE50 mutant strains, we amplified the wild type STE50 gene  from W303 genomic DNA and cloned the PCR product into pRS406 at the XhoI site, creating pSTE50-406. We performed site-directed mutagenesis and sent for sequencing as above, using primer pairs STE50M1f/STE50M1r, STE50-s202a-f/STE50-s202a-r, and STE50-t205a-f/STE50-t205a-r and methylated pSTE50-406 as the template, creating pSTE50m1-406, pSTE50s202a-406, and pSTE50t205a-406. We linearized the mutant plasmids in the STE50 promoter region with PshAI , transformed into DPY250 and plated on SD plates lacking tryptophan and uracil, creating DPY5001, TCY3344.2, and TCY3345.2. We verified the presence and normal abundance of Ste50S202A,T205A, Ste50S202A, and Ste50T205A proteins by Western blot analysis and the absence of the Ste50 protein in the Ste50D reference strain.To make the PRM1-YFP). Starting from single colonies on YAPD plates, we inoculated 4 mL cultures in YAPD. We monitored growth by A600 and diluted into 4 mL SDC at the end of the day to obtain mid-log phase cultures in the morning. We diluted cultures to OD600 = 0.2 in YAPD and grew to OD600 = 0.8. We centrifuged 1.5 mL cells for 30 sec at 15,000 rpm, resuspended in 1.5 mL SDC with 40 µg/mL casein  and sonicated the cells to disperse clumps. We pipetted 500 µL of each strain into a 96 well deep well plate for the untreated (no pheromone) samples and added 50 µL 50 µg/mL cycloheximide , San Diego, CA). We pipetted 495 µL of each strain into the same 96 well deep well plate and added 5 µL of 100 µM pheromone in SDC/casein. We incubated the plate at 30°C for 15 minutes with shaking (300 rpm) and stopped the experiment with 50 µL 50 µg/mL cycloheximide in SDC/casein , San Diego, CA). We incubated an additional 2.5 hrs at 30°C, shaking at 300 rpm, to allow for fluorophore maturation. We sonicated the cells again, diluted 1:20 in SDC/casein/cycloheximide, pipetted 200 µL into 96 well glass bottom plates and let the cells settle for 10 minutes. We performed optical microscopic cytometry and image capture as described elsewhere  and image analysis, and data processing using the open source software packages Cell-ID and PAW .We quantitatively tested the pheromone response of all strains by measuring FP fluorescence in single cells as a surrogate for transcriptional output from a pheromone responsive promoter . We prepared a 4-fold dilution series of pheromone in SDC/casein ranging from 20 nM - 0.31 nM. We aliquoted 7×0.5 mL of each dilution into a 96-well deep well plate, and to another set of 7 wells we added 0.5 mL SDC/casein/cycloheximide in order to measure baseline pathway output. We sonicated 1.0 mL of each culture to disperse cell clumps and added 50 µL of each culture to the wells containing SDC/casein/cycloheximide and the pheromone-dilution series. We incubated the plate at 30°C for 3 hours, shaking at 300 rpm, at which point we stopped the experiment and allowed the fluorophores to mature as described above. We sonicated the plate and quantified reporter fluorescence by microscopy (3.1.a) and flow cytometry. 5 ul of cells was subjected to flow cytometric analysis using a BD LSR-II flow cytometer (UCSF QB3 core facility) equipped with a high throughput sampler, a 488 nm 100 mW laser, FITC emission filter and FACS DIVA software to compile .fcs files.We compared pathway output in ACLY379pch, DPY112, DPY1203, CRY1004, CRY1005, CRY1006, and CRY1007. Starting from single colonies, we inoculated 4 mL cultures in SDC (ACLY379pch and DPY112) or SD/-U  and grew over the course of the day to obtain log phase cells. We diluted overnight 4 mL cultures in the same media to obtain mid-log phase cells in the morning, at which point we adjusted to OD600 = 0.25 and allowed the cells to grow for one generation (90 minutes). We prepared a 4-fold dilution series of pheromone in SDC/casein ranging from 20 nM-0.31 nM. We aliquoted 6×0.5 mL of each dilution into a 96-well deep well plate, and to another set of 6 wells we added 0.5 mL SDC/casein/cycloheximide in order to measure baseline pathway output. We sonicated 1.0 mL of each culture to disperse cell clumps and added 50 µL of each culture to the wells containing SDC/casein/cycloheximide and the pheromone-dilution series. We incubated the plate at 30°C for 3 hours, shaking at 300 rpm, at which point we stopped the experiment and allowed the fluorophores to mature as described above. We sonicated the plate and quantified reporter fluorescence by microscopy (3.1.a).We compared pathway output in RCY1130pch, RCY2005pch, DPY1003, TCY3328, TCY3329, and TCY3330. Starting from single colonies, we inoculated 4 mL cultures in SDC (RCY1130pch), SD/-W (RCY2005pch), or SD/-U  and grew over the course of the day to obtain log phase cells. We diluted overnight 4 mL cultures in the same media to obtain mid-log phase cells in the morning, at which point we adjusted to OD600 = 0.25 and allowed the cells to grow for one generation (90 minutes). We prepared a 4-fold dilution series of pheromone in SDC/casein ranging from 20 nM-0.31 nM. We aliquoted 5×0.5 mL of each dilution into a 96-well deep well plate, and to another set of 5 wells we added 0.5 mL SDC/casein/cycloheximide in order to measure baseline pathway output. We sonicated 1.0 mL of each culture to disperse cell clumps and added 50 µL of each culture to the wells containing SDC/casein/cycloheximide and the pheromone-dilution series. We incubated the plate at 30°C for 3 hours, shaking at 300 rpm, at which point we stopped the experiment and allowed the fluorophores to mature as described above. We sonicated the plate and quantified reporter fluorescence by microscopy (3.1.a).We compared pathway output in TCY3154, DPY250, DPY5001, TCY3344.2, and TCY3345.2. Starting from single colonies, we inoculated 4 mL cultures in SD/-W (TYC3154 and DPY250), SD/-W-U  and grew over the course of the day to obtain log phase cells. We diluted overnight 4 mL cultures in the same media to obtain mid-log phase cells in the morning, at which point we adjusted to ODwww.proteome.com] and the Saccharomyces genome database (S288C strain background) [www.yeastgenome.org].Previously determined sites of phosphorylation, protein domains, protein/protein interaction information and gene and protein sequences were obtained from primary literature, the Biobase YPD database [S. cerevisiae pheromone pathway protein orthologs in other yeast species. In two cases (Fus3 and Kss1) orthologs from some species were not included in the ortholog assignments. In these cases we obtained the absent ortholog sequences from the Y. lipolytica database (9) from orthlogues assigned in (10) and from the Wapinski update (January 2009) that is available on SGD (yeastgenome.org) in the fungal orthogroups repository. We used the Yeast Gene Order Browser (YGOB) to distinguish orthologs and paralogs in cases of retained duplicates (11).We used tree-assisted ortholog alignments to identify S. cerevisiae Ste12, Dig1, and Ste50 to the best matching sequences in the orthologs identified by Wapinski et al. to demonstrate the conservation of motifs and phosphorylation sites.We aligned regions of For each protein of interest , we wrote a set of ordinary differential equations (ODEs) to describe roles for phosphorylation sites in the context of pheromone signaling. All reaction equations are based on mass action kinetics, and a Hill function describes the transcriptional induction step. Although the models employ the standard mathematical approach of ODE-based mass action equations, the models qualitatively differ from standard approaches in two important ways.First, instead of explicitly keeping track of concentrations of the species in physical units, the models represent the species in abstract, non-physical units of “activity”. These abstract species still exert their effects in proportion to their amounts, and thus still operate in a mass action paradigm. This method emphasizes the generic architectural constraints of the pathway and avoids the requirement of fitting specific unmeasured parameters.Second, the models incorporate phosphorylation in a non-canonical way. Standard ODE models represent unmodified and modified proteins as distinct species that have their own production, decay and reaction rates. Here, in contrast, phosphorylation does not generate novel species with new properties, rather phosphorylation tunes the inherent activity of the native proteins by acting “in trans”. In this way, the models remain uncluttered by additional unmeasured parameters and assumptions, and therefore emphasize how the phosphorylation events tune the activity of the protein they modify. This approach could be used to study the role of any protein modification.To implement the models, equations were coded and simulated across a pheromone dose response in MatLab R2008a using the ODE23s solver . Parameters were all set to 1 to initiate the system, and were modified to fit the experimental data. Once a set of parameters was obtained that fit the experimental data, we performed sensitivity analysis by sweeping through 2- and 10-fold increases and decreases of each parameter and simulating the ratio of mutant to reference strain transcription in response to 20 nM pheromone (supplementary figures). The observed differences between the mutants and reference strain transcriptional responses were insensitive to most parameter changes. Sensitive parameters are discussed in the main text.Figure S1S402A and Ste12T406A have the same dose response as wild type.Ste12 Cells bearing wild type or mutant Ste12 were treated with the indicated doses of pheromone and PRM1 driven mCherry was measured by flow cytometry.(PDF)Click here for additional data file.Figure S2Modeling phosphorylation sites in trans. The modeling strategy employed here treats the phosphorylation sites as separate entities from the proteins they modify (left). These phosphorylation sites (p sites) activate or inhibit the protein they modify (substrate) as a function of their concentration. In the abstracted example shown, reminiscent of the S202-mediated negative feedback loop, the effect of the phosphorylation site is the same whether “in trans” or as a “new species” – that is, a net negative effect on the activity of the MAPK. Advantages of the “in trans” model are that there is one fewer species and 4 fewer reaction rates to model. Moreover, there are fewer mechanistic assumptions in the “in trans” model, since the net inhibitory effect is all that is modeled. In the “new species” model, a mechanism must be specified for how the inhibitory effect happens (here it is shown as increasing the rate of MAPK dephosphorylation). The “in trans” formulation allows the models to be simplified, generic and easily modifiable without making mechanistic assumptions.(PDF)Click here for additional data file.Figure S3Results of Ste12 modeling are robust to changes in parameters. The strength of each parameter depicted in the cartoon model as well as the degradation constant for Ste12 were increased and decreased by 2-fold (top panels) and 10-fold (bottom panels), and the ratio of simulated output of wild type to S400A at 20 nM pheromone (the mutant phenotype) is plotted. The phenotype persists in the presence of 2-fold changes, but changes in magnitude with 10-fold changes to the parameters.(PDF)Click here for additional data file.Figure S4S202A,T205A and Ste50T205A.Dose responses of Ste50 Cells bearing mutant versions of Ste50 were treated with pheromone in the presence of 1-NM-PP1, imaged by epifluorescent microscopy and quantified using Cell-ID.(PDF)Click here for additional data file.Figure S5Results of Ste50 modeling are robust to changes in parameters. The strength of each parameter depicted in the cartoon model were increased and decreased by 2-fold (top panels) and 10-fold (bottom panels), and the ratio of simulated output of wild type to S202A at 20 nM pheromone (the mutant phenotype) is plotted. The phenotype persists in the presence of 2-fold and 10-fold changes.(PDF)Click here for additional data file.Figure S6T277A,S279A,T280A resides in the nucleus and does not destabilize Ste12.Dig1 Cells bearing CFP-Ste12 and either wild type or mutant Dig1-YFP were imaged in by epifluorescence microscopy. Single channel and merged images are shown.(PDF)Click here for additional data file.Figure S7S269A,S272A,S275A activates the pheromone response like wild type.Dig1 A. Alignment of the full tryptic peptide identified by mass spec as being phosphorylated against Dig1 orthologs in other yeast species. B. Cells bearing Dig1, Dig1S269A,S272A,S275A , Dig1T277A,S279A,T280 and cells deleted for DIG1 treated with 20nM pheromone for 3hrs. Dig1S269A,S272A,S275A is indistinguishable from wild type.(PDF)Click here for additional data file.Figure S8Dig1 model 2 and model 4 do not fit the experimental data. A. Cartoon depiction of Dig1 model 2, in which phosphorylation of T277 and T280 is constitutive and independent of pheromone. In this model, in order to have a dose dependent increase in Dig1 activity in the presence of constitutive phosphorylation of T277 and T280, we inserted a pheromone bypass directly on Dig1. B. Simulation of Dig1 model 2: To agree with the wild type response, the strength of this bypass was such that the contribution of phospho-T277 and -280 were negligible. Thus the mutants are identical to the wild type. C. Cartoon depiction of Dig1 model 4, in which dephosphorylation of both T277 and T280 is pheromone-dependent. D. Simulation of Dig1 model 4: The strength of the influence of each phosphorylation site had to be so strong, such that if one site was mutated, the effect of the other dominated over the pheromone response. Thus, the mutants cannot recapitulate the experimental dose responses.(PDF)Click here for additional data file.Figure S9Dig1 model 1 is robust to 2-fold changes in parameters that determine the influence of the phosphorylation sites. The strength of each parameter depicted in the cartoon model were increased and decreased by 2-fold (top panels) and 10-fold (bottom panels), and the ratios of simulated output of wild type to T277A (black) and wild type to T280A (red) at 20 nM pheromone are plotted. The T277A phenotype persists (within pink boxes) with 2-fold changes to every parameter. The T280A phenotype persists except when the strength of the the Dig1-independent pheromone bypass (B4) becomes too strong. 10-fold changes to any parameter significantly change the simulation results.(PDF)Click here for additional data file.Figure S10Dig1 model 3 is robust to 2-fold changes in parameters that determine the influence of the phosphorylation sites. The strength of each parameter depicted in the cartoon model were increased and decreased by 2-fold (top panels) and 10-fold (bottom panels), and the ratios of simulated output of wild type to T277A (black) and wild type to T280A (red) at 20 nM pheromone are plotted. The T277A phenotype persists (within pink boxes) with 2-fold changes to every parameter. The T280A phenotype persists except when the strength of the the Dig1-independent pheromone bypass (B5) becomes too strong. 10-fold changes to any parameter significantly change the simulation results.(PDF)Click here for additional data file.Table S1Strains used in this study.(DOCX)Click here for additional data file.Table S2Primers used for strain construction and mutagenesis.(DOCX)Click here for additional data file.Table S3Plasmids used in this study.(DOCX)Click here for additional data file.Table S4Public database links to phosphopeptides analyzed in this study.(DOCX)Click here for additional data file.Table S5P-values for mutant phenotypes.(DOCX)Click here for additional data file.Materials and Methods S1(DOCX)Click here for additional data file.Text S1Matlab code for simulations.(DOCX)Click here for additional data file.


RNAi-mediated depletion of MAP3K4 and MAP3K10 results in the inhibition of the TGFβ-induced p38 MAPK phosphorylation. Furthermore, the depletion of MAP3K10 from cells homozygously knocked-in with a catalytically inactive mutant of MAP3K4 completely abolishes the TGFβ-induced phosphorylation of p38 MAPK, implying that among MAP3Ks, MAP3K4 and MAP3K10 are sufficient for mediating the TGFβ-induced activation of p38 MAPK.The signalling pathways downstream of the transforming growth factor beta (TGFβ) family of cytokines play critical roles in all aspects of cellular homeostasis. The phosphorylation and activation of p38 mitogen-activated protein kinase (MAPK) has been implicated in TGFβ-induced epithelial-to-mesenchymal transition and apoptosis. The precise molecular mechanisms by which TGFβ cytokines induce the phosphorylation and activation of p38 MAPK are unclear. In this study, I demonstrate that TGFβ-activated kinase 1 (TAK1/MAP3K7) does not play a role in the TGFβ-induced phosphorylation and activation of p38 MAPK in MEFs and HaCaT keratinocytes. Instead,  These pTGFβ ligands initiate cellular responses by binding to their cognate type II and type I transmembrane receptor serine threonine protein kinases. Upon ligand binding, the type II receptor phosphorylates and activates the type I receptor kinase . In the −/− cells [Among the MAPK pathways activated by the TGFβ ligands, the activation of p38 MAPK has been the best characterized and widely investigated. Both SMAD-dependent and -independent mechanisms have been proposed for the TGFβ-induced phosphorylation and activation of p38 MAPK –17. Inhi/− cells . Another/− cells . MEKK1  and MLK2 (MAP3K10) results in a moderate reduction in the TGFβ-induced phosphorylation of p38 MAPK. The depletion of MLK2 (MAP3K10) in cells with homozygous knockin of catalytically inactive MEKK4 (MAP3K4) results in a complete loss of the TGFβ-induced phosphorylation of p38 MAPK, implying that MEKK4 and MLK2 mediate the TGFβ-induced phosphorylation and activation of p38 MAPK in MEFs and HaCaT keratinocytes.In this paper, I examine the roles of various MAP3Ks in mediating the TGFβ-induced phosphorylation of p38 MAPK. I demonstrate that the loss of TAK1 (MAP3K7) in mouse embryonic fibroblasts (MEFs) or human keratinocytes (HaCaT) does not affect the levels of TGFβ-induced phosphorylation of p38 MAPK. Furthermore, restoring wild-type (WT) or catalytically inactive TAK1 in TAK1-deficient MEFs does not alter the ability of TGFβ to induce the phosphorylation of p38 MAPK. By using a comprehensive 3.3.1.a). Treatment of these cells with TGFβ for 45 min resulted in phosphorylation of SMAD2 to the same extent (figure 1b). Rather surprisingly, the levels of TGFβ-induced phosphorylation of p38 MAPK observed in TAK1−/− MEFs were similar to those seen in WT MEFs (figure 1b). Restoration of WT TAK1 or KD TAK1 in TAK1-deficient MEFs did not result in significant changes to the levels of TGFβ-induced phosphorylation of p38 MAPK, albeit the expression of HA KD TAK1 was less than HA WT TAK1 (figure 1b). In order to determine whether TAK1 plays a role in modulating a time-dependent activation of p38 MAPK in response to TGFβ, a time course of TGFβ treatment was performed in these cells (figure 1c). No significant differences in TGFβ-induced phosphorylation of SMAD2 or p38 MAPK were observed in WT or TAK1-deficient MEFs, nor in TAK1-deficient MEFs restored with WT or KD TAK1 at any of the time points assayed (figure 1c). As expected, interleukin-1α (IL-1α) induced a robust p38 MAPK phosphorylation and loss of IκBα only in WT MEFs but not in TAK1-deficient MEFs (figure 1c). The IL-1α-induced p38 MAPK phosphorylation, and loss of IκBα was partially rescued in TAK1-deficient MEFs expressing HA WT TAK1 but not HA KD TAK1 (figure 1c).In order to investigate the contribution of TAK1 in mediating the TGFβ-induced phosphorylation of p38 MAPK, I obtained WT and TAK1-deficient MEFs . Additiofigure 1d). TGFβ induced similar levels of SMAD2 phosphorylation in WT or TAK1-knockout MEFs (figure 1d). As expected, IL-1α-induced p38 MAPK was significantly inhibited in TAK1-knockout MEFs compared with the WT (figure 1d).In order to complement the above findings and definitively establish that TAK1 does not mediate the TGFβ-induced phosphorylation of p38 MAPK, I obtained a different set of MEFs from WT and TAK1-deficient mice that were generated independently using different targeting strategy . By usinfigure 13.2.in vitro kinase assay developed for the measurement of TAK1 activity from cell extracts [Next, in order to assess whether TGFβ induces TAK1 kinase activity, I used an extracts . As expe3.3.It has been reported that TAK1 impacts the BMP pathway in chondrocytes in part by directly phosphorylating the BMP-activated SMADs at their activating SXS motif . Treatme3.4.RNAi-based screening targeting the depletion of all of the human MAP3Ks individually to assess whether the depletion of specific MAP3Ks resulted in the inhibition of TGFβ-induced p38 MAPK phosphorylation. As control, I treated cells with human IL-1β, which is known to promote p38 MAPK phosphorylation through activation of TAK1 [siRNAs were transfected into HaCaT cells. As anticipated, the IL-1β-induced phosphorylation of p38 MAPK was substantially depleted only upon TAK1 (MAP3K7) knockdown, but was unaffected by knockdown of other MAP3Ks . The siRNA pool targeting TAK1 resulted in a robust depletion in expression of endogenous TAK1 protein (b). In all cases, the treatment of cells with TGFβ resulted in the phosphorylation of SMAD2 (a). The TGFβ-induced p38 MAPK phosphorylation was not affected by depletion of the majority of MAP3Ks, including TAK1 . However, the siRNA depletion of MAP3K4 (MEKK4) and MAP3K10 (MLK2) resulted in a significant reduction in the levels of TGFβ-induced phosphorylation of p38 MAPK (a), an observation that is further evident when MAP3K4, TAK1 and MAP3K10 siRNA screens are compared together (b). No immunoblotting antibodies were available to detect endogenous levels of MAP3K4 and MAP3K10 proteins (b).The surprising observations that TAK1 was not activated by TGFβ and did not mediate the TGFβ-induced p38 MAPK phosphorylation in MEFs and HaCaT keratinocytes suggested a role for other MAP3Ks in mediating the TGFβ-induced phosphorylation and activation of p38 MAPK. In order to address this in an unbiased manner, I undertook a comprehensive  of TAK1 . For eacr MAP3Ks a,b. The  protein b. In allof SMAD2 a. The TGing TAK1 a,b. Howep38 MAPK a, an obstogether b. No immproteins b.Figure3.5.a). Interestingly, IL-1α-induced phosphorylation of JNK1/2 was upregulated in MAP3K4-KD MEFs compared with the WT cells (figure 5a). The TGFβ-induced phosphorylation of p38 MAPK in MAP3K4-KD MEFs was inhibited by about 50 per cent compared with the WT MEFs , whereas the phosphorylation of SMAD2 was unaffected (figure 5b). These observations are consistent with the siRNA knockdowns of MAP3K4  and indicate that while MAP3K4 has a role in mediating part of the TGFβ-induced phosphorylation of p38 MAPK, there is a role for further MAP3Ks in mediating the remainder of the TGFβ-induced p38 MAPK phosphorylation. Next, both WT and MAP3K4-KD MEFs were transfected with a control siRNA targeting FOXO4 [siRNAs targeting MAP3K10, which resulted in the depletion of the MAP3K10 mRNA by more than 70 per cent (figure 5c). The depletion of MAP3K10 expression with two independent siRNAs in WT MEFs resulted in the inhibition of the TGFβ-induced p38 MAPK phosphorylation by about 50 per cent compared with the control (figure 5b), indicating that MAP3K10 also plays a role in mediating the TGFβ-induced phosphorylation of p38 MAPK. Interestingly, the depletion of MAP3K10 in MAP3K4-KD MEFs resulted in a complete loss of the TGFβ-induced p38 MAPK phosphorylation (figure 5b), suggesting that MAP3K4 and MAP3K10 are sufficient for the TGFβ-dependent phosphorylation of p38 MAPK. The depletion of MAP3K10 in either cell line did not alter the levels of TGFβ-induced phospho-SMAD2 (figure 5b). Interestingly, both siRNAs that yielded the depletion of MAP3K10 mRNA in both WT and MAP3K4-KD cells resulted in a significant increase in the expression of MAP3K11 transcripts (figure 5c).MAP3K4 (MEKK4) has previously been implicated in mediating SMAD-dependent activation of p38 MAPK . This hafigure 5f MAP3K4 a,b and ing FOXO4  or two i3.6.a). This phosphorylation was inhibited by VX745, a selective and potent inhibitor of p38 MAPK (figure 6a) [figure 6a). By RT-PCR, I demonstrate that TGFβ induces the expression of AREG and IL-6 transcripts in MEFs (figure 6b). VX745 completely abolished the TGFβ-induced expression of AREG and IL-6 transcripts, suggesting that TGFβ-induced activation of p38 MAPK is necessary and sufficient for expression of these transcripts (figure 6b).I investigated whether TGFβ-induced activation of p38 MAPK impacted downstream signalling in MEFs. cAMP response element-binding protein (CREB) is phosphorylated at Ser133 upon activation of p38 MAPK and drives the expression of multiple target genes, including AREG and IL-6 –38. In Mfigure 6gure 6a) . VX745 h4.In this study, I have demonstrated that TAK1 (MAP3K7) does not mediate the TGFβ-induced phosphorylation of p38 MAPK. By using two sets of MEFs from independently generated WT and TAK1-deficient mice, as well as TAK1-deficient MEFs restored with WT and catalytically inactive TAK1, I have demonstrated that the TGFβ-induced phosphorylation of SMAD2 and p38 MAPK remain unaffected in these cells. Furthermore, while the treatment of cells with IL-1α resulted in a robust activation of TAK1 in cells expressing WT TAK1, TGFβ stimulation did not enhance TAK1 activity. These findings contradict many reports implying a role for TAK1 in mediating the TGFβ-induced phosphorylation of p38 MAPK ,11,17,25RNA screen targeting all the human MAP3Ks, I have demonstrated that depletion of MAP3K4 (MEKK4) and MAP3K10 (MLK2) results in a significant inhibition of the TGFβ-induced phosphorylation of p38 MAPK, whereas the depletion of other MAP3Ks, including TAK1, did not significantly affect the p38 MAPK phosphorylation in response to TGFβ. As a proof that the siRNA screen used was an acceptable approach, I show that IL-1β-induced phosphorylation of p38 MAPK, which requires TAK1, is inhibited upon depletion of TAK1 by siRNA pool. However, some off-target effects of the siRNAs in the screen cannot be ruled out. Furthermore, because I was unable to verify the expression of intended targets by immunoblotting or RT-PCR, it is possible that certain targets may not have been depleted by certain siRNAs. Despite the limitations of the siRNA screen, it was very interesting that depletion of MAP3K4 resulted in the inhibition of TGFβ-induced p38 MAPK phosphorylation. MAP3K4 has previously been reported to mediate SMAD-dependent activation of p38 MAPK, in part by associating with an activator GADD45β, which is transcribed in response to TGFβ [siRNAs from MAP3K4-KD MEFs, the TGFβ-induced p38 MAPK phosphorylation was completely inhibited. However, depletion of MAP3K10 from WT MEFs, which still have intact MAP3K4, resulted in partial inhibition of the TGFβ-induced p38 MAPK phosphorylation. Taken together, it is clear that MAP3K4 and MAP3K10 are the two MAP3Ks that sufficiently mediate the TGFβ-induced phosphorylation of p38 MAPK in MEFs and HaCaT cells.By using an unbiased si to TGFβ . By usinOne of the most interesting observations from this study is that MAP3K10 (MLK2) lies upstream of p38 MAPK phosphorylation in response to TGFβ. MLK2 is a member of the mixed-lineage subfamily of kinases that includes three other members, namely MLK1 (MAP3K9), MLK3 (MAP3K11) and MLK4 (KIAA1804). It is interesting, however, that depletion of MLK1, MLK3 or MLK4 by siRNAs did not result in the inhibition of the TGFβ-induced p38 MAPK phosphorylation, indicating that MLK2 is sufficient for TGFβ-induced phosphorylation of p38 MAPK. In fact, depletion of MLK2 by two independent siRNAs, despite increasing the levels of MLK3 mRNA, inhibited TGFβ-induced p38 MAPK phosphorylation. It has been reported that overexpressed MAP3K11 (MLK3) was activated by TGFβ and was able to mediate the TGFβ-induced phosphorylation of p38 MAPK . HoweverBecause p38 MAPK lies at the heart of multiple pro-inflammatory signalling inputs, it has been an attractive target for inhibition to treat inflammatory diseases such as rheumatoid arthritis, psoriasis and chronic obstructive pulmonary disease ,42. As a5.5.1.32P γ-ATP was from Perkin-Elmer. BMP-2, TGFβ1 and mouse IL-1α were from R&D Biosystems. Polybrene, Puromycin, DMSO and Tween-20 were from Sigma. Antibody recognizing SMAD1 was generated in sheep against a glutathione S-transferase-tagged SMAD1(144–268) fragment and affinity purified [−/−) and corresponding WT MEFs were a generous gift from S. Akira  [Antibodies recognizing total p38 MAPK, phospho-p38 MAPK (Thr180 and Tyr182), total SAPK/JNK, phospho-SMAD1 (Ser463/465), phospho-SMAD2 (Ser465/467), total SMAD2/3, phospho-CREB Ser133), total CREB and MAP3K3 (MEKK3) were purchased from Cell Signaling. Antibodies recognizing phospho-JNK1/2 (Thr183/Tyr185) and Lipofectamine 2000 reagent were purchased from Invitrogen. Antibodies recognizing TAK1, MAP3K8, MAP3K4, MAP3K10 (N- and C-terminus) and MAP3K11 were purchased from Santa Cruz Biotechnology. ed SMAD11–268 frag, Japan) . The MAP, total C5.2.www.dnaseq.co.uk) using Applied Biosystems Big-Dye v. 3.1 chemistry on an Applied Biosystems model 3730 automated capillary DNA sequencer. In order to knockdown the indicated panels of human MAP3Ks  or catalytically inactive mutant of TAK1 (TAK1(D175A); TAK1-KD) was cloned into a pBABE-puro retroviral vector (Cell Biolabs). pCMV-Gag-Pol and pCMV-VSVG constructs were purchased from Cell Biolabs. All DNA constructs used were verified by DNA sequencing, performed by DNA Sequencing and Services : mouse MAP3K4-F: CTAAGTCCTATGATAACGTCATGC; R: TGAAATCGAATCTCCTTCATGG; mouse MAP3K10-F: CTGGTGATGGAATATATGCTCG; R: CCAGGATTAGGATGTTGATGG; mouse MAP3K11-F: CCCTTCAACTCTGAATCTAATCC; R: CGAAGTGGATCTACTTGAAGC; mouse GAPDH-F: TATGATGACATCAAGAAGGTGG; R: CATTGTCATACCAGGAAATGAG; mouse IL-6-F: TTCCATCCAGTTGCCTTCTTG; R: AGGTCTGTTGGGAGTGCTATC; mouse AREG-F: CGACAAGAAAACGGGACTG; R: AACTGGGCATCTGGAACC; mouse 18S-F: GTAACCCGTTGAACCCCATT; R: CCATCCAATCGGTAGTAGCG.For real-time PCR, isolated RNA (1 µg) was used to prepare cDNA using I-script kit (BioRad). Reactions from three biological replicates were performed in triplicates of 20 µl each, including 0.5 per cent cDNA, 1 µM forward and reverse primers, and 50 per cent SYBR Green (Quanta). RT-PCR was performed using a standard protocol in a CFX 384 real-time system (BioRad). Data were normalized to a housekeeping gene (GAPDH or 18S). The data were analysed as reported previously ,45.5.3.−1 Polybrene reagent was added to aid infection. 24 h post-infection, cells were cultured in the presence of 2 µg ml−1 puromycin for selection of infected cells. Western blots with TAK1 or HA antibodies were used to confirm successful infection of appropriate targets. The retroviral means of generating stable cell lines ensures expression of target proteins at levels that are comparable with the endogenous levels of expression in similar cells that express the proteins naturally.Retroviral pBABE-puro constructs (1 µg each) encoding an HA tag or an N-terminally HA-tagged TAK1-WT or TAK1-KD were co-expressed with CMV-Gag/Pol (0.9 µg) and CMV-VSVG (0.1 µg) constructs in HEK-293T cells. Retroviruses were collected 48 h-post transfection from the culture media by filtering it through 0.45 µm filters onto sterile falcon tubes. TAK1-deficient MEFs, plated at approximately 40 per cent confluent, were infected by transferring the filtered retroviruses directly onto the cells, and 5 µg ml5.4.+/+, and MAP3K4-KD MEFs were cultured in dishes of 10 cm diameter in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10 per cent foetal bovine serum (FBS), 1 per cent penicillin/streptomycin mix and 2 mM l-glutamine (D10F). All cells were grown under a humidified atmosphere with 5 per cent CO2 at a constant temperature of 37°C. TAK1-deficient MEFs stably expressing a control vector or WT TAK1 (TAK1-WT MEFs) or KD TAK1 (TAK1-KD MEFs) were cultured as above except that the medium was supplemented with 2 µg ml−1 puromycin. Individual or pools of siRNAs  were transfected using Lipofectamine 2000 reagent as described previously [−1 final) for 45 min, and human IL-1β  or mouse IL-1α  for 10 min. Cells were then washed once with ice-cold PBS and lysed in 0.5 ml ice-cold complete lysis buffer  2-mercaptoethanol, 0.5 µM microcystin-LR, one tablet per 25 ml of complete protease inhibitor cocktail). The extracts were cleared by centrifuging at 16 000g at 4°C for 10 min and snap-frozen in liquid nitrogen for storage at −80°C or processed immediately. For RNA isolation, cells were processed using Nucleospin II RNA Isolation kit (Macherey-Nagel) according to the manufacturer's instructions.HaCaT cells, two independent sets of WT MEFs and TAK1-deficient MEFs, MAP3K4eviously ,46. Cell5.5.Cleared cell extracts (20 μg) were heated at 95°C for 5 min in 1× SDS sample buffer  glycerol, 2% (w/v) SDS, 0.02% (w/v) bromophenol blue and 1% (v/v) β-mercaptoethanol), resolved on a 10 per cent polyacrylamide gel by electrophoresis and transferred to nitrocellulose membranes. Membranes were blocked in TBS-T buffer  Tween-20) containing 10 per cent (w/v) non-fat milk for 1 h at room temperature. The membranes were then incubated with the indicated antibodies (diluted in TBS-T containing 10% (w/v) milk) for 16 h at 4°C, washed 2 × 10 min in TBS-T buffer, probed with the HRP-conjugated secondary antibodies (diluted 1 : 5000 in TBS-T/5% milk) for 1 h at room temperature, and washed 3 × 10 min in TBS-T buffer. Enhanced chemiluminescence reagent was used to detect the signals.5.6.TAK1 assays were performed as described previously . Briefly


Na+/H+Exchanger isoform 1 (NHE1) is a highly versatile, broadly distributed and precisely controlled transport protein that mediates volume and pH regulation in most cell types. NHE1 phosphorylation contributes to Na+/H+ exchange activity in response to phorbol esters, growth factors or protein phosphatase inhibitors, but has not been observed during activation by osmotic cell shrinkage (OCS). We examined the role of NHE1 phosphorylation during activation by OCS, using an ideal model system, the Amphiuma tridactylum red blood cell (atRBC). Na+/H+ exchange in atRBCs is mediated by an NHE1 homolog (atNHE1) that is 79% identical to human NHE1 at the amino acid level. NHE1 activity in atRBCs is exceptionally robust in that transport activity can increase more than 2 orders of magnitude from rest to full activation. Michaelis-Menten transport kinetics indicates that either OCS or treatment with the phosphatase inhibitor calyculin-A (CLA) increase Na+ transport capacity without affecting transport affinity (Km = 44 mM) in atRBCs. CLA and OCS act non-additively to activate atNHE1, indicating convergent, phosphorylation-dependent signaling in atNHE1 activation. In situ32P labeling and immunoprecipitation demonstrates that the net phosphorylation of atNHE1 is increased 4-fold during OCS coinciding with a more than 2-order increase in Na+ transport activity. This is the first reported evidence of increased NHE1 phosphorylation during OCS in any vertebrate cell type. Finally, liquid chromatography and mass spectrometry (LC-MS/MS) analysis of atNHE1 immunoprecipitated from atRBC membranes reveals 9 phosphorylated serine/threonine residues, suggesting that activation of atNHE1 involves multiple phosphorylation and/or dephosphorylation events.The  Because CLA is a phosphatase inhibitor, this implies that phosphorylation is involved in these processes. We further examine the net phosphorylation status of the NHE1 protein directly with 32P-orthophosphate labeling, and provide the first reported evidence that NHE1 is phosphorylated in situ in response to OCS. Candidate sites of phosphorylation or dephosphorylation are subsequently identified using NHE1 immunoprecipitated from atRBCs and mass spectrometry (LC-MS/MS). These studies confirm that phosphorylation is involved in activation of NHE1 during OCS, and demonstrate the complexity of NHE1 phosphorylation in situ in living cells.In the present study, we use the atRBC model to provide kinetic and biochemical evidence that activation of NHE1 during OCS involves phosphoryation-dependent signaling as well as direct phosphorylation of the NHE1 protein. Na+ transport activity in osmotically shrunken atRBCs is dependent upon a rate-limiting phosphorylation-dependent biochemical event +/H+ exchange activity. Because the rate-limiting event in shrinkage-activation of NHE1 is sensitive to the phosphatase inhibitor CLA, a major implication of the model is that this rate-limiting event involves protein phosphorylation. Furthermore, OCS and CLA treatment are presumed to affect identical downstream phosphorylation-dependent events in the activation of NHE1. Thus, it follows that the endpoint biochemical mechanisms controlling NHE1 activity are identical in response to OCS or CLA treatment. To test the notion that OCS and CLA treatment utilize the same biochemical mechanisms to increase NHE1 activity, we examined NHE1 activity, including Michaelis-Menten Na+ transport kinetics in osmotically shrunken atRBCs.We previously demonstrated that activation of NHE1-mediated Na+ transport activity by NHE1 in atRBCs suspended in hyperosmotic media. Na+ transport activity was determined following complete activation of NHE1 by pre-incubation in thermodynamically nulled (n) media (with respect to Na+/H+ exchange) of matched hyperosmolarity, thereby clamping RBCs at their initial shrunken volumes prior to flux determinations , to determine initial Na+ influx rates over a broad range of media osmolarities. These Na+ influx rate data conformed well to a sigmoidal stimulus-response relationship between media osmolarity and Na+ flux activity (H = 4) reflecting cooperativity in the cell volume-dependent signal transduction. The data demonstrate a more than 2-order of magnitude increase in inducible Na+/H+ exchange activity (180-fold)  relative to basal Na+ flux rates for NHE1 in unstimulated RBCs in isosmotic medium ).First, we assessed the shrinkage-dependent Naactivity , though + transport kinetics of NHE1 in atRBCs following induction of maximal NHE1 activity in hyperosmotic medium with or without CLA treatment. Based on the stimulus-response information in m and Jmax were then determined with or without CLA present    . In addictively) . Therefo+ transport kinetics) to that in response to CLA treatment alone in isosmotic medium . Consistent with the transport kinetics of NHE1 in the maximally activated state, the Km values for NHE1 were identical (Km≅44 mM) in all three stimulated conditions  was significantly greater than the sum of the individual mean Jmax values for osmotic cell shrinkage and CLA stimulation (13.8 mmoles Na+ kg−1 dcs min−1) (p<0.05) , such that NHE1 cannot be further activated once in the maximally activated state. If this were true, then the two treatments would be strictly additive under conditions of modest NHE1 activation c medium . As seennditions . In cont(p<0.05) ; Table 2in situ [32P]-orthophosphate labeling. RBCs were pre-equilibrated with [32P]-orthophosphate and then exposed to isosmotic, or hyperosmotic medium (1.6×IR) with or without CLA treatment  by suspension of atRBCs in hyperosmotic medium alone, and 5-fold  with inclusion of CLA. These values were not significantly different from each other (p>0.05), however they were significantly increased relative to baseline in isosmotic medium  (+ transport activity data in + transport activity and the corresponding net increase in NHE1 phosphorylation (4-fold) during OCS, suggesting that the molecular mechanism of NHE1 activation is more complex than that of a simple unimolecular phosphorylation event.To determine if NHE1 activation involves direct NHE1 phosphorylation, we assessed the net phosphorylation status of NHE1 by ; n = 6) . Notablyin situ, we qualitatively examined the post-translational modifications of NHE1 by liquid chromatography (LC) and tandem mass spectrometry (MS/MS). The immunoprecipitation products of three in situ treatments were examined: IR, 1.6×IR, and CLA treatment (as described for 2 spectra from tryptic peptides identified 9 phosphorylated serine/threonine sites: with greater than 90% probability (Amphiuma numbering): S607, S610, S711, and S783. Four additional sites were identified from phosphorylated peptides found only in the 1.6×IR, and CLA treatments, but not in the IR (unstimulated) condition: S613, T693, T727, and S794. The phosphorylation site S701 was also identified, though only in one sample due to lack of coverage of this residue in the MS/MS data. A table summarizing the qualitative identification of phosphorylated peptide fragments is included as The discrepancy between the amount of net NHE1 phosphorylation and the magnitude of inducible NHE1 activity strongly suggests that NHE1 activation involves synergistic effects of multiple phosphorylation sites, including the possibility of simultaneous phosphorylation and dephosphorylation of NHE1. To identify exact sites of NHE1 phosphorylation + transport rate (Jmax), with no effect on Na+ transport affinity (Km). Several laboratories, including ours, have noted that NHE1 activity can also be increased through increased Na+ transport affinity, e.g., in response to decreased intracellular pH + transport kinetics for NHE1 in the present study , and Na+ transport activity is manifest entirely as an increase in Jmax, and further demonstrate that these transport kinetic properties are the same in response to CLA treatment. Therefore the biochemical mode of NHE1 activation is the same whether induced by OCS or CLA treatment, yet fundamentally differs from that of intracellular acidification. Because CLA is a protein phosphatase inhibitor this further implies that activation of NHE1 by OCS is phosphorylation-dependent, however other possible mechanisms may exist to explain this behavior.Control of volume regulatory inorganic ion transport activity in response to cell volume disturbances depends upon fundamental cell physiological processes that are very poorly understood. The biochemical and molecular events involved in OCS-induced NHE1 activation are completely unknown. In the present study, we first described NHE1 transport activity using enzyme kinetics as a basis for understanding upstream cell signaling and the putative role of phosphorylation in OCS-induced NHE1 activation. We found that two treatments, OCS and CLA, increase NHE1 activity via the same biochemical mechanism: increased maximal Nant study , 2 suppoPreviously we proposed a model for control of NHE1 activity in which NHE1 is activated by OCS or CLA through effects on a single rate-limiting activation event consisting of an activating kinase and an opposing phosphatase in situ32P labeling, we observed that the net phosphorylation of NHE1 is increased 4-fold during OCS compared to unstimulated cells in isosmotic medium  specifically detects phosphorylated serine residues adjacent to positive or uncharged amino acid residues, therefore it is possible that many phospho-sites are not detected. This is very likely the case in that 50% of the phospho-serine sites identified in In an earlier study of NHE1 phosphorylation in cultured mammalian cells c medium . This isc medium . This diin situ in atRBCs. These loci correspond to sites where increased phosphorylation is associated with increased activity in mammalian cells: phosphorylation at S703 by the p90 ribosomal S6 kinase (p90RSK) is necessary for NHE1 activity in response to growth factor treatment Because in most studies increased NHE1 phosphorylation is observed exclusively on serine residues distal to amino acid 698 of the cytosolic C-terminus , we suspPotentially other phosphorylation sites contribute to control of NHE1 activity in atRBCs. Our LC-MS/MS data identifies phosphorylation of three serine residues not previously reported, S599 (S607), S602 (S610), and S605 (S613) within the proximal C-terminus of NHE1 . It is nBecause the increase in NHE1 activity during OCS is disproportionately greater than the measured increase in net NHE1 phosphorylation, it is equally likely that other sites exist where simultaneous decreases in phosphorylation occur during OCS. In mammalian cells, few examples exist in which increased NHE1 activity coincides with dephosphorylation of NHE1. Studies of truncated NHE1 mutants expressed in mammalian fibroblasts have shown that phosphorylation of NHE1 is decreased in the region of residues 635–698 in response to serum treatment + uptake was significantly higher in the T685A mutant cell line compared to T685D in response to hypertonicity  suggesting that the presence of a negative charge at T685 decreases the response of NHE1 to hypertonicity (unpublished data by RR Rigor). Further studies of this kind are necessary to more precisely determine the role of phosphorylation/dephosphorylation within the CaM binding domains in control of NHE1 activity during OCS.Dynamic interactions of S648 with calmodulin (CaM) may explain the role of dephosphorylation in activation of NHE1. In mammalian cells calmodulin (CaM) binding is necessary for OCS-induced NHE1 activity The evidence presented here support a role for phosphorylation in the cell signaling mechanisms upstream of NHE1 activation, and that NHE1 is directly phosphorylated during OCS. NHE1 activation by OCS involves phosphorylation of the distal C-terminus of NHE1, coinciding with predicted dephosphorylation of the CaM binding domains at residues 635–698. However the specific contribution of each phosphorylated or dephosphorylated locus must be further tested by systematic site-directed mutagenesis and biochemical analysis of the C-terminal serine residues of NHE1. The complex requirements for activation by OCS can readily explain why changes in net phosphorylation of NHE1 were not previously seen in studies with mammalian cells. In contrast, NHE1 phosphorylation is clearly seen during OCS in atRBCs due to the robust volume regulatory responses of this model system. This information is important for the fundamental understanding of cell volume regulation in confirming that phosphorylation-dependent signaling and direct phosphorylation of NHE1 are integral to OCS-induced NHE1 activation.This work was approved by the University of California Davis Animal Welfare Assurance on file with the US Public Health Service, under the IACUC approved animal care and use protocol no. 07-12754.22Na+ was obtained from New England Nuclear  as NaCl; 32P-orthophosphate (500 µCi/µl) was from MP Biomedicals ; reagent grade chemicals, dimethyl pimelimidate (DMP), ouabain and 5,5′ N-ethylisopropyl-amiloride (EIPA) were from Sigma-Aldrich ; Mini Complete protease inhibitor tablets were from Roche Diagnostics ; kinase inhibitors and phosphatase inhibitors were from Calbiochem ; protein G sepharose fast-flow beads were from Amersham ; Anti-phosphoserine mouse monoclonal antibody (4A3) was from Biomol ; Anti-NHE1 mouse monoclonal antibody (MAb3140) was from Chemicon ; X-ray film was from Eastman Kodak; Narrow 500 µl PE microcentrifuge tubes were from E&K Scientific ; Heparin (1000 U/ml) was from Henry Schein .2 1.0, CaCl2 0.5, HEPES 30, NaOH 18, glucose 5, pH 7.65±0.02 were adjusted for desired osmolarity with NaCl, or NMDGCl to either reduce or fix solution [Na+]. The osmolarity of Isosmotic Ringer's (IR) solution, is 240±3 mOsm. The osmolarities of hyperosmotic solutions were adjusted relative to normal physiological osmolarity (240 mOsm) and are listed as a multiple of Isosmotic Ringer, i.e. 1.2, 1.4, 1.6… × IR. Thermodynamically nulled (n) flux media were formulated by adjusting media K+ and Na+ concentrations such that the net thermodynamic driving force for volume regulatory ion transporters (K+/H+ exchange or Na+/H+ exchange) is set equal to zero, as described previously + transport kinetics were formulated by varying media Na+ as described previously +/K+-ATPase activity.HEPES buffered Ringer's solutions: (mM) KCl 3, MgClAmphiuma tridactylum were purchased from Atchafalaya Biological Supply  and maintained in filtered freshwater tanks. Blood was drawn by cardiac puncture, into heparinized (1000 U) 20 ml syringes. Serum osmolarity for animals used in this study ranged 240±20 mOsm, as measured with an Advanced Instruments  model 3D3 freezing point depression osmometer. RBCs were washed three times by low-speed centrifugation , supernatant was removed by vacuum aspiration, and the RBC pellet was resuspended in IR solution for 60 minutes at room temperature (22°C) to permit cells to reach steady-state, then stored overnight (4°C) for use the next day. Prior to experimentation, cell suspensions were adjusted to room temperature for 30 minutes in fresh IR solution. All RBC experiments were performed at 10% hematocrit (hct).Wild captured adult + transport activity was assayed as the unidirectional influx of 22Na+22Na+ (2 µCi/ml), and sampled over a brief interval (2–5 minutes) to measure initial flux rate and minimize backflux. Aliquots of RBC suspension were added to isotope-free ‘cold’ flux medium layered over dibutyl phthalate, and separated by centrifugation . RBC pellets were isolated by inverting the 1.5 ml tubes and cutting off the conical tips. Radioactivity in the cell pellets were quantified with a Packard gamma counter, and normalized to the amount of dried cell solids. Prior to flux measurements, RBCs were pre-incubated in nulled (n) hyperosmotic media to allow for complete activation of Na+/H+ exchange, as described previously + flux was operationally defined as EIPA-sensitive Na+ influx.NaAmphiuma RBCs were incubated to steady-state on a tube rotator in IR solution containing 500 µCi/ml [32P]-orthophosphate . Labeled RBCs were equilibrated to room temp (30 min), then sub-divided into equal volumes (0.25 ml/sample) and transferred to nIR or n1.6×IR solutions in the continued presence of [32P]-orthophosphate for 1 hour . Following the incubation period, RBCs were centrifuged  and RBC pellets were flash frozen in liquid N2 for 10 minutes.RBCs were treated in a similar fashion to that described by Lytle 32P labeled bands were incubated with a phosphor-imaging screen for 5 days for autoradiography using a STORM Imager (Molecular Devices). PVDF membranes were subsequently rehydrated for Western blotting and chemiluminescence. Integrated band intensities were quantified using NIH Image J software. Background corrected 32P band intensities were normalized to total phosphorylation. Corresponding NHE1 bands detected by Western blotting were normalized to total NHE1 and used to express relative NHE1 phosphorylation (32P/unit NHE1). The calculated IP efficiency was 52% (n = 5). A similar IP protocol with IP materials scaled up 10-fold was used to prepare samples for mass spectrometry, starting with 0.5 ml of cell pellet material. 5% of the harvested material was used to confirm successful IP of NHE1 by Western blot. The remaining 95% was separated on large format SDS-PAGE gels (7.5%), stained with Colloidal Coomassie Blue stain (Novex) to confirm purity, and the NHE1 band was excised for protein extraction and trypsin digest prior to mass spectrometry, carried out as described previously Frozen RBC pellets were resuspended in (4°C) lysis buffer (PBS (pH 7.4) plus (mM) sodium fluoride 30, tetrasodium pyrophosphate 20, EDTA 5, EGTA 2, orthovanadate 1, ß-glycerophosphate 40, dithiothreitol 1, and Mini Complete protease inhibitor (Roche) (1 tab/10 ml). Lysates were centrifuged , and the resulting pellets were washed twice more in 20 volumes of lysis buffer (4°C). Washed pellets were suspended in immunoprecipitation (IP) buffer (lysis buffer with 0.5% triton ×100) (4°C), incubated for 20 minutes on ice, and centrifuged . Supernatants were used for IP. IP beads were prepared by covalently crosslinking anti-NHE1 antibody to protein G sepharose beads by treatment with dimethyl pimelimidate (DMP), essentially as described by Schneider et al NanoLC-MS/MS experiments were performed on a Finnigan LTQ-FT hybrid linear ion trap/7T Fourier transform ion cyclotron resonance mass spectrometer , equipped with a Finnigan Nanospray ion source (Thermo Electron), a Finnigan Surveyor MS pump (Thermo Electron), and a Finnigan micro-autosampler (Thermo Electron). The tryptic peptide mixture was separated on a 50 µm ID PicoFrit column packed in-house with Magic C18AQ material . The column was packed to a length of 12 cm with a 100% MeOH slurry of C18 reversed-phase material  using a high-pressure cell pressurized with helium. The column was equilibrated before sample injection for 10 min at 2% solvent B (0.1% (v/v) formic acid in acetonitrile) and 98% solvent A (0.1% (v/v) formic acid in water) at a flow rate of 140 nl/min. Separation was achieved by using a linear gradient from 2 to 50% solvent B in 24 min at a flow rate of 320 nl/min. The LTQ-FT mass spectrometer was operated in the data dependent acquisition mode using the TOP10 method: a full-scan MS acquired in the FTICR mass spectrometer was followed by 10 MS/MS experiments performed with the LTQ on the ten most abundant ions detected in the full-scan MS.Tandem mass spectra were extracted and charge state deconvoluted by bioworks version 3.3. Deisotoping was not performed. All MS/MS samples were analyzed using X! Tandem ). X! Tandem was set up to search the uniprot Amphibian database including an equal number of reverse sequences  and 101 contaminant protein sequences from the common Repository of Adventitious Proteins, cRAP database (thegpm.org/crap) assuming the digestion enzyme trypsin. X! Tandem was searched with a fragment ion mass tolerance of 0.40 Da and a parent ion tolerance of 20 PPM. Iodoacetamide derivative of cysteine was specified in X! Tandem as a fixed modification. Deamidation of asparagine and glutamine, oxidation of methionine and tryptophan, sulphone of methionine, tryptophan oxidation to formylkynurenin of tryptophan, acetylation of the n-terminus and phosphorylation of serine, threonine and tyrosine were specified in X! Tandem as variable modifications. The LC-MS/MS data associated with this manuscript may be downloaded from ProteomeCommons.org Tranche network using the following hash: tKUCAKV1XQpg3fiEuLGer5jUKXooAjuhpnDBqQTtpfuDIFwKKYPj1lhhL6hQuYuyFApkn9g/Mn3b9c6IMJ4NvfP32wcAAAAAAAAHIQ =  = .Scaffold  was used to validate MS/MS based peptide and protein identifications. Peptide identifications were accepted if they could be established at greater than 80.0% probability as specified by the Peptide Prophet algorithm m and Jmax ± SEM. Tests for significance (p<0.05) were performed using Student's t-test with a two-tailed distribution.General data analysis was performed with Prism 4.0 (Graph Pad) software. Stimulus-response data were fit to a sigmoidal function by non-linear regression. For transport kinetics, data were pooled from several identical experiments and fit to a single-binding site hyperbola by non-linear regression to generate values for KTable S1A summary of LC-MS/MS data generated from analysis of atNHE1. This complete list of NHE1 phosphorylated peptides identified by LC-MS/MS includes other post-translational modifications, as well as probability of identification, X!Tandem values, mass:charge (m/z), mass, charge and mass confidence (delta PPM) information.(TIF)Click here for additional data file.