PIK3CA, which encodes the p110α subunit of PI3K, is frequently mutated and oncogenic in breast cancer. PI3Kα inhibitors are in clinical development and despite promising early clinical activity, intrinsic resistance is frequent among patients. We have previously reported that residual downstream mTORC1 activity upon treatment with PI3Kα inhibitors drives resistance to these agents. However, the mechanism underlying this phenotype is not fully understood. Here we show that in cancer cells resistant to PI3Kα inhibition, PDK1 blockade restores sensitivity to these therapies. SGK1, which is activated by PDK1, contributes to the maintenance of residual mTORC1 activity through direct phosphorylation and inhibition of TSC2. Targeting either PDK1 or SGK1 prevents mTORC1 activation, restoring the antitumoral effects of PI3Kα inhibition in resistant cells.  •The PDK1-SGK1 axis can sustain mTORC1 activity upon PI3K/AKT suppression•SGK1 directly phosphorylates TSC2, resulting in mTORC1 activation•PIK3CA-mutant cells to PI3Kα inhibitionTargeting PDK1 sensitizes  Castel et al. show that PDK1 activates SGK1 to phosphorylate and inhibit TSC2, contributing to maintenance of mTORC1 activity and resistance of PIK3CA-mutant cancer cells to PI3Kα inhibition. Targeting either PDK1 or SGK1 restores the sensitivity of these resistant cancer cells to PI3Kα inhibition. PIK3CA, the gene that encodes for the α isoform of the p110 catalytic subunit of PI3K. However, despite these encouraging results some tumors are resistant to these agents. In this work we show that, upon PI3Kα inhibition, the PDK1-SGK1 axis can overcome AKT inhibition by activating mTORC1 via direct phosphorylation of TSC2. Therefore, both AKT and PDK1 must be suppressed to achieve full mTORC1 inhibition and antitumor activity in these tumors resistant to PI3Kα inhibition. This study uncovers a mechanism of cell survival under pharmacological pressure that can be exploited to improve the therapeutic options of patients with breast cancer.Promising clinical activity has been reported in breast tumors bearing activating mutations in 3) at the plasma membrane, promoting the recruitment of the pleckstrin homology (PH) domain-containing proteins PDK1 and AKT (The phosphoinositide 3-kinase (PI3K) pathway integrates many extracellular stimuli and triggers the phosphorylation of key downstream effectors such as AKT and the mammalian Target of Rapamycin Complex 1 and 2 (mTORC1 and 2). This signaling cascade is essential for regulating cell size, proliferation, survival, and metabolism . Activat and AKT , where t and AKT  and mTOR and AKT . Once ac and AKT . Moreove and AKT .PIK3CA, which encodes the α isoform of the p110 catalytic subunit of PI3K, results in hyperactivation of the PI3K/AKT/mTOR pathway  screen using a library targeting 710 kinases and 298 phosphatases encoded in the human genome. We measured cell viability and S6 ribosomal protein (S6) phosphorylation, a bona fide readout of mTORC1 activity, in the presence of BY719, a PI3Kα-specific inhibitor.PIK3CA mutant and insensitive to BYL719. After treatment over 6 days, we found that knockdown of 37 enzymes in HCC1954 and 35 enzymes in JIMT1 sensitized cells to PI3Kα inhibition  eIF4G and eIF4A, components of the eIF4F cap-initiation complex. As expected, eIF4E remained unchanged. In long-term treatments, the combination of BYL719 and PDK1 knockdown induced poly(ADP-ribose)polymerase (PARP) cleavage  kinase family that includes AKT, PKC, RSK, SGK, and S6K . To confcleavage C and inccleavage D, surrogPharmacological inhibition of PI3Kα resulted in a modest delay in tumor growth in shGFP control xenografts but was sufficient to induce durable tumor shrinkage in tumors with ablated PDK1 E. AnalysNext, we tested the activity of BYL719 in combination with GSK2334470, a highly selective PDK1 inhibitor . We dete7GTP pulldowns when both drugs were combined, consistent with mTORC1 inhibition (PDK1 inhibition did not decrease the phosphorylation of AKT at the activation loop (T308) as a result of a compensatory mechanism involving PIP3 and mTORC2, an observation in line with previous reports . Analysihibition K. Consishibition I and cashibition J.We then expanded our results in vivo. Although some antitumor activity was observed with treatment with BYL719 or GSK2334470, only the combination of both compounds induced durable tumor shrinkage K and inhTaken together, these results indicate that PDK1 inhibition sensitizes cells to PI3Kα blockade via suppression of mTORC1.3-dependent manner (PDPK1-null (PDPK1−/−) isogenic model  and the activation loop. Several kinases prime AGC kinases for activation through phosphorylation at the HM. PDK1, which acts as a master regulator of this family of kinases, scaffolds at the phosphorylated HM using the PIF (PDK1-interacting fragment) binding pocket. This interaction enables phosphorylation of the activation loop, thereby fully activating their activity. However, AKT does not require the PIF-binding pocket of PDK1 but instead needs its PH domain to interact with PDK1 at the plasma membrane in a PIPt manner . To explic model . HCT116 d mTORC1 P.PDPK1−/− cells with the wild-type (WT), kinase-inactive K111N (KD), PIP3-binding deficient K546E (KE), and PIF-pocket-deficient L155E (LE) mutants  or negatively (CCND1) regulated by FOXO3  is a family of AGC serine/threonine kinases that comprises three members (SGK1–3) highly homologous to AKT . SGK1 acSGK1 mRNA compared with sensitive cells  in 273 breast invasive carcinomas, comprising 138 triple-negative breast cancer (TNBC), 68 estrogen-/progesterone-receptor-positive, and 67 human epidermal growth factor 2 (HER2)-positive breast cancer patients. High pNDRG1 staining was found in TNBC (21%) and HER2-positive tumors (12%) D, a finds cohort .PIK3CA-mutant breast cancer samples from 18 patients treated with BYL719 in combination with an aromatase inhibitor (NCT01870505). Three of these tumors expressed high levels of SGK1 mRNA while the remaining 15 had medium to low levels of SGK1 mRNA. The three patients with tumors exhibiting high SGK1 expression, which also stained positive for pNDRG1, did not respond to therapy , while resistant cell lines displayed low levels of SGK1 promoter methylation  (SGK1 mRNA levels in these cells (SGK1 transcription is active in these resistant cell lines (SGK1 promoter (SGK1 promoter DNA methylation (data not shown) and increased mRNA levels of SGK1 in the four sensitive cell lines tested  F. The dese cells G. By chrll lines H. On thepromoter H. Treatms tested I. Our reAlthough pNDRG1 and SGK1 expression correlates in vivo , AKT canNext, we immunoprecipitated endogenous SGK1 and found that BYL719 treatment was not sufficient to completely abolish the kinase activity of the enzyme, in contrast to GSK2334470 I. On theConsistent with previous results, GSK2334470 alone is not capable of inhibiting AKT activity J and 3I.These results demonstrate that both PI3K and PDK1 activities have to be suppressed to inhibit downstream AKT and SGK1 phosphorylation and activity in our resistant models.We next assessed the contribution of SGK1 in mediating resistance to PI3Kα inhibition. The overexpression of a constitutively active form of SGK1 in MDA-MB-361 cells, which are sensitive to PI3Kα inhibition, was sufficient to increase cell viability in the presence of BYL719 A. In par50 of 4.8 nM at 10 μM ATP using a recombinant SGK1 kinase assay, with appreciable activity also toward SGK2 and SGK3   . SGK1-inctively) C. The spctively) A. Despitfor SGK1 B. At thef ∼20 μM C. Next, f ∼20 μM D. This sOur computational analyses and preliminary characterization of SGK1-inh suggested that this compound acts as a type II kinase ATP-competitive inhibitor binding preferentially to the inactive conformation of the kinase D. By per−7 cm s−1 in Caco2 cell permeability assays)  . Treatme assays) G and S5KTP beads L. This tTP beads I and phoTP beads J and S5OThese results show that targeting SGK1 pharmacologically is feasible, and demonstrate that dual inhibition of AKT and SGK1 is required to achieve full suppression of mTORC1 and proliferation.Due to its similarity with AKT, we reasoned that SGK1 could modulate mTORC1 activity by interacting with a component of the TSC/RHEB/mTORC1 axis. Immunoprecipitation of TSC1, TSC2, RHEB, and mTOR in 293T cells revealed that SGK1 physically interacts with both mTOR and TSC2 proteins A and S6ACo-immunoprecipitation assays using five different fragments of TSC2 demonstrated that SGK1 binds to the N-terminal region of TSC2 D, which S/T), where R is arginine, X is any amino acid, and (S/T) is a phosphorylatable serine or threonine (S/T) sites of TSC2, even when cells were pre-treated with AKT inhibitor , the subcellular localization of mTORC2 is ambiguous  and AKT1 (67%). Thus, it is tempting to speculate that due to the high overlap of their substrates, Drosophila dAkt plays the role of both AKT and SGK1. In fact, Ypk2 and Gad8, the SGK1 orthologs in budding and fission yeast, respectively, are the main TORC2 downstream effectors , pAKT (T308), pS6K (T389), pS6 (S240/4), pS6 (235/6), p4EBP1 (S65), PARP, Actin, pRSK (S227), cleaved caspase 3, pFOXO1/3 (T24/T32), SGK1, SGK2, SGK3, pNDRG1 (T346), NDRG1, FLAG, HA, and phospho-RXRXX(S/T) were from Cell Signaling Technology.6 cells in 1:1 PBS/Matrigel (Corning) were injected subcutaneously into athymic Foxn1nu nude mice. When a volume of ∼150 mm3 was reached mice were randomized and treated, and tumors were measured twice per week for 1 month. Full details can be found in Animals were housed, maintained, and treated at Memorial Sloan Kettering Cancer Center (MSKCC) in accordance with Institutional Animal Care and Use Committee (protocol number 12-10-019). 5 × 10NCT01870505 conducted at MSKCC were used for immunohistochemistry (IHC). Informed consent was obtained from all subjects. Full details of tissue microarray construction are provided in The MSKCC Institutional Review Board approved the study. Pre-treatment formalin-fixed paraffin-embedded blocks from patients treated with the PI3Kα inhibitor BYL719 enrolled in the clinical trial P.C., D.R.A., J.B., and M.S. designed the research. P.C. and H.E. performed the in vitro and in vivo experiments. R.B. performed endogenous kinase assays. E.T. performed ChIP experiments. S.K. and C.S.V. performed the docking and MS. F.J.C. performed methylation analysis. E.B. scored and quantified IHC experiments. P.R., S. C., and M.D. provided patient samples. P.C. prepared the figures. P.C., M.S., and J.B. wrote the manuscript.


Our ability to model the dynamics of signal transduction networks will depend on accurate methods to quantify levels of protein phosphorylation on a global scale. Here we describe a motif-targeting quantitation method for phosphorylation stoichiometry typing. Proteome-wide phosphorylation stoichiometry can be obtained by a simple phosphoproteomic workflow integrating dephosphorylation and isotope tagging with enzymatic kinase reaction. Proof-of-concept experiments using CK2-, MAPK- and EGFR-targeting assays in lung cancer cells demonstrate the advantage of kinase-targeted complexity reduction, resulting in deeper phosphoproteome quantification. We measure the phosphorylation stoichiometry of >1,000 phosphorylation sites including 366 low-abundance tyrosine phosphorylation sites, with high reproducibility and using small sample sizes. Comparing drug-resistant and sensitive lung cancer cells, we reveal that post-translational phosphorylation changes are significantly more dramatic than those at the protein and messenger RNA levels, and suggest potential drug targets within the kinase–substrate network associated with acquired drug resistance. Measuring phosphorylation stoichiometry on a proteomic scale remains a challenge. Tsai et al. develop a technique to measure the basal level of phosphorylation stoichiometry in a single human phosphoproteome and identify molecular changes associated with gefitinib resistance in lung cancer cells. Deregulated signalling through protein phosphorylation is closely linked to pathogenesis of human cancer2323et al.6Pioneering work on large-scale analyses of protein phosphorylation stoichiometry was reported by Olsen et al.Wu To overcome the current bottleneck in accessing the stoichiometry of single-state human phosphoproteomes, we have developed a motif-targeting quantitative proteomic approach. By using kinase reactions and immobilized metal ion affinity chromatography (IMAC), this approach can enrich these initially unphosphorylated peptides, that is, the counterpart of the phosphorylated form, which effectively reduces complexity of kinase–substrate peptides prior to stoichiometry measurement by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. To our knowledge, this method is the first large-scale approach to provide system-wide phosphorylation stoichiometry of a single-state human proteome. In addition to the demonstrated sensitivity, reliability and accuracy, this assay offers the advantage of kinase-targeted complexity reduction for deeper phosphoproteome analysis; hundreds of tyrosine phosphopeptides could be detected from only 50 μg cell lysates. The practicality of this approach was demonstrated on the quantitative measurement of drug-resistant and sensitive lung cancer cell lines; this motif-targeting approach differentiates drug resistance-associated changes in phosphorylation stoichiometry from those at the protein as well as messenger RNA (mRNA) levels in lung cancer cells, which also suggested potential druggable target proteins in the EGFR- and CK2-centred kinase–substrate network.In this study, we developed a motif-targeting quantitative proteomic approach for the large-scale measurement of absolute site stoichiometry in the human phosphoproteome. This workflow integrates dephosphorylation and isotope tagging with an enzymatic kinase reaction. As shown in In the last step, the dephosphorylated peptides and unphosphorylated counterparts in the flow through of IMAC are subjected to phosphorylation via a kinase reaction . In most7R2=0.968 (s.d.=6.1%) for CK2 reaction and R2=0.960 (s.d.=6.4%) for MAPK reaction, indicating the good reproducibility in these steps for phosphorylation stoichiometry measurement.The validity of the key steps, including dephosphorylation efficiency, motif-targeting kinase specificity and reproducibility for phosphorylation stoichiometry measurement in the workflow, were evaluated by a model study of Raji B cells . The effTo date, an effective strategy to overcome drug resistance still remains a challenge in the treatment of cancer. In the case of non-small-cell lung cancer (NSCLC), gefitinib, a tyrosine kinase inhibitor (TKI) that targets the epidermal growth factor receptor (EGFR), has been used clinically to treat patients with the EGFR mutation. However, nearly all patients eventually develop resistance to these TKI drugs50 curves of gefitinib to these two lung cancer cell lines were shown in previous studyHere we apply our motif-targeting approach to measure the absolute stoichiometry for both gefitinib-sensitive cells (PC9) and their gefitinib-resistant counterpart (PC9/gef). PC9 is a gefitinib-sensitive cell line, while PC9/gef is a gefitinib-resistant cell line. Both cell lines harboured an exon 19 deletion mutation on EGFR. The ICWe further applied two filters, matching to known motifs14151617et al.et al.To compare the phosphorylation-dependent signalling between PC9 and PC9/gef cells, we analyzed the phosphorylation stoichiometry of these two cells individually. To identify further proteins that might contribute to the different extent of resistance, we constructed a protein–protein interaction network of these identified phosphoproteins with motifs of CK2 and a known oncogenic kinase EGFR. Among their first neighbour protein interaction network , the higBased on the measured absolute stoichiometry, phosphorylation sites of CDK1, HMGA1 and AP2A1 show the highest expression of phosphorylation stoichiometry among these resistance-related elevated phosphorylation sites in the network . Besides22To our knowledge, this is the first large-scale approach to assess the phosphorylation stoichiometry of a single-state human proteome. This approach was able to provide reproducible quantitation result (s.d.=±6%). The proof-of-concept experiments on CK2-, MAPK- and EGFR-targeted assays show the advantages of kinase specificity–based complexity reduction of phosphopeptides, which further demonstrates efficient enrichment of low-abundance phosphorylation sites. Such kinase-targeted assays also show high sensitivity for determining the stoichiometry of hundreds of tyrosine phosphorylation sites in 50 μg of cell lysate. In a single cellular state, our results revealed that distinct phosphorylation stoichiometry distributions of different substrates and motifs can be distinguished. Through quantitative measurement of the drug-resistant and sensitive lung cancer cells, this motif-targeting approach suggested potential drug-targeting proteins in the EGFR- and CK2-centred kinase–substrate network. Based on the three most dramatically elevated phosphorylation sites  in response to drug resistance, our stoichiometry measurement also revealed that post-translational phosphorylation changes are much more dramatic than changes either at the protein or the mRNA levels. This approach can provide system-wide maps of protein phosphorylation stoichiometry for either single or multiple cellular states under physiological or pathological regulation.3), acetic acid, formic acid, HPLC-grade acetonitrile (ACN), sodium deoxycholate (SDC), sodium lauroyl sarcosinate (SLS), heavy and light (13CD2O or 12CH2O) formaldehyde were purchased from Sigma Aldrich . The BCA protein assay kit was obtained from Pierce . Trifluoroacetic acid (TFA) and lysyl endopeptidase were purchased from WAKO . Modified sequencing-grade trypsin was purchased from Promega . Ni-NTA silica resin was purchased from Qiagen . SDB-XC Empore disks were obtained from 3M . Water was obtained from a Millipore Milli-Q system .Protease inhibitor was obtained from Merck . Triethylammonium bicarbonate (TEABC), iron (III) chloride  for 30 min. After treatment, cells were harvested and washed three times with phosphate-buffered saline and then lysed in lysis buffer . The protein concentrations were determined via BCA protein assays.The Raji human B cell line was cultured in RPMI-1640 medium  supplemented with 10% foetal bovine serum and 1% penicillin G  at 37 °C in 5% CO50 curve of gefitinib to these two lung cancer cell lines were shown in previous study2 and 95% air. Cells were washed three times with phosphate-buffered saline   and harvested in lysis buffer . The protein concentrations were determined via BCA protein assays.The human lung adenocarcinoma cell line PC9 and derivative PC9/gef clones were gifts from Dr C.H. Yang . PC9 is a gefitinib-sensitive cell line, while PC9/gef is a gefitinib-resistant cell line. Both cell lines harboured an exon 19 deletion mutation on EGFR. The ICg at 25 °C to remove the lysis buffer. Subsequently, the original lysis buffer was replaced by adding 400 μl of 40 mM Tris-HCl (pH=7.5) followed by centrifugation. This step was repeated five times. The resulting concentrate was diluted with 100 μl of 40 mM Tris-HCl (pH=7.5) and separated into two parts. These two parts were treated with or without thermosensitive alkaline phosphatase (TSAP)  at 37 °C for 1 h  at room temperature for 30 min. The proteins were loaded into 10 kDa molecular weight filter (Amicon Ultra device from Millipore). The device was centrifuged at 14,000 1 h ref.  for deph13CD2O or 12CH2O, and then 4 μl of freshly prepared 0.6 M sodium cyanoborohydride was immediately added. The mixture was agitated for 60 min at room temperature. The reaction was stopped by adding 16 μl of 1% ammonium hydroxide on ice and agitating the mixture for 1 min. Then dimethyl labelling peptides were mixed with 20 μl of 10% formic acid. The differentially peptides were mixed into one sample and desalted by using reversed phase-Stage TipsStable isotope labelling was performed as previously described2+ ions were removed with 50 mM EDTA in 1 M NaCl. The tip was then activated with 100 mM FeCl3 and equilibrated with loading buffer (6% (v/v) acetic acid at pH 3.0) prior to sample loading. Tryptic peptides were reconstituted in loading buffer and loaded onto the IMAC tip. After successive washes with 6% (v/v) acetic acid, 25% ACN and 6% (v/v) acetic acid (AA), the bound peptides were eluted with 200 mM NH4H2PO4. The eluted peptides were desalted using reversed phase-Stage TipsThe details can be found from previous reports302 (pH=7.5) for CK2; 50 mM Tris-HCl, 10 mM MgCl2, 0.1 mM EDTA, 2 mM DTT and 0.01% Brij 35 (pH=7.5) for MAPK; 40 mM Tris-HCl, 20 mM MgCl2 and 0.1 mg ml−1 BSA contacting 50 mM DTT, 2 mM MnCl2 (pH=7.5) for EGFR). All recombinant kinases of CK2 and MAPK were obtained from New England BioLabs  except for EGFR (Promega). Each kinase  was added to the desalted peptide mixture containing 1 mM ATP at 30 °C overnight, kinase reactions were stopped by adding TFA to a final concentration of 0.5%. The acidified peptides were desalted by using reversed phase-Stage TipsThe tryptic peptides in the flow through of IMAC were first desalted by using reversed phase-Stage Tips. The desalted peptides were dissolved in kinase reaction buffer , the MS survey scan range was m/z 300–1,500, and data were acquired for 250 ms. The top 10 precursor ions were selected based on threshold of 100 counts per second in each MS survey scan, and 10 MS/MS scans were performed for 200 ms in each acquisition. The collision energy was automatically adjusted by the rolling CID function of Analyst TF 1.5. To minimize repeated scans, dynamic exclusion was set for 6 s, and the precursor was then removed from the exclusion list.The TripleTOF 5600 system  was equipped with a nanoACQUITY UPLC . The 3 μm ReproSil-Pur C18-AQ particles  were packed into a 15 cm self-pulled column with a 100 μm inner diameter and 7 μm opening to prepare an analytical column using ‘stone-arch’ frit. The LC system consisted of water with 0.1% FA (buffer A) and ACN with 0.1% FA (buffer B). Peptides were separated through a gradient of up to 80% buffer B over 120 min at flow rate of 500 nl minP value <0.05 were accepted. The identified phosphopeptides after kinase reaction were classified into three classes. Class 1 means all of identified phosphorylation sites by kinase reaction. Class 2 means the sequence of these phosphopeptides should be corresponded to these kinase motifs in Human Protein Reference Database (HPRD). Class 3 means these phosphorylation sites in Class 2 have been reported in multiple public resource databases14151617http://proteomecentral.proteomexchange.org) via the PRIDEFor phosphopeptides identification, the raw MS/MS data were processed using the AB_SCIEX MS Data Converter and analyzed using Mascot  against the SwissPort database  with the following constraints: allowing for tryptic peptides with up to two missed cleavage sites, a fragment ion mass tolerance of 0.1 Da and a parent ion tolerance of 20 p.p.m. For unlabelled phosphopeptides, phosphorylation  and oxidation (M) were selected as variable modifications. For phosphopeptides labelled with dimethyl labelling, dimethyl isotope labels on the peptide N-termini and lysine residues, phosphorylation  and oxidation (M) were selected as variable modifications. The identification false discovery rate was evaluated by search against a randomized decoy database created by Mascot at the PSM level. In addition, only peptide-spectrum matches (PSMs) with m/z range and to eliminate isolated peaks that are likely to be noise. In this study, detected feature charge states were 2+ to 4+ and the minimum number of isotope peaks was 2. For each identified MS/MS spectrum , all precursor features observed in MS1 data with close monoisotopic m/z (within 40 p.p.m.), close retention time (<±1 min) and same charge state were considered as candidates. Among these candidates, the MS1 feature with the closest retention time was determined as the precursor ion for the MS/MS spectrum. The peptide ion intensity and its retention time were determined from the apex of the monoisotopic peak. The quantitation results for phosphopeptides in class 3 were listed in The peptide ion quantitation was performed based on MS1 feature intensity using the DDA quantitation module from DIA-Umpirehttp://www.phosphosite.org) was used to visualize significantly conserved sequences. We applied the Motif-X algorithmP<10−6, and the occurrence was set at 20. The extracted phosphorylation motifs were analyzed using the Human Protein Reference Database (http://www.hprd.org/) to search for predicted kinasesTo characterize the amino acid composition of the identified phosphopeptides, the Sequence Logo Generator . After electrophoresis, the gels were blotted onto PVDF membranes (Millipore) and blocked with blocking buffer (5% BSA in TBS) for 1 h, and then incubated with anti-EGFR antibody , anti-EGFR phosphosite-specific antibody , anti-CDK1 antibody (Abnova) and anti-CDK1 (Abgent) phosphosite-specific antibody by 1:1,000 diluted in blocking buffer. After washing with TBST (0.05% Tween-20 in TBS), the membranes were incubated with peroxidase-conjugated second antibodies for developing the signal.For Western blotting, cells were lysed by lysis buffer  and then incubated on ice for 15 min. Following incubation, the samples were spun at 13,000 −1. The 20 μl PCR mixture included 2 μl complementary DNA (10 ng), 10 μl 2 × SYBR-green PCR Master Mix (KAPA cat. KK4600), 0.4 μl ROX, 1 μl 4 μM each primer (forward and reverse)  is defined as the fractional cycle number at which the fluorescence passes the fixed threshold.The real-time reverse transcription (RT–PCR) was performed using a standard protocol on an Applied Biosystems 7500 System. Complementary DNA have been purified and diluted to 5 ng μlreverse)  and 5.6 C.-F.T., Y.I. and Y.-J.C. designed the research. C.-F.T., Y.-T.W., P.-Y.L., H.-Y.Y. and H.-Y.C. participated in the data generation. C.-F.T., C.-C.T. and A.I.N. participated in data quantitation. Y.-J.C., Y.I. and C.-F.T. wrote the manuscript, and Y.-J.C., Y.I., C.-F.T., Y.-T.W. and W.-C.K. edited it.http://proteomecentral.proteomexchange.org) via the PRIDEPXD000728.Accession codes: The raw data sets have been deposited in the ProteomeXchange Consortium .Supplementary Figures 1-3, Supplementary Tables 1-4, Supplementary Note 1List of total identified phosphopeptides in PC9 and PC9/gef. cells.Summary of stoichiometry of motif-targeting phosphopeptides after kinase reaction by CK2, MAPK and EGFR in PC9 and PC9/gef cells.


Rapid drug desensitization (RDD) is widely used to re-introduce medications that have caused an IgE-mediated hypersensitivity in allergic patients. However, RDD protocols are largely based on empiric experience and few in vitro models have explored the rationale guiding the rate at which the dose should be increased, what the starting dose should be and how the time elapsed between doses affect the effectiveness of desensitization. This study addresses these issues in a new humanized in vitro model of rapid desensitization.Bone marrow-derived mast cells (BMMCs) from transgenic Balb/c mice expressing the human high affinity IgE receptor alpha chain (hFcRI) were sensitized with human serum containing IgE against dust mites. Sensitized BMMCs were challenged with Dermatophagoides pteronyssinus administered at once (activation) or through a step-wise progressive increase in concentration (desensitization). The influence of the concentration fold-increase per step, of the starting concentration and of the time elapsed between steps on the inhibition of mediator release (-hexosaminidase) induced by desensitization was assessed.Inhibition of -hexosaminidase release correlated with the fold-increase per step, the starting concentration and the time elapsed between steps. A two-fold increase per step protocol induced 81% inhibition compared to 51% (p=0.001) and 19% (p=0.003) for four-fold and ten-fold increase per step protocols. Maximal inhibition was reached with a starting concentration below the activation threshold (80%) and a progressive reduction in inhibition was observed with starting concentrations above that threshold. One-minute intervals between steps induced a small degree of inhibition (15%) that was maximal with 10-minute intervals (81%) (p<0.001).in vitro humanized mast cell/IgE-mediated desensitization model will allow evaluation of drug hypersensitivity patients and provide the basis for adjusting the fold-increase per step, the starting concentration and the time between steps necessary for safe rapid drug desensitization. These three factors independently influence the inhibition of mediators release and should be taken into account in all RDD protocols.This


Human brain microvascular endothelial cells (hBMVECs) are integral part of the blood brain barrier. Post-translational modifications of adherens junction proteins regulate the permeability of human brain microvascular endothelial cells. Pro-inflammatory signals can induce tyrosine phosphorylation of adherens junction proteins. The primary objective of this work is to provide a molecular model; how the HIV-1 Tat protein can compromise the BBB integrity and eventually lead to neurological consequences. We exposed hBMVECs to recombinant HIV-1 clade C Tat protein to study the effect of HIV-1 Tat C on permeability of hBMVECs. Trans-endothelial electrical resistance and fluorescent dye migration assay have been used to check the permeability of hBMVECs. DCFDA staining has been used for intracellular reactive oxygen species (ROS) detection. Western blotting has been used to study the expression levels and co-immunoprecipitation has been used to study the interactions among adherens junction proteins.HIV-1 Tat C protein induced NOX2 and NOX4 expression level and increased intracellular ROS level. Redox-sensitive kinase; PYK2 activation led to increased tyrosine phosphorylation of VE-cadherin and β-catenin, leading to disruption of junctional assembly. The dissociation of tyrosine phosphatases VE-PTP and SHP2 from cadherin complex resulted into increased tyrosine phosphorylation of VE-cadherin and β-catenin in HIV-1 Tat C treated hBMVECs.Unrestricted phosphorylation of junctional proteins in hBMVECs, in response to HIV-1 Tat C protein; leads to the disruption of junctional complexes and increased endothelial permeability. HIV enters the central nervous system (CNS) by crossing the blood brain barrier (BBB) during early stages of HIV infection through infected blood cells ,2. HIV iet al. [VE-PTP is a tyrosine phosphatase, transmembrane binding partner of VE-cadherin. It connects with VE-cadherin through an extracellular domain and maintains the unphosphorylated state of VE-cadherin . Anotheret al. ; reporteet al.  and VE-cet al. .Phosphorylated states of the VE-cadherin and β-catenin regulate their interactions, and control the adhesion forces . VE-cadhPro-inflammatory factors affect the phosphorylated state of VE-cadherin complex and disrupt the barrier integrity ,20. In t2 in a humidified incubator.Primary hBMVECs were obtained from Dr. Joan Berman, department of pathology, Albert Einstein College of Medicine, New York as a kind gift. hBMVECs were cultured as described previously . For allHIV-1 Tat C protein has been expressed and purified as per our standardized protocol, described elsewhere in detail . ImmunochBMVECs were grown as confluent monolayer and exposed with HIV-1 Tat C protein at various doses  in serum-free M199 media. Control cells were treated with Tat buffer . BMVECs have been exposed to Tat C at different concentration ranges due to its closeness to reported serum levels and hBMVECs would normally encounter such concentrations of Tat in NeuroAIDS patients ,25. hBMVCell lysis were done in RIPA buffer . Estimation of protein concentrations was done by Bradford assay (Bio-Rad). Proteins samples were boiled in SDS-loading buffer and run on 12% SDS-gel, transferred on PVDF membrane (Millipore) at 100 V for 2 hrs. Primary antibody incubations were given overnight at 4°C with dilutions (1:1000). HRP conjugated secondary antibody were applied for 1 hour at room temperature and developed by using Super Signal developing reagent . Antibodies against p-Y-731-VE-cadherin (Invitrogen), VE-cadherin, anti-β-tubulin, NOX2 and NOX4 (Abcam), β-catenin (Santacruz biotechnology), PYK2 , SHP2 (Sigma) have been used in the study. VE-PTP antibody was provided as a kind gift by Astrid F. Nottebaum, Max Planck Institute of Molecular Medicine, Muenster, Germany.4 in 500 μl of complete M199 media. To check the development of junctional integrity, TEER values were checked on regular intervals until reached at consistent resistance in endothelial cells. After attaining the optimal confluency, the hBMVECs were treated with different doses of HIV-1 Tat C protein. TEER of hBMVECs was measured after 12 hrs of HIV-1 Tat C protein exposure. The resistance of empty insert membranes, without cell seeding was deducted from recorded TEER values.EVOM2 (World precision Instruments) was used to measure electrical resistance across the endothelial monolayer. PTFE membrane inserts (12 well plate) (Corning Life sciences) consisting of 3.0 μm pore sizes were used in the permeability assays. 0.2% bovine gelatin coating was done on insert membrane before cell seeding for better adherence of hBMVECs. Cell seeding density was 2 × 10The fluorescein migration assay was performed as described previously elsewhere . hBMVECsCells were pelleted after 12 hours of HIV-1 Tat C treatment (500 ng/ml), washed with cold PBS and lysed in NP-40 mild lysis buffer . Equal amounts of protein samples were incubated with VE-cadherin antibody overnight at 4°C. These samples were incubated with protein-G-sepharose beads for 3–4 hours followed by centrifugation. The immunoprecipitated samples along with beads were washed three times with lysis buffer and finally eluted by boiling in SDS-loading buffer. The samples were run on 12/% SDS-Page gel and probed with respective antibodies.hBMVECs were grown in 6 well culture dishes till confluency. HIV-1 Tat treatment was given for 12 hours at the different doses as described earlier. Cells were washed with HBSS and treated with final concentration of 10 μM of cell permeant fluorogenic dye 2’ 7’ dichlorofluorescein diacetate (DCFDA) for 15 minutes at 37°C in incubator chamber. After 15 minutes of incubation, cells were washed and fluorescence was visualized under fluorescence microscope .Chemical inhibiter against PYK2 (PF-431396) (Tocris Bioscience) has been used to inhibit the kinase activity. hBMVECs were cultured till confluency and treated with 22 nM PF-431396. Cells treated with equal volume of DMSO have been taken as control. Diphenyleneiodonium chloride (DPI) (Sigma Aldrich) dissolved in DMSO has been used as ROS scavenger, at 100 nM concentration. hBMVECs were harvested for lysate preparation after 12 hours of treatment.Results have been expressed as the mean and standard error of the mean. Level of significance in treated group versus untreated group has been measured by using Student’s t test. P-values < 0.05 have been taken as significant in one tailed array.We investigated the tyrosine phosphorylation of VE-cadherin and β-catenin in hBMVECs treated with increasing doses from 100 ng/ml to 1 μg/ml of HIV-1 Tat C. Both the adherens junction proteins (AJPs) (VE-cadherin and β-catenin) were significantly phosphorylated up to 4 folds at their respective tyrosine positions in dose dependent manner  and PTP (protein tyrosine phosphates) balance in cells . IntraceProline-rich tyrosine kinase 2 (PYK2) is a non-receptor tyrosine kinase, belongs to the focal adhesion kinase (FAK) family . HIV-1 TRedox-sensitive PYK2 activation and phosphorylation of β-catenin leads to conformational disorganization of cadherin complex in endothelial cells . We expohBMVECs were treated with PYK2 inhibiter PF-431396 (Inhibiter of kinase activity) (Tocris Bioscience) and checked for tyrosine phosphorylation of β-catenin. Significant reduction in tyrosine phosphorylation of β-catenin resulted into an accumulation of total β-catenin Figure A, B. No Neurological consequences still persist in the era of HAART therapy, where viral load has been effectively controlled in infected patients. However HIV-1 protein such as Tat has been detected in the CSF of patients kept on anti-retroviral therapy and show effectively controlled viremia . Therefoin vitro BBB model study showed that HIV-1 infection of pericytes can also result into compromised BBB integrity [Different mechanisms and pathways have been reported for the regulation of endothelial permeability. Involvement of PPAR/lipid raft-dependent MMP-2 and MMP-3 activation lead to the degradation of occludin and tricellulin, which has been reported in C12-HSL-induced perturbations of epithelial barrier functions . Role ofntegrity . Anotherntegrity .In our study, we observed a dose-dependent increase in tyrosine phosphorylation of VE-cadherin at p-Y731 position and β-catenin at p-Y654 position  reported the generation of ROS through activation of NADPH oxidases and activation of redox-sensitive tyrosine kinase PYK2 and their effect on cell-cell junctions. They suggested that activation of PYK2 could be essential for VE-cadherin/VE-PTP dissociation [VE-PTP enhances VE-cadherin mediated cell–cell adhesion and plays a major role in maintaining endothelial barrier permeability . The sigociation . In our ociation  and deph et. al. 013 reporPro-inflammatory insults affect the binding of VE-cadherin and β-catenin . We obseWe checked the tyrosine phosphorylation of β-catenin in hBMVECs treated with PYK2 inhibiter (PF-431396). PF-431396 abrogates the kinase activity of PYK2/FAK family kinases. A significant decrease in p-Y-β-catenin was observed in the hBMVECs treated with PF-431396 Figure A, B. OurHIV-1 Tat C mediated activation of NADPH oxidases (NOX2/ NOX4) led to the increased generation of ROS in hBMVECs and activation of PYK2 kinase. Upregulation of PYK2 activity resulted into the increased tyrosine phosphorylated forms of β-catenin and VE-cadherin. The dissociation of VE-PTP and SHP2 from VE-cadherin complex increased the tyrosine phosphorylation of VE-cadherin/β-catenin, which led to disrupted physical association of AJPs within VE-cadherin complex at endothelial junctions. These conformational alterations increased the permeability in hBMVECs. ROS scavenging as well as inhibition of the PYK2 activity showed a significant potential in combating the HIV-1 Tat C mediated disruption of endothelial permeability Figure . This stAll authors declare that they have no competing interests.RM and SKS designed research; RM performed research; RM and SKS analyzed data; SKS wrote the paper. Both authors read and approved the final manuscript.RM is currently working as CSIR-Senior Research Fellow and pursuing her Ph.D at CCMB, Hyderabad. SKS is leading a research group in the area of Neurovirology at CCMB, Hyderabad.


Pull-down assay results showed that EGCG could bind with RSK2 at both kinase catalytic domains in vitro and ex vivo. Furthermore, results of an ATP competition assay and a computer-docking model showed that EGCG binds with RSK2 in an ATP-dependent manner. In RSK2+/+ and RSK2-/- murine embryonic fibroblasts, EGCG decreased viability only in the presence of RSK2. EGCG also suppressed epidermal growth factor-induced neoplastic cell transformation by inhibiting phosphorylation of histone H3 at Ser10. Overall, these results indicate that RSK2 is a novel molecular target of EGCG.The most active anticancer component in green tea is epigallocatechin-3-gallate (EGCG). Protein interaction with EGCG is a critical step for mediating the effects of EGCG on the regulation of various key molecules involved in signal transduction. By using computational docking screening methods for protein identification, we identified a serine/threonine kinase, 90-kDa ribosomal S6 kinase (RSK2), as a novel molecular target of EGCG. RSK2 includes two kinase catalytic domains in the N-terminal (NTD) and the C-terminal (CTD) and RSK2 full activation requires phosphorylation of both terminals. The computer prediction was confirmed by an  O-tetradecanoyl-phorbol-13-acetate (TPA) and epidermal growth factor (EGF)-induced cell transformation  with freezing and thawing. Protein concentration was measured using a protein assay kit  for Western blotting. Proteins were transferred onto polyvinylidene difluoride membranes and hybridized with antibodies to detect RSK2, β-actin, phosphorylated histone H3 (Ser10), or total histone H3. Antibody binding was performed at 4°C overnight. Protein bands were visualized with a horseradish peroxidase-conjugated secondary antibody and a chemiluminescence detection kit. The blots were treated with stripping buffer  and re-probed with β-actin and histone H3 antibodies as loading controls.JB6 Cl41 , 10 mM NaF, 1 mM sodium orthovanadate and 25 mM β-glycerophosphate]. Nuclei were recovered by centrifugation at 13,000 rpm for 10 min at 4°C. Nuclei were suspended in buffer . Nuclei were extracted with 0.4 N H2SO4 to isolate total histones. The samples were precipitated with trichloroacetic acid (TCA) and then resuspended in double-distilled H2O.To isolate histone proteins, cells were homogenized in nuclear preparation buffer [10 mM Tris-HCl (pH 7.6), 150 mM NaCl, 1.5 mM MgClhttp://www.uniprot.org/) and the crystal structures of RSK2 NTD and CTD. Prime is a powerful and complete tool for generating accurate receptor models for structure level analysis. It provides an easy-to-use interface from sequence to refined structure. The full-length RSK2 homology structure was generated with loop energy minimization and dynamics by using the Impact module from Schrödinger Suite 2014. Molecular dynamics simulations were performed with default options or modified settings. For the default options, a constant temperature (NVT) simulation was run at room temperature with constant dielectric (dielectric constant 1.0) and the OPLS_2005 force field. For the modified settings, we increased the number of MD steps from 100 to 100,000 and as a result, a total 100 ps simulation was performed for the RSK2 homology structure. Following the molecular dynamics simulation, the full-length RSK2 homology structure was prepared under the standard procedure of the Protein Preparation Wizard in Schrödinger Suite 2014. The 30 Å grid for docking was generated based on the ATP binding pocket for both the NTD and CTD of RSK2. EGCG was prepared for docking by default parameters using the LigPrep program from Schrödinger Suite 2014. Then the docking of EGCG and RSK2 was conducted using the Induced Fit docking program of Schrödinger. The program allows EGCG to bind flexibly within the ATP binding pocket. For the Glide docking parameters, the van der Waals scaling of receptors and ligands was set at 0.5 and only the residues within 5.0 Å of ligands were refined. The other options were kept at default parameters and the best 20 poses were retained under the extra precision (XP) mode. In this way, we could obtain the best-docked representative structure.To date, no full-length RSK2 crystal structure has been reported. However, our laboratory has published the respective CTD and NTD crystal structures of RSK2 , 22. For+/+ or RSK2-/- MEFs were seeded (5 × 103) into 96-well plates in 100 μl of 10% FBS/DMEM and then incubated with 10 μM EGCG for 24 or 48 h in a 37°C, 5% CO2 incubator. CellTiter 96 Aqueous One Solution  was added and cells incubated for 1 h in a 37°C, 5% CO2 incubator. To stop the reaction, 25 μl of a 10% SDS solution were added and absorbance read at 492 and 690 nm using a plate reader .RSK23/well) were suspended in 1 mL basal medium Eagle (BME), 10% FBS and 0.33% agar and plated with various concentrations of EGCG on 3 mL of solidified BME containing 10% FBS and 0.5% agar with the same concentrations of EGCG as on the top layer. Colony number was determined by microscope and the Image-Pro Plus software program .JB6 Cl41 cells  as substrate. Treatment with EGCG resulted in a dose-dependent inhibition of histone H3 Ser10 phosphorylation  of ATP. Beads were washed and RSK2 binding was visualized by Western blotting with an RSK2 antibody. Results showed that EGCG binds with RSK2 in an ATP competitive manner  totally abolished the phosphorylation of histone H3 at Ser10. Histone H3 phosphorylation at Ser10 by RSK2 is critical for neoplastic cell transformation induced by EGF or TPA [We previously reported that RSK2 promoted anchorage-independent cell growth induced by EGF or TPA . PhosphoF or TPA . We examCellular kinase-signaling networks are a major regulator of cancer progression and are often involved in pathogenesis. Kinase mutations are relatively common and potent drivers of oncogenesis , 35. TarThe targeted inhibition of multiple kinase signaling pathways by small molecules is becoming an increasingly popular strategy for chemoprevention and chemotherapy . In receComputational methods have been widely applied in biological studies, with the intrinsic advantage of selecting a smaller number of lead compounds in a large database for biological testing, while avoiding expensive and time-consuming experiments , 42. ManEGCG, the main and most significant polyphenol in green tea, has shown antioxidant, anti-inflammatory and anti-atherogenic activities , 2, 4. Srsk2 gene failed to exhibit EGF-stimulated phosphorylation of histone H3 at Ser10 [Fibroblasts with mutations of the at Ser10 . Increasat Ser10 , 46. EGFat Ser10 . In thatat Ser10 . In the in vitro and ex vivo pull down assay results indicated that EGCG could bind with RSK2 at both the NTD and CTD in an ATP competitive manner Click here for additional data file.S2 FigEGCG significantly inhibits the size of EGF-induced colonies. Using the Image-Pro Premier offline software , the size of each colony was measured as relative surface area expressed as pixels2. Results are expressed as mean values ± S.D.  for triplicate experiments.(TIF)Click here for additional data file.


From the scientific literature, we manually collected experimentally identified phosphorylation sites on seven types of residues, including serine, threonine, tyrosine, aspartic acid, histidine, cysteine and arginine. In total, the dbPSP database contains 7391 phosphorylation sites in 3750 prokaryotic proteins. With the dataset, the sequence preferences of the phosphorylation sites and functional annotations of the phosphoproteins were analyzed, while the results shows that there were obvious differences among the phosphorylation in bacteria, archaea and eukaryotes. All the phosphorylation sites were annotated with original references and other descriptions in the database, which could be easily accessed through user-friendly website interface including various search and browse options. Taken together, the dbPSP database provides a comprehensive data resource for further studies of protein phosphorylation in prokaryotes.As one of the most important post-translational modifications, phosphorylation is highly involved in almost all of biological processes through temporally and spatially modifying substrate proteins. Recently, phosphorylation in prokaryotes attracted much attention for its critical roles in various cellular processes such as signal transduction. Thus, an integrative data resource of the prokaryotic phosphorylation will be useful for further analysis. In this study, we presented a curated database of phosphorylation sites in prokaryotes (dbPSP, Database URL: Database URL:http://dbpsp.biocuckoo.org Escherichia coil by Garnak and Reeves , the reversible protein phosphorylation was involved in almost all biological processes , 2. Phosd Reeves  in 1979,eckenius , aspartieckenius . It was eckenius , while Seckenius .et al.  mass spectrometry based proteomic technologies greatly advanced the identification of phosphorylation sites , 14. Numet al.  identifi  with keywords including ‘bacteria phosphorylation’, ‘archaea phosphorylation’ and ‘archaebacteria phosphorylation’ (1 March 2014). All the retrieved 16 658 articles were manually reviewed and checked by domain experts to collect the experimentally identified prokaryotic phosphorylation sites. The curated phosphorylated residues were explicitly mapped to UniProt proteomes sequences (Release 2014_06) (The construction of database dbPSP was summarized as a diagram in 2014_06) , while tBesides manual curation from literatures, the prokaryotic phosphorylation sites in public databases were also collected. From databases including PHOSPHORYLATION SITE DATABASE , SysPTM Crenarchaeota and Proteobacteria have the most substrates with the most proportions of 39.43% and 24.10%, respectively  was selected as an example to describe the usage of browse and search options. In the ‘Browse by residue types’, the phosphorylated residues are shown in diagrams  (E. Coli k12) and Sulfolobus acidocaldarius, which contained the most identified phosphoproteins and sites in bacteria and archaea, respectively. The gene ontology (GO) (31 March 2012) association files were downloaded from the The Gene Ontology Annotation (GOA) database at the European Bioinformatics Institute (EBI) (http://www.ebi.ac.uk/goa)  and S. acidocaldarius . It was observed that translation (GO:0006412) was the intensively enriched biological process in phosphoproteins from E. Coli k12  , rRNA binding (GO:0019843), protein binding (GO:0005515), magnesium ion binding (GO:0000287), identical protein binding (GO:0042802) and RNA binding (GO:0003723) , ligase activity (GO:0016874), aminoacyl-tRNA editing activity (GO:0002161), nucleic acid binding (GO:0003676) and ATP binding (GO:0005524)   and the .uk/goa) . With hy.uk/goa) , we statColi k12 A, while aldarius . For mol0000166) . Further0003723) A, while 0005524) B. In addColi k12 A, while Taken together, in this study the dbPSP database was developed to maintain the experimentally identified phosphorylation sites in prokaryotes. We anticipated that such database could provide a useful resource for further studies and understanding of phosphorylation in prokaryotes.National Basic Research Program (973 project) (2013CB933900 and 2012CB910101); Natural Science Foundation of China ; International Science and Technology Cooperation Program of China (2014DFB30020); and China Postdoctoral Science Foundation (2014M550392). Funding for open access charge: 31171263.This work was supported by grants from the Conflict of interest. None declared.


Latrophilins, receptors for spider venom α-latrotoxin, are adhesion type G-protein-coupled receptors with emerging functions in synapse development. The N-terminal region binds the endogenous cell adhesion molecule FLRT, a major regulator of cortical and synapse development. We present crystallographic data for the mouse Latrophilin3 lectin and olfactomedin-like (Olf) domains, thereby revealing the Olf β-propeller fold and conserved calcium-binding site. We locate the FLRT-Latrophilin binding surfaces by a combination of sequence conservation analysis, point mutagenesis, and surface plasmon resonance experiments. In stripe assays, we show that wild-type Latrophilin3 and its high-affinity interactor FLRT2, but not the binding-impaired mutants we generated, promote HeLa cell adhesion. In contrast, cortical neurons expressing endogenous FLRTs are repelled by wild-type Latrophilin3 and not by the binding-impaired mutant. Taken together, we present molecular level insights into Latrophilin structure, its FLRT-binding mechanism, and a role for Latrophilin and FLRT that goes beyond a simply adhesive interaction.  •The LPHN olfactomedin-like domain forms a five-bladed β propeller•A conserved calcium-binding site is located at the center of the protein•Latrophilin-FLRT binding depends on a conserved binding site•Mutations in the binding site inhibit Latrophilin-FLRT signaling Jackson et al. describe a crystal structure of mLPHN3 lectin and olfactomedin-like (Olf) domains, revealing the Olf β-propeller fold and calcium-binding site. Assays using HeLa cells and cortical neurons reveal a bi-functional role for Olf and its ligand FLRT, leading to HeLa cell adhesion and neuron repulsion. Latrophilins (LPHN1–3) are a family of adhesion type G-protein-coupled receptors (GPCRs) first characterized as calcium-independent receptors for the black widow spider toxin α-latrotoxin, which causes massive exocytosis of calcium at nerve terminals . More retrans through their ectodomains to mediate cell adhesion, an interaction that promotes the development of glutamatergic synapses  . In zebrsynapses . The LPHsynapses .Lec-Olf). We find that the Olf domain folds into a five-bladed β propeller with metal ions buried in the center of the molecule. We show that, by introducing specific mutations at the surface of the Olf domain, we can reduce or impair binding to FLRT. We also show that LPHN3Lec-Olf is sufficient to attract FLRT-expressing cells through its adhesive FLRT-binding properties. Interestingly, the FLRT-binding site on LPHN3 is required for repulsive activity of LPHN3 toward cortex-derived neurons. The structural data presented here suggest that LPHN3 is a bi-functional protein with adhesive and repulsive properties, possibly mediated by similar surfaces of the Olf domain.Olf domains are present in at least 13 different proteins in mammals including the LPHNs (1–3), noelins , olfactomedin 4, olfactomedin-like , myocilins, and gliomedins ; howeverLec-Olf in human embryonic kidney (HEK) 293T cells using established protocols to circumvent the formation of heterogeneous glycans (α atoms). The Olf domain folds into a five-bladed β propeller, with each blade consisting of a four-stranded β sheet (Lec-Olf contains a reduced cysteine (C227) buried in the core of the Olf domain. This cysteine is conserved in the three murine LPHNs, but not in other Olf domains  to infer their chemical identities . The resLec-Olf structure with structures in the Dali database (Xanthomonas campestris (PDB accession code 3MBR)  ; the rmsropeller B and S1CLec-Olf and the previously solved FLRT2 leucine-rich repeat (LRR) domain , R324N+G326T (LPHN3LF(2)), T267N+K269T (LPHN3LF(3)), and P244N+R246T (LPHN3LF(4))  domain   domain A and 2B.onserved A. On FLRonserved B. We preonserved . To probonserved . For LPHN3LF(4)) A and 2C. FLRT2UF .Kd values in the range 18–40 nM depending on the experimental setup (Lec-Olf mutants LPHN3LF and LPHN3LF(2) do not have measurable affinity to the FLRT2 ectodomain. LPHN3LF(3) and LPHN3LF(4) bind FLRT2, but with greatly reduced affinity  experiments revealed high-affinity binding between wild-type FLRT2 and LPHN3 proteins, with al setup A–3E. In affinity C–3E. We of cells F and 3G.FF-ires-GFP) chose between growth on alternating stripes of LPHN3Lec-Olf and control protein (Fc)  led only to a mild preference for LPHN3Lec-Olf stripes  A. For al stripes D and 4E.elopment . Next, w stripes A. We cho stripes . In cont stripes B–5D. The stripes B–5D, indX. campestris  acts as a general acid and base to assist in the intramolecular cyclization reaction. No such residue is found in the putative active site of LPHN3, meaning it is unlikely that LPHN3Olf and bacterial QCs have exactly the same function. The “entrance” to the ion-binding pocket of LPHN3 Olf is obscured by loops. Should the LPHN3 Olf harbor an enzymatic function, the binding of substrate would likely involve structural rearrangement of these loops, perhaps providing substrate specificity. We expect that future studies will shed light on this exciting question.Our crystallographic data reveal the structure of a mammalian olfactomedin-like domain. The β-propeller fold reveals surprising structural homology with a range of enzymes, especially type I QCs from plant and bacteria. QCs catalyze the formation of pyroglutamate from glutamine or glutamate residues at the N terminus of proteins and peptides, and contain calcium or zinc in the catalytic site . Mammalsmpestris C. Furthereaction , is markAmong other mammalian Olf-containing protein families, the ion-coordinating residues of LPHN are conserved in at least three: myocilin, olfactomedin-like 2, and, to a lesser degree, noelins D. IndeedLec-Olf revealed that LPHN3 can be repulsive under certain conditions. This repulsive activity likely resides in the FLRT-binding site of the molecule, since the non-FLRT-binding mutant LPHN3LF failed to be repulsive. How could FLRT proteins expressed on the growth cones of neurons mediate repulsion? Engagement of LPHN3 with FLRTs may recruit in cis and activate other guidance receptors with repulsive activity, such as Robo1  and LPHN3Olf (residues 202–463) were cloned into the pHLSec vector and transiently expressed in kifunensine-treated HEK293T cells using previously described methods  was cloned into the same vector and transiently expressed in HEK293S GlnTI2. FLRT2 ectodomain proteins were coupled to CM5 Biacore chips via direct amine coupling. LPHN3Lec-Olf proteins were biotinylated enzymatically at a C-terminal avidity tag (Avi-Tag) and attached via the resulting biotin label to streptavidin-coated Biacore chip surfaces to mimic the native membrane insertion topology. Data were analyzed with Scrubber2 (BioLogic). Kd and maximum analyte binding (Bmax) values were obtained by nonlinear curve fitting of a 1:1 Langmuir interaction model (bound = Bmax/(Kd + C), where C is analyte concentration calculated as monomer).Equilibrium experiments were performed at 25°C using a Biacore T200 instrument . The experiments were carried out at pH 7.5  polysorbate 20). The regeneration buffer was 2 M MgClLec-Olf or LPHN3Lec-Olf LF mutant protein pre-clustered (ratio 1:4) with His-probe rabbit polyclonal immunoglobulin G (IgG) (Santa Cruz Biotechnology). Cells were washed twice with PBS and fixed with 4% paraformaldehyde for 20 min at 4°C. Bound LPHN3Lec-Olf proteins were then visualized with Alexa561-conjugated anti-rabbit IgG antibody  after 30 min of blocking with 1% BSA. Nuclei were counterstained with DAPI before mounting.HeLa cells in six-well plates were transfected with 2.0 μg of pCAGIG vector DNA encoding full-length FLRT2 using FuGENE 6 transfection reagent (Promega), according to the manufacturer’s instructions. Thirty-six hours after transfection, cells were incubated for 20 min at 4°C in Hank’s balanced salt solution containing LPHN3c protein mixed with anti-hFc for 30 min at 37°C, washed with PBS and, for culturing neurons only, coated with 20 μg/ml of laminin overnight at 37°C. HeLa cells or dissociated cortical (E15.5) neurons were cultured on the stripes for 3 hr (HeLa cells) or 16 hr (neurons), fixed, and stained. Details are provided in the Stripe assays were prepared essentially as previously described . In brieV.A.J. performed the crystallographic analysis, protein engineering, SPR experiments, and cell stripe assays. D.dT. aided and oversaw all stripe assay experiments. M.C. purified proteins for functional analysis. P.R. analyzed the LPHN3 ion-binding sites. K.H. performed heavy atom soaking and aided data collection and processing. E.S. produced protein crystals and oversaw biophysical experiments. All authors contributed to discussion and writing of the manuscript.


Aedes camptorhynchus, a salt marsh breeding mosquito and a prominent vector for Ross River virus in Australia. Aedes camptorhynchus usually has few competitors due to its halo-tolerance and distribution in salt marshes. However, sympatric ostracod micro-crustaceans often co-occur within these salt marshes and can be found in dense populations, with field evidence suggesting exploitative competition for resources. Our experiments demonstrate resource limiting conditions caused significant increases in mosquito developmental times, decreased adult survival and decreased adult size. Overall, non-culicid exploitation experiments showed little effect on larval development and survival, but similar effects on adult size. We suggest that the alterations of adult traits owing to non-culicid controphic competition has potential to extend to vector-borne disease transmission.Aquatic environments can be restricted with the amount of available food resources especially with changes to both abiotic and biotic conditions. Mosquito larvae, in particular, are sensitive to changes in food resources. Resource limitation through inter-, and intra-specific competition among mosquitoes are known to affect both their development and survival. However, much less is understood about the effects of non-culicid controphic competitors (species that share the same trophic level). To address this knowledge gap, we investigated and compared mosquito larval development, survival and adult size in two experiments, one with different densities of non-culicid controphic conditions and the other with altered resource conditions. We used  The effectiveness of exploitative competition for available food resources is driven by the presence of species within the same trophic level (controphic species) and species that share the same resources and functional feeding group , 2. For Aedes aegypti (Linnaeus) and Aedes albopictus (Say)) and mosquito oviposition behaviour as a means of predation and competition avoidance [Over the last two decades, significant effort has been directed to understanding the diverse effects that biotic interactions have on the ecology of mosquito vectors , 4–7. Thvoidance , 12. Thevoidance , 14.Ae. camptorhynchus (Thomson) [Alphavirus). Epidemiologically, RRV is Australia’s most important vector-borne disease with clinical notifications ranging between 1451 – 7754 per annum, resulting in an annual economic impact of approximately $15 million dollars [Ae. camptorhynchus, which is indicative of regions where this mosquito occurs across Australia [Ae. camptorhynchus lays desiccation resistant eggs that undergo mass hatching with large pulses of rainfall or tidal inundations [Diacypris spp. (Crustacea: Ostracoda) that dominate the remaining aquatic fauna in these environments [Ae. camptorhynchus. In addition, a negative density relationship from field evidence suggests these species may interact via exploitative competition [Across southern Australia Thomson) , 16 is a dollars . Salt maustralia –20. In tndations , 22. Likndations , 24. Theronments  are detrpetition . If explpetition .Ae. camptorhynchus development and survival. We examined our hypothesis using two experiments: an intra-specific resource limitation experiment with low densities of Ae. camptorhynchus; and a non-culicid controphic exploitative competition experiment with ostracods in increasing densities. Between the two experiments we contrast the changes in larval developmental times and survival, and effects on adult size. For both experiments, we predict decreased larval survival, increased development time, and reduced adult size as resources become limiting and controphic competition increases. We observed development and survival changes with intra-specific resource limitation and changes in adult size for both intra-specific resource limitation and controphic competition treatments. Our findings suggest no evidence of exploitative competition among Ae. camptorhynchus and ostracods during larval development, but detectable similarities to resource limitation with adult size.In this study we test the hypothesis that non-culicid controphic exploitative competition with ostracods reflects intra-specific resource limitation. The reciprocal of our hypothesis is that exploitative competition is not occurring between these taxa and ostracods will therefore have no impact on et.al. [Ae. camptorhynchus (56%) and ostracods (33%), increasing to 91% in drying conditions (Ae. camptorhynchus 46% and ostracods 45%) [Diacypris spp. (Crustacea:Ostracoda) [Ae. camptorhynchus and was, therefore, used in the competition experiment. Mosquitoes and ostracods were collected either after substantial rainfall or tidal inundations that submerged most of the salt marsh which provided newly hatched Ae. camptorhynchus larvae . While every attempt was made to collect early first mosquito instars, age was difficult to control in practice, so for consistency examination of developmental rates in this study are restricted to the second instar onwards. All invertebrates were collected using a 350 mL plastic larval dipper .All mosquitoes and ostracods used in this study were sourced from the Primrose Sands salt marsh , east of Hobart, Tasmania, whereby permission to access the marsh was granted by the land owner. Water bodies found in the Primrose Sands salt marsh are very ephemeral, lasting on average only 14 days after inundation over the peak of summer . Such enet.al.  where, aods 45%) . Examinatracoda) , is the Following field collections, mosquito larvae were placed into 500 mL translucent cylindrical plastic containers with 200 mL of water at 35 ppt salinity , 420–440 Ca (mg/L), 1250–1310 Mg (mg/L) and 380–400 K (mg/L)), with containers placed randomly in temperature cabinets  at 23°C ± 0.05 S.E., 14:10 day/night. The temperature and salinity were chosen for laboratory conditions based on the average summer daily temperatures (°C) and salinity (ppt) of water bodies in the field near Hobart .It is difficult to know the exact nutrient variables most relevant to mosquitoes within salt marshes and this is an important area for future studies. As a consequence, invertebrate food consisted of ground “Nutrafin Max Fish Flakes” (Pets Domain). Four grams were ground using a mortar and pestle and suspended in 1 L distilled water. At each feed the solution was agitated to allow for homogeneity and refrigerated at 6°C between feeds to standardise the potential growth of microbes. Although not entirely analogous to their field based diets, food levels and type were representative of other laboratory studies of culicid nutrition and development –31 and hn = 442) [We conducted a paired experimental design to examine the effects of both intra-specific resource limitation and non-culicid exploitative competition on mosquito development and survival. While a fully crossed design would have been optimal, this was beyond the scope of the study owing to the logistics of available incubators and number of ostracods required. Instead this study provides a paired design where intra-specific resource limitation and non-culicid controphic exploitative competition experiments are contrasted. In the resource limitation experiment 50 larvae were exposed to one of four food resource levels , with six replicate cylinders per treatment. For the exploitative competition trials 50 larvae were exposed to one of four treatments of competitor (ostracod) density (0 (control), 150, 300 and 600 ostracods/cylinder). This reflects the observed range of ostracod densities per 350 mL larval dippers  in water bodies at Primrose Sands between 2011 and 2012  . Food reDaily counts of mosquito larvae included the number of larvae, instar of each larva, number of pupae and number and sex of adults. Any mosquito larvae or pupae that died were recorded and removed from the container. All emergent mosquitoes were collected, sexed and their wings removed and mounted using water onto glass slides and sealed with clear nail varnish. The average length of left and right wings were used as a proxy for adult size . These wTo account for size variation of ostracods among treatments, a subsample of five ostracods from each controphic resource limiting replicate was removed at the beginning of the experiment and again at the end of the experiment (when the last mosquito emerged or died in each replicate container). Measurements of the carapace, from posterior to anterior, were conducted using an ocular micrometer (0.016mm units per graticule unit) on a Nikon SM2800 dissecting microscope at × 6.3 magnification. All remaining ostracods in each replicate were scored for survival.Yij  was measured for each replicat cylinder i = 1,…, nj for incubator j = 1,…, k. The distribution of Y among replicates was assumed to have a Gaussian distribution with parameter πij:πij is the modelled Y of replicate i in incubator j. We modelled the Y, πij, based on the effects of treatmentα and β are the model intercept and slope, respectively, for replicate i varying by incubator j, and x was the assigned experimental treatment (intra-specific resource or non- culicid controphic exploitative resource limiting level) for replicate i. An additional fixed effect of sex was included for the model of adult size. Prior distributions for all model parameters in the hierarchy (incubators) were given with the goal of providing conjugate priors that contain little to no influence on the posterior distributions of all the model parameters. We assumed normal prior distributions on slopes, α, and intercepts, β, with mean μ and variance σ2:In both experiments we evaluated how treatment affected larval developmental times, survival, and adult size. Larval development was determined as developmental time when 50% of surviving larvae had reached the next each instar stage, pupa or adult. Survival was measured as the number of emerging adults and size was based on wing length measurements. An alternative approach to evaluating survival is by Cox hazard models, but we could not reliably identify individual survival in our experiment design, precluding this type of analysis. We used a Bayesian mixed effects modelling approach, with incubator as the random effect, owing to its superior ability to estimate coefficients than non-bayesian approaches, in a mixed effects framework . In eachσ2, we determined and utilized non-informative uniform prior hyper-parameter distributions, specified as σ2~Uniform , which was used across all models. Models were fitted in R (v 3.0.3) [β, by the Bayesian median and 95% credible intervals and MCMC simulated P-values.For the variance parameters, v 3.0.3)  using thv 3.0.3) , with MCv 3.0.3) . We summWe assessed consistency of results between the two experiments at the 0.4 mL/day intra-specific resource limiting treatment and the control treatment (no ostracods and same food level) from the non-culicid resource exploitation experiment. This was undertaken for development, survival and adult size using a Bayesian mixed effects model as described above, but with experiments being the fixed effect.Ae. camptorhynchus developmental times, survival and size or ostracod development and mortality. This analysis was undertaken for quality control purposes, as changes in these could confound non-culicid exploitative competition treatment effects.Using a Bayesian mixed effects model as previously described, we also investigated ostracod size (measured through sub-samples) and mortality amongst competition treatments (end count of ostracods) to explore if these factors changed Ae. camptorhynchus to develop decreased (Table 1). This relationship was observable within each larval stage with the exception of the pupal stage when mosquitoes do not feed. Overall, the mean developmental time of Ae. camptorhynchus to adult was 35 days with a range of 21–70 days . Mean time to develop to adult was 27 days ranging between of 33–39 days (p = 0.176) , with a mean range of survival between 60.8% – 72.6%  . limited . The mea limited . By comp% Fig 1; . CompariAe. camptorhynchus (based on wing length) declined as intra-specific resources became more limiting (Table 1). Overall, emerging adults were 9.86% larger in the most resource rich treatment, relative to all the other resource treatments (Ae. camptorhynchus adults (Table 1). On average adults emerging from the control (no ostracods) were 4% larger than adults from the highest ostracod density treatment . There was no significant sex-specific size difference between treatments owing to ostracods (Table 1). Comparing the two experiments, adult size did not differ .The size of eatments . There wP = 0.624). Similarly, ostracod survival did not significantly differ between experimental treatments (P = 0.628), with an overall average 17% loss of ostracods.Ostracods within the non-culicid controphic exploitative treatments averaged 0.842 mm in length with no significant difference in size over the duration of the experiment  and Ae. aegypti in limiting diets and this was inferred to indicate impacts on accumulation, assimilation and storage of energy gained from food resources [As expected, reducing the resources available to al times , 38–41 lesources . Prolongesources , therebyAe. camptorhynchus development. This expectation was supported by other studies, such as Stav et al. [Culex pipens (Linnaeus) in the presence of Daphnia magna (Straus). In our trials the only significant impact on development we observed was during the third instar, with no effect of ostracod density on overall developmental times. While it is plausible that the densities within our trials were inadequate to result in exploitative competitive outcomes on Ae. camptorhynchus life history, the number of ostracods used in these trials reflect ostracod densities found in natural water bodies [Ae. camptorhynchus maintained consistent rates of development across density treatments of ostracods, and ostracod mortality was not significant across treatments, we suggest exploitative competition is unlikely to be limiting larval development in our system.The effects on non-culicid controphic competition on mosquitoes is a relatively new field of research, with few studies detailing increased developmental times in the presence of such exploitative competitors , 4, 44. r bodies , 27. TheAe. camptorhynchus survival declined as resources became limited, but Ae. camptorhynchus survival did not change with increasing densities of ostracod competitors. Declines in mosquito survival has been documented in other non-culicid controphic competitive studies [Aedes australis survival as a result of interference competition between tadpoles (Limnodynastes peronii), however this was a result of chemical interference not exploitative competition. In contrast, Daugherty and Juliano [Ae. triseriatus in the presence of higher densities of scirtid beetles, because of the quantities of faeces excreted by the scirtids supported microorganisms that nourished the developing mosquito larvae. This, again, is not exploitative competition. Overall, our results suggest that, like developmental rates, the density of ostracods has little impact on mosquito survival through exploitative competition in this system.Similarly, our intra-specific resource limiting trials showed  studies , 13, for Juliano  demonstrAe. camptorhynchus larval development and survival, it was somewhat surprising to see an effect on adult size. Limiting resources is known to cause emerging mosquitoes to be smaller [Ae. agypti adults emerging from nutrient deprived crowded conditions were significantly smaller. Here we suggest ostracod competitors may have a similar effect. Therefore, detecting the effects of competition between ostracods and Ae. camptorhynchus may be most sensitively measured through adult size rather than larval development and survival. On the other hand, it is possible that there is a coexistence between Ae. camptorhynchus and ostracods in these habitats and consequentially partitioning of resources driven by differences in species’ niches [Given the lack of detectable effects of ostracod density on  smaller . For exa’ niches  and thatAe. camptorhynchus reproductive success. In fact, resource limitation is correlated with fewer oogenesis cycles resulting in reduced fecundity [Ae. camptorhynchus being anautogenous [Ae. camptorhynchus limits vectorial abilities, although further research is necessary to understand the connection with Ae. camptorhynchus size and the ability to transmit RRV. A potential caveat is that experimental adults would not represent field adults, however, we have found substantial overlap in mean wing length between field caught adults and experimental adults .Even though adult size was negatively affected by intra-specific resource limitation, males were significantly larger than females for the most limiting resource treatment. It is known that larval females take longer to develop as a trade-off for greater accumulation of resources which ultimately results in larger sizes and improved fecundity , 49. Howecundity  and a deecundity , 41, 51.togenous  thereby Ae. camptorhynchus and ostracods is limited in laboratory conditions. It is possible that environmental conditions may be more important than competition alone in that competitive effects may change given different abiotic conditions [Ae. camptorhynchus larvae are more sensitive to environmental changes or intra-specific competition [Ae. camptorhynchus development, survival and size) would benefit our understanding on the relationship between Ae. camptorhynchus inter- and intra-specific interactions and provide further insight on the complexity of competitive systems.Overall our experiments suggest exploitative competition between nditions , 53, 54.nditions . For exanditions , 57. Sucpetition . TherefoAe. camptorhynchus survival and development, it is possible that densities of non-culicid competitors (and resource limitation) may result in reduced adult longevity especially considering both treatments had an effect on adult size.A limitation of our study is that we did not measure adult survival. Epidemiological models of mosquito-borne disease transmission incorporate adult longevity which can have significant effects on disease transmission . HoweverAe. camptorhynchus life history in exploitation competition environments is not so obvious. We conclude that controphic competition, although quite complex, may have a role in influencing vector-borne disease and implications to human health.We demonstrate that intra-specific resource limitation and controphic competition have a direct impact on adult sizes, however, changes to S1 Table(PDF)Click here for additional data file.


Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation. Sequences of stereotyped actions are central to the everyday lives of humans and animals. It was hypothesized over half a century ago that these behaviors were enabled by linking together groups of neurons (or “cell assemblies”) into a feedforward chain using correlation-based learning rules. These chains could then be activated to generate particular behavioral sequences. However, recent data from HVC  paint a more complicated picture: inhibitory and excitatory cells lock to different phases of a rhythm, with inhibitory cells providing windows of opportunity for the excitatory cells to fire. This study puts forward a mathematical model that uses both a feedforward chain geometry and local feedback inhibition to generate stereotyped neural sequences. The chain conducts an excitatory pulse through multiple spatial regions, arriving at each as local inhibition dips. Our simulations and analysis demonstrate that such patterned local inhibition can synchronize the firing of pools of neurons and stabilize spike timing along the chain. Our model provides a new way of thinking about sequence generation in the songbird and in neural circuits more generally. From the kingfisher’s dive to the performance of a piano concerto, sequences of stereotyped actions are central to the everyday lives of humans and animals. One of the most well-studied behavioral sequences in nature is birdsong, and the physiology underlying HVC  has been a topic of intense interest. Principal neurons in HVC produce sparse, time-locked bursts of activity that are stereotyped from trial to trial , 2. TempA well-studied model that provides a possible answer is the synfire chain , 7. The RA) receive stereotyped excitatory inputs at multiple points during the song, but only burst when excitatory inputs align with pauses in inhibition. And Markowitz et al. ), whTi that agreed roughly with the amount of time it took for an excitatory pulse to circle the loop once. If Ti was too large, inhibitory decay was too slow to produce noticeable synchronizing effects; if it was too small, the inhibition would be almost entirely gone by the time the pulse returned, with similar results.At each spike volley, the decay of the inhibition produced by the previous local volley had to still be in progress. Thus, we had to choose an inhibitory decay time constant Synaptic conductances had to be tuned such that excitatory volleys consistently evoked responses in downstream excitatory and inhibitory cells, even when those cells were partially inhibited. As we note in the Discussion, propagation failure due to inhibition could help control for relaxed architectural constraints; however, pulse propagation failure was also outside the scope of our study.Mi was set to 1, we did not observe improved timing across trials.For feedback inhibition to improve the consistency of spike volley timing across trials, the response of the inhibitory populations to local spike volleys had to be consistent across trials. Running the simulation with a large number of inhibitory cells helped average out the effects of noise on the inhibitory population: when Parameters were chosen for this model in order to produce the desired dynamics when local feedback was activated. Specifically, the model was built and tuned with the following objectives in mind:As long as these four conditions were met, the effects of local feedback inhibition on spike volley synchronization and timing described below were robust to variation in model parameters.Me = 20, Mi = 50 and N = 5, and simulated the system with and without feedback inhibition. As we discuss below, this simulation run with feedback inhibition produced short periodic volleys of inhibitory spikes in each zone, an activity pattern considerably tidier than that of inhibitory cells observed in HVC. These dynamics obeyed conditions that made the system analytically tractable, allowing us to provide a quantitatively accurate theory explaining our simulation results. However, we also wanted to show that a more complex pattern of inhibitory activity could produce qualitatively similar results. For this purpose, we performed simulation 2, for which we set Me = 50 and adjusted various parameters related to the inhibitory cells. All parameter values for both simulations are listed in We simulated this system with two different sets of parameters. In simulation 1, we set E(t):τr is the time constant for the rise of the EPSC, r is the duration of its rise, and τd is the time constant of its decay  When we introduced feedback inhibition, the trial-averaged vp instead decreased slightly and appeared to stabilize. Thus, feedback prevented the progressive desynchronization of pools and instead stabilized a tight distribution of spikes about the mean.As a measure of within-pool synchrony and its evolution over time, we calculated the mean lation 1 . WithoutF of the possible global E-to-I and I-to-E connections and then normalized connection strengths to ensure that the excitatory pulse still reached the last pool. We normalized connection strengths by modifying To quantify the dependence of the synchronizing effect of local feedback on the model topology, we gradually introduced non-local E-to-I and I-to-E connections into the network in simulation 2. For each trial, we instantiated a fraction nections .p that receives its excitatory pulse earlier than the others in its pool also receives its pulse under a heavier blanket of inhibition, so its latency to spike is greater, whereas a cell that receives its pulse late can fire with reduced latency. Thus, decaying inhibition reigns in outlier spike times and forces spike times within a volley towards a shared mean. This intuition is explored more thoroughly in the Analysis section below.The synchronizing effect of local feedback inhibition on chained pools of cells can be understood as a specific instance of the more general phenomenon of synchronization by a slow-decaying pulse of shared inhibition described by Börgers and Kopell in . A cell i and each pool p, we calculated the mean spike time p .  Thus, the reduction in inter-trial variability created by feedback inhibition was due to the stabilizing effect of lingering local feedback inhibition described above, which most directly influenced not the time of pulse propagation along excitatory connections, but rather the time for the pulse to circle the network and return.Both with and without feedback, ation in  that, asIn order to more fully understand the cause of progressive synchronization in our model with feedback, we introduced additional assumptions and approximations to make the model analytically tractable. These assumptions and approximations made it possible to linearize the dynamics around a set of excitatory spike times and allowed us to express the relationship between model parameters and the stabilization of synchrony in terms of the solution to a first passage time problem. Combining this analysis with a computational investigation of the first passage problem, we found that we could quantitatively describe the effects of IPSC decay rate, EPSC rise rate, and noise on pool synchronization. Simulation 1 met our additional assumptions, and we found that the synchronizing behavior of simulation 1 indeed agreed with our analytical predictions. Our analysis demonstrates that progressive synchronization by feedback inhibition is not a special property of a finely tuned computational model but a generic property of spatially recurrent feedforward chains with local feedback inhibition.ϕp mod N continues to decay exponentially while the cells in pool p fire.We first assume that principal cell spike volleys are not interrupted by the firing of local inhibitory cells. In simulation 1, this condition was met because parameters were set to ensure a sufficient delay between an excitatory spike volley and the local inhibitory response. If such interruptions do not occur, we can assume that m in pool p crosses above zero, its excitatory current  is well-approximated by a linearization with negative slope −bp, where bp > bmin for some constant bmin > 0 . Note that the slopes ap and bp are assumed to be the same throughout the firing of a given pool. Let t thatm in pool p crosses zero. Our approximations can be expressed as follows: for any p, ϕn) for all m = 0, …, Me. These approximations are most accurate while pools of cells remain near synchrony, as was the case throughout simulation 1 with feedback inhibition.We make the approximation that, as the drive to any excitatory cell bp be negative and bounded away from zero was fulfilled in simulation 1 because regular inhibitory spiking kept ϕn bounded away from zero. The requirement that the EPSC slope be positive was fulfilled because EPSCs were large enough that the drive to any cell crossed zero during the rise of its EPSC.Since inhibition decays at a rate proportionate to its level, the requirement that the IPSC slope −p as its drive crosses zero with the linearization:αp is a constant. Similarly, we can describe the local IPSC as the drive to cells in pool p crosses zero with the linearization:βp is a constant.Given these approximations, we can describe the EPSC to each excitatory cell in pool ϕp mod N and the excitatory cell spike times VS, where I(t) to the QIF neuron described in T, the distribution of its first spike time about T can be expressed as a function of only the rate I′(T) at which the neuron’s drive crosses zero (and the parameters of the QIF neuron). This assumption implies that the distribution of first spike times does not depend on initial voltage or on the drive I(t) outside a small neighborhood of the time it is brought past threshold. Under this assumption, the standard deviation of the distribution of first spike times can be expressed as σ(I′(T)). In I(t) outside a small neighborhood of T within the regimes relevant to this system. We also show the dependence of this distribution on threshold-crossing rate (σ(I′(T)) (I′(T).Given the trajectory of ing rate , and ploσ(I′(T)) , noting m in pool p, zp is a constant for each pool p, and σp.In μp to be the mean firing time in pool p, and we consider the variance vp of spike times within each pool p:vp is a measure of synchrony of spiking in pool p. If vp = 0, synchrony is perfect; larger vp denotes a higher degree of asynchrony. p given initial conditions, is a measure of the expected degree of synchrony in pool p.We want to describe the evolution of intra-pool synchrony over time. We define p in terms of bp = 0, so this expression predicts that expected variance should grow linearly at rate In bp > 0, the recursive relation sets an asymptotic upper bound on σ(⋅) is the standard deviation of the QIF neuron’s first passage time as a decreasing function of the rate of depolarization. In other words, the expected variance of spike times within a pool eventually becomes less than σ(amin + bmin) and bmin, the asymptotic upper bound on bmin is larger, i.e., if inhibition is decaying more sharply as local pools fire.In ap by measuring the slope of rising excitation over 4ms leading up to each spike, and averaging over all spikes. We then calculated σ(ap) by applying ramp depolarizations to QIF neurons as described in σ(ap)2 ≈ 0.21ms2. In ms2 per pool predicted by our analysis. Our prediction falls close to the cross-trial mean of vp, with some small deviation for early pools that may reflect a small artificial increase in synchrony due to initializing all cell voltages together.We validated our analytical results by checking them against the results of simulation 1. In simulation 1 without feedback, we approximated p ≥ 5. We computed ap and bp for pools p ≥ 5 by averaging the slope of the PSCs over the 4ms leading up to each spike, and then averaging the result over all spikes in pool p. We set amax, amin and bmin to the maximal and minimal values of ap and the minimal value of bp, respectively, during this run. We found that amax = 0.0787, amin = 0.0702, and bmin = 0.0042. By running QIF simulations as described in σ(amin+bmin) = 0.47. Thus, the upper bound on the variance predicted by our analytical results wasvp over trials was less than 2.23 (dotted line) with 99% confidence for all p ≥ N, strongly suggesting that the true value of In simulation 1 with feedback, we compared the upper bound on within-pool variance predicted by our analysis with the variance observed in simulation. Since the appropriate spatiotemporal coordination of the pulse and local inhibition is not present until the pulse has circled the network once, we considered only pools We have put forward a model of sequence generation based on recent experimental findings in the songbird , 13. In Though previous models of neural sequence generation have used inhibition in a variety of ways , 22–25, We have shown in simulation that our model of an excitatory chain spiraling through inhibitory zones creates local alternation between excitatory and inhibitory cells, consistent with the observation of cell-type specific phase preferences in the 30Hz component of the local field potential in HVC . MoreoveRA neurons should be primarily localized to a subregion of HVC, but recent evidence suggests that HVCRA pairs inhibit each other over relatively large distances (hundreds of μm) [RA neurons is in fact local or global.However, our model deviates from what is known experimentally in two important respects. First, interneurons in our model fire with strong periodicity, yet HVC interneurons have dense firing patterns with intermittent periodicity during singing , 33 see. Additios of μm) . Our simAs constructed for this study, our model has the capacity to play back only one sequence. In the case of the zebra finch, which learns only one song, this is an appropriate constraint, but this limitation would have to be addressed for broader applications. Storage of and selection between multiple sequences has been explored by other authors, both in HVC , 14, 15 bmin, where bmin represents an upper bound on the magnitude of the decay rate of inhibition during local excitatory spiking. The more sharply the local inhibition is decaying during the spiking of a pool, the larger a value we can choose for bmin. Consequently, the more sharply local feedback inhibition is decaying when a pool of cells spikes, the tighter the resulting synchrony guaranteed by our analysis. We have demonstrated in simulation and through proof that the presence of shared decaying inhibition progressively synchronizes the firing of pools of excitatory cells. We have also derived a specific asymptotic upper bound for the expected variance that decreases with increasing We have also shown in simulation that local feedback inhibition creates sequences with timing that is more stereotyped across trials. One possible intuitive explanation for this effect is that the inhibitory state of each zone stores information about the timing of the most recent local volley; thus, the drift in volley timing due to noise can be partially corrected as the excitatory pulse reaches each zone. In other words, the information about the timing of the previous volley delivered by E-to-E connections and the information about the timing of the most recent local volley delivered by I-to-E connections are both incorporated to determine the timing of each spike volley.Our model is closely related to the mechanism of “communication through resonance” developed by Hahn et al. . In theiIt is important to note the relationship between our model and the ideas discussed by Long et al. in . They shRA cells during zebra finch song [It could be argued that a chain of excitatory connections with periodic spatial recurrence is biophysically implausible. However, our model only requires that excitatory activity pass through inhibitory zones sequentially and return to them regularly; preliminary simulations suggest that such a pattern of activity may be achievable on a random excitatory network grouped into zones with localized inhibitory feedback. As an excitatory pulse propagates through the network, it is followed by a wave of local inhibition. This inhibition prevents excitation from returning to a zone until it has decayed sufficiently. Once it has decayed, random percolation ensures that activity does return. The result is a pulse that passes through the zones in an order determined by connectivity and initial levels of inhibition, and that meets the decaying inhibition from its previous pass as it reaches each zone. This pulse may activate different cells on each pass, generating a sequence significantly longer than a single pass through the network. The extraneous excitatory connections in such a random network would trigger EPSCs in some cells while they remained under strong inhibition, potentially explaining the observation of multiple stereotyped depolarizations in HVCnch song . FurtherFor this mechanism to function, excitatory activity returning to a region of HVC must arrive during the decaying slope of the inhibition, and must therefore circulate through the inhibitory zones on a time scale matching the decay of inhibition. In our model, this is achieved through manual tuning. However, a learning process in HVC like the one described above might help to match these timescales by ensuring that excitatory activity returns to a zone as soon as inhibition decays sufficiently to permit it. Alternatively, the timescale of recurrence may relate to the cortical-thalamic loop cycle time, which does appear to match the time-constant of inhibitory decay . In thisOur model also may throw a new light on certain dynamics in the mammalian brain. Two brain regions in which precisely-timed sequential activity is thought to be essential are the motor cortex  and hippS1 FigI(t) that crosses zero at time T = 0. Simulations are performed varying the steepness I′(T) of the current ramp, its beginning and ending height, and the initial QIF voltage V0 within the approximate range relevant to QIF neurons in our simulation. The first passage time distribution of the neuron changes with I′(T); however, within the regime relevant to the model presented here, first passage time distribution is insensitive to the initial voltage V0 and to the starting and ending point of the current ramp. Intuitively, this is the case because these neurons lack long time scale terms, so in noisy conditions they have very limited memory of recent state and input history. Below, the mean of the distribution of first passage times is plotted as conditions are varied. Shading indicates standard deviation. Above, depolarizing ramps are plotted for several values of each parameter. A, The initial voltage of the neuron is varied. Unless the initial voltage is very close to threshold, this does not significantly affect the first passage time distribution. B, The depolarizing ramp is shifted diagonally such that the initial and final drive vary but the depolarizing ramp crosses threshold at the same rate and time. Unless the initial drive is close to threshold or the final drive does not cross threshold, this does not significantly affect the first passage time distribution. C, The rate of depolarization is varied. Increasing the steepness of the current ramp slightly decreases the mean first passage time and tightens the distribution. D, The standard deviation σ of the first passage time is plotted as a function of depolarization rate I′(T). Note that σ decreases with increasing I′(T).Parameters for the QIF neuron are those chosen for the excitatory neurons in the model see . The QIF(TIFF)Click here for additional data file.S2 FigData from . Trials (TIFF)Click here for additional data file.S1 Textbmin.This text contains a derivation of (PDF)Click here for additional data file.