Septins are guanine nucleotide-binding proteins that polymerize into filamentous and higher-order structures. Cdc42 and its effector Gic1 are involved in septin recruitment, ring formation and dissociation. The regulatory mechanisms behind these processes are not well understood. Here, we have used electron microscopy and cryo electron tomography to elucidate the structural basis of the Gic1-septin and Gic1-Cdc42-septin interaction. We show that Gic1 acts as a scaffolding protein for septin filaments forming long and flexible filament cables. Cdc42 in its GTP-form binds to Gic1, which ultimately leads to the dissociation of Gic1 from the filament cables. Surprisingly, Cdc42-GDP is not inactive, but in the absence of Gic1 directly interacts with septin filaments resulting in their disassembly. We suggest that this unanticipated dual function of Cdc42 is crucial for the cell cycle. Based on our results we propose a novel regulatory mechanism for septin filament formation and dissociation.DOI:http://dx.doi.org/10.7554/eLife.01085.001 Septins are proteins that provide structural support for cells as they divide. Yeast cells are known to have seven types of septins, which have been widely studied, and 13 different septins have been identified in human cells, although they all seem similar to those found in yeast. Mutations in the genes that carry the genetic code for septins lead to a range of debilitating conditions in humans, including neurodegenerative diseases and male infertility.An enzyme called Cdc42 is thought to have a key role in the formation of ring-like structures by septins before a cell divides, and in the subsequent dismantling of these rings after the cell has divided. A pair of proteins, called Gic1 and Gic2, is known to be critical for the formation of the septin rings, but the details of the interactions between these two proteins, Cdc42 and the septins are sketchy.Now Sadian et al. have used two imaging approaches—electron microscopy and cryo-electron tomography—to scrutinise the role of Gic1 in greater detail in yeast cells. Gic1 interacts with specific subunits within adjacent septins, and these interactions have the effect of crosslinking the septins and stabilizing them in long filaments. However, high concentrations of the enzyme Cdc42 block the interaction between the Gic1 proteins and the subunits, causing the filaments to be dismantled. A future challenge will be to elucidate the interaction of these proteins in molecular detail using other techniques, in particular X-ray crystallography.DOI:http://dx.doi.org/10.7554/eLife.01085.002 Septins are ubiquitous guanine nucleotide-binding proteins that have been implicated in many cellular processes such as cytokinesis, spindle positioning, morphogenesis, and exocytosis, and their mutation or overexpression is associated with neoplasia, neurodegenerative diseases and male infertility .S. cerevisiae, where they form filaments of variable size and combinations. Whereas the human genome encodes thirteen septins, C. elegans has only two and plants are devoid of septin genes  are found at the bud neck , where tin genes . Despitein genes , 2009. SThe basic structural unit of the yeast septin complex is an octamer, composed of four subunits, namely Cdc10, Cdc3, Cdc12 and Cdc11, arranged into two tetramers with two-fold rotational symmetry .Cdc42 has been identified as a central regulator of septin ring assembly and disassembly during different stages of the cell cycle . MutatioAmong the essential effectors of Cdc42 in yeast are the two structurally homologous proteins Gic1 and Gic2, which are functional homologues of the human Borg protein . It has In this study, we have used electron microscopy and cryo electron tomography (cryo-ET) to describe the structural basis for the direct interaction of Gic1 and Cdc42 with septin filaments. Gic1 interacts with Cdc10 subunits of adjacent septin filaments and cross-links them. Because of this scaffolding, septin filaments are stabilized and form long railroad-like ordered filament cables. Cdc42-GTP directly binds to Gic1 and at higher concentrations inhibits the Gic1 interaction with Cdc10, resulting in the dissociation of the Gic1-septin complex. In its GDP-state, however, in absence of Gic1 Cdc42 interacts directly with Cdc10 and thereby mechanically disassembles septin filaments. Gic1 and Cdc42-GDP therefore compete for the same septin subunit. Finally, based on our results we propose a novel regulatory mechanism for septin ring formation and dissociation involving Cdc42 and Gic1.EGFP-labeled septins without Gic1  form relatively short and straight filaments . InteresTo determine which septin subunit interacts with Gic1, we labeled septin-Gic1 complexes with antibodies against Cdc11 and observed that it sits exactly in the middle of a septin filament between two Gic1 cross-bridges . Based oHowever, previous yeast two-hybrid, in vitro interaction and coimmunoprecipitation data indicated that Gic1 directly interacts with Cdc12 . TherefoAs expected from the results of antibody labeling, septin-Cdc10Δ, which formed short filaments, did not bind to Gic1 . Septin-In addition, yeast two-hybrid studies supported our in vitro data, showing that Gic1 only interacts with Cdc10 . NotablyBertin et al. reported that septin filaments are cross-linked by overlapping C-terminal extensions of Cdc3 and Cdc12 . DependiTo study the native three-dimensional structure of the filaments, we vitrified septin-Gic1 complexes and determined their structure using cryo electron tomography (cryo-ET) . We obseBoth in three-dimensional reconstructions and two-dimensional class averages, the density corresponding to Gic1 is poorly defined, suggesting a flexible structure of Gic1. Gic1, which based on its sequence has a molecular weight of 23 kDa (Gic1(104-314)) , elutes It was previously reported that Gic1 and its homologue Gic2 are effectors of Cdc42, which bind via their CRIB motif to the GTP-bound form of the Rho GTPase in cells . We madeSPA and cryo-ET of the Gic1-Cdc42-septin complex revealed that the cross-bridges were almost one and a half times larger in size, spanning not only two but four septin subunits, leaving only four septins unoccupied , Video 5Unexpectedly, an increase of the Cdc42-GppNHp concentration resulted in dissociation of the septin-Gic1-Cdc42 complex . SmallerTo determine whether Cdc42 interacts directly with septins in the absence of Gic1, we produced septin filaments in the presence of Cdc42-GppHNp and Cdc42-GDP, respectively. Although Cdc42 in its GTP-state bound to septin filaments, no regular pattern as in the case of Gic1 was observed, indicating non-specific interaction . Surpris2QA5) as a reference and mapped regions of conservation between the four structures on their surfaces. Examining the Cdc10-Cdc10 interface, which is an N/C interface, we found that the N-terminal region is the least conserved, and would therefore present an ideal site for specific Cdc42-GDP binding  do not polymerize at all and form tetramers or inside-out octamers . InteresOur data see , we thinBecause Cdc42-GDP binds to Cdc10 in septin complexes and prevents their polymerization, we propose that Cdc42-GDP rather than Gic1 recruits septin octamers (with Cdc10 at the caps) to the bud site . At the At later stages of the cell cycle the local Cdc42-GTP concentration increases at the bud neck, probably caused by an up-regulation of Cdc24 and/or identical spatial localization . As a regic1(310-942) (primers GIC1-N3: CCAAGGATCCATGTTCAAAAAAAAGGACCTGTTGTCGAGG and GIC1-C1: CCAAGTCGACGGTATTTCGAGGAGTACTAGTTTC) and gic1(670-942) (primers GIC1-N4: CCAAGGATCCGATTTGGAAATGACCTTGGAAGAC and GIC1-C1: CCAAGTCGACGGTATTTCGAGGAGTACTAGTTTC) were amplified by using yeast chromosomal DNA as a template and the Expand High Fidelity PCR system . The PCR products were digested with BamHI and SalI and fragments were introduced between the BamHI and SalI sites of pEG202 or pJG4-5 vectors. The same PCR products were also used in the construction of expression plasmids pFM812 (gic1(310-942) in pEGST with C-terminal His6-tag) or pFM562 (gic1(670-942) in pGEX4T-3). All plasmid constructs were confirmed by sequencing.Construction of yeast two-hybrid plasmids of septins were previously described . In ordeE. coli. Since the full-length protein aggregated during expression, we tested different constructs and could obtain sufficient amounts of stable non-aggregating protein only after deleting the N-terminal 103 amino acids (The yeast septin complex was expressed and purified as described earlier . In ordeno acids . Gic1(10E. coli strain BL21 (DE3) Rosetta . The cells were grown in TB medium, supplemented with ampicillin and chloramphenicol at 37°C and induced by addition of 0.2 mM IPTG at an optical density of OD600 = 0.6. After 8 hr at 28°C, cells were harvested by centrifugation, resuspended in isolation buffer IB1  and disrupted by using a microfluidizer . After high-speed centrifugation at 100000×g, the supernatant was incubated with 50 ml (Vt) Ni-NTA-Sepharose , washed with 300 ml buffer IB2  and with 100 ml of buffer IB3 . Gic1 was eluted with 300 mM imidazole in buffer IB3 and the GST-tag was cleaved using thrombin at 4°C. Then, the GST and the undigested fusion protein were removed by glutathione sepharose column chromatography . Gic1 was concentrated and further purified on a Superdex S200 column . Expression and purification of Cdc42(G12V) was performed as previously described (2 concentration) and 20 times excess of the desired nucleotide over the protein were added to Cdc42 and incubated at room temperature for 2 hr. Subsequently, the protein was concentrated using Amicon Ultra-4 Centrifugal Filters with a cut-off of 10 kDa and washed with the gel filtration buffer devoid of EDTA and nucleotide .For the bacterial expression of Gic1(104-314), the plasmid pFM812 was transformed into the escribed . Due its2, 50 mM Tris-HCl pH 7.5, 1 mM DTT) at a final concentration of 0.3 µM were dialyzed overnight at 4°C against a low-salt buffer . In the case of Gic1-septin complexes, septin oligomers  were mixed with Gic1  in a high-salt buffer and dialyzed as described above. For antibody decoration, 5 μl of polyclonal antibodies against Cdc11  and Cdc3  (1:100) were added to 20 μl of a sample containing the filaments or the septin octamers and incubated overnight at 4°C. For studies involving Cdc42, 0.1 μM of the septin octamer and 0.5 μM of Gic1 were used. Cdc42-GppNHp and Cdc42-GDP were used at the same concentration as Gic1 or at higher concentrations (as indicated in the figures) and incubated for different time intervals  column. The sample was run at 0.4 ml/min with a buffer containing 100 mM NaCl, 20 mM Tris-HCl pH 7.5, 1 mM DTT and 1 mM MgClTwo-hybrid studies were performed using the LexA-based system as described previously . The yea6-tag, the filaments can be adsorbed to a lipid monolayer containing Ni-NTA-lipids. To obtain single-stranded filaments, 30 µl of the samples were adsorbed to a lipid monolayer composed of 0.5 mg/ml of DOGS-NTA:DOPC at a molar ratio of 1:3 and incubated for 1 hr at 4°C. The monolayer was transferred to a carbon-coated grid and then negatively stained as described below.To obtain more details on the structure of septin-Gic1 complexes, we formed single railroad tracks by untangling the bundles on a lipid monolayer, which we then studied by EM and SPA. Since Cdc3 carries a His6-tags of the proteins are not responsible for the entangling of the filaments, we performed additional experiments. Both Gics and septins have been reported to interact strongly with PIP2  were scanned with a Heidelberg Tango drum scanner with 2419 dpi resolution yielding a pixel size of 4.5 Å on the specimen level. Alternatively, images were recorded with a 4k × 4k CMOS camera F-416 (TVIPS) at a calibrated magnification of 67,200×, resulting in a pixel size of 2.32 Å/pixel. Single particles were manually selected using boxer  and plunge-frozen in liquid ethane using a Cryoplunge3 (Gatan Inc.). Images were collected with a JEOL JEM 3200FSC TEM equipped with an 8k × 8k pixel TVIPS CMOS camera (F-816) at an acceleration voltage of 200 kV and a magnification of 85,470×. An in-column omega energy filter was used to improve image contrast by zero-loss filtering with a slit-width of 15 eV.−/Å2 per image. Images were then reduced by 4 × 4 pixel averaging resulting in a pixel size of 7.3 Å. Data were processed using the IMOD software package  into the density of septin filaments and placing of GROEL/GROES (PDBid: 1AON) into the density corresponding to Gic1-Cdc42-GppNHp cross-bridges in one of our reconstructions  were dialyzed overnight at 4°C against a low-salt buffer . In order to form the septin-Gic1 complexes, 1.5 µM of Gic1 was included during dialysis. Since Gic1 forms dimers and septin octamers contain two Cdc10 subunits, the molar ratio (Cdc10:Gic1) is 1.25:1. For antibody decoration, 5 μl of polyclonal antibodies against Cdc11 (Santa Cruz Biotechnology Inc.) and Cdc3  (diluted 1:100) were added to 20 μl of a sample containing either septin-Gic1 complex or the septin octamers  and incubated overnight at 4°C to allow efficient binding.For septin filament production, 0.3 µM of septin hetero-oligomers  mutants) in a high-salt buffer . Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent  by a Senior editor and 3 reviewers, one of whom is a member of our Board of Reviewing Editors.Thank you for sending your work entitled “The Role of Cdc42 and Gic1 in the Regulation of Septin Filament Formation and Dissociation” for consideration at The Reviewing editor and the other reviewers discussed their comments before we reached this decision, and the Reviewing editor has assembled the following comments to help you prepare a revised submission.In this in vitro study with recombinant proteins, the role of the guanine nucleotide binding protein Cdc42 and the regulator Gic1-septin filament formation and dissociation is elucidated. Using a combination of negative stain electron microscopy and cryo electron tomography, along with manipulations of the septin complex or the nucleotide state of Cdc42, a dual role of Cdc42 was discovered. In the GTP-state, Cdc42 leads to disassembly of the Gic1-septin complex, whereas in the GDP-state, Cdc42 leads to further disassembly of the septin complex in absence of Gic1. Moreover, the cryo EM reconstructions show that Gic1 can bind to multiple septin filaments in a heterogeneous fashion, accounting for flexibility of septin filaments during cell division and cytokinesis.Previous studies have linked Gic1/2 and Cdc42 nucleotide cycling to septin assembly in vivo but really how Cdc42 and its myriad of effectors actually lead to septin ring and collar formation remain mysterious. While Gic1/2 function has been genetically linked to septin organization and shown to physically associate with septin complexes, precisely what the Cdc42 effector does to regulate septins is unknown. Similarly, for Cdc42 itself, which is essential for septin assembly, it has not been determined if Cdc42 can bind septins and directly promotes filament assembly, filament bundling and/or if it simply indirectly recruits septins to the bud site.The electron micrographs are striking and represent some of the most detailed glimpses at purified septins presented to date. However, there are significant concerns about the quality and resolution of the EM tomograms that need to be addressed, along with the other concerns outlined below, before a decision can be made.Overall, the data indicate that 1) Gic1 can bundle septins through specific interactions at Cdc10, 2) Cdc42-GDP can bind septin octamers (through a surprisingly differently-ordered octamer than what has been shown for pure septin complex), 3) Cdc42-GTP changes how Gic1 associates with septin filaments and may itself associate with Gic1 bound to filaments, 4) high concentrations of Cdc42-GTP can lead to Gic1 dissociation for filaments and therefore ultimately destabilize the filaments. These are intriguing findings and do represent the first clean reconstitution of regulated septin assembly. Thus, the studies in this work should stimulate future studies to confirm that this is what is happening in vivo.Required revisions:1) The authors employ cryo-ET to view these fascinating assemblies 3D. However, lack of details precludes confidence in the displayed models. The authors need to detail the number of data sets collected and analyzed, post-processing and segmentation procedures, and should provide slices in X Y directions. Moreover, from reviewing the movies kindly provided the claim of isotropic resolution is inadequate. The resolution in Z direction is severely diminished, and this is the long axis of the bundles used. There is no way of telling what type of artifacts this geometry will introduce. If the authors want to prove that their conclusions are supported by the data, the authors will need to come up with some more convincing arguments. Maybe the authors can apply some simulations with idealized models or make use of the bundles with their long axis running in the other directions . As it stands there is some probability that the data is over interpreted, at least to some extent. Furthermore, because of the absence of averaging, the authors are looking at single motifs in a fairly noisy background, which is not helping in building confidence for their conclusions.2) The bundles of septin-Gic complexes were “untangled” by adsorbing them to a lipid monolayer containing NTA-lipids that bind to His6-tags attached to the Cdc3 septin molecule. Do the His-tags themselves cause some aggregation in this system, i.e., could that be the origin of the entangling of the filaments? In other words, were EM studies attempted with a different method to tether them to the surface?3) Please provide the control polymerization done in absence of fluorophore to establish the lack of interference (artifacts) induced by the addition of the EGFP-tag.4) What is the estimated resolution of the cryo-EM tomograms in xy and z, respectively ?5) What is the concentration of Cdc42-GppNHp in 6) The Gic components in the septin-Gic complexes appear rather heterogeneous. Do they consist of multiple Gic molecules or is Gic thought to be a flexible multi-domain protein?7) 8) 9) The interpretation of 10) 11) It is perplexing that filaments breaking at Cdc10 interface in presence of excess Cdc42. It would be interesting in seeing this result validated in some other manner.12) For easy reference please keep the color coding of Cdc3-EGFP, Cdc10, Cdc11 and Cdc12 consistent with the one published in 13) In eLife. Your revised article has been evaluated by a Senior editor, a member of the Board of Reviewing Editors (Axel Brunger), and two reviewers. We thank the authors for addressing many of the concerns raised by the reviewers and the Reviewing editor. The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below.Thank you for resubmitting your work entitled “The Role of Cdc42 and Gic1 in the Regulation of Septin Filament Formation and Dissociation” for further consideration at There are remaining significant concerns about the quality and reliability of the cryo-EM tomography results (see the comments by Reviewer 3 below). The reviewers and editors had considerable discussions about these concerns. They recognize that main conclusion that is drawn from the tomograms is that Gic1 cross-bridges more than two filaments, a result that could not be drawn from the negative stain EM images alone. The potential artifacts that are caused by the missing wedge in the EM data could have affected this particular conclusion, especially the connections between the filaments, as the authors also showed in their simulations.Ideally, the authors should revisit their existing EM tomograms at the orthogonal orientation to show that these connections are independent of the geometry (see Reviewer 3 comments). The authors  for this geometrically challenging system, the authors should have generated tomo-series in both orthogonal orientations to provide dual axis tomograms. Such data scheme would allow assessing the extent of the missing wedge and isotropic distortions for the system and thus provide measurable values to the confidence to the described conclusions.Furthermore it is somewhat concerning that the whole analysis is based on five reconstructions, 2 of septin-Gic1 and 3 of septin-Gic-Cdc42-GppNHp complexes. These numbers are on the lower side to draw robust conclusions, specifically as thousand of such assemblies were viewed.In summary, the reliability of the features in the reconstructions is questionable and the presentation of the data is misleading by implying that artifacts caused by the missing wedge would be somehow overcome by using a specific geometry. 1) The authors employ cryo-ET to view these fascinating assemblies 3D. However, lack of details precludes confidence in the displayed models. The authors need to detail the number of data sets collected and analyzed, post-processing and segmentation procedures, and should provide slices in XY directions.We admit that the description of our approach was not completely adequate, and apologize for this. We now provide more technical details in Materials and methods.We also provide slices and the corresponding segmentations in XY and Z direction and also included a direct comparison between raw and processed subtomograms in an additional figure , showingMoreover, from reviewing the movies kindly provided the claim of isotropic resolution is inadequate. The resolution in Z direction is severely diminished, and this is the long axis of the bundles used. There is no way of telling what type of artifacts this geometry will introduce. If the authors want to prove that their conclusions are supported by the data, the authors will need to come up with some more convincing arguments. Maybe the authors can apply some simulations with idealized models or make use of the bundles with their long axis running in the other directions . As it stands there is some probability that the data is over interpreted, at least to some extent. Furthermore, because of the absence of averaging, the authors are looking at single motifs in a fairly noisy background, which is not helping in building confidence for their conclusions.To obtain an optimal coverage of the complexes during a single-tilt tomographic image acquisition, the long axis of the complexes had to run either parallel to the tilt axis or parallel to the beam axis of the microscope. In the first case, the complexes were strongly affected by the missing wedge. The filaments appeared stretched and merged partially with each other and therefore their tracing was difficult. On the other hand, in tomograms with complexes running parallel to the beam, the septin filaments were clearly defined, all filaments around Gic1 had the same diameter and their tracing was straightforward. Furthermore, the densities corresponding to Gic1 and Gic1/Cdc42, respectively were fully comparable respective their overall shape and size to tomograms with complexes running in perpendicular directions, at least at the resolution level of 40-50 Å. Thus, tomograms of complexes running in the z direction provided the best possible 3D reconstructions of these complexes. We added two additional Videos  showing However, we are aware that these tomograms are still affected by the missing wedge along the z direction, as pointed out by the reviewers. In order to show to what extent this results in structural artifacts, we performed tomography-simulations using an idealized railroad-like structure model, as suggested. These simulations are now included in In the case of the model running with its long axis parallel to the beam at 0˚, the filaments do not show prominent missing wedge artifacts at a resolution of 45 Å and are fully comparable to the filaments of the original model. Only the density of GROEL/GROES (simulating Gic1-Cdc42)  The bundles of septin-Gic complexes were “untangled” by adsorbing them to a lipid monolayer containing NTA-lipids that bind to His6-tags attached to the Cdc3 septin molecule. Do the His-tags themselves cause some aggregation in this system, i.e., could that be the origin of the entangling of the filaments? In other words, were EM studies attempted with a different method to tether them to the surface? Note to authors: the response to our query along with the PIP2 control should be included in the revised paper; no additional experiments are needed.In a classical EM grid preparation, samples are incubated on carbon coated copper grids to which they absorb non-specifically. In the case of filaments that tend to bundle, the whole grid is often covered with protein making the analysis of single filaments difficult and tedious. Septin filaments only interact with lipid monolayers if the monolayers contain special lipids. His-tagged septin filaments can be immobilized on lipid monolayers with Ni-NTA lipids and by varying the concentration of Ni-NTA lipids the concentration of septin filaments on the grid can be conveniently adjusted. This facilitates the sample preparation and is an established method in electron microscopy .However, in order to prove that the His-tags of the proteins are not responsible for the entangling of the filaments, we performed additional experiments. Both Gics and septins have been reported to interact strongly with PIP2 . We therAnother good argument against the hypothesis of a His-tag-induced interaction is that we also observed the “entangling” of septin filaments when we studied unmodified wildtype septins purified from yeast . The bunIn our study, we showed that His-tagged Gic1 interacts with the septin Cdc10 . The HisFinally, the His-tags do not aggregate homogeneous Gic1  or septiIn summary, we can exclude artifacts induced by the His-tags.3) Please provide the control polymerization done in absence of fluorophore to establish the lack of interference (artifacts) induced by the addition of the EGFP-tag.The only experiments we have done in the presence of a fluorophore are shown in We also performed experiments with EGFP-tagged septins see , but did4) What is the estimated resolution of the cryo-EM tomograms in xy and z, respectively ?Despite much progress in electron tomography, quantitative assessment of resolution in single tomograms remains a problematic issue. A resolution estimate is given for only 25 of the 60 tomograms deposited in the EMDB. For 7 of these 25 tomograms, although a value is given, it is not described how the authors determined it. For 5 tomograms, the resolution was estimated by visual inspection regarding certain known features in the tomograms. For 7 tomograms, the resolution was estimated by the first zero-crossing of the CTF in the 0˚ image . For the remaining specimens, the resolution was determined by electron diffraction . A cross validation-based criterion exists for electron tomography , but because of many problems it extremely underestimates the resolution of the tomograms and is therefore not used by the tomography community.Therefore, due to the absence of a standard method, we avoid estimating the resolution of our tomograms. However, segmentation of our tomograms was straightforward after filtering down the raw tomograms to 30 Å. The first zero-crossing in the CTF in the 0˚ images of the various tomograms is at about 35-45 Å. Moreover, a visual comparison, between the densities of septin filaments in our tomograms and down-filtered crystal structures of human septin see also , suggest5) What is the concentration of Cdc42-GppNHp inAs described in the Materials and methods, Cdc42-GppNHp was added at equal concentrations as Gic1 for filament preparation, i.e., 0.5 µM and at 10x higher concentrations, i.e. 5 µM. To prevent any confusion we included the values now in the legend to Taken into account that each yeast cell contains around 1000 copies of septin octamers and Gic1 , the estimated concentration of septins or Gic1 in a yeast cell is around 0.05 µM. However, the local concentration of Cdc42 and Gic1 in yeast (for example at the budding neck) can be much higher . We ther6) The Gic components in the septin-Gic complexes appear rather heterogeneous. Do they consist of multiple Gic molecules or is Gic thought to be a flexible multi-domain protein?Gic1, which based on its sequence has a molecular weight of 23 kDa (Gic1(104-314)), elutes at about 49 kDa from a gel filtration column corresponding roughly to a dimer . In a ty7): The fluorescence in B looks just aggregated rather than bundled: these images raise some concern about what the relevance is of filament cables to normal septin assemblies. There is no scale bar annotation for panels C-F.To get a strong signal in the light microscope high concentrations of septin and septin-Gic1 filaments were used. In addition, the images were taken with an epifluorescence microscope not with a confocal microscope. That is why the overlapping septin filaments appear aggregated. However, the extended EM study clearly shows that we observe filament cables and bundles, but no aggregates. The scale bar annotations are included in the revised manuscript.8): There are no scale bar annotations. There is only one spot along the fiber that is Cdc11 labeled. Please mention how many particles were used for the averaging in. This is an important potential issue because previous work by Iwase et al. found Gic specifically complexing with Cdc12 not Cdc10.The scale bar annotations are included in the revised manuscript.As explained in the legend the arrow in As stated in the Material and methods, we used 199 particles that had clearly antibodies bound for this analysis. Each class average contained 15 single particles. We state that now in the revised manuscript.However, the number of single particles in the class average is not an important potential issue. Because of the work by Iwase et al. that indicated that Gic would bind to Cdc12, we did three independent studies to prove that Gic1 binds to Cdc10. First, we did the antibody labeling mentioned above. Second, we performed septin-Gic1 complex formation with septin-Cdc10Δ complexes that showed that Gic1 does not bind to septin-Cdc10Δ filaments although they contain Cdc12 . Third, 9) The interpretation ofthat the bridges get bulkier with Cdc42 added is that Cdc42 is part of enlarged bridging structure with Gic, but this could also be Gic1 oligomerization – without further experiments this can't be excluded.In 10): How does one know that band from gel filtration is Cdc42-GDP and not a contaminant from bacteria? Could a Western blot also be included?E. coli and purified by affinity chromatography to high purity. We prepared septin filaments, added Cdc42-GDP and incubated the mixture overnight prior to gel filtration.The experiment represented in In order to prove the purity of our proteins, we added SDS-PAGE lanes of the purified proteins to 11) It is perplexing that filaments breaking at Cdc10 interface in presence of excess Cdc42. It would be interesting in seeing this result validated in some other manner.In an additional experiment, we identified the Cdc42 binding site on Cdc10 validating our previous results. The following passage, including figures, has been added to the revised manuscript:“To identify the Cdc42 binding site on Cdc10, we calculated homology models of Cdc3, Cdc10, Cdc11 and Cdc12 using the SEPT2 structure (PDB 2QA5) as a reference and mapped regions of conservation between the four structures on their surfaces…”12) For easy reference please keep the color coding of Cdc3-EGFP, Cdc10, Cdc11 and Cdc12 consistent with the one published inWe changed the color coding in all figures accordingly.13) In, cross-bridges between pairs of filaments were observed emanating from Cdc12 and Cdc3, suggested to be their CTEs. Here, Sadian et al. only observe cross bridges if Gic or Cdc42 are added (through Cd10). The authors need to discuss the underlying source of the conflicting results.Looking at high concentrations of septin filaments we see the same thin cross-bridges that were described by We added a passage discussing this issue in the revised manuscript.There are remaining significant concerns about the quality and reliability of the cryo-EM tomography results (see the comments by Reviewer 3 below). The reviewers and editors had considerable discussions about these concerns. They recognize that main conclusion that is drawn from the tomograms is that Gic1 cross-bridges more than two filaments, a result that could not be drawn from the negative stain EM images alone. The potential artifacts that are caused by the missing wedge in the EM data could have affected this particular conclusion, especially the connections between the filaments, as the authors also showed in their simulations.Ideally, the authors should revisit their existing EM tomograms at the orthogonal orientation to show that these connections are independent of the geometry (see Reviewer 3 comments). The authors (using the geometry infor example) showed that there are clear extra crosslinks visible in tomograms.We revisited our EM tomogram at the orthogonal orientation and searched for filaments running parallel to the tilt axis, exactly as simulated in However, we would be prepared to accept the paper in essentially its current form if the authors would clearly point out the limitations of their current tomography study . The authors need to make a convincing case that the main conclusion drawn from the tomograms (more than two filaments binding to Gic1) is probably not affected by these concerns. Moreover, the authors must clearly state in the main text, the figure captions, and the conclusions that the images themselves may have gross errors.We hope that our additional reconstructions and our answers to the reviewer’s comments (see below) are convincing. Additionally we included some sentences that explain the limits of cryo-ET, such as missing wedge artifacts, in the revised manuscript.Comments from Reviewer 3:The authors have now given a much clearer picture of the tomography data and processing. Unfortunately, much of what was laid out only confirmed the reviewer's initial concerns. It is not the quality of the reconstruction that improves by changing the relationship between beam direction and tilt axis. The data in the missing wedge is missing, still. The artifacts are just along a different direction. The illusion of “improvement” is actually dangerous because it gives a false sense of quality for the reconstruction.This reviewer is correct in stating that the missing wedge is always there , independent of the beam direction and tilt axis. We did not claim that there are no missing wedge artifacts. But dependent on the orientation of the complexes during tomography these artifacts have different effects on the overall computed structures of the complexes.If the symmetry or pseudo-symmetry axis of an object is running parallel to the tilt axis of the microscope, the overall tomographic coverage of the structure improves. This is a fact that all EM users take seriously into account during the recording of single particles tomograms, especially when averaging is not possible.http://bio3d.colorado.edu/SerialEM/index.html), Strategies for Cryoelectron Tomography: “There is essentially no dual-axis capability due to the low dose requirements. So, we are left with single-axis reconstructions. If the sample allows you to, taking advantage of sample orientation to the tilt-axis can become very important. The best resolution is parallel to the tilt-axis.”From the home page of SerialEM , this relationship will not change.If there are any thin connections between the filaments, it is very likely that they will not appear in the reconstruction with the chosen geometry.As described above we revisited our EM tomogram at the orthogonal orientation and calculated a reconstruction of filaments running parallel to the tilt axis . As expeThe thin connections described in Bertin et al  are expeThe resolution of our reconstructions is 40-60 Å at best . It is therefore expected that these structures are not resolved in our tomograms. Even if the thin connections were visible, their segmentation would be highly ambiguous, independent of the chosen geometry. This issue is pointed out in the revised manuscript more clearly.The modeling of the cross-links as featureless barrels is not helpful to convince the reviewer.We chose GROEL/GROES as a model because it has similar dimensions to Gic1 cross-bridges and has been extensively studied by electron microscopy.The question is what would happen to finer features that may be attached to these barrels or emanate from/connect between the filaments.As described above, finer features will not be resolved at a resolution of 40-60 Å. We have used electron tomography to study these complicated structures, not X-ray crystallography. We therefore restrict our description and conclusion to gross features. We agree with the reviewer that this would be worth analyzing in future studies, but with other techniques, in particular X-ray crystallography.In trying to get a quantitative assessment of the assembly features (filaments and linkers) for this geometrically challenging system, the authors should have generated tomo-series in both orthogonal orientations to provide dual axis tomograms. Such data scheme would allow assessing the extent of the missing wedge and isotropic distortions for the system and thus provide measurable values to the confidence to the described conclusions.Although dual axis tomography theoretically improves the quality of tomograms, it harbors many technical problems and has therefore not been routinely used by the EM community. Most electron microscopes, including ours, are not equipped with a dual axis tomography holder. Therefore one has to remove the grid from the microscope after recording the first tomogram, turn it by 90˚ and enter it again. After finding the right position the second tomogram is recorded. Besides many obvious technical difficulties such as ice contamination when removing the grid and problems with alignment, the electron dose of such tomograms is doubled, resulting in decreased resolution. Any potential improvement of our tomograms would therefore be questionable. Instead we revisited our EM tomograms at the orthogonal orientation and searched for filaments running parallel to the tilt axis. This showed that the overall structure of the septin-Gic1 complexes is independent of its orientation in the tomogram.http://bio3d.colorado.edu/SerialEM/index.html), Strategies for Cryoelectron Tomography: “There is essentially no dual-axis capability due to the low dose requirements. So, we are left with single-axis reconstructions.”From the home page of SerialEM , Dual-axis tomography: “Tilting around two tilt axes perpendicular to each other reduces missing wedge–induced distortions and improves information content. However, dual-axis tomography has rarely been used in cryo-ET due to the need to acquire an increased number of projections and difficulties with alignment....”Furthermore it is somewhat concerning that the whole analysis is based on five reconstructions, 2 of septin-Gic1 and 3 of septin-Gic-Cdc42-GppNHp complexes. These numbers are on the lower side to draw robust conclusions, specifically as thousand of such assemblies were viewed.We could provide hundreds of reconstructions with complexes running in random directions relative to the tilt axis. However, as described above and demonstrated by simulations, only reconstructions with filaments running parallel to the tilt axis or to the beam result in analyzable reconstructions. To find filaments in this orientation is very challenging. We are convinced that the number of reconstructions provided is sufficient to support our conclusions.In summary, the reliability of the features in the reconstructions is questionable and the presentation of the data is misleading by implying that artifacts caused by the missing wedge would be somehow overcome by using a specific geometry.We clearly show that we do not overcome the missing wedge artifacts. This is not possible in a single tomogram experiment. However, we show that the orientation of the longitudinal complexes during tomography definitely has an impact on the resolution and overall quality of the reconstructions. We rephrased this passage in the revised manuscript to prevent any misunderstandings.Due to the overall methodical and resolution limitations our paper focuses exclusively on gross features of the complex. We can clearly determine the number of filaments and we can even fit the crystal structure of human septin into our reconstructions to verify that the overall dimensions are correct. Although we cannot exclude the possibility that the density corresponding to Gic1 appears more stretched due to the missing wedge artifacts, we can state that Gic1 cross-bridges several septin filaments. These are our conclusions from the cryo-ET data.We are convinced that we have carefully interpreted, and not over-interpreted, the data presented and have avoided any overstatement. Therefore, we are confident that the conclusions we draw from our data, namely that Gic1 scaffolds more than two septin filaments, are robust and justified.


We have recently demonstrated that exposure to a suboptimal diet during early development leads to abnormal epigenetic regulation of a promoter-enhancer interaction at the gene encoding HNF-4α, a key transcription factor required for pancreatic β-cell differentiation and glucose homeostasis. In addition, our studies revealed that the suboptimal maternal diet amplifies the age-associated epigenetic silencing of this locus. In this research perspective we discuss these novel findings in the context of the growing list of epigenetic mechanisms by which the environment can affect gene activity and emphasize their implications for the understanding of the mechanistic basis of the development of type 2 diabetes with age. However, there is growing evidence to suggest that diet during pregnancy and lactation may be particularly important as not only does it influence the health of the mother, it may have a permanent effect on the health of her children and even her grandchildren. The concept that environmental factors, such as nutrition during early development, influence both our health span and lifespan has been termed the developmental origins of health and disease hypothesis . Focus o obesity .in utero during periods of famine have shown direct relationships between severe maternal nutrient deficiency and increased risk of T2D in the offspring [Observational studies linking patterns of early growth with long-term health don't provide proof that suboptimal nutrition mediates these relationships. However studies in human cohorts and in animal models have provided strong evidence that environmental factors, including nutrition, play an important role. The strongest evidence from human studies supporting the role of the environment in mediating the relationships between birth weight and long-term health has come from the study of monozygotic  twins. These studies revealed that in monozygotic twin pairs discordant for T2D, the diabetic twin has a lower birth weight than their non-diabetic co-twin ,7 Assessffspring ,9. The iffspring  and subsffspring . Animal Most conditions associated with patterns of early growth and nutrition are diseases associated with aging. Therefore, perhaps not too surprisingly, the small size at birth has been associated with increased mortality in humans. In a large Finnish study a low birth weight was associated with increased mortality at all ages in women and with premature death (< age 55) in men . StudiesThe islets of Langerhans in the endocrine pancreas, the only cells in the body that can produce insulin, appear to be particular vulnerable to the detrimental effects of maternal diet on their aging trajectory. This is consistent with the early environment having a major influence on regulation of glucose homeostasis and consequently diabetes risk. Some of the earliest effects on telomere shortening resulting from maternal protein restriction are observed in pancreatic islets and this is accompanied by premature induction of p16, one of the most robust biomarkers of aging . In addiThe molecular bases of the interaction between maternal diet, aging and the risk for T2D are currently poorly understood. However, the hypothesis that this interaction could be mediated by epigenetic mechanisms offers an attractive explanation for the link between nutrition, regulation of gene expression, and the risk for disease Figure .Gene transcription is the result of the interactions between transcription factors and chromatin at a number of genomic regulatory elements including promoters, enhancers, insulators and silencers. Accessibility to these sites is mediated by epigenetic modifications of histones and DNA. It is widely accepted, for example, that upon histone acetylation, genes become actively transcribed, whereas deacetylation leads to repression. Modifications of the DNA itself, such as methylation and most recently hydroxymethylation, are also important indicators of the transcriptional regulatory activity of many genomic loci.Epigenetic marks are responsive to environmental and developmental cues, as there is a need to modify the transcriptional outputs of genes throughout the life of an organism ,18. It iDeregulation of epigenetic processes with age is a common feature in mammals . WidesprHnf4a transcription at a young age  that persisted throughout life when compared to normally fed controls. LP offspring develop T2D at old age (17M), whereas normally fed controls rarely do so. The authors showed that the reduced Hnf4a expression observed at a young age was made permanent throughout life and aging, via the stable maintenance of repressive epigenetic marks. Remarkably, the early-diet epigenetic silencing effects were targeted to a regulatory element distal to the active promoter - an enhancer element. The abnormal epigenetic marking weakened the physical interaction with the upstream promoter and resulted in reduced expression of the gene. Interestingly, the accumulation of the repressive marks were more pronounced in aged rats that were exposed to a sub-optimal diet in early life than those exposed to a normal diet, which is suggestive of an interaction between early-nutrition and aging effects at this locus. Down-regulation of Hnf4a has been found in T2D patients [Hnf4a resulting from de-regulation of an epigenetically controlled enhancer-promoter interaction is thus likely to contribute to the T2D effects in this model. This work is relevant to human T2D risk, as the epigenetic mechanisms that regulate Hnf4a in rats are highly conserved in human islets [A recent study in rats sheds novel insights on the epigenetic mechanisms by which environmental exposures can increase the risk of T2D . Sandovipatients  and genepatients . The susn islets .Several HNF-4α protein variants can arise from mRNAs transcribed from two promoters, proximal P1 and distal P2, however, in islets only the P2 promoter is active. An enhancer region is located upstream of the P1 promoter and downstream of the P2 promoter Figure . This shet al. provides novel insights into the epigenetic deregulation during aging and the associated decline in function of the endocrine pancreas. Hnf4a levels decline with age, an effect that was associated with recruitment of the Polycomb-mediated histone repressive mark H3K27me3. Repression by H3K27me3 across the P2 and enhancer regions was greater in magnitude in rats fed a sub-optimal LP maternal diet compared to controls. This finding raises several questions: does age-related H3K27me3 repression occur earlier in LP rats compared to controls, which would be indicative of premature epigenetic “aging” at this locus? Do H3K27me3 levels contribute to the age-associated increased risk for diabetes?  Is age-related Polycomb-mediated accumulation of H3K27me3 associated with repression of other key diabetes genes in islets?The work by Sandovici et al. there was only one published report analysing the effects of early life-events on epigenetic states during aging [Avp) gene enhancer at 6 weeks of age, with age-associated hypomethylation (at 1 year of age) occurring stochastically across the entire Avp locus [et al. similarly shows that early-life epigenetic changes are targeted towards important regulatory elements, while age-associated effects are widespread and likely stochastic. However, in contrast to the Avp study, the differential changes in epigenetic states at the Hnf4a locus in response to early-life events and aging seem to be mechanistically and functionally linked. Indeed, whilst the age-associated hypomethylation of the Avp had no effect on mRNA expression levels, Hnf4a repression by histone modifications with age resulted in lower levels of expression. Furthermore, the early-diet induced epigenetic programming effects at the enhancer were largely maintained during aging, and were even more pronounced for the Polycomb-dependent histone mark H3K27me3. Therefore, the aging process did not disrupt the long-lasting programming effects at this locus and may have instead amplified its effects.Prior to the work by Sandovici ng aging . In thisvp locus . The stuet al. showed that environmental stimuli could induce specific changes in epigenetic states at an enhancer region and provided insights into the mechanisms by which transcript levels were altered. By using the chromatin conformation capture (3C) technology the study identified a stable P2 promoter-enhancer interaction in islets that determines the establishment of a functional expression domain (Figure et al. proposed that the epigenetic control of the P2-enhancer interactions in islets underpins the sustained changes in Hnf4a expression levels, which influence in turn the risk for the age-associated T2D. It is tempting to speculate that this model could also provide a mechanistic understanding of how polymorphisms within the human Hnf4a locus may increase T2D risk, as the genetic sequence, in addition to the epigenotype, could modulate the strength of the promoter-enhancer interaction.The work by Sandovici  capture C technol capture C technol capture C technolet al. led to the proposal that altered epigenetic control of enhancer-promoter interactions are crucial for establishing long-lasting programming and aging effects. The catalogue of environmentally-induced epigenetic modifications that affect enhancers is still rather limited, including so far the Avp enhancer mentioned above [Ppara [Hnf4a [5-106, that are used to drive specific gene expression patterns in the estimated 200 cell types of the human body [The findings by Sandovici ed above , Ppara [e [Ppara  and now a [Hnf4a . Using ga [Hnf4a -29. One man body . Resultsman body . The effman body ,31 is a


The role of lateral prefrontal cortex (LPFC) in speech monitoring has not been delineated. Recent work suggests that medial frontal cortex (MFC) is involved in overt speech monitoring initiated before auditory feedback. This mechanism is reflected in an event-related potential (ERP), the error negativity (Ne), peaking within 100 ms after vocal-onset. Critically, in healthy individuals the Ne is sensitive to the accuracy of the response; it is larger for error than correct trials. By contrast, patients with LPFC damage are impaired in non-verbal monitoring tasks showing no amplitude difference between the Ne measured in correct vs. error trials. Interactions between the LPFC and the MFC are assumed to play a necessary role for normal action monitoring. We investigated whether the LPFC was involved in speech monitoring to the same extent as in non-linguistic actions by comparing performance and EEG activity in patients with LPFC damage and in aged-matched controls performing linguistic (Picture Naming) and non-linguistic (Simon) tasks. Controls did not produce enough errors to allow the comparison of the Ne or other ERP in error vs. correct trials. PFC patients had worse performance than controls in both tasks, but their Ne was larger for error than correct trials only in Naming. This task-dependent pattern can be explained by LPFC-dependent working-memory requirements present in non-linguistic tasks used to study action monitoring but absent in picture naming. This suggests that LPFC may not be necessary for speech monitoring as assessed by simple picture naming. In addition, bilateral temporal cortex activity starting before and peaking around vocal-onset was observed in LPFC and control groups in both tasks but was larger for error than correct trials only in Naming, suggesting the temporal cortex is associated with on-line monitoring of speech specifically when access to lexical representations is necessary. When speech production is monitored on-line, before it is produced, the process is referred to as the “inner loop” of speech monitoring. After speech has been produced, monitoring is referred to as the “outer loop” as it relies primarily on external auditory feedback  and positron emission tomography (PET) studies suggest temporal regions, and especially the posterior superior temporal gyrus (pSTG), but also medial frontal regions, including the anterior cingulate cortex (ACC) and the supplementary motor area (SMA), are associated with speech monitoring  investigations examining the “error negativity” (Ne) have reinforced the idea that speech monitoring relies partly on a monitoring system common to speech and other actions. The Ne is an event-related negative potential initially observed following the onset of erroneous responses in non-linguistic tasks  and moreIn sum, the proposed involvement of a domain-general monitoring system in inner speech monitoring is supported by modulation of the BOLD signal in the ACC in situations in which the constraints on speech monitoring are manipulated; the observation of the Ne in overt speech and; the observations that the Ne is modulated similarly by time-pressure, competition between representations or uncertainty of the response , in patiIn the language domain, production studies investigating interactions between brain regions subserving on-line speech monitoring are scarce. The limited temporal or spatial resolution of the available imaging techniques and the problem posed by articulation-related artifacts in EEG and MEG have contributed to the paucity of research in this area. Thus, whether or not the domain-general monitoring process involved in inner speech monitoring and indexed by the Ne is dependent on the LPFC has not been directly investigated.Patients with lesions to the LPFC have language production deficits characterized by impaired verbal fluency which varies depending on the specific area of PFC damage and the extent of the lesion . WhereasTo address this hypothesis we recorded EEG in a cohort of patients with lesions centered in the left or right PFC and in aged-matched controls as they performed a simple overt picture naming task and a verbal Simon task. The Simon task  involvesA total of 17 patients  with focal unilateral lateral frontal lesions  were recruited to participate in the study. All right frontal patients had no language impairment as diagnosed by neurological assessment. All left frontal patients were examined on at least two subtests of the Western Aphasia Battery WAB; , measuriThree left frontal patients  could not perform the experimental tasks adequately due to marked aphasia: they either did not understand the instructions properly or their error rate on the experimental tasks was over 40% . EEG could not be recorded in two other left PFC patients : one could not sit for the entire duration of the experiment and EEG recording had to be interrupted and the other had a sore spot on the scalp that bothered her. The data of these five left PFC patients were excluded from the analysis.Figure 1.The remaining six left PFC patients had a mean Spontaneous Speech score of 19/20 (SD = 0.63), reflecting overall good production abilities despite some articulation problems (one patient had a score of 18 reflecting a lack of detail in the picture description or in answering one of the questions). The mean Sequential Command score was of 76/80 . We note that four out of the five patients had a perfect score of 80, only one had a relatively low score of 59.5. This patient asked to be reminded of the Simon task rule regularly at the breaks but was nevertheless able to perform both tasks correctly. Thus the language production deficits of the left PFC group we kept for further analysis were overall mild in nature allowing the patients to perform the tasks adequately. Lesion overlapping of the 12 remaining patients is presented in t(21.90) < 1] were collected. Patients had on average 16.6 years of education (SD = 3.0) and controls had on average 16.7 years of education . However, the controls produced few errors . No clear Ne was observed in the controls due to poor signal-to-noise ratios and their EEG data for errors were not analyzed further, although we report their EEG data in correct trials. We note patients had on average 28 errors (SD = 16) left after artifact rejection in the Naming task and 23 (SD = 23) in the Simon task.The data of 12 controls  matched in age, gender, and education to the remaining 12 patients . They were all 525 × 250 pixels high and were presented in free viewing within a visual angle of 7°. A total of 252 pictures were used: 216 were the experimental items and 36 were used as practice trials. For purposes unrelated to the present study, the pictures were issued from six semantic categories , each member  was represented by six different items , and they were presented within semantically related vs. unrelated blocks in similar fashion as in The stimuli were line drawings of common objects or animals selected from a published collection  or constParticipants were tested in a sound-attenuated dimly lit environment. They were seated comfortably 148 cm from a computer screen on which the stimuli were displayed. The experiment was controlled by the Eprime 2.0 Professional software , which allows on-line recording of the participants’ verbal responses.A trial consisted of the following events: (1) a fixation point (“plus” sign presented at the center of the screen) for 500 ms; (2) a picture for 2000 ms (3) a blank screen for 2000 ms. The following trial started automatically. Participants performed two tasks in separate blocks: a picture naming task and a verbal Simon task. In the Naming task, participants were asked to name the picture by saying the name of the picture preceded by the possessive determiner “my” . In the Simon task, participants were asked to say “my right” or “my left” depending on the color of the picture while ignoring the side to which the picture was presented. Thus interference is greater for a picture presented on the left of the fixation cross when the response to be given is “my right” and vise-versa. The stimulus-response association rule  and the order in which the tasks were performed were counterbalanced across participants.The possessive determiner was added to reduce variability in vocal onsets and because we also recorded EMG activity of three facial articulators. Since the nature of the first phoneme influences the EMG activity pattern , we chosVocal-onsets were used as the response-onset measure. Each task was split into 4 blocks of 108 trials each, with two pauses equally spaced within each block. Participants performed all four blocks of one task before the four blocks of the other task. Altogether, the participant saw the same item four times corresponding to the four possible color/side configurations: green on the left, green on the right, purple on the right, and purple on the left. The type of configuration seen per task and per type of block was counterbalanced across participants.The participants were asked to give their response verbally as fast and as accurately as possible. Participants were informed that no correction was possible in the case of errors . ParticiThe EEG was recorded from 64 Ag/AgCl pre-amplified electrodes . The sampling rate was 1024 Hz . The vertical electro-oculogram (EOG) was recorded by means of two surface electrodes just above and below the left eye, respectively. The horizontal EOG was recorded with two electrodes positioned over the two outer canthi. The passive reference was placed over the left mastoid.The accuracy of the responses and the verbal reaction times were measured offline using the software CheckVocal . Trials After acquisition, the EEG data were filtered (high pass = 0.16 Hz) and resampled at 256 Hz. Vertical eye movements were corrected based on an independent component analysis as implemented in EEGLAB . SpeakinTM , was applied to each participant’s averages and on the grand average as in 2. A 30-Hz low-pass and 1-Hz high-pass filters were applied off-line on the EEG data.Following the BSS-CCA procedure, all other artifacts were rejected on the basis of a trial-by-trial visual inspection of monopolar recordings. The retained monopolar recordings were averaged and time-locked to vocal-onset. Laplacian transformation , as implemented in BrainAnalysert-tests or ANOVAs for comparison of more than two means. When unpaired t-tests were performed, a Welch correction for non-homogeneity of variance was applied.The analysis included the factor “accuracy” (correct or error) and “participants” as a random effect. The behavioral data were analyzed using Student’s t-tests) or Kruskal–Wallis rank sum test for comparison of more than two means because the measures were based on few error trials and the normality of the data could not be assumed. Following t-values, corresponding to the sum of the absolute values of the ranks of the least represented sign, and the associated p-values, and Kruskal–Wallis H-values and corresponding p-values. All statistical analysis were performed using R 2.15.2  = 4.53, p = 0.045] but was not significantly higher for patients than for controls . There was no main effect of lesion side in patients [F < 1] and only a marginal interaction between lesion side and task  in that left PFC patients had less trials rejected in the Simon task  than in the Naming task  but the right PFC patients did not .Overall, 3.26% (SD = 3.26%) of the trials were removed from further analysis due to no responses. This rejection rate was higher in the Naming task  than in the Simon task  and tended to be higher in the Naming than in the Simon task . There was no group by task interaction [F < 1]. There was no effect of lesion side in patients t[F < 1], nor any interaction of lesion side with task . Overall, participants self-corrected their responses despite instructions in only 0.8% of trials.The average error rate  was higher for patients  than for controls . For patients, the average RT was 816 ms (SD = 89 ms) in the Naming task, and 782 ms (SD = 109 ms) in the Simon task. For controls, the average RT was 798 ms (SD = 105 ms) in the Naming task and 740 ms (SD = 104 ms) in the Simon task. Patients were not significantly slower than controls [F < 1] and there was no effect of lesion side on average RTs [F < 1] nor any interaction between lesion side and task [F < 1]. Overall, two controls  and two patients  made less than five errors in one or both tasks. Their data were not included in the following analyses of RTs in errors and comparison between RTs in errors and correct trials leaving 10 controls, 5 right and 5 left PFC patients for these analysis (these groups still did not differ in terms of age or education: ts < 1). The average RT for errors for patients in the Naming task was 918 ms (SD = 133 ms) and it was 872 ms (SD = 105 ms) in the Simon task. The average RT for errors for controls in the Naming task was 867 ms (SD = 192 ms) and it was 825 ms (SD = 144 ms) in the Simon task. There was no difference between patients and controls on error RTs [F < 1] nor any main effect of task  or interaction between these factors [F < 1]. There was no effect of lesion side [F < 1] on error RTs. RTs were significantly longer in errors than in correct trials in patients and controls for both tasks , there was no interaction between lesion side and accuracy [F < 1].The average RT for correct trials was longer in the Naming than in the Simon task for both patients and controls . The latency of the preceding positivity was not different between errors and correct trials . Critically, the peak-to-peak amplitude between the Ne and the preceding positivity was larger for incorrect than correct trials . As can be seen on Figure 3 , this was true for all but one patient. We did not have a sufficient number of left vs. right patients to test for the effect of lesion side on the amplitude of the Ne. Interestingly, the only patient who did not have a larger Ne in errors vs. correct trials was the one with a large lesion including part of the left temporal lobe, roughly the superior anterior quadrant.Figure 4). Negative components in errors peaked on average 55 ms (SD = 88 ms) after vocal-onset at T7, 71 ms (SD = 68 ms) at TP8 and 125 ms (SD = 67 ms) at TP7. In correct trials, negative components peaked on average 17 ms (SD = 41 ms) after vocal onset at T7, 18 ms (SD = 47 ms) at TP8 and 63 ms (SD = 35 ms) at TP7. There was an effect of accuracy on the latencies at which these components reached their maximum , latencies were longer in errors than in correct trials. This effect was due to a significant difference in latencies at TP7 only . The slopes of the waveforms were significantly below zero for error trials  with a trend for correct trials . The peak-to-peak ]amplitudes were greater for error than correct trials . There was no significant activity at T8 for error trials  or correct trials  despite a positive slope observed on the grand averages. As can be seen on the topographies, the right-sided temporal activity was reduced compared to the left side in both correct and incorrect trials.We also report activity at left and right temporal recording sites  peaking around and after vocal-onset which was larger for error than correct trials  and was associated with a fronto-central local topography . The slopes of the waveforms were below zero on the 100-ms time-window preceding vocal onset for correct trials  but not for error trials . We note the number of error trials left after artifact rejection was not lower in the Simon task  than for the Naming task . Moreover, when the data of the three patients who had less than five error trials left after artifact rejection in the Simon task were also removed from the slope analysis of the error trials in the Naming task, there was still a reliable Ne apparent . Thus, the difference in patterns we observe in errors is not likely due to a lower signal-to-noise ratio in the Simon task. To be able to compare errors to correct trials in the Simon task, we used the same latency values in errors as in correct trials to measure the peak-to-peak amplitudes in errors. There was no significant difference in the peak-to-peak amplitudes thus measured between errors and correct trials . The interaction between task and accuracy on these peak-to-peak amplitudes was not significant .Figure 7). In errors, negative peaks of activity were reached 187 ms (SD = 64 ms) post-vocal onset at T7, 41 ms (SD = 51 ms) at TP8, and 18 ms (SD = 49 ms) at TP7. In correct trials, negative peaks of activity were reached at 172 ms (SD = 114 ms) post-vocal onset at T7, 26 ms (SD = 63 ms) at TP8, and 30 ms (SD = 72 ms) post-vocal onset at TP7. There was no effect of accuracy on these latencies . We note two peaks of activity are observed on grand averages at T7 in errors. We considered the highest peak of activity for the latency measures and peak-to-peak measures. The slopes of the waveforms were smaller than zero in errors  and correct trials at T7, TP8, and TP7 . Critically and in contrast with the Naming task, there was no difference in amplitude between errors and correct trials for these temporal activities in the Simon task . We note we also observed a positivity at a right temporal site (T8) peaking on average 99 ms after vocal onset (SD = 66 ms) for error trials  but not for correct trials where the slope of the waveform was not significantly different from zero .We also observed temporal activity peaking around vocal onset in the Simon task in PFC patients : on average 5 ms after vocal onset at T7 (SD = 35 ms), 20 ms before vocal onset at TP8 (SD = 32 ms), and 34 ms before vocal onset at TP7 (SD = 36 ms). The slopes of the waveforms were different from zero . Although the negativity peaking around vocal onset at TP8 appeared bigger than the negativity peaking at TP7, there was no statistical difference between the peak-to-peak amplitudes measured . We did note the presence of a component at CP6, just superior to TP8 that seemed absent at the contralateral site (CP5). We compared the peak-to-peak amplitudes measured for correct trials in patients to those measured in controls. Peak-to-peak amplitudes were marginally smaller in controls than in patients . We also note that the activity at TP7 did not persist after vocal onset as in patients, the cartographies at 50 ms after vocal onset did not show any activity over left or right temporal cortices.Simon task. Similarly to the Naming task, no reliable Ne was observed at fronto-central sites for the Simon task. We report activity at left and right temporal recording sites peaking around vocal-onset : at 51 ms (SD = 66 ms) after vocal-onset on average at T7, at 38 ms (SD = 69 ms) after vocal-onset at TP8, and at 2 ms (SD = 89 ms) before vocal onset at TP7. The slopes of the waveforms were inferior to zero . On the grand averages, a positivity can be seen at T8 but the slope of the waveform was not significantly different from zero on the 100 ms preceding vocal-onset . Although the right temporal activity at TP8 seemed larger than the left temporal activity at T7 and TP7, there was no effect of recording site on the peak-to-peak amplitude measured . Peak-to-peak amplitudes were not smaller in controls than in patients .In agreement with our hypothesis, we observed an amplitude difference between the Ne for error and correct trials in PFC patients in overt picture naming but not in the verbal Simon task. This suggests the domain-general monitoring process supported by MFC and reflected by the Ne is not as dependent on the LPFC when no arbitrary rule has to be maintained in working memory . The chaThough the LPFC, and especially the inferior part of the left PFC (BA44/45), has been associated with a range of language deficits, our results suggest that its involvement in speech monitoring as assessed by simple picture naming is not as critical as in other actions in which an arbitrary rule has to be maintained in working memory. Patients made more errors than controls overall, suggesting both tasks were harder for patients than for controls. However for patients, the Ne was larger in errors than in correct trials in Naming but not in the Simon task. This suggests that despite having more difficulty overall, the patients’ monitoring system was relatively preserved in the Naming task but not in the Simon task. In our study, the slope analysis failed to reveal a significant component in errors in the Simon task. However, the absence of an amplitude difference replicates the pattern of results reported in In our Simon task as in Simple picture naming does not require the participants to hold an abstract rule into working memory as the link between the stimulus and the response to be made  is subserved by lexical access to long term memory. The importance of the LPFC in holding an abstract rule or goal in working memory has been reported by numerous neuropsychological and neuroimaging studies  have to be articulated in the Simon task.The observation that temporal activity starts before vocal onset in both patients and controls supports a role in inner speech monitoring, before overt auditory feedback can be perceived as suggested in Bilateral temporal activity was also visible in correct trials in aged-matched controls although it was marginally smaller in the Naming task and had a slightly different time-course. Indeed, there was no more visible activity on the scalp cartographies over the left or right temporal cortices 50 ms after response onset. This leads to two possible interpretations. First, LPFC patients relied on the mechanism underlying this brain activity, linked to both inner and outer speech monitoring, more than aged-matched controls. This seems plausible as patients had more difficulty in performing the task than controls. An alternate interpretation may be that this mechanism was affected in the patients. Indeed, PFC patients may have difficulty in resolving competition at the level of lexical selection. As mentioned below, different regions of the left temporal cortex have been associated with lexical selection e.g., . It has The reason why the pattern of activity we report in older patients and controls is somewhat different than what was reported in young controls is also uncertain. This might again be due to the use of the possessive determiner in the present study and not in Although valuable information is gained from the fine temporal resolution available with EEG, its limited spatial resolution does not enable certainty as to which brain region(s) is/are generating the activity we report. The focal lateral scalp topography supports a generator in temporal cortices but we cannot be more specific on the basis of this study. The posterior STG has been associated with speech monitoring, and especially external speech monitoring based on fMRI studies manipulating auditory feedback e.g., . BecauseUsing computational simulations and neuropsychological data, these authors provided a detailed theoretical account in which a domain-general conflict-detection mechanism, assumed to be hosted in the medial frontal lobe, plays a central role in the on-line monitoring of speech production by interacting with the speech production system itself. Their model was able to successfully predict error detection patterns of 29 aphasic patients performing a simple picture-naming task . Although these authors do not deny the role of speech comprehension in speech monitoring, they suggest its role is limited to external feedback monitoring taking place after speech has actually been produced, as suggested by studies in which auditory feedback is either masked or distorted  of We also did not observe a clear Ne in correct trials in aged-matched controls in either task. No clear component was visible at FCz. The reason why aged-matched controls did not show a typical Ne in correct trials as reported in An additional limitation comes from the absence of difference in performance between left and right PFC patients. As mentioned in the introduction, damage to the left PFC has been associated to a range of language deficits, leading to the prediction that the left PFC patients would have more difficulty in performing the Naming task than the right PFC patients. This was however not the case. The number of patients in each group may have been too small for an effect of lesion side to emerge. Moreover, because of task requirements, the patients we kept for analysis had overall good language production and comprehension as assessed by standard neuropsychological testing which may have prevented observing differences between left and right PFC patients. Such a limitation may be hard to avoid in EEG studies of overt speech monitoring though possible differences between left and right PFC patients may be investigated using linguistic tasks involving manual responses.Taken together, our results shed new light on the network underlying on-line speech monitoring in simple overt picture naming. They reinforce the idea that a common node in the MFC is involved in speech and non-speech action monitoring manifested by the Ne potential. However, this domain-general monitoring system appears to be not as critically dependent on the LPFC in speech vs. other actions which involve arbitrary S-R mapping to be maintained in working memory. Moreover, in speech production, temporal regions are involved in monitoring not only through auditory feedback but also in on-line monitoring before speech is actually produced. This temporal involvement is particularly needed when lexical representations have to be accessed. We propose that a network of interacting brain regions involving medial frontal regions and temporal regions supports inner speech monitoring and that the role of the LPFC in action monitoring may be restricted to situations involving arbitrary stimulus-response associations to be maintained in working memory.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


PTPRC genetic locus, the present study was undertaken to test established RA susceptibility variants, including PTPRC, in the prediction of response to TNF blockade in a large cohort of patients from the UK.Several rheumatoid arthritis (RA) susceptibility variants map close to genes involved in the tumor necrosis factor (TNF) signaling pathway, prompting the investigation of RA susceptibility variants in studies of predictors of response to TNF blockade. Based on a previously reported association of RA with the DNA was extracted from the blood of 1,115 UK patients with RA who were receiving anti-TNF biologic therapy. Samples were analyzed for 29 single-nucleotide polymorphisms (SNPs) previously established as RA susceptibility variants. In the primary analysis, the effect of each SNP on treatment response was assessed by linear regression, using an additive model, in which absolute change in the Disease Activity Score in 28 joints at 6 months of followup was the outcome measure. In a secondary analysis, logistic regression models were used to compare patients with a good treatment response (n = 274) to those with a poor response (n = 195), as defined using the European League Against Rheumatism response criteria. Results were combined with those from previous studies to confirm the findings by meta-analysis.PTPRC rs10919563 SNP was associated with improved treatment response in both the primary analysis  and secondary analysis . A meta-analysis combining these data with the results from a previous study strengthened the evidence for association with the PTPRC SNP (P = 5.13 × 10−5). No convincing association of the treatment response with other candidate loci was detected.The PTPRC gene locus predicts improved response to anti-TNF biologic therapy. Fine-mapping studies are required to determine whether this SNP or another variant at the locus provides the greatest predictive accuracy for treatment response.Presence of the rs10919563 RA susceptibility variant at the  The introduction of anti–tumor necrosis factor (anti-TNF) biologic drugs in the clinical management of rheumatoid arthritis (RA) has proven highly successful in suppressing both inflammation and joint damage in many of the treated patients . HoweverTNF gene itself  studies and related meta-analyses –21. InteRC genes , 20, 21.RC genes .HLA–DRB1 shared epitope nor the PTPN22 locus is correlated with the response to biologics treatment (AFF3 locus (Previous investigations of RA susceptibility markers in determining the response to anti-TNF drugs have found that neither the reatment . In contF3 locus  and antiPTPRC locus (rs10919563) with response to TNF blockade, where the minor allele (A) of the PTPRC locus was associated with a poor treatment response. Protein tyrosine phosphatase receptor type C was first identified as a susceptibility locus for RA in a meta-analysis performed by Raychaudhuri et al  see . Blood shttp://www.Sequenom.com). For purposes of quality control, a 90% sample threshold and 90% genotyping success threshold were used.DNA samples were genotyped using the Sequenom MassArray iPLEX system. In each reaction, 10 ng of DNA was used and the protocol was followed according to the manufacturer's instructions   at 6 monhttp://pngu.mgh.harvard.edu/purcell/plink/). No adjustment was made for anti–cyclic citrullinated peptide (anti-CCP) antibody positivity, but a subgroup analysis of patients positive for anti-CCP was performed. No adjustment was made for anti-TNF drug type, as the aim was to identify a class effect. However, in order to establish whether a drug type–specific effect existed at any of the associated loci, an interaction term between SNP loci and drug type  was fitted.All SNP associations were analyzed with reference to the minor allele. Regression analyses were adjusted for covariates that had been identified in the BRAGGSS cohort as independent predictors of change in the DAS28: baseline DAS28, baseline Health Assessment Questionnaire (HAQ) score , concurrPTPRC locus, a meta-analysis that included data from previously published studies . Power calculations were performed using Quanto  under an additive model, for a range of marker allele frequencies.For the marker mapping to the  studies  was alsoSPRED2], rs10488631 [IRF5], rs3184504 [SH2B3], rs7155603 [BATF], and rs11203203 [UBASH3A]) failed to meet the imposed quality control threshold. Of 1,270 patients, 155 were ineligible for analysis, for the following reasons: 98 patients stopped treatment with biologics for reasons other than efficacy, 4 patients changed biologic agents, and 53 patients had a missing baseline or 6-month DAS28 value.A total of 35 SNP markers previously identified as RA susceptibility variants were genotyped in 1,387 DNA samples from patients receiving TNF blockade therapy. Following genotype and sample quality control, 29 SNP markers remained available for analysis in 1,270 samples (further details available from the corresponding author upon request). Six SNP markers  for allele frequencies of >5%. The demographic and clinical characteristics of the 1,115 patients available for analysis are presented in PTPRC locus (rs10919563) was associated with an improved response to TNF blockade therapy, as determined under an additive model    but failed to demonstrate any significant association with the 6-month change in DAS28 . All other analyses of the remaining markers revealed no compelling evidence for an association with treatment response (details available from the corresponding author upon request).In the initial multivariate analysis, which used the absolute change in the DAS28 over 6 months as the primary outcome measure, presence of the major allele G, which is also the RA susceptibility allele, at the  = 0.04) . This as = 0.03) . The genP = 5.13 × 10−5), thus further increasing the evidence base for this marker as a predictor of TNF blockade efficacy. These analyses revealed no evidence of genetic heterogeneity between the previous study and the current study (P = 0.64).A previous study by Cui et al demonstrated an OR of 0.55 for an association of anti-TNF treatment response with rs10919563, and the 95% confidence intervals  overlapped with the point estimate detected in the current study  . Meta-anPTPRC genetic marker was included in the model, the explained variance in this outcome measure increased to 14% (results not shown).Taking into account the clinical and demographic factors predictive of TNF treatment response  , the varPTPRC marker diminished when the stratum of anti-CCP–positive patients was investigated separately for either the absolute change in DAS28 as the outcome  or the EULAR response . Although the effect estimates were qualitatively similar to those obtained in the unstratified analyses, they were no longer significant at the 5% threshold. It should be noted that the anti-CCP status was only available for 595 patients (552 were seropositive), thus substantially reducing the power of the data in the stratified analyses.The association of the PTPRC SNP rs10919563 was investigated for drug type–specific effects, by fitting an interactive term in the analysis of absolute change in DAS28. No statistical correlation between the type of therapy used and SNP marker was observed (P = 0.42).The PTPRC locus with response to anti-TNF therapy, which was first described by Cui et al in populations of Northern European descent .The current study investigated 29 SNP markers for correlation with treatment response, but no correction for multiple testing was applied, so as not to preclude the identification of small effects. As a result, the association at the eviously . Furthereviously  strengthPTPRC gene on chromosome 1q31.3  appear to lie on the TNF signaling pathway. More powerful studies in the future may permit the investigation of possible statistical interactions between related loci. It should be noted that this is an observational study of RA, as opposed to a randomized controlled clinical trial, and this may have an important impact on the interpretation of such results.None of the other RA susceptibility markers tested showed a correlation with treatment response, as measured both by change in the DAS28 and by the EULAR response criteria, in the current study. However, the One reason that the effect sizes observed were modest may be because the outcome tested is a relatively subjective measure of treatment success, the DAS28 score. Although a powerful means of measuring treatment response, the DAS28 is a composite score that relies on information about the swollen and tender joint counts, patient-reported general health status, and the erythrocyte sedimentation rate. Strong associations with the DAS28 have been reported in pharmacogenetic studies, in experimental conditions where there is usually a well-defined phenotype, such as a rare adverse event or correlation with an objective, biologic marker. It may be that testing a more objective measure of outcome, such as a biologic marker of inflammation, will allow the identification of genetic markers with greater effects on treatment response. This will be a focus for future work.PTPRC variant is 0.5%, which alone will not be clinically useful. This SNP may provide clinical utility in the future when used as part of a treatment algorithm in combination with other genetic and clinical predictors. A number of other influences, such as patient demographics and psychological factors, may also be important contributors and require further investigation, as the mechanisms of the anti-TNF response are likely to be multifactorial.To date, the contribution of genetic factors in explaining treatment response to anti-TNF agents is not known. Clinical markers  may account for up to 20% of the variance in treatment response , leavingPTPRC) and treatment response. These results suggest that further investigations, including fine-mapping and functional studies, at the PTPRC locus are now warranted.In summary, we have performed an association study of established RA susceptibility markers with response to anti-TNF treatment in a large panel of RA patients from the UK. We have replicated the association between rs10919563 (


The in vivo monitoring of the transplanted myoblasts was assessed by bioluminescence imaging and showed both the viability of the epigastric artery within the 3-dimensional construct and again that cell survival in vivo is highly depending on the blood supply with the beginning of capillarization within the BAT seven days after transplantation in the perfused group. However, further studies focussing on the matrix improvement will be necessary to create a transplantable BAT with the epigastric artery as anastomosable vessel.The creation of musculoskeletal tissue represents an alternative for the replacement of soft tissue in reconstructive surgery. However, most of the approaches of creating artificial tissue have their limitations in the size as the maximally obtainable dimension of bioartificial tissue (BAT) is limited due to the lack of supporting vessels within the 3-dimensional construct. The seeded myoblasts require high amounts of perfusion, oxygen, and nutrients to survive. To achieve this, we developed a 3-dimensional scaffold which features the epigastric artery as macroscopic core vessel inside the BAT in a rat model (perfused group,  The background signal was evaluated at different locations not close to the bioreactor chamber as well as at different time points  and subtracted from the corresponding peak signal.The followup of the transplanted myoblasts inside the Cryosections of explanted bioartificial tissue containing myoblasts of d7 were washed with PBS. The cultures were then incubated with blocking solution (5% goat serum and 0.1% TRITON X-100 in PBS) for 10 min. After being washed with PBS, the cultures were incubated with mouse anti-MyoD monoclonal antibody , diluted 1 : 50 in blocking solution (2 h at 20°C), and again washed with PBS and incubated with anti-mouse IgG  for 2 h diluted 1 : 100 in blocking solution. After being washed with PBS and mounted with Mowiol, anti-MyoD-stained cultures were viewed and photographed by fluorescence microscopy.8 photons/sec, see 7 photons/sec and 3.031 × 106 photons/sec) indicating the remission of the myoblasts cell survival. The evaluated background signals (4.822 × 105 photons/sec) showed no significant differences in terms of location and time points. However, in unperfused BATs without arterial inflow, and therefore, no possible Luciferin supply, only the background signals  could be detected as well. Furthermore, the circumstance of retrieving bioluminescence signals in the perfused BATs (see Figures in vivo bioreactor model for musculoskeletal or other different cell types including a central anastomosable core vessel as well as the possibility of monitoring the transplanted cells, in our study transfected myoblasts in vivo. Thus, the required animal number can be reduced, as there is no exceeding animal sacrifice necessary at different time points.The bioluminescence followup monitoring of the Luciferase-transfected myoblasts showed the expected results with a high number of photons per second on day 0 directly after surgery (1.769 × 10Pulsatile perfusion within a 3-dimensional bioartificial tissue construct is promoting the capillarization , 9. In oin vivo. The implantation of the in vivo bioreactor with the epigastric artery as core vessel was performed routinely with regular patency of the vessel and without any side effects or wound problems during the experimental period. Again, starting capillarization was found in the areas close to the core vessel. Thus, the epigastric artery is applicable as central-core vessel of the 3-dimensional construct and could later be also used as an anastomosable vessel of artificial musculoskeletal tissue for further experimental reconstructive surgeries after optimizing both matrix and cell survival. However, with the use of a predefined customized in vivo bioreactor chamber, this model offers also a variety of possible applications to create vascularized artificial tissue.Myoblasts can be transfected with Luciferase and, therefore, bioluminescence is an effective and reliable method for assessment of myoblasts cell graft survival