Therefore, precise quantification of wall motion is essential. However, using standard-of-care imaging data, approaches for patient-specific estimation of pulsatile deformation are prone to uncertainties due to, e.g., contrast agent inflow-related intensity changes and small deformation compared to the image resolution. A ground truth dataset that allows evaluating and finetuning algorithms for deformation estimation is lacking. We designed a flow phantom with deformable structures that resemble cerebral vessels and exhibit physiologically plausible deformation. The deformation was simultaneously recorded using a flat panel CT and a video camera, yielding video data with higher resolution and SNR, which was used to compute ‘ground truth’ structure deformation measures. The dataset was further applied to evaluate registration-based deformation estimation. The results illustrate that registration approaches can be used to estimate deformation with adequate precision. Yet, the accuracy depended on the registration parameters, illustrating the need to evaluate and finetune deformation estimation approaches by ground truth data. To fill the existing gap, the acquired benchmark dataset is provided freely available as the CAPUT  dataset, accessible at  The weakened structural integrity results in a depletion of the wall strength2. When the circumferential stresses, due to heart cycle-related pressure variations, surpass the (reduced) wall strength, the risk of rupture increases significantly3. Rupture and the following subarachnoid hemorrhage are associated with dangerous complications, ranging from severe cognitive or physical impairments to fatality5. Despite the extreme consequences of aneurysm rupture, the initiation, growth, and development of aneurysms are still not entirely understood and are probably processes dependent on multiple factors6. Decision finding for optimal treatment of aneurysms  currently incorporates only aneurysm size and location as controlling factors. Yet, multiple studies suggest that the complex interaction of mechanical and physiological factors  plays a considerable role during pathogenesis and ultimately rupture9. The underlying hypothesis is that aneurysm deformation could be correlated to corresponding wall stresses, which, in turn, could (considering the biomechanics of vessel structures) be linked to a risk of rupture. Respective quantitative data could in principle be valuable information to refine existing guidelines for treatment9, but reliability and robustness of existing methods to derive them in standard-of-care image data need to be improved for application in clinical routine.A cerebral aneurysm is an acquired pathological local dilation of the diameter of a vessel wall, which is associated with a structural weakening of the vessel wall10. Our results revealed a dependency of the intensity changes due to contrast agent inflow on the extent of estimated wall deformation, therefore illustrating, that computational methods used in high-precision studies such as the quantification of cerebral wall motion have to be fine-tuned and verified using ground truth data. Our current study extends this work and addresses the uncertainties of image-based analysis of related hemodynamic properties, specifically the deformation of aneurysm structures using a deformable flow phantom. Currently, one essential limitation in the context of automated estimation of pulsatile deformation of aneurysms and wall motion of vessel structures is the lack of ground truth data. Proposed methods for vessel structure deformation estimation  are prone to uncertainty due to, for instance, challenges caused by intensity changes as the result of contrast agent inflow and limited spatial/temporal resolution of the image data. The influence of these challenges affects the accuracy of deformation estimation. However, the accuracy cannot be reliably assessed using only in vivo radiology imaging data, which limits the reliability of respective patient-specific vessel wall motion estimation. Furthermore, related deformation quantification uncertainties propagate into the computation of derived measures like associated stresses, rendering them also questionable.In previous work, we focussed on the effects of contrast agent inflow on the quantification of wall motion using a non-deforming flow phantomAccordingly, the aim and contribution of the current study are twofold. First, we generated and provide a new benchmark dataset, the so-called CAPUT  dataset, that can be used for evaluation of frameworks for cerebral wall motion estimation. Therefore, we constructed a novel deforming flow phantom see Fig. . The cen16. This addresses the inherent conflict between the low resolution of respective standard-of-care clinical image data and the necessity for high precision regarding the wall motion estimation, and, consequently, the validity of previous findings of studies employing CT and MRI data for cerebral wall motion quantification (for an overview of related studies see9). The structure of the paper follows the afore-mentioned contributions. In the section “Flow Phantom and Benchmark Data”, the flow phantom design is explained and the benchmark data introduced. The experiments on the accuracy of DIR-based quantification of wall motion quantification are described in the subsequent section. Respective results are presented and discussed in the “Results” and “Discussion”. The paper is concluded with final remarks.As second contribution, we illustrate the application of the benchmark data to evaluate the accuracy of automated wall motion estimation by deformable image registration (DIR). As part of the analysis, we also investigate how precise a deformation can be quantified in medical image sequences with, in comparison to the FPCT data, significantly reduced spatial and temporal resolution as commonly found for other imaging modalities like computed tomography (CT) and magnetic resonance imaging (MRI)The flow phantom was designed to provide a repeatable, physiologically reasonable deformation of vessel-like structures. The entire measurement setup is displayed in Fig. in vivo and in vitro experiments17), we generated pulsatile deformation of the flow phantom structures in the range of 0.08 to 0.25 mm.Flat panel computer tomography image data was acquired using a Philips AlluraXper . The spatial resolution for the FPCT sequences was 0.185 × 0.185 mm with a temporal resolution of 25 FPS. During the experiments, the valve was triggered with a frequency of 1 Hz, resembling a physiologically plausible heart rate. The pressure of the pump was varied to produce anatomically plausible deformations for the different flow phantom structures. For planning purposes, the deformation was estimated analytically  was used. Since the video files did not contain dedicated pixel spacing information, pixel spacing calibration had to be performed manually. Therefore, the extent of a non-deforming structure of the flow phantom was measured in pixels and compared to its known geometric extension in millimeters. Thereby, the spatial resolution of the acquired video data was determined to be approximately 0.0336 × 0.0336 mm.https://www.github.com/IPMI-ICNS-UKE/CAPUT.Simultaneous data acquisition was repeated for all central structures. Thus, the CAPUT dataset finally consists of six pairs of corresponding FPCT and video data. The data is provided freely available and can be accessed via et al.12 appeared promising to us because most parts of their approach were either automated or automatable, rendering the results less observer-dependent than comparable manual thresholding approaches also frequently described in the literature. We, therefore, implemented and slightly extended their registration-based approach for wall motion quantification, and used it as an application example of the benchmark dataset. An overview of the approach is given in Fig. 19, the ANTs framework20 was applied for registration, using a multi-resolution, symmetric diffeomorphic image registration scheme with mutual information as distance measure. The exact registration parameters are provided in supplemental materials During literature review, especially the registration-based wall motion estimation by Oubel The described registration-based deformation estimation approach was applied to the original FPCT images of the six vessel structures of the CAPUT dataset. To further illustrate the influence of registration parameters on the resulting deformation data, repeated runs were performed with different registration parameters  structure deformation. The relatively low number of landmarks could, however, be considered as leading to residual uncertainties of the obtained wall deformation. We, therefore, performed multiple repetitions with different landmark sets, revealing robust and consistent results; respective landmark sets are provided as part of the CAPUT dataset.To also capture the dynamics of the imaged processes, we further applied the described automated registration-based deformation estimation to the high-resolution video data. Landmark displacements observed for the video data were finally compared to the structure deformation and landmark displacements, respectively, estimated for the FPCT data.21, which states that the sampling rate should be larger than twice the highest frequency component of the original signal.To investigate the feasibility of accurate quantification of geometric deformation of the vessel wall using typical image resolution of different imaging modalities also applied in the given context , our high-resolution FPCT imaging data was resampled. In detail, we resampled the FPCT data to an isotropic spatial resolution of 0.37, 0.74 and 1.48 mm/px. Moreover, the original temporal resolution of 25 FPS was reduced to 4 FPS, 2 FPS and 1.5 FPS to cover typical CT, MRI and FPCT literature values. Especially sampling frequencies around 2 FPS are interesting. Given the original dynamic process with an underlying frequency of 1 Hz, it is to be expected that around and especially below this frequency, the reconstruction of the original signal is no longer reliable. This relates to the Nyquist-Shannon sampling theoremFor evaluation of the deformation quantification performance in the presence of reduced FPCT image resolution, we focussed on a structure with comparably high deformation  and applied the registration parameters that led to minimal errors during the original resolution experiments.The results of the automatic deformation estimation during the inflow of contrast agent for the different structures  at both inner diameters of the feeding vessel 3 mm, 4 mm) are summarized in Fig.  mm, 4 mmThe spreading of the blue lines, observed for all structures, nevertheless illustrates a dependence of deformation estimation accuracy and registration parameters. Please note that in our case and based on long(er) standing registration experience the registration parameters were already chosen to cover only a relatively small but reasonable range; for inexperienced users, the parameter search space could be far larger. To identify the best registration parameter set , we calculated the root-mean-square error (RMSE) of the reference deformation data (red continuous line) and parameter-specific results (i. e. the blue lines) for every structure. The RMSE values, averaged across all structures, are plotted in Fig. The results of the deformation estimation accuracy evaluation using the downsampled FPCT data are depicted in Fig. Regarding temporal resampling, the 4 FPS and also in parts the 2 FPS temporal resolution data result in a good fit relative to the full temporal resolution data. Yet, deviations from the ground truth data can still be observed; potential higher frequency motion components (likely due to structure vibration) are, in agreement with the Nyquist theorem, not reflected. Also in agreement with the Nyquist theorem, using the 1.5 FPS dataset, the original signal cannot be reliably retrieved anymore, thereby extensively lowering confidence of the calculated results.These observations are further supported by the respective RMSE evaluation summarized in Table The origin of our work was the wish and demand to develop a deformable flow phantom and measurement setup that allows evaluating computational approaches to assess pulsatile-type cerebral vessel and vessel-like structure wall deformation; the presented data demonstrate successful implementation and data acquisition.The experimental setup provided us with the means to generate a reliable ground truth and benchmark dataset, enabling us to fine-tune our registration-based deformation estimation. Evaluation of the generated results showed that the estimation of wall motion is possible to a high degree of precision. However, we were also able to demonstrate that the measured deformation  depends on the chosen registration parameters. This illustrates the need to test approaches for wall motion estimation using respective ground truth data to assess the capability and accuracy limits of the respective approaches. In turn, we hope that other working groups in this field also benefit from the release of the acquired data (consisting of both the FPCT and video data) as a freely accessible benchmark dataset and make use of the CAPUT data. By testing and appropriately tuning of respective deformation estimation approaches using the CAPUT dataset, shortcomings of individual algorithms can be identified and accounted for. In turn, thereby evaluated approaches and parameter settings, i.e. those that are capable of reproducing the geometric movement of the structures in the CAPUT dataset, can be considered to be better suited to reliably and precisely represent wall motion in clinical image data. Therefore, this dataset is expected to be especially interesting for groups working in a clinical setting, since not only wall motion deformation but also derived information such as flow velocity profiles or wall shear stress distributions can be more reliably estimated and interpreted with a higher degree of fidelity by using thoroughly evaluated algorithms and parameter sets. We will further work on complementing the dataset by additional measurements and data and encourage interested readers to contact us in case of specific ideas and desired scenarios.The second data analysis part addressed the question of the achievable precision of deformation estimation using imaging data with reduced spatial and/or temporal image resolution compared to the CAPUT dataset. Evaluating the full temporal resolution data at different spatial image resolution, even for an image spacing of 1.48 mm/px, a wall motion estimation error up to slightly above 30% was observed. Considering the resolution in relation to the small structure deformation (in the order of 0.25 mm), these results were surprisingly accurate. Therefore, automated assessment of wall motion deformation seems to be feasible even in standard-of-care imaging data when using well-tuned deformation estimation approaches. Yet, it has to be considered that the resulting error is not entirely negligible. Depending on the application , the introduced uncertainties and errors will propagate, potentially leading to misleading derived measures that might turn into erroneous conclusions.The results obtained by analysis of the temporally downsampled data also demonstrated robust performance of the registration-based analysis approach. Although the FPCT framerate was reduced substantially, the maximum deformation could still be retrieved at 4 and 2 FPS with adequate precision. Results at <1.5 FPS revealed substantial difficulties and emphasized the relevance of the Nyquist theorem for the given application. Thus, since most patients have probably a higher resting pulse than 60 bpm (ca. 60–100 bpm), we consider a minimum imaging sampling frequency of 4 FPS to be advisable.in vivo. Yet, addressed uncertainties of deformation estimation accuracy are especially relevant for smaller structures. It is to be expected that larger aneurysms exhibit stronger deformation, which, in turn, is easier to quantify  from an image processing perspective, but also of particular interest from the clinical perspective. Another debatable aspect is the usage of water as a substitute for blood in our experiment since the viscosity of blood is distinctly higher than water. Yet, as our study did not investigate exact flow patterns but only the deformation of the phantom structures, the simplistic usage of water is not expected to have any influence on the presented results.Regarding the deformable structure size, it could be finally argued, that the chosen aneurysm height is relatively small in comparison to aneurysms often observed see Fig. . MoreoveIn summary, we acquired and provide a benchmark dataset  for evaluation and fine-tuning computational approaches for cerebral wall motion estimation and aneurysm deformation, respectively. Our experiments further showed that registration-based deformation estimation using the recorded data is possible to a high degree of precision, even for imaging data with relatively low spatial and/or temporal resolution. However, we also illustrated that parameters for, e.g., registration-based deformation estimation approaches have to be well selected to produce viable results. This, in turn, is precisely the envisioned purpose of the CAPUT dataset, which aims to advance toward reliable and transparent wall motion estimation in standard-of-care images and the development of respective standardized methods that potentially allow incorporating wall deformation measures into treatment decision workflows.AppendixExamplary video file of a flow phantom structure


Autoinhibition is an effective mechanism that guards proteins against spurious activation. Despite its ubiquity, the distinct organizations of the autoinhibited states and their release mechanisms differ. Signaling is most responsive to the cell environment only if a small shift in the equilibrium is required to switch the system from an inactive (occluded) to an active (exposed) state. Ras signaling follows this paradigm. This underscores the challenge in pharmacological intervention to exploit and enhance autoinhibited states. Here, we review autoinhibition and release mechanisms at the membrane focusing on three representative Ras effectors, Raf protein kinase, PI3Kα lipid kinase, and NORE1A (RASSF5) tumor suppressor, and point to the ramifications to drug discovery. We further touch on Ras upstream and downstream signaling, Ras activation, and the Ras superfamily in this light, altogether providing a broad outlook of the principles and complexities of autoinhibition. Ras effectors play major roles in cell fate  is unlikely to capture the autoinhibited conformation; if they are slightly more stable, it will  lipid kinase, and Ras association domain family 5  tumor suppressor; however, our discussion is general. Cell signaling needs to be sensitive to the environment, and sensitivity is feasible We selected Raf, PI3Kα, and NORE1A as representative Ras targets Fig. . To incrFiguring out the autoinhibition and activation mechanisms of Ras targets at the membrane may not directly suggest Ras pharmacology; however, it can help clarify what may or may not work. Below, our review is within this light.Autoinhibition and its release are common regulatory mechanisms, in solution, as for example in cyclic adenosine monophosphate (cAMP)- and cyclic guanosine monophosphate (c-GMP)-dependent protein kinases which are autoinhibited by interactions between their respective regulatory and catalytic domains  are typically in the autoinhibited state with only 2 to 10% in the extended, active conformation . PAK1 autoinhibitory domain quenches the catalytic kinase domain. Cdc42 high-affinity interaction activates PAK1 by binding to the same region as the regulatory domain. Conformational rearrangements and autophosphorylation release the autoinhibition , RASSF5 (NORE1A), and Ras. But relatively, weak interactions enable higher affinity activators, if present at sufficiently high effective local concentrations, to shift the equilibrium in favor of an “open” active state, executing the cell’s adaptation to the environment.(i).Removal of the N-terminal region dysregulates Raf’s kinase activity .Overexpression of CR1 abolishes Raf’s catalytic activity (Chong and Guan (iii).B-Raf binding to active HRas abolishes the interaction of the N-terminal region with the kinase domain;(iv).Ser446 phosphorylation of B-Raf weakens the autoinhibition but S446A substitution increases it, suggesting that alanine strengthens the interaction;(v).Acidic substitutions at phosphorylation sites in the activation loop, Thr599 and Ser602 .Phosphorylations of Ser338 and Tyr341  weaken the autoinhibition (Chong and Guan (vii).B-Raf Ser446 (Ser338 in Raf-1) is constitutively phosphorylated in immortalized COS and PC12 cells .Phosphorylation of Ser259 (Raf-1) or Ser365 (B-Raf) in the CR2 by protein kinase A (PKA)  structure of Raf’s autoinhibited conformation suggests an ensemble of “closed” monomeric states with the N-terminal tail, Ras binding domain (RBD), cysteine-rich domain (CRD), and linker, with its Ser/Thr-rich segment, hindering kinase domain dimerization. (The RBD-CRD region is denoted conserved region 1 (CR1) and the Ser/Thr-rich region as CR2 Fig. a Lavoie). SeveraFinally, the importance of the region in autoinhibition is also implied by other nearby substitutions that enhance Ras–Raf binding  has been known for decades, exactly how Ras activates Raf has been puzzling. Over the last few years, the community focused on the kinase domain dimer and its structure with the aim of unraveling the mechanism of the autophosphorylation, why and how resistance can defeat Raf inhibitors interacting with the kinase domains and overcoming the dimerization requirement, and broadly drug discovery , we consider the high affinity of the Ras–RBD interaction: the residues whose phosphorylation abolishes the autoinhibition, data related to the consequences of alanine substitution, the suggested binding of the 14-3-3 protein to two phosphorylated sites as described above  from phosphatidylinositol 4,5-bisphosphate (PIP2), a critical signaling molecule that stimulates the PI3K/Akt/mTOR  pathway, which regulates cell growth and survival, cytoskeleton reorganization, and metabolism  of RTKs, such as EGFR  . Finally, the two-component activation explains why even without Ras, PI3Kα can be activated—albeit not fully.Thus, unlike Raf whose activation at the membrane involves a shift of the ensemble toward the more stable Ras–Raf interaction Fig. , PI3Kα aKD, for the Ras–PI3K complex is higher than that for the Ras–Raf RBD . The Michaelis-Menten kinetic efficiency (kcat/Km) directly measures the enzyme activity. Here, the dissociation of nSH2 from p110α enables the effective formation of phosphate transfer transition complex, analogous to an increase of kcat. Experimental data indicate that both membrane binding capability and effective formation of the phosphate transfer transition complex are required for a fully active PI3Kα  binding, phosphoryl transfer, and dissociation of the products. If we do not consider ATP binding and ADP and PIP3 dissociation steps, activation can be evaluated by kcat/Km based on a two-step reaction  interacts with active Ras and activates the MST1/2   by binding to the n/cSH2 domains, replacing the missing RTK signal , phosphatidylinositol 4-phosphate 5-kinase Iα , and PI3Kα lipid kinases; all scaffolded by IQGAP1  and Akt, that are also in the complex. Blocking the interaction of IQGAP1 with PIPKIα or PI3K inhibits generation of PIP3 and signaling. The four IQ motifs of IQGAP1 can interact with apo- or holo- CaM  substrate and the subsequent extracellular signal-regulated kinase (ERK) in the MAPK pathway) can also be scaffolded by IQGAP1; however, their major scaffolding protein is kinase suppressor of Ras (KSR). Raf family pseudokinases KSR1 and KSR2 can support the interaction of Raf isoforms with MEK. Unlike Raf, KSR lacks a Ras-binding domain; however, its dimerization with Raf stimulates Raf’s catalysis (Lavoie et al. In addition to increasing the effective local concentration, enhancing, and stabilizing molecular adjacency, allosteric actions in scaffolding proteins are also expected to promote catalytic activity (Nussinov et al. 2, is a membrane-anchored lipid, which has been synthesized by sequential catalytic actions by lipid kinases. Even though PI3Kα is a dimer, p85α is a regulatory subunit. In the cell, it mostly keeps the p110 catalytic kinase subunit in the inactive autoinhibited state. Through release of the autoinhibition of its SH2 domains, it triggers activation. The lower affinity of its RBD to Ras suggests that as long as Ras predominantly exists as dimers or nanoclusters, Raf signaling will go through (Nussinov et al. Activation of Raf, PI3Kα, and NORE1A involves release of autoinhibition at the membrane; however, the distinct mechanisms differ. Activation of Raf kinase domains requires dimerization, which necessitates their spatial proximity, along with the high affinity Ras–Raf interaction which drives the shift in the population from the inactive to the active, “open” Raf state Fig. . By contIt has been suggested that proteins regulated by autoinhibitory domains can be promising targets for allosteric drugs that stabilize the native, autoinhibited fold (Peterson and Golemis


This paper explores the significance of narrative in collaborative reasoning using a qualitative case study of two teams of intelligence analysts who took part in an exercise using an online collaborative platform. Digital ethnographic methods were used to analyze the chat transcripts of analysts as they reasoned with evidence provided in a difficult, fictional intelligence-type problem and produced a final intelligence report. These chat transcripts provided a powerful “microscope” into the reasoning processes and interactions involved in complex, collaborative reasoning. We found that Individuals and teams used narrative to solve the kinds of complex problems organizations and intelligence agencies face daily. We observed that team members generated what we term “micro-narratives”, which provided a means for testing, assessing and weighing alternative hypotheses through mental simulation in the context of collaborative reasoning. The creation of micro-narratives assisted in the teams’ reasoning with evidence, an integral part of collaborative reasoning and intelligence analysis. Micro-narratives were combined into, and compared with, an ideal or ‘virtual’ narrative which informed the judgements the team came to in their final intelligence report. The case study developed in this paper provides evidence that narrative thought processes play an important role in complex collaborative problem-solving, reasoning with evidence and problem-solving. This is contrary to a widespread perception that narrative thinking is fundamentally distinct from formal, logical reasoning. Decision-makers and analysts are often faced with complex, uncertain and rapidly evolving problems and situations where data and information may be incomplete and where judgements and decisions have serious, at times even life-and-death ramifications. These problems and situations may, for example, relate to how best to organize emergency disaster relief after a major earthquake, and whether a given building houses a terror mastermind such as Osama bin Laden.There has been a widespread perception, following Jerome Bruner , that nareasoning in intelligence analysis, despite Gregory Treverton’s  would be a standard repair tool for a mobile phone/ electrical device (but that’s my assumption!)13:57 Quoll97: So really, the owners DNA could have been on there from ages ago. But still doesn’t explain how the old friend got his DNA stuck on there13:58 Platypus20: If we consider the secondary DNA transfer, as I think someone mentioned previously, then the shared hookah pipe would explain how the old friend’s DNA got stuck on there.13:58 Kookaburra31: Quoll97 There is a section in the background reading which talks about secondary DNA transfer. Seems unlikely, but worth considering.13:58 Quoll97: But only if the owner went down into the workshop afterwardsIn another example, Team Purnululu evaluates the intelligence presented to them in the problem regarding items found in the basement of the Telecom Shop, where the bomb-making workshop was found. The Owner has claimed that he rented the basement out on a cash basis to two foreign workers, and that he does not go there, while “The Courier”, the shop’s assistant and errand-runner, claims that he has never been in the basement. However, items that were formerly in the shop—a used mobile phone and a computer keyboard formerly used by customers—as well as the soldering iron found in the workshop, were found to have different constellations of the DNA of the Owner, Courier and Old Friend. Team Kakadu considers a number of micro-narratives in their assessment of this data:13:54 Currawong23: Keyboard DNA could arise from secondary contact though, based off the amplification process.13:54 Crocodile97: And the DNA for the keyboard has been explained as the old desktop from the office.13:54 Cockatoo27: @Cassowary55- could the Courier’s DNA on the keyboard be from him using the keyboard legitimately in the shop/office?13:55 Bilby77: That’s what I understood13:55 Echidna28: Yeah they confirmed the computer used to be used for sales so that explains courier and owner’s DNA on it13:55 BlackCockatoo55: The courier is also a store attendant—he works in the shop? He just doesn’t ’go that far out the back of the store building’.13:55 BlackSwan14: Help me with something—if the owner/courier attests to not being in the basement for 6 months, how did the computer/keyboard/mobile phone/soldering iron end up in the basement?13:56 Echidna28: The DNA of ‘others’ could also possibly be former staff? Other customers maybe. It’s difficult to say if there’s significance to that13:56 Cassowary55: It could, it just never states that the courier used the computer in its old position13:56 Crocodile97: @Blackswan!!! The computer was replaced a ‘few weeks ago’ who DID put it in the basement?13:56 Echidna28: @BlackSwan14 That’s the thing. Whoever took them down there has to be involved13:57 Dingo48: If not involved then at least aware of[…]13:58 Currawong23: While unlikely, it is possible that the items could have been sold to the ‘renters’ of the basement without any of the others actually going down there …13:59 BlackCockatoo55: @BlackSwan14 they could have chucked the old keyboard out or put it out the back and the bombers took it for their basement?13:59 Cockatoo27: Do the renters even exist?In this exchange, it is evident that participants are engaging in what Bex et al.  refer toThe person who moved the items was involved in terrorist activitiesThe person who moved the items was aware of the terrorist activities but not involved in themThe computer was thrown out, and the renters recuperated itThe renters do not exist, and the Owner lied about their existence.We found that the use of micro-narratives formed an integral part of both teams’ reasoning processes as they collectively analyzed the problem and went about producing a collaborative final report. Furthermore, as discussed in the following section, the conclusions reached by teams in their reports clearly indicate that the reasoning which informed the generation of micro-narratives was incorporated into the final knowledge product, the intelligence-style report.We also analyzed the two teams’ final knowledge product—their submitted intelligence report. In particular, we looked for ways that the teams used the  conclusions reached through the use of micro-narratives in their chat deliberations to inform and produce the final report. Having observed the use of micro-narratives in our analysis of the chat transcripts, we hypothesized that groups would use these micro-narratives, as well as the way these fit together into larger macro-narrtives, to help construct their intelligence product,Micro-narratives are not fully developed narratives, they are incomplete stories or scenarios. They serve as basic units that individuals and teams can debate, deliberate upon, and discuss in an iterative process in which micro-narratives are generated and weighed against each other for plausibility with regard to evidence, general knowledge about the world, and fit with other micro-narratives. They can then be organized and assembled into a larger, more developed narrative structure. This larger narrative structure would, for example, tell a story about each of the suspects in the Kalukistan problem, their interactions and their actions in the time period surrounding the bombing of the Ministry of Mines, and their participation in, knowledge of (or lack thereof) the bomb factory in the basement of the Telecom store. Because this full narrative(s) was never fully written down or recounted, but could clearly be inferred from the data in the chat transcripts and final report, we have chosen to call it a virtual, or ideal, macro-narrative. While aspects of this more complete story were found both in the chat transcripts and in the final report, this “macro-narrative” was never fully written down as one complete narrative—but elements of it could be seen in both the chats and the final reports. We could infer its existence as an “ideal”, or “virtual” narrative co-created by team members as they used the chat function, and we could also view “glimpses” of these macro-narratives in the final report.In the exercise, the teams were directed to assess four different suspects in terms of their likely involvement in terrorist activities. We took each suspect’s assessed involvement, and its justification, to be a macro-narrative, as they were composed of relevant micro-narratives developed over the exercise justifying the assessment. Importantly, since the problem specifically asks for four separate assessments, each assessment was a natural candidate for conceptualization as a macro-level narrative.In the previous section, we saw an example of how two teams engaged with the possibility of DNA transfer by creating micro-narratives to reason with evidence. The final reports of both teams synthesized these micro-narratives into a more complete narrative as part of their final report. Team Purnululu wrote:The Old Friend’s DNA matched a sample collected from a soldering iron in the bomb workshop. We assess that transfer of The Old Friend’s DNA through contact with The Owner provides a plausible explanation for the presence of his DNA at the bomb-making site. We note that under test conditions, secondary DNA transfer was detected in 85% of cases following extended hand-to-hand contact, which could have occurred through The Owner and Old Friend sharing a hookah pipe the evening before the explosion. While the DNA transfer could have occurred in reverse, implicating The Old Friend, we assess that The Owner’s presence at Oasis Telecom immediately after their evening meeting and The Owner’s DNA on all three items found in the workshop indicate it is much more likely to have been transferred by The Owner. We assess that it is plausible that The Old Friend directly handled the soldering iron, but that his DNA was more likely to have been transferred in the absence of any other evidence linking him to the workshop.Similarly, team Kakadu concluded that:DNA material obtained from soldering iron could be explained by secondary DNA transfer: If a) the Old Friend and Owner sharing a hooker pipe the night before the bombing  and b) the Owner touched the soldering iron that night or on the day of the bombing .In In Telling stories, and using narrative, is a fundamental part of how we understand the world. According to Aristotle, the purpose of a story is to show us “what may happen—what is possible according to the laws of probability or necessity” . NarratiOver the past few decades, researchers in the humanities, psychology and organizational studies have contributed to a growing body of interdisciplinary work connecting the study of narrative with our understanding of human society, the workings of the human mind, and our perception of the world. People use narratives and stories to compare perspectives, organize experiences, represent and “construct” reality and personal identities, elucidate goals, evaluate strategies, interpret results and outcomes, evaluate evidence and judge the validity of knowledge claims. , 40, 41.In the last several decades, narrative has been an expanding area of interdisciplinary research, and has inspired “research questions with direct relevance to national security” . There hOur findings support and contribute to the growing body of research supporting the simulation model of narrative. Mar and Oatley  argue thIn the context of intelligence analysis, as also with scientific claims, it is not sufficient that a person or persons making a claim have some level of authority; rather, a judgement of validity must be based on weighing and evaluating the argument, evidence and “intel” put forward in support of a knowledge claim . ReasoniWe found that teams used micro-narratives to assist in reasoning with evidence, the exploration of competing and alternative hypotheses, in making judgements necessary to solve a difficult intelligence type problem and in the production of an intelligence report. We believe that future research can elaborate the role of narrative and narrative thought processes in collaborative knowledge-building and knowledge-building more broadly.We have used the terms micro-narrative and micro-narrative to describe the often quite brief and fragmentary narratives which teams produced in the chat function of the SWARM platform. In doing so we are consciously drawing a parallel between the “on the fly”, informal reasoning process we observed as it emerged in the text chats on the SWARM platform, and the structured analytical technique of scenario generation as it has developed in post-WWII strategic thinking in the public and private sector particularly in the U.S. and France –48.While scenario analysis continues to evolve, it has become an established structured analytical technique for predicting and considering multiple possible futures in intelligence analysis  and otheWe are also particularly interested in developing tie-ins with related narrative techniques, such as what futurist and author August Cole refers to as FICINT , or FictThis case study was undertaken as part of ongoing exploratory research associated with the testing and development of the SWARM platform. The SWARM platform has offered a critical window, or metaphorical microscope, for peering into and better understanding a complex reasoning process that would otherwise be largely opaque. Using chat transcripts and final knowledge products in the form of an intelligence-type report, we observed that teams of individuals used micro-narratives and incomplete stories to make hypotheses about evidence, motivations, actors and actions, and so on. They then weighed these often competing scenarios against each other, the evidence, and their knowledge of the real world, and used these micro-narratives to create larger, more complete ideal narratives regarding the intelligence-type problem they were tasked to address. While these larger narratives were not written down, we could infer them from our analysis of the teams’ chat and the production of the final intelligence report. The team members then used these larger, more complete narratives  to write an intelligence-style report evaluating the likelihood that each of the 4 suspects was involved in terrorist activities. We further inferred that the use of these micro-narratives in the creation of a larger, ideal narrative were indicative of a kind of mental simulation, consistent with models of narrative thought processes from the field of cognitive psychology (e.g. Mar and Oatley ).While narrative has received increasing attention in a number of fields in recent years, scant attention has been paid to the role of narrative in complex problem-solving outside of the literature on jury decision-making (e.g. Pennington and Hastie ). We hopAs organizations attempt to navigate, adapt to and coevolve with complex environments , the abi


PMEL is a pigment cell-specific protein that forms a functional amyloid matrix in melanosomes. The matrix consists of well-separated fibrillar sheets on which the pigment melanin is deposited. Using electron tomography, we demonstrate that this sheet architecture is governed by the PMEL repeat (RPT) domain, which associates with the amyloid as an accessory proteolytic fragment. Thus, the RPT domain is dispensable for amyloid formation as such but shapes the morphology of the matrix, probably in order to maximize the surface area available for pigment adsorption. Although the primary amino acid sequence of the RPT domain differs vastly among various vertebrates, we show that it is a functionally conserved, interchangeable module. RPT domains of all species are predicted to be very highly O-glycosylated, which is likely the common defining feature of this domain. O-glycosylation is indeed essential for RPT domain function and the establishment of the PMEL sheet architecture. Thus, O-glycosylation, not amino acid sequence, appears to be the major factor governing the characteristic PMEL amyloid morphology. The protein assembles into a characteristic architecture of well-separated sheets consisting of laterally associated amyloid fibrils5. The resulting matrix serves for the deposition of the pigment melanin and likely also sequesters toxic reaction intermediates in the melanin synthesis pathway6, keeping these from diffusing out of the organelle and into the cell2. The amyloid core of the fibrils is formed by a proteolytic product derived from the PMEL protein1. This proteolytic fragment assembling into and forming the core was originally discovered via its reactivity with antibody I517. We termed this product the core amyloid fragment (CAF) and recently unraveled its sequence identity8. There is a second type of proteolytic fragment associated with melanosomal fibrils, MαC9, which is also derived from the PMEL protein and which contains the polycystic kidney disease (PKD) domain and the highly O-glycosylated repeat (RPT) domain9. After incorporation into the fibrils, this fragment undergoes massive proteolysis both within the RPT domain as well as between the PKD domain and the RPT domain9. The PKD domain is essential for fibril formation10 and may possibly contribute to the fibril core alongside the CAF7. The RPT domain had originally been suggested to be required for amyloid formation based on studies in HeLa cells10 and was even proposed to form the amyloid core12. However, later work showed that this domain is dispensable for amyloid formation both in vitro7 as well as in vivo in living melanocytic cells13. However, the RPT domain controls amyloid morphology, as the characteristic PMEL sheet structure appears disrupted in melanoma cells expressing a PMEL-ΔRPT deletion mutant13  are good measures of the ER export efficiency, which depends on proper protein folding19.PMEL is a transmembrane glycoprotein that is exported from the endoplasmic reticulum (ER) in an immature form called P1. Along the secretory route, N-glycans undergo modifications and extensive O-glycosylation is added, resulting in a significant shift in the apparent molecular weight, giving rise to the so-called P2 form. While migrating to the plasma membrane the protein is cleaved by furin, which produces two cleavage products, the membrane-standing C-terminal Mβ fragment and the lumenal N-terminal Mα fragment13, stably expressed in the PMEL-deficient human melanoma cell line Mel220, folded well and was efficiently released from the ER . At steady state, we also found similar levels of the core amyloid fragment (CAF) accumulating in cells expressing wildtype human PMEL and the corresponding ΔRPT mutant . Because the CAF is extremely unstable in cells unless it undergoes incorporation into melanosomal amyloid13, all CAF detectable by Western blotting likely represents amyloid-associated material. Hence, consistent with our previous results13, the RPT domain is not required for amyloid formation. This result was confirmed by electron microscopy (EM), which detected vigorous, albeit somewhat reduced fibril formation for the mutant ant Fig. . Howeverein Fig. . This phein Fig.  or by hiein Fig. .top panel) and formed fibrils that were quantitatively and qualitatively indistinguishable from human PMEL  nor in the overall number of fibril-containing organelles per cell , and was quantitatively largely unaffected in fibril formation , others lack one or two segments (e.g. repeats 10 and 11 with a shortened a-b structure or repeats 12 and 15 with a shortened a-c structure)   Fig. . This pote) Fig. . The snate) Fig. .Figure 423, we wondered whether O-glycosylation may be the shared feature of RPT domains in all species. To address this, we used NetOGlyc 4.024 to predict the number of mucin-type GalNAc O-glycosylation sites in the RPT domains of mammalian, bird, reptile, amphibian, and fish PMEL. Interestingly, for all species examined the RPT domain was predicted to be extensively O-glycosylated  in the transmembrane domain to produce the functional wildtype allele. In order to obtain reptile PMEL, we cloned from one individual corn snake two alleles of the single snake PMEL gene. The two alleles differ from each other by five SNPs, one of which is silent , although the gene is almost certainly expressed (see below). The problems in detection may reflect the significantly higher GC content of chicken PMEL , potentially resulting in more stable nucleic acid secondary structures interfering with cDNA synthesis. Accordingly, unlike with other PMEL genes, we also experienced substantial problems to sequence through certain regions of the chicken PMEL cDNA (data not shown). In any case, the expression of all other foreign PMEL genes as well as human PMEL was readily detected by RT-PCR , indicating that fish PMEL is not functional in human cells. This result was particularly surprising with respect to zebrafish PMEL-A, which in contrast to its paralog PMEL-B has been shown to form functional melanosomal amyloid in fish retinal pigment epithelium (RPE)28. Nevertheless, all other PMEL proteins including chicken PMEL did form melanosomal amyloid , chicken , snake , frog , or fish  origin , chicken (PMEL-RPTGG), and snake PMEL  and PMEL-RPTPG-B ) were all able to fully substitute for the function of the human domain. Less than 7% of melanosomes harbored fibrils displaying the collapsed sheet phenotype characteristic of ΔRPT mutants  and PMEL-B (PMEL-RPTXL-B) were slightly less efficient in promoting proper sheet separation   and PMEL-B (PMEL-RPTDR-B) were much less efficient in substituting for the function of the human domain  Fig.  and thisly) Fig. . Neverthly) Fig. . Surprisain Fig. . 72% andain Fig. , and thiain Fig. . Neverthain Fig. .Figure 79. Thus, the fish RPT domain may be less able to form a functional unit with the human PKD domain in construct PMEL-RPTDR-A. To address this scenario, we generated a chimeric PMEL construct in which not only the RPT domain, but the entire MαC region in human PMEL was substituted for the corresponding zebrafish PMEL-A sequence (PMEL-MαCDR-A) .The fibril-associated MαC fragment consists of the PKD domain and the RPT domain-A) Fig. . This co-A) Fig.  and P1:M-A) Fig.  ratios a-A) Fig. . Howeverets Fig.  as constR-A Fig. . Thus, aDR-A)  Fig. . As a co-A) Fig. . Both co-A) Fig.  and form-A) Fig. . As expe-A) Fig. . This coion Fig.  as humanR-A Fig.  (84% of 30. The segment was inserted in place of the RPT domain in human PMEL (construct PMEL-RPTMUC2) , thereby somewhat reducing cleavage efficiency. In any case, significant levels of Mβ did form . As a control, ΔRPT mutants harbored 0% melanosomes with normal sheets  Fig. . The resC2) Fig. , indicatC2) Fig. . We specorm Fig. , indicatels Fig.  and fibrels Fig. . 77% of els Fig. , while 2els Fig. , panel 3ets Fig. . Thus, t34 for four days. This treatment did not affect PMEL expression or ER export . Defective pigment deposition may have significant implications for melanin detoxification. PMEL loss-of-function mutations including the Smoky allele in chickens26 and the silver mutation in mice10 are associated with reduced pigmentation similar to PMEL knockout mice39. This likely reflects reduced melanocyte viability in the absence of functional PMEL41, which is also consistent with the observation that the human PMEL locus is under purifying selection39. Defective melanin detoxification probably underlies reduced melanocyte viability in silver mice and an analogous scenario may apply in cells expressing ΔRPT mutants. If the solid ΔRPT block-like assemblies are less supportive of melanin deposition, toxic pigment precursors6 may leak out of melanosomes, causing oxidative damage to cellular proteins and DNA. Thus, the ultimate function of the RPT domain may be to mitigate pigmentation-associated toxicity.We identify the highly O-glycosylated RPT domain as the critical factor driving the formation of the PMEL amyloid sheet architecture. Specifically, we demonstrate that without the RPT domain PMEL amyloid does not organize into sheets but instead collapses into a block-like assembly Fig. . Interes28, very much unlike the well-separated sheets in mammalian organelles  resulting in significant shedding of fragments, thereby reducing the effective concentration of RPT domain in the fibrils below the threshold of adequate function. Another possibility is that the fish RPT domains do not efficiently incorporate into the PMEL matrix in the first place.Given this potentially crucial function, it is puzzling that the RPT domain is the only PMEL lumenal domain whose primary amino acid sequence is not conserved Fig. . Neverthles Fig. 5. Thus, 30. A similar mechanism may underlie the separation of PMEL amyloid sheets. O-glycans pointing away from the fibrillar layers may prevent direct sheet-sheet contact, thereby suppressing their association and collapse into a single block  may more definitively clarify the role of charge in PMEL amyloid structure, but such experiments would have to carefully control for proper incorporation of the domain into the fibrils.Moreover, RPT domains generally have a negative overall charge which is not found on the MUC2 segment. Such a negative charge may aid via electrostatic repulsion in the outward positioning of sialic acid-carrying carbohydrates and thereby support amyloid sheet separation. However, as our inhibitor experiments in Fig. 45. Alternatively, they could suppress secondary nucleation events, which often drive high amyloid toxicity46 and which likely depend on a naked amyloid surface47. We have not observed acute toxicity of our ΔRPT mutants in Mel220 cells, but more subtle phenotypes may exist and primary melanocytes may be more sensitive than a tumor cell line. Moreover, oxidative damage can cause membrane disruption and leakage48 and might synergize in a melanin-producing organelle with potential direct amyloid toxicity. Isolated cytosolic melanocores not surrounded by a membrane as well as late (but not early) melanosomes with partially disrupted membranes have been observed in melanoma cells49. Under such circumstances stable binding of toxic pigment compounds to the amyloid matrix may be particularly critical and mutants lacking the RPT domain may be very poorly protective.Finally, RPT domain glycosylation may not only be important in indirectly preventing melanin-associated toxicity (see above) but may additionally mitigate amyloid-associated toxicity in a more direct manner. Specifically, glycans could shield potentially harmful interactions between the PMEL amyloid and membranesMaintenance of and experiments on animals were approved by the Geneva Canton ethical regulation authority (authorization GE/82/14 and GE/73/16) and performed according to Swiss law. Corn snakes were bred at the LANE, University of Geneva.50, was grown in IMDM (Sigma)/10% FCS (HyClone) containing non-essential amino acids (Gibco), GlutaMax (Gibco) and penicillin/streptomycin (Gibco). PMEL transfectants were grown in medium additionally containing 2 mg/ml G418 (Gibco).LG2-MEL-220 (Mel220), a human PMEL-deficient melanoma cell linePantherophis guttatus (corn snake) PMEL, total RNA was obtained from the skin of one individual corn snake as described51 and cDNA was synthesized (AffinityScript Multi Temperature cDNA Synthesis Kit (Agilent)). Snake PMEL was then amplified by a HiFi Platinum Taq-driven PCR (Invitrogen) using primer pair 5′-ATGTCACGGATCTGGTTCCTATGGG-3′/5′-GTATCTCCCCACCCAGGCAGGC-3′. This lead to the cloning of two cDNAs corresponding to two different alleles of the single corn snake PMEL gene . The two contigs are spanning the entire open reading frame. Both mouse and snake PMEL were captured into pCR 2.1-TOPO using the TOPO TA Cloning Kit (Invitrogen). The cloned mouse PMEL (MH882516.1), snake PMEL allele A (MH882514.1), and snake PMEL allele B (MH882515.1) sequences were deposited in GenBank.Mouse PMEL was cloned by a HiFi Platinum Taq-driven PCR (Invitrogen) using primer pair 5′-TTTGGCTGCTGGCAAGAGGACC-3′/5′-CCCAGGAAATCCACGGTGCC-3′ and YUMM1.1 cDNA (murine melanoma cDNA kindly provided by Dr. J. Jacox) as a template. To clone Dominant White PMEL allele in pcDNA3.1 + /C-(K)DYK (Clone ID: OGa27055C) was purchased from Genscript. The three amino acid transmembrane insertion, which renders this allele pathogenic26, was removed using a standard QuikChange mutagenesis with primer pair 5′-CCGTGGGGCTGCTCCTCATGGCCGCTGC-3′/5′-GCAGCGGCCATGAGGAGCAGCCCCACGG-3′. Xenopus laevis PMEL-A in pCMV-SPORT6.ccdb (Clone ID: 6952781) and PMEL-B in pCMV-SPORT6 (Clone ID: 4959771) were purchased from Dharmacon. Zebrafish PMEL-A in pExpress-1 (Clone ID: BC117628) and PMEL-B (Clone ID: BC116462) were purchased from Transomic. The single EcoRI cleavage site in zebrafish PMEL-A was silently modified using an overlap extension PCR with inner primers 5′-TTTGCACGTTATCGTTCATGGAACTCACAGATGTATCCGGTCTGGAGG-3′/5′-CCTCCAGACCGGATACATCTGTGAGTTCCATGAACGATAACGTGCAAA-3′ and appropriate outer primers (Supplementary Table 19 as EcoRI-EcoRI fragments.The cDNA encoding the chicken 53), which is generally present in PMEL. This is followed by the entire C-terminal sequence of human PMEL, starting with the P4 residue of the cleavage motif (Leu-466). Thus, all chimeric constructs share the same core of the human proprotein convertase cleavage motif (residues P4 through P1)53. An analogous strategy was employed to clone construct xenopus laevis PMEL-A-RPTDR-A  in a three-step HiFi Platinum Taq-driven reaction  was cloned by a standard QuikChange mutagenesis using Xenopus PMEL-A in pBMN-IRES-neo as a template together with primer pair 5′-CTACACCATGTGGCGTGGTTATTGCAAAGC-3′/5′-GCTTTGCAATAACCACGCCACATGGTGTAG-3′. Mouse PMEL mutants ΔRPT (Δ315–402) and ΔRPTΔGlyc (Δ304–429/S299G/S302P/S303G) were cloned by a standard QuikChange mutagenesis using mouse PMEL in pBMN-IRES-neo as a template together with primer pairs 5′-GATGGCTACATGCCAGAGGGTCCAGATGC-3′/5′-GCATCTGGACCCTCTGGCATGTAGCCATC-3′ and 5′-GCCATTCCTCTTGTTGGCTGTGGTCCCGGGATAATGCTTGTGAAG-3′/5′-CTTCACAAGCATTATCCCGGGACCACAGCCAACAAGAGGAATGGC-3′, respectively.13 into Mel220 cells and selection with 2 mg/ml G418 (Gibco). The human PMEL constructs wt-PMEL and ΔRPT in pBMN-IRES-neo have been described19.All vectors were sequenced before retroviral transduction7. The rabbit polyclonal antisera 6777 and 6778 also recognize the human and mouse CAF and were raised by Genscript to a peptide with sequence SSAFTITDQVPFSVSVSQLRC (human PMEL 204–223 appended with a cysteine) conjugated to KLH. NKI-beteb (Abcam) is a mouse monoclonal antibody recognizing a conformation-sensitive epitope within PMEL54. HMB45 (NeoMarkers) is a mouse monoclonal antibody recognizing the sialylated RPT domain35. E-7 (Santa Cruz) (sc-377325) is a mouse monoclonal antibody recognizing the PMEL N-terminus8. EP4863(2) (Abcam) and EPR4864 (Abcam) are rabbit monoclonal antibodies recognizing the PMEL N-terminus (NTF)13 and the PMEL C-terminus, respectively. HRP- and fluorophore-labeled secondary antibodies were purchased from Jackson ImmunoResearch and Molecular Probes.I51 is a rabbit polyclonal antiserum recognizing the human and mouse PMEL CAF31 was purchased from Sigma Aldrich. For each experiment, a 100 mg/ml stock solution was freshly prepared in DMSO and Mel220 cells expressing human PMEL were treated for four days at a final concentration of 0.4 mg/ml. Benzyl-2-acetamido-2-deoxy-α-D-galactopyranoside had originally been described as a T synthase inhibitor34, but later work demonstrated that the compound blocked carbohydrate maturation mainly by inhibiting sialylation33.The O-glycosylation inhibitor Benzyl-2-acetamido-2-deoxy-α-D-galactopyranoside55. Briefly, 5 × 106 cells were resuspended in 1 ml 10 mM Tris-HCl pH 7.4 containing protease inhibitor  and incubated for 10 min on ice. Lysed cells were Dounce homogenized with 30 strokes (“tight” pestle) and centrifuged at 800 g/4 °C/10 min. The resulting supernatant was spun at 45,000 rpm/4 °C using the TLA-55 rotor in a Beckman Optima TL ultracentrifuge. The pellet was lysed in PBS/1% SDS/1% β-mercaptoethanol for 10 min at RT followed by 10 min at 95 °C and subjected to SDS-PAGE. Western blotting was carried out as described56.Total membranes were prepared as described57 using the antibodies NKI-beteb or EP4863(2) at a concentration of 1: 10 and 1: 100, respectively, followed by Alexa647- or Alexa488-conjugated secondary antibodies on an Accuri C6 flow cytometer.Flow cytometry was performed as described58. To amplify a fragment containing the full open reading frame of human and non-human PMEL, pBMN-IRES-neo-specific vector primers were used (5′-GACCACCCCCACCGCCCTC-3′/5′-GAATGCTCGTCAAGAAGACAGGGC-3′) in a standard Taq-driven PCR .Total RNA was extracted from Mel220 transfectants using the RNeasy Mini Kit (Qiagen) and cDNA was prepared using the AffinityScript Multi Temperature cDNA Synthesis Kit (Agilent). Actin-specific primers have been described13. For electron tomography, 15 nm fiducial gold particles were added on sections before imaging. The dual-axis tilt series was collected using a FEI Tecnai TF20 at 200 kV TEM equipped with a field emission gun. Images were recorded using SerialEM software  and a FEI Eagle 4Kx4K CCD camera. Tilting range was from −60° to 60° at 1° increments. Tomogram reconstruction, segmentation, and modeling were performed using IMOD .Cells in Petri dishes were fixed for one hour using 2.5% glutaraldehyde in 0.1 M sodium cacodylate buffer pH 7.4 containing 2% sucrose. Buffer-rinsed cells were scraped in 1% gelatin and spun down in 2% agar. Chilled blocks were trimmed and post-fixed in 1% osmium tetroxide for one hour. Next, the samples were rinsed three times in sodium cacodylate rinse buffer and post-fixed in 1% osmium tetroxide for one hour. Then they were rinsed and en-bloc stained in aqueous 2% uranyl acetate for one hour, rinsed again, dehydrated in an ethanol series, and infiltrated with Embed 812 (Electron Microscopy Sciences) resin. The samples were placed in silicone molds and baked at 60 °C for 24 hours. Hardened blocks were sectioned using a Leica UltraCut UC7. 60 nm sections were collected on Formvar-coated nickel grids and 250 nm sections were collected on copper slot grids and stained using 2% uranyl acetate and lead citrate. 60 nm sections were viewed using a FEI Tecnai Biotwin TEM at 80 kV. Images were collected using a Morada CCD camera and iTEM (Olympus) software. Fibril-containing organelles in 15 arbitrarily chosen cells in one view field per sample were counted as described previouslyMovie S1Movie S2Supplementary Material


Allosteric communication among domains in modular proteins consisting of flexibly linked domains with complimentary roles remains poorly understood. To understand how complementary domains communicate, we have studied human Pin1, a representative modular protein with two domains mutually tethered by a flexible linker: a WW domain for substrate recognition and a peptidyl-prolyl isomerase (PPIase) domain. Previous studies of Pin1 showed that physical contact between the domains causes dynamic allostery by reducing conformation dynamics in the catalytic domain, which compensates for the entropy costs of substrate binding to the catalytic site and thus increases catalytic activity. In this study, the S138A mutant PPIase domain, a mutation that mimics the structural impact of the interdomain contact, was demonstrated to display dynamic allostery by rigidification of the α2-α3 loop that harbors the key catalytic residue C113. The reduced dynamics of the α2-α3 loop stabilizes the C113–H59 hydrogen bond in the hydrogen-bonding network of the catalytic site. The stabilized hydrogen bond between C113 and H59 retards initiation of isomerization, which explains the reduced isomerization rate by ~20% caused by the S138A mutation. These results provide new insight into the interdomain allosteric communication of Pin1. P. P11]. PPrevious studies demonstrated that physical contact of the WW domain to the PPIase domain changes the conformational dynamics in the catalytic site distant from the contact interface and this change in dynamics modulates enzyme activity A 17]. B. B17]. BCrystal structures of Pin1 show that the WW and the PPIase domains contact at specific sites, which include residues H27-I28-T29 (“HIT-loop”) in the WW domain and residues in α4 and β3 of the PPIase domain A 11,20,,20,21. Ncis- and trans-locked substrates cause different conduit responses . T. T28]. T1H at Nε2 in H59. The isomerization is thought to start by disrupting the hydrogen bond between C113–H59, the stabilized hydrogen bonding at the site explains the reduced isomerization rate of the S138A mutant PPIase domain . AsThe thermal denaturation temperature for the S138A mutant increased by 6.4 °C relative to the wild-type , as moniKD, the stoichiometry was fixed to 1.0 because of the limited affinities to the substrate: the site numbers (n) recalculated with the ΔH and ΔS values gained by the above fitting procedure were n = 1.000 ± 0.001 (wild) and n = 1.021 ± 0.036 (S138A), respectively ..τc are nJ(0)–J(Nω) correlations for residues in the wild-type protein and the S138A mutant are plotted on the solid line representing Equation (1) (cτ (J(0) values for residues that are dominated by cτ in the wild-type and the S138A mutant were 3.9 ± 0.2 ns/rad and 3.6 ± 0.2 ns/rad, respectively (J(0) values within the average J(0) ± 0.5σ  values) was 79 of a possible 108 residues in the wild-type and 79 of a possible 104 residues in the S138A mutant. The re-averaged J(0) values for the selected residues were 3.9 ± 0.2 ns/rad (wild-type) and 3.7 ± 0.2 ns/rad (S138A mutant), respectively (J(0) values give the overall rotational correlation times, cτ, as 9.8 ± 0.5 ns (wild-type) and 9.3 ± 0.5 ns (S138A mutant). The lower cτ value for the S138A mutant shows that this mutant is smaller in molecular volume when compared with that of the wild-type PPIase domain (The tion (1) A. As envtion (1) , most re (1) (τc A. The avectively A. The nuectively A. J(0) ve domain A.J(0) values over the average J(0) + 0.5σ  + 0.5σ .J(0) was estimated by a difference between the experimental J(0) and the calculated Jcalc(0) using the cτ  values that can be described by two correlation times as:S0 (0 < S0 < 1.0) is used for scaling to the contribution from rapid internal motion, which is equivalent to the square order parameter, S2, in the Lipari-Szabo formalism [lτ is defined by two correlation times as 1/lτ = 1/cτ + 1/eτ [J(0)–Jcalc(0) estimated by assuming a single tumbling motion would underestimate the conformational exchange contribution to J(0), if the residue had a significant magnitude of internal motion –Jcalc(0) between the wild-type and S138A mutant without further correction to the values  and J(hω) uncovered other aspects of changes in conformational dynamics induced by the S138A mutation  calculated as J(Nω)S138A − J(Nω)wild−type for most residues in S138A mutant were positive due to the smaller cτ value of the mutant (cτ tend to have greater J(Nω) values, if the residue has minimal internal motion (J(Nω) values  values A, which ) values A.J(hω) values defined as J(hω)S138A − J(hω)wild−type showed a profile that did not correlate with that of ΔJ(Nω) (J(hω) values over the residues is also ascribed to the smaller cτ for the S138A mutant [The Δf ΔJ(ωN) B. ResiduA mutant .S138A − hNOEwild−type) showed that the residues F103–A116 are outliers that have increased hNOE values  and ΔhNOE consistently suggest that the region comprising residues F103–A116 reduced their internal dynamics on the timescale ranging from sub-ns to a few ns in the S138A mutant [The correlated profiles between the ΔA mutant .15N nuclear spin relaxation analyses described above demonstrated that the S138A mutation caused significant changes in conformational dynamics to residues in the catalytic site  spectra , two discrete signals from 15NH and 15ND components are observed, thus giving a doublet . We think the S138E mutation makes the PPIase domain too unstable and this instability impedes NMR analysis of the sample.The isolated S138E PPIase domain was used because we could avoid the requirement of the WW domain interaction with the PPIase domain. Attempts to obtain the S138E PPIase domain for the NMR analysis failed. We applied various approaches for obtaining the sample by changing the vectors, expression and purification protocols, but none of them was successful. For unknown reasons the expression of the S138E PPIase domain in As an alternative to S138E, we decided to work on the S138A mutant that is known to lose about 50% activity relative to the wild-type . We coulThe predicted dynamic allostery in the S138A mutant PPIase domain was found to be valid in the present work. Here, the S138A mutation caused significant changes to the conformational dynamics of residues within the catalytic site with limited impact on the structure. Although our dynamics changes yielded a negative effect to the catalytic rate, the S138A mutant PPIase mimics the interdomain contact state to cause dynamic allostery to modulate catalytic activity. The present analysis, therefore, gives a model to understand how dynamic allostery changes the catalytic action at the atomic level.The structure of the S138A mutant PPIase showed changes to the β2-α4 loop when compared with the wild-type structure. This was also indicated by changes in the chemical shifts when compared with those of the wild-type protein . The strThe other loops in the catalytic site including β1-α1 and α2-α3 did not show apparent structural changes in the S138A mutant, which is supported by the marginal chemical shift changes for residues in these regions of the protein . HoweverThe above observation describing changes in conformational dynamics of the loops β1-α1 and α2-α3 over a wide range of timescales caused by the S138A mutation are hypothesized to represent dynamic allostery, because the loops showed no apparent structural changes in the mutant when compared with the structure of the wild-type protein . We, theMicrosecond-long molecular dynamics (MD) simulations have revealed the change in the dynamic contacts among residues in the PPIase domain upon binding to the substrate . The simAs evident by the changes in the H/D exchange rates for residues near S138 B with th15N signals in 50% D2O solution for H59 and H157 [The dynamic allostery in the S138A mutant strengthened the hydrogen bond between C113 and H59 . In the J(hω) values  values B. The reδ1 from Nε2 [The strengthened hydrogen bond between C113 and H59 stabilized the structure of the PPIase domain A, but itfrom Nε2 . In theifrom Nε2 . AccordiThe cDNA encoding human Pin1 PPIase domain was cloned into the pET28a expression vector , as reported previously ,30. Siteθ222,obs) was used to monitor the thermal denaturing process of the proteins using a 720 W spectrometer  and a 1 mm quartz cell. The sample buffer consisted of 50 mM sodium phosphate (pH 6.0), 100 mM Na2SO4 and 1 mM dithiothreitol (DTT). The protein concentration was adjusted to 2 µM. The temperature range used was 20–80 °C, with an increment rate at 1 °C/min. The loss of helical content was calculated as follows:θ222,max and θ222,min are the maximum and minimum θ222 values in the range of 20−80 °C, respectively.The change in the molar ellipticity at 222 nm (13C/15N-labeled sample [1H resonance frequency of 700 MHz. The protein sample was dissolved in a buffer solution consisting of 50 mM sodium phosphate (pH 6.6), 100 mM Na2SO4, 5 mM EDTA, 1 mM DTT and 0.03% NaN3. The protein concentrations were 1.0 mM and the sample temperature was 299 K for all NMR experiments, unless otherwise noted. Data processing and analysis were performed with the programs NMRPipe [The structure of the S138A Pin1 PPIase domain was determined according to standard NMR methods using a uniformly d sample . All NMR NMRPipe  and KUJI NMRPipe  running  NMRPipe , respect NMRPipe ,47. Back NMRPipe . The 50  NMRPipe . The 10  NMRPipe  were usecis−trans isomerization rates of the S138A Pin1 PPIase domain were measured by 2D 1H,1H-EXSY spectroscopy [3. The experiments were carried out at 295 K. The mixing times (tmix) were 2, 5, 10, 15, 25, 35, 50 (twice), 75, 100 (twice), 200, 300 and 400 ms. The net exchange rate, kEX, was determined using the equation below (Equation (4)) to fit the ratios of the trans-to-cis exchange cross-peaks against the trans diagonal peaks:kCT and kTC are adjustable parameters in fitting and the net exchange rate, kEX, is defined as kEX = kCT + kTC, where kCT and kTC are the exchange rates from cis to trans and trans to cis, respectively [kEX values, we simultaneously used the buildup profiles from the signals for pT5 CH3, pT5 HN, and V7 HN for fitting, as in a global fitting manner. The phosphor-peptide Cdc25C was purchased from Funakoshi  and used without further purification.The troscopy ,33. The ectively . Uncerta15N R1 and R2 relaxation rates and steady state heteronuclear 15N NOE (hNOE) data were collected on the same 700.33 MHz NMR spectrometer at 299 K [R1 measurements (trelax) were 10.3 (twice), 153.9, 307.9, 461.8, 615.7 (twice), 769.6, 923.6, 1128.8 and 1539.3 ms, whereas the delays for R2 (trelax) were 0.0, 16.0 (twice), 40.0, 80.0 (twice) and 160.0 ms. Spectra for R1 and R2 were collected in an interleaved manner. For measuring hNOEs, we recorded an interleaved pair of spectra in which 1H saturation of 3 s was applied alternatively with the relaxation delay set to 2 s. R1 and R2 relaxation rate constants for each signal were determined using the modelXY TCL built-in function of NMRPipe [R1 and R2 were estimated in a Monte Carlo manner using the duplicated data points. The uncertainty for each hNOE value was evaluated using the standard deviation of the noise on a spectral region with no peaks, which was obtained by the NMRPipe built-in module [Jeff(0), J(Nω) and J(hω), were calculated using the software suite RELAX [hω represents the scaled 1H angular velocity 0.87Hω with Hω being 2π × 700.33 × 106 rad s−1 in the present work.All backbone at 299 K . Each pe NMRPipe . Uncertan module . The redte RELAX ,53; ωh r2SO4, 5 mM EDTA, 1 mM DTT and 0.03% NaN3) was rapidly frozen in liquid nitrogen and placed in a vacuum chamber for approximately 12 h. Just prior to recording a series of 2D 1H–15N HSQC spectra the lyophilized sample was dissolved in the same volume of D2O as it was before lyophilization. NMR measurements were initiated within 10 min after dissolving the sample. One spectrum was collected for 35 min and 35 data sets were collected sequentially. No apparent spectral difference was observed between the data before and after lyophilization, which ensures the preparation had no impact on the structure of the mutant. H/D exchange rates were determined through the peak intensities of a series of 2D spectra, as described in our previous work [The amide proton/deuteron exchange (H/D exchange) rates were measured with extensively lyophilized samples. The sample solution (S138A Pin1 PPIase domain in 50 mM sodium phosphate (pH 6.6), 100 mM Na−1 cm−1. All concentrations were measured on a Nanodrop 2000 . The phosphopeptide compound was weighed using an electronic microbalance CP225D . The collected data were analyzed with the Microcal ORIGIN software . The corrected binding isotherms were fitted using a single-site with the stoichiometry fixed to n = 1, because the system in this study indicated low binding-affinity [Isothermal titration calorimetry (ITC) experiments consisted of a series of 1.5 μL injections of 10 mM Cdc25C phosphor-peptide into 200 µL 0.2 mM wild-type or S138A Pin1 PPIase domain solution in the thermostatic cell with an initial delay of 60 s, a 3 s duration of injection and a spacing between injections of 150 s using a Microcal Auto iTC200 instrument . The protein concentrations were determined by absorption at 280 nm using a molar extinction coefficient of 6.99 mMaffinity ,32. All 15N chemical shifts were measured using multiple-bond 2D 1H–15N HSQC spectra for sample solutions containing 6%, 50% and 100% D2O [2O and then subjected to further lyophilization. The procedure was repeated twice to extensively purge protons from the sample. In the final sample solution containing different amounts of D2O, 5 mM EDTA, 1 mM DTT and 0.03% NaN3 were added. All NMR data were collected at 299 K.The imidazole 100% D2O . The samIn this report, the functional role of dynamic allostery in the PPIase domain of Pin1 was examined. The S138A mutation rearranged residue-residue contacts near the mutation site, which changed the conformational dynamics of the catalytic β1-α2 and α2-α3 loops that are both distal from the mutation site A. Despitγ in C113 and the Nε2 in H59 (The S138A mutation caused the α2-α3 loop to be more rigid than the wild-type domain to stabilize the hydrogen bond between C113 and H59 in the hydrogen bond network B. Proton2 in H59 B, theref2 in H59 .In summary, using the S138A mutant, we revealed that dynamic allostery affects the catalytic reaction through rearrangement of the hydrogen bond network within the catalytic site . PreviouIn this sense, it is intriguing to note that S138E mutation destabilized the PPIase domain structure. This observation may suggest that positive dynamic allostery may destabilize the hydrogen bonding network, especially at the bond formed at C113–H59, to facilitate the rearrangement in the hydrogen bonds in the network B.


The Sin3A complex acts as a transcriptional hub, integrating the function of diverse transcription factors with histone modifying enzymes, notably, histone deacetylases (HDAC) 1 and 2. The Sin3A protein sits at the centre of the complex, mediating multiple simultaneous protein-protein interactions via its four paired-amphipathic helix (PAH) domains (PAH1-4). The PAH domains contain a conserved four helical bundle, generating a hydrophobic cleft into which the single-helix of a Sin3-interaction domain (SID) is able to insert and bind with high affinity. Although they share a similar mode of interaction, the SIDs of different repressor proteins bind to only one of four potential PAH domains, due to the specific combination of hydrophobic residues at the interface. Here we report the identification of a highly conserved SID in the 5-methylcytosine dioxygenase, Tet1 (Tet1-SID), which interacts directly with the PAH1 domain of Sin3A. Using a combination of NMR spectroscopy and homology modelling we present a model of the PAH1/Tet1-SID complex, which binds in a Type-II orientation similar to Sap25. Mutagenesis of key residues show that the 11-amino acid Tet1-SID is necessary and sufficient for the interaction with Sin3A and is absolutely required for Tet1 to repress transcription in cells. The complex lacks intrinsic DNA binding activity and is therefore recruited to specific loci by transcription factors, including Mxd1, PLZF and HBP13. These factors ‘plug-in’ to the Sin3A complex via interactions mediated by four conserved paired amphipathic helix (PAH) domains (PAH1-4). PAH domains consist of a left-handed four helix bundle, forming a hydrophobic cleft into which a single helix from the transcription factor binds using specific hydrophobic and charged interactions5. While structurally similar, PAH domains have an intrinsic specificity for their binding partners. The repressor protein, Mxd1, for example, will bind tightly to Sin3A-PAH2, but not PAH1, 3 or 47. This modular array of protein docking domains enables Sin3A to form a hub of transcription factors and chromatin modifying activities in the cell. Although HDAC1/2 form the core catalytic engine of the complex, Sin3A has also been associated with other enzymatic activities, including the O-linked N-acetylglucosamine transferase (OGT8) and helicases of the Swi/Snf chromatin remodelling complex9. Sin3A has also been found to interact with the 5-methylcytosine (5mC) dioxygenase, Ten-eleven translocation 1 (Tet1)11 although thus far its mode of interaction is unknown.The Sin3A protein is the central component of the multi-protein Sin3A complex, which along with its core components, histone deacetylase 1 and 2 (HDAC1/2), regulates chromatin structure and gene expression in all eukaryotic cells12. Through a series of iterative oxidative steps, Tet1 (and its sister proteins Tet2 and Tet3) are able to partially convert 5mC to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and finally 5-carboxylcytosine (5caC), thus initiating DNA demethylation, either by passive dilution during replication or enzymatically via the base excision repair pathway14. The association of Sin3A/HDAC1 with DNA demethylation activity, which at face value are opposing epigenetic modifications, may have an important role to play in stem cells. Williams et al.11, showed that Sin3A and Tet1 co-occupy many of the same target genes in embryonic stem (ES) cells. Moreover, knockdown of Tet1 causes a loss of Sin3A recruitment, suggesting that Tet1 recruits the Sin3A complex to DNA11. Here, we have identified a highly conserved Tet1 Sin3A interaction domain (Tet1-SID) which interacts directly with the PAH1 domain of Sin3A. Using a combination of NMR spectroscopy and homology modelling we present a model of the PAH1/Tet1-SID complex, which binds in a similar orientation (type-II) to Sap25. Mutagenesis of key residues show that the 11-amino acid Tet1-SID is necessary and sufficient for the interaction with Sin3A and are absolutely required for Tet1 to repress transcription in cells.DNA methylation is a key epigenetic regulator of chromatin structure and gene expression whose pattern is maintained through cell division by DNA methyl transferase 1 (Dnmt1)et al.11, and Deplus et al.10, showed that Tet1 and Tet3 interact with Sin3A, whereas Tet2 does not. Crucially, the rationale for this differential behaviour was not identified. We therefore postulated that a yet unidentified characteristic region would be present in Tet1 and Tet3, but not in Tet2. Thus, we began by aligning Tet1, 2 and 3 and searching for conserved regions between the three proteins using the online alignment tool, Multalin15. All three proteins contain a conserved dioxygenase domain which catalyses the conversion of 5mC to 5hmC  we identified a putative Sin3 interaction domain (SID) with high similarity between Tet1 (889–903) and Tet3 (257–271), which was predicted to have a helical structure. This region was particularly outstanding since there is little or no predicted secondary structure outside of the already known dioxygenase and ZnF-CxxC domains of Tet1  containing the putative SID binds to Sin3A, whereas a C-terminal truncation of this region (746–887), or a deletion of the predicted SID helix (746–951 Δhelix1) fails to interact . As expected on the basis of the visual comparison, the largest Δδmin is obtained from the comparison of the spectra of the apo-protein and the wild-type complex (Δδmin = 0.127). Consistent with the crucial role of L897 in formation of the complex, the 15N-HSQC spectrum of the Tet1-SID L897A mutant complex showed the largest difference relative to that of the WT complex (Δδmin = 0.118). Indeed, of all mutant complexes, the 15N-HSQC spectrum of the L897A mutant most resembles that of the apo-protein , while the changes in the 15N-HSQC spectrum of I894A (Δδmin = 0.061) appear smaller compared to the effects caused by either the L897A or L900A mutations. The 15N-HSQC spectrum of T898A most resembled that of the WT complex (Δδmin = 0.026), whereas the complex with the T898E mutation only displays minor changes relative to WT (Δδmin = 0.038), indicating that the PAH1 domain is able to accommodate the bulky and charged glutamate sidechain with modest disruption. Collectively, this suggests that the importance of the contributions to the PAH1:Tet1-SID interface decreases as L897 > L900 > I894 > T898.Chemical shift changes are a sensitive probe to establish protein-protein binding, able to detect both major and more subtle changes in the structure resulting from the interaction, as well as changes in dynamics. By comparing the spectra of apo-PAH1 complexed with the Tet1-SID, or its mutants  and PAH1:REST (PDB code 2CZY18) structures. The transcriptional repressor REST binds PAH1 with the N-terminal portion of the SID pointing directly into the hydrophobic cleft (type-I), while the Sap25-SID is rotated by 180° relative to REST (type-II). Using these two structures as a starting point, we generated two models for the PAH1:Tet1 complex (see methods) and used the relative contribution of individual residues  derived model yields a compromised helix and a much less convincing interface  constructs to generate ES cell lines stably expressing full-length flag-tagged Tet1  to the Gal4-DNA binding domain and measured its ability to modulate the transcription in a reporter assay  inhibited transcription to the same degree as Gal4-MadN35. However, mutation of either L897A, or L900A completely abolished repression, strongly suggesting that the ability to suppress transcription is dependent on Sin3A recruitment, consistent with the activity of many other SID containing repressors. In agreement with its limited involvement in mediating the PAH1-Tet1 interaction , the Tet1-SID consists of a single helix with an arrangement of specific hydrophobic residues which form a lock and key interaction with one of four potential Sin3A PAH domains (PAH1-4). Mutation of critical hydrophobic residues within the TET1-SID (L897A/L900A) was sufficient to completely abolish binding of the two proteins in cells  than PAH1 alone (1–205), suggesting that there may be cooperativity between these two adjacent PAH domains, a phenomenon also observed for Mxd1-SID/PAH27. The isolated PAH1 domain, which displays a classical four helical-bundle topology in the absence of a SID19, is able to form a complex with purified Tet1-SID(878–911), resulting in a general conformational change in each domain  or type-II (Sap25) orientation which differ in a 180° rotation of the ligand relative to the PAH1 domain19. Mutagenesis experiments  may not be a limiting factor in complex assembly in cells.We have identified a highly conserved region of Tet1 which is necessary and sufficient for its interaction with Sin3A. Similar to the Sin3 interaction domain (SID) of other transcriptional repressors  and a 5mC hydroxylase , ought to have opposing effects on gene regulation. However, genome-wide ChIP experiments for HDAC1 have shown that it maps preferentially to transcriptional start sites (TSS) of active genes, questioning the conventional wisdom of HDACs exclusively leading to transcriptional repressionn3A Fig. . Tet1 iset al.30, reported the binding site of Tet1 to the Sin3A PAH1 domain, and found that the Tet1/PAH1 association was required for ES cell pluripotency. Sin3A helps recruit Tet1 to genes such as the Nodal antagonist, Lefty1, maintaining its transcriptional activity and thus preventing commitment towards a mesendodermal lineage30. These data underscore the importance of this ‘odd couple’ of chromatin modifying activities and hints at additional roles in the epigenetic regulation of gene expression.In conclusion, we have discovered a novel and highly conserved SID domain within Tet1 which is necessary and sufficient for its interaction with Sin3A. While our manuscript was under revision, Zhu Protocols, materials and constructs used in the study will be made available upon request.293 T cells were maintained in Dulbecco modified Eagle medium supplemented with 10% foetal calf serum, penicillin-streptomycin, and glutamine. Cells were transiently transfected with plasmid constructs using Lipofectamine 2000 (ThermoFisher) according to the manufacturer’s instructions. For transient repression assays, cells were plated on gelatinized 24-well tissue culture plates and then transfected with Gal4.LexA.TATA.Luc (500 ng), β-actin-LacZ control plasmid (150 ng), Gal4.Mxd1 or Gal4.Tet1-SID (100 ng), and LexA.VP16 (100 ng). A constant amount of DNA was maintained in each sample by the addition of an empty vector. At 48 h after transfection, cells were harvested and assayed for luciferase (Biovision) and β-galactosidase activities using standard protocols.31, 500 μg of whole cell extract, prepared from transfected 293 T cells, was incubated overnight at 4 °C with antibody-coated  protein-G sepharose beads in IP buffer . Following incubation, beads were washed four times in IP buffer. Captured proteins were resolved by SDS/PAGE, transferred to a nitrocellulose membrane and then probed with anti-Flag , anti-Sin3A (Ab129087) or anti-Halo Tag (Promega G921A) antisera and then scanned using a LI-COR Odyssey scanner.For co-immunoprecipitation (co-IP) experiments were performed as described previouslyet al.7. Briefly, recombinant cDNAs for mSin3A, Tet1 and their mutant derivatives were transcribed and translated in vitro using a TNT reticulocyte lysate kit (Promega) in the presence of [35S]-methionine according to the manufacturer’s instructions. GST-Tet, GST-Sap25, GST-PAH1-3 constructs and mutant derivatives were expressed in Escherichia coli DH5α and purified by using glutathione-Sepharose (GE). mSin3A proteins labelled with [35S]-methionine were incubated with the GST fusions proteins bound to Sepharose beads in a buffer containing 150 mM NaCl, 20 mM Tris (pH 8.0), 1 mM EDTA, and 0.5% IGEPAL CA-630 for 3 h and then washed three times in the same buffer. Bound proteins were analysed by SDS-PAGE and then visualized with a phosphorImager.These were based on the protocols used previously in Cowley E. coli. The latter two proteins contained an additional GB1 solubility tag. PAH1 was 15N labelled using M9 minimal media containing (15N) NH4Cl. Following IPTG induction and cellular lysis, affinity chromatography was used to elute the tagged proteins from the greater lysate. In the case of the TET1/Sap25 proteins, these were dialyzed into a 20 mM Tris-Cl pH8, 50 mM NaCl and 1 mM DTT solution using a 3500 MW membrane. The dialyzed TET1/Sap25 proteins were subsequently purified and concentrated using anion exchange chromatography. Tag removal for NMR was conducted as needed, following the dialysis, using a histidine tagged TEV protease. This permitted the separation of both the tag and the TEV from the untagged protein solution using the same nickel column.Histidine tagged Sin3A-PAH1 115–212 (PAH1), SAP25 126–186 (Sap25-SID) and TET1 878–911 (TET1-SID) were produced using BL21 Star (DE3) 15N-1H HSQC NMR spectra of the various PAH1-Tet1 complexes (1:1) were recorded at 303 K on Bruker 600 MHz AVIII, 600 MHz AVIII HD, or 800 MHz AVII spectrometers equipped with CryoProbes. Samples contained 150 µM 15N-labelled PAH1(115–212) and 150 µM unlabelled Tet1(878–911) in 20 mM Tris-HCl pH 7.4, 50 mM NaCl and 1 mM DTT, 95:5 v/v % H2O/D2O. NMR data processing was performed using TOPSPIN v3.1 and analysis using the CcpNmr Analysis32 and AnalysisAssign33 programmes. The spectra were peak-picked automatically at ~1.4 the noise level of the spectrum, followed by manual curation of spurious peaks. All peaks from the Asn, Gln NH2 sidechains were excluded from the analysis. The average minimal shift values over all peaks between two spectra, Δδmin, were used to assess the effects of mutations as proposed by Bate et al.34. It served to establish the differential effects of the mutation, i.e. the extent to which a specific residue contributes to the interaction. The Δδmin value for each spectral comparison was defined as the summed difference over all matched peaks divided by the number of peaks. Peaks were matched between the peak lists of the relevant spectra using a minimal distance algorithm . Peak distances Δδ were calculated using the common 7:1 1H:15N weighting. The whole procedure was implemented in an in-house python script using the SciPy library and the AnalysisAssign API to access the NMR data.The 19) and the PAH1:REST NMR ensemble (PDB code 2CZY18) were used as the starting point for the molecular modelling of the PAH1-Tet1 complex using the program YASARA-Structure35 (www.yasara.org). The two structures displayed a 0.9 Å backbone RMSD over the four helices. Both the Sap25-based model and the REST-based model were generated using identical procedures. First, the peptide was mutated in-silico to the homologous Tet1 residues and any major steric clashes manually resolved by sampling residue-specific preferred sidechain rotamer conformations. Next, the structure of the Tet1 peptide was optimised by a short MD simulation in H2O using the YAMBER4 force field36 and periodic boundary conditions, keeping the PAH1 part fully fixed. Next, another short MD simulation was performed, with residues in the PAH1-Tet1 interface additionally allowed to adjust. The final Sap25-based model displayed plausible overall conformational characteristics, together with a well-defined PAH1-Tet1 interface (Fig. 2. In contrast, the Tet1 peptide in the REST-based model displayed a somewhat distorted helical conformation, presumably from a non-optimal fit. Crucially, in the REST-based model T898 directly faces the hydrophobic binding pocket of the PAH1 domain, whereas it is significantly solvent exposed in the Sap25-based model.The first members of the PAH1:Sap25-SID NMR ensemble (PDB code 2RMSace Fig.  coveringSupplementary Figures