Stress of polymerization is one of the most significant drawbacks of dental resin composites, since it is related to poor marginal adaptation, postoperative pain, and secondary caries. Previous studies have shown that thiourethane oligomers incorporated into the organic matrix represents a promising strategy to reduce stress and increase fracture toughness in dental composites. However, this strategy promotes a significant increase of the viscosity system, which may represent a challenge for clinical application. The objective of this study was to functionalize the surface of inorganic filler particles with thiouretanes and evaluate the impact on mechanical properties and kinetics of polymerization. Our results showed that composites filled with thiourethane-silanized inorganic fillers showed up to 35% lower stress while doubling mechanical properties values. This was achieved with no prejudice to the viscosity of the material and following a clinically acceptable photoactivation protocol. Stress generation has been hypothesized to facilitate bacterial infiltration and biofilm formation at the interface between the tooth and the restoration, and when combined with composite material degradation by hydrolysis and enzymatic attack, may explain the relatively short life-time of composite restorations3. Therefore, research efforts have concentrated on modifying composition to render the composite material less prone to stress generation at the bonded interface4, and more resistant to fracture5.Resin composites are widely used for direct restorative procedures due to their esthetics and generally acceptable mechanical properties. However, composite restorations last an average of only about 10 years9 have demonstrated the potential of a relatively simple approach to improve conversion and fracture toughness of dental resin-based composites, while at the same time reducing polymerization stress. It has been shown that the addition of relatively small concentrations of thiourethane oligomers to the organic matrix of resin composites and luting cements leads to a 50–60% reduction in stress and a two-fold increase in fracture toughness6. Since the additive is simply incorporated into the traditional composite during formulation, no modification of the normal operatory technique is required, which in turn should facilitate its translation to clinical practice6. These benefits are achieved through the presence of pendant thiol functionalities on the backbone of the thiourethane additive6. As it has been widely demonstrated for thiol-ene10 and thiol methacrylate reactions11, thiols, via chain-transfer reactions, lead to delayed gelation and vitrification in vinyl-based polymer networks. This, in turn, allows for greater conversion to be achieved12, and for modulus development in the material to be delayed to higher conversion values11, ultimately leading to lower contraction stress generation. In addition, thiol-containing networks have been demonstrated to produce materials with narrow tan delta peaks in dynamic mechanical analysis11, characteristic of more homogeneous polymer networks13. This, combined with the flexibility of thio-carbamate bonds, results in increased toughness8 and reduced polymerization stress14.Recent studies6.One potential pitfall of including pre-polymerized additives, however, is the increase of viscosity, which limits the amount that can be incorporated into the monomer matrix. The addition of thiourethanes above 20 wt% in concentration increases the viscosity of the monomer mixture, which prevents the incorporation of adequate amounts of inorganic filler, and also leads to a slight decrease in elastic modulus15. Others have demonstrated the use of polymer brushes to functionalize silicon-containing surfaces16 with reported decrease in polymerization stress, as well as evidence for strengthening mechanisms such as crack deflection17. Considering the average surface coverage with conventional methacrylate silanes (about 5%) for a composite with 70 wt% filler content, it should be possible to incorporate an equivalent amount of thiorethane in the composite. In that case, the oligomer is distributed throughout the material through attachment to the filler particles, with no negative effect on the viscosity of the monomer matrix itself.One possible way to incorporate the thiourethane oligomer in the composite material and overcome the viscosity issue is to attach it directly to the surface of the filler particle via common silanization proceduresThe aim of the present study was to examine different properties of resin composites containing inorganic filler particles silanized with a thiourethane oligomer obtained by the combination of tri- and tetra-functional thiols with different isocyanates. The hypotheses of the study were: (1) Filler particles functionalized with thiourethane will be easily distributed into a resin matrix without negatively affecting kinetics of polymerization and depth of cure, and (2) fracture toughness will be improved and stress polymerization reduced in the groups with thiourethane-silanized particles.The TGA results showed that the TU fillers had at least 48.5% more organic content than the commercially obtained methacrylate-silanized filler, i.e., particles functionalized with thiourethanes showed more oligomer available on the filler surface than the commercial particles silanized with methacrylate Table .Table 1PKIC was significantly increased by the addition of thiourethane-silanized particles, and polymerization stress was significantly reduced  was dictated by an increase in viscosity, which in turn precluded the incorporation of inorganic fillers to the level necessary to produce adequate mechanical properties6. One way to possibly overcome this limitation was tested in this present study: to functionalize the thiourethane oligomers with trimethoxy silane functionality, so that the oligomer itself could be later tethered to the surface of the inorganic filler particle via common silanization procedures15. In this way, we aimed to improve the distribution of the oligomer within the composite, and to harness the same benefits obtained with the incorporation of the oligomer directly in the matrix, but without the drawback of significant increase of the viscosity. In fact, our results have shown that even for the fully formulated, highly filled composite, the viscosity average for the TU-silanized materials were similar or lower than the control groups  as compared with the methacrylate silane (around 0.25 kDa), rather than indicating a more extensive surface coverage. Other studies evaluating silicon-containing surfaces functionalized with polymer brushes found similar results and attributed the mass loss to the formation of a coat of brush heap structures at the surface18. In the current study, given the loosely crosslinked nature of the oligomer formed, the surface coating is likely less organized than a conventional polymer brush16. In any case, when the percentage of filler surface coverage was calculated based on the mass loss from the TGA experiment, the average thiourethane concentration in the six composites containing the TU filler was found to be 7.2%. This is nearly one third of the amount of TU added to the resin matrix in previous studies to produce the same effects, such as increased fracture toughness and reduced polymerization stress6.In the present study, the concentration of thiourethane used in the silanization procedure was kept constant at 2% of the total mass of the silanizing solution. The resulting fillers were characterized with thermogravimetric analysis to determine the extent of final surface coverage on the particles. It is important to note that even the unsilanized particles showed some mass loss after the test, likely due to the presence of organic contamination. The same contamination is unlikely to be present on the surface of the silanized filler particles, given the fact that the silanization process entails exposure to organic solvent in an acidic environment. In addition, the fillers were kept in sealed containers after silanization, so it is reasonable to assume that the mass loss in those cases was due to mainly the silane coating. The percent of surface functionalization based on the mass loss ranged from 5.45–9.21%, with the TU fillers showing at least 50% greater functionalization in comparison to the methacrylate control . Contrary to what was expected for the reaction rate, all of the groups containing the thiourethane-silanized filler showed equivalent or higher maximum rate of polymerization compared to the methacrylate control. However, all of the composites with TU filler showed equivalent or significantly lower DC at Rpmax. In any case, there was no significant correlation between the measured stress and the Rpmax or measured stress and DC at Rpmax. One possible explanation is that the overall concentration of thiourethane in the present study was lower, and therefore, the effects on network formation were not as marked as had been seen previously. In addition, because the incorporation of the thiourethanes to the filler surface did not affect the material’s viscosity, its effect on early mobility restrictions observed with the thiourethanes added directly into the matrix was not observed here. Even though gelation and vitrification were not directly assessed in this study, the kinetic profiles are strong indicators for those events21, and it can be speculated that these did not play a role in the decreased stress observed, which then must be explained by other factors.Degree of conversion for the TU filler composites (except for TMP-BDI) was on average 5–7% higher than for the control (SIL-MA). Previous studies have demonstrated the potential of the chain breaking events caused by the presence of thiols to delay gelation and vitrification in radical polymerizations2. The results  and DC at Rpmax . Further, the TU-silanized groups showed 4–6% higher final DC than the methacrylate-silanized control, which is in agreement with our previous results22. In combination with the depth of cure data, this shows the general ability of the thiourethanes to maintain or increase the degree of conversion and improve homogeneity of the polymer network, likely due to the chain-transfer mechanism leading to the delayed gelation/vitrification, thus maximizing the degree of conversion before the reaction becomes diffusion-controlled11. Among the tested thiourethanes, PETMP–containing materials showed higher conversion than the control at the bottom of the specimen for two out of the three groups, whereas TMP only led to higher conversion at the bottom for the combination with the DHDI isocyanate, as shown in the heat map plots. This is at least in part explained by the fact that PETMP is tetrafunctional and TMP trifunctional, which results in higher concentration of thiol functionalities pendant from the thiourethane backbone6 available on the filler surface to undergo the chain-transfer mechanism. The cyclic isocyanate DHDI led to consistently high and more uniform conversion throughout the specimen, likely because it represented an intermediate between the stiff backbone imparted by the presence of the aromatic BDI and the highly flexible backbone imparted by HDDI. Interestingly, for the more highly crosslinked PETMP-containing TUs, the use of HDDI led to higher initial DC and then essentially equivalent DC as with DHDI throughout the specimen23. As the refractive index is expected to increase with the addition of any of the TU silanes, leading to improved light transmission22, the depth of cure was expected to increase for all TU-containing groups. However, as shown on the plot for percent cure in depth in relation to the conversion at the top, two of the three PETMP are actually the lowest depth of cure in percentage, but when PETMP is paired with DHDI the depth of cure is still high. In fact, the DHDI-containing groups present the highest values in terms of cure throughout, and at the greatest depth . The TMP groups present the best percent depth of cure with DHDI, and then even slightly better than PETMP when paired with BDI and HDDI. It is important to highlight that the degree of conversion is high throughout the specimens, so these differences are likely non-clinically relevant. In summary, this study demonstrates that TU-additives are capable of maintaining the high conversion at the top throughout the specimen much more efficiently than the non-modified control, and highlights the influence of the TU structure on depth of cure.A specifically low irradiance was used for the kinetics test in order to highlight the differences between the tested thiourethanes. However, to better reproduce clinically relevant conditions, selected groups  were evaluated for polymerization kinetics under the same conditions described previously but at a much higher irradiance of 650 mW/cmlts Fig.  showed t24. However, this was not observed here, as the non-silane treated filler showed equivalent stress to the methacrylate-silane control. This suggests that the fillers acting as pores is not likely the explanation for this result. The second, and arguably the most relevant factor relates to the flexible and tough nature of the thiourethane networks, as extensively demonstrated in the literature25. It can be speculated that the presence of the TU around the filler particles acted to locally relieve the stress developed during polymerization, which then resulted in overall less stress generation in the composite. In fact, this mechanism has been proposed in other studies evaluating the efficacy of polymer brush functionalization on stress reduction at interfaces with silicon-containing materials17. Polymer brushes or tethered polymers may stretch away from the surface and accommodate for the change in free volume that accompanies polymerization27. Another possible explanation is active strand behavior, demonstrated recently for urethane-containing materials28.There was a significant 15–35% reduction in polymerization stress for materials containing thiourethane silanized filler particles. As previously mentioned, this was true in spite of the apparent lack of delayed gelation/vitrification phenomena, at least as inferred from the polymerization kinetics curves. In this case, other factors likely contributed to the reduced stress values observed. The TGA results demonstrate that the filler coverage with the thiourethane silane represents between 5.4 to 9.2% of the mass of the filler, as compared to only 3% for the methacrylate silane controls. Two factors need to be considered: 1. the same amounts by weight of each molecule were used during the silanization, and 2. each methacrylate silane molecule presents only one trimethoxy silane functionality, compared to multiple functionalities for the TU oligomer silane. Therefore, it is possible that the methacrylate silane formed a mono-layer of molecules, and the TU-silane likely formed a much thicker layer on the filler surface. Also, due to the greater complexity of the molecular structure of the TU-silane, even with a greater mass of silane, it is very unlikely that the surface was covered to the same extent as with the methacrylate silane. It follows that the stress reduction mechanism may stem from two factors. The first is the possibility for the surface of the particle to be more exposed (“unsilanized”) for the TU silane than for the methacrylate controls, which would then reduce stress because the filler particle in part actually acts as a void. This type of behavior was shown when non-silanated nanoparticles were used to fill dental composites29. Therefore, the more crosslinked material likely produced a stiffer network around the filler particle, which was then less able to relieve stress. Interestingly, the use of more rigid isocyanate precursors  did not seem to influence stress development more or less than the other TU silanes, suggesting that the structure of the TU oligomer itself, independent of its base monomer structure, had the greatest influence on stress reduction. The loss and storage modulus obtained with dynamic mechanical analysis  were dependent on the molecular structure of the precursors used to synthesize the thiourethane silanes. Overall, the groups where the tri-functional thiol (TMP) was used as a precursor exhibited lower stress than groups containing the tetra-functional thiol (PETMP), which then correlates with the likely greater degree of crosslinking provided by PETMP. This has been previously shown in studies using dynamic mechanical analysis to evaluate crosslinking (via the rubbery plateau method)31. When thiourethanes are added into the methacrylate matrix, the improvement of the mechanical properties is attributed to the flexible nature of the covalent bonds formed between the thiol on the thiourethane with the methacrylate via chain-transfer reactions8, leading to a more uniform and tougher network32. In the present study, those flexible bonds were formed around the filler particles, a region where stress concentration occurs33. This, in conjunction with the tough nature of the thio-carbamate bonds in the oligomer structure, likely led to some crack deflection or crack shielding mechanism around the particles34, as has been suggested by nanomechanical analysis of silicon interfaces treated with polymer brushes. It is also possible that the thiourethane-based silane bonding to the methacrylated matrix was more efficient due to its multiple methoxysilane functionalities, which could have enhanced the filler particle-matrix interaction leading to an increase in mechanical properties. Furthermore, fracture toughness is correlated to tensile stresses build up around the filler particles, and the efficiency of silane treatment plays an important role in gap formation35. Therefore, it can be speculated that the interfacial bonding between the organic matrix and filler particles was strong enough to resist the polymerization shrinkage, creating fewer gaps. PETMP groups showed better performance than TMP (increase between 40–85% for PETMP groups versus 0–40% for TMP groups) which may be due to PETMP being tetrafunctional while TMP is trifunctional. The greater crosslinking improved the mechanical strength of the matrix around the particles, and while that likely resulted in less efficient stress relief, as described earlier, it led to reinforcement of the material overall. The isocyanate structure did not influence the results, though a trend could be observed for increased mechanical properties and decreased polymerization stress, which could be due to the more flexible nature of this material23.The same mechanisms used to explain stress relief and ultimately overall stress reduction can be used to explain the fracture toughness results. Thiourethane silanized particle groups showed a 25–85% increase in fracture toughness compared to the control groups. Fracture toughness may be important to help predict the clinical behavior of the dental composite restoration as it is related to chipping and bulk fractureIn general, the results of this study demonstrate that the incorporation of thiourethane silanized fillers into resin composites led to increased conversion at faster rates than the control, while increasing fracture toughness, and reducing stress of polymerization. Even though the microbiological aspect was not considered on the scope of this investigation, these materials might be able to reduce gap formation, and hamper bacterial colonization at the bonded interface, ultimately helping avoid restoration failures due to secondary decay. Studies are underway utilizing a secondary caries model to test this hypothesis.The experimental composites were composed of Bis-phenol A diglycidyl dimethacrylate (Bis-GMA), urethane dimethacrylate (UDMA) and triethylene glycol dimethacrylate (TEGDMA) at a 50:30:20 mass ratio. All monomers were purchased from Esstech . Photoinitiators were added to the monomers as follows: 0.2 wt.% of dl-camphoroquinone , 0.8 wt.% of a tertiary amine , and 0.2 wt.% inhibitor .21, leaving pendant thiols and trimethoxy silanes. Oligomers were purified by precipitation in hexanes and rotoevaporation, and then characterized by mid-IR and NMR spectroscopy6. The disappearance of the isocyanate mid-IR peak at 2270 cm−1 and the appearance of NMR resonance signals at 3.70 ppm were used as evidence for completion of isocyanate reaction and thiourethane bond formation, respectively36.Six thiourethane oligomers were synthesized in solution in the presence of catalytic amounts of triethylamine. Two multi-functional thiols – pentaerythritol tetra-3-mercaptopropionate (PETMP) or trimethylol-tris-3-mercaptopropionate (TMP) – were combined with three di-functional isocyanates – 1,6-hexanediol-diissocyante (HDDI) or 1,3-bis(1-isocyanato-1-methylethyl) benzene (BDI) (aromatic) or 1-isocyanato-4-[(4-isocyanatocyclohexyl) methyl] cyclohexane (DHDI) in 60 ml of methylene chloride. In addition, 1 mol of 3-(triethoxysilyl)propyl isocyanate was also added to each of the six combinations described above – this is the source of trimethoxy silane to be used for the subsequent silanization step. The reaction was catalyzed by triethylamine. The isocyanate:thiol mol ratio was kept at 1:2.5 (with thiol in excess) to avoid macro-gelation of the oligomer during reaction, according to the Flory–Stockmayer theoryFor the silanization procedures, thiourethane oligomers were combined with 65 ml of an ethanol: distilled water solution (80:20 vol%), previously acidified by the addition of glacial acetic acid (pH = 4.5). Thiourethane was added at 2 wt%, in relation to the solution mass. Five grams of neat barium silicate glass filler  was added to the solution, kept under magnetic stirring for 24 hours, filtered, and dried for 4 days in an oven at 37 °C.The TU fillers were introduced at 50 wt% to the monomer matrix with a centrifugal mixer  operated for 2 min at 1800 rpm. All procedures were carried out under yellow light.Control groups were prepared with a commercially available unsilanized (UNS) and methacrylate-silanized (SIL-MA) barium glass filler particles . All photocuring procedures were carried out using a mercury arc lamp  filtered at 320–500 nm (light guide diameter = 5 mm). In order to verify the achieved functionalization and its efficiency, the different filler particles were analyzed by thermogravimetric analysis (TGA) over a temperature range of 50 °C to 850 °C at 10 °C/minute.KIC was determined using the single-edge notch beam method. Specimens were fabricated according to ASTM Standard E399–9037 by filling a 5 × 2.5 × 25 mm (n = 6) split steel mold with a razor blade insert providing a 2.5 mm long notch in the middle of the specimen. The resin composites were photoactivated for 2 min on each side at an irradiance of 800 mW/cm2. The light guide was kept 7 cm away from the sample and a radiometer  was used to measure the power output from the mercury arc lamp and guarantee that 800 mW/cm2 irradiance reached the top surface of the sample. The bending fracture test was performed using a universal test machine  at a cross-head speed of 0.5 mm min−1 and KIC was calculated according to the following equation (P is load at fracture (N), L is the length, W is the width, B is the thickness, and a is the notch length .38. The surface of the fused silica plate was treated with a thin layer of silane ceramic primer  and the surface of the 5 mm diameter steel piston with Z-Prime Plus . The composite was then inserted into the 1-mm gap between the upper rod and the lower glass slide and shaped into a cylinder, removing the excess. The samples were light-cured through the glass using the light curing unit for 40 s (n = 5) at 280 mW/cm2. Data were recorded for 10 min on a computer and the final shrinkage-stress calculated.Polymerization stress in real-time was analyzed using a cantilever beam apparatus (Bioman) previously described−1 39 was recorded before and after 300 s of irradiation with the light source located 4 cm from the surface of the glass slide, delivering 20 mW/cm2 directly to the specimen. Real-time monitoring of the polymerization kinetics for 300 s was carried out on specimens of the same size at 2 scans per spectrum with 4 cm−1 resolution.Three specimens (8 mm in diameter and 0.6 mm in thickness), laminated between two glass slides, were cured and then measured with near-infrared (NIR) spectroscopy  to calculate the degree of conversion (DC). The area corresponding to the methacrylate double bond overtone at 6165 cm2. After 7 days dry storage, the samples were embedded in slow curing epoxy resin and then sectioned using a diamond saw (Accutom-50) to obtain two slices of 0.4 mm thickness. The degree of conversion of the vinyl groups with depth was measured in near-IR (6165 cm−1) using an IR microscope attached to a spectrometer bench . 2D surface maps of conversion were set up with 200 µm step sizes.Samples (2 × 5 mm cross-section and 5 mm depth) were prepared using silicon molds (n = 3) and photocured through a glass slide for 300 s at 20 mW/cmViscosity was measured in a cone-plate rheometer . 1.03 g of each unpolymerized resin was placed between 20-mm diameter plates and tested at 1 Hz with a gap size of 0.3 mm (n = 3).Data for each property was tested for normality and homocedasticity , and then analyzed with one-way ANOVA and Tukey’s test for multiple comparisons. The significance level was set at 95%.Supplementary Information - Dynamic Mechanical Analysis


The concept of planetary boundaries identifies a safe space for humanity. Current energy systems are primarily designed with a focus on total cost minimization and bounds on greenhouse gas emissions. Omitting planetary boundaries in energy systems design can lead to energy mixes unable to power our sustainable development. To overcome this conceptual limitation, we here incorporate planetary boundaries into energy systems models, explicitly linking energy generation with the Earth's ecological limits. Taking the United States as a testbed, we found that the least cost energy mix that would meet the Paris Agreement 2 degrees Celsius target still transgresses five out of eight planetary boundaries. It is possible to meet seven out of eight planetary boundaries concurrently by incurring a doubling of the cost compared to the least cost energy mix solution (1.3% of the United States gross domestic product in 2017). Due to the stringent downscaled planetary boundary on biogeochemical nitrogen flow, there is no energy mix in the United States capable of satisfying all planetary boundaries concurrently. Our work highlights the importance of considering planetary boundaries in energy systems design and paves the way for further research on how to effectively accomplish such integration in energy related studies. Designing energy systems within planetary boundaries is crucial to preserving the Earth's ecological capacity given the power sector's environmental footprint. Planetary boundaries are global limits on environmental flows that should never be transgressed to prevent the occurrence of catastrophic nonlinear events challenging the Earth's ecological capacity. Motivated by the planetary boundaries concept, the World Business Council for Sustainable Development created a clear sustainable pathway known as Action2020, which reflects upon the global momentum towards a broader scope of environmental policies going beyond greenhouse gas emissions. The power sector is key to sustainability, yet it has never been studied through the lens of planetary boundaries. Energy systems are intrinsically complex due to the wide range of engineering and reliability constraints governing their behavior. Developing decision-support tools for designing energy systems meeting these constraints while operating within planetary boundaries is considered critical. Here, we provide an approach that (i) characterizes environmental flows of electricity technologies in terms of planetary boundaries contributions, (ii) downscales planetary boundaries to the regional and sectoral level and (iii) incorporates both pieces of information into energy systems models to design more sustainable energy mixes. Our approach can assist in designing energy mixes that meet planetary boundaries, while opening up new avenues for the widespread incorporation of planetary boundaries in energy related problems.1 NEMS,2 SWITCH3,4 and Electricity Systems Optimization (ESO)5 are examples of ESMs that follow the same mathematical principles and general approach while differing in the modeling assumptions and data sources.Designing sustainable energy mixes of the future is a complex task that requires the use of energy systems models (ESMs) to support decision-making. ESMs available at present identify electricity mixes that minimize the total cost while meeting a set of technical constraints, including demand satisfaction and capacity limitations. MARKAL/TIMES,6–10 is not sufficient to ensure our sustainable development, since other key environmental impacts cannot be overlooked . Hence, ESMs face at present the challenge of embracing additional environmental criteria beyond cost minimization to guide us towards sustainable energy systems. Recent works incorporated environmental impacts in ESMs following primarily Life Cycle Assessment (LCA) principles.11–14 Unfortunately, while enabling a deeper environmental analysis, the integration of LCA with ESMs fails to provide absolute bounds on the impact of an energy mix and, consequently, cannot identify sustainable energy mixes guaranteed to operate within the Earth's ecological capacity.15 Here, we present an approach to assist in the design of sustainable energy mixes based on the concept of Planetary Boundaries (PBs),16 a set of ecological limits that should never be transgressed by our planet to operate safely. Originally introduced by Rockström et al.,17 PBs on nine out of ten Earth-system Processes (ESPs) identify thresholds for humanity that, if surpassed, may trigger a series of nonlinear changes with unpredictable effects at a global scale.18 By including PBs in ESMs, we here link unambiguously the performance of electricity generation technologies with their wide environmental impact, ultimately designing energy mixes fully consistent with the Sustainable Development Goals.19,20In past years, it has become clear that reducing Greenhouse Gas (GHG) emissions6 was modified to include planetary boundaries (ERCOM with Planetary Boundaries (ERCOM-PB) henceforth) to ultimately identify mixes operating below all PBs and to analyze the economic implications thereof. We found that the Business as Usual (BAU) energy mix, i.e., the US 2012 default developments in the power sector required to meet the 2030 electricity demand, transgresses six out of the eight PBs considered, including the climate change PBs. Furthermore, the least cost energy mix, which is in line with the 2 degrees Celsius (°C) target governed by the Paris Agreement (the Paris Agreement solution henceforth), transgresses five out of the eight PBs, including those on climate change, though in this solution the magnitude of the transgression is lower. Our model could not identify any single mix satisfying all the shares of PBs assigned to the US power sector concurrently, yet seven of the eight PBs could be met simultaneously with an energy mix relying on wind (both onshore and offshore), natural gas with Carbon Capture and Storage (CCS), hydropower and Bio-energy with CCS (BECCS). This mix would incur an extra cost of 40% compared to the BAU solution (or 0.8% of the US Gross Domestic Product (GDP) in 2017), while doubling the cost of the Paris Agreement solution . This extra cost needed to improve the performance of the mix in terms of PBs would be associated with mandatory investments in relatively expensive electricity technologies, such as wind offshore, natural gas with CCS and BECCS.To demonstrate the capabilities of our approach, the United States (US) was taken as a testbed to discuss the implications of including PBs in energy systems design. Our previously developed ESM for the US, the Emissions Reduction Cooperation Model (ERCOM),via the environmental flows they generate. We discuss both challenges in detail next.When attempting to incorporate PBs into ESMs, two main challenges were addressed : (i) dowi.e., an upper bound on the total impact) that shall be respected by the US power sector in 2030 . Here, without loss of generality, we apply an egalitarian-based sharing principle,27 whereby the US power sector share of the safe operating space is quantified from the ratio of the US population to the global population times the ratio of the US power sector Gross Value Added (GVA) to the GVA of the whole US economy . Based on the first criterion, the biosphere integrity PBs and the regional PBs on land-system change, freshwater use and biogeochemical Phosphorus (P) flow were omitted. Based on the second criterion, we discarded the PB on atmospheric aerosol loading, as the current PB focuses on the Indian subcontinent.18 Similarly, the PB on the introduction of novel entities was also omitted because it has not been formally defined yet.18 This leads to the consideration of eight out of fourteen global and regional PBs on seven out of ten ESPs already identified in the literature.18Some PBs still show data and methodological gaps that prevent their full use in some practical application. Here, PBs relevant to the US energy systems were chosen based on (i) availability of the corresponding inventory entries in life cycle repositories; and (ii) applicability of the specific PB to our region of interest  that could potentially be harnessed in environmental policies. These life cycle inventories are connected to ESPs 2 concentration (ppm) and energy imbalance at top-of-atmosphere (W m−2), are used to describe climate change, which is responsible for both physical and biosphere fluctuations.17,18 GHG emissions such as CO2, CO, CH4 and NMVOC quantify the atmospheric CO2 concentration PB, while additional air emissions such as N2O, NF3, SF6, CFCs and HCFCs characterize in turn the energy imbalance PB.28Two PBs, atmospheric CO17 Ozone depleting substances remove stratospheric ozone via reaction with chlorine and bromine;29 these include air emissions such as CFCs, HCFCs, Halons and R-40.28 Although the existing method to compute PBs28 does not assign a characterization factor that quantifies the N2O impact on the stratospheric ozone depletion PB, N2O emissions do exert a noticeable pressure on the ozone layer.30 Therefore, we here expand the existing method developed by Ryberg et al.28 by designing a characterization factor that quantifies the impact of N2O emissions on the stratospheric ozone depletion PB. In essence, we first convert the N2O emissions to CFC-11 equivalent 30 and then apply the characterization factor that links CFC-11 to the stratospheric ozone depletion PB available in the existing framework.28Stratospheric ozone depletion PB, measured in Dobson Unit (DU), evaluates the role of the ozone layer in filtering ultraviolet radiation from the Sun.arag. Since marine species are vulnerable to changes in the CO2 chemistry of oceans,17 this PB is closely related to the atmospheric CO2 concentration PB. An increasing concentration of CO2 in the ocean could raise its acidity causing many aragonite shells to dissolve.17 Ocean acidification mangles marine biodiversity and, therefore, it could affect the ability of oceans to sink CO2.17,18 Similar to the atmospheric CO2 concentration PB, though using different characterization factors, the ocean acidification PB is quantified via air emissions that include CO2, CO, CH4 and NMVOC.28The ocean acidification PB is measured in Ω18 An excess amount of biogeochemical P and N flows induced by human interventions could disturb their global cycles,31,32 pushing marine systems across their tipping point.17 Global biogeochemical P flow is quantified from the P flow to freshwater; meanwhile, the biogeochemical N flow is obtained from NOx and NH3 to air, N-tot and NO3− to freshwater and NO3− to groundwater.28Freshwater eutrophication is connected to PBs that limit global biogeochemical P and Nitrogen (N) flows, measured in Tg P and Tg N, respectively.18 The global PB on land-system change imposes a lower bound on the forest cover remaining area relative to the original forest cover.18 The land-system change PB is linked to the area of forest transformation associated with a given process.28Land-system change PB, expressed as a percentage of the original forest cover, evaluates the way in which climate is regulated through the exchange of energy and water between land and the atmosphere.3, limits the consumption of blue water.18,33 This PB reflects the vulnerability of biodiversity, food and health security to global manipulation of the freshwater cycle.17 When implementing this PB into an ESM, freshwater from rivers, lakes, reservoirs and groundwater should be considered to ensure consistency with the designed PB on freshwater use.18,33The freshwater use PB, measured in kmi,j,l, connected to PBs were retrieved from the ecoinvent LCA database34,35 as well as from other specific technically sound sources36–39  minimizing the total transgression of downscaled PBs to the US power sector, while considering technical constraints relevant to energy mixes.The PBs mentioned previously were incorporated into ERCOM,The model is outlined next, while a full description of ERCOM-PB and the corresponding data sources is available in Notes S1, S2 and Table S1 ESI. Furtherp by the US power sector share of the safe operating space, PBTp is a continuous positive variable that measures by how much each downscaled PB p is transgressed, EPi,j,p is the total environmental burden generated per unit of energy supplied by each technology i in every state j linked to PB p, xi,j is a continuous variable denoting the amount of electricity supplied in 2030 by technology i in state j, SoSOSp is the US power sector absolute share of the safe operating space for every PB p derived viaAi,j is the engineering technical matrix of constraints defined for technology i in state j, ai,j is the accompanying upper bound vector for each engineering constraint  for technology i in state j and  is the set of real numbers to which variables WT, PBTp and xi,j belong.ERCOM-PB can be expressed in compact form as follows:i.e., the same breakdown of technologies as in 2012 would be implemented to cover the energy demand in 2030). The ‘Paris Agreement’ solution (S2) corresponds to the least cost solution that meets the US commitment to the Paris Agreement 2 °C target in 2030 while satisfying the same electricity demand as in the BAU solution. To obtain this mix, we solved a slight variant model of ERCOM-PB, where objective function TOT is a continuous variable that quantifies the value of the objective function to be minimized given by the summation of the total cost of electricity supply, cTi,j is the Levelized Cost of Electricity (LCOE) of technology i in state j, GWP100i,j is the 100-year Global Warming Potential (GWP100) per unit of energy generated by technology i in state j and TARG is the GWP100 target in line with the US commitment to the Paris Agreement 2 °C target in 2030. That is, PBs are not enforced, but the model needs to meet a bound on the GWP100 consistent with the Paris Agreement 2 °C target in 2030. As shall be discussed later, the model produces the same solution regardless of whether the GWP100 limit is enforced or not, that is, the minimum cost mix satisfies the Paris Agreement 2 °C target even when this condition is not included explicitly in the model. This is due to the economic competitiveness of some renewable technologies with very low carbon emissions  and minimize the total cost  is obtained as follows. We first solve ERCOM-PB tal cost , findinget al.18 and considered the main uncertainties associated with the environmental burdens  connected to PBs as well as with the LCOE values of electricity technologies  through the lens of PBs . We assu2 concentration, energy imbalance at top-of-atmosphere, ocean acidification, biogeochemical N flow, freshwater use and stratospheric ozone depletion (We found that six out of the eight PBs considered are transgressed in solution (S1), including atmospheric COepletion , which ri.e., the yellow zone in i.e., the red high risk zone in 2 concentration is transgressed by 1515 times above the limit, while energy imbalance at top-of-atmosphere is transgressed by 1442 times above the limit. They are followed by ocean acidification, transgressed by 483 times above the limit. Analyzing the contribution of the electricity technologies to PBs, we found that the deployment of coal and natural gas power plants seem to be the main reason behind the transgression of the climate change PBs and the PB on ocean acidification  mainly due to the reliance on coal power plants and, albeit to a lesser extent, natural gas plants.Though the transgression of the PB on stratospheric ozone depletion is within the uncertainty zone  under the Paris Agreement 2 °C target. The US INDC commits the nation to reduce its GWP100 by 26–28% in 2025 (or around 39% in 2030) compared to the 2005 levels. onshore . In fact2 concentration and energy imbalance at top-of-atmosphere are transgressed by 462 and 442 times above the limit, respectively, as both PBs on climate change are more stringent than the Paris Agreement 2 °C target. The PB on ocean acidification is also transgressed by 147 times above the limit. Similar to the BAU mix, the reliance of solution S2 on natural gas and, to a lesser extent, coal power plants contribute to the transgression of the climate change PBs and the PB on ocean acidification (The Paris Agreement mix (S2) would reduce the transgression of every PB ranging from 49 to 69% in contrast to the BAU mix (S1); however, the five transgressed PBs would still lie in the PBs high risk zone  and 81% compared to the BAU mix (S1). In solution S3, this transgression is mainly due to the deployment of BECCS and natural gas with CCS plants as well as the presence of nuclear plants.i.e., life cycle inventories) towards the performance of each solution in every PB is shown in Note S5 and Fig. S1 . The Paris Agreement mix is also cost optimal when no bounds on emissions are imposed, which highlights the economic40  benefits of meeting the Paris Agreement 2 °C target.The least cost solution that minimizes the transgression of PBs (S3) has the drawback of increasing the cost of electricity by 40% compared to the BAU mix (S1) while doubling the cost compared to the Paris Agreement mix (S2) . The dife.g., BECCS) than in conventional ones  deployed in solution S3 do not change substantially our economic results   are also cost advantageous in the future compared to technologies dominating currently the BAU mix  in the power sector would provide some degree of flexibility in meeting the total atmospheric CO2 concentration and ocean acidification PBs at the global level, as the power sector could offset, to some extent, the contribution of other worse-endowed sectors to these PBs. Nonetheless, with the current technological landscape in the US power sector, meeting the global biogeochemical N flow seems unattainable; this is due to the limited potential of those technologies that are competitive across all PBs, such as hydropower and wind technologies. Pathways that could improve the current potential and reliability of hydropower and wind technologies through, for example, the deployment of more affordable storage facilities45,46 could aid meeting all of the PBs concurrently.Wind onshore and offshore, natural gas with CCS and BECCS play a key role in meeting concurrently seven of the eight PBs considered in the US, while minimizing the transgression of the remaining PB on biogeochemical N flow. In fact, the ability to deploy negative emission technologies  could trade shares of PBs so one sector (or country) could operate under more stringent targets in those PBs easier to meet, while performing worse in those harder to satisfy. For example, the poor performance of energy systems in terms of biogeochemical N flow could be offset to some extent by imposing more stringent targets on other economic sectors with potential for offsetting such impact. Particularly, the power sector could exert a net negative contribution towards atmospheric COe.g., wind offshore, natural gas with CCS and BECCS) needed to meet seven of the eight PBs while minimizing the transgression of the biogeochemical N flow PB would increase the cost of electricity generation, 40% relative to the BAU solution and 100% relative to the Paris Agreement solution. These additional costs relative to the BAU and Paris Agreement mixes would constitute 0.8% and 1.3% of the US GDP in 2017, respectively. Therefore, further research to decrease the LCOE of such technologies is needed to dampen the cost of meeting PBs. In this context, other negative emissions technologies, such as Direct Air Capture (DAC),47 could also be incorporated in ERCOM-PB. We keep the exploration of this idea as part of our future work due to the current limited availability of projected economic and technical data to the future of other negative emissions technologies.The reliance on expensive technologies  to regional PBs. Lastly, global PBs on atmospheric aerosol loading and introduction of novel entities need to be quantified to sustain their safe operating space zones.Finally, urgent research is needed to design characterization factors that link life cycle inventory entries to the PBs on the two ESPs overlooked so far, namely biosphere integrity and introduction of novel entities. Similarly, characterization models need to be designed to connect life cycle inventory entries readily available in LCA repositories (BAUBusiness as usualBECCSBio-energy with carbon capture and storageCCSCarbon capture and storageDACDirect air captureERCOMEmissions reduction cooperation modelERCOM-PBEmissions reduction cooperation model with planetary boundariesESMEnergy systems modelESOElectricity systems optimizationESPEarth-system processGDPGross domestic productGHGGreenhouse gasGVAGross value addedGWP100100-year global warming potentialINDCIntended nationally determined contributionLCALife cycle assessmentLCOELevelized cost of electricityNNitrogenPPhosphorusPBPlanetary boundaryiElectricity generation technologyjStatepPlanetary boundaryReal numbersAi,ji in state jTechnical matrix of constraints for technology ai,ji in state jUpper bound vector for technology USpoweraSAssigned share of the full safe operating space to the power sector in the United StatescTi,ji in state jCost of electricity generation for technology l,pCFl to planetary boundary pCharacterization factor that links life cycle inventory entry i,j,pEPp per unit of energy supplied by technology i in state jEnvironmental burden linked to planetary boundary USGVAUnited States total gross value addedUSpowerGVAUnited States power sector gross value addedi,jGWP100i in state j100-year global warming potential per unit of energy generated by technology i,j,lLCIl generated when one unit of electricity is supplied via technology i in state jLife cycle inventory USPOPUnited States populationWorldPOPWorld populationpSOSpFull safe operating space for planetary boundary pSoSOSpUnited States power sector absolute share of the full safe operating space for planetary boundary TARG100-year global warming potential target in line with the United States commitment to the Paris Agreement 2 degrees Celsius target in 2030TOTCOSTTotal cost of electricity supplyWTTotal weighted transgression of planetary boundaries by the United States power sector share of the safe operating spacepPBTpTransgression of downscaled planetary boundary xi,ji in state jElectricity generated by technology There are no conflicts to declare.EE-012-C8EE03423K-s001


Ankyrin-3 (ANK3) is one of the few genes that have been consistently identified as associated with bipolar disorder by multiple genome-wide association studies. However, the exact molecular basis of the association remains unknown. A rare loss-of-function splice-site SNP (rs41283526*G) in a minor isoform of ANK3 (incorporating exon ENSE00001786716) was recently identified as protective of bipolar disorder and schizophrenia. This suggests that an elevated expression of this isoform may be involved in the etiology of the disorders. In this study, we used novel approaches and data sets to test this hypothesis. First, we strengthen the statistical evidence supporting the allelic association by replicating the protective effect of the minor allele of rs41283526 in three additional large independent samples . Second, we confirm the hypothesis that both bipolar and schizophrenia patients have a significantly higher expression of this isoform than controls . Third, we determine the transcription start site for this minor isoform by Pacific Biosciences sequencing of full-length cDNA and show that it is primarily expressed in the corpus callosum. Finally, we combine genotype and expression data from a large Norwegian sample of psychiatric patients and controls, and show that the risk alleles in ANK3 identified by bipolar disorder GWAS are located near the transcription start site of this isoform and are significantly associated with its elevated expression. Together, these results point to the likely molecular mechanism underlying ANK3´s association with bipolar disorder. Although clearly polygenic in nature, BD’s high heritability has enabled well-powered genome-wide association studies (GWAS) to reveal part of the genetic architecture of the disorder by identifying common genetic variants that contribute to BD risk2. However, most associated variants are located in non-coding regions and are typically, but not always3, difficult to interpret functionally. Thus, although associated variants may provide relatively strong evidence of a gene’s implication in the etiology, they typically shed little light on the underlying molecular mechanisms5.Bipolar disorder (BD) is a severe psychiatric pathology with a lifetime prevalence rate of 1–2%ANK3 gene (encoding ankyrin-G) illustrates this well. It was the first gene to be implicated in a BD GWAS study6 and the association has been confirmed by multiple subsequent studies10, yet it remains unclear which specific gene isoform mediates the association, whether it is a lowered or elevated level of functional protein which is a risk factor, or in which cell type the relevant isoform is expressed.The case of the 12. It has several alternatively spliced exons, the largest of which has historically been referred to as the “neuronal” exon and can be spliced in three different ways11, resulting in big differences in total protein mass , a rare loss-of-function splice-site variant (rs41283526*G), which is strongly protective of both BD and schizophrenia (SCZ)gth Fig. . The varANK3 transcript incorporating exon ENSE00001786716 is elevated in cases. Third, to determine the transcription start site (TSS) and cell-type specificity of this isoform. And, fourth, to investigate the relationship between the current genome-wide associated SNPs and the expression of this isoform.The present study has four tightly related aims. First, to further test the protective effect of the loss-of-function allele of rs41283526 in new independent samples to better estimate the odds ratio. Second, to directly test whether the expression of the 18, while four of them are new.In the present study, we performed allelic association tests for rs41283526 in seven independent samples and a meta-analysis. Three of these samples were used in our previous workThe samples from previous work are Norwegian (BD and SCZ) and Swedish (BD). The Swedish BD data is used unchanged , but the Norwegian samples are a merging of exome chip and TaqMan genotyped data sets. As a result, we have one Norwegian BD data set (504 cases), one Norwegian SCZ data set (411 cases), and one Norwegian control data set (369 controls).19. We identified four cohorts that fulfill these criteria: Danish BD (193 cases and 696 controls), German BD (895 cases and 2367 controls), Swedish SCZ (4822 cases and 6088 controls), and Danish SCZ (1872 cases and 1091 controls). All studies obtained informed consent from participants and obtained approval of protocols and procedures from their local Ethics Committees (Sample details in Table We set two requirements for the new samples: (1) rs41283526 needs to be present at as high a frequency as possible, thus we focus on North-European samples where the allele frequency ranges between 1.2 and 3.1 percent Table ; (2) sam20 to test for Hardy–Weinberg equilibrium . Heterogeneity statistics were computed in PLINK (Q and I2) and METAL (I2 heterogeneity test).In addition to being analyzed separately, the four new samples presented here were combined with the three samples from previous work to give a total of seven allelic association tests (four BD and three SCZ) and used in a meta-analysis. We use METALANK3 exon expression in the developmental transcriptome data set from BrainSpan22. This is a RNA-seq data set from the brains of 38 individuals with ages ranging from 5 weeks post-conception to 40 years old where tissue samples were taken from 8 to 16 structures of each brain. This data set provides a quantitation of expression levels of each exon of ANK3 in each structure at different points in human brain development. We plotted this data in Fig. We analyzed t test of higher expression in cases than controls for each of the diagnostic groups (both including and excluding carriers of rs41283526*G)  Table . DiagnosThere are three splice patterns in the region of interest (genetic ROI), as illustrated in Fig. ANK3 . Target-specific products were generated directly from first-strand cDNA products, using the QIAGEN LongRange PCR Kit  and four different forward primers placed in each of the four first exons of NK3 Fig.  and one We obtained no amplification from the TSSes of NM_001204403 or NM_001149 and multiple peak sizes in the expected ranges for NM_001204404 and NM_020987 Table . The larWe aimed to determine from which TSS the different splice patterns of the genetic ROI are expressed and their relative abundance . Since we intended to determine the exonic structures while preserving relative abundances, we avoided length amplification bias by generating shorter amplification products: we use the full-length cDNA previously generated and performed target-specific PCR using the forward primers in the first exon of NM_001204404 and NM_020987 (as these are the active TSSs) and a reverse primer three exons downstream of the ROI (rather than in the 3’ UTR). For each brain region, the two amplifications were pooled on equal volumes and sample preparation for Pacific Biosciences sequencing was performed with the SMRTbell Template Prep Kit 1.0 followed by sequencing on one flow cell of the Pacific BioSciences RS II . We obtained ~700k subreads for each brain region library Table  and S10.http://jgi.doe.gov/data-and-tools/bbtools/) with kmer length of 18 bp and edit distance of 2 (necessary because of the high error rate in Pacific Biosciences data). In both brain regions, there were a few dominant splice patterns present at 1% or more and a large number present at <1%. Of the splice patterns present at <1%, some were due to a failure to correctly detect an exon sequence due to the high error rate of the SMRT system, whereas others may reflect molecules that are present at very low concentrations. For any splice pattern present in one of the brain regions at 1% or more, we summarized the percentage of subreads corresponding to this pattern in each of the brain regions , rs41283526, and four other SNPs that are in proximity to it and in strong LD with it. We obtained summary statistics for the PGC BD GWAS from the Ricopili tool (https://data.broadinstitute.org/mpg/ricopili/). Norwegian samples were directly genotyped and imputed as previously described23. Haplotypes were inferred from the 1167 genotyped Norwegian samples using Haploview25, and haploblocks were determined using the 4 gametes rule26 (with the requirement that the 4th gamete be observed at a frequency above 1%). D’ and r2 were computed using PLINK20 with –ld option for 1167 samples and plotted in R , Sweden SCZ , and Denmark SCZ  samples , 0.51 (BD Germany), 0.81 (SCZ Sweden), 0.64 (SCZ Denmark). In our previous work, we established that rs41283526*G has a protective effect, thus the one-tailed Fisher test is the relevant metric for replication and it shows that the association is replicated in three of the four new independent samples: the Germany BD (es Table .Z-score) were all nominally significant in both BD and SCZ groups . In order to determine whether this temporal pattern is consistent between brain regions, we plot the expression level of the little exon in infants and children vs. adolescents and adults for each brain region   Table .We established that the alt-2 splice pattern is most strongly expressed in the corpus callosum by PCR amplification of cDNA generated from total RNA of seven different regions of human brain Table . The RefWe determined that only the TSSes of NM_001204404 and NM_020987 are active in the seven brain regions that we tested Table . Our Pac7. There are 22 genome-wide significant SNPs in the PGC BD phenotype association study located in ANK3. They are all in strong linkage disequilibrium, with an OR of ~1.3 and located within ~100 kbp of the TSS of NM_020987. There are no significant SNPs upstream of the TSS of NM_001204404, which suggests that the significant SNPs may control the regulation of an ANK3 isoform transcribed from the TSS of NM_020987. For each of 28 SNPs , we tested for differential expression (DE) of alt-2 in carriers vs. non-carriers of the minor allele . As expected, the protective allele rs41283526*G stands out with a highly significant lowered expression (Table We have demonstrated that (1) rs41283526*G has protective and statistically significant effect in multiple independent samples; (2) BD and SCZ patients have elevated expression of the alt-2 splice pattern in blood (even when excluding the effect of rs41283526*G); and (3) the alt-2 splice pattern is transcribed from the TSS of NM_020987 which is the dominant TSS in corpus callosum. We then sought to establish how these results relate to the existing GWAS results Fig.  and in pr2 and D’ between the tag SNPs 03 (rs12357972) and 26 (rs1938526). Moreover, these risk haplotypes are independent of rs41283526*G which is located on its own haplotype 05 in block 1 which extends into the major haplotype 01 in block 02 and 03.Four of the significant SNPs are located close to the “little” exon whereas four are upstream of the TSS. We therefore investigate the LD structure of the region to establish its influence on these results Fig. . This shp-values > 0.05 in all three diagnostic groups), so the logistic regression with conditioning on rs41283526 was not informative. This lead us to focus on the differential expression results presented above, where informative results were obtained.We did also perform a classical conditional regression analysis for rs41283526 for the BD, SCZ, and BD & SCZ diagnostic groups in the Norwegian sample (unpublished) as a second approach to studying the relationship between the BD GWAS SNPs and rs41283526. However, due to the modest sample size, none of the genome-wide associated hits from PGC BD GWAS showed significant association in the logistic regression  for BD  and SCZ  are both significant.We report replication of our previous findings, confirming the protective effect of rs41283526*G against BD and SCZ despite the fact that it is difficult to achieve statistical significance for low frequency SNPsce Table . In addi7, while the Norwegian effect (OR = 0.25) is several times stronger. However, the range of ORs is wide for BD  and for SCZ , thus making it difficult to estimate the true strength of the protective effect. There are two factors that are most likely to be driving the variance in ORs: the low frequency of rs41283526*G  rivals that of the strongest risk effects previously reported*G Table  and stud18. Finally, it may also seem illogical that dysregulation of a minor isoform of ANK3 could be the underlying cause of the gene’s association with the disorder. However, the 50% change in expression observed in heterozygote carriers18 is as likely to have physiologic effects, as similarly sized changes to the other more abundant isoforms, because it is the relative dosage of proteins that is the key.The protective effect of a loss-of-function variant may be somewhat counter-intuitive, because one typically thinks of loss-of-function as being deleterious. This is correct when considering a variant in isolation; however, if one considers the wider genetic context in which other variation may lead to pathologically high expression levels, it then becomes clear how a loss-of-function allele can restore balance. The high-effect size may also be surprising, but this is explained by the total loss-of-function of the splice site for the affected alleleANK3 expression are much lower in blood than in brain. However, as long as rank order of expression is somewhat maintained , then we expect to be able to detect significant differences between groups, if our main hypothesis is correct.Ideally we would have obtained RNA samples from the brains of the cases and controls that we had genotyped. For obvious reasons, this was not possible, so we had to rely on blood samples. We know that the absolute levels of 30 and are both characterized by psychotic symptoms.The mean expression of alt-2 is significantly elevated in SCZ and BDI relative to controls Fig.  and, cru1 and no other exon of ANK3 shows such a change in expression during post-natal development according to the BrainSpan database.The test of differential expression of alt-2 between those over and under 10 years old (Brainspan data set) shows that expression of the isoform begins in adolescence Fig. . This pr31 for the little exon peptide sequence (GNRCTWYKIPKVQEFTVK) is for an N-myristoylation site which mediates myristate attachment to an N-terminal glycine residue. In ANK3, this glycine residue is not N-terminal; however, post-translational myristoylation is known to typically occur following a caspase cleavage event resulting in the exposure of the internal glycine residue32. The C-terminal amino acids of the “medium” exon followed by this glycine residue is a possible match for a caspase cleavage site33. Further, the extended model of the myristoylation motif is 17 amino acids long34, which is a close match to the 18 amino acids of the “little” exon. Interestingly, myristate attachment to an N-terminal glycine residue acts as a membrane anchor for some soluble cytoplasmic proteins32.The function of the evolutionarily conserved peptide sequence encoded by the little exon is unknown. However, available bioinformatic structural data suggests that the peptide sequence is unstructured linker possibly containing a linear motif. The most significant hit in the Eukaryotic Linear Motif databaseANK3 transcripts shows that the RefSeq list is not complete, since it contains only one of the five isoforms that we detect, namely the most abundant isoform in the corpus callosum . Further, RefSeq suggests that the NM_001204404 isoform incorporates the alt-2 pattern, but our data show only the alt-0 and alt-1 splice patterns being expressed from this TSS.Our long read sequencing of 35. Thus, our data are consistent with the existing data obtained by conditional knock-out of ANK3 in mouse oligodendrocytes14, as they also show that the NM_020987 TSS is dominant in oligodendrocytes. The alt-2 splice pattern is not incorporated into the isoforms transcribed from the TSS of NM_001204404, which is dominant in the cerebral cortex. Axons in the cerebral cortex, and particularly the sections in layers I–III have been shown to not be myelinated36, thus sequence from this brain region provides a better indication of the RNA content of neurons. In summary, our results suggest that alt-2 is expressed in oligodendrocytes, but probably not in neurons.The alt-2 splice pattern is incorporated into the isoform transcribed from the TSS of NM_020987 and is expressed in the corpus callosum, but not in the cerebral cortex Fig. . The TSS38. There has been some suggestive evidence of molecular abnormalities at the nodes of Ranvier39, but perhaps the most compelling evidence of this comes from brain imaging data which shows the smaller size of the corpus callosum in both BD patients and their first degree relatives41, and reduced levels of myelin44. Our results indicate that, at least with regards to ANK3’s role in the etiology of BD, the elevated expression of the alt-2 splice form is most likely occurring in oligodendrocytes and probably not in neurons, and its protein product may well be located at the nodes of Ranvier since an ANK3 isoform has been detected on the glial side of the paranodes , but it strongly suggests that elevated expression of the ANK3 isoform incorporating exon ENS00001786716 may be a factor in the pathobiology of the disorder. Our analysis of human RNA data sets shows that the available data strongly support this hypothesis and previous GWAS findings are also consistent with it. Further, we provide evidence that the specific isoform is most strongly expressed in corpus callosum, which suggests that it may be in oligodendrocytes that the imbalance occurs. We look forward to future studies of the role of this specific isoform in myelination and, particularly, in the formation and maintenance of nodes of Ranvier.The loss-of-function allele rs41283526*G has a strong protective effect against both BD and SCZ that replicates in six independent samples. It is not itself a major contributing factor to the association of Supplementary material


Actin polymerization is essential for cells to migrate, as well as for various cell biological processes such as cytokinesis and vesicle traffic. This brief review describes the mechanisms underlying its different roles and recent advances in our understanding. Actin usually requires “nuclei”—preformed actin filaments—to start polymerizing, but, once initiated, polymerization continues constitutively. The field therefore has a strong focus on nucleators, in particular the Arp2/3 complex and formins. These have different functions, are controlled by contrasting mechanisms, and generate alternate geometries of actin networks. The Arp2/3 complex functions only when activated by nucleation-promoting factors such as WASP, Scar/WAVE, WASH, and WHAMM and when binding to a pre-existing filament. Formins can be individually active but are usually autoinhibited. Each is controlled by different mechanisms and is involved in different biological roles. We also describe the processes leading to actin disassembly and their regulation and conclude with four questions whose answers are important for understanding actin dynamics but are currently unanswered. Actin, one of the two core components of the eukaryotic cytoskeleton, together with tubulin, is a small globular protein that is one of the most abundant proteins in many cells. Both polymerize into filaments that are absolutely required for several aspects of normal cell physiology.Actin is best known in two structures that are connected with movement. Muscle is a stable, almost crystalline array of parallel α-actin and myosin filaments. Upon activation, the myosin molecules pull on the actin filaments, converting energy in the form of ATP to contraction. The actin of non-muscle cells, made of two slightly different isoforms (β- and γ-) is much more dynamic and complex, comprising both the fairly stable cortex and a range of highly dynamic protrusions at the edges of cells, in which actin filaments have lifetimes of tens of seconds. It remains unclear why nature uses near-identical molecules for structures with such contrasting lifetimes. A more recently appreciated feature of non-muscle actin is its role in vesicle dynamics. Vesicles of multiple classes require actin to bud and sort correctly. This review describes past and recent progress in the physiological roles of actin polymerization and how it is controlled.1. Cells overcome this kinetic barrier by employing “actin nucleation factors” that catalyze thede novo formation of actin filaments. Of the several actin nucleation factors that have been described so far, the actin-related protein 2/3 (Arp2/3) complex and formins  stable assembly of seven subunits all highly conserved in eukaryotes: Arp2, Arp3, and five other supporting subunits named ArpC1 (p40), ArpC2 (p34), ArpC3 (p21), ArpC4 (p20), and ArpC5 (p16).In vitro studies demonstrated that, rather than nucleatingde novo actin filaments, the Arp2/3 complex promotes the assembly of a new filament from the side of a pre-existing one at a 70° Y-branched angle4. Both Arp2 and Arp3 structures resemble the actin fold, and the two subunits together mimic an actin dimer from which nucleation can take place. The nascent filament is capped at its slow-growing pointed end by the complex, linking it firmly to the older filament, but is free to elongate in the fast-growing barbed direction5.The Arp2/3 complex was the first major actin nucleator to be identified6; it is believed that WASP proteins recruit actin monomers through their V region and bind Arp2/3 complex through the C and A portions7.The Arp2/3 complex alone is an inefficient nucleator: its Arp2 and Arp3 subunits are too far apart to nucleate a new filament, and its binding to the side of an actin filament is kinetically unfavorable. However, its ability to promote actin polymerization is strongly increased by the engagement of nucleation-promoting factors (NPFs). The main NPFs of the Arp2/3 complex are members of the Wiskott-Aldrich syndrome protein (WASP) family, which includes WASP and N-WASP, Scar/WAVE, WASH, WHAMM, and JMY . These NPFs contain a conserved C-terminal VCA domain, which consists of one or more verprolin homology domains (V) that bind actin monomers, and a central amphipathic linker (C) and an acidic region (A) that together bind the Arp2/3 complexIt is traditional to consider actin and the Arp2/3 complex as primarily motility proteins, but it is striking how vesicle-centered the NPF family as a whole is: Scar/WAVE is the key activator of pseudopods and lamellipods, but WASH, WHAMM, and JMY are purely vesicular, and WASP/N-WASP are now thought to have mainly endocytic roles.8. When cross-linked in this conformation, the complex is hyperactive and bypasses the need for WASP in activation. Moreover, its activity is even higher than WASP-activated Arp2/3 complex, indicating that the cross-link stabilizes an activated state of the complex. This confirms that WASP’s main activating function consists in its ability to move Arp2 and Arp3 closer in a short-pitch active conformation. More recently, these results have been extended using fluorescence spectroscopy and EM to determine the conformational changes induced by NPF binding to the Arp2/3 complex9. As earlier suspected, VCA binding causes a large conformational change that moves Arp2 closer to Arp3. Moreover, it also favors the complex binding to the side of an actin filament, leading to further rearrangements that are required for nucleation of a new actin filament.Recent work has progressed our understanding of the role of NPFs in the activation of the Arp2/3 complex. Chemical cross-linking of cysteines engineered in Arp2 and Arp3 has been used to hold yeast Arp2/3 complex in a short-pitch conformation10. Recently, these linear actin filaments generated by WDS-bound Arp2/3 complex have been found to act as initial seed filaments, upon which WASP-activated Arp2/3 complex can bind and catalyze the formation of branched actin11.WASP-activated Arp2/3 complex can nucleate new actin only when templated by an existing filament. Thus, the generation of branched actin networks has been thought to require priming by nucleators other than the Arp2/3 complex. However, a newly identified class of NPFs, named WISH/DIP/SPIN90 (WDS) proteins, may activate the Arp2/3 complex without the presence of a preformed filament and form linear filaments12 and the actin patches at the sites of clathrin-mediated endocytosis13. Actin dynamics driven by WASH have not often been consistently visualized, but, in mutants that cause excess activity, lamellipod-like actin may be seen streaming off post-lysosomes14. In addition to these well-known functions, a link between Arp2/3 complex-mediated actin assembly and mammalian autophagy has been suggested. An actin branched network generated by the Arp2/3 complex is essential for autophagosomal membrane shaping15, and two NPFs, WHAMM16 and JMY17, colocalize with autophagosome markers and play a role in autophagosome biogenesis. In particular, LC3 and stress-responsive activator of p300 (STRAP) were recently identified as regulators of JMY activity during autophagosome formation: LC3 recruits JMY to the membrane and stimulates its actin nucleation activity, while STRAP inhibits JMY and antagonizes its activation mediated by LC319.The Arp2/3 complex is unique among nucleators because it catalyzes the formation of branched filaments, instead of separate linear ones. The resulting “dendritic” network is responsible for the formation of several actin structures, including lamellipodia20. This regulation appears to be particularly important, as mitochondrial dynamics affect most cellular processes, including cell migration21 and invasion22.Thus, Arp2/3 complex-dependent actin nucleation is involved in the organization of several organelles, including endosomes, lysosomes, and autophagosomes. This list has been recently extended to include mitochondria: a crosstalk between branched actin and microtubules has been proposed to control mitochondria distribution23, but it could also be used by metastatic cells to migrate through dense tissues.The Arp2/3 complex activity has also been recently shown to be involved in the generation of a dynamic perinuclear actin network that allows cells to deform their nucleus and go through narrow pores. This mechanism is used by dendritic cells to move from peripheral tissues to lymph nodes for antigen presentation24; the second found it to be dispensable25. We consider real biology to be more nuanced. The paper by Wuet al. clearly shows that directed motion is possible under specific circumstances. Similar results—from dendritic cells lacking Scar/WAVE and therefore unable to assemble Arp2/3 complex at the leading edge26—show that directed migration is possible but hugely different from normal Arp2/3 complex-driven migration. We conclude that actin-driven migration can be driven by multiple parallel mechanisms. The Arp2/3 complex dominates the process in normal cells, but in its absence migration is possible, if too inefficient for most physiology. Curiously, inDictyostelium cells, loss of Scar/WAVE is less damaging because WASP can be repurposed and take over27. The implications for upstream signaling are complex and not understood, but this work does show that Arp2/3 complex assembly is fundamentally similar between different nucleators.One key question in recent years surrounds the essential nature—or otherwise—of Arp2/3 complex in migration. Two near-simultaneous papers, using similar cells, came to opposite conclusions. The first found that the Arp2/3 complex was absolutely essential for directed motion28). Formins were first described in 1990, following a screen to identify genes involved in mouse limb deformities29. Subsequent structural studies of these proteins identified homology domains and the link to the actin cytoskeleton was established30. Initial studies in yeast showed that formin proteins were essential for the formation of actin bundles that conferred polarity upon the cells and that this was regulated by the Rho GTPase network via the formin homology domains31. Formins were then shown to nucleate actin filaments byin vitro experiments with purified proteins, with the FH2 (formin homology 2) domain playing an essential role via its ability to bind the barbed end of actin filaments32. However, unlike other proteins which bind the barbed end and halt elongation, formins have been described as “leaky cappers”, referring to their ability to cap the filament while still allowing actin monomers to join and elongation to continue33. After nucleation, the formin FH2 domain encircles the tip of the barbed end and allows filament elongation. All formins slow elongation owing to an equilibrium between conformations that block or allow subunit addition35. This inhibition varies from about 5 to 95% depending on the formin. Delivery of actin-profilin from binding sites on FH1 domains to the barbed end can increase the rate of elongation beyond the rate of a bare filament end depending on the formin in question, its conformations, and the concentrations of profilin and other proteins35. These differences in elongation rates suggest a “gating model” in which a more open conformation of the FH2 domain favors monomer addition and therefore elongation, and a closed conformation inhibits the process35. Differing models have proposed how this inhibition and the open and closed conformations occur. Recently, simulation data focused on analysis of the gating model have suggested that the FH2 domain of formins can cause this effect by both steric blocking of actin subunits at the barbed end of the filament and changing the helical twist of the filament which interferes with availability of the binding site36.Another key player, with a contrasting role in the control of actin assembly, is the formin family of proteins (more thoroughly reviewed in37). Formins play a critical role in filopodia formation. This result is reinforced by studies of the homologous dDia2 inDictyostelium, which not only localizes to the tips of filopodia and regulates their formation but also contributes to polymerization by competing with capping proteins at the barbed end of the filaments38. dDia2 mutants have a much-reduced rate of filopod production. A recent study has shown that formins and capping proteins can bind the barbed end of actin filaments simultaneously, leading to a weakened state of binding of both39. This adds complexity to their interaction and subsequent effect on elongation, with the possibility that capping proteins can also compete with formins for binding and thereby inhibit elongation.After nucleation, the FH2 domains of the formins remain attached to the barbed end, encircling the growing filament, unlike the Arp2/3 complex, which is drawn backwards into the cell with bulk actin. The key to understanding formins is that their roles tend to be narrow: individual formins are used for specific processes, unlike the broad roles of Arp2/3 complex  activity is abolished, lamellipodial dynamics and appearance are quite different. Lamellipodia become narrower, with less intense actin filament networks at the leading edge. This disruption of FMNL2 also decreases the force generated by B16F1 cells and impacts their ability to push whilst migrating46. Taken together, these studies clearly demonstrate that the reality of actin filament assembly is not as simple as “formins nucleate filopodial actin filaments and the Arp2/3 complex nucleates lamellipodial filaments” and that they can cooperate. It is also important to remember that the Arp2/3 complex is an amplifier of existing actin, rather than a creatorab initio. Arp2/3 complex requires pre-existing (and preferably new) actin filaments to grow; formins probably provide the template.Formins can collaborate with the Arp2/3 complex. As well as their role in linear filament and filopodia formation, they are also important in the branched actin of lamellipodia. mDia2 depletion in the cell inhibits lamellipodia formation, and it was speculated that this was due to the formins protecting the growing filaments from capping proteins that would halt their protrusion47. The authors examined the growth of filopodia that were attached to fibronectin-coated beads which were under a constant pulling force and found that the adhesion to these beads and the growth caused by the force was dependent on myosin IIA and formin mDia2. When these proteins were inhibited, both the growth and the force exerted by the filopodia were significantly diminished47. This study provides a crucial insight into a new role for formin in actin dynamicsin vivo, where cells are constantly responding to forces from both within the cell and their environment.Interestingly, it appears that formins’ role in filopodia is not only to nucleate/elongate filaments but also to play a part in adhesions. A recent study sought to investigate the mechanisms by which filopodia respond to force and how this affects their adhesion to the extracellular matrixAs discussed in previous sections, cells simultaneously assemble, maintain, and disassemble actin filaments to generate a wide array of actin architectures. This complexity requires precise spatial and temporal coordination at different levels and the ability to rapidly and efficiently answer to intracellular and extracellular signals. Despite continuing progress in understanding how actin structures are assembled, less is known about how the actin nucleating systems are integrated. However, several papers in recent years have addressed this question.1. In addition, profilin distributes actin monomers between filaments nucleated by Arp2/3 complex and formins in both fission yeast49 and animal fibroblasts49. When the Arp2/3 complex is present in excess, profilin can inhibit its nucleating activity by disrupting the association between WASP proteins and actin. By doing so, it favors formin-mediated actin nucleation and maintains the homeostasis between the two main actin assembly machineries49. More generally, competition for resources is clearly fundamental to actin function: WASP, Scar/WAVE, and formins all compete for a limited pool of actin monomers, and imbalances caused by the loss of one can deregulate the others51.Arp2/3 complex and formins nucleate different actin filaments from a common limited pool of actin monomers. High concentrations of G-actin are maintained in the cell by the cooperation of actin monomer-binding proteins such as profilin and capping proteins56. During frustrated phagocytosis in mammalian macrophages, the plasma membrane enclosed by F-actin waves shows polarized distribution of both actin and lipids. In this region of plasma membrane, cortical actin is absent and the lipid composition is altered, with depletion of phosphatidylinositol 4,5-bisphosphate  and enrichment of PIP257. However, altering actin polymerization by the use of an N-WASP inhibitor causes a rapid loss of the lipid polarized distribution. This implies a positive feedback from the actin network to lipid-modifying enzymes. At the same time, the lipid composition of the plasma membrane can control and modify actin assembly.Spatial differentiation of the many actin-binding proteins is crucial for subcellular compartmentalization. Inositol lipids are essential, though their roles are complex and subject to misinterpretation. Several studies of actin waves—structures that may represent frustrated phagosomes or may be fundamental mechanisms underpinning normal protrusion dynamics—address the interplay between lipid composition of the plasma membrane and actin dynamics2 dephosphorylation, starting a cascade of reactions that alter the lipid composition of the membrane and activate the actin machinery at specific cellular locations58.The interplay between the plasma membrane and actin network is dependent not only on its phosphoinositide composition but also on its curvature. Indeed, high membrane curvature has been shown to increase PIP59. However, its mechanism of action has been opaque. One important reason for this is the large five-subunit complex in which it is found; the intact complex seems excessively large  and complicated. Rac binds to one subunit . Initially this interaction was described as a simple interaction with an N-terminal domain60, but this is complicated by the discovery of a possible second binding site61. Genetic analysis in melanoma cells andDictyostelium show the N-terminal site is essential for Scar/WAVE to function, while the second is important for its efficiency62. A second protein, CYRI, shares a similar N-terminal domain but appears to act as a competitive inhibitor that limits actin polymerization63. WASH regulation is similarly complex and similarly poorly understood. Like Scar/WAVE, WASH is found in a large five-membered complex, which, very unusually, is assembled using a dedicated chaperone64. Reports that WASH is directly regulated by small GTPases are at best controversial, but it is clearly regulated by covalent modifications like ubiquitination65.The upstream control of the NPFs has also been a mystery. The small GTPase Rac is clearly essential for the activation of the Scar/WAVE66. After nucleation of an actin filament by the Arp2/3 complex or formins, actin filaments can naturally assemble new monomers at the barbed end and disassemble monomers from the pointed end. This is a process known as actin treadmilling67, which depends on the hydrolysis of ATP bound by the assembled actin monomers and dissociation of the γ-phosphate from the terminal subunits68.Whilst the assembly of actin filaments is vigorously studied to explain how cells achieve motility, it is also necessary to understand how the filaments disassemble. However, much less is known about this. The pool of actin monomers must be maintained to allow rapid polymerization of new or existing filamentsin vitro, it cannot account for the rapid and varied extents of actin disassembly in the cell. ADF/cofilin participates in active severing of actin filaments69. The mechanism by which cofilin regulates actin turnover has been studied in detail, and it is known that the binding of cofilin to the filament induces a helical twist70. This causes an increase in flexibility of the areas of the filament bound by cofilin, leaving the unbound areas stiff71. Severing can then occur between these areas, as the difference between the bound and unbound areas puts stress on the filament72. Although cofilin has a higher affinity for ADP actin monomers than for ADP-Pi actin monomers or ATP actin monomers in the filament73, cofilin can bind the ADP-Pi actin monomers and promote the release of the γ-phosphate74.Although actin treadmilling explains the natural turnover of filaments75. The mechanism by which this occurs has been explored in different ways. One approach investigated how these proteins work together by examining the effect they have on different actin filament architectures76. Using protein micropatterning of an NPF in combination with Arp2/3 complex and actin, the authors were able to reconstruct three different kinds of actin networks: Arp2/3 complex branched networks, polarized actin cables, and non-polarized actin filaments. ADF/cofilin and Aip1 acted differently on these structures76. While ADF/cofilin alone was sufficient to disassemble the Arp2/3 complex branched networks, the addition of Aip1 was needed to act on the others. Another interesting observation was that the timing of the addition of these proteins also changed the outcome. When ADF/cofilin was added before the Aip1, the disassembly when the Aip1 was eventually added was much greater than if both proteins were added simultaneously. The authors propose that ADF/cofilin actin binding limits the rate at which Aip1 can act and that the shape change of a filament when ADF/cofilin binds acts as a scaffold for Aip1 activity. An interesting remaining study is to explore further the action of the Aip1 on disassembly after it is recruited to ADF/cofilin-bound actin76.Subsequent work showed that cofilin works in combination with actin-interacting protein 1 (Aip1), which drives disassembly through a different mechanism77. However, recent work found actin filaments in thymus extract can disassemble quickly in spite of high cofilin concentrations. The authors used imaging of single actin filaments and determined that Aip1 was responsible for this, allowing the filaments to quickly switch from a stable state to rapid disassembly78. This highlights an important mechanism by which cells can switch their actin networks from stable to unstable to allow dynamic changes in architecture. It is also now known that Aip1 binds to the side of actin filaments, possibly competing with cofilin for binding to create unbound areas that promote severing79. Further work using advanced single molecule imaging has highlighted the importance of coronin1B for this process, as it binds to actin filaments leading to the recruitment of cofilin and saturation of the filament before Aip1 promotes severing amongst the high concentration of cofilin80. The authors have since further explored this process and determined that different isoforms of tropomyosin which bind actin protect and stabilize the filaments from this process to different extents, identifying another layer of complexity to the control of disassembly81.An alternative line of research involved manipulating the concentration of cofilin. The ratio of cofilin to actin drastically changes the effect on the filament, with lower cofilin densities favoring severing and higher densities favoring stabilizationDespite the large volume of work briefly summarized in this review, we still lack a coherent picture; many individual factors that control actin are known, but it is still not possible to describe the global mechanisms that make actin appear in some places and not others. Obvious unanswered questions include:82. However, simpler organisms like yeast andDictyostelium have single forms of each subunit, so this seems a refinement for multicellular organisms rather than a fundamental feature. The Scar/WAVE and WASH complexes have only five members each but are huge (around 450 kDa) despite described functions that are achieved efficiently with single, smaller proteins. Is the large size of these complexes somehow physically important to their function? Or do they have large numbers of interactions that remain unknown?(1) Why are large complexes needed? There seems to be no logic for the Arp2/3 complex to have seven members, given our current understanding of its function. Arp2 and Arp3 have obvious roles, but it seems hugely complex to use five other subunits to connect them to an established filament. One answer may come from different subunits that modulate the complex’s behavior83); positive feedback loops can produce unpredictable and complex patterns from simple inputs.(2) How do the multiple small GTPases of the Rho, Rac, and Cdc42 families collectively regulate actin? Actin’s polymerization occurs in an extremely complex and localized architecture, but most experiments suggest that activated GTPases are rather diffusely localized. How can diffuse signals specify finely regulated structures? One possible answer is positive feedback, in which actin polymerization is the proximal stimulus for more actin polymerization. This has been generally accepted to be important since the seminal work of Vicker  However, if positive feedback is the key, how does it work? Most authors have looked at feedback at the level of signals such as small GTPases, but that cannot answer the previous question. There is presumably a mechanism by which new actin causes the initiation of yet more actin filaments, for example by the Arp2/3 complex showing a preference for free barbed ends85, VASP86, and CAP87? A range of data show each protein is fundamentally important, but each paper shows glimpses of their roles without offering a compelling mechanism. Our ultimate goal should be a complete, informative mathematical model showing how actin works during migration, as we can achieve for signaling during chemotaxis88. To construct such a model, we need a more complete understanding of all of the key components of actin signaling and their interactions.(4) Finally, what are the roles for IQGAP