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Over the last five years prior to the Glasgow Climate Pact 1 , 154 Parties have submitted new or updated 2030 mitigation goals in their nationally determined contributions and 76 have put forward longer-term pledges. Quantifications of the pledges before the 2021 United Nations Climate Change Conference (COP26) suggested a less than 50 per cent chance of keeping warming below 2 degrees Celsius 2 – 5 . Here we show that warming can be kept just below 2 degrees Celsius if all conditional and unconditional pledges are implemented in full and on time. Peak warming could be limited to 1.9–2.0 degrees Celsius (5%–95% range 1.4–2.8 °C) in the full implementation case—building on a probabilistic characterization of Earth system uncertainties in line with the Working Group I contribution to the Sixth Assessment Report 6 of the Intergovernmental Panel on Climate Change (IPCC). We retrospectively project twenty-first-century warming to show how the aggregate level of ambition changed from 2015 to 2021. Our results rely on the extrapolation of time-limited targets beyond 2030 or 2050, characteristics of the IPCC 1.5 °C Special Report (SR1.5) scenario database 7 and the full implementation of pledges. More pessimistic assumptions on these factors would lead to higher temperature projections. A second, independent emissions modelling framework projected peak warming of 1.8 degrees Celsius, supporting the finding that realized pledges could limit warming to just below 2 degrees Celsius. Limiting warming not only to ‘just below’ but to ‘well below’ 2 degrees Celsius or 1.5 degrees Celsius urgently requires policies and actions to bring about steep emission reductions this decade, aligned with mid-century global net-zero CO 2 emissions. If all new and updated national climate change mitigation pledges stemming from the Paris Agreement are implemented in full and on time, then 21st-century warming could be limited to just below 2 degrees Celsius.

Artificial metalloenzymes (ArMs) formed by incorporating synthetic metal catalysts into protein scaffolds have the potential to impart to chemical reactions selectivity that would be difficult to achieve using metal catalysts alone. In this work, we covalently link an alkyne-substituted dirhodium catalyst to a prolyl oligopeptidase containing a genetically encoded L-4-azidophenylalanine residue to create an ArM that catalyses olefin cyclopropanation. Scaffold mutagenesis is then used to improve the enantioselectivity of this reaction, and cyclopropanation of a range of styrenes and donor–acceptor carbene precursors were accepted. The ArM reduces the formation of byproducts, including those resulting from the reaction of dirhodium–carbene intermediates with water. This shows that an ArM can improve the substrate specificity of a catalyst and, for the first time, the water tolerance of a metal-catalysed reaction. Given the diversity of reactions catalysed by dirhodium complexes, we anticipate that dirhodium ArMs will provide many unique opportunities for selective catalysis. Artificial metalloenzymes (ArMs) have the potential to improve transition metal reactivity in complex media. Here, the authors link a dirhodium catalyst to a prolyl oligopeptidase to create an ArM that catalyzes enantioselective olefin cyclopropanation in aqueous solution.

Halocyclization of alkenes is a powerful bond-forming tool in synthetic organic chemistry and a key step in natural product biosynthesis, but catalyzing halocyclization with high enantioselectivity remains a challenging task. Identifying suitable enzymes that catalyze enantioselective halocyclization of simple olefins would therefore have significant synthetic value. Flavin-dependent halogenases (FDHs) catalyze halogenation of arene and enol(ate) substrates. Herein, we reveal that FDHs engineered to catalyze site-selective aromatic halogenation also catalyze non-native bromolactonization of olefins with high enantioselectivity and near-native catalytic proficiency. Highly selective halocyclization is achieved by characterizing and mitigating the release of HOBr from the FDH active site using a combination of reaction optimization and protein engineering. The structural origins of improvements imparted by mutations responsible for the emergence of halocyclase activity are discussed. This expansion of FDH catalytic activity presages the development of a wide range of biocatalytic halogenation reactions. Catalytic enantioselective halocyclization of alkenes is an important bond forming tool and a key step in natural product biosynthesis, but so far no examples of the enzymatic counterpart of this reaction on simple achiral olefins have been reported. Here, the authors describe examples of engineered flavin-dependent halogenases that catalyze halolactonization of olefins with high enantioselectivity and near-native catalytic activity.

Dynamic control over protein function is a central challenge in synthetic biology. To address this challenge, we describe the development of an integrated computational and experimental workflow to incorporate a metal-responsive chemical switch into proteins. Pairs of bipyridinylalanine (BpyAla) residues are genetically encoded into two structurally distinct enzymes, a serine protease and firefly luciferase, so that metal coordination biases the conformations of these enzymes, leading to reversible control of activity. Computational analysis and molecular dynamics simulations are used to rationally guide BpyAla placement, significantly reducing experimental workload, and cell-free protein synthesis coupled with high-throughput experimentation enable rapid prototyping of variants. Ultimately, this strategy yields enzymes with a robust 20-fold dynamic range in response to divalent metal salts over 24 on/off switches, demonstrating the potential of this approach. We envision that this strategy of genetically encoding chemical switches into enzymes will complement other protein engineering and synthetic biology efforts, enabling new opportunities for applications where precise regulation of protein function is critical. Dynamic control over protein function is a central challenge in synthetic biology. Here the authors present an integrated computational and experimental workflow for engineering reversible protein switches; metal-chelating unnatural amino acids genetically encoded into two conformationally dynamic enzymes to yield robust switches.

Scientifically rigorous guidance to policy makers on mitigation options for meeting the Paris Agreement long-term temperature goal requires an evaluation of long-term global-warming implications of greenhouse gas emissions pathways. Here we employ a uniform and transparent methodology to evaluate Paris Agreement compatibility of influential institutional emission scenarios from the grey literature, including those from Shell, BP, and the International Energy Agency. We compare a selection of these scenarios analysed with this methodology to the Integrated Assessment Model scenarios assessed by the Intergovernmental Panel on Climate Change. We harmonize emissions to a consistent base-year and account for all greenhouse gases and aerosol precursor emissions, ensuring a self-consistent comparison of climate variables. An evaluation of peak and end-of-century temperatures is made, with both being relevant to the Paris Agreement goal. Of the scenarios assessed, we find that only the IEA Net Zero 2050 scenario is aligned with the criteria for Paris Agreement consistency employed here. We investigate root causes for misalignment with these criteria based on the underlying energy system transformation. Here the authors present a framework to assess the temperature outcomes of decarbonization scenarios from institutions such as the IEA, BP and Shell. Scenarios are evaluated for consistency with the long-term temperature goal of the Paris Agreement.

Random mutagenesis has the potential to optimize the efficiency and selectivity of protein catalysts without requiring detailed knowledge of protein structure; however, introducing synthetic metal cofactors complicates the expression and screening of enzyme libraries, and activity arising from free cofactor must be eliminated. Here we report an efficient platform to create and screen libraries of artificial metalloenzymes (ArMs) via random mutagenesis, which we use to evolve highly selective dirhodium cyclopropanases. Error-prone PCR and combinatorial codon mutagenesis enabled multiplexed analysis of random mutations, including at sites distal to the putative ArM active site that are difficult to identify using targeted mutagenesis approaches. Variants that exhibited significantly improved selectivity for each of the cyclopropane product enantiomers were identified, and higher activity than previously reported ArM cyclopropanases obtained via targeted mutagenesis was also observed. This improved selectivity carried over to other dirhodium-catalysed transformations, including N-H, S-H and Si-H insertion, demonstrating that ArMs evolved for one reaction can serve as starting points to evolve catalysts for others.

Location information from long-duration super-pressure balloons flying in the Southern Hemisphere lower stratosphere during 2014 as part of X Project Loon are used to assess the quality of a number of different reanalyses including National Centers for Environmental Prediction Climate Forecast System version 2 (NCEP-CFSv2), European Centre for Medium-Range Weather Forecasts (ERA-Interim), NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA), and the recently released MERRA version 2. Balloon GPS location information is used to derive wind speeds which are then compared with values from the reanalyses interpolated to the balloon times and locations. All reanalysis data sets accurately describe the winds, with biases in zonal winds of less than 0.37 m s−1 and meridional biases of less than 0.08 m s−1. The standard deviation on the differences between Loon and reanalyses zonal winds is latitude-dependent, ranging between 2.5 and 3.5 m s−1, increasing equatorward. Comparisons between Loon trajectories and those calculated by applying a trajectory model to reanalysis wind fields show that MERRA-2 wind fields result in the most accurate simulated trajectories with a mean 5-day balloon–reanalysis trajectory separation of 621 km and median separation of 324 km showing significant improvements over MERRA version 1 and slightly outperforming ERA-Interim. The latitudinal structure of the trajectory statistics for all reanalyses displays marginally lower mean separations between 15 and 35° S than between 35 and 55° S, despite standard deviations in the wind differences increasing toward the equator. This is shown to be related to the distance travelled by the balloon playing a role in the separation statistics.

Polysaccharides comprise an extremely important class of biopolymers that play critical roles in a wide range of biological processes, but the synthesis of these compounds is challenging because of their complex structures. We have developed a chemoenzymatic method for regioselective deprotection of monosaccharide substrates using engineered Bacillus megaterium cytochrome P450 (P450BM₃) demethylases that provides a highly efficient means to access valuable intermediates, which can be converted to a wide range of substituted monosaccharides and polysaccharides. Demethylases displaying high levels of regioselectivity toward a number of protected monosaccharides were identified using a combination of protein and substrate engineering, suggesting that this approach ultimately could be used in the synthesis of a wide range of substituted mono- and polysaccharides for studies in chemistry, biology, and medicine.

Diversification of structurally complex natural products remains a key challenge in the discovery of next-generation therapeutics. Premarineosin A, a potent and selective antimalarial natural product, is a promising yet underexplored scaffold due to its limited availability and synthetic complexity. In this work, we overcome both barriers by coupling metabolic engineering with late-stage derivatization, enabling the first systematic exploration of the premarineosin A scaffold. Rational engineering of Streptomyces eitanensis , encoding a premarineosin A biosynthetic gene cluster, increased titers over 170-fold. Sustainable production of (−)-premarineosin A enabled a unique semi-synthetic and biocatalytic derivatization campaign. In this structure-activity relationship study of premarineosin A, we accessed a suite of analogs, including a C12-brominated derivative with nanomolar potency (EC 50  < 5 nM). This work establishes (−)-premarineosin A as a tractable and evolvable antimalarial scaffold, demonstrating how chemical biology approaches can unlock structural and pharmacological space from complex microbial metabolites. Premarineosin A, a potent and selective antimalarial natural product, is a promising yet underexplored scaffold due to its limited availability and synthetic complexity. Here, the authors employ metabolic engineering and late-stage functionalization to enhance the production of premarineosin A and unveil analogs with enhanced potency.

The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text‐based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non‐specialists to access CMIP data in a new, user‐friendly way. We present a dataset of annual, monthly, global‐, hemispheric‐ and land/ocean means derived from a selection of CMIP5/CMIP6 experiments of key interest to climate data analysts and reduced complexity climate modellers. Our dataset is orders of magnitude smaller than the source data and hence does not require specialised ‘big data’ or netCDF expertise. We enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, i.e. identified as erroneous.