A highly efficient, stable NiAu catalyst that exhibits unprecedented low temperature activity in lignin hydrogenolysis was for the first time developed, leading to the formation of 14 wt% aromatic monomers from organosolv lignin at 170 °C in pure water.

Significance: Class I terpene synthases are essential in biosynthesis of bioactive terpenoids (e.g., Taxol). Identification of structure–function correlations is hampered by highly dynamic carbocation-driven reactions and the limited availability of catalytically relevant crystal structures. We provide the closed, catalytically active conformations of taxadiene synthase (TXS) and various taxonomically unrelated class I terpene synthases in complex with their catalytically relevant carbocationic intermediates. Our methodology allows direct prediction and validation of universal structural features that govern the highly dynamic catalytic processes of class I terpene synthases. Our data enabled delineation of a discrete reaction pathway for TXS and allowed targeted enzyme engineering to generate alternate macrocyclic core structures, which can act as synthons for bioactive lead structures.

Data sharing and reuse are crucial to enhance scientific progress and maximize return of investments in science. Although attitudes are increasingly favorable, data reuse remains difficult due to lack of infrastructures, standards, and policies. The FAIR (findable, accessible, interoperable, reusable) principles aim to provide recommendations to increase data reuse. Because of the broad interpretation of the FAIR principles, maturity indicators are necessary to determine the FAIRness of a dataset. In this work, we propose a reproducible computational workflow to assess data FAIRness in the life sciences. Our implementation follows principles and guidelines recommended by the maturity indicator authoring group and integrates concepts from the literature. In addition, we propose a FAIR balloon plot to summarize and compare dataset FAIRness. We evaluated the feasibility of our method on three real use cases where researchers looked for six datasets to answer their scientific questions. We retrieved information from repositories (ArrayExpress, Gene Expression Omnibus, eNanoMapper, caNanoLab, NanoCommons and ChEMBL), a registry of repositories, and a searchable resource (Google Dataset Search) via application program interfaces (API) wherever possible. With our analysis, we found that the six datasets met the majority of the criteria defined by the maturity indicators, and we showed areas where improvements can easily be reached. We suggest that use of standard schema for metadata and the presence of specific attributes in registries of repositories could increase FAIRness of datasets.

Management of nanomaterials and nanosafety data needs to operate under the FAIR (findability, accessibility, interoperability, and reusability) principles and this requires a unique, global identifier for each nanomaterial. Existing identifiers may not always be applicable or sufficient to definitively identify the specific nanomaterial used in a particular study, resulting in the use of textual descriptions in research project communications and reporting. To ensure that internal project documentation can later be linked to publicly released data and knowledge for the specific nanomaterials, or even to specific batches and variants of nanomaterials utilised in that project, a new identifier is proposed: the European Registry of Materials Identifier. We here describe the background to this new identifier, including FAIR interoperability as defined by FAIRSharing, identifiers.org, Bioregistry, and the CHEMINF ontology, and show how it complements other identifiers such as CAS numbers and the ongoing efforts to extend the InChI identifier to cover nanomaterials. We provide examples of its use in various H2020-funded nanosafety projects. Graphical Abstract