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Natural microbial communities are phylogenetically and metabolically diverse. In addition to underexplored organismal groups 1 , this diversity encompasses a rich discovery potential for ecologically and biotechnologically relevant enzymes and biochemical compounds 2 , 3 . However, studying this diversity to identify genomic pathways for the synthesis of such compounds 4 and assigning them to their respective hosts remains challenging. The biosynthetic potential of microorganisms in the open ocean remains largely uncharted owing to limitations in the analysis of genome-resolved data at the global scale. Here we investigated the diversity and novelty of biosynthetic gene clusters in the ocean by integrating around 10,000 microbial genomes from cultivated and single cells with more than 25,000 newly reconstructed draft genomes from more than 1,000 seawater samples. These efforts revealed approximately 40,000 putative mostly new biosynthetic gene clusters, several of which were found in previously unsuspected phylogenetic groups. Among these groups, we identified a lineage rich in biosynthetic gene clusters (‘ Candidatus Eudoremicrobiaceae’) that belongs to an uncultivated bacterial phylum and includes some of the most biosynthetically diverse microorganisms in this environment. From these, we characterized the phospeptin and pythonamide pathways, revealing cases of unusual bioactive compound structure and enzymology, respectively. Together, this research demonstrates how microbiomics-driven strategies can enable the investigation of previously undescribed enzymes and natural products in underexplored microbial groups and environments. Global ocean microbiome survey reveals the bacterial family ‘ Candidatus Eudoremicrobiaceae’, which includes some of the most biosynthetically diverse microorganisms in the ocean environment.

AlphaFold2 (ref.  1 ) has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein’s biological function often depends on multiple conformational substates 2 , and disease-causing point mutations often cause population changes within these substates 3 , 4 . We demonstrate that clustering a multiple-sequence alignment by sequence similarity enables AlphaFold2 to sample alternative states of known metamorphic proteins with high confidence. Using this method, named AF-Cluster, we investigated the evolutionary distribution of predicted structures for the metamorphic protein KaiB 5 and found that predictions of both conformations were distributed in clusters across the KaiB family. We used nuclear magnetic resonance spectroscopy to confirm an AF-Cluster prediction: a cyanobacteria KaiB variant is stabilized in the opposite state compared with the more widely studied variant. To test AF-Cluster’s sensitivity to point mutations, we designed and experimentally verified a set of three mutations predicted to flip KaiB from Rhodobacter sphaeroides from the ground to the fold-switched state. Finally, screening for alternative states in protein families without known fold switching identified a putative alternative state for the oxidoreductase Mpt53 in Mycobacterium tuberculosis . Further development of such bioinformatic methods in tandem with experiments will probably have a considerable impact on predicting protein energy landscapes, essential for illuminating biological function. An analysis of the evolutionary distribution of predicted structures for the metamorphic protein KaiB using AF-Cluster reveals that both conformations of KaiB were distributed in clusters across the KaiB family.

Microplastics (MPs) are a significant environmental health issue and increasingly greater source of concern. MPs have been detected in oceans, rivers, sediments, sewages, soil and even table salts. MPs exposure on marine organisms and humans has been documented, but information about the toxicity of MPs in mammal is limited. Here we used fluorescent and pristine polystyrene microplastics (PS-MPs) particles with two diameters (5 μm and 20 μm) to investigate the tissue distribution, accumulation, and tissue-specific health risk of MPs in mice. Results indicated that MPs accumulated in liver, kidney and gut, with a tissue-accumulation kinetics and distribution pattern that was strongly depended on the MPs particle size. In addition, analyses of multiple biochemical biomarkers and metabolomic profiles suggested that MPs exposure induced disturbance of energy and lipid metabolism as well as oxidative stress. Interestingly, blood biomarkers of neurotoxicity were also altered. Our results uncovered the distribution and accumulation of MPs across mice tissues and revealed significant alteration in several biomarkers that indicate potential toxicity from MPs exposure. Collectively, our data provided new evidence for the adverse consequences of MPs.

Intercropping has the potential to improve plant nutrition as well as crop yield. However, the exact mechanism promoting improved nutrient acquisition and the role the rhizosphere microbiome may play in this process remains poorly understood. Here, we use a peanut/maize intercropping system to investigate the role of root-associated microbiota in iron nutrition in these crops, combining microbiome profiling, strain and substance isolation and functional validation. We find that intercropping increases iron nutrition in peanut but not in maize plants and that the microbiota composition changes and converges between the two plants tested in intercropping experiments. We identify a Pseudomonas secreted siderophore, pyoverdine, that improves iron nutrition in glasshouse and field experiments. Our results suggest that the presence of siderophore-secreting Pseudomonas in peanut and maize intercropped plays an important role in iron nutrition. These findings could be used to envision future intercropping practices aiming to improve plant nutrition. Intercropping has the potential to improve plant nutrition and crop yield. Here, the authors intercrop peanut and maize and show that Pseudomonas secreted siderophore pyoverdine play an important role in plant iron nutrition.

Predicting longer-term mortality risk requires collection of clinical data, which is often cumbersome. Therefore, we use a well-standardized metabolomics platform to identify metabolic predictors of long-term mortality in the circulation of 44,168 individuals (age at baseline 18–109), of whom 5512 died during follow-up. We apply a stepwise (forward-backward) procedure based on meta-analysis results and identify 14 circulating biomarkers independently associating with all-cause mortality. Overall, these associations are similar in men and women and across different age strata. We subsequently show that the prediction accuracy of 5- and 10-year mortality based on a model containing the identified biomarkers and sex ( C -statistic = 0.837 and 0.830, respectively) is better than that of a model containing conventional risk factors for mortality ( C -statistic = 0.772 and 0.790, respectively). The use of the identified metabolic profile as a predictor of mortality or surrogate endpoint in clinical studies needs further investigation. Biomarkers that predict mortality are of interest for clinical as well as research applications. Here, the authors analyze metabolomics data from 44,168 individuals and identify key metabolites independently associated with all-cause mortality risk.

Chemical modifications of RNA have key roles in many biological processes 1 – 3 . N 7 -methylguanosine (m 7 G) is required for integrity and stability of a large subset of tRNAs 4 – 7 . The methyltransferase 1–WD repeat-containing protein 4 (METTL1–WDR4) complex is the methyltransferase that modifies G46 in the variable loop of certain tRNAs, and its dysregulation drives tumorigenesis in numerous cancer types 8 – 14 . Mutations in WDR4 cause human developmental phenotypes including microcephaly 15 – 17 . How METTL1–WDR4 modifies tRNA substrates and is regulated remains elusive 18 . Here we show,  through structural, biochemical and cellular studies of human METTL1–WDR4, that WDR4 serves as a scaffold for METTL1 and the tRNA T-arm. Upon tRNA binding, the αC region of METTL1 transforms into a helix, which together with the α6 helix secures both ends of the tRNA variable loop. Unexpectedly, we find that the predicted disordered N-terminal region of METTL1 is part of the catalytic pocket and essential for methyltransferase activity. Furthermore, we reveal that S27 phosphorylation in the METTL1 N-terminal region inhibits methyltransferase activity by locally disrupting the catalytic centre. Our results provide a molecular understanding of tRNA substrate recognition and phosphorylation-mediated regulation of METTL1–WDR4, and reveal the presumed disordered N-terminal region of METTL1 as a nexus of methyltransferase activity. Structures of the human METTL1–WDR4 complex are revealed, providing molecular insights into substrate recognition, modification and catalytic regulation by the N 7 -methylguanosine methyltransferase complex.

G-protein-coupled receptors (GPCRs) relay numerous extracellular signals by triggering intracellular signaling through coupling with G proteins and arrestins. Recent breakthroughs in the structural determination of GPCRs and GPCR–transducer complexes represent important steps toward deciphering GPCR signal transduction at a molecular level. A full understanding of the molecular basis of GPCR-mediated signaling requires elucidation of the dynamics of receptors and their transducer complexes as well as their energy landscapes and conformational transition rates. Here, we summarize current insights into the structural plasticity of GPCR–G-protein and GPCR–arrestin complexes that underlies the regulation of the receptor’s intracellular signaling profile.

Economically important softwood from conifers is mainly composed of the polysaccharides cellulose, galactoglucomannan and xylan, and the phenolic polymer, lignin. The interactions between these polymers lead to wood mechanical strength and must be overcome in biorefining. Here, we use 13 C multidimensional solid-state NMR to analyse the polymer interactions in never-dried cell walls of the softwood, spruce. In contrast to some earlier softwood cell wall models, most of the xylan binds to cellulose in the two-fold screw conformation. Moreover, galactoglucomannan alters its conformation by intimately binding to the surface of cellulose microfibrils in a semi-crystalline fashion. Some galactoglucomannan and xylan bind to the same cellulose microfibrils, and lignin is associated with both of these cellulose-bound polysaccharides. We propose a model of softwood molecular architecture which explains the origin of the different cellulose environments observed in the NMR experiments. Our model will assist strategies for improving wood usage in a sustainable bioeconomy. Understanding the interactions between the constituents of the cell walls in wood is important for understanding the mechanical properties. Here, the authors report on a solid-state NMR study of never-dried softwood, noticing differences to previous reports and develop a model of softwood architecture.

The carboxy-terminal domain (CTD) of RNA polymerase (Pol) II is an intrinsically disordered low-complexity region that is critical for pre-mRNA transcription and processing. The CTD consists of hepta-amino acid repeats varying in number from 52 in humans to 26 in yeast. Here we report that human and yeast CTDs undergo cooperative liquid phase separation, with the shorter yeast CTD forming less-stable droplets. In human cells, truncation of the CTD to the length of the yeast CTD decreases Pol II clustering and chromatin association, whereas CTD extension has the opposite effect. CTD droplets can incorporate intact Pol II and are dissolved by CTD phosphorylation with the transcription initiation factor IIH kinase CDK7. Together with published data, our results suggest that Pol II forms clusters or hubs at active genes through interactions between CTDs and with activators and that CTD phosphorylation liberates Pol II enzymes from hubs for promoter escape and transcription elongation.

Eukaryotic cells can undergo different forms of programmed cell death, many of which culminate in plasma membrane rupture as the defining terminal event 1 – 7 . Plasma membrane rupture was long thought to be driven by osmotic pressure, but it has recently been shown to be in many cases an active process, mediated by the protein ninjurin-1 8 (NINJ1). Here we resolve the structure of NINJ1 and the mechanism by which it ruptures membranes. Super-resolution microscopy reveals that NINJ1 clusters into structurally diverse assemblies in the membranes of dying cells, in particular large, filamentous assemblies with branched morphology. A cryo-electron microscopy structure of NINJ1 filaments shows a tightly packed fence-like array of transmembrane α-helices. Filament directionality and stability is defined by two amphipathic α-helices that interlink adjacent filament subunits. The NINJ1 filament features a hydrophilic side and a hydrophobic side, and molecular dynamics simulations show that it can stably cap membrane edges. The function of the resulting supramolecular arrangement was validated by site-directed mutagenesis. Our data thus suggest that, during lytic cell death, the extracellular α-helices of NINJ1 insert into the plasma membrane to polymerize NINJ1 monomers into amphipathic filaments that rupture the plasma membrane. The membrane protein NINJ1 is therefore an interactive component of the eukaryotic cell membrane that functions as an in-built breaking point in response to activation of cell death. Structural, biochemical and mutagenesis studies indicate that, in dying cells, the membrane protein NINJ1 assembles into filaments, disrupting the cell membrane.