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Non-ribosomal peptide synthetase (NRPS) is a diverse family of biosynthetic enzymes for the assembly of bioactive peptides. Despite advances in microbial sequencing, the lack of a consistent standard for annotating NRPS domains and modules has made data-driven discoveries challenging. To address this, we introduced a standardized architecture for NRPS, by using known conserved motifs to partition typical domains. This motif-and-intermotif standardization allowed for systematic evaluations of sequence properties from a large number of NRPS pathways, resulting in the most comprehensive cross-kingdom C domain subtype classifications to date, as well as the discovery and experimental validation of novel conserved motifs with functional significance. Furthermore, our coevolution analysis revealed important barriers associated with re-engineering NRPSs and uncovered the entanglement between phylogeny and substrate specificity in NRPS sequences. Our findings provide a comprehensive and statistically insightful analysis of NRPS sequences, opening avenues for future data-driven discoveries.

Background The incidence of total hip arthroplasty (THA) is dramatically increasing, particularly in older adults. Enhanced recovery after surgery (ERAS) has been used in the postoperative care of patients undergoing surgical treatment. Aims This study compared the effects of ERAS and regular nursing on older adult patients undergoing THA to evaluate ERAS’s potential in patients’ postoperative care. Methods Ninety older adult patients (age ≥ 60 years) who underwent THA were enrolled and randomly divided into two groups: regular and ERAS nursing strategies. The ERAS nursing strategy was optimized based on regular nursing in terms of pain management, nutrition management, intestinal preparation, drainage tube nursing, catheter nursing, and normothermia maintenance. The efficiency of the two nursing strategies was evaluated from the perspectives of postoperative pain, hospitalization conditions, hip function, daily life ability, complications, and satisfaction. Results The ERAS group showed earlier first aerofluxus, getting out of bed, and defecation; the moving distance after getting out of bed was greater than that in the regular group. The removal of urinary and drainage tubes was also earlier in the ERAS group than in the regular group. ERAS significantly alleviated postoperative pain, increased Harris scores and the Barthel index, reduced hospitalization duration and expenses, and lowered the occurrence of complications. The ERAS group also showed higher satisfaction levels than the regular group. Conclusions This single-blind randomized controlled trial showed that the ERAS nursing strategy reduced pain, length and cost of hospital stay, and incidence of complications after THA compared with regular care. Therefore, ERAS nursing strategies are recommended to improve the postoperative recovery rates in older adult patients undergoing THA.

Microbial secondary metabolites are a rich source for pharmaceutical discoveries and play crucial ecological functions. While tools exist to identify secondary metabolite clusters in genomes, precise sequence-to-function mapping remains challenging because neither function nor substrate specificity of biosynthesis enzymes can accurately be predicted. Here, we developed a knowledge-guided bioinformatic pipeline to solve these issues. We analyzed 1928 genomes of Pseudomonas bacteria and focused on iron-scavenging pyoverdines as model metabolites. Our pipeline predicted 188 chemically different pyoverdines with nearly 100% structural accuracy and the presence of 94 distinct receptor groups required for the uptake of iron-loaded pyoverdines. Our pipeline unveils an enormous yet overlooked diversity of siderophores (151 new structures) and receptors (91 new groups). Our approach, combining feature sequence with phylogenetic approaches, is extendable to other metabolites and microbial genera, and thus emerges as powerful tool to reconstruct bacterial secondary metabolism pathways based on sequence data.

In this work, we introduced a siderophore information database (SIDERTE), a digitized siderophore information database containing 649 unique structures. Leveraging this digitalized data set, we gained a systematic overview of siderophores by their clustering patterns in the chemical space. Building upon this, we developed a functional group‐based method for predicting new iron‐binding molecules with experimental validation. Expanding our approach to the collection of open natural products (COCONUT) database, we predicted a staggering 3199 siderophore candidates, showcasing remarkable structure diversity that is largely unexplored. Our study provides a valuable resource for accelerating the discovery of novel iron‐binding molecules and advancing our understanding of siderophores.

Microbes communicate and compete using small molecules, yet linking specific metabolites to visible behaviors is difficult. We combine imaging mass spectrometry, genomics, analytical chemistry, and bioassays to decode an interaction between a marine Bacillus and the pathogen Vibrio parahaemolyticus . Surfactin-like lipopeptides act at a distance to stimulate Vibrio swarming and draw cells toward the colony. Amicoumacin B accumulates at the interface and halts growth, yielding a simple “catch and kill” outcome. This study shows that the spatial localization of natural products shapes microbial behavior on surfaces and provides a general, scalable workflow that maps chemistry to phenotype. Beyond this case, the approach can be applied broadly to understand and, ultimately, tune microbial interactions relevant to marine ecosystems, aquaculture health, and microbiome engineering.

Iron is a critical yet limited nutrient for microbial growth. To scavenge iron, most microbes produce siderophores—diverse small molecules with high iron affinities. Different siderophores are specifically recognized and uptaken by corresponding recognizers, enabling targeted interventions and intriguing cheater-producer dynamics. We propose constructing a comprehensive iron interaction network, or “iron-net”, across the microbial world. Such a network offers the potentialfor precise manipulation of the microbiota, with conceivable applications in medicine, agriculture, and industry as well as advancing microbialecologyandevolutiontheories.Previously,oursuccessfulconstruction of an iron-net in the Pseudomonas genus demonstrated the feasibility of coevolution-inspired digital siderophore-typing. Enhanced by machine learning techniques and expanding sequencing data, forging such an iron-net calls for multidisciplinary collaborations and holds significant promise in addressing critical challenges in microbial communities.

Microbial secondary metabolites are a rich source for pharmaceutical discoveries and play crucial ecological functions. While tools exist to identify secondary metabolite clusters in genomes, precise sequence-to-function mapping remains challenging because neither function nor substrate specificity of biosynthesis enzymes can accurately be predicted. Here, we developed a knowledge-guided bioinformatic pipeline to solve these issues. We analyzed 1928 genomes of Pseudomonas bacteria and focused on iron-scavenging pyoverdines as model metabolites. Our pipeline predicted 188 chemically different pyoverdines with nearly 100% structural accuracy and the presence of 94 distinct receptor groups required for the uptake of iron-loaded pyoverdines. Our pipeline unveils an enormous yet overlooked diversity of siderophores (151 new structures) and receptors (91 new groups). Our approach, combining feature sequence with phylogenetic approaches, is extendable to other metabolites and microbial genera, and thus emerges as powerful tool to reconstruct bacterial secondary metabolism pathways based on sequence data.

Effective treatment of critical-sized bone defects remains challenging due to impaired osteogenesis, insufficient vascularization and oxidative stress–induced cell loss. Here, we report a chemically defined, cell-free sterosomal nanoplatform composed of sphingosine-1-phosphate (S1P) and 20(S)-hydroxycholesterol (Oxy) that integrates cytoprotective, pro-angiogenic, and osteogenic functions. S1P/Oxy sterosomes simultaneously enhance osteogenic differentiation and endothelial angiogenic activity while protecting resident cells from oxidative stress. In a rat critical-sized calvarial defect model, local administration of sterosomes promoted robust and spatially organized bone regeneration, without exogenous cells or growth factors. Mechanistically, transcriptomic and functional analyses identified ubiquitin-specific peptidase 18 (USP18) as a novel and essential mediator of sterosomal S1P-induced osteogenesis, independent of canonical S1P receptors. Notably, this effect is observed only when S1P is presented in a sterosomal assembly rather than in its free molecular form. Our work establishes a cell-free sterosomal strategy for effective bone regeneration accompanied by functional neovascularization and discovered a novel intracellular actuator for S1P. A multifunctional self-therapeutic S1P/Oxy sterosome confers cellular resilience, enhances angiogenesis, and drives S1PRs-independent osteogenesis and S1PR1-dependent angiogenesis for exogenous cell-free bone regeneration. Image created with BioRender.com, with permission. [Display omitted] •A drug-constituted sterosomal platform where S1P and Oxy co-assemble into a therapeutic nanostructure, not an inert carrier.•Supramolecular assembly reprograms S1P signaling, enabling USP18-mediated osteogenesis distinct from conventional pathways.•The sterosomal system integrates cytoprotection, angiogenisis, and osteogenesis in a single platform.•Enables effective cell-free bone regeneration in a rat critical-sized defect model.

Abstract The modular architecture of nonribosomal peptide synthetases (NRPSs) has inspired efforts to study their evolution and engineering. In this study, we analyze in detail a unique family of NRPSs from the defensive intracellular bacterial symbiont, Candidatus Endobryopsis kahalalidifaciens (Ca. E. kahalalidifaciens). We show that intensive and indiscriminate recombination events erase trivial sequence covariations induced by phylogenetic relatedness, revealing nonmodular functional constraints and clear recombination units. Moreover, we reveal unique substrate specificity determinants for multiple enzymatic domains, allowing us to accurately predict and experimentally discover the products of an orphan NRPS in Ca. E. kahalalidifaciens directly from environmental samples of its algal host. Finally, we expanded our analysis to 1,531 diverse NRPS pathways and revealed similar functional constraints to those observed in Ca. E. kahalalidifaciens’ NRPSs. Our findings reveal the sequence bases of genetic exchange, functional constraints, and substrate specificity in Ca. E. kahalalidifaciens’ NRPSs, and highlight them as a uniquely primed system for diversifying evolution.

Nonribosomal peptides are chemically and functionally diverse natural products with important applications in medicine and agriculture. Bacterial and fungal genomes contain thousands of nonribosomal peptide biosynthetic gene clusters (BGCs) of unknown function, providing a promising resource for peptide discovery. Core structural features of such peptides can be inferred by predicting the substrate(s) of adenylation (A) domains in nonribosomal peptide synthetases (NRPSs). However, existing approaches to A domain prediction rely on limited datasets and often struggle with domains selecting large substrates or from less-studied taxa. Here, we systematically curate and computationally analyse 3,254 A domains and present two new high-accuracy specificity predictors, PARAS and PARASECT. A new type of A domain with unusually high l-tryptophan specificity was identified through the application of PARAS, and intact protein mass spectrometry to the corresponding NRPS showed it to direct the production of tryptopeptin-related metabolites in Streptomyces species. Together, these technologies will accelerate the characterisation of novel NRPSs and their metabolic products.Competing Interest StatementG.L.C. is non-executive director, consultant and shareholder of ErebaGen Ltd. M.H.M. is a member of the scientific advisory board of Hexagon Bio.Footnotes* https://zenodo.org/records/13165500* https://github.com/bthedragonmaster/parasect