Polyethylene terephthalate (PET) hydrolases have been extensively studied for their potential applications in plastic degradation. However, the structural and mechanistic factors that limit their catalytic efficiency are not yet fully understood. Here, we identify the protruding, surface-exposed C-terminal loop (SEC-loop) in Cryptosporangium aurantiacum PETase (CaPETase) that negatively impacts enzymatic activity by restricting productive access of enzyme to PET. Loop replacement experiments show the non-protruding SEC-loop enhances PET depolymerization rates, despite being ~25 Å from the active site. Kinetic and adsorption studies indicate the non-protruding SEC-loop promotes productive PET access to the enzyme without affecting binding affinity. To further assess the broader applicability of this strategy across diverse PETases, SEC-loop replaced variants of representative PETases are characterized through kinetic and adsorption analyses. We show an engineering strategy focused on modulating enzyme accessibility rather than simply modifying the catalytic site, in rational enzyme design aimed at improving PET degradation efficiency. Polyethylene terephthalate (PET) hydrolases have been extensively studied for their applications in plastic degradation, but the structural and mechanistic factors that limit their catalytic efficiency are not yet fully understood. Here, the authors identify the protruding, surface-exposed C-terminal loop (SEC-loop) in Cryptosporangium aurantiacum PETase that negatively impacts enzymatic activity by restricting productive access of enzyme to PET substrates.

Methanol is a promising C1 feedstock for bioproduction but its cytotoxicity limits applications. Here we enhanced Komagataella phaffii GS115 methanol tolerance to 10–13% (v/v) by overexpressing four genes (phosphatidylethanolamine methyltransferase (PET2), phosphatidylserine synthase (PSA), PAS_chr1-4_0178 (0178) and PAS_chr2-2_0267 (0267)) (S33 strain). Our results show that, under high methanol stress, S33 undergoes membrane lipid remodelling-driven metabolic reprogramming, with central carbon flux being redistributed from the pentose phosphate pathway and citric acid cycle towards glycolysis. Within this framework, 0178 encodes a vacuolar transporter of sulfur-containing amino acids, which we propose supports phospholipid methylation and redox balance. Meanwhile, 0267 encodes a peroxisomal thiolase-degrading long‑chain fatty acyl‑CoAs, limiting toxic long-chain sphingolipid accumulation, maintaining membrane stability. These genes enable S33 to achieve lipid titre of approximately 40 g l−1 under non-sterile fed‑batch fermentation conditions. This work positions S33 as a methanol-tolerant K. phaffii chassis for further strain and process development. Bioproduction from methanol is often challenging owing to the cytotoxicity of methanol. Here a methanol-tolerant Komagataella phaffii chassis is engineered by overexpressing four membrane genes, increasing tolerance to 10–13% methanol and enabling non-sterile lipid production (>40 g l−1) via membrane lipid remodelling and metabolic rewiring.

The term ‘gut health’ is increasingly used as a catch-all phrase by many stakeholders, including scientists, health-care professionals, industry and the general public, to describe a wide range of health-related concepts. Despite its widespread use, particularly in relation to studies on diet, fermented foods, biotics and the gut microbiome, it remains unclear what the term gut health means. Therefore, an expert panel was convened by the International Scientific Association for Probiotics and Prebiotics to address the current state of scientific and clinical knowledge on the physiology, manifestation, application and measurement of the concept of gut health. The panel evaluated the term in the context of the central role of the gastrointestinal tract in health and overall well-being and proposed a definition of gut health as “a state of normal gastrointestinal function without active gastrointestinal disease and gut-related symptoms that affect quality of life”. The definition was developed mindful of the functional, subjective and extrinsic domains that contribute to gut health. In this Consensus Statement, clinically relevant and accessible metrics to assess these domains are reviewed and a comprehensive approach to gut health is proposed that is relevant to clinical practice as well as to studies of dietary and biotic interventions. This Consensus Statement provides a definition of the term ‘gut health’, as well as a discussion of the relevant domains that contribute to gut health and a framework for appropriate use of the term in the context of therapeutic interventions.

Structure-based virtual screening (VS) via molecular docking is a pivotal approach for hit identification. Many artificial intelligence (AI)-powered protein–ligand docking and scoring methods have demonstrated impressive speed and accuracy. Retrospective benchmarking studies using enrichment rate and computational efficiency on curated datasets have corroborated their potential for discovering bioactive compounds. However, determining which method suits a specific application and implementing it efficiently remains challenging. Here we present the Comprehensive VS Platform with AI Engine (CVSP-AIE) for drug discovery from compound libraries. It integrates three AI models: KarmaDock, a fast docking model that directly updates atomic coordinates; CarsiDock, an accurate docking model that predicts protein–ligand distances and reconstructs binding poses; and RTMScore, an accurate scoring model that learns residue–atom distance distributions for affinity prediction. Their hierarchical application enables dynamical balances in screening speed and accuracy. CVSP-AIE is available as an online web server ( https://cadd.zju.edu.cn/cvsp/ ) and a local software package. Users can efficiently initiate drug screening by uploading a protein and a known binder that defines the binding pocket. The following workflow involves (1) preprocessing, including protein structure repair and molecule standardization, (2) binding pose and affinity prediction powered by KarmaDock, CarsiDock and RTMScore and (3) postprocessing, comprising protein–ligand interaction calculation and visualization. It takes 30–45 min to hierarchically screen 100,000 compounds, and the output is a ranked list of molecules with predicted binding scores, intermolecular interaction profiles and interactive chemical space analysis. Users can also install locally the hierarchical screening module through command-line package for arbitrary-scale screening. This Protocol describes an artificial intelligence-driven virtual screening platform for drug discovery that includes an online webserver and a local software package, offering a user-friendly alternative for drug screening targeting compound libraries of arbitrary-scale.

Lignocellulose is a promising renewable resource for anaerobic biochemical production, but its microbial conversion remains challenging. To elucidate metabolic networks in lignocellulose-degrading consortia, inocula of various origins were enriched on cellulose or xylan. Community composition and metabolic functions were revealed by amplicon sequencing, metagenomics, genome-scale metabolic modelling, and metabolic simulations. In cellulose-enriched communities, Fibrobacter and Lacrimispora consistently dominated as primary cellulose degraders, whereas Bacteroides likely functioned as secondary degraders. Acetic acid (up to 1.3 g l-1) and CO2 were the main fermentation products. Xylan enrichments produced C2-C6 fatty acids (up to 3.9 g l-1), lactic acid (up to 1.2 g l-1), ethanol (up to 1.2 g l-1), CO2, and H2. Clostridium dominated one xylan community and produced mainly butyric acid, while Bifidobacterium dominated another and produced mainly lactic acid. Caproic acid production was experimentally observed in one xylan enrichment. Metagenomic annotations and metabolic simulations suggest that Lacrimispora amygdalina degraded xylan and Robinsoniella peoriensis consumed xylobiose as a secondary consumer, both likely producing ethanol and lactic acid that supported caproic and butyric acid production by Caproicibacter fermentans. Integrated analysis identified functional guilds and clarified the roles of degraders and non-degraders, providing a blueprint for engineering synthetic consortia for sustainable biochemical production.

Pseudomonas putida KT2440, renowned for its diverse metabolic capabilities, is a promising platform for downstream processing and revalorisation of recalcitrant molecules. In this study, we examined and optimized P. putida KT2440's ability to utilize products of the degradation of polyethylene (PE), the most used and disposed plastic. PE degradation creates over 200 molecules that vary in oxidation level and, thus, chemical properties. Among those, long-chain alcohols represent one of the most challenging fractions to process due to their poor solubility. Using them as feedstock for microbial growth would close the plastic-derived carbon cycle, reducing environmental impact. First, we discovered that P. putida KT2440 can use the long-chain alcohols, 1-hexadecanol and 1-eicosanol, as the sole carbon and energy source. Using adaptive laboratory evolution (ALE), we generated variants with improved growth rates on such substrates. Mutations that became fixed during ALE provided insights into the mechanism, highlighting the importance of cell–substrate interaction. By heterologously expressing a hydrocarbon transporter-encoding gene, we successfully reproduced the ALE-derived phenotype, suggesting that the bottleneck in long-chain alcohol utilisation lies in uptake rather than substrate transformation. These findings lay the groundwork for the potential application of P. putida KT2440 for the valorization of PE degradation products.

Bitter taste is a critical quality determinant in food systems, particularly those using sustainable protein hydrolysates, where the unpredictable formation of bitter peptides severely limits consumer acceptance. Achieving predictive control over flavor chemistry requires deciphering the complex sequence-activity relationship. To address this, we integrated the generative capacity of a protein language model with BitterPep-GCN, a Graph Convolutional Network (GCN) capable of robust in silico bitter/non-bitter classification, to target the de novo design of functional bitter and non-bitter sequences. We achieved this by generating two strategic peptide libraries: a targeted tripeptide library derived from known bitter and non-bitter peptide sequences, and a set of de novo designed sequences. For the de novo designed peptides, we fine-tuned the conditional language model ZymCTRL on our curated dataset of sensory-validated bitter peptides (BPS-1000). Both libraries were subjected to classification and rigorous filtering using BitterPep-GCN to select high-confidence candidates for validation. The selected peptides were purchased and rigorously assessed for high purity. Sensory tests were conducted by an expert human panel to determine intrinsic taste quality and taste recognition thresholds. The results validated the high predictive fidelity of our pipeline: out of the 31 tested peptides, 25 were correctly classified, including 15 confirmed bitter and 10 confirmed non-bitter sequences. This study successfully demonstrates the application of machine learning frameworks in the design of bioactive peptides. It provides a set of novel taste-active peptides that can be used to accelerate the rational mitigation of off-tastes in next-generation food products.

Plants and pathogens engage in complex biochemical communication, mediated by proteins, specialized metabolites, phytohormones and phytohormone-mimicking compounds. These interactions drive a dynamic ‘co-evolutionary arms race’, as plants and microbes compete to gain an advantage, ultimately transforming the infection site into a distinct micro-ecosystem. Microbe-induced galls are abnormal plant organogenesis induced by specific pathogens, creating a niche where the pathogen manipulates the host plant machinery to ensure its own survival. Such galls adversely affect agricultural and horticultural productivity by stunting plant growth and causing deformities. However, the rapid cell proliferation in tumourigenesis, along with the mechanisms driving robust shoot and root re-differentiation, present exciting opportunities for innovative biotechnological applications. Therefore, elucidation of these mechanisms is crucial for advancing basic research with significant potential for agricultural applications. This review focuses on galls induced by Agrobacterium tumefaciens and Rhodococcus fascians—two phytopathogens that utilize phytohormones as tumor-inducing molecules—to highlight the mechanisms underlying plant–pathogen interactions within this specialized microenvironment. It also explores the evolutionary adaptations and strategies of these pathogens. Gaining insight into these biological processes is key to understanding the mechanisms driving biological diversity and evolution, with implications extending beyond plant pathology into the broader field of molecular plant physiology.

Amino acid substitutions may substantially alter protein stability and function. However, the contribution of substitutions that arise from alternate translation (deviations from the genetic code) is unknown. Here to address this issue, we analysed deep proteomic, transcriptomic and genomic data from more than 1,000 human samples, including 6 cancer types and 26 healthy human tissues. This global analysis identified 60,803 fragmentation spectra corresponding to 8,746 unique substitutions in proteins derived from 1,767 genes, including 1,955 confidently localized sites. Some substitutions were shared across samples, whereas others exhibited strong tissue-type and cancer specificity. Notably, products of alternate translation were more abundant than their canonical counterparts for hundreds of proteins, which suggests that there is sense-codon recoding. Recoded proteins included transcription factors, proteases, signalling proteins and proteins associated with neurodegeneration. Mechanisms that contribute to substitution abundance included protein stability, codon frequency, codon–anticodon mismatches and RNA modifications. We also characterized how alternatively translated proteoform ratios vary across protein domains, tissue types and cancers. These ratios were positively associated with intrinsically disordered regions and genetic polymorphisms in the gnomAD database, although the polymorphisms could not account for the substitutions. The sequence, relative abundance and the tissue specificity of alternatively translated proteins were conserved between humans and mice. These results demonstrate the contribution of alternate translation to the diversification of mammalian proteomes and its association with protein stability, tissue-specific proteomes and disease. Alternate RNA decoding, an understudied process, leads to peptide sequence modifications that can have substantial functional effects on protein stability, tissue-specific proteomes and disease.

Natural products remain a major source of antibiotics, but discovery efforts have traditionally treated biosynthetic gene clusters as sources of individual bioactive molecules. Increasing evidence has suggested that microorganisms can instead encode coordinated multi-metabolite systems, yet the genetic architectures and biological logic of such systems remain poorly understood. Here we show that Streptomyces spp. encode a highly conserved biosynthetic megacluster that produces four structurally distinct natural product families—stravidins, acidomycin, dapamycins, and 2-methyl-7-keto-8-aminopelargonic acid (α-Me-KAPA)—alongside the biotin-binding protein streptavidin. These components converge on bacterial biotin metabolism through complementary mechanisms, including enzyme inhibition, prodrug activation, cofactor mimicry and biotin sequestration. The encoded metabolites are co-produced and act synergistically across Gram-negative and mycobacterial species, with stravidin S2 and α-Me-KAPA showing enhanced efficacy in combination in a mouse model of multidrug-resistant E. coli infection. This megacluster reveals a genetically encoded chemical arsenal that functions as a naturally evolved combination therapy against a conserved metabolic pathway. More broadly, our findings suggest that higher-order biosynthetic architectures may represent an overlooked reservoir of antibiotic mechanisms and support a shift from discovering isolated natural products to reconstructing native synergistic systems. In Streptomyces spp., a conserved biosynthetic gene megacluster produces an arsenal of distinct antimicrobials that converge on bacterial biotin biosynthesis as a naturally evolved combination therapy.

The cross-species delivery of megabase-scale synthetic DNA molecules, from microorganisms into mammalian cells, remains a major challenge for synthetic genomics. Recently, we developed nucleus isolation for chromosome extraction (NICE), a method that enables the isolation of yeast nuclei containing intact synthetic megabase-scale DNA with preserved chromatin structure. By leveraging the unique epigenomic features of Saccharomyces cerevisiae, which lacks cytosine methylation and repressive histone marks, synthetic DNA encapsulated within isolated yeast nuclei was successfully delivered into mouse early embryos, maintaining a naive state. This work established a unique platform for studying the establishment of de novo epigenetic modifications and their influence on transcriptional regulation over time. Here, we provide a detailed protocol for NICE, including the isolation of yeast nuclei and their subsequent delivery into mammalian embryos. The high-concentration and high-purity isolated nuclei can be stored at –80 °C for >6 months. Using microinjection, we achieved 100% delivery efficiency, reliably transferring isolated yeast nuclei into mouse embryos. The entire procedure, including pulsed-field gel electrophoresis verification, can be completed within ~5 d. When the isolated yeast nuclei are intended for cross-species delivery into embryos, prior familiarity with mammalian embryo microinjection techniques may be required. This protocol offers an efficient and reliable method for the delivery of large-scale genetic information, advancing the study of complex biological functions. This protocol presents a method for isolating intact yeast nuclei containing megabase-scale synthetic DNA and delivering them into mouse embryos, enabling efficient cross-species transfer and studies of de novo epigenetic regulation.