Microbes, as the planet’s most abundant and diverse organisms, drive soil functions globally and are vulnerable to environmental stressors triggered by global change. Yet, knowledge regarding the impacts of multiple environmental stressors on their functional profiles as well as the consequences for soil functionality largely remains unknown. Here, we analyze two global-scale datasets including information on soil metagenomics and multiple environmental stressors. We find that across terrestrial ecosystems worldwide, up to 60% of all functional genes significantly shift when soil microbes experience the high-level of concurrent stressors. In this regard, the relative abundances of genes involved in microbial growth are negatively linked to the increasing number of stressors. Conversely, those genes linked to stress resistance and energy production exhibit positive responses. Taken together, our findings highlight a significant restructuring of global soil functional microbiomes in response to multiple environmental stressors. Consequently, such restructuring drives community-level shifts in matter and energy reallocations, thereby impacting the maintenance of soil functionality under the projected global change. Soil microbes drive ecosystem functions but are vulnerable to environmental stressors triggered by global change. This study reveals that multiple environmental stressors drive community-level restructuring of soil functional microbiomes globally.

Plants decode environmental light cues through photoreceptors to orchestrate growth and developmental programs. Upon photon absorption, photoreceptor proteins transition from non-photoexcited to photoexcited states, with most functional studies focusing on the activities of the photoexcited form. However, emerging evidence reveals that non-photoexcited photoreceptors exert distinct biological functions in darkness, suggesting unexpected complexity in photon-mediated signalling. In this Perspective, we enumerate current observations underpinning photoreceptor-mediated control of plant development in darkness, categorize mechanisms of photon-dependent modulation and propose an expanded conceptual model that integrates both photoexcited and non-photoexcited activities. These insights reassess the previously overlooked importance of darkness, redefining light and darkness as dynamic, multidimensional regulators of plant physiology. In a manner distinct from their light-activated canonical roles, non-photoexcited photoreceptors can also exert biological functions in darkness, suggesting unexpected complexity in photon-mediated signalling.

Branched receptor-binding protein (RBP) systems enable bacteriophages to broaden their host range through the incorporation of two or more RBPs. Using the Klebsiella podophages KP32, K11, and KP34 as model systems, we experimentally validated the interaction between the branching domain of the primary RBP (RBP1) and the conserved docking peptide of the secondary RBP (RBP2) as an essential architectural pair enabling dual-RBP incorporation into the virion. Systematic engineering revealed that loss of either of these domains, the branching domain or the conserved peptide, abolishes RBP2 assembly, underscoring their structural role in organizing the branched configuration and demonstrating that the anchor domain is the sole element directly attaching the RBP complex to the virion. Exploiting this interaction, we engineered a chimeric phage based on the Klebsiella phage KP32 scaffold that was capable of cross-genus infection and productive propagation on both Klebsiella and Escherichia hosts. In contrast to previous approaches that required replacement of the entire RBP, the adaptor and nozzle proteins, this strategy achieved host-range reprogramming through modular domain swapping and positional relocation of RBPs (i.e., exchanging RBP1 and RBP2 positions). Conversely, an Escherichia phage K1F scaffold was also successfully engineered to infect Klebsiella. Our study confirms that the RBP branching domain and the conserved peptide function as specific interacting partners. Our findings establish the conserved peptide as a docking element and highlight the structural flexibility of podoviruses to accommodate RBPs from different positional and taxonomic contexts. Collectively, this work provides a mechanistic framework for rational phage engineering and defines a general design principle for generating customized therapeutic phages with an expanded host spectrum, including cross-genus infectivity.

Ribosome synthesis is one of the most energy-intensive processes in a growing cell, consuming >60% of cellular energy reserves. As such, ribosome biogenesis is highly sensitive to stress to prevent costly expenditures under adverse conditions. Moreover, successful assembly requires precise stoichiometric balance between ribosomal proteins and ribosomal RNAs (rRNA). Here, we define novel regulatory mechanisms of ribosome biogenesis under stress that reveal previously unrecognized aspects of rRNA maturation. We demonstrate that early pre-rRNA processing is particularly sensitive to stress induced by environmentally relevant heavy metals. Surprisingly, our analysis shows that 5′ and 3′ end processing can be uncoupled in human cells, with 3′ end cleavage occurring independently of 5′ end processing. We further show that classical inducers of endoplasmic reticulum stress suppress ribosomal protein synthesis without inhibiting rRNA transcription, leading to an imbalance between these essential components of ribosome assembly. This imbalance may exacerbate cellular stress and compromise proteostasis. Together, our findings uncover stress-specific checkpoints in ribosome biogenesis that link environmental exposures to disrupted nucleolar function and highlight new layers of regulation in human rRNA maturation.

All eukaryotes, including yeast, plants, animals and humans, possess linear chromosomes. The conserved eukaryotic telomere-telomerase systems, originated and evolved over 1 billion years, protect the chromosomal ends and regulate critical physiological functions through complex networks. In this study, we replace the endogenous eukaryotic telomeres in the single-chromosome yeast Saccharomyces cerevisiae with the prokaryotic telomere system TelN/tos from the Escherichia phage N15, which forms a closed hairpin structure, by interrupting the MRX/Sae2 pathway. The prokaryotic telomeres effectively protect linear chromosomal ends and prevent genetic instability. Through adaptive evolution, we identify yeast strains harboring additional mutations (TEL1 and CYR1) that restore functional MRX/Sae2 activity, thereby improving host fitness and meiotic capacity. Interestingly, the two-associated TelN/tos telomeres position deeper into chromosomes and exhibit increased interactions with their adjacent regions. The successful replacement of a complex eukaryotic chromosomal telomere with a simple bacteriophage system demonstrates functional equivalence between these divergent systems, implying possible natural origins of such stochasticity (e.g., horizontal gene transfers). Furthermore, these engineered strains facilitate development of a tos-YAC system that enabled iterative assembly and stable maintenance of megabase-level heterogeneous DNA (1.23-2.77 Mb), providing a robust platform for large-scale DNA manipulation. Telomeric systems are conserved across eukaryotes and may have originated over 1 billion years ago. Here the authors replaced yeast’s telomeres with a bacterial virus system, resulting in a stable functional assembly of DNA molecules up to 2.77 Mb, offering insights into the possible origins of telomeres.

In Pseudomonas umsongensis GO16, a LysR-type transcriptional regulator (LTTRs) ttdR is located 5′ of the gene for glyoxylate carboligase (gcl), involved in ethylene glycol (EG) metabolism. GO16 wildtype (WT) can utilize EG as a sole carbon and energy source but the ttdR knockout strain (ΔttdR) cannot grow on EG, demonstrating its role as an activator in EG metabolism. When ΔttdR was grown with terephthalic acid (TA) or glucose, the growth was comparable to the WT. GO16 originally produces both C4 short-chain-length (scl) PHA and C6-C12 medium-chain-length (mcl) PHA from various carbon sources. Interestingly, ΔttdR produced scl-PHA monomer 5.4-fold and 1.4-fold increased than the WT when TA and glucose were used respectively. Furthermore, ΔttdR exhibited a very long lag phase when grown with fatty acids, namely butyrate or octanoate. This indicates a more complex role of TtdR than simply activating EG metabolism in GO16. The analysis of the GO16 ΔttdR proteome revealed that EG catabolic genes were expressed, but their abundance was 2.8- to 10.5-fold lower (log2) compared to the WT. In addition, higher abundance of enzymes that could be contributing to higher scl-PHA content was also observed. GO16 ΔttdR was further subjected to adaptive laboratory evolution (ALE) with butyrate and octanoate. The evolved strains regained the ability to grow with these fatty acids as the WT, but the mutations accumulated did not confer growth with EG or acetate, suggesting that a mechanism different to glyoxylate shunt has evolved to allow growth with fatty acids.

De novo peptide sequencing directly infers sequences from mass spectrometry data without relying on protein databases. Although recent deep learning models can also identify posttranslational modifications (PTMs), they require labeled training data for this task. Here we introduce rotary positional embedding-enhanced de novo sequencing algorithm (RNovA), a transformer-based de novo sequencing algorithm enhanced with relative positional embeddings and a reinforcement-learning-style sequential decision framework. RNovA enables open PTM discovery in a zero-shot setting—without retraining or a predefined list of candidate residues—while maintaining state-of-the-art performance on standard benchmarks. Demonstrating this capability, we successfully identified peptides modified by kynurenine—an uncommon and biologically relevant PTM—in clinical samples from patients with RA and validated this discovery with synthetically synthesized reference peptides. Furthermore, we demonstrated open de novo PTM discovery by analyzing the bacterial strain A1232E, which lacks a reference proteome, and detected an unannotated glutamic acid modification. RNovA enables exploration of previously inaccessible regions of the proteome, including peptides with unexpected or unannotated modifications. RNovA is an open-search de novo peptide sequencing model.

Staphylococcus aureus is a major cause of bloodstream infections, but how variation between strains in their ability to adhere to host proteins influences disease severity remains unclear. Here we show that adhesion is a highly variable and biologically important trait in 236 phylogenetically diverse, representative bacteremia isolates profiled for binding to fibrinogen and fibronectin and analysed together with bacterial whole-genome sequences and matched patients’ clinical data. Stronger fibrinogen-binding, particularly in strains lacking α-toxin, correlates with heightened systemic inflammation (r = 0.401, P = 0.0001) but lower mortality (16.6% vs. 38.7%, P = 0.018), linking bacterial adhesion to distinct clinical outcomes. Genome-wide association analyses identify top-associated variants in genes encoding known adhesins (clfA, fnbA, fnbB, ebh), other surface factors (spa, sdrH), mobile genetic elements, and novel loci (csbB, glcA), although not statistically significant. Functional analyses reveal that protein A limits ClfA-dependent fibrinogen binding through steric hindrance, CsbB interferes with ClfA exposure on bacterial surface, and GlcA enhances fibronectin binding via metabolic regulation. These findings define adhesion as a polygenic, evolutionarily variable trait and suggest that highly-adhesive, α-toxin-defective isolates promote inflammatory but self-limiting infections, whereas weakly adhesive, high-toxicity strains favour immune evasion and severe disease. To uncover how Staphylococcus aureus strain variation influences adhesion and thus disease outcomes, the authors profile 236 bacteremia isolates, showing that high-adhesion, low-toxicity isolates may elicit inflammatory yet self-limiting infections.

Liquid–liquid phase separation (LLPS) is a key mechanism driving the assembly of membrane-less organelles and is increasingly recognized for its involvement in essential cellular functions and various diseases. However, existing computational approaches largely rely on sequence-level descriptors and often fail to explicitly incorporate structural topology information, limiting their ability to capture the complex determinants of LLPS behavior. Accurate identification of LLPS-capable proteins remains challenging due to their sequence diversity and complex structural determinants. Here, we present MuFGPS (Multi-level Feature Graph-based Predictor for Phase-Separating proteins), a predictive framework integrating sequence-derived physicochemical features, Define Secondary Structure of Proteins-annotated secondary structures, and graph-based structural embeddings from AlphaFold residue contact maps via a multi-head Graph Attention Network. Class imbalance is addressed using Synthetic Minority Oversampling Technique (SMOTE), and classification is performed through a stacking ensemble of Random Forest, XGBoost, and LightGBM. Benchmarks against six representative methods demonstrate that MuFGPS achieves superior performance across all metrics, with notable gains in F1-score and matthews correlation coefficient (MCC). Ablation analyses confirm the synergistic contributions of structural features and ensemble learning to accuracy and robustness. MuFGPS offers a scalable and high-accuracy framework for proteome-wide LLPS protein prediction.

Many viral proteins self-assemble into capsid structures, often using their genetic material as a template for assembly. To date, de novo designed capsid-like proteins do not require genetic material as a template for assembly, which can be both an advantage and a disadvantage depending on the use case. Templates are indispensable, for example, in the assembly of linear structures with well-defined lengths. As a first step towards fully de novo designed templated assembly, here we redesign proteins from the Transcription activator-like effector (TALE) family of transcriptional regulators to polymerize on double-stranded DNA (dsDNA) templates. Starting from natural TALE protein sequences, we create idealized repeat proteins with sequence-independent DNA binding properties that self-assemble to form linear protein-DNA complexes with template-controlled lengths. We use high-resolution atomic force microscopy (AFM) and cryo electron microscopy (cryo-EM) to characterize the three-dimensional structures of the DNA-protein hybrid complexes. In these structures, a protein filament helically wraps around the dsDNA similar to natural TALE proteins. As an example application of these materials, we show the system can be used for repetitive peptide antigen display at precisely controlled repeat distances, and that such immunogens elicit robust antigen-specific antibodies in mice. Viral capsids use their genome as an assembly template, but designed proteins lack this feature. Here, the authors redesign TALE proteins to polymerize on DNA, forming linear fibers that display peptide antigens and elicit antibodies in mice.

Primer design remains a fundamental yet non-trivial step in modern molecular biology workflows. Although numerous tools are available, they are often fragmented across disparate applications, constrained by commercial licensing, or dependent on external servers, limiting workflow integration and compromising sequence confidentiality. To address this challenge, we developed PrimerWeaver https://ignea.lab.mcgill.ca/primerweaver, a free browser-based tool that integrates primer design, quality control, and support for diverse cloning workflows within a single platform. PrimerWeaver enables overlap PCR, site-directed mutagenesis, multiplex PCR, restriction enzyme-based cloning (including Type II and Golden Gate assembly), and homology-directed methods such as Gibson assembly and Uracil-Specific Excision Reagent (USER) cloning. Primers were generated by optimizing the 3′ annealing region for efficient amplification while appending workflow-specific 5′ sequences according to the selected application. In silico and wet lab validation across diverse cloning workflows demonstrated consistent results relative to established molecular cloning software. All calculations are performed locally in the user’s browser without sequence upload, preserving data confidentiality and supporting reproducible performance across systems. Overall, PrimerWeaver streamlines primer workflows for users ranging from undergraduate students to experienced researchers by integrating multiple PCR and cloning strategies into a single browser-based platform.