Temperate bacteriophages are increasingly recognized as important drivers of microbial evolution. However, their role in mediating competition among members of the same species during infection remains poorly defined. Pseudomonas aeruginosa (Pa), an opportunistic pathogen associated with acute and chronic infections, frequently exhibits clonal dominance within infected individuals, suggesting the existence of effective mechanisms for excluding conspecific competitors. Here, we investigate the contribution of temperate bacteriophages to intraspecies competition among clinical Pa isolates. Screening of filtered cell-free supernatants from a diverse panel of clinical strains revealed that cell-independent antagonism is widespread, with most strains inhibiting the growth of at least one other Pa isolate. Susceptibility was strongly associated with twitching motility, a type IV pili-dependent phenotype, which also serves as the primary receptor for most Pa bacteriophages. Plaque assays confirmed the presence of infectious phage particles with strain-specific host ranges. Exposure of susceptible strains to infective phages resulted in the emergence of phage-induced small colony variants (pSCVs) that retained and propagated the acquired phages and associated inhibitory capacity. Whole genome sequencing revealed extensive prophage diversity and mosaicism across clinical isolates, supporting a model in which poly-lysogeny expands competitive potential. Using isogenic pSCV systems and murine wound infection models, we demonstrate that acquisition of specific temperate phages confers a competitive advantage both in vitro and in vivo. These findings establish temperate bacteriophages as dynamic ecological weapons that shape intraspecies competition providing a mechanistic basis for clonal dominance during Pa infection and highlighting the broader role of prophages in structuring microbial populations.

Ionization states are crucial to protein function, yet predicting their equilibrium constants remains challenging. Here we present KaML-ESMs, sequence-based neural networks built on the ESM protein language models and trained on the GAINES-augmented PKAD-3r dataset. KaML-ESM2/ESMC outperform alternative approaches across four benchmarks, achieving root-mean-square errors of about 0.5 units for Asp/Glu/His/Cys/Tyr/Lys residues in native proteins. Performance degrades on 89 buried engineered mutations lacking evolutionary support, revealing a limitation that supervised training may help overcome. These results suggest that protein sequence, through its evolutionary context, encodes not only structure and function but also, indirectly, electrostatic characteristics. Applying KaML-ESM2 to the entire human proteome, we show that predicted pKa values can identify functional sites and infer catalytic mechanisms. We offer KaML, a sequence-based pKa prediction platform supporting biological exploration, protein engineering, and biomolecular simulation. With further development, GAINES could provide a general framework for addressing data scarcity in machine learning. Ionization states are crucial to protein function, yet predicting their equilibrium constants remains challenging. Shen et al. developed KaML-ESMs, sequence-based models that predict pKa values with accuracy rivaling experiment.

Mutualistic interactions are widely hypothesized to broaden ecological niches and promote diversification, yet evidence for this relationship at macroevolutionary scales remains limited. Here, we investigate how fungal seed endophytes (Epichloë) influence niche breadth and diversification across over 100 species of the globally-distributed grass genus Poa. Combining global-scale climate, environmental, phylogenetic, and symbiosis data, we construct species distribution models for suites of symbiotic and non-symbiotic plant species, and use phylogenetic comparative methods to assess the influence of these symbionts on niche breadth, niche breadth evolution, and diversification. Endophyte-positive species have ~1.4 times broader primary niche axes (most often associated with temperature tolerances), ~2.5 times larger geographic ranges, and >30 times faster rates of niche breadth evolution than non-symbiotic species. Endophytic plants also have significantly drier climate centroids, consistent with endophyte-mediated drought tolerance, while simultaneously showing constrained niche centroid evolution. Despite pronounced niche expansion, hidden state speciation and extinction models reveal two modes of diversification: endophytes decrease diversification rates in young lineages, and have a neutral effect in older lineages. Together, our results indicate that mutualists can be associated with broader niches without necessarily increasing diversification, highlighting a potential decoupling between niche expansion and diversification. Mutualistic interactions are hypothesized to broaden ecological niches and promote diversification, yet evidence for this relationship remains limited. This study finds that, across Poa grasses, fungal endophytes are associated with broader niches and faster niche breadth evolution, but reduced diversification rates.

The rise of antibiotic resistance, particularly among pathogens such as methicillin-resistant Staphylococcus aureus, necessitates innovative antibacterial strategies. Here we introduce FibriLysins, a class of engineered enzymes combining staphylokinase and endolysin, which dismantle fibrin-encapsulated multicellular staphylococcal communities, including biofilms and staphylococcal abscess communities (SACs). We characterized diverse staphylokinases, developing a library of 27 FibriLysins, with a 78% positive hit rate. The lead variant, FL-028, has significant antibacterial activity against prevalent clinical S. aureus isolates. In vitro, FL-028 reduced bacterial counts in SACs by 3.4 log and in biofilms by 2.3 log. In vivo, FL-028 exhibits superior efficacy in a mouse model of bone fracture-related infection, outperforming vancomycin by 1 log and eliminating SAC presence in tissues. FL-028 shows no adverse effects on bone healing, as confirmed by histological examination, mechanical testing and micro-computed tomography analyses. These preclinical findings highlight the potential of FibriLysins as a robust and safe therapeutic approach against difficult-to-treat staphylococcal infections. Engineered FibriLysins dismantle fibrin-encapsulated Staphylococcus aureus communities and outperform vancomycin in a preclinical model of fracture-related infection.

Self-sustained luminescence enables non-invasive monitoring of molecular events at the whole-organism level, but its intensity depends on both gene expression and cellular metabolism, limiting quantitative interpretation. Here we present an approach that disentangles the contributions of gene expression and metabolism. By co-expressing an engineered reference luciferase variant that uses the same substrate but emits light at a different wavelength and monitoring the color ratio, we substantially reduced signal variability, enabling quantitative physiological imaging despite changes in metabolic activity. In glowing plants, monitoring colour shifts instead of changes in luminescence intensity enables quantitative measurements of physiology despite changes in metabolic activity.

Over the past two decades, there has been a staggering increase in greenhouse gas emissions, particularly carbon dioxide (CO2) from unrestrained anthropogenic activities, leading to notable environmental shifts. Despite continuous efforts to reduce emissions, the world is not making satisfactory progress, which calls for immediate action to implement alternative strategies to enhance environmental sustainability. The Earth naturally absorbs and stores carbon through various processes, but merely keeping pace with ongoing human activities is no longer sufficient. Land plants and marine prokaryotes absorb CO2 during photosynthesis and store carbon as biomass. Eukaryotic organisms also represent a valuable resource that can provide insights into the biological fixation and removal of atmospheric CO2. Expanding the capacities of Earth’s natural systems offers enormous potential for enhancing carbon sinks and promoting environmental resilience. Although extensive synthetic engineering of plant systems has been conducted to enhance their native carbon fixation pathways, research on microorganisms, especially fungi, has been limited. In this review, we specifically explore the role of soil-borne fungi in carbon management, elucidating their responses to environmental shifts and their potential for climate change mitigation. We place particular emphasis on the role of various fungal guilds in this process, highlighting those that should be prioritized for future synthetic biology applications. We then engage with previous endeavors to address primary challenges in advancing genetic tools for these understudied fungi. Lastly, we discuss how integrating synthetic biology practices into the field of soil-associated fungi can drive advances in long-term carbon storage, enhance degradation of environmental pollutants, and improve nutrient exchange and soil health, contributing to more resilient soil ecosystems and sustainable environmental interventions. 

G-protein coupled receptors (GPCRs) mediate precise ligand-specific signaling profiles, yet structural visualization of how ligands alter receptor conformational landscapes in the absence of signaling partners or mimetics has proven challenging. Here we show that by combining generative protein design with deep-learning based ensemble prediction we can reliably design fiducial markers to facilitate cryogenic electron microscopy (cryoEM) of GPCRs at arbitrary fusion points, enabling the visualization of previously intractable states. We validate the approach with high-throughput determination of inactive state structures of four pharmaceutically relevant GPCRs, allowing for key details of receptor pharmacology to be resolved in each case. We then engineered an extracellular fiducial marker for the prototypical β2-adrenergic receptor that enabled direct structural characterization of the rearrangement of key intracellular motifs in the absence of G-protein. Comparison with recent co-folding models highlights major gaps in current methods for predicting ligand-induced GPCR conformations. These results present a generalizable framework for accessing traditionally inaccessible structural states of small, dynamic proteins. Visualizing how drugs reshape GPCR receptors by cryo-EM has been difficult for many conformational states. Here, authors use designed protein fiducials to image elusive GPCR states, revealing details of ligand induced receptor activation.