In all living cells, chemical reactions known as metabolism generate energy and building blocks for cellular structures. Metabolism produces and consumes ATP, the major currency of cellular energy. Because approximately 85% of ATP is bound to Mg2+, bacteria reduce their ATP concentration when cytoplasmic Mg2+ availability drops below a certain threshold. This reduction in ATP concentration reshapes metabolism and gene transcription as well as protein synthesis, solubility, and turnover. This article reviews how ATP acts both directly and via ATP-derived signaling molecules, such as 3′,5′-cyclic AMP (cAMP), bis-(3′,5′)-cyclic dimeric-AMP (c-di-AMP), diadenosine tetraphosphate (Ap4A), and guanosine-3′,5′-tetra- and pentaphosphate [(p)ppGpp], which direct adaptations to stresses bacteria experience in their natural environments. It also discusses how Mg2+-responsive regulatory systems supersede canonical control of metabolism and protein homeostasis by governing ATP amounts and how this bacterial response slows growth, modifies cell envelope structures, and favors survival.

Eppur si muove—the work of Galileo Galilei marked the beginning of the quantitative study of motion for scope-observable entities. Extending this physics-based perspective to the microscope-observable microbial world has uncovered principles of motion that diverge sharply from our everyday intuition, revealing physics as being essential to understanding microbial motility. In this review, we explore the fundamental physical principles that enable and constrain the motility strategies evolved by diverse microorganisms, with a focus on prokaryotes, to enable propulsion in fluids and along surfaces. We examine how microbial motility functions in complex, heterogeneous environments, and we provide a brief evolutionary perspective on microbial motility by highlighting its costs and benefits. In summary, we show how including a physical approach in the study of microbial motility both unveils general solutions and specific adaptations and enables a better understanding of a world for which our intuition is not trained.

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.

Antibiotic-resistant bacteria are common in natural environments, including the microbiota of animal and human hosts. The local physical, chemical, and biological conditions of environmental patches and matrices vary both qualitatively and quantitatively. Often, these conditions are found as gradients, creating intersections that can either facilitate or inhibit the spread and evolution of antibiotic resistance (AbR). Ecological kinetics (EcoK) describes how combinations of these conditions influence the abundance and transmission of antibiotic-resistant populations, as well as the mobile genetic elements that carry resistance genes. Evolutionary dynamics (EvoD) concerns the effects of environmental conditions on genetic variation, the expression of resistance traits, and the evolvability of host bacteria, ultimately contributing to the emergence and selection of AbR. This review examines the influence of numerous environmental conditions on EcoK and EvoD. This field remains poorly understood, and further research is essential to identify high-risk areas where surveillance for the emergence and spread of AbR should be implemented.

Protein glycosylation involves the co-translational or post-translational addition of glycans to proteins and is a crucial protein modification in health and disease. The aim of glycoproteomics is to understand how glycosylation shapes biological processes by understanding peptide sequences, glycan structures and sites of modification in a system-wide context. Over the past two decades, mass spectrometry (MS) has emerged as the primary technique for studying glycoproteins, with intact glycopeptide analysis — the study of glycopeptides decorated with their native glycan structures — now a preferred approach across the community. In this Primer, we discuss glycoproteomic methods for studying glycosylation classes, including best practices and critical considerations. We summarize how glycoproteomics is used to understand glycosylation at a systems level, with a specific focus on N-linked and O-linked glycosylation (both mucin-type and O-GlcNAcylation). We cover topics that include sample selection; techniques for protein isolation, proteolytic digestion, glycopeptide enrichment and MS fragmentation; bioinformatic platforms and applications of glycoproteomics. Finally, we give a perspective on where the field is heading. Overall, this Primer outlines the current technologies, persistent challenges and recent advances in the exciting field of glycoproteomics. Glycoproteomic techniques give information on the structure and location of glycan protein modifications. In this Primer, Bagdonaite et al. summarize these techniques, discuss best practices for their use and explore their applications, including identifying biomarkers of disease.

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.