Peptides are among the smallest functional biomolecules. Learning to systematically design their activity would revolutionize biology and medicine. Yet achieving this goal remains an open challenge. Recent advances in machine learning enable the discovery and design of peptides at scale, not only yielding new antibiotic agents effective against priority pathogens but also revealing unexpected roles for peptides in host immunity. In this review, we survey how artificial intelligence (AI) methods can be used to mine genomes, proteomes, and even ancient sequence data to uncover “encrypted” peptide antibiotics across the tree of life and over evolutionary time. We highlight emerging approaches for activity prediction, structure–activity modeling, sequence optimization, and de novo peptide generation, and we discuss workflows that tightly couple in silico design with high-throughput experimental validation. We further introduce the concept of “encrypted immunity,” in which ordinary proteins encode latent antimicrobial fragments, and we outline translational opportunities as well as remaining challenges on the path to bringing AI-designed peptides to the clinic.
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 Mg 2+ , bacteria reduce their ATP concentration when cytoplasmic Mg 2+ 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 (Ap 4 A), and guanosine-3′,5′-tetra- and pentaphosphate [(p)ppGpp], which direct adaptations to stresses bacteria experience in their natural environments. It also discusses how Mg 2+ -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.
Bacteria use membraneless compartments, or biomolecular condensates, to organize cellular processes in space and time. These condensates assemble and function within a highly constrained physical landscape shaped by a crowded cytoplasm, structured nucleoid, membrane surfaces, and distinct polar zones. In this review, we examine condensates involved in genome maintenance, RNA metabolism, cell division, signaling, and metabolic regulation, focusing on how cellular microenvironments and physiological state shape when and where these condensates form, which molecules they recruit, and the material states they adopt. In turn, condensates can concentrate molecules for biochemical reactions, sequester them for storage or protection, release or redistribute them as conditions change, and position them at specific cellular sites. Disentangling the contribution of the condensed state from that of the underlying molecular interactions will be essential for determining how condensates regulate bacterial physiology.
Helicobacter pylori is a motile bacterium that uses its high-torque flagella to colonize the diverse and challenging landscapes within the human stomach. H. pylori flagella possess numerous variations from canonical systems in motor dimensions, stator occupancy, flagellin composition, and the incorporation of additional basal body elements. Many, but not all, of these variations have been identified and characterized. H. pylori flagellar gene transcriptional regulation diverges from that of canonical models in its lack of a single master regulator, reliance on a hierarchy based on two σ factors, and use of a distributed set of regulatory checkpoints. Emerging evidence suggests H. pylori flagella play roles in mechanosensing and regulating the motile–sessile transition, relying on flagellar cage protein homologs of the type 4 pili PilO, PilN, and PilM and operating independently of c-di-GMP. The study of H. pylori flagella has revealed many surprises, and more surprises certainly await in this exciting field.
