Intrinsically disordered proteins and regions (collectively IDRs) are found across all kingdoms of life and have critical roles in virtually every eukaryotic cellular process. IDRs exist in a broad ensemble of structurally distinct conformations. This structural plasticity facilitates diverse molecular recognition and function. Here we combine advances in physics-based force fields with the power of multi-modal generative deep learning to develop STARLING, a framework for rapid generation of accurate IDR ensembles and ensemble-aware representations from sequence. STARLING supports environmental conditioning across ionic strengths and demonstrates proof of concept for the interpolative ability of generative models beyond their training domain. Moreover, we enable ensemble refinement under experimental constraints using a Bayesian maximum-entropy reweighting scheme. Beyond ensemble characterization, STARLING sequence representations can be used in multiple ways. We showcase two examples: first, STARLING lets us perform ensemble-based search for ‘biophysical look-alikes’. Second, we demonstrate how these latent representations can be used to accelerate ensemble-first sequence design from weeks or hours per candidate to seconds, enabling library-scale designs. Together, STARLING dramatically lowers the barrier to the computational interrogation of IDR function through the lens of emergent biophysical properties, complementing bioinformatic protein sequence analysis. We evaluate the accuracy of STARLING against extant experimental data and offer a series of vignettes illustrating how STARLING can enable rapid hypothesis generation for IDR function and aid the interpretation of experimental data. The deep learning model STARLING can generate accurate ensembles of intrinsically disordered regions of proteins using only protein sequence as input.

Biological functions depend on the spatiotemporal distribution of proteins within cells. Key cellular activities such as signal transduction, metabolism, cell cycle and cell death are driven by the interactions of proteins that are localized in multiple cellular compartments. Such multilocalization can even allow protein with identical sequences to display multifunctionality, a phenomenon known as moonlighting. Despite its biological importance, the relationship between protein localization and function remains underexplored. In this Review, we discuss the known mechanisms of protein localization (including RNA transport, role of proteoforms and molecular interactions) and how subcellular localization controls protein function. Proper regulation of protein localization is crucial for specialized cell and tissue functions, including cell differentiation, polarization and the epithelial–mesenchymal transition. Protein mislocalization can also have important roles in pathological processes, such as in cancer, neurodegeneration and autoimmunity. We end with a discussion of current technological and conceptual challenges in the field of subcellular proteomics and spatial biology. Addressing these challenges will allow us to link the dynamic nature of protein localization and function across biological scales and contexts, with great impact on fundamental cell biology and clinical applications. Proteins can localize to multiple cellular compartments and some exhibit distinct functions depending on their location. This Review discusses the mechanisms of protein localization, the control of specialized protein functions through subcellular localization, and how mislocalization is involved in cancer, neurodegeneration and autoimmunity.

Small-molecule metabolites are key pharmaceutical resources embedded in complex organismal metabolomes. Scalable microbial production depends on metabolic activation capacity, which in turn requires efficient genetic variation. Structural variants (SVs), key drivers of phenotypic diversity, are pivotal for organism evolution, yet their highly efficient induction remains challenging. While DNA double-strand breaks (DSBs) facilitate SVs formation, existing mutagenesis technologies struggle to balance high DSB efficiency with cellular preservation, particularly in microbial strain improvement for metabolite production. Conventional irradiation methods suffer from low SVs induction rates, making strain enhancement a lengthy and labor-intensive process. Here, we systematically compare six irradiation technologies in Streptomyces lividans 1326 and identify high-energy pulsed electron beams (HEPE) as an approach which effectively induces strong DSBs while preserving cellular integrity. This results in extensive SVs that reshape genome sequences and 3D chromatin structure, leading to activation of secondary metabolite production. By integrating HEPE with high-throughput metabolomics (HEPE-HiTMS), we discover two secondary metabolites with unusual C-N linkage, respectively. Applied across various microorganisms, HEPE enables record-high clavulanic acid and microcin J25 production, and markedly increases lovastatin yields. With its ability to induce SVs with minimal cytotoxicity, HEPE represents a powerful tool for cryptic metabolite discovery and industrial strain development. The majority of microbial metabolites remain cryptic or minimally expressed under laboratory conditions. Here authors show that high-energy pulsed electron beams (HEPE) can be used to induce extensive structural variation, activating secondary metabolite biosynthesis.

Oral and dental health is an important indicator and determinant of an individual’s overall well-being. Untreated oral diseases can lead to severe systemic complications. Monitoring the oral environment and identifying biochemical and physiological patterns associated with disease states, such as periodontitis, gingivitis, caries, and oral cancers, is essential for early diagnosis and effective intervention. This review evaluates the current clinical needs in biochemical and physiological monitoring for oral healthcare and state-of-the-art biosensors capable of continuous analyte measurement. We surveyed the relevant biomarkers for common oral and dental diseases in patients compared to healthy controls. The design and performance of recent biosensing devices for these target analytes are reviewed and evaluated. For biochemical sensing, we found intraoral biosensors for high-abundance small molecules, such as ions and metabolites, have advanced significantly in recent years. However, robust sensing technologies for low-abundance analytes, including cytokines and other inflammatory biomarkers, remain limited and require further development in sensing mechanisms, bio-interfaces, and device integration. For physiological sensing, particularly the measurement of forces in tooth movement, recent developments in force sensor technologies have substantially improved measurement accuracy over traditional techniques. Despite these advancements, current platforms still face limitations in achieving long-term, real-time monitoring of mechanical conditions within the oral cavity due to challenges related to biocompatibility and device miniaturization. In conclusion, while notable progress has been made in biosensing for oral applications, continued research in device integration with clinical practices is essential to realize robust and clinically deployable biosensor systems that can advance precision oral healthcare.

The compact CRISPR-Cas12f system is promising for AAV-delivered gene therapy, but its application has been constrained by restrictive PAM recognition (e.g., TTTR) and suboptimal editing efficiency. Through bacterial library screening and mammalian cell validation, we engineer evoCas12f, an optimized variant incorporating five key mutations, that dramatically expands PAM recognition to NTNR/NYTR. This advancement reduces median distance between two neighbouring PAM sites to 2 nucleotides in the human genome. It also demonstrates 1.4-fold enhanced activity at TTTR sites compared to wild-type Un1Cas12f1, achieving up to 91% editing efficiency. Remarkably, evoCas12f enables efficient generation of homozygous mutations in F0 generation mice, even at non-canonical PAM sites. We further adapt this system for robust transcriptional activation and precise base editing with a well-defined editing window. As a compact yet highly efficient platform, evoCas12f represents a significant advance in CRISPR technology, enabling multiplexed editing for high-resolution targeting applications and expanding possibilities for therapeutic genome engineering. Compact Un1Cas12f1 enzyme suits AAV delivery but is limited by narrow PAMs and modest activity. Here, authors engineer evoCas12f to recognize broader NTNR/NYTR PAMs and boost editing efficiency up to 91%, enabling efficient multiplex editing, base editing, and gene activation in cells and mice.

Anabaena, a nitrogen-fixing cyanobacterium from the Nostocaceae family, is a promising chassis for sustained space exploration. Using NEKO, this study surveys 2000 publications on Anabaena and summarizes the research, including systems biology, modeling, and potential space applications. Future research should examine its metabolism in space environments, such as microgravity and radiation, and develop bioreactor designs and genetic tools for reliable, self-regulating biomanufacturing systems in these environments.