New pathogens typically arise from host jump events between species. Staphylococcus aureus is a multihost pathogen responsible for a global burden of human disease and a leading cause of intramammary infection in dairy cattle. Here, we demonstrate that following historical human-to-bovine host switch events, S. aureus has undergone adaptive metabolic remodeling in response to distinct nutrient availability in the dairy niche. In particular, we found that bovine S. aureus has evolved the capacity for protease-mediated degradation of casein, a protein abundant in bovine milk, to access nutrients for proliferation. This phenotype has evolved convergently in different S. aureus lineages via mutations in distinct gene loci driving overexpression of the protease aureolysin. Together, we have dissected a key host-adaptive trait, which facilitates the enzymatic release of nutrients from a substrate specific to the new host milieu. These findings highlight the remarkable evolutionary plasticity of a major bacterial pathogen underpinning its multihost species tropism.

Evolutionary conservation has been considered a hallmark of essential basic functions in cells. Therefore, the study of evolutionarily conserved post-translational modifications (PTMs) can provide insight into their role in protein function. In this context, mass spectrometry can identify and quantify thousands of PTM sites. However, a major bottleneck lies in analyzing the large amounts of data collected by the mass spectrometer. Here we address the need for a protein sequence alignment tool for multiple PTMs across several species. We developed a tool named PTMOverlay that takes peptide identification output files and overlays PTM sites onto multiple protein sequence alignments. Examining 31 bacteria isolates, we combined their protein sequences with select PTM types, including acetylation, phosphorylation, monomethylation, dimethylation, and trimethylation. The tool revealed a variety of conserved modification sites on the bacterial central carbon metabolism. Further structural analysis revealed possible interactions between methylated arginine and lysine residues with phosphothreonine/serine sites on the homodimer interface of enolase. Overall, this tool can parse large amounts of mass spectrometry data and allows for more informed and efficient selection of sites for future studies of protein function.

Understanding how evolutionary constraints shape protein sequences is fundamental to deciphering the molecular mechanisms underlying protein stability and function, which has broad implications in protein engineering and therapeutics development. Recent advances in protein language models (pLMs) have enabled accurate prediction of mutation effects through evolutionary information, effectively capturing the selective pressure that governs protein sequence variation. A critical challenge, however, remains in disentangling the intertwined mutation effects on protein stability and function, as evolutionary signals conflate both stability-driven and function-driven pressures, obscuring the mechanistic basis of mutation effects and limiting their utility for rational protein engineering. In this work, we introduce DETANGO, a novel deep learning framework that explicitly deconvolves the mutation effects on protein functions by removing components attributable to stability perturbations from the pLM-predicted mutation effects. Guided by computational or experimental stability measurements, DETANGO estimates a functional plausibility score for each single-point mutation that is the component of the mutation effect not accounted for by changes in stability. Single-point mutations with low functional plausibilities are predicted to be stable-but-inactive (SBI) variants, whose compromised activities are caused by direct perturbations on functional mechanisms rather than structural stability. Residues enriched for such variants are inferred to be functionally critical, as indicated by the strong evolutionary pressures to maintain protein function. Through extensive benchmarking experiments, we show that DETANGO accurately identifies SBI variants and pinpoints functionally important residues across contexts, including ligand binding, catalysis, and allostery. Moreover, extending DETANGO from individual proteins to homologous protein families reveals shared and distinctive functional patterns across protein families. Collectively, these results establish DETANGO as a biologically grounded framework for disentangling evolutionary constraints on protein stability and function, advancing mechanistic understanding of protein function, and informing rational protein engineering.

Overlapping genes—wherein two different proteins are translated from alternative reading frames of the same DNA sequence—provide a means to stabilize an engineered gene by directly linking its evolutionary fate with that of an overlapping gene. However, creating overlapping gene pairs is challenging, as it requires redesigning both protein products to accommodate overlap constraints. Here, we present a new “overlapping, alternate-frame insertion” (OAFI) method for creating synthetic overlapping genes by inserting an “inner” gene, encoded in an alternate frame, into a flexible region of an “outer” gene. Using OAFI, we create new overlapping gene pairs of genetic reporters and bacterial toxins within an antibiotic resistance gene. We show that both the inner and outer genes retain function despite redesign, with translation of the inner gene influenced by its overlap position in the outer gene. Importantly, we show that, despite these inner gene sequences not contributing to outer gene function, selection for the outer gene alters the permitted inactivating mutations in the inner gene, and that overlapping toxins can restrict horizontal gene transfer of the antibiotic resistance gene. Overall, OAFI offers a versatile tool for synthetic biology, expanding the applications of overlapping genes in gene stabilization and biocontainment.

Iron is an essential micronutrient for nearly all microorganisms, yet its bioavailability is severely limited in most environments. To overcome this restriction, microorganisms produce siderophores, high-affinity iron-chelating molecules that play pivotal roles in microbial iron homeostasis, interspecies competition, and host–pathogen interactions. Despite extensive research, current understanding of siderophore biosynthetic and regulatory diversity remains largely limited to specific models, with comprehensive cross-taxonomic frameworks only beginning to emerge. This review systematically integrates recent advances in the genetic and biochemical foundations of microbial siderophore production, focusing on the two major biosynthetic pathways: nonribosomal peptide synthetase (NRPS)-dependent and NRPS-independent synthetase (NIS). We further elaborate on the diverse transport systems in Gram-negative and Gram-positive bacteria, as well as fungi, alongside the iron-responsive regulators (e.g., Fur) and gene clusters that coordinate iron uptake and utilization. Beyond physiological mechanisms, we discuss how these insights inform emerging applications of siderophores across multiple fields: in medicine, enabling “Trojan horse” antimicrobial strategies; in agriculture, enhancing plant iron uptake and serving as biocontrol agents; in environmental remediation, facilitating heavy-metal detoxification; and in biosensing, acting as selective probes for metals and pathogens. By bridging fundamental mechanisms with practical applications, this review aims to provide an integrative perspective for future exploration of microbial iron homeostasis and its biotechnological potential.

Recombinant E. coli with nitrogen-fixation activity has been constructed using a simple approach of introducing a minimal gene set of nitrogen fixation genes along with its upstream region from Paenibacillus species; however, limitations may exist in nif expression. To understand the limitations of heterologous mass production of nitrogenase in E. coli, we evaluated this approach using various nif operons cloned from Paenibacillus species. Initial attempts revealed that, despite the high nitrogenase activity observed in the parental strains, the corresponding nif operons did not consistently function in E. coli. Further analysis revealed that certain upstream regions of the nif operons function as constitutive σ70-dependent promoters in E. coli, and the host acquired nitrogenase activity only when the upstream region acted as a constitutive promoter. Notably, recombinant E. coli achieved high nitrogenase activity by linking a functional upstream region to the nif operon from a highly active parental strain. Additional improvements in nitrogenase activity were achieved by combining promoter replacement with synthetic biology approaches to enhance electron transfer from glucose metabolism to nitrogenase and metal cluster assembly for protein maturation. These findings provide new insights into heterologous nitrogenase production in E. coli for sustainable nitrogen fixation.

Efficient delivery remains a major challenge for therapeutic genome editing because many widely used CRISPR nucleases are large and leave limited space for regulatory elements or additional payloads in a single adeno-associated virus (AAV) vector. Miniature Cas12 nucleases are particularly appealing, as their reduced size alleviates packaging constraints while preserving RNA-guided DNA cleavage. Here, we outline a workflow that links large-scale sequence mining with phylogenetic and structural filtering, followed by PAM profiling, in vitro cleavage, bacterial genome interference, and genome-editing assays in human cells to confirm activity. This protocol is intended to distill broad sequence collections into a small set of compact Cas12 nucleases with demonstrated functions that can serve as starting points for further engineering in delivery-limited settings.

Synthetic gene circuits often behave unpredictably in batch cultures, where shifting physiological states are rarely accounted for in conventional models. Here, we find that degradation-tagged protein reporters could exhibit transient oscillatory expression, which standard single-scale models do not capture. We resolve this discrepancy by developing Gene Expression Across Growth Stages (GEAGS), a dual-scale modeling framework that explicitly couples intracellular gene expression to logistic population growth. Using a chemical reaction network model with growth phase–dependent rate-modifying functions, GEAGS accurately reproduces the observed transient oscillations and identifies amino acid recycling and growth-phase transition as key drivers. We reduce the model to an effective form for practical use and demonstrate its adaptability by applying it to layered feedback circuits, resolving long-standing mismatches between model predictions and measured dynamics. These results establish GEAGS as a generalizable platform for predicting emergent behaviors in synthetic gene circuits and underscore the importance of multiscale modeling for robust circuit design in dynamic environments.

This work constructed a recombinant lactic acid bacterium secreting β-galactosidase for GOS formation during milk fermentation. First, GalINF, a β-galactosidase derived from infant feces, was characterized to effectively produce GOS in milk, reaching a content of 10.03 g/L. To export GalINF in Lactococcus lactis, six signal peptide candidates were employed, resulting in extracellular activities as low as 52.83–85.65 U/L. Then, GalINF (114.6 kDa) was split into two complementary modules, M1-P723 and A724-I1023, which could be independently secreted and actively reconstituted with the help of the protein scaffold SpyCatcher/SpyTag. The resultant Lc. lactis B1RG exhibited an extracellular β-galactosidase activity of 544.22 U/L. Fermentation of pasteurized milk with Lc. lactis B1RG and the traditional yogurt starters reduced lactose to 19.67 g/L and yielded 7.17 g/L GOS. This work established an effective strategy to export large-sized proteins extracellularly and demonstrated the applicability of LAB secreting β-galactosidase for GOS-enriched fermented dairy products.