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.

Taxonomic classification alone fails to capture the ecological and functional diversity of vaginal microbiomes, particularly those dominated by Gardnerella species. Using the expanded VIRGO2 gene catalog, we developed the vaginal inference of subspecies and typing algorithm (VISTA), a novel ortholog-based framework that defined metagenomic subspecies and 25 metagenomic community state types (mgCSTs), including six distinct Gardnerella-dominated profiles. The mgCSTs exhibit marked differences in species composition, functional gene content, transcriptional activity, and host immune responses. These findings reveal that Gardnerella predominance does not uniformly equate to dysbiosis and underscore the importance of functional context in shaping host-microbiome interactions. VISTA provides scalable classifiers and an interactive application to support mechanistic studies of vaginal microbiome function and its implications for reproductive health.

Saturation mutagenesis is a powerful tool for understanding and engineering the function of biological systems, and has been applied successfully to characterize the mutational landscape of individual proteins and genetic loci. However, it has not been applied at the whole-genome scale due to the challenges of both creating and quantifying a saturating set of mutations. Here we introduce Biobloom, a retron-based method for barcoded saturation mutagenesis at the scale of a whole bacterial genome. We constructed a barcoded Biobloom library with >99% projected sampling of saturating single-nucleotide polymorphism (SNP) mutations of the E. coli genome, and applied it to identify beneficial mutations under salt and antibiotic selection. Relative to other techniques like CRISPR-enabled mutagenesis or Adaptive Laboratory Evolution, Biobloom excels at identifying diverse causal SNPs quickly and at smaller working volumes. A barcoded, saturating mutation library is also a shared resource, and we are releasing the updated Biobloom-E.coli-2.0 library to the scientific community for broader adoption and application. Together, Biobloom makes barcoded saturation mutagenesis accessible at whole-genome scale, creating new opportunities for large-scale data collection and bacterial engineering.

Antibiotic treatment can fail due to insufficient drug availability at the site of infection or limited accumulation within bacterial pathogens. However, it is poorly understood how antibiotics penetrate infected tissues and complex bacterial aggregates, limiting insights into the mechanisms of treatment failure. Here, we present genetically-encoded allosteric biosensors for two antibiotic classes, trimethoprim and tetracycline, which enable real-time monitoring of antibiotic concentrations inside bacterial cells. The biosensors consist of circularly permuted EGFP linked to the sensory domains DHFR or TetR. To extend this approach to low oxygen environments, we engineered an oxygen-independent trimethoprim biosensor by fusing DHFR to a circularly permuted version of the fluorogenic protein FAST. Using these biosensors, we monitored the antibiotic exposure dynamics of intracellular Salmonella enterica during macrophage infection at the single-cell level, and antibiotic penetration into anaerobic regions of Vibrio cholerae biofilms, as well as antibiotic availability in microoxic conditions in a human bladder tissue model infected with uropathogenic Escherichia coli. These fluorescent biosensors have the potential to be broadly applied for determining antibiotic distributions at infection sites with high spatial and temporal resolution.

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.

Biomass separation represents a critical bottleneck in Komagataella phaffii-based biopharmaceutical processes, as typically high cell densities of 40 - 50 % create significant operational, technical and economic challenges for harvest operations. Yeast cell aggregation (flocculation) provides a solution to accelerate cell sedimentation by increasing particle size, thus allowing to improve biomass-supernatant separation efficiency during both natural gravity settling and (continuous) centrifugation operations. This study demonstrates successful engineering of K. phaffii strains with an inducible flocculation phenotype using CRISPR/Cas9-based genome editing to integrate the Saccharomyces cerevisiae FLO1 (FLO1) gene under control of various regulatory elements, including methanol-inducible and derepressible promoters. Flocculation strength could be enhanced by implementing transcriptional positive feedback circuits based on the methanol-inducible AOX1 promoter. To address methanol-free production requirements, we developed alternative systems to retrofit PAOX1-based ScFLO1 expression and exploited the derepressible PDF promoter, offering broader compatibility with biopharmaceutical manufacturing facilities. Flocculating cells cultivated in a bioreactor demonstrated significantly improved sedimentation behavior, with considerably lower supernatant turbidity after short low-speed centrifugation compared to non-flocculating controls. Crucially, cell flocculation had no negative impact on product amount and quality when expressing a multivalent NANOBODY® VHH molecule with pharmaceutical relevance. Thus, this work establishes the first genetically engineered flocculation system in K. phaffii compatible with recombinant protein production, providing the basis for an innovative approach to streamline harvest operations in biopharmaceutical processes.

In synthetic biology, DNA assembly is a routine process where increasing demands for standardization, high-throughput capacity, and error-free execution are driving the development of accessible, automated solutions. Here, we present Slowpoke, a user-friendly and flexible workflow for Golden Gate-based cloning designed for the popular entry-cost, open-source liquid-handling platforms Opentrons OT-2 and Flex. Slowpoke automates the key steps of the DNA assembly process, including cloning, E. coli transformation, plating, and colony PCR, requiring user intervention primarily for colony picking and plate transfers. To further simplify the usage, we developed a free graphical user interface (GUI), available at https://slowpoke.streamlit.app/, which enables rapid protocol generation through simple file uploads. We validated the workflow using two Golden Gate-based toolkits, the MoClo Yeast Toolkit (YTK), and SubtiToolKit (STK). High assembly efficiencies were achieved across platforms for basic transcript unit constructions: 17/17 positive colonies with YTK on OT-2, 11/12 on Flex, and 8/13 with STK on OT-2. High-throughput assemblies were also performed with six parts in Flex using YTK-compatible parts, and 55 out of 57 combinations resulted in correct constructs. These results confirm the robustness and adaptability of the workflow across toolkit complexity and automation platforms. The Slowpoke suite, including code scripts and templates, is freely available at https://github.com/Tom-Ellis-Lab/Slowpoke, offering an accessible and modular solution for automating Golden Gate cloning in synthetic biology laboratories.