E. coli couples the initiation of DNA replication with cell size by modulating the activity of the replication initiator protein DnaA. The activity of DnaA is regulated by both its interconversion between an active and inactive form and its titration on binding sites on the chromosome. Whereas its interconversion has been thoroughly studied, the extent to which DnaA titration can control replication initiation is poorly understood. Here, we describe the control of E. coli DNA replication via titration by modulating the expression of an 'always-active' DnaA variant in four growth conditions. While we obtained stable cell cycles during slow growth, faster growth associated with overlapping replication forks led to replicative instability and DNA damage. Overall, our results provide insights into the limits of titration-based systems in the control of genome replication and their potential role in the evolutionary trajectory of E. coli. Finally, this study provides design principles for a simplified, titration-only regulatory mechanism for DNA replication in synthetic cells.

Microbial death pathways (MDPs) are increasingly recognized as key drivers of terrestrial carbon cycling, primarily through their regulation of microbial necromass carbon (MNC), a critical pool in global carbon dynamics. Yet explicit representation of MDPs in soil organic carbon (SOC) models remains limited. Here, we developed and evaluated three SOC models that differ in their structure of MNC pool: the multiple-pathway necromass (MPN) model, which partitions microbial necromass carbon (MNC) into four MDP-derived subpools; the dual necromass (DUN) model, which differentiates two necromass pools with distinct decay rates; and the single necromass (SIN) model, which aggregates necromass into a single pool. Using a unified data assimilation framework and SOC observations from six major agricultural regions in China, we found that the MPN model consistently outperformed DUN and SIN models across most regions, producing necromass subpool dynamics, scenario responses, and parameter sensitivities that closely reflect the mechanistic understanding of MDPs. In cold or nutrient-limited regions, however, the simpler DUN model performed similarly while requiring fewer parameters, emphasizing the importance of balancing model complexity with regional ecological constraints. Our results demonstrate that explicitly incorporating MDPs enhances the robustness and mechanistic realism of SOC simulations and provides a robust foundation for more explicit representations of MDPs to assess the soil carbon sequestration potential and guide sustainable land management.

Metagenomic workflows involve complex multi-step analyses, from quality control and assembly to binning, annotation, and strain-level profiling. Few existing metagenomic pipelines achieve the combination of flexibility, reproducibility, and hybrid assembly support within a unified workflow. We present StrainMake, a Snakemake-based workflow for de novo metagenomic analysis from short, long, or hybrid sequencing data. StrainMake   integrates widely used tools across all major steps—quality control, assembly, binning, dereplication, taxonomic and functional annotation—while also providing non-redundant gene catalogues, community-scale metabolic models, and strain-level microdiversity metrics. The modular design enables the use of alternative tools, scalable execution on HPC systems, and full reproducibility through Snakemake and Conda. Applied to the CAMI II strain-madness dataset, StrainMake   produced high-quality assemblies and metagenome-assembled genomes (MAGs), while enabling strain-resolved comparisons across samples. Hybrid assemblies improved contiguity, whereas short-read assemblies offered faster runtimes, illustrating the workflow’s benchmarking capacity.

Brown rot wood-degrading fungi release carbon (C) from deadwood but leave behind a large fraction of C sequestered in lignin residues or as fungal metabolites. The strength of sequestration in these C residuals remains unclear, but proteobacteria-dominated bacterial communities have been implicated in metabolizing C from decay residues, possibly erasing the C sequestration potential assumed for brown rot. Here, we paired a model brown rot fungus (Rhodonia placenta) with a model Alphaproteobacterium (Rhodopseudomonas palustris) to track fungal release and bacterial utilization of C derived from decaying wood. We found that fungal decay products generated by R. placenta could be used by R. palustris for growth, and later decay stages contained more usable substrates than early stages. High performance liquid chromatography with mass spectrometry identified a range of aromatic and non-aromatic compounds in the fungal-decayed wood, but after 95 days of bacterial growth, R. palustris preferentially consumed non-aromatic acids over aromatic lignin monomers. Genes involved with aromatic compound degradation were unimportant for bacterial growth, and RNA sequencing revealed that aromatic compound degradation genes were repressed on decayed wood extract. Randomly barcoded transposon sequencing failed to identify a solitary catabolic pathway used by R. palustris, suggestive of substrate co-utilization, and surprisingly, showed that genes involved with copper toxicity were essential. Finally, we found that genes involved with biosynthesis of certain cofactors and amino acids were no longer essential on decayed wood extract, suggesting these nutrients were readily accessible. This study helps lay the foundation to understand potential bacterial-fungal interactions in decayed wood.

Designing minimal biological systems with emergent functions such as spatiotemporal self-organization is a central goal of bottom-up synthetic biology. While computational optimization and design show promises to accelerate functional protein engineering through Design-Build-Test-Learn cycles, screening libraries for complex functions remains a major challenge. Conventional screens typically lack the spatiotemporal resolution and cell-like confinement required in bottom-up synthetic biology. Here, we present PUREdrop, an automated microfluidic platform that encapsulates and expresses protein libraries in thousands of picolitre-sized synthetic cells per construct. These droplets are sorted into a 96-well plate and analyzed by time-lapse imaging, allowing parallel quantification of expression kinetics and emergent functions. To demonstrate the platform's potential, we first screened computationally re-designed variants of the bacterial cell division protein FtsZ, identifying variants with improved bundling phenotypes and faster kinetics. We then extended our screening procedure towards general protein modulators of FtsZ and identified a combination that anchors filaments to the interface, producing a ring-like phenotype. PUREdrop bridges computational protein engineering and synthetic cell research, elevating the rational engineering of complex biological function to the next level.

The eukaryotic genome is non-randomly organized within the nucleus, with positioning linked to function. Still, genome-wide radial maps are missing for the majority of experimental model systems. We adapted Genomic loci Positioning by Sequencing (GPSeq) to Saccharomyces cerevisiae, enabling high-resolution mapping along the nuclear cente–periphery axis. GPSeq confirms known spatial features and shows that peripheral telomeres and centromeres impose long-range constraints extending up to 200 kb, restricting short chromosome arms from the nuclear interior. Telomere repositioning to the nuclear center, either artificially or during quiescence, reorganizes much of the genome through inward movement of sub telomeric regions and compensatory shifts of mid-arm chromatin outward. In quiescence, reduced centromere peripheral localization further alters genome organization. While transcription has a modest impact on radial positioning in all studied conditions, we uncover that in the absence of centromere or telomere constraints, GC–content functionally organizes chromatin in the nucleus.

Genetic code expansion introduces new-to-nature chemical moieties into ribosomally synthesized proteins. In practice, the scope of functional groups that can be accessed using this method is often limited by noncanonical amino acid (ncAA) availability. Producing ncAAs directly in cells can circumvent poor ncAA uptake or commercial unavailability, but limited enzymes suitable for this application exist. In vitro evolution campaigns have been remarkably successful in yielding synthetically useful "ncAA synthases." However, these enzymes are optimized for preparative-scale synthesis and their activities often do not translate well to cellular biosynthesis. Thus, expanding strategies to engineer enzymes specifically for ncAA production within cells will benefit further implementation of genetic code expansion. Here, we use phage-assisted noncontinuous and continuous evolution to evolve enzymes for improved synthesis of non-canonical tyrosine derivatives in E. coli. Using simple serial passaging, we uncovered mutations that doubled the production of an expensive ncAA, 3-methoxytyrosine, by tyrosine phenol lyase, and furthermore evolved variants that enable 3-iodotyrosine biosynthesis, a transformation the parent enzyme is unable to catalyze. Additionally, we evolved a recently reported tyrosine synthase for improved production of 3-halogenated tyrosines, identifying variants that exhibit high activity even at low substrate concentrations owing to a ~8-fold reduction in KM. Our results demonstrate that phage assisted evolution can be used to rapidly improve the activity of enzymes for ncAA production in cells.

Budding yeast Saccharomyces cerevisiae is a workhorse chassis for producing added food and agricultural compounds. However, building multi-enzymatic pathways for these chemicals often requires iterative genomic integration, underscoring the need for efficient, rapid genome-editing tools that can reliably target transcriptionally active chromosomal regions. In this study, to accelerate strain construction, we established a genome-editing toolkit to rapidly engineer eight loci, highly expressed hot-spots, but nonessential genomic sites suitable for stable pathway assembly. Our approach integrates three key design features: (i) selectable markers to enable rapid screening of edited cells, (ii) extended homology arms that leverage the yeast homology-directed repair machinery for robust genomic integration, and (iii) co-delivery of Cas9 and guide RNAs to promote efficient double-stranded DNA breaks at specific integration sites. The sequence independence of FASTOP relies on the release of integration cassettes from integrative vectors, mediated by restriction digestion at two flanking multiple-cutting sites in the integration module to minimize the risk of introducing sequence errors during PCR amplification of the integration cassettes. Following the introduction of a fluorescent reporter cassette, we observed high integration efficiencies across the target sites. We then integrated the biosynthetic pathway of plant-derived flavonoid naringenin into the hot-spots of the yeast genome using the FASTOP toolkit. Our results demonstrated that upon expressing the five essential genes in simple shake flask culture, naringenin production reached 505.7 mg/L, representing a significant (69-fold) increase over previously reported titers for comparable minimal heterologous pathways in S. cerevisiae. Together, the FATSOP toolkit provides a user-friendly platform for reliably modifying hot-spot loci to rapidly construct multi-enzymatic metabolic pathways in S. cerevisiae, while achieving high production levels for high-value food-relevant metabolites.

Crop nutrition depends on plant-microbe interactions, yet it remains unclear whether conserved genetic pathways impose universal rules on root microbiome assembly across plant hosts. Here, we show that the Common Symbiosis Signalling Pathway (CSSP), a conserved genetic module controlling endosymbiosis with arbuscular mycorrhizal fungi and nitrogen-fixing bacteria, regulates root microbiome assembly in a host-specific manner across contrasting fertilization regimes. Using Lotus japonicus and Hordeum vulgare, we demonstrate that mutations in orthologous CSSP genes remodel root bacterial communities in both species, but with distinct taxonomic outcomes. In Lotus, CSSP disruption reduces rhizobial colonization and promotes niche replacement by commensal taxa, whereas in Hordeum, the same mutations broadly restructure bacterial lineages without converging on Lotus-like responses. Root exudate profiling reveals host-specific metabolic differences, particularly in phenylpropanoid (flavonoids and coumarins) and gibberellin pathways, linking CSSP activity to chemically distinct rhizosphere environments that correlate with divergent microbiome assembly patterns across hosts. Moreover, root bacterial community composition accurately predicts plant nutritional status, highlighting tight coupling between host physiology and microbiome composition. Together, our results show that conserved symbiosis signalling regulates root microbiome assembly, while host-specific metabolic environments determine taxonomic outcomes. This extends CSSP function beyond canonical endosymbioses and positions symbiosis signalling as a general determinant of plant-microbiome interactions with implications for crop nutrition.

Variants affecting RNA splicing are a major contributor to human disease, yet the consequences of variants outside of the canonical splice motifs are often difficult to determine. Here, we present a protocol for minigene-based evaluation of candidate splice-altering variants. The methodology described includes locus-specific insert design, commercial gene fragment synthesis, and long-read sequencing. The combined approach enables rapid assay development and nucleotide level resolution of the effect on splice isoforms in vitro, providing a scalable framework for functional validation of predicted cryptic splice variants.