Biofilms are a form of microbial growth consisting of cells, often attached to a surface, embedded in a structured 3D extracellular matrix that confers important emergent properties such as increased resistance to physical removal and antimicrobials. Despite the importance of biofilms to a variety of systems and despite increasing attention from both the public and private sectors, high-throughput approaches to study them are scarce, limiting investigations of complex mechanisms critical for the structure and function of biofilms, such as interactions in multispecies communities. We thus developed a novel workflow to grow and analyze bacterial cells adhered to plastic beads encapsulated within highly parallel nanoliter-scale water-in-oil microfluidic droplets. We term this pipeline for bead-in-droplet biofilm cultivation and characterization BiDBiC. To benchmark BiDBiC, we utilized a well-characterized biofilm former, Stenotrophomonas maltophilia, as well as a poorly studied drinking water biofilm isolate, Sphingopyxis sp. OPL5. Each bacterium exhibited strong adherent growth when co-encapsulated with polystyrene beads in droplets. Furthermore, we retrieved beads from the droplets and removed planktonic cells, enabling focused analysis of adhered cells. From bead-associated biomass, we extracted DNA and RNA for molecular analysis and recovered viable cells for subculturing. We conclude with a discussion of further development of the platform as well as suggestions for microbial biofilm systems that may benefit from ultra-high-throughput droplet-enabled cultivation and analysis.

Ammonia oxidation is a rate-limiting step in the nitrogen cycle, yet viral contributions to this process remain largely unresolved. Here, we identify three genomically distinct groups of amoC-encoding phages (155-338 kilobases in length; termed as amoC-phages) from multiple freshwater lakes in Europe and North America, including the Laurentian Great Lakes. These phages are highly divergent in phylogeny, genome architecture, and gene content, and are predicted to infect two distinct Nitrosomonadaceae ammonia-oxidizing bacterial lineages. The placement of phage-encoded amoC genes across these divergent viral clades indicates independent acquisition of amoC. Time-series and depth-resolved metagenomes and metatranscriptomes reveal persistent and depth-structured distributions of amoC-phages and their predicted hosts, with seasonal mixing periodically reshaping their co-occurrence patterns. Furthermore, virome data from Lake Mendota show that some of the amoC-phages occur as free viral particles, supporting active viral lysis and particle redistribution along the water column. Metatranscriptomes of the Laurentian Great Lakes reveal coordinated expression of phage structural genes (e.g., major capsid protein) together with phage-encoded amoC, indicating active infection in situ. Together, these results support a framework in which amoC-phage infection is depth-structured, seasonally dynamic, and coupled to ammonia-oxidizing bacterial host activity, highlighting viruses as previously overlooked components of freshwater nitrogen cycling.

Serine integrases enable precise genome engineering but remain underused for iterative genome integration because current workflows are often labor-intensive and difficult to scale. Here, we report SARGE, a serine integrase-assisted rapid genome integration platform, that enables iterative insertion of large DNA fragments into the E. coli genome through cassette exchange. By combining the orthogonal serine integrases PhiC31 and Bxb1 with rational donor plasmid design, SARGE supports rapid, programmable integration cycles without the need for resistance marker excision between rounds. To simplify the identification of correct recombinants, we incorporated a dual-fluorescence reporter system based on sfGFP and mKate and developed a green–red screening strategy for direct, naked-eye colony selection. This visual screen identified the desired recombinants with 100% accuracy among the colonies tested. SARGE achieved cassette exchange efficiencies of up to 95% and maintained efficiencies of approximately 90% for cargoes as large as 10 kb. Together, these features substantially streamline iterative genome integration and establish SARGE as a robust and accessible platform for genome engineering and synthetic biology in E. coli, with potential for extension to other genetically tractable microbial hosts.

Ribosomal proteins contain flexible terminal regions that are averaged out during electron density reconstructions, rendering them absent from experimental models derived by X-ray crystallography or cryogenic electron microscopy. These flexible protein fragments (FPFs) collectively form an invisible coat on the ribosome surface whose presence has been systematically overlooked. Here we analyzed FPFs from 36 ribosomes spanning bacteria, eukaryotes, and mitochondria. We found that mitoribosomes harbor the most numerous and longest FPFs. Structural predictions confirmed that FPFs are predominantly disordered across all ribosome classes. Comparison of FPF amino acid composition against proteome-wide background frequencies revealed strong and domain-specific compositional biases. The balance between arginine and lysine content tracks the cardiolipin content of the membrane each ribosome class contacts. The arginine enrichment in mitoribosomal FPFs may additionally reflect selection arising from the RNA-rich environment of mitochondrial RNA granules, membraneless condensates where mitoribosomes are assembled. FPFs are uniformly depleted in aromatic residues, arguing against protein-driven liquid--liquid phase separation propensity. Our findings suggest that the flexibly tethered coat is a highly functional intrinsic part of all ribosomes.

Generative genome design models can now produce previously unobserved genome-length sequences, but assessing their capabilities is complicated by limitations in functional prediction. The ability to engineer genomes faster than we can understand them risks creating biosecurity vulnerabilities. To evaluate these potential risks systematically, we propose a framework that distinguishes between (i) evolutionary novelty, quantified through phylogenetic and sequence similarity to natural genomes; and (ii) design efficiency - the efficiency with which a model finds viable sequences compared to simple baseline generators. Applying this framework to bacteriophages designed by the genome language model Evo 2, we find that model likelihood strongly predicts experimental viability, capturing functional constraints beyond simple biological heuristics. However, this efficiency derives largely from staying close to previously observed sequences rather than exploring novel sequence space, reflecting the combined performance of the model and additional filters that were applied to its outputs. Compared to baselines of random mutagenesis and serial passage, the model achieves substantial design efficiency while its outputs remain phylogenetically close to natural genomes. We conclude that the generative capabilities of Evo 2 warrant low to moderate biosecurity concern for de novo hazard creation, although the degree to which these findings generalise to larger or less constrained viral architectures is an open question. Our framework enables an evidence-based capability assessment of generative genome design tools, informing future biosecurity evaluations.