Biomolecular condensates formed through liquid–liquid phase separation regulate cellular processes, and their dysregulation causes disease. Current methods for identifying endogenous phase-separating proteins have low throughput and cannot capture dynamic responses to stimuli. Here we present a protocol combining osmotic compression or transforming growth factor-β (TGF-β) treatment to induce condensation with sucrose density gradient centrifugation and quantitative mass spectrometry to enable systematic, high-throughput identification of endogenous condensates and phase-separating proteins. The method exploits the density changes that occur when phase-separating proteins undergo oligomerization during condensate formation. In H1975 cells, we identified over 1,500 phase-separating proteins under osmotic compression or TGF-β treatment; 538 of these candidates were not present in PhaSepDB, a database that compiles in vivo, in vitro and omics-derived proteins. The approach detects constitutive condensates and proteins that dynamically phase-separate in response to osmotic stress or TGF-β signaling. This protocol provides proteome-wide analysis of fractions of proteins having different densities and enables temporal resolution of phase-separation events. The procedure takes ~9 d and requires expertise in cell culture, biochemistry and mass spectrometry. This method enables systematic study of biomolecular condensates and disease-associated phase-separation mechanisms. This protocol identifies endogenous biomolecular condensates by combining sucrose density gradient centrifugation with quantitative mass spectrometry, enabling proteome-wide, stimulus-responsive profiling of phase-separating proteins.

Thermogenetics enables noninvasive spatiotemporal control over protein activity in living cells and tissues, yet its applications have largely been restricted to transcriptional regulation and membrane recruitment. Here, we present a generalizable strategy for engineering thermosensitive allosteric proteins through the insertion of optimized Avena sativa LOV2 domain variants. Applying this approach to a diverse set of structurally and functionally unrelated proteins in E. coli, we generated potent, thermoswitchable chimeric variants that can be tightly controlled within narrow temperature ranges (37–41 °C). Extending this strategy to mammalian systems, we engineered CRISPR–Cas genome editors directly modulated by subtle temperature changes within the physiological range. Lastly, we showcase the incorporation of a chemoreceptor domain as an alternative thermosensing module, suggesting thermosensitivity to be a widespread feature in receptor domains. This work expands the toolkit of thermogenetics, providing a blueprint for temperature-dependent control of virtually any protein of interest. Thermogenetics enables spatiotemporal control of protein activity using temperature. Now, engineering of a compact, insertable thermoresponsive protein module diversifies the classes of proteins amenable to allosteric thermoregulation.

genome editing: BASIS, bacterial artificial chromosome (BAC) stepwise insertion synthesis; BGM, B. subtilis genome; CasHRA, Cas9-facilitated Homologous Recombination Assembly; CONEXER, conjugation coupled with programmed excision for enhanced recombination; GC, guanine-cytosine; GENESIS, GENomE Stepwise Interchange Synthesis; HAnDy, Haploidization-based DNA Assembly and Delivery in yeast; IWe, inchworm elongation; MRA, meiotic recombination-mediated assembly; NA, not applicable; REXER, Replicon EXcision Enhanced Recombination; SwAP-In, switching auxotrophies progressively for integration; TAR, transformation-associated recombination; YLC, yeast life cycle.

Yarrowia lipolytica is a promising host for a range of biotechnological applications. However, the costs and sustainability of common feedstocks limit the commercial viability of current bioproduction. Consolidated bioprocessing using plant biomass offers a desirable alternative to reduce costs and improve sustainability, though such approaches are often constrained in single-organism systems due to metabolic burden. Here, we have investigated the use of division of labor (DOL) in Y. lipolytica consortia for the degradation of starch, a common component of plant biomass. We engineered a panel of strains expressing α-amylase and/or glucoamylase, with varying promoter and signal peptide combinations. We found that stronger expression led to higher metabolic burden, and that expressing both amylases imposed a greater burden than expressing either enzyme alone. When combining both amylase strains, we found that some consortia could achieve faster growth rates than the equivalent monoculture. The fastest growing consortium identified from the panel was scaled-up into flasks, where the consortium achieved the highest final biomass, although the fastest growth rate was achieved by the α-amylase strain alone. These findings suggest that DOL is a promising strategy for degrading complex macromolecules in plant biomass, offering a potential route to more sustainable bioprocessing.

Regulation of translation initiation is central to bacterial adaptation, but species-specific mechanisms remain poorly understood. We present high-resolution mapping of translation start sites in Staphylococcus aureus, revealing distinct features of initiation alongside numerous unannotated small ORFs. Our analysis, combined with cryo-EM of a native mRNA-ribosome complex, shows that S. aureus relies on extended, start codon proximal Shine-Dalgarno (SD) interactions, creating specificity against phylogenetically distant bacteria. Several natural S. aureus initiation sites are not correctly decoded by E. coli ribosomes. We identify new and conserved non-canonical start codons, whose regulatory initiation sites contain these characteristic extended SD sequence motifs. Finally, we characterize a novel example of uORF-mediated translational control in S. aureus, demonstrating that translation of a small leader peptide modulates expression of a key biofilm regulator. The described mechanism involves codon rarity, ribosome pausing, and arginine availability, linking nutrient sensing to biofilm formation in this major human pathogen. Kohl et al. combine high-resolution Ribo-seq and cryo electron microscopy to show that the bacterium Staphylococcus aureus uses extended Shine-Dalgarno motifs to initiate translation, which can make start-site decoding incompatible with phylogenetically distant ribosomes.

Bacteriophage infect, lyse, and propagate within bacterial populations. However, physiological changes in bacterial cell state can protect against infection even within genetically susceptible populations. One such example is the generation of endospores by Bacillus and its relatives, characterized by a reversible state of reduced metabolic activity that protects cells against stressors including desiccation, energy limitation, antibiotics, and infection by phage. Here we tested how sporulation at the cellular scale impacts phage dynamics at population scales when propagating amongst B. subtilis in spatially structured environments. Plaques resulting from infection and lysis were approximately 3-fold smaller on lawns of spore-forming bacteria vs. non-spore-forming bacteria. Analysis of plaque growth revealed that final plaque size was reduced due to an early termination of expanding phage plaques rather than the reduction of plaque growth speed. Microscopic imaging of the plaques revealed “sporulation rings”, i.e., spores enriched around plaque edges relative to phage-free regions. We developed a series of mathematical models of phage, bacteria, spore, and small molecules that recapitulate plaque dynamics. We show evidence that phage infections trigger the formation of sporulation rings that reduce the productivity of phage infections and halt plaque spread even when resources are available for infection and lysis further away from plaque centers. Moreover, sporulation rings are also enriched in viable virospores, suggesting that although dormancy limits phage infections at population scales in the near-term, viruses may co-opt phage-avoidance strategies to re-emerge over the long-term, opening new avenues to explore the entangled fates of phages and their bacterial hosts.

Synthetic microbial communities syncom, with different strains brought together by balancing their nutrition and promoting their interactions, demonstrate great advantages for exploring complex performance of communities and for further biotechnology applications. The potential of such microbial communities has not been explored, due to our limited knowledge of the extremely complex microbial interactions that are involved in designing and controlling effective and stable communities.  Genome-scale metabolic models (GEM) have been demonstrated as an effective tool for predicting and guiding the investigation and design of microbial communities, since they can explicitly and efficiently predict the phenotype of organisms from their genotypic data and can be used to explore the molecular mechanisms of microbe-habitats and microbe-microbe interactions. In this work, we reviewed two main categories of GEM-based approaches and three uses related to design of syncom: predicting multi-species interactions, exploring environmental impacts on microbial phenotypes, and optimizing community-level performance.  Although at the infancy stage, GEM-based approaches exhibit an increasing scope of applications in designing syncom. Compared to other methods, especially the use of laboratory cultures, GEM-based approaches can greatly decrease the trial-and-error cost of various procedures for designing syncom and improving their functionality, such as identifying community members, determining media composition, evaluating microbial interaction potential or selecting the best community configuration. Future efforts should be made to overcome the limitations of the approaches, ranging from quality control of GEM reconstructions to community-level modeling algorithms, so that more applications of GEMs in studying phenotypes of microbial communities can be expected.

As one of the representative protein materials, protein nanocages (PNCs) are self-assembled supramolecular structures with multiple advantages, such as good monodispersity, biocompatibility, structural addressability, and facile production. Precise quantitative functionalization is essential to the construction of PNCs with designed purposes.  With three modifiable interfaces, the interior surface, outer surface, and interfaces between building blocks, PNCs can serve as an ideal platform for precise multi-functionalization studies and applications. This review summarizes the currently available methods for precise quantitative functionalization of PNCs and highlights the significance of precise quantitative control in fabricating PNC-based materials or devices. These methods can be categorized into three groups, genetic, chemical, and combined modification.  This review would be constructive for those who work with biosynthetic PNCs in diverse fields.

Dietary fibers are crucial in shaping gut microbial composition and functionality. Physical complexity and chemical interactions between fibers and the gut environment lead to diverse and specialized responses that involve entire food webs of gut bacteria; however, there is comparatively less emphasis on understanding ecological dynamics to predict these outcomes. These responses may potentially promote either a broader (less specific) or narrower (more specific) group of gut bacterial taxa, which may vary across individuals. This review examines fiber specificity at the organismal and community levels by exploring mechanistic interactions among dietary fibers and gut bacteria. We discuss the interplay of exogenous and endogenous factors and the structure–function relationships influencing fiber specificity. We establish a mathematical framework to describe specificity in fiber–microbiome interactions based on directionality, magnitude, and stochasticity of fiber–microbiome ecological responses. Finally, we identify research gaps to enhance fiber–microbiota predictions, with implications for strategies aimed at optimizing fiber design.