Project description:Synthetic microbial consortia represent a new frontier for synthetic biology given that they can solve more complex problems than monocultures. However, most attempts to co-cultivate these artificial communities fail because of the ‘‘winner-takes-all’’ in nutrients competition. In soil, multiple species can coexist with a spatial organization. Inspired by nature, here we show that an engineered spatial segregation method can assemble stable consortia with both flexibility and precision. We create microbial swarmbot consortia (MSBC) by encapsulating subpopulations with polymeric microcapsules. The crosslinked structure of microcapsules fences microbes, but allows the transport of small molecules and proteins. MSBC method enables the assembly of various synthetic communities and the precise control over the subpopulations. These capabilities can readily modulate the division of labor and communication. Our work integrates the synthetic biology and material science to offer new insights into consortia assembly and server as foundation to diverse applications from biomanufacturing to engineered photosynthesis.
Project description:<p>Environmental co-contamination presents significant challenges. To tackle these, while microbial consortia offer advantages over single-strain approaches, such as functional redundancy and synergistic degradation, rationally designing effective synthetic microbiomes specifically for complex co-contamination scenarios remains a major challenge. Here, we utilized our advanced genome-scale metabolic modeling (GSMM) tool, SuperCC, to simulate the metabolic behavior of communities consisting of six isolated key strains under single- and multi-carbon source conditions, mimicking single-pollutant or co-contamination scenarios respectively. By integrating multi-omics data with metabolic modeling of cultured consortia, we systematically elucidated key strain interaction networks and adaptive strategies under co-contamination. This revealed that the specific secretory products of broad-spectrum resource-utilizing bacteria serve as key metabolites driving cooperation and highlighted the pivotal role of indigenous keystone strains in stabilizing and enhancing community function. Consequently, we propose a novel and rational paradigm for consortium design: DHP-Com (Degrader-Helper-Potentiator). Synthetic microbiomes constructed based on this framework exhibited enhanced ecological fitness (survival and growth) and, most importantly, substantially improved remediation performance across diverse co-contamination scenarios. Our findings advance the practical application of GSMM predictions to decipher intricate multi-pollutant/multi-strain interaction networks, offering a powerful rational framework and robust methodological tools for engineering multi-functional and effective synthetic microbiomes for complex environmental remediation.</p>
Project description:Microbial coexistence in complex communities requires mechanisms that minimize competition and optimize resource use. Here, we show that bacteria modulate protein abundance in response to specific community members, reducing functional redundancy and promoting metabolic complementarity. Using synthetic gut-derived consortia exposed to distinct carbon sources, we systematically profiled proteomic responses of individual species across isolate, pairwise, and four-member communities. We found that biotic interactions, rather than abiotic conditions, were the dominant drivers of proteomic variation. These interactions led to reproducible, partner-specific expression shifts that significantly reduced functional overlap and were frequently associated with increased community productivity. Our findings reveal that microbes dynamically reshape their realized niche through protein abundance plasticity, enabling them to partition metabolic space and stabilize community structure. This study provides a mechanistic link between microbial interaction networks, regulatory flexibility, and coexistence, offering a generalizable framework for understanding and engineering functional microbial ecosystems.
Project description:Microbial coexistence in complex communities requires mechanisms that minimize competition and optimize resource use. Here, we show that bacteria modulate protein abundance in response to specific community members, reducing functional redundancy and promoting metabolic complementarity. Using synthetic gut-derived consortia exposed to distinct carbon sources, we systematically profiled proteomic responses of individual species across isolate, pairwise, and four-member communities. We found that biotic interactions, rather than abiotic conditions, were the dominant drivers of proteomic variation. These interactions led to reproducible, partner-specific expression shifts that significantly reduced functional overlap and were frequently associated with increased community productivity. Our findings reveal that microbes dynamically reshape their realized niche through protein abundance plasticity, enabling them to partition metabolic space and stabilize community structure. This study provides a mechanistic link between microbial interaction networks, regulatory flexibility, and coexistence, offering a generalizable framework for understanding and engineering functional microbial ecosystems.
Project description:Metabolic sensors are microbial strains modified such that biomass formation correlates with the availability of specific target metabolites. These sensors are essential for bioengineering (e.g. in growth-coupled selection of synthetic pathways), but their design is often time-consuming and low-throughput. In contrast, in silico analysis can accelerate their development. We present a systematic workflow for designing, implementing, and testing versatile metabolic sensors using Escherichia coli as a model. Glyoxylate, a key metabolite in synthetic CO2 fixation and carbon-conserving pathways, served as the test molecule. Through iterative screening of a compact metabolic reconstruction, we identified non-trivial growth-coupled designs that resulted in six metabolic sensors with different glyoxylate-to-biomass ratios. These metabolic sensors had a linear correlation between biomass formation and glyoxylate concentration spanning three orders of magnitude and were further adapted for glycolate sensing. We demonstrate the utility of these sensors in pathway engineering (implementing a synthetic route for one-carbon assimilation via glyoxylate) and environmental applications (quantifying glycolate produced by photosynthetic microalgae). The versatility and ease of implementation of this workflow make it suitable for designing and building multiple metabolic sensors for diverse biotechnological applications.
Project description:Microbial consortia consist of a multitude of prokaryotic and eukaryotic microorganisms. Their interaction is critical for the functioning of ecosystems. Until now, there is limited knowledge about the communication signals determining the interaction between bacteria and fungi and how they influence microbial consortia. Here, we discovered that bacterial low molecular weight arginine-derived polyketides trigger the production of distinct natural products in fungi. These compounds are produced by actinomycetes found on all continents except Antarctica and are characterized by an arginine-derived positively charged group linked to a linear or cyclic polyene moiety. Producer bacteria can be readily isolated from soil as well as fungi that decode the signal and respond with the biosynthesis of natural products. Both arginine-derived polyketides and the compounds produced by fungi in response shape microbial interactions.