Predicting partner fitness based on spatial structuring in a light-driven microbial community.

Microbial communities have vital roles in systems essential to human health and agriculture, such as gut and soil microbiomes, and there is growing interest in engineering designer consortia for applications in biotechnology (e.g., personalized probiotics, bioproduction of high-value products, biosensing). The capacity to monitor and model metabolite exchange in dynamic microbial consortia can provide foundational information important to understand the community level behaviors that emerge, a requirement for building novel consortia. Where experimental approaches for monitoring metabolic exchange are technologically challenging, computational tools can enable greater access to the fate of both chemicals and microbes within a consortium. In this study, we developed an in-silico model of a synthetic microbial consortia of sucrose-secreting Synechococcus elongatus PCC 7942 and Escherichia coli W. Our model was built on the NUFEB framework for Individual-based Modeling (IbM) and optimized for biological accuracy using experimental data. We showed that the relative level of sucrose secretion regulates not only the steady-state support for heterotrophic biomass, but also the temporal dynamics of consortia growth. In order to determine the importance of spatial organization within the consortium, we fit a regression model to spatial data and used it to accurately predict colony fitness. We found that some of the critical parameters for fitness prediction were inter-colony distance, initial biomass, induction level, and distance from the center of the simulation volume. We anticipate that the synergy between experimental and computational approaches will improve our ability to design consortia with novel function.

Developing Cyanobacterial Quorum Sensing Toolkits: Toward Interspecies Coordination in Mixed Autotroph/Heterotroph Communities.

There has been substantial recent interest in the promise of sustainable, light-driven bioproduction using cyanobacteria, including developing efforts for microbial bioproduction using mixed autotroph/heterotroph communities, which could provide useful properties, such as division of metabolic labor. However, building stable mixed-species communities of sufficient productivity remains a challenge, partly due to the lack of strategies for synchronizing and coordinating biological activities across different species. To address this obstacle, we developed an inter-species communication system using quorum sensing (QS) modules derived from well-studied pathways in heterotrophic microbes. In the model cyanobacterium, Synechococcus elongatus PCC 7942 (S. elongatus), we designed, integrated, and characterized genetic circuits that detect acyl-homoserine lactones (AHLs), diffusible signals utilized in many QS pathways. We showed that these receiver modules sense exogenously supplied AHL molecules and activate gene expression in a dose-dependent manner. We characterized these AHL receiver circuits in parallel with Escherichia coli W (E. coli W) to dissect species-specific properties, finding broad agreement, albeit with increased basal expression in S. elongatus. Our engineered "sender" E. coli strains accumulated biologically synthesized AHLs within the supernatant and activated receiver strains similarly to exogenous AHL activation. Our results will bolster the design of sophisticated genetic circuits in cyanobacterial/heterotroph consortia and the engineering of QS-like behaviors across cyanobacterial populations.

Characterization of a novel herbicide and antibiotic-resistant Chlorella sp. with an extensive extracellular matrix.

A herbicide and antibiotic-resistant microalgal strain, isolated from a eutrophic site at Giofyros river (Heraklion, Crete, Greece) was extensively characterized. In the presence of relatively high concentrations of common photosynthesis inhibitors (DCMU and atrazine), as well as various antibiotics (spectinomycin, kanamycin, and chloramphenicol), the green microalga was able to increase its biomass in approximately equal levels compared to the control. Despite the high concentrations of the inhibitors, photosynthetic efficiency and chlorophyll a amount per dry cell biomass were comparable to those of control cultures in almost all cases. 18S rDNA analysis showed that this microalga belongs to the Chlorella genus. Optical and electron microscopy studies revealed the presence of an extensive extracellular matrix (EM) that surrounds the cells and plays an important role in colony formation and cell-cell interactions. Fourier transform infrared spectroscopy provided evidence that the EM consists of a polysaccharide. This matrix could be separated from the cells with a simple centrifugation. Depending on growth conditions, the dry cell biomass of this Chlorella strain was found to contain 35-39% proteins and 27-42% carbohydrates. The results of this study have demonstrated that the EM plays a protective role for cell homeostasis maintenance against the various chemical agents. This green microalga is a suitable candidate for further studies regarding sustainable biomass production in waste waters for a series of applications.