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Anaerobic digestion (AD) is a well-established waste-to-value technology commonly used at water resource recovery facilities (WRRFs), generating biogas from organic waste. However, the generated biogas is typically used only for heat and electricity generation due to contaminants, while the nutrient-rich AD effluent requires further treatment before environmental release. Methanotroph-microalgae cocultures have recently emerged as promising candidates for integrated biogas valorization and nutrient recovery. Although the choice of the coculture pairs is one of the most important factors that determine the performance of the application, there have not been any results on the comparison or screening of different coculture pairs for a desired application. To expedite the screening of methanotroph-microalgae cocultures for optimal performance, we developed a cost-effective screening system consisting of nine parallel bioreactors. The compact design of the system allows it to fit in a fume hood, and enables the simultaneous evaluation of multiple species with triplicates under uniformly controlled conditions. The system was applied to screen seven methanotrophs, five microalgae, and six methanotroph-microalgae coculture pairs on a diluted AD effluent from a local WRRF. To systematically assess the growth performance of different monocultures and cocultures, mathematical models that describe the microbial growth under batch cultivation were developed to determine the maximum growth rate, delay time, and carrying capacity from growth data, allowing for consistent and systematic assessment of different species, as well as the identification of the coculture pairs with synergistic and inhibitory interactions. The developed experimental system and modeling approach enabled expedited strain screening and unbiased assessment for integrated biogas valorization and nutrient recovery. Specifically, the cost of each bioreactor system in S3 is less than 5% of commercially available bioreactor system (such as Bioflo 120), while the screening throughput of S3 is 9 times that of a single bioreactor system. In addition, the identified synergistic cocultures demonstrate potential for scalable biogas valorization and nutrient recovery in wastewater treatment. 

Aim: Metabolic interactions within a microbial community play a key role in determining the structure, function, and composition of the community. However, due to the complexity and intractability of natural microbiomes, limited knowledge is available on interspecies interactions within a community. In this work, using a binary synthetic microbiome, a methanotroph-photoautotroph (M-P) coculture, as the model system, we examined different genome-scale metabolic modeling (GEM) approaches to gain a better understanding of the metabolic interactions within the coculture, how they contribute to the enhanced growth observed in the coculture, and how they evolve over time. Methods: Using batch growth data of the model M-P coculture, we compared three GEM approaches for microbial communities. Two of the methods are existing approaches: SteadyCom, a steady state GEM, and dynamic flux balance analysis (DFBA) Lab, a dynamic GEM. We also proposed an improved dynamic GEM approach, DynamiCom, for the M-P coculture. Results: SteadyCom can predict the metabolic interactions within the coculture but not their dynamic evolutions; DFBA Lab can predict the dynamics of the coculture but cannot identify interspecies interactions. DynamiCom was able to identify the cross-fed metabolite within the coculture, as well as predict the evolution of the interspecies interactions over time. Conclusion: A new dynamic GEM approach, DynamiCom, was developed for a model M-P coculture. Constrained by the predictions from a validated kinetic model, DynamiCom consistently predicted the top metabolites being exchanged in the M-P coculture, as well as the establishment of the mutualistic N-exchange between the methanotroph and cyanobacteria. The interspecies interactions and their dynamic evolution predicted by DynamiCom are supported by ample evidence in the literature on methanotroph, cyanobacteria, and other cyanobacteria-heterotroph cocultures. 

Driven by increasing greenhouse gas (GHG) concentrations in the atmosphere, extreme weather events have become more frequent and their impacts on human lives have become more severe. Therefore, the need for short-term GHG mitigations is urgent. Recently, methane has been recognized as an important mitigation target due to its high global warming potential (GWP). However, methane’s low concentration in the atmosphere and stable molecular structure make its removal from the air highly challenging. This review first discusses the fundamental aspects of the challenges in atmospheric methane removal and then briefly reviews the existing research strategies following the mechanisms of natural methane sinks. Although still in its infancy, recent research on methane removal from the air holds great potential for slowing down global warming. At the same time, it is important to carefully examine the energy consumption of these methane removal strategies and whether they will be able to achieve net GHG reduction. In addition, due to the scale of methane removal from the air, any potential solution’s environmental impacts must be carefully evaluated before it can be implemented in practice.