Top-down and bottom-up microbiome engineering approaches to enable biomanufacturing from waste biomass
Xuejiao Lyu1, Mujaheed Nuhu1, Pieter Candry2
1Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Journal of Industrial Microbiology & Biotechnology
|July 13, 2024
Summary
Microbial consortia are engineered using top-down or bottom-up approaches for waste valorization and biomanufacturing. This review explores advancements and challenges in optimizing these microbial communities for resource recovery.
Area of Science:
- Biotechnology and Environmental Science
- Microbiology and Metabolic Engineering
Background:
- Growing environmental concerns necessitate waste valorization and circular economy principles.
- Microbial consortia are key to biomanufacturing valuable products from waste biomass, offering alternatives to petrochemicals.
Purpose of the Study:
- To review advancements, challenges, and opportunities in microbiome engineering for waste valorization.
- To explore top-down and bottom-up approaches for designing and optimizing microbial consortia.
Main Methods:
- Discusses top-down approach: selective steering of existing consortia using environmental variables.
- Explores bottom-up approach: designing synthetic consortia based on known metabolic pathways and interactions.
- Highlights integration of both approaches and metabolic modeling for optimization.
Main Results:
- Characterization of microbial communities is advanced by high-throughput sequencing, yet disentangling interactions remains challenging.
- Bottom-up approach offers control but faces challenges in assembly and stability.
- Review presents strategies, tools, and opportunities for optimizing microbial consortia design and stability.
Conclusions:
- Microbiome engineering using microbial consortia is crucial for sustainable waste valorization and biomanufacturing.
- Both top-down and bottom-up strategies, alongside integrated approaches, are vital for efficient resource recovery.
- Further research is needed to overcome challenges in consortium assembly, stability, and predictive modeling.


