Research focus
The Michener team studies the interactions between heterologous metabolic pathways and their new hosts. These pathways may have transferred between strains either in nature through horizontal gene transfer, or in the laboratory through metabolic engineering and synthetic biology. Nothing inside a cell acts as a black box, and interactions between host and pathway can determine whether a newly-acquired pathway functions in a recipient strain as efficiently as it does in its native host.
Much of the research in the lab involves genetic modification of non-model microbes. We use high-throughput screens and selections for untargeted discovery, combined with lower-throughput validation of particular genetic modifications. The lab is investigating the use of microfluidics and machine learning to link non-growth phenotypes to genetic variation on a genome-wide scale.
Pathway Discovery:
In many cases, the phenotypes that we wish to study have no known genetic basis, which limits our ability to transfer or optimize that phenotype. In these situations, we must first identify the genes that are required for the phenotype, potentially uncovering new biology. We then use a combination of bacterial genetics and in vitro biochemistry to validate novel enzymes.
Relevant publications:
Pathway Transfer:
Once we identify a pathway of interested, we typically reconstruct that pathway in a new host to verify that we have all the necessary genetic elements and to determine the range of organisms in which the pathway functions. From an engineering perspective, knowing when you can reuse a particular pathway in a new strain simplifies the design process. In nature, understanding the genetic and physiological factors that limit post-transfer pathway function helps us to understand and predict horizontal gene transfers.
Relevant publications:
Host/Pathway Optimization:
Pathways frequently function poorly after transfer into a new host or environment. In these cases, we identify mutations that improve pathway activity, and then work backwards from those mutations to uncover the deleterious interactions that were previously limiting pathway activity. Once we know the interactions between host and pathway, we can design pathways and select hosts to minimize these interactions. We are additionally using directed evolution to optimize enzymes for new reactions and environments.
Relevant publications:
Much of the research in the lab involves genetic modification of non-model microbes. We use high-throughput screens and selections for untargeted discovery, combined with lower-throughput validation of particular genetic modifications. The lab is investigating the use of microfluidics and machine learning to link non-growth phenotypes to genetic variation on a genome-wide scale.
Pathway Discovery:
In many cases, the phenotypes that we wish to study have no known genetic basis, which limits our ability to transfer or optimize that phenotype. In these situations, we must first identify the genes that are required for the phenotype, potentially uncovering new biology. We then use a combination of bacterial genetics and in vitro biochemistry to validate novel enzymes.
Relevant publications:
- Presley GN†, Werner AZ†, et al., Pathway discovery and engineering for cleavage of a β-1 lignin-derived biaryl compound. Metab Eng 2021. Link.
- Cecil JH et al., Rapid, parallel identification of pathways for catabolism of lignin-derived aromatic compounds in Novosphingobium aromaticivorans. 2018. Appl Env Microbiol 84 (22) e01185-18. Link.
Pathway Transfer:
Once we identify a pathway of interested, we typically reconstruct that pathway in a new host to verify that we have all the necessary genetic elements and to determine the range of organisms in which the pathway functions. From an engineering perspective, knowing when you can reuse a particular pathway in a new strain simplifies the design process. In nature, understanding the genetic and physiological factors that limit post-transfer pathway function helps us to understand and predict horizontal gene transfers.
Relevant publications:
- Michener JK, et al., Transfer of a catabolic pathway for chloromethane in Methylobacterium strains highlights different limitations for growth with chloromethane or with dichloromethane. Front Microbiol 2016. Link
- Michener JK, et al., Phylogeny poorly predicts the utility of a challenging horizontally-transferred gene in Methylobacterium strains. J Bacteriol., June 2014 196:2101-2107 Link.
Host/Pathway Optimization:
Pathways frequently function poorly after transfer into a new host or environment. In these cases, we identify mutations that improve pathway activity, and then work backwards from those mutations to uncover the deleterious interactions that were previously limiting pathway activity. Once we know the interactions between host and pathway, we can design pathways and select hosts to minimize these interactions. We are additionally using directed evolution to optimize enzymes for new reactions and environments.
Relevant publications:
- Millet L, et al., Genetic selection for small molecule production in competitive microfluidic droplets. ACS Synth Biol 2019. Link.
- Close D, et al., Horizontal transfer of a pathway for coumarate catabolism unexpectedly inhibits purine nucleotide biosynthesis. Mol Microbiol 2019. Link
- Clarkson SM, et al., Construction and optimization of a heterologous pathway for protocatechuate catabolism in Escherichia coli enables bioconversion of model aromatic compounds. Appl Env Microbiol 2017. Link.
- Michener JK, et al., Effective use of a horizontally-transferred pathway for dichloromethane catabolism requires post-transfer refinement. eLife 2014. Link.
Center affiliations
Center for Bioenergy Innovation (CBI):
In CBI, we are developing tools for quantitative trait-locus mapping in P. putida and C. thermocellum for gene functional annotation.
Agile Biofoundry (ABF):
Within the ABF, we are investigating how pathways for catabolism of lignocellulosic sugars function (or fail to function) in diverse bacteria. If we transfer an optimized, engineered metabolic pathway from one bacterium into increasingly divergent hosts, how quickly does the pathway activity decrease, and why?
Plant Microbe Interfaces (PMI):
As part of PMI, we are interested in measuring the rates and consequences of horizontal gene transfer (HGT) in soil bacterial communities. We wish to understand how rapidly bacteria evolve through HGT and how pathway acquisition affects (or doesn't affect) a bacterium's interactions with the plant host.
Secure Ecosystem Engineering Design (SEED):
In SEED, we are investigating the genetic determinants of establishment and HGT in environmental strains of Bacillus. We wish to enhance or limit these processes when new strains are introduced into managed ecosystems such as biofuels plantations.
Center for Plastic Innovation (CPI):
Working with CPI, we are engineering enzymes to convert depolymerized plastic waste to new value-added polymer precursors.
In CBI, we are developing tools for quantitative trait-locus mapping in P. putida and C. thermocellum for gene functional annotation.
Agile Biofoundry (ABF):
Within the ABF, we are investigating how pathways for catabolism of lignocellulosic sugars function (or fail to function) in diverse bacteria. If we transfer an optimized, engineered metabolic pathway from one bacterium into increasingly divergent hosts, how quickly does the pathway activity decrease, and why?
Plant Microbe Interfaces (PMI):
As part of PMI, we are interested in measuring the rates and consequences of horizontal gene transfer (HGT) in soil bacterial communities. We wish to understand how rapidly bacteria evolve through HGT and how pathway acquisition affects (or doesn't affect) a bacterium's interactions with the plant host.
Secure Ecosystem Engineering Design (SEED):
In SEED, we are investigating the genetic determinants of establishment and HGT in environmental strains of Bacillus. We wish to enhance or limit these processes when new strains are introduced into managed ecosystems such as biofuels plantations.
Center for Plastic Innovation (CPI):
Working with CPI, we are engineering enzymes to convert depolymerized plastic waste to new value-added polymer precursors.