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Optical biosensors and lipidomics for biophysical characterization of pMMO function

The conditions necessary for native pMMO function must be understood to enable heterologous expression for methane mitigation technologies.

Published onJan 26, 2025
Optical biosensors and lipidomics for biophysical characterization of pMMO function
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Note: A bug in PubPub's citation formatting is causing citations to appear as bare DOIs, so citations have been formatted as hyperlinks.

Contributors: Amy Rosenzweig1, Verena Kriechbaumer2, Eli Hornstein3, Arjun Khakar4, Jonas Wilhelm5, Rachel Strickman6, Paul Reginato7

Author contributions: This problem statement was outlined at a Workshop on Biological Methane Removal hosted by Homeworld Collective and Spark Climate Solutions in November, 2024. Paul Reginato and Rachel Strickman polished the outline into a final draft. All other authors outlined the problem statement at the workshop and gave feedback on later drafts.

Lead contact: Paul Reginato ([email protected])

Problem Statement

Motivating Factor

Novel technology for methane removal (MR) at 1-100 MtCH4 scale is needed, particularly for oxidizing atmospheric concentrations (2 ppm) (NASEM, 2024, Abernethy, 2024) and emissions at 2-1000 ppm that are too dilute to be scalably oxidized with existing technology (Abernethy, 2023).

Several MR strategies have been proposed that would leverage biological CH4 oxidation in engineered contexts. One example is methane oxidation bioreactors (Lidstrom, 2024); another is engineered crops or managed trees expressing methane monooxygenase (MMO) in their leaves or roots, which could oxidize CH4 in soil or ambient air (Strand, 2022; Spatola Rossi, 2023). 

Development of MMO-bearing plants or optimizing CH4 oxidation in reactors will require engineering, heterologous expression, and/or or context-specific characterization of MMO. However, significant challenges limit such manipulation of MMO, particularly the particulate MMO (pMMO), which is thought to have the highest affinity for CH4 (He, 2024; Reginato, 2024).

Specific Constraint

Native pMMO is embedded in intracytoplasmic membranes in ordered arrays of multi-subunit complexes (Tucci, 2024). While non-functional or low-activity protein complexes have been assembled outside the native host (Koo, 2022; Rossi, 2023; Gou, 2006), pMMO with near-full function has not been expressed outside of its native host. Further, substantial open questions remain about how the native membrane environment provides the necessary biophysical conditions for pMMO to function, which hinder efforts to heterologously express and engineer high-activity pMMO (Koo, 2021). 

The membrane potential, ion concentrations, redox state, and pH in the native environment of pMMO are expected to substantially impact enzyme function, but are uncharacterized. Additionally, an elaborate lipid environment has been identified around pMMO in the intracytoplasmic membrane, in which at least 20% of the lipids have not been identified (Woo, 2022; Tucci, 2024). Unidentified lipids may have a role in pMMO function. Determining these unknown biophysical parameters in the native context of pMMO would likely aid engineering efforts involving pMMO.

Actionable Goals 

To characterize biophysical factors in pMMO function, optical biosensors for voltage, pH, reactive oxygen species, and ions should be adapted for use in model methanotrophs with protocols for quantitative measurement through microscopy. These systems could include development of specific intracellular membrane localization tags for structures inside methanotrophs. Dye-based studies of the same factors, where applicable, should also be pursued.

To characterize the lipid environment in which pMMO is natively situated, lipidomics analysis (likely LC-MS based) of the pMMO array should be performed to  comprehensively identify not only known lipid species, but also to identify lipids not present in libraries used for analysis.

The biophysical characterization studies described here would be further empowered if coupled with forward- and reverse-genetic studies of pMMO function. To enable such studies, tools must be developed for generating mutant libraries of pMMO in methanotrophs; that challenge is discussed in a related problem statement (Reginato, 2024).

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