About This Project
Enhancing the ability of methane monooxygenase (MMO) enzymes to oxidize atmospheric CH4 could substantially mitigate climate change by removing this greenhouse gas from the atmosphere. Here, we combine several novel technologies (Ligify, SELIS, SpeedyGenes, machine learning) to present a road map for engineering the bacterial transcription factor BmoR into a methane biosensor that can subsequently facilitate high-throughput enzyme engineering of MMOs.
Ask the Scientists
Join The DiscussionMotivating Factor
CH4 emissions have contributed ~30% of global warming to date [1] and natural sources may increase via feedback to warming [2]. Technologies for oxidizing atmospheric CH4, area CH4 emissions, and unavoidable point sources could substantially mitigate climate change. While CH4 above ~44,000 ppm can be flared, ~75% of CH4 pollution is atmospheric (2 ppm) or area emissions below 1000 ppm that are too dilute to be oxidized at scale using existing technologies [3].
Methane monooxygenase (MMO) enzymes, found in methanotrophic bacteria, naturally catalyze oxidation of CH4 to methanol in a one-step reaction at ambient conditions [4]. Oxidation of dilute CH4 at scale may be possible in engineered systems using methanotrophs or cell-free MMO, for example via flow-through reactors [5][6], or expression in plants [undefined]. Enhancing oxidation rate at low CH4 concentrations is necessary to achieve feasible cost and scalability for these applications.
Specific Bottleneck
Engineering MMO or screening many natural variants may provide a path to efficient CH4 oxidation. Of the two MMO families, soluble MMO (sMMO), a three-part enzymatic system, is a stronger candidate for engineering, since it faces fewer challenges to study, handling and heterologous expression compared to particulate MMO (pMMO) [4][7][8]. Nonetheless, sMMO presents barriers to engineering. The MMOH hydroxylase component of sMMO is challenging to express in E. coli. One study reported MMOH expression in E. coli using chaperones and solubility-enhancing mutations, but stopped short of engineering enhanced activity [9]. However, efficient protein engineering requires a method for rapidly characterizing variants. A system for robustly screening diverse natural and engineered sMMO variants, such as a methanol biosensor, would enable progress on engineering or discovering efficient sMMO.
Actionable Goals
Methods should be developed for robust screening of diverse natural and engineered sMMO variants. Such methods should handle >105 variants, and should facilitate rapid design of solubility, stability and/or activity enhanced versions of natural variants. A recently developed a platform in E. coli [10] provides a host for engineering sMMO but specific protein engineering has not yet been undertaken. Future protein engineering or natural homologue screening campaigns using this platform will require the development of efficient methods for characterizing the activity of large numbers of different variants. These will require nM range sensitivity, which can be achieved using biosensors based on allosteric transcription factors.
Budget
Total budget is for a salary for 1 year, consumables, essential travel and university overhead.
Meet the Team
Affiliates
Samuel Bradley
After studying molecular and cellular biochemistry at the University of Oxford, Dr. Samuel Bradley took up a PhD position in the Synthetic Biology Tools for Yeast group under Dr Michael Krogh Jensen at the NNF Centre for Biosustainability (Technical University of Denmark). During his PhD research, Dr Bradley developed a suite of S. cerevisiae strains capable of producing unnatural, halogenated variants of medicinal phytochemicals. Following the realization that many metabolic pathway engineering projects are limited by just one or two poorly performing enzymes, his research interests focused on how protein engineering techniques can be more integrated into the metabolic engineering workflow. In particular, how powerful new computational techniques that aid protein engineering, such as Alpha Fold, ESM, ProteinMPNN and RFDiffusion, can be combined with smart library design for rapid enzyme improvement. After being awarded his PhD in 2024, Dr Bradley took up a post-doctoral researcher position in the new Computational Protein Engineering group, led by Dr Carlos Acevedo-Rocha, at the Technical University of Denmark, where he is involved in a) developing a platform, ProteusAI, to allow biologists without technical computing knowledge to deploy machine learning models developed for protein engineering, and b) developing high-throughput methods for generating protein variant libraries for training machine learning algorithms.
Carlos Acevedo-Rocha
Dr Acevedo-Rocha leads the “Computational Protein Engineering” group at The Novo Nordisk Center for Biosustainabiltiy at the Technical University of Denmark. He researches how protein sequences determine structure and function. In particular, his group combines state-of-the-art experimental and computational approaches to understand and engineer proteins and enzymes to create more sustainable biosolutions for society while protecting the environment and human health. Previously, he worked at the Danish biotech company Biosyntia where he co-developed the world-first processes to produce B vitamins using renewable feedstocks (instead of fossil fuels). Before moving to Denmark, he took a postdoctoral position with Manfred Reetz, a pioneer in protein directed evolution and biocatalysis at the University of Marburg, Germany. He did his PhD in biotechnology in the area of genetic code expansion at the lab of Ned Budisa at the Max Planck Institute of Biochemistry near Munich, Germany. Carlos is well-known for developing innovative methods to engineer proteins using directed evolution. He has 5 patents and over 60 scientific publications in the areas of directed evolution, biocatalysis, metabolic engineering, bioinformatics, and machine learning. Currently, he supervises a culturally diverse, international and interdisciplinary team composed of 5 postdocs, 5 PhD students, 5 ressearch assistants as well as many MSc and BSc students.
Simon d'Oelsnitz
Dr. Simon d’Oelsnitz is a Synthetic Biology Fellow in the Systems Biology Department at Harvard Medical School. He leads a group within the Synthetic Biology HIVE focused on the development and application of small molecule-responsive biosensors. Dr. d’Oelsnitz received his B.S. in Pharmacology from Stony Brook University, and then went on to complete his PhD in Molecular Biology at the University of Texas at Austin where he was supervised by Profs. Andy Elllington, a pioneer in directed evolution, and Hal Alper, a renowned leader in metabolic engineering. There, Simon developed novel genetic selection systems to rapidly customize the chemical specificity of transcription factor-based biosensors for various high-value molecules, including terpenes and alkaloids. He has also developed a suite of software tools for the discovery, characterization, and documentation of chemical-responsive transcription factors. In 2022, Simon worked as a visiting researcher at the National Institute of Standards and Technology, where he used massively parallel reporter assays to simultaneously measure the performance of >100,000 biosensor variants. In 2023, Simon joined Harvard Medical School as a Synthetic Biology Fellow, where he is continuing to expand the palette of available biosensors for pharmaceuticals, hormones, metabolites, and environmental pollutants. Simon is also a project co-lead for the Datasets Initiative within Align to Innovate, which aims to collect large genotype-phenotype datasets in support of the predictive engineering of proteins.
Yosephine Gumulya
Dr Yosephine Gumulya is a Future Academic Leader in the School of Agriculture and Food Sustainability (AGFS) at the University of Queensland (UQ). She also leads a group at the UQ Biosustainability Hub in Australian Institute for Bioengineering and Nanotechnology. Her academic journey began after completing her PhD at the Max Planck Institute under Prof Reetz in protein engineering, Dr Gumulya joined UQ as a postdoctoral fellow where she developed novel tools for engineering highly thermostable and promiscuous enzymes. In 2016, she was awarded the prestigious Endeavour Scholarship to visit the lab of Prof Frances Arnold, a Noble Laureate in Chemistry, at Caltech in US. She then joined Commonwealth Scientific and Industrial Research Organisation (CSIRO) as Research Scientist, focusing on engineering microbes for metal leaching from low grade ores. In 2021, she moved to Queensland University of Technology as Senior Research Postdoctoral Research fellow, focusing on methane mitigation and gut microbiome engineering. In 2024, she returned to UQ as Future Academic leader. Her research focus on using synthetic and system biology approaches to engineer proteins, microbes and microbiomes. She has successfully secured $2.5 M in funding from National Health and Medical Research Council (NHMRC), CSIRO, the Food and Beverage Accelerator program, ARC Centre of Excellence, and multiple industry partners. She has published over 32 peer-reviewed journal articles and holds three patent applications in protein engineering. She has co-supervised more than six PhD candidates and supervised numerous master’s students. Dr Gumulya is a member of the Australian Society for Biochemistry and Molecular Biology and serves on the AGFS Early and Mid-Career Academics Committee. She frequently speaks at national and international conferences and symposiums, reflecting her role as an emerging academic leader in protein engineering.
Project Backers
- 0Backers
- 0%Funded
- $0Total Donations
- $0Average Donation



