Genomics Basis for Molecular and Metabolic Resource Allocation Strategies in Methanotrophic Bacteria


Student thesis: Doctoral Thesis

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Award date14 Jan 2021


Rates of methane accumulation in the atmosphere have been increasing during the last century. Methane emissions from natural and anthropogenic sources are projected to rise over the next 30 years. Methanotrophic bacteria, which are microorganisms that can use methane as a carbon and energy source, are paramount to reduce the accumulation of methane in the environment. Methanotrophs act not only as a biological sink for methane but also as primary producers in several natural ecosystems, as the carbonic compounds excreted as by-products of methanotrophic methane metabolism can sustain diversity in microbial communities. Because methanotrophic bacteria can produce diverse chemicals, these organisms have been suggested as a promising scaffold for the biotech industry of the future. The possibility of using methanotrophic bacteria to produce value-added chemicals is attractive. However, the economics of this process is speculative, mainly because the conditions that modulate methanotroph phenotypes remain unclear. To better understand the phenotypic manifestations of different populations of methanotrophs, I applied genomic data science, molecular evolution, and systems biology methods, to investigate the molecular and metabolic strategies that methanotrophic bacteria have evolved to harness methane.

In the first section of this thesis, I investigated the molecular evolution of genes that encode enzymes that catalyze methane oxidation reactions. A thorough molecular characterization of the genomes of aerobic methanotrophs was conducted, with a particular focus on phylogenomics, nucleotide composition, codon usage bias, transcript biosynthesis cost, and protein translation efficiency. The results revealed that the type Ia phylogenetic group of aerobic methanotrophs harbors a variant of the pmoCAB operon (genes that encode enzymes involved in the methane to methanol conversion) with strong nucleotide and codon usage biases that can optimize methane oxidation by maximizing translation efficiency and accuracy while minimizing protein and transcript synthesis costs.

Having discovered that type Ia methanotrophs can optimize transcript synthesis costs through genomic codon usage biases, I further extended my research question to the entire tree of life of microorganisms. I then investigated whether the choice of codons can also control the energy required to unwind double-stranded (ds) DNA molecules by controlling the hydrogen bond number. I observed a generalizable phenomenon in which codon usage bias creates an exponential ramp of hydrogen bonding at the 5ʹ-ends of coding sequences in Bacteria and Archaea, thus creating a position-dependent energetic requirement for unwinding dsDNA.

To obtain a system-level overview of the metabolism of methane oxidation and tap into the knowledge gathered from the other sections of this thesis, I finally constructed a genome-scale metabolic model (GEM) of the type Ia methanotroph Methylomicrobium album BG8, a model organism in environmental microbiology and a promising microbial cell factory for the conversion of methane to value-added biochemicals. Time-series metabolomics data were collected from several experiments and further integrated into the GEM to construct multiple contextspecific GEMs and simulate metabolic fluxes under several conditions. The results revealed that trade-offs between the metabolic pathways lead to optimal biomass and metabolite production, suggesting that oxygen-to-methane uptake rate ratios have a strong effect on the metabolic resource allocation in M. album BG8 required for the efficient use of methane as a carbon source.

Overall, the investigation presented in this thesis generated novel insights into the molecular and metabolic strategies that aerobic methanotrophs, especially type Ia organisms, have developed to optimize methane oxidation catalysis. Moreover, the discoveries made for methanotrophs allowed me to further generalize my findings to the interplay between the molecular evolution of genes and the energy required by Bacteria and Archaea to unwind the DNA molecule. The findings presented here are expected to not only establish new knowledge in our field but also stimulate new research questions on the strategies that microorganisms have evolved to harness energy and interact with their environment.