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Record W7105989612 · doi:10.7939/83293

Exploring the Survival Strategies of Aerobic Methanotrophs in Oxygen-Limited Conditions; an Interdisciplinary Approach

2025· dissertation· en· W7105989612 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial metabolism and enzyme function
Canadian institutionsnot available
Fundersnot available
KeywordsMethanotrophObligateMethaneOrganismBiomass (ecology)Anaerobic oxidation of methaneMicroorganismBacteria

Abstract

fetched live from OpenAlex

Anthropogenic pollution is a critical threat to life on Earth. Methane is a powerful greenhouse gas, emitted directly to the atmosphere as a polluting byproduct of many industries. It is also emitted from natural sources, and it is produced by microbes whose growth is promoted by other anthropogenic pollutants, such as nitrogen fertilizers and the growing accumulation of human and domestic animal waste. Luckily, nature contains a group of opportunistic, counterbalancing microorganisms capable of consuming methane and converting it into biomass or value-added products. These so-called methanotrophs are the organisms which are featured in this dissertation, and in particular, a sub-group of aerobic methanotrophs that survive in environments where oxygen is transiently available. One model organism representing this group is a methanotroph in the class Gammaproteobacteria, Methylomonas denitrificans FJG1. This bacterium is an obligate aerobe, requiring oxygen to survive, yet it has recently been discovered to simultaneously consume methane and nitrate in a combined metabolic pathway which allows the bacterium to survive for extended durations without access to oxygen. This unique ability also corresponds with a profound phenotypic change from a cream colour to bright pink when oxygen is depleted. The first aim of this thesis was to investigate the molecular responses of M. denitrificans FJG1 to oxygen limitation and its regulation of the methane and denitrification pathways. Searching a combined set of transcriptome and proteome data measuring the gene expression and protein production of M. denitrificans FJG1 collected before, during, and after oxygen depletion, a strong candidate protein for oxygen binding and delivery was identified. This gene was found to be highly upregulated in response to decreasing oxygen availability, and the corresponding protein was produced in very high abundance. The gene, annotated as bacteriohemerythrin, is a homologue, or copy, of a gene for a pink-coloured iioxygen-transport protein found in the blood of annelid worms that lack the usual hemoglobin employed by most animals. In Chapter 2, comparative genomics between M. denitrificans FJG1, other methanotrophic microorganisms, and other non-methanotrophic bacteria revealed ten homologues in the genome of M. denitrificans FJG1 alone. One, designated bhr-00 was specific to methanotrophs in the Methylococcales order. The predicted structure of this Bhr protein is similar to a previously characterized Bhr-Bath protein shown to bind and deliver O2 to support methane oxidation in the methanotroph, Methylococcus capsulatus Bath. In Chapter 3, this discovery of the methanotroph-specific Bhr-00 protein was employed as a biomarker, in correlation with the most often used pmoA biomarker, to identify aerobic methanotroph activity in the anoxic regions of a Canadian Boreal lake (Lake 227) using metatranscriptome data. Aerobic methanotrophs in the order Methylococcales have been identified in bacterial communities of many anoxic environments, yet the metabolism that supports their presence and abundance has not yet been solved, particularly in how they access requisite O2 to support methane oxidation. Both bhr-00 and pmoA transcripts were found in methanotroph metagenome assembled genomes (MAGs) reconstructed from Lake 227 and the metatranscriptome indicated they are upregulated in a manner similar to M. denitrificans FJG1 under oxygen limitation. In addition, genes for gas vesicles and extracellular electron transport were upregulated in some of the methanotroph MAGs indicating they have evolved distinctive methods for utilizing bhr in conjunction with motility and alternative terminal electron acceptors in Lake 227. In Chapter 4, a gene regulatory network (GRN) was developed based on differential gene expression of M. denitrificans FJG1 grown under oxygen limitation and two different nitrogen sources across a six point time course, through the development of a methodology incorporating unsupervised machine learning (ML) algorithms. This methodology was able to capture and interpret complex regulatory patterns contained in the gene expression values iiiof 12 individual sampling points by combining two different ML algorithms (ARACNE and GENIE3) and retaining only those network connections agreed upon by both algorithms. A comprehensive workflow was developed to strategically maximize confidence in these models to interpret the links between genes and their regulators when comparing across growth conditions. Chapter 5 presents an overall conclusion and future research directions for further understanding of methanotrophs in anoxic ecosystems and their genomic regulation as they transition from one physicochemical context to another. Taken together, the work presented in this dissertation identified a key methanotroph-specific protein, Bhr-00, that promotes survival of Methylococcales bacteria in ecosystems with limited oxygen availability. This information connected laboratory observations from a model methanotroph strain with the activity of related methanotrophs in a natural lake ecosystem and showed potential mechanisms that allow methanotrophs in the Methylococcales order to thrive in anoxic zones. Last, a new method for interpreting gene regulatory networks, called ProGRN, was developed with the potential for increasing scientific return on transcriptome data. The resulting GRN revealed regulatory connections between methane oxidizing genes and bhr-00 by way of transcription factors sigma 70 and sigma 24, shedding new light on the regulatory system of methanotrophs when faced with oxygen depletion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.232
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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