Towards an understanding of methylotrophic methane production in anoxic coastal sediments

Lead Research Organisation: Queen Mary University of London
Department Name: Sch of Biological & Behavioural Sciences

Abstract

Methane is a powerful greenhouse gas which significantly contributes to global warming. Coastal sediments are dynamic ecosystems with substantial methane production. Yet, we know very little about the diversity of microbes producing methane in these ecosystems. This prohibits our understanding of how methane production in coastal sediments is regulated under changing environmental conditions and the development of models for accurate prediction of the future global methane budget under climate change.

The major route to methane production in coastal sediments is the microbial degradation of methylated compounds, mainly methanol, trimethylamine (TMA) and dimethylsulfide (DMS). These compounds are highly abundant in the environment therefore lead to the production of substantial amount of methane. We recently found that the contribution of these compounds to the methane production in estuarine and saltmarsh sediments is likely underestimated and several different microbes convert TMA and DMS to methane in these sediments. Yet, we do not know which microbes actively convert these abundant methylated compounds to methane. This limits further research on the metabolic pathways of this process and how these pathways are regulated by environmental conditions (e.g. temperature and salinity). In this project, we aim to reveal the identity of the active microbes degrading methanol, TMA and DMS to methane in anoxic coastal sediments. This will not only open up new research avenues on global methane production but will also allow to develop models to predict future methane production in anoxic coastal sediments.

We are well suited for this study, because:
-we showed methanol, TMA and DMS are degraded to methane in a range of anoxic sediments.
-we studied the key gene in methane production in anoxic sediments, allowing us to pinpoint the underlying microbial diversity.
-we developed and used extensively the advanced microbiology tools such as stable isotope probing required for this study.

Our objectives:

1. Quantify the concentrations of methanol, TMA, DMS and methane in anoxic coastal sediments: We will quantify the depth distribution of methanol, TMA, DMS and methane concentrations in estuarine, coastal wetland and saltmarsh sediments. This will show the significance of each compound at sampling sites. This will enable us to design the stable isotope probing (SIP) experiments (Objective 2).


2. Identify the methanogens that actively degrade methanol, TMA and DMS to methane in anoxic coastal sediments: We will use the SIP-sequencing approach that we developed to elucidate the identity of active microbes that degrade methanol, TMA and DMS to methane. We will amend the samples with 13C-methanol, 13C-TMA and 13C-DMS, and follow the incorporation of 13C into the genetic material (DNA) of microbes degrading these compounds. Sequencing the 13C-labelled DNA, we will obtain unprecedented detail about these microbes' identity.

3. Determine the global distribution patterns of active methylotrophic methanogens in anoxic sediments: Using bioinformatics tools, we will search the publicly available sequence datasets for genetic markers from the active methanogens that we identify in Objective 2. This will include several advanced sequence datasets from marine and coastal ecosystems. Results will reveal the global distribution of dominant methanogens that degrade methanol, TMA and DMS in anoxic sediments across the world.

This project will answer critical questions as to the identity of the active microorganisms degrading ubiquitous compounds to methane in coastal sediments as well as their global distribution patterns. The outcome of this research programme will pave the way for future research that would focus on the metabolism of these key microbial species and how they response to changing environmental conditions. This will allow developing models for better prediction of future methane production in a changing climate.

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