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Methane (CH4) is a potent greenhouse gas with rising atmospheric concentrations.
Microorganisms are essential players in the global methane cycle. In fact, the largest part of methane emissions derives from microbial production by methanogenic Archaea (methanogens). Microorganisms do not only produce methane: methanotrophs can also oxidize the methane produced by methanogens. In addition, soil methanotrophs are the only biological methane sink, oxidizing up to 30-40 Tg of this potent greenhouse gas per year worldwide.
However, intensified management of grasslands and forests may reduce the methane sink capacity of soils.
In general, the interaction of methanogens and methanotrophs determines whether a soil is a source or a sink for methane. It is, therefore, crucial to understand the microbial part of the methane cycle and which factors influence the abundance and activity of methane-cycling microbes. However, capturing the soil microbiome's abundances, activity, and identity is
challenging. There are numerous target molecules and myriad methods, each with certain
limitations. Linking microbial markers to methane fluxes is therefore challenging. This thesis aimed to understand how methane-cycling microbes in the soil are related to soil methane fluxes and how soil characteristics and human activity influence them.
The first publication investigated the biotic and abiotic drivers of the atmospheric methane sink of soils. It assessed the influence of grassland land-use intensity (150 sites) and forest management type (149 sites) on potential atmospheric methane oxidation rates (PMORs) and the abundance and diversity of CH4-oxidizing bacteria (MOB) with qPCR in topsoils of three temperate regions in Germany. PMORs measured in microcosms under defined conditions were approximately twice as high in forest than in grassland soils. High land-use intensity of grasslands negatively affected PMORs (−40%) in almost all regions. Among the different aspects of land-use intensity, fertilization had the most adverse effect reducing PMORs by 20%.
In contrast, forest management did not affect PMORs in forest soils. Upland soil cluster (USC)α was the dominant group of MOBs in the forests. In contrast, USCγ was absent in more than half of the forest soils but present in almost all grassland soils. USCα abundance had a direct positive effect on PMOR in forests, while in grasslands, USCα and USCγ abundance affected PMOR positively with a more pronounced contribution of USCγ than USCα.
In the second publication, we used quantitative metatranscriptomics to link methane-cycling microbiomes to net surface methane fluxes throughout a year in two grassland soils. Methane fluxes were highly dynamic: both soils were net methane sources in autumn and winter and net methane sinks in spring and summer. Correspondingly, methanogen mRNA abundances per
gram soil correlated well with methane fluxes. Methanotroph to methanogen mRNA ratios were higher in spring and summer when the soils acted as net methane sinks. Furthermore, methane uptake was associated with an increased proportion of USCα and γ pmoA and pmoA2 transcripts. High methanotroph to methanogen ratios would indicate methane sink properties.
Our study links the seasonal transcriptional dynamics of methane-cycling soil microbiomes for the first time to gas fluxes in situ. It suggests mRNA transcript abundances as promising indicators of dynamic ecosystem-level processes.
We conclude that reduction in grassland land-use intensity and afforestation can potentially increase the methane sink function of soils and that different parameters determine the microbial methane sink in forest and grassland soils. Furthermore, this thesis suggests mRNA transcript abundances as promising indicators of dynamic ecosystem-level processes. Methanogen transcript abundance may be used as a proxy for changes in net surface methane emissions from grassland soils.
An Innovative Protocol for Metaproteomic Analyses of Microbial Pathogens in Cystic Fibrosis Sputum
(2021)
Hallmarks of cystic fibrosis (CF) are increased viscosity of mucus and impaired mucociliary clearance within the airways due to mutations of the cystic fibrosis conductance regulator gene. This facilitates the colonization of the lung by microbial pathogens and the concomitant establishment of chronic infections leading to tissue damage, reduced lung function, and decreased life expectancy. Although the interplay between key CF pathogens plays a major role during disease progression, the pathophysiology of the microbial community in CF lungs remains poorly understood. Particular challenges in the analysis of the microbial population present in CF sputum is (I) the inhomogeneous, viscous, and slimy consistence of CF sputum, and (II) the high number of human proteins masking comparably low abundant microbial proteins. To address these challenges, we used 21 CF sputum samples to develop a reliable, reproducible and widely applicable protocol for sputum processing, microbial enrichment, cell disruption, protein extraction and subsequent metaproteomic analyses. As a proof of concept, we selected three sputum samples for detailed metaproteome analyses and complemented and validated metaproteome data by 16S sequencing, metabolomic as well as microscopic analyses. Applying our protocol, the number of bacterial proteins/protein groups increased from 199-425 to 392-868 in enriched samples compared to nonenriched controls. These early microbial metaproteome data suggest that the arginine deiminase pathway and multiple proteases and peptidases identified from various bacterial genera could so far be underappreciated in their contribution to the CF pathophysiology. By providing a standardized and effective protocol for sputum processing and microbial enrichment, our study represents an important basis for future studies investigating the physiology of microbial pathogens in CF in vivo – an important prerequisite for the development of novel antimicrobial therapies to combat chronic recurrent airway infection in CF.