Peatlands are among the largest natural sources of atmospheric methane (CH 4 ) worldwide. Microbial processes play a key role in regulating CH 4 emissions from peatland ecosystems, yet the complex interplay between soil substrates and microbial communities in controlling CH 4 emissions as a function of global change remains unclear.Herein, we performed an integrated analysis of multi-omics data sets to provide a comprehensive understanding of the molecular processes driving changes in greenhouse gas (GHG) emissions in peatland ecosystems with increasing temperature and sulfate deposition in a laboratory incubation study. We sought to first investigate how increasing temperatures (4, 21, and 35°C) impact soil microbiome-metabolome interactions; then explore the competition between methanogens and sulfate-reducing bacteria (SRBs) with increasing sulfate concentrations at the optimum temperature for methanogenesis. Our results revealed that peat soil organic matter degradation, mediated by biotic and potentially abiotic processes, is the main driver of the increase in CO 2 production with temperature. In contrast, the decrease in CH 4 production at 35°C was linked to the absence of syntrophic communities and the potential inhibitory effect of phenols on methanogens. Elevated temperatures further induced the microbial communities to develop high growth yield and stress tolerator trait-based strategies leading to a shift in their composition and function. On the other hand, SRBs were able to outcompete methanogens in the presence of non-limiting sulfate concentrations at 21°C, thereby reducing CH 4 emissions. At higher sulfate concentrations, however, the prevalence of communities capable of producing sufficient lowmolecular-weight carbon substrates for the coexistence of SRBs and methanogens was translated into elevated CH 4 emissions. The use of omics in this study enhanced our understanding of the structure and interactions among microbes with the abiotic components of the system that can be useful for mitigating GHG emissions from peatland ecosystems in the face of global change.

Background Microbiomes are now recognized as the main drivers of ecosystem function ranging from the oceans and soils to humans and bioreactors. However, a grand challenge in microbiome science is to characterize and quantify the chemical currencies of organic matter (i.e., metabolites) that microbes respond to and alter. Critical to this has been the development of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), which has drastically increased molecular characterization of complex organic matter samples, but challenges users with hundreds of millions of data points where readily available, user-friendly, and customizable software tools are lacking. Results Here, we build on years of analytical experience with diverse sample types to develop MetaboDirect, an open-source, command-line-based pipeline for the analysis (e.g., chemodiversity analysis, multivariate statistics), visualization (e.g., Van Krevelen diagrams, elemental and molecular class composition plots), and presentation of direct injection high-resolution FT-ICR MS data sets after molecular formula assignment has been performed. When compared to other available FT-ICR MS software, MetaboDirect is superior in that it requires a single line of code to launch a fully automated framework for the generation and visualization of a wide range of plots, with minimal coding experience required. Among the tools evaluated, MetaboDirect is also uniquely able to automatically generate biochemical transformation networks (ab initio) based on mass differences (mass difference network-based approach) that provide an experimental assessment of metabolite connections within a given sample or a complex metabolic system, thereby providing important information about the nature of the samples and the set of microbial reactions or pathways that gave rise to them. Finally, for more experienced users, MetaboDirect allows users to customize plots, outputs, and analyses. Conclusion Application of MetaboDirect to FT-ICR MS-based metabolomic data sets from a marine phage-bacterial infection experiment and a Sphagnum leachate microbiome incubation experiment showcase the exploration capabilities of the pipeline that will enable the research community to evaluate and interpret their data in greater depth and in less time. It will further advance our knowledge of how microbial communities influence and are influenced by the chemical makeup of the surrounding system. The source code and User’s guide of MetaboDirect are freely available through (https://github.com/Coayala/MetaboDirect) and (https://metabodirect.readthedocs.io/en/latest/), respectively.

Background: Microbiomes are now recognized as main drivers of ecosystem function ranging from the oceans and soils to humans and bioreactors. However, a grand challenge in microbiome science is to characterize and quantify the chemical currencies of organic matter (i.e. metabolites) that microbes respond to and alter. Critical to this has been the development of Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), which has drastically increased molecular characterization of complex organic matter samples, but challenges users with hundreds of millions of data points where readily available, user-friendly, and customizable software tools are lacking. Results: Here, we build on years of analytical experience with diverse sample types to develop MetaboDirect, an open-source, command-line based pipeline for the analysis, visualization, and presentation of metabolomics data by direct injection FTICR-MS after molecular formula assignment has been performed. When compared to all other available FTICR software, MetaboDirect is superior with respect to its compute time as it only requires a single line of code that launches a fully automated framework for the generation and visualization of a wide range of plots, with minimal coding experience required. Among the tools evaluated, MetaboDirect is also uniquely able to automatically generate biochemical transformation networks (ab initio) based on mass differences that provide a comprehensive experimental assessment of metabolite connectives within a given sample or a complex metabolic system, thereby providing important information about the nature of the samples and the set of the microbial reactions or pathways that gave rise to them. Finally, for more experienced users, MetaboDirect allows users to customize plots, outputs, and analyses. Conclusion: Application of MetaboDirect to FTICR-MS-based metabolomics datasets from a marine phage-bacterial infection experiment and a Sphagnum leachate microbiome incubation experiment showcase the exploration capabilities of the pipeline that will enable the FTICR-MS research community to evaluate and interpret their data in greater depth and in less time. It will further advance our knowledge of how microbial communities influence and are influenced by the chemical makeup of the surrounding system. Source code and User guide of MetaboDirect are freely available through (https://github.com/Coayala/MetaboDirect) and (https://metabodirect.readthedocs.io/en/latest/) respectively.