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Vapor-Fed Cathode Microbial Electrolysis Cells with Closely Spaced Electrodes Enables Greatly Improved Performance
Hydrogen can be electrochemically produced in microbial electrolysis cells (MECs) by current generated from bacterial anodes with a small added voltage. MECs typically use a liquid catholyte containing a buffer or salts. However, anions in these catholytes result in charge being balanced predominantly by ions other than hydroxide or protons, leading to anode acidification. To enhance only hydroxide ion transport to the anode, we developed a novel vapor-fed MEC configuration lacking a catholyte with closely spaced electrodes and an anion exchange membrane to limit the acidification. This MEC design produced a record-high sustained current density of 43.1 ± 0.6 A/m 2 and a H 2 production rate of 72 ± 2 LH 2 /L-d (cell voltage of 0.79 ± 0.00 V). There was minimal impact on MEC performance of increased acetate concentrations, solution conductivity, or anolyte buffer capacity at applied voltages up to 1.1 V, as shown by a nearly constant internal resistance of only 6.8 ± 0.3 mΩ m 2 . At applied external voltages >1.1 V, the buffer capacity impacted performance, with current densities increasing from 28.5 ± 0.6 A/m 2 (20 mM phosphate buffer solution (PBS)) to 51 ± 1 A/m 2 (100 mM PBS). Furthermore, these results show that a vapor-fed MEC can produce higher and more stable performance than liquid-fed cathodes by enhancing transport of hydroxide ions to the anode.
Thermophilic microbial deconstruction and conversion of natural and transgenic lignocellulose
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Interactive effects of biochar amendment and lead toxicity on soil microbial community
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Inside the microbial black box: a redox-centric framework for deciphering microbial metabolism
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Tendencies of Soil Microbial NO Emissions During HI‐SCALE as Predicted by a Nitrification/Denitrification Scheme
Many atmospheric chemical processes, including the formation of secondary organic aerosol (SOA), are strongly modulated by the reactions of NO and NO 2 (NO x ). Though NO x is controlled by anthropogenic emissions near urban areas, in rural areas soil microbes can be a significant contribution to NO emission globally. The relative rates of emissions of different nitrogen-containing species (e.g., NO, N 2 O, HONO, and N 2 ) are strong functions of soil properties such as temperature, moisture content, pH, and soil carbon and nitrogen pools. However, typical large-scale biogeochemical models either express these emissions simplistically, or not at all. Here we investigate the potential impact of soil NO emissions on atmospheric chemistry and SOA formation over regional and monthly time scales, specifically the 2016 spring and summer Intensive Observational Periods (IOPs) of the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign. We implement the soil NO nitrification/denitrification parameterization of Rasool et al. (2019) into the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), supplemented by a 1-km soil moisture analysis. We then simulate both IOPs over the U.S. Great Plains, evaluating against ground stations and flight data. We show that soil NO emissions can account for a large fraction of total NO x and locally increase O 3 concentrations by up to 25%, while alleviating negative biases of gases and aerosols toward observations. Soil moisture and temperature changes between IOP1 and IOP2 lead to overall differences in emissions, but with large regional variability due to heterogeneous surface characteristics.
A Reproducible and Tunable Synthetic Soil Microbial Community Provides New Insights into Microbial Ecology
Microbes associate with plants in distinct soil communities to the benefit of both the soil microbes and the plants. Interactions between plants and these microbes can improve plant growth and health and are therefore a field of study in sustainable agricultural research.
Microbial Models for Simulating Soil Carbon Dynamics: A Review
Abstract Soils store the largest amount of carbon (C) in the biosphere, and the C pool in soil is critical to the global C balance. Numerous microbial models have been developed over the last few decades to represent microbial processes that regulate the responses of soil organic carbon (SOC) to climate change. However, the representation of microbial processes varies, and how microbial processes are incorporated into SOC models has not been well explored. Here, we reviewed 71 microbial models to characterize the microbial processes incorporated into SOC models and analyzed variations in mechanistic complexity. We revealed that (a) four processes (microbial‐mediated decomposition, mineral interaction, microbial necromass recycling, and active and dormant microbial dynamics) are commonly incorporated in microbial models, (b) ∼48% of models simulate only one microbial process (i.e., microbial‐mediated decomposition) and 35% of models simulate two microbial processes: for example, microbial‐mediated decomposition and mineral interaction, (c) more than 80% microbial models use nonlinear equations, such as forward Michaelis‐Menten kinetics, to represent SOC decomposition, (d) the concept of persistence of SOC due to its intrinsic properties has been replaced by organo‐mineral interaction (∼39% of microbial models) that protects SOC from decomposition, and (e) various temperature and moisture modifiers and pH effects have been used to explain the environmental effect on microbial processes. In the future, to realistically incorporate microbial processes into Earth System Models, it is imperative to identify experimental evidence on rate limitation processes and firmly ground model structure on the field and laboratory data.
Necromass responses to warming: A faster microbial turnover in favor of soil carbon stabilisation
Microbial byproducts and residues (hereafter ‘necromass’) potentially play the most critical role in soil organic carbon (SOC) sequestration. However, little is known about the influence of climate warming on necromass accumulation in the agroecosystem and the underlying mechanisms associated with microbial life strategies. Here, in order to address these knowledge gaps, we used amino sugars as biomarkers of microbial necromass, and investigated their variation through an 8-year trial in an agroecosystem with two warming levels (+1.6 and + 3.2 °C) compared to ambient temperature. The results showed that the lower warming level had no impact on total microbial necromass carbon. Conversely, warming the soil 3.2 °C above ambient increased total microbial necromass by 17 % and its contribution to SOC by 21.3 %, mainly by increasing fungal necromass (+19.8 %), whereas +3.2 °C warming had no impact on bacterial necromass. At the phylum level, compared with the ambient control, +3.2 °C warming induced an increase in the abundance of Proteobacteria and a decrease in both Acidobacteria and Actinobacteria, whereas in the fungal community, Ascomycota increased and Mortierellomycota decreased. This indicates that r-strategists outcompete K-strategists in warmer climates, which led to increased microbial necromass production and accumulation, as supported by the positive correlation between r-strategists and microbial necromass. Stronger microbial competition for resources also resulted in a higher biomass turnover rate, greater cell death, and greater production of microbial necromass. This was supported by the lower bacterial and fungal network complexity and trophic links under warming conditions. In addition, the necromass generated from accelerated microbial turnover further offsets warming-induced deceases in microbial biomass. Consequently, bulk SOC did not change, despite microbial necromass having a much greater response to warming than the soil C pool. Therefore, future climate warming may influence the composition and persistence of SOC during microbial degradation.
Microbial necromass in cropland soils: A global meta-analysis of management effects
Microbial necromass is a large and persistent component of soil organic carbon (SOC), especially under croplands. The effects of cropland management on microbial necromass accumulation and its contribution to SOC have been measured in individual studies but have not yet been summarized on the global scale. For this study, we conducted a meta-analysis of 481-paired measurements from cropland soils to examine the management effects on microbial necromass and identify the optimal conditions for its accumulation. Nitrogen fertilization increased total microbial necromass C by 12%, cover crops by 14%, no or reduced tillage (NT/RT) by 20%, manure by 21%, and straw amendment by 21%. Microbial necromass accumulation was independent of biochar addition. NT/RT and straw amendment increased fungal necromass and its contribution to SOC more than bacterial necromass. Manure increased bacterial necromass higher than fungal, leading to decreased ratio of fungal-to-bacterial necromass. Greater microbial necromass increases after straw amendments were common under semi-arid and in cool climates in soils with pH <8, and were proportional to the amount of straw input. In contrast, NT/RT increased microbial necromass mainly under warm and humid climates. Manure application increased microbial necromass irrespective of soil properties and climate. Management effects were especially strong when applied during medium (3–10 years) to long (10+ years) periods to soils with larger initial SOC contents, but were absent in sandy soils. Close positive links between microbial biomass, necromass and SOC indicate the important role of stabilized microbial products for C accrual. Microbial necromass contribution to SOC increment (accumulation efficiency) under NT/RT, cover crops, manure and straw amendment ranged from 45% to 52%, which was 9%–16% larger than under N fertilization. In summary, long-term cropland management increases SOC by enhancing microbial necromass accumulation, and optimizing microbial necromass accumulation and its contribution to SOC sequestration requires site-specific management.
METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks
Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.
Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology
Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.