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At least 307 records · Page 17

Application of Machine Learning Techniques to an Agent-Based Model of Pantoea

Agent-based modeling (ABM) is a powerful simulation technique which describes a complex dynamic system based on its interacting constituent entities. While the flexibility of ABM enables broad application, the complexity of real-world models demands intensive computing resources and computational time; however, a metamodel may be constructed to gain insight at less computational expense. Here, we developed a model in NetLogo to describe the growth of a microbial population consisting of Pantoea . We applied 13 parameters that defined the model and actively changed seven of the parameters to modulate the evolution of the population curve in response to these changes. We efficiently performed more than 3,000 simulations using a Python wrapper, NL4Py . Upon evaluation of the correlation between the active parameters and outputs by random forest regression, we found that the parameters which define the depth of medium and glucose concentration affect the population curves significantly. Subsequently, we constructed a metamodel, a dense neural network, to predict the simulation outputs from the active parameters and found that it achieves high prediction accuracy, reaching an R 2 coefficient of determination value up to 0.92. Our approach of using a combination of ABM with random forest regression and neural network reduces the number of required ABM simulations. The simplified and refined metamodels may provide insights into the complex dynamic system before their transition to more sophisticated models that run on high-performance computing systems. The ultimate goal is to build a bridge between simulation and experiment, allowing model validation by comparing the simulated data to experimental data in microbiology.

59 BASIC BIOLOGICAL SCIENCES↗

Revising the dynamic energy budget theory with a new reserve mobilization rule and three example applications to bacterial growth

Dynamic energy budget (DEB) theory has been applied to model a wide range of organisms, including microbes. In the standard DEB model, biomass is partitioned into reserve and structural compartments, where reserve biomass is mobilized in a pseudolinear manner (while the reserve biomass density, defined as the ratio between reserve and structural biomass, decays linearly) to drive maintenance and the growth of structural biomass (and extracellular enzyme production if it is considered). However, the linear dynamics of the reserve biomass density makes the standard DEB model incapable of explaining the slowdown of microbial growth at high reserve density that is caused by macromolecular crowding effect which reduces biochemical reaction rates (a typical situation occurs when microbes are experiencing severe moisture stress) and is inconsistent with the observation that intracellular enzymatic reactions generally follow non-linear kinetics. By partitioning biomass into reserve, kinetic, and structural compartments, we show here that the Equilibrium Chemistry Approximation (ECA) kinetics can be used to represent enzymatically catalyzed reserve biomass mobilization that can then drive the kinetic and structural biomass synthesis. This revised DEB model better represents the tradeoff in ribosome allocation for structural growth and internal enzyme production, is structurally compatible with metabolic models of cell individuals, and includes the standard DEB model and the popular compromise model as special cases for representing population growth. We then applied the revised DEB model to interpret components of bacterial respiration, their dependence on substrate availability, and emergent microbial carbon use efficiency dynamics for an exponentially growing population. We found that the revised DEB model enables a better understanding of bacterial substrates use (carbon in our examples) than that can be derived from a few other models in the literature. In particular, the revised DEB model explains why carbon use efficiency may first increase, then plateau, and finally decrease with growth rate (and substrate uptake rate), as a function of proteomics. Additionally, the revised DEB model explains why the kinetic biomass compartment needs to be divided to reasonably incorporate proteomic control of microbial growth.

59 BASIC BIOLOGICAL SCIENCES↗

Microbiological Methodology in Astrobiology

Searching for life in astromaterials to be delivered from the future missions to extraterrestrial bodies is undoubtedly related to studies of the properties and signatures of living microbial cells and microfossils on Earth. As model terrestrial analogs of Martian polar subsurface layers are often regarded the Antarctic glacier and Earth permafrost habitats where alive microbial cells preserved viability for millennia years due to entering the anabiotic state. For the future findings of viable microorganisms in samples from extraterrestrial objects, it is important to use a combined methodology that includes classical microbiological methods, plating onto nutrient media, direct epifluorescence and electron microscopy examinations, detection of the elemental composition of cells, radiolabeling techniques, PCR and FISH methods. Of great importance is to ensure authenticity of microorganisms (if any in studied samples) and to standardize the protocols used to minimize a risk of external contamination. Although the convincing evidence of extraterrestrial microbial life will may come from the discovery of living cells in astromaterials, biomorphs and microfossils must also be regarded as a target in search of life evidence bearing in mind a scenario that alive microorganisms had not be preserved and underwent mineralization. Under the laboratory conditions, processes that accompanied fossilization of cyanobacteria were reconstructed, and artificially produced cyanobacterial stromatolites resembles by their morphological properties those found in natural Earth habitats. Regarding the vital importance of distinguishing between biogenic and abiogenic signatures and between living and fossil microorganisms in analyzed samples, it is worthwhile to use some previously developed approaches based on electron microscopy examinations and analysis of elemental composition of biomorphs in situ and comparison with the analogous data obtained for laboratory microbial cultures and fossilized microorganisms. This communication will be focused on the analysis of our experience in working with ancient microorganisms and fossils and discussion of some issues that are crucial for development of the program for future finding of extraterrestrial life and its evidence.

Abyzov, S. S.↗

An Improved CRISPR Interference Tool to Engineer Rhodococcus opacus

Rhodococcus opacus is a non-model bacterium that is well suited for valorizing lignin. Despite recent advances in our systems-level understanding of its versatile metabolism, studies of its gene functions at a single gene level are still lagging. Elucidating gene functions in non-model organisms is challenging due to limited genetic engineering tools that are convenient to use. To address this issue, we developed a simple gene repression system based on CRISPR interference (CRISPRi). This gene repression system uses a T 7 RNA polymerase system to express a small guide RNA, demonstrating improved repression compared to the previously demonstrated CRISPRi system (i.e., the maximum repression efficiency improved from 58% to 85%). Additionally, our cloning strategy allows for building multiple CRISPRi plasmids in parallel without any PCR step, facilitating the engineering of this GC-rich organism. Using the improved CRISPRi system, we confirmed the annotated roles of four metabolic pathway genes, which had been identified by our previous transcriptomic analysis to be related to the consumption of benzoate, vanillate, catechol, and acetate. Furthermore, we showed our tool’s utility by demonstrating the inducible accumulation of muconate that is a precursor of adipic acid, an important monomer for nylon production. While the maximum muconate yield obtained using our tool was 30% of the yield obtained using gene knockout, our tool showed its inducibility and partial repressibility. In conclusion, our CRISPRi tool will be useful to facilitate functional studies of this non-model organism and engineer this promising microbial chassis for lignin valorization.

09 BIOMASS FUELS↗

Influence of physical and chemical hydrology on bioremediation of a U-contaminated aquifer informed by reactive transport modeling incorporating 238 U/ 235 U ratios

Microbially-catalyzed reductive immobilization of aqueous uranium (U) as a solid phase has been proposed as a U remediation technique. Both laboratory and field experiments have demonstrated that this reduction reaction alters the 238 U/ 235 U ratio, producing a 238 U-enriched U(IV) solid. In contrast, other major U reactive transport processes fractionate these isotopes much less. This suggests the potential to quantify the extent of bioreduction occurring in groundwater containing U using the 238 U/ 235 U ratio, which would substantially improve upon current practices largely relying on U concentration measurements alone. Current reactive transport models for uranium dynamics include only concentration measurements, which are strongly influenced by highly coupled reactive transformation and aqueous transport processes. The complex physical and chemical behavior of U potentially compromises such quantitative analysis of U storage and release. Here we report the first numerical reactive transport model which explicitly incorporates variations in the 238 U/ 235 U ratio of U and demonstrates improved interpretation of the principal chemical reactions and groundwater transport processes affecting the subsurface mobility and distribution of this widespread contaminant. Recent U bioreduction studies performed in a contaminated aquifer in Rifle, Colorado, USA applied Rayleigh distillation models to interpret U stable isotope fractionation observed as a result of acetate amendment. These simplified models were unable to resolve the spatiotemporal pattern of U isotope fractionation recorded in the aqueous solutes. Here, we employ the multi-component, isotope-enabled CrunchTope reactive transport software to interpret these measured U isotope ratios, and demonstrate accurate reproduction of observed trends in both geochemistry and 238 U/ 235 U ratios for two consecutive years of field experiments. Overall, our results indicate that accurately modeling both the U concentration and isotope ratio distributions greatly constrains the parameter space of the model. We find that the transport properties of U in the Rifle aquifer are governed by the presence of low-permeability regions, which the isotopes are uniquely sensitive to. When U reduction is spatially constrained by these low-permeability regions, the shift in the 238 U/ 235 U ratio becomes more muted. Accurate modeling of observed U isotope ratios thus provides a powerful means to better understand bioremediation, and the current study serves to advance the application of this novel method.

238U/235U↗

Paramyxovirus Infection Mimics In Vivo Cellular Dynamics in Three-Demensional Human Bronchio-Epithelial Tissue-Like Assemblies

Respiratory syncytial virus and parainfluenza virus cause severe respiratory disease, especially in infants, children and the elderly. An in vitro model that accurately mimics infection of the human respiratory epithelium (HRE) would facilitate vaccine development greatly. Monolayer cultures traditionally used to study these viruses do not accurately and precisely differentiate the replication efficiencies of wild type and attenuated viruses. Therefore, we engineered novel three-dimensional (3D) tissue-like assemblies (TLAs) of human broncho-epithelial (HBE) cells to produce a more physiologically relevant in vitro model of the HRE. TLAs resemble HRE structurally and by expression of differentiated epithelial cell markers. Most significantly, wild type viruses exhibited a clear growth advantage over attenuated strains in TLAs unlike monolayer cultures. In addition, the TLAs responded to virus infection by secreting pro-inflammatory mediators similar to the respiratory epithelia of infected children. These characteristics make the TLA model a valuable platform technology to develop and evaluate live, attenuated respiratory virus vaccine candidates for human use. Respiratory virus diseases, the most frequent and least preventable of all infectious diseases, range in severity from the common cold to severe bronchiolitis and pneumonia . Two paramyxoviruses, respiratory syncytial virus (RSV) and parainfluenza virus type 3 (PIV3), are responsible for a majority of the most severe respiratory diseases of infants and young children. RSV causes 70% of all bronchiolitis cases and is a major cause of morbidity and mortality worldwide, especially in infants. PIV3 causes 10-15% of bronchiolitis and pneumonia during infancy, second only to RSV, and 40% of croup in infants To date, licensed vaccines are not available to prevent these respiratory diseases. At present, traditional monkey kidney (Vero and LLC-MK2) and human (HEp-2) tissue culture cells and small animal models (mouse, cotton rat, guinea pig, ferret, and hamster) fail to accurately imitate viral replication and human disease states (8). Lacking an authentic model has impeded the development and evaluation of live, attenuated vaccine candidates. Development of a physiologically relevant in vitro tissue culture model that reproduces characteristics of the HRE, the primary target of RSV and PIV3, would aid in predicting clinical attenuation and safety of vaccine candidates. Successful tissue engineering of a 3D human intestinal model using novel NASA technology inspired the development of a tri-culture 3D model for the HRE. Sequential layering of primary mesenchymal cells (comprised of normal human fibroblasts and endothelial cells) followed by BEAS-2B epithelial cells derived from human bronchi and tracheae were recapitulated on Cultisphere and/or cytodex3 microcarriers in cylindrical vessels that rotate horizontally creating an organized epithelial structure. Horizontal rotation randomizes the gravity vector modeling aspects of microgravity. Mesenchymal and epithelial cells grown under these conditions reproduce the structural organization, multi-cellular complexity, and differentiation state of the HRE. The opportunity to study respiratory viruses in a nasal epithelium model is invaluable because the most promising respiratory virus vaccine candidates are live attenuated viruses for intranasal administration. Here we characterize the interactions of respiratory viruses and epithelial cells grown under modeled microgravity in comparison to gravity-ladened monolayers. 3D HBE TLAs and traditional monolayers (2D) are infected at 35 C, the upper temperature of the upper HRE, to simulate in vivo infection conditions. Growth kinetics of wild type (wt) RSV and PIV3 viruses were compared in 2D and 3D cells to that of strains attenuated in humans or rhesus macaques. This novel 3D HBE model also offers an opportunity to study whether the epithelial cell function, especially in host defenses recapitulated by mimicking the structural organization of the HRE. In vivo, airway epithelial cells play a significant and dynamic role in host defense by blocking paracellular permeability and modulating airway function through cellular interactions or tight junctions. As regulators of the innate immune response, epithelial cells constitutively express cytokines, chemokines, and colony stimulating factors including RANTES, IL-8, IL-6, GM-CSF, and G-CSF for proactive host defense. In response to viral infection, epithelial cells induce potent immuno-modulatory and pro-inflammatory cytokines that recruit phagocytic and inflammatory cells to clear the virus and enhance protection. Although disease pathogenesis is classically attributed to the cytopathic effects of the pathogen, severe disease states associated with RSV and PIV3 are attributed to the inflammatory response, especially in infants. RSV is a potent inducer of cytokines and pro-inflammatory mediators in epithelial cells in vivo. A differentiated human epithelial model independent of the complete functional immune system will help elucidate the role of epithelial cells in respiratory disease. We reported here, virus and host cell interactions in 3D HBE TLAs are similar to that in vivo. Because the epithelial cell organization of the TLAs impacts not only the expression of airway epithelial characteristics, but also cellular communication, the TLAs represent a more physiologically relevant model of the HRE than BEAS-2B or other non-tumour monolayer models of respiratory disease. As a result, wild type respiratory viruses have a clear growth advantage over attenuated viruses in TLAs unlike traditional monolayers. In addition, the TLAs respond to wild type virus infection by secreting pro-inflammatory mediators characteristic of infected HRE. TLAs expressing microbial defense mechanisms provide an excellent model to study the interactions of respiratory pathogens with their host and to identify the innate immunity mediators. Therefore, 3D HBE TLAs offer advantages for the study of respiratory viruses and the development of viral vaccine candidates.

Deatly, Anne M.↗

Methanogenesis and Acetogenesis in Hydrogenotrophy with Carbonate Minerals: Dependence on Mineral Surface Area, Biofilm Growth, and Microbial Community

The production, storage, and use of hydrogen are anticipated to grow substantially to achieve energy and climate goals. Consequently, microbial communities in many terrestrial and subsurface Earth environments could be exposed to elevated hydrogen concentrations. Hydrogen stimulates metabolic processes that reduce aqueous chemical species, such as bicarbonate or sulfate, that can exchange with solid mineral phases, but the controls on microbial hydrogenotrophy with mineral sources of electron acceptors are not fully understood. Herein, we applied laboratory experiments and biogeochemical modeling to study the response of a natural microbial community to an elevated partial pressure of hydrogen in the presence of carbonate minerals of varying composition, solubility, and size. Experimental incubations and simulation results showed that hydrogen consumption by microbial communities was initially dominated by sulfate reduction and, subsequently, transitioned to acetogenesis and methanogenesis. The rates of acetogenesis and methanogenesis were not correlated with the solubility of carbonate minerals. Instead, we observed strong linear correlations between the rates and surface area of carbonate minerals. Methane and acetate production slowed down in all incubations after about 2 weeks of incubation, although biogeochemical modeling predicted that the metabolic processes were not thermodynamically limited. Electron microscopy and infrared spectroscopy showed that biofilms with diverse microorganisms grew on the carbonates during this period. The methane δ13C value significantly increased, consistent with slower growth at elevated pH. This work highlights that microbial communities form biofilm on carbonate mineral surfaces as a response to hydrogen and that biofilm formation could pose a strong kinetic limitation to hydrogenotrophic metabolism utilizing carbonate minerals.

Acetobacterium↗

Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO2 Fluxes Upon Soil Warming

Abstract Understanding factors influencing carbon effluxes from soils to the atmosphere is important in a world experiencing climatic change. Two important uncertainties related to soil organic carbon (SOC) stock responses to a changing climate are (a) whether soil microbial communities acclimate or adapt to changes in soil temperature and (b) how to represent this process in SOC models. To further explore these issues, we included thermal adaptation of enzyme‐mediated processes in a mechanistic SOC model (ReSOM) using the macromolecular rate theory. Thermal adaptation is defined here to encompass all potential responses of soil microbes and microbial communities following a change in temperature. To assess the effects of thermal adaptation of enzyme‐mediated processes on simulated SOC losses, ReSOM was applied to data collected from a 13‐year soil warming experiment. Results show that a model omitting thermal adaptation of enzyme‐mediated processes substantially overestimates observed CO 2 effluxes during the initial years of soil warming. The bias against observed CO 2 effluxes was lower for models including thermal adaptation of enzyme‐mediated processes. In addition, for a simulated linear 3°C soil warming over 100 years, models including thermal adaptation of enzyme‐mediated processes simulated SOC losses of a factor of three smaller than models omitting this process. As thermal adaptation of microbial community characteristics is generally not included in models simulating feedback between the soil, biosphere and atmosphere, we encourage future studies to assess the potential impact that microbial adaptation has on soil carbon – climate feedback representations in models. Plain Language Summary A major uncertainty in projecting how much soil organic carbon (SOC) will be converted to CO 2 as a consequence of climate change is related to how soil microbes may adapt to increasing soil temperatures. While this “microbial thermal adaptation” has been shown to occur in short‐term lab incubation experiments, its effect on SOC cycling on a decadal timescale is not clear. To address this knowledge gap, a mechanistic SOC model was used to simulate data collected from a 13‐year soil warming experiment, to assess how microbial thermal adaptation affects predicted SOC losses upon soil warming. The model results show that incorporating microbial thermal adaptation into the model led to reduced CO 2 effluxes from the soil to the atmosphere compared to the common approach of omitting this mechanism. Our results imply that projected SOC losses for the decades to come may be reduced when this mechanism is incorporated in land models. We therefore advocate for more research on the mechanisms controlling microbial thermal adaptation, and how to implement this mechanism in SOC models. Key Points A crucial aspect of soil organic carbon (SOC) models is the representation of soil microbes Predicted soil CO 2 fluxes upon soil warming are reduced when accounting for microbial thermal adaptation On a centennial time scale, this thermal adaptation results in up to a factor of three lower predicted SOC loss

Van de Broek, Marijn↗

The Role of Retardation, Attachment and Detachment Processes during Microbial Coal-Bed Methane Production after Organic Amendment

Microbially enhanced coal-bed methane could allow for a more sustainable method of harvesting methane from un-mineable coaldbeds. The model presented here is based on a previously validated batch model; however, this model system is based on upflow reactor columns compared to previous experiments and now includes flow, transport and reactions of amendment as well as intermediate products. The model implements filtration and retardation effects, biofilm decay, and attachment and detachment processes of microbial cells due to shear stress. The model provides additional insights into processes that cannot be easily observed in experiments. This study improves the understanding of complex and strongly interacting processes involved in microbially enhanced coal-bed methane production and provides a powerful tool able to model the entire process of enhancing methane production and transport during microbial stimulation.

54 ENVIRONMENTAL SCIENCES↗

Genomic signatures in Variovorax enabling colonization of the Populus endosphere

Microbial colonization of plant roots involves strong selective pressures that shape the structure and function of root-associated communities. In particular, the endosphere represents a highly selective environment requiring host entry and in planta persistence. However, strain-specific microbial traits that enable endosphere colonization remain poorly understood. Here, we use a defined, genome-resolved community of 28 Variovorax strains isolated from the roots of Populus deltoides and Populus trichocarpa (poplar trees) to determine which strains partition between rhizosphere and endosphere compartments and to identify the genomic traits associated with endosphere specialization. By combining strain-resolved metagenomic profiling, comparative genomics, and functional assays, we demonstrate that dominant endosphere colonizers are enriched in genes related to nutrient metabolism, redox balance, transcriptional regulation, and a conserved L-fucose utilization pathway experimentally shown to enhance root colonization. Not all strains succeed through the same strategy. Community-wide functional profiling revealed a distinct and reduced set of traits in the endosphere, including orthogroups associated with low-abundance strains that were overlooked in strain-level analyses. These findings reveal that multiple ecological strategies, such as metabolic competition, regulatory adaptation, and niche specialization, can support endosphere colonization. Our results advance the understanding of how bacterial colonization traits are distributed and deployed within a plant microbiome and suggest that host filtering selects for distinct, and sometimes complementary, microbial strategies. This work supports a shift toward mechanistic, genome-resolved models of microbiome assembly and offers a framework for linking microbial function to host colonization success.

comparative genomics↗

Increased microbial growth, biomass, and turnover drive soil organic carbon accumulation at higher plant diversity

Species-rich plant communities have been shown to be more productive and to ­exhibit increased long-term soil organic carbon (SOC) storage. Soil microorganisms are central to the conversion of plant organic matter into SOC, yet the relationship between plant diversity, soil microbial growth, turnover as well as carbon use efficiency (CUE) and SOC accumulation is unknown. As heterotrophic soil microbes are primarily carbon limited, it is important to understand how they respond to increased plant-derived carbon inputs at higher plant species richness (PSR). We used the long-term grassland biodiversity experiment in Jena, Germany, to examine how microbial physiology responds to changes in plant diversity and how this affects SOC content. The Jena Experiment considers different numbers of species (1–60), functional groups (1–4) as well as functional identity (small herbs, tall herbs, grasses, and legumes). We found that PSR accelerated microbial growth and turnover and increased microbial biomass and necromass. PSR also accelerated microbial respiration, but this effect was less strong than for microbial growth. In contrast, PSR did not affect microbial CUE or biomass-specific respiration. Structural equation models revealed that PSR had direct positive effects on root biomass, and thereby on microbial growth and microbial biomass carbon. Finally, PSR increased SOC content via its positive influence on microbial biomass carbon. We suggest that PSR favors faster rates of microbial growth and turnover, likely due to greater plant productivity, resulting in higher amounts of microbial biomass and necromass that translate into the observed increase in SOC. We thus identify the microbial mechanism linking species-rich plant communities to a carbon cycle process of importance to Earth's climate system.

59 BASIC BIOLOGICAL SCIENCES↗

Producing multiple chemicals through biological upcycling of waste poly(ethylene terephthalate)

Poly(ethylene terephthalate) (PET) waste is of low degradability in nature, and its mismanagement threatens numerous ecosystems. To combat the accumulation of waste PET in the biosphere, PET bio-upcycling, which integrates chemical pretreatment to produce PET-derived monomers with their microbial conversion into value-added products, has shown promise. The recently discovered Rhodococcus jostii strain PET (RPET) can metabolically degrade terephthalic acid (TPA) and ethylene glycol (EG) as sole carbon sources, and it has been developed into a microbial chassis for PET upcycling. However, the scarcity of synthetic biology tools, specifically designed for the non-model microbe RPET, limits the development of a microbial cell factory for expanding the repertoire of bioproducts from post-consumer PET. Herein, we describe the development of potent genetic tools for RPET, including (1) two inducible and titratable expression systems for tunable gene expression and (2) Serine Integrase-based Recombinational Tools (SIRT) for genome editing. Using these tools, we systematically engineer the RPET strain to ultimately establish microbial supply chains for producing multiple chemicals, including lycopene, lipids, and succinate, from post-consumer PET waste bottles, achieving the highest titer of lycopene ever reported thus far in RPET (i.e., 22.6 mg/L of lycopene, approximately 10,000-fold higher than that of the wild-type strain). Furthermore, this work highlights the great potential of plastic upcycling as a generalizable means of sustainable production of diverse chemicals.

36 MATERIALS SCIENCE↗

Dynamic soil columns simulate Arctic redox biogeochemistry and carbon release during changes in water saturation

Thawing Arctic permafrost can induce hydrologic change and alter redox conditions, shifting the balance of soil organic matter (SOM) decomposition. There remains uncertainty about how soil saturation and redox transitions impact dissolved and gas phase carbon fluxes, and efforts to link hydrobiogeochemical processes to ecosystem-scale models are limited. This study evaluates SOM decomposition of Arctic tundra soils using column experiments, water chemistry measurements, microbial community analysis, and a PFLOTRAN reactive transport model. Soil columns from a thermokarst channel (TC) and an upland tundra (UC) were exposed to cycles of saturation and drainage, which controlled carbon emissions. During saturation, an outflow of dissolved organic carbon from the UC soil correlated with elevated reduced iron and decreased pH; during drainage, UC carbon dioxide fluxes were 70% higher than TC fluxes. Intermittent methane release was observed for TC, consistent with higher methanogen abundance. Slower drainage in the TC soil correlated with more subtle biogeochemical changes. PFLOTRAN simulations captured experimental trends in soil carbon fluxes, oxygen concentrations, and water contents. The model was then used to evaluate additional soil water drainage rates. This study emphasizes the importance of considering hydrologic change when evaluating and simulating SOM decomposition in dynamic Arctic tundra environments.

54 ENVIRONMENTAL SCIENCES↗

Engineering Methanogenic Microbiomes to Redirect Flux to Biomass

In this study, we present a method for acquiring and characterizing novel microbial consortia that regulates methanogens and methanotrophs through selective cultivation and metagenomic analysis of indigenous microorganisms in the environment. In addition, we present the work performed as part of this project to model the pathways that act as limiting factors in microbial methane metabolism based on a carbon cycle model. In this report, we describe the methods for selective cultivation of methane-metabolism-related microorganisms from environmental samples, the method for monitoring their methane consumption performance, and the method and results for verifying their functions using quantitative PCR and metagenomics techniques. The microbial consortia containing methanotrophs were obtained through selective cultivation and molecular biological verification, and their methane consumption performance was evaluated. In addition, the potential of the existence of bacteriophages interacting with methane metabolism-related microorganisms was identified through metagenomic sequencing.

09 BIOMASS FUELS↗

Direct evidence for the role of microbial community composition in the formation of soil organic matter composition and persistence

The largest terrestrial carbon sink on earth is soil carbon stocks. As the climate changes, the rate at which the Earth’s climate warms depends in part on the persistence of soil organic carbon. Microbial turnover forms the backbone of soil organic matter (SOM) formation and it has been recently proposed that SOM molecular complexity is a key driver of stability. Despite this, the links between microbial diversity, chemical complexity and biogeochemical nature of SOM remain missing. Here we tested the hypotheses that distinct microbial communities shape the composition of SOM, and microbial-derived SOM has distinct decomposition potential depending on its community of origin. We inoculated microbial communities of varying diversities into a model soil matrix amended with simple carbon (cellobiose) and measured the thermal stability of the resultant SOM. Using a Rock-Eval ® ramped thermal analysis, we found that microbial community composition drives the chemical fingerprint of soil carbon. While diversity was not a driver of SOM composition, bacteria-only communities lead to more thermally labile soil C pools than communities with bacteria and fungi. Our results provide direct evidence for a link between microbial community structure, SOM composition, and thermal stability. This evidence demonstrates the relevance of soil microorganisms in building persistent SOM stocks.

Domeignoz-Horta, Luiz A. (ORCID:0000000346186253)↗

Agent-based modeling of microbes in space

Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal microgravity; however, much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER results agree with experimental data indicating that indirect effects of radiation (reactive oxygen species generation, metabolic impairment) have a greater impact on microorganisms than direct effects (DNA damage).

Jessica A Lee↗

Agent-Based Modeling of Microbes in Space

Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal gravity, and much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER growth curves recapitulate experimental results, and allow comparison between direct effects (DNA damage) and indirect effects (reactive oxygen species generation, metabolic impairment) of radiation.

microbiology↗