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NASA NTRS2024

Spaceflight-Induced Changes in Microbial Virulence and the Impact to the Host Immune Response

Many microbial pathogen shave repeatedly exhibited unexpected responses relevant to infectious disease when grown in microgravity and microgravity analogue environments, including changes in final cell concentration, biofilm production, stress resistance, antibiotic sensitivity, gene expression, host-pathogen interactions, and virulence. Notably, the classic foodborne pathogen Salmonella enterica serovar Typhimurium displayed increased virulence in animals when cultured in either the spaceflight analogue or true spaceflight environment. Recently, Serratia marcescens also was shown to increase virulence when cultured in the spaceflight environment. In parallel, astronaut studies have characterized a persistent spaceflight-induced dysregulation of the human immune system at multiple levels, which suggests an increased risk of infectious diseases. Moreover, astronauts have some degree of clinical infectious disease incidence. However, the contribution of the microgravity environment on host-pathogen interactions and potential for clinical disease remains understudied and poorly characterized. The goal of this study is to gain insight into the breadth of other medically significant microbial pathogens that may exhibit altered virulence and pathogenesis-related responses when cultured in space flight analogue conditions. Specifically, we are characterizing the effect of spaceflight analogue culture (Low Shear Modeled Microgravity/LSMMG) on microbial pathogenesis-related stress responses, in vitro host-pathogen interactions, gene expression, and virulence potential in animals using five important model bacterial pathogens, Salmonella enterica Enteritidis, Pseudomonas aeruginosa, Burkholderia cepacia, Streptococcus pneumoniae, and enterohemorrhagic Escherichia coli. Herein, we present data from one of these pathogens, the foodborne bacterium, S. enterica Enteritidis, which is closely related to S. enterica Typhimurium. Phenotypes evaluated included growth profiles, environmental stress responses(acid, oxidative, bile, and thermal stresses),and in vitro colonization of3-D biomimetic cultures of human intestinal tissue containing immune cells. Transcriptomic profiling and virulence studies are ongoing. We show that S. Enteritidis exhibited key alterations in pathogenic responses to LSMMG culture that suggest increased infection risk, including several responses which were different from those observed in the closely related pathovar S. Typhimurium. This information will provide critical mechanistic insight into the potential impact of microgravity on alterations in microbial virulence and associated infectious disease risk to crew health during spaceflight missions.

C.M. Ott↗

DOE OSTI2026

Beyond microbial abundance: metadata integration enhances disease prediction in human microbiome studies

Multiple studies have highlighted the interaction of the human microbiome with physiological systems such as the gut, immune, liver, and skin, via key axes. Advances in sequencing technologies and high-performance computing have enabled the analysis of large-scale metagenomic data, facilitating the use of machine learning to predict disease likelihood from microbiome profiles. However, challenges such as compositionality, high dimensionality, sparsity, and limited sample sizes have hindered the development of actionable models. One strategy to improve these models is by incorporating key metadata from both the human host and sample collection/processing protocols. This remains challenging due to sparsity and inconsistency in metadata annotation and availability. In this paper, we introduce a machine learning-based pipeline for predicting human disease states by integrating host and protocol metadata with microbiome abundance profiles from 68 different studies, processed through a consistent pipeline. Our findings indicate that metadata can enhance machine learning predictions, particularly at higher taxonomic ranks like Kingdom and Phylum, though this effect diminishes at lower ranks. Our study leverages a large collection of microbiome datasets comprising 11,208 samples, therefore enhancing the robustness and statistical confidence of our findings. This work is a critical step toward utilizing microbiome and metadata for predicting diseases such as gastrointestinal infections, diabetes, cancer, and neurological disorders.

Mathematics and Computing↗

DOE OSTI2023

CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics

Abstract. Microbial activity and chemical reactions in porous media depend on the local conditions at the pore scale and can involve complex feedback with fluid flow and mass transport. We present a modeling framework that quantitatively accounts for the interactions between the bio(geo)chemical and physical processes and that can integrate genome-scale microbial metabolic information into a dynamically changing, spatially explicit representation of environmental conditions. The model couples a lattice Boltzmann implementation of Navier–Stokes (flow) and advection–diffusion-reaction (mass conservation) equations. Reaction formulations can include both kinetic rate expressions and flux balance analysis, thereby integrating reactive transport modeling and systems biology. We also show that the use of surrogate models such as neural network representations of in silico cell models can speed up computations significantly, facilitating applications to complex environmental systems. Parallelization enables simulations that resolve heterogeneity at multiple scales, and a cellular automaton module provides additional capabilities to simulate biofilm dynamics. The code thus constitutes a platform suitable for a range of environmental, engineering and – potentially – medical applications, in particular ones that involve the simulation of microbial dynamics.

58 GEOSCIENCES↗

DOE OSTI2025

Opposite Response of DNA and RNA Viruses to Soil Warming and Implications for Microbial Functions

Soil viruses control the dynamics and metabolism of their hosts, strongly modifying carbon and nutrient cycling as well as soil biochemistry. Warming specifically affects viruses and their hosts, but the consequences of climate warming on the virus–host interactions, and for soil functions, remain unknown. Here, we investigated the viral communities and the virus–host interactions under warming in situ based on a forest soil column translocation experiment. The abundance of the Petitvirales (DNA viruses) decreased by 25%, but that of the Durnavirales and Martellivirales (RNA viruses) strongly increased. The DNA viral lysogenic signals and RNA viral lytic proteins increased in soil, indicating the opposite lifestyles of DNA and RNA viruses. Correspondingly, the DNA abundance of viral hosts increased, whereas RNA viral hosts remained stable. The high DNA viruses/host ratios reflect very intensive interactions between the virus and host, leading to the drop in the host functions (such as carbon metabolism processes and nitrogen and phosphorus cycles) up to 43%. In contrast, the functions of the hosts for RNA viruses increased by up to 48%. The fundamental difference in behaviour of DNA and RNA viruses is that the former use mainly lysogenic, whereas the latter lytic, lifestyles and thus control the responses of host communities to warming. Conclusively, the opposite response of DNA and RNA viruses to warming in abundance, lifestyle, and interactions with hosts leads to divergent changes in nutrient fluxes in soil. These new perspectives on viral regulations of microbial communities and their function under soil warming reveal the undeniable role of viruses in microbial ecology.

forest soil↗

DOE OSTI2024

Microbial Community Changes across Time and Space in a Constructed Wetland

Constructed wetlands are artificial ecosystems designed to replicate natural wetland processes. Microbial communities play a pivotal role in cycling essential elements, particularly sulfur, which is crucial for trace metal fixation and remobilization in these ecosystems. By their response to their environment, microbial communities act as biological indicators of the wetland performance. To address knowledge gaps pertinent to the changes in trace metal bioavailability in relation to microbial activities in the H-02 constructed wetland, we performed this study to investigate temporal and spatial variations in microbial communities by using molecular biology tools. Quantitative polymerase chain reaction and next generation sequencing techniques were employed to analyze archaeal and bacterial groups associated with sulfur and methane cycling. Alpha diversity indices were used to assess species richness, evenness, and dominance. Results indicated high gene abundance of Desulfuromonas (5.37 × 10 6 g.cell –1 ), methane oxidizing bacteria (6.92 × 10 6 g.cell –1 ), and methanogenic microorganisms (3.02 × 10 5 g.cell –1 ) during cool months. Warm months were marked by sulfate reducing bacteria dominance (3.31 × 10 6 g.cell –1 ), potentially due to competitive interactions and environmental conditions, higher temperatures, and lower redox potential. Spatial variability among microbial groups was insignificant, but trends in gene abundance indicated complex factors influencing these groups. Next generation sequencing data demonstrated Firmicutes as the most abundant phylum with over 50% regardless of the season or sampling location. Cool months exhibited higher alpha diversity than warm months. Overall, this study showed that seasonal changes significantly impacted the microbial communities in the H-02 constructed wetland that are associated with the sulfur cycle and eventually trace metal biogeochemistry, revealing two distinct mechanisms of the sulfur cycle between the two main seasons, whereas spatial variability effects were not conclusive.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Holo-omics for deciphering plant-microbiome interactions

Host-microbiome interactions are recognized for their importance to host health. An improved understanding of the molecular underpinnings of host-microbiome relationships will advance our capacity to accurately predict host fitness and manipulate interaction outcomes. Within the plant microbiome research field, unlocking the functional relationships between plants and their microbial partners is the next step to effectively using the microbiome to improve plant fitness. We propose that strategies that pair host and microbial datasets—referred to here as holo-omics—provide a powerful approach for hypothesis development and advancement in this area. We discuss several experimental design considerations and present a case study to highlight the potential for holo-omics to generate a more holistic perspective of molecular networks within the plant microbiome system. In addition, we discuss the biggest challenges for conducting holo-omics studies; specifically, the lack of vetted analytical frameworks, publicly available tools, and required technical expertise to process and integrate heterogeneous data. Finally, we conclude with a perspective on appropriate use-cases for holo-omics studies, the need for downstream validation, and new experimental techniques that hold promise for the plant microbiome research field. We argue that utilizing a holo-omics approach to characterize host-microbiome interactions can provide important opportunities for broadening system-level understandings and significantly inform microbial approaches to improving host health and fitness.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Genomic fingerprints of the world’s soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2010

Tissuelike 3D Assemblies of Human Broncho-Epithelial Cells

Three-dimensional (3D) tissuelike assemblies (TLAs) of human broncho-epithelial (HBE) cells have been developed for use in in vitro research on infection of humans by respiratory viruses. The 2D monolayer HBE cell cultures heretofore used in such research lack the complex cell structures and interactions characteristic of in vivo tissues and, consequently, do not adequately emulate the infection dynamics of in-vivo microbial adhesion and invasion. In contrast, the 3D HBE TLAs are characterized by more-realistic reproductions of the geometrical and functional complexity, differentiation of cells, cell-to-cell interactions, and cell-to-matrix interactions characteristic of human respiratory epithelia. Hence, the 3D HBE TLAs are expected to make it possible to perform at least some of the research in vitro under more-realistic conditions, without need to infect human subjects. The TLAs are grown on collagen-coated cyclodextran microbeads under controlled conditions in a nutrient liquid in the simulated microgravitational environment of a bioreactor of the rotating- wall-vessel type. Primary human mesenchymal bronchial-tracheal cells are used as a foundation matrix, while adult human bronchial epithelial immortalized cells are used as the overlying component. The beads become coated with cells, and cells on adjacent beads coalesce into 3D masses. The resulting TLAs have been found to share significant characteristics with in vivo human respiratory epithelia including polarization, tight junctions, desmosomes, and microvilli. The differentiation of the cells in these TLAs into tissues functionally similar to in vivo tissues is confirmed by the presence of compounds, including villin, keratins, and specific lung epithelium marker compounds, and by the production of tissue mucin. In a series of initial infection tests, TLA cultures were inoculated with human respiratory syncytial viruses and parainfluenza type 3 viruses. Infection was confirmed by photomicrographs that showed signs of damage by viruses and virus titers (see figure) that indicated large increases in the populations of viruses during the days following inoculation.

Goodwin, Thomas J.↗

NASA NTRSDate not supplied

Responses of Microbes to Modeled Space Radiation

The built environment of spaceships is host to a microbial community that affects crew and craft alike. While the static composition of this community has been characterized and its temporal dynamics examined, the mechanisms controlling its make-up and evolutionary trajectory are not understood. Systematic analyses of microbial diversity show consistent patterns in community composition and function. Understanding these patterns' ecological origins remains a significant challenge, as it requires connecting processes at varying temporal and spatial scales. However, it is clear that the state and trajectories of microbial communities are in-part determined by their physical environment. In this regard, the spaceflight environment includes numerous interacting factors that differentiate it from Earth environments, including an altered atmospheric composition, reduced gravity (and thus altered fluid dynamics), and increased ionizing radiation. These factors impart selective pressures on microbial communities that affect their evolutionary trajectories and thus the risks and benefits these communities represent to crew and craft. The radiation environment of space leads to chronic exposure to low doses and is difficult to mimic on Earth. Thus, little is known about how microbial communities in spacecraft will respond and evolve. Therefore, given the limitations of existing studies, we aim to empirically determine how exposure to low doses of ionizing radiation for thousands of cell divisions affects rates of mutation accumulation in bacteria and the trajectory of their evolution. In this way, we will provide a critical set of data for designing safe and robust space missions. Here we discuss our progress towards this aim, including the construction of exposure facilities, our culturing and analysis approach, and preliminary data.

radiation↗

DOE OSTI2025

Community Dynamics Drive Calcium Carbonate Production in an Enriched Consortium of Soil Microbes

Recently, there has been a focus on using soil microbes as a means to store carbon in the soil in the form of calcium carbonate, outcomes of which include soil stabilization and biocementation. The molecular processes involved in microbially induced calcium carbonate formation are known, but there is still a significant knowledge gap regarding how community interactions, emergent processes that are distinct from the roles of individual members, may drive the formation of carbonate. To answer these questions, we describe the development and application of a consortium of soil microbes consisting of one species each of the Rhodococcus , Microbacterium , and Curtobacterium genera and two species from the Bacillus genus. We term these five species cultivated together carbon storing consortium A (CSC-A). Growth assays show that only a subset of CSC-A members produces CaCO 3 with Rhodococcus producing the most CaCO 3 but the complete CSC-A produces significantly higher amounts of CaCO 3 compared to the sum total carbonate produced by all member species. The development of CSC-A shows that CaCO 3 production may be as much a community process as it is the contribution of individual species, requiring us to move beyond single species analysis to fully understand carbonate formation by microbial communities in nature. CSC-A will allow the scientific community to ask and answer key questions about the molecular interactions surrounding inorganic carbon formation in soil, an important knowledge gap that must be filled if we wish to stabilize soils and harness microbial processes for materials production.

calcium carbonate↗

DOE OSTI2022

Plant root exudates and rhizosphere bacterial communities shift with neighbor context

A plant's neighborhood context can alter its interactions with other organisms, but little is known about how these dynamics occur belowground, especially with soil microbes. Microbial communities in rhizosphere soil are influenced by many factors, including abiotic conditions and root-derived signals. In particular, root exudates have strong effects on rhizosphere assembly, respond to changes in abiotic conditions, and help plants interact with neighbors. Therefore, we predicted that root exudates likely play a central role in neighbor-induced shifts in rhizosphere communities. We conducted a greenhouse experiment to test this and determine how the rhizosphere bacterial community of a focal plant, Panicum virgatum, changed when beside different neighbors, and whether these shifts were mediated by neighbor-induced changes in root exudation. We found that neighbor altered both focal plant exudates and rhizosphere community, and that changes were largest when the focal plant was beside the most competitive neighbor, Rudbeckia hirta, which reduced both focal plant growth and nitrogen uptake. Several factors contributed to neighbor impacts on rhizosphere assembly, including neighbor-induced changes in root exudates during nitrogen-limitation and microbial spillover from roots of larger neighbors. Using an additional soil incubation, we also found that these changes in exudates can have even greater effects on soil nutrients than on microbial assembly. Overall, we show that neighbors influence one another's microbiomes, and highlight neighbor-induced changes in root exudates as one mechanism through which this may occur. Furthermore, this work suggests that rhizosphere assembly may differ in mixed-species communities and thus emphasizes a need for microbiome studies that consider neighborhood context.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

A Computational Workflow of Elucidating Viral Impact on Mediating Microbial Response to In-situ Experimental Warming: Bridging microbial modeling to carbon and mineral modeling

Viruses are abundant in soils and shape microbial communities in ways that can potentially influence ecosystem processes, yet their contributions to carbon cycling and mineral transformations remain poorly understood. Here we present a multi-phase framework that links virus-host interactions to soil biogeochemistry by combining ecological simulations, genome- and community-scale metabolic modeling, and statistical and machine-learning analyses. We first calibrated microbial abundance profiles under explicit infection scenarios to capture how viral pressure alters community structure, then explored alternative interaction strategies, including kill-the-winner, piggyback-the-winner, and mixed lytic-lysogenic modes, through forward simulations. These ecological shifts were translated into metabolic consequences using exchange fluxes summarized into biologically meaningful categories, while integrated statistical and machine-learning screens elevated subtle but consistent signals. Application of this framework revealed that viral infections shift the balance between organic and inorganic fluxes, redirecting metabolism from diffuse organic transformations toward inorganic pools such as protons and CO 2 , directly linking viral regulation to respiration and soil carbon balance. The roll-up analysis also isolated perturbations in critical mineral ions, including magnesium, manganese, zinc, and copper, which serve as essential enzymatic cofactors. In piggyback-the-winner scenarios, uptake of these ions was strongly suppressed. Contrasting viral strategies produced distinct community structures and metabolic outcomes, from broad suppression under kill-the-winner dynamics to dramatic redistributions under high-lytic and high-gain lysogenic regimes that collapsed vulnerable microbial populations while promoting opportunists. Together, these results provide a tractable path to trace viral perturbations from host abundance shifts to metabolic flux adjustments and ecosystem-scale processes, offering a practical way to include viruses in earth system models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization

Abstract Background Microbiome studies have uncovered associations between microbes and human, animal, and plant health outcomes. This has led to an interest in developing microbial interventions for treatment of disease and optimization of crop yields which requires identification of microbiome features that impact the outcome in the population of interest. That task is challenging because of the high dimensionality of microbiome data and the confounding that results from the complex and dynamic interactions among host, environment, and microbiome. In the presence of such confounding, variable selection and estimation procedures may have unsatisfactory performance in identifying microbial features with an effect on the outcome. Results In this manuscript, we aim to estimate population-level effects of individual microbiome features while controlling for confounding by a categorical variable. Due to the high dimensionality and confounding-induced correlation between features, we propose feature screening, selection, and estimation conditional on each stratum of the confounder followed by a standardization approach to estimation of population-level effects of individual features. Comprehensive simulation studies demonstrate the advantages of our approach in recovering relevant features. Utilizing a potential-outcomes framework, we outline assumptions required to ascribe causal, rather than associational, interpretations to the identified microbiome effects. We conducted an agricultural study of the rhizosphere microbiome of sorghum in which nitrogen fertilizer application is a confounding variable. In this study, the proposed approach identified microbial taxa that are consistent with biological understanding of potential plant-microbe interactions. Conclusions Standardization enables more accurate identification of individual microbiome features with an effect on the outcome of interest compared to other variable selection and estimation procedures when there is confounding by a categorical variable.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Microbial diversity drives carbon use efficiency in a model soil

Abstract Empirical evidence for the response of soil carbon cycling to the combined effects of warming, drought and diversity loss is scarce. Microbial carbon use efficiency (CUE) plays a central role in regulating the flow of carbon through soil, yet how biotic and abiotic factors interact to drive it remains unclear. Here, we combine distinct community inocula (a biotic factor) with different temperature and moisture conditions (abiotic factors) to manipulate microbial diversity and community structure within a model soil. While community composition and diversity are the strongest predictors of CUE, abiotic factors modulated the relationship between diversity and CUE, with CUE being positively correlated with bacterial diversity only under high moisture. Altogether these results indicate that the diversity × ecosystem-function relationship can be impaired under non-favorable conditions in soils, and that to understand changes in soil C cycling we need to account for the multiple facets of global changes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Hot springs viruses at Yellowstone National Park have ancient origins and are adapted to thermophilic hosts

Geothermal springs house unicellular red algae in the class Cyanidiophyceae that dominate the microbial biomass at these sites. Little is known about host-virus interactions in these environments. We analyzed the virus community associated with red algal mats in three neighboring habitats (creek, endolithic, soil) at Lemonade Creek, Yellowstone National Park (YNP), USA. We find that despite proximity, each habitat houses a unique collection of viruses, with the giant viruses, Megaviricetes, dominant in all three. The early branching phylogenetic position of genes encoded on metagenome assembled virus genomes (vMAGs) suggests that the YNP lineages are of ancient origin and not due to multiple invasions from mesophilic habitats. The existence of genomic footprints of adaptation to thermophily in the vMAGs is consistent with this idea. The Cyanidiophyceae at geothermal sites originated ca. 1.5 Bya and are therefore relevant to understanding biotic interactions on the early Earth.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Fungi and viruses as important players in microbial mats

ABSTRACT Microbial mats are compacted, surface-associated microbial ecosystems reminiscent of the first living communities on early Earth. While often considered predominantly prokaryotic, recent findings show that both fungi and viruses are ubiquitous in microbial mats, albeit their functional roles remain unknown. Fungal research has mostly focused on terrestrial and freshwater ecosystems where fungi are known as important recyclers of organic matter, whereas viruses are exceptionally abundant and important in aquatic ecosystems. Here, viruses have shown to affect organic matter cycling and the diversity of microbial communities by facilitating horizontal gene transfer and cell lysis. We hypothesise fungi and viruses to have similar roles in microbial mats. Based on the analysis of previous research in terrestrial and aquatic ecosystems, we outline novel hypotheses proposing strong impacts of fungi and viruses on element cycling, food web structure and function in microbial mats, and outline experimental approaches for studies needed to understand these interactions.

Carreira, Cátia↗

DOE OSTI2024

How microscopic epistasis and clonal interference shape the fitness trajectory in a spin glass model of microbial long-term evolution

The adaptive dynamics of evolving microbial populations takes place on a complex fitness landscape generated by epistatic interactions. The population generically consists of multiple competing strains, a phenomenon known as clonal interference. Microscopic epistasis and clonal interference are central aspects of evolution in microbes, but their combined effects on the functional form of the population’s mean fitness are poorly understood. Here, we develop a computational method that resolves the full microscopic complexity of a simulated evolving population subject to a standard serial dilution protocol. Through extensive numerical experimentation, we find that stronger microscopic epistasis gives rise to fitness trajectories with slower growth independent of the number of competing strains, which we quantify with power-law fits and understand mechanistically via a random walk model that neglects dynamical correlations between genes. We show that increasing the level of clonal interference leads to fitness trajectories with faster growth (in functional form) without microscopic epistasis, but leaves the rate of growth invariant when epistasis is sufficiently strong, indicating that the role of clonal interference depends intimately on the underlying fitness landscape. The simulation package for this work may be found at https://github.com/nmboffi/spin_glass_evodyn .

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

How microscopic epistasis and clonal interference shape the fitness trajectory in a spin glass model of microbial long-term evolution

59 BASIC BIOLOGICAL SCIENCES↗