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At least 541 records · Page 30

A genome-scale metabolic model for the denitrifying bacterium Thauera sp. MZ1T accurately predicts degradation of pollutants and production of polymers

The denitrifying bacterium Thauera sp . MZ1T, a common member of microbial communities in wastewater treatment facilities, can produce different compounds from a range of carbon (C) and nitrogen (N) sources under aerobic and anaerobic conditions. In these different conditions, Thauera modifies its metabolism to produce different compounds that influence the microbial community. In particular, Thauera sp . MZ1T produces different exopolysaccharides with floc-forming properties, impacting the physical disposition of wastewater consortia and the efficiency of nutrient assimilation by the microbial community. Under N-limiting conditions, Thauera sp . MZ1T decreases its growth rate and accelerates the accumulation of polyhydroxyalkanoate-related (PHA) compounds including polyhydroxybutyrate (PHB), which plays a fundamental role as C and energy storage in this β-proteobacterium. However, the metabolic mechanisms employed by Thauera sp . MZ1T to assimilate and catabolize many of the different C and N sources under aerobic and anaerobic conditions remain unknown. Systems biology approaches such as genome-scale metabolic modeling have been successfully used to unveil complex metabolic mechanisms for various microorganisms. Here, we developed a comprehensive metabolic model (M-model) for Thauera sp . MZ1T ( i Thauera861), consisting of 1,744 metabolites, 2,384 reactions, and 861 genes. We validated the model experimentally using over 70 different C and N sources under both aerobic and anaerobic conditions. i Thauera861 achieved a prediction accuracy of 95% for growth on various C and N sources and close to 85% for assimilation of aromatic compounds under denitrifying conditions. The M-model was subsequently deployed to determine the effects of substrates, oxygen presence, and the C:N ratio on the production of PHB and exopolysaccharides (EPS), showing the highest polymer yields are achieved with nucleotides and amino acids under aerobic conditions. This comprehensive M-model will help reveal the metabolic processes by which this ubiquitous species influences communities in wastewater treatment systems and natural environments.

Tec-Campos, Diego (ORCID:0000000188194150)↗

Impact of dilution on microbial community structure and functional potential: comparison of numerical simulations and batch culture experiments

A series of microcosm experiments was performed using serial dilutions of a sewage microbial community to inoculate a set of batch cultures in sterile sewage. After inoculation, the dilution-defined communities were allowed to regrow for several days and a number of community attributes were measured in the regrown assemblages. Based upon a set of numerical simulations, community structure was expected to differ along the dilution gradient; the greatest differences in structure were anticipated between the undiluted-low-dilution communities and the communities regrown from the very dilute (more than 10(-4)) inocula. Furthermore, some differences were expected among the lower-dilution treatments (e.g., between undiluted and 10(-1)) depending upon the evenness of the original community. In general, each of the procedures used to examine the experimental community structures separated the communities into at least two, often three, distinct groups. The groupings were consistent with the simulated dilution of a mixture of organisms with a very uneven distribution. Significant differences in community structure were detected with genetic (amplified fragment length polymorphism and terminal restriction fragment length polymorphism), physiological (community level physiological profiling), and culture-based (colony morphology on R2A agar) measurements. Along with differences in community structure, differences in community size (acridine orange direct counting), composition (ratio of sewage medium counts to R2A counts, monitoring of each colony morphology across the treatments), and metabolic redundancy (i.e., generalist versus specialist) were also observed, suggesting that the differences in structure and diversity of communities maintained in the same environment can be manifested as differences in community organization and function.

Non-NASA Center↗

Searching for fat tails in CRISPR-Cas systems: Data analysis and mathematical modeling

Understanding CRISPR-Cas systems—the adaptive defence mechanism that about half of bacterial species and most of archaea use to neutralise viral attacks—is important for explaining the biodiversity observed in the microbial world as well as for editing animal and plant genomes effectively. The CRISPR-Cas system learns from previous viral infections and integrates small pieces from phage genomes called spacers into the microbial genome. The resulting library of spacers collected in CRISPR arrays is then compared with the DNA of potential invaders. One of the most intriguing and least well understood questions about CRISPR-Cas systems is the distribution of spacers across the microbial population. Here, using empirical data, we show that the global distribution of spacer numbers in CRISPR arrays across multiple biomes worldwide typically exhibits scale-invariant power law behaviour, and the standard deviation is greater than the sample mean. We develop a mathematical model of spacer loss and acquisition dynamics which fits observed data from almost four thousand metagenomes well. In analogy to the classical ‘rich-get-richer’ mechanism of power law emergence, the rate of spacer acquisition is proportional to the CRISPR array size, which allows a small proportion of CRISPRs within the population to possess a significant number of spacers. Our study provides an alternative explanation for the rarity of all-resistant super microbes in nature and why proliferation of phages can be highly successful despite the effectiveness of CRISPR-Cas systems.

59 BASIC BIOLOGICAL SCIENCES↗

High-Throughput Microbial Community Analyses to Establish a Natural Fungal and Bacterial Consortium from Sewage Sludge Enriched with Three Pharmaceutical Compounds

Emerging and unregulated contaminants end up in soils via stabilized/composted sewage sludges, paired with possible risks associated with the development of microbial resistance to antimicrobial agents or an imbalance in the microbial communities. An enrichment experiment was performed, fortifying the sewage sludge with carbamazepine, ketoprofen and diclofenac as model compounds, with the aim to obtain strains with the capability to transform these pollutants. Culturable microorganisms were obtained at the end of the experiment. Among fungi, Cladosporium cladosporioides, Alternaria alternata and Penicillium raistrickii showed remarkable degradation rates. Population shifts in bacterial and fungal communities were also studied during the selective pressure using Illumina MiSeq. These analyses showed a predominance of Ascomycota (Dothideomycetes and Aspergillaceae) and Actinobacteria and Proteobacteria, suggesting the possibility of selecting native microorganisms to carry out bioremediation processes using tailored techniques.

59 BASIC BIOLOGICAL SCIENCES↗

The Transformation and Export of Organic Carbon Across an Arctic River-Delta-Ocean Continuum

The Arctic Ocean is surrounded by land that feeds highly seasonal rivers with water enriched in high concentrations of dissolved and particulate organic carbon (DOC and POC). Explicit estimates of the flux of organic carbon across the land-ocean interface are difficult to quantify and many interdependent processes makes source attribution difficult. A high-resolution 3-D biogeochemical model was built for the lower Yukon River and coastal ocean to estimate biogeochemical cycling across the land-ocean continuum. The model solves for complex reactions related to organic carbon transformation, including mechanistic photodegradation and multi-reactivity microbial processing, DOC to POC flocculation, and phytoplankton dynamics. The baseline DOC and POC flux out of the delta from April to September 2019, was 977 and 536 Gg C (~80% of the annual total), but only 50% of the DOC and 25% of the POC exited the plume across the 10 m isobath. Microbial breakdown of DOC accounted for a net loss of 168 Gg C (17% of delta export) within the plume and photodegradation accounted for a net loss of 46.6 Gg C DOC (5% of delta export) in 2019. Flocculation decreased the total organic carbon flux by only 6.4 Gg C (~1%), while POC sinking accounted for 63.3 Gg C (10%) settling in the plume. The loss of chromophoric dissolved organic matter (CDOM) due to photodegradation increased the light available for phytoplankton growth throughout the coastal ocean, demonstrating the secondary effects that organic carbon reactions can have on biological processes and the net coastal carbon flux.

Land-Ocean Continuum↗

GROWdb US River Systems - Samples

GROW Overview We developed the Genome Resolved Open Watersheds database (GROWdb), which aims to increase genomic sampling and understanding of global river microbiomes. An emphasis of GROWdb is to create a publicly available and ever-expanding microbial genome database that is focused on rivers while being interoperable with databases from other ecosystems. GROWdb is based on a network-of-networks approach to move beyond a small collection of well-studied rivers, towards a spatially distributed, global network of systematic observations. GROWdb represents the first microbial, river-focused resource parsed at various scales from genes to MAGs to community level including expression and potential based measurements that will be of interest to microbiologists, ecologists, geochemists, hydrologists, and modelers. Dataset Acknowledgement GROWdb contains data from various research campaigns, please acknowledge the following data generators, as appropriate: WHONDRS derived genomes or samples - include this statement in your acknowledgements: “This study used data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) under the River Corridor Science Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL) that was generated at the U.S. Department of Energy (DOE) Joint Genome Institute User Facility. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under Contract No. DE-AC05-76RL01830. The SFA is supported by the U.S. DOE, Office of Biological and Environmental Research (BER), Environmental System Science (ESS) Program.” Total Samples loaded onto this Narrative: 178 Note: Not all GROW samples may be loaded into KBase Data Availability The data underlying GROWdb are accessible across various platforms to ensure all levels of data structure are widely available. First, all reads and MAGs are publicly hosted on National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. Second, all data related data presented here including MAG annotations, extended data tables, phylogenetic tree files, antibiotic resistance gene database files, and MAG abundance tables are available in Zenodo (link). Beyond the flat database files listed above, our aim for GROWdb was to maximize data use by making the data available in searchable and interactive platforms including the National Microbiome Data Collaborative (NMDC) data portal, the Department of Energy’s Systems Biology Knowledgebase (KBase), and a GROW specific user interface released here, GROWdb Explorer. Each platform provides different ways to interact with GROWdb: NMDC GROWdb formed a pilot project for the NMDC. Specifically, individual GROWdb datasets (metagenomes, metatranscriptomes, etc) are easily accessible and searchable through the NMDC data portal, where they are systematically connected to each other and to a rich suite of sample information and standard analysis results, following Findable, Accessible, Interoperable, and Reusable (FAIR) data practices. KBase GROWdb is publicly available within KBase, including samples (this Narrative), MAGs, and corresponding genome scale metabolic models. Access within KBase allows for immediate access and reuse of data, including comparison to private data using KBase’s 500+ analysis tools. Other linked narratives in KBase: GROW Metagenome Assembled Genomes (MAGs) GROW Metabolic Models GROWdb Explorer GROWdb data is also explorable through a graphical user interface built through the Colorado State University Geospatial Centroid (https://geocentroid.shinyapps.io/GROWdatabase/), allowing users to search and graph microbial and spatial data simultaneously. In summary, this microbial genome resource represents the first publicly available genome collection from rivers and offers data that can be leveraged across microbiome studies. GROWdb is an expanding repository to incorporate and unify global river multi-omic data for the future.

59 BASIC BIOLOGICAL SCIENCES↗

KGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating N<sub>2</sub>O emission using data from mesocosm experiments

Abstract. Agricultural nitrous oxide (N2O) emission accounts for a non-trivial fraction of global greenhouse gas (GHG) budget. To date, estimating N2O fluxes from cropland remains a challenging task because the related microbial processes (e.g., nitrification and denitrification) are controlled by complex interactions among climate, soil, plant and human activities. Existing approaches such as process-based (PB) models have well-known limitations due to insufficient representations of the processes or uncertainties of model parameters, and due to leverage recent advances in machine learning (ML) a new method is needed to unlock the “black box” to overcome its limitations such as low interpretability, out-of-sample failure and massive data demand. In this study, we developed a first-of-its-kind knowledge-guided machine learning model for agroecosystems (KGML-ag) by incorporating biogeophysical and chemical domain knowledge from an advanced PB model, ecosys, and tested it by comparing simulating daily N2O fluxes with real observed data from mesocosm experiments. The gated recurrent unit (GRU) was used as the basis to build the model structure. To optimize the model performance, we have investigated a range of ideas, including (1) using initial values of intermediate variables (IMVs) instead of time series as model input to reduce data demand; (2) building hierarchical structures to explicitly estimate IMVs for further N2O prediction; (3) using multi-task learning to balance the simultaneous training on multiple variables; and (4) pre-training with millions of synthetic data generated from ecosys and fine-tuning with mesocosm observations. Six other pure ML models were developed using the same mesocosm data to serve as the benchmark for the KGML-ag model. Results show that KGML-ag did an excellent job in reproducing the mesocosm N2O fluxes (overall r2=0.81, and RMSE=3.6 mgNm-2d-1 from cross validation). Importantly, KGML-ag always outperforms the PB model and ML models in predicting N2O fluxes, especially for complex temporal dynamics and emission peaks. Besides, KGML-ag goes beyond the pure ML models by providing more interpretable predictions as well as pinpointing desired new knowledge and data to further empower the current KGML-ag. We believe the KGML-ag development in this study will stimulate a new body of research on interpretable ML for biogeochemistry and other related geoscience processes.

54 ENVIRONMENTAL SCIENCES↗

Deciphering the microbial and molecular responses of geographically diverse Setaria accessions grown in a nutrient-poor soil

The microbial and molecular characterization of the ectorhizosphere is an important step towards developing a more complete understanding of how the cultivation of biofuel crops can be undertaken in nutrient poor environments. The ectorhizosphere of Setaria is of particular interest because the plant component of this plant-microbe system is an important agricultural grain crop and a model for biofuel grasses. Importantly, Setaria lends itself to high throughput molecular studies. As such, we have identified important intra- and interspecific microbial and molecular differences in the ectorhizospheres of three geographically distant Setaria italica accessions and their wild ancestor S . viridis . All were grown in a nutrient-poor soil with and without nutrient addition. To assess the contrasting impact of nutrient deficiency observed for two S . italica accessions, we quantitatively evaluated differences in soil organic matter, microbial community, and metabolite profiles. Together, these measurements suggest that rhizosphere priming differs with Setaria accession, which comes from alterations in microbial community abundances, specifically Actinobacteria and Proteobacteria populations. When globally comparing the metabolomic response of Setaria to nutrient addition, plants produced distinctly different metabolic profiles in the leaves and roots. With nutrient addition, increases of nitrogen containing metabolites were significantly higher in plant leaves and roots along with significant increases in tyrosine derived alkaloids, serotonin, and synephrine. Glycerol was also found to be significantly increased in the leaves as well as the ectorhizosphere. These differences provide insight into how C 4 grasses adapt to changing nutrient availability in soils or with contrasting fertilization schemas. Gained knowledge could then be utilized in plant enhancement and bioengineering efforts to produce plants with superior traits when grown in nutrient poor soils.

59 BASIC BIOLOGICAL SCIENCES↗

Three Decades of Global Methane Sources and Sinks

Methane is an important greenhouse gas, responsible for about 20 of the warming induced by long-lived greenhouse gases since pre-industrial times. By reacting with hydroxyl radicals, methane reduces the oxidizing capacity of the atmosphere and generates ozone in the troposphere. Although most sources and sinks of methane have been identified, their relative contributions to atmospheric methane levels are highly uncertain. As such, the factors responsible for the observed stabilization of atmospheric methane levels in the early 2000s, and the renewed rise after 2006, remain unclear. Here, we construct decadal budgets for methane sources and sinks between 1980 and 2010, using a combination of atmospheric measurements and results from chemical transport models, ecosystem models, climate chemistry models and inventories of anthropogenic emissions. The resultant budgets suggest that data-driven approaches and ecosystem models overestimate total natural emissions. We build three contrasting emission scenarios which differ in fossil fuel and microbial emissions to explain the decadal variability in atmospheric methane levels detected, here and in previous studies, since 1985. Although uncertainties in emission trends do not allow definitive conclusions to be drawn, we show that the observed stabilization of methane levels between 1999 and 2006 can potentially be explained by decreasing-to-stable fossil fuel emissions, combined with stable-to-increasing microbial emissions. We show that a rise in natural wetland emissions and fossil fuel emissions probably accounts for the renewed increase in global methane levels after 2006, although the relative contribution of these two sources remains uncertain.

periodic variations↗

Effects of ingested nanocellulose on intestinal microbiota and homeostasis in Wistar Han rats

Micron scale crystalline and fibrillar cellulose materials are “generally regarded as safe” (GRAS) as binders and thickeners in food products. Yet, partly due to a lack of relevant toxicological data, nanocellulose (NC) materials, which have unique properties that can be exploited to improve food quality and safety, have yet to receive FDA approval as food ingredients. Results of in vitro and in vivo toxicological studies of ingested NC, detailed in a recent companion report, revealed minimal acute in vitro cytotoxicity, and no toxicity in a subacute rat gavage model, suggesting that NC materials are non-hazardous. However, ingested materials may also modulate gut microbial populations, or alter aspects of intestinal function not evaluated in standard totoxicity testing, which could have important health implications. Here, we report the results of studies of the effects of ingested cellulose nanofibrils (CNF) on the fecal microbiome and metabolome, intestinal (ileal) epithelial cell mRNA expression of cell junction genes, and ileal cytokine production. Feces, plasma, and ileum samples were collected from Wistar Han rats before and after five weeks of biweekly gavages of water or cream, with or without 1% w/w CNF. Analysis of fecal microbial populations revealed that CNF caused changes in both genus and species diversity, with specific effects on species that produce short chain fatty acids, and that have been associated with increased IgA production and elevation of insulin levels. Fecal metabolomic analysis revealed relatively few effects of CNF, with significant changes in the levels of only ten metabolites out of 366 measured. Exposure to CNF also caused differential regulation of mRNA expression of several genes involved in epithelial cell junctions, and increased production of cytokines that both promote and inhibit proliferation of CD8 T cells. These perturbations in intestinal homeostasis contrast somewhat with the absence of in vitro and in vivo toxicity observed previously but would appear to represent minor effects. Additionally, the gut microbiome is highly sensitive to ingested substances, and such disturbances of the intestinal microbial ecosystem do not necessarily represent or predict meaningful pathology. Further studies, including chronic feeding studies, are needed to assess the real health implications, if any, of these changes.

59 BASIC BIOLOGICAL SCIENCES↗

Phage-specific metabolic reprogramming of virocells

Ocean viruses are abundant and infect 20–40% of surface microbes. Infected cells, termed virocells, are thus a predominant microbial state. Yet, virocells and their ecosystem impacts are understudied, thus precluding their incorporation into ecosystem models. Here we investigated how unrelated bacterial viruses (phages) reprogram one host into contrasting virocells with different potential ecosystem footprints. We independently infected the marine Pseudoalteromonas bacterium with siphovirus PSA-HS2 and podovirus PSA-HP1. Time-resolved multi-omics unveiled drastically different metabolic reprogramming and resource requirements by each virocell, which were related to phage–host genomic complementarity and viral fitness. Namely, HS2 was more complementary to the host in nucleotides and amino acids, and fitter during infection than HP1. Functionally, HS2 virocells hardly differed from uninfected cells, with minimal host metabolism impacts. HS2 virocells repressed energy-consuming metabolisms, including motility and translation. Contrastingly, HP1 virocells substantially differed from uninfected cells. They repressed host transcription, responded to infection continuously, and drastically reprogrammed resource acquisition, central carbon and energy metabolisms. Ecologically, this work suggests that one cell, infected versus uninfected, can have immensely different metabolisms that affect the ecosystem differently. Finally, we relate phage–host genome complementarity, virocell metabolic reprogramming, and viral fitness in a conceptual model to guide incorporating viruses into ecosystem models.

Environmental Sciences & Ecology↗

Meanders as a scaling motif for understanding of floodplain soil microbiome and biogeochemical potential at the watershed scale

Abstract Background Biogeochemical exports from watersheds are modulated by the activity of microorganisms that function over micron scales. Here, we tested the hypothesis that meander-bound regions share a core microbiome and exhibit patterns of metabolic potential that broadly predict biogeochemical processes in floodplain soils along a river corridor. Results We intensively sampled the microbiomes of floodplain soils located in the upper, middle, and lower reaches of the East River, Colorado. Despite the very high microbial diversity and complexity of the soils, we reconstructed 248 quality draft genomes representative of subspecies. Approximately one third of these bacterial subspecies was detected across all three locations at similar abundance levels, and ~ 15% of species were detected in two consecutive years. Within the meander-bound floodplains, we did not detect systematic patterns of gene abundance based on sampling position relative to the river. However, across meanders, we identified a core floodplain microbiome that is enriched in capacities for aerobic respiration, aerobic CO oxidation, and thiosulfate oxidation with the formation of elemental sulfur. Given this, we conducted a transcriptomic analysis of the middle floodplain. In contrast to predictions made based on the prominence of gene inventories, the most highly transcribed genes were relatively rare amoCAB and nxrAB (for nitrification) genes, followed by genes involved in methanol and formate oxidation, and nitrogen and CO 2 fixation. Within all three meanders, low soil organic carbon correlated with high activity of genes involved in methanol, formate, sulfide, hydrogen, and ammonia oxidation, nitrite oxidoreduction, and nitrate and nitrite reduction. Overall, the results emphasize the importance of sulfur, one-carbon and nitrogen compound metabolism in soils of the riparian corridor. Conclusions The disparity between the scale of a microbial cell and the scale of a watershed currently limits the development of genomically informed predictive models describing watershed biogeochemical function. Meander-bound floodplains appear to serve as scaling motifs that predict aggregate capacities for biogeochemical transformations, providing a foundation for incorporating riparian soil microbiomes in watershed models. Widely represented genetic capacities did not predict in situ activity at one time point, but rather they define a reservoir of biogeochemical potential available as conditions change.

54 ENVIRONMENTAL SCIENCES↗

Coastal Wetland Carbon Sequestration in a Warmer Climate (Final Report)

Coastal wetlands are global hotspots of carbon storage and locations where carbon and nitrogen cycles have a disproportionately large impact on land, water, and air in comparison to the area they occupy. The extremely high rates of carbon sequestration in these systems are the result of complex feedbacks between vegetation and the physical environment. The plant and microbial interactions that drive these feedbacks are absent in ecosystem- and global-scale Earth System models. The goal of this proposal was to address the uncertain response of the coastal carbon sink to climate change, a critical knowledge gap in coastal carbon research and a significant barrier to incorporating coastal wetlands into Earth System Models. The Salt Marsh Accretion Response to Temperature eXperiment (SMARTX) was designed to understand the ecosystem-scale consequences of warming and elevated CO₂ (eCO₂) in tidal wetlands at the coastal terrestrial-aquatic interface. We successfully designed and built a novel whole-ecosystem warming and eCO₂ experiment in a coastal wetland. The gradient design of the warming treatments (+0, +1.7, +3.4, +5.1 ⁰C) allowed us to discover unexpected non-linear and non-additive responses arising from plant-microbe interactions. We concluded that these non-linear responses to warming were the result of plants and microbes responding to temperature at different thresholds, with important consequences for forecasting terrestrial ecosystem responses to climate change and understanding global trends.

54 ENVIRONMENTAL SCIENCES↗

2025 Workshop on Envisioning Frontiers in AI and Computing for Biological Research: Position Papers

This workshop aims to identify key research directions for transforming biology using artificial intelligence (AI), machine learning (ML) and computational methods to facilitate the discovery of new behaviors, mechanisms, and designs of biological processes relevant to DOE missions, underpinning a broader U.S. bioeconomy. By developing novel AI/ML technologies to analyze and interpret complex biological data, researchers can organize and simulate biological processes at various scales as well as advance predictive understanding and manipulation of biological systems. This integration of computation, experimentation, and next-generation experimental technologies can lead to discoveries in new biological behaviors and mechanisms relevant to DOE missions. The focus is on how advanced computational and mathematical methods can impact this mission by exploring digital twins, foundation models, automated laboratory experiments, modeling of complex living systems, and data-driven approaches for the biodesign of plants and microbial systems. While data management is important, it is not the primary focus of this workshop, which will assess the current state, trends, and AI/ML challenges at the interface between biology and computational science to identify opportunities for high-impact research at their intersection. The goal is to define research needs and opportunities that align with biological sciences, computational sciences, and applied mathematics research.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial vitamin biosynthesis links gut microbiota dynamics to chemotherapy toxicity

ABSTRACT Dose-limiting toxicities pose a major barrier to cancer treatment. While preclinical studies show that the gut microbiota influences and is influenced by anticancer drugs, data from patients paired with careful side effect monitoring remains limited. Here, we investigate capecitabine (CAP)-microbiome interactions through longitudinal metagenomic sequencing of stool from 56 advanced colorectal cancer patients. CAP significantly altered the gut microbiome, enriching for menaquinol (vitamin K2) biosynthesis genes. Transposon library screens, targeted gene deletions, and media supplementation revealed that menaquinol biosynthesis protectsEscherichia colifrom drug toxicity. Stool menaquinol gene and metabolite levels were associated with decreased peripheral sensory neuropathy. Machine learning models trained in this cohort predicted toxicities in an independent cohort. Taken together, these results suggest treatment-associated increases in microbial vitamin biosynthesis serve a chemoprotective role for bacterial and host cells. Further, our findings provide a foundation for in-depth mechanistic dissection, human intervention studies, and extension to other cancer treatments. IMPORTANCE Side effects are common during the treatment of cancer. The trillions of microbes found within the human gut are sensitive to anticancer drugs, but the effects of treatment-induced shifts in gut microbes for side effects remain poorly understood. We profiled gut microbes in colorectal cancer patients treated with capecitabine and carefully monitored side effects. We observed a marked expansion in genes for producing vitamin K2 (menaquinone). Vitamin K2 rescued gut bacterial growth and was associated with decreased side effects in patients. We then used information about gut microbes to develop a predictive model of drug toxicity that was validated in an independent cohort. These results suggest that treatment-associated increases in bacterial vitamin production protect both bacteria and host cells from drug toxicity, providing new opportunities for intervention and motivating the need to better understand how dietary intake and bacterial production of micronutrients like vitamin K2 influence cancer treatment outcomes.

Microbiology↗

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

INTRODUCTION Over the past 50 years, many microorganisms have displayed unexpected responses relevant to infectious disease when grown in microgravity and microgravity analogue environments, including changes in stress resistance, biofilm production, antibiotic sensitivity, final cell concentration, gene expression, enhanced host-pathogen interaction, and virulence. In parallel, astronaut studies have characterized a persistent spaceflight-induced dysregulation of the human immune system; consisting of altered leukocyte distribution, reductions in T and NK cell function, altered cytokine profiles, and reactivation of latent herpesviruses. Further, astronauts have some degree of clinical incidence, primarily infectious disease episodes and atopic dermatitis. The impact of the microgravity environment on host-pathogen interactions and potential for clinical disease remains understudied and poorly characterized. SPECIFIC AIMS In this study, the following Specific Aims are being investigated, using the microbial pathogens, Salmonella enterica Enteritidis, Pseudomonas aeruginosa, Burkholderia cepacia, Streptococcus pneumoniae, and enterohemorrhagic Escherichia coli (EHEC). Aim 1: Characterize the effect of spaceflight analogue culture on microbial pathogenesis-related stress responses and in vitro host-pathogen interactions. Analyses include microbial stress responses as well as colonization and viability following pathogen challenge of three-dimensional (3-D) tissue co-culture models containing immune cells. We specifically selected obligate and opportunistic pathogens that are medically important and have been or are likely to be found aboard spacecraft. Aim 2: Characterize the effect of spaceflight analogue culture on the virulence potential of pathogenic microorganisms. Virulence will be assessed using a mouse model of infection. SIGNIFICANCE The goal of this study is to use spaceflight analogue conditions to gain insight into the breadth of medically-significant International Space Station microorganisms that have altered virulence and the impact of those changes on the immune response of the host. This information will provide critical understanding into the impact of microgravity on potential alterations in microbial virulence and associated infectious disease risk to crew health during spaceflight missions.

C M Ott↗

Genome-Resolved Metagenomics and Detailed Geochemical Speciation Analyses Yield New Insights into Microbial Mercury Cycling in Geothermal Springs

Geothermal systems emit substantial amounts of aqueous, gaseous, and methylated mercury, but little is known about microbial influences on mercury speciation. Here, we report results from genome-resolved metagenomics and mercury speciation analysis of acidic warm springs in the Ngawha Geothermal Field (< 55°C, pH < 4.5), Northland Region, Aotearoa New Zealand. Our aim was to identify the microorganisms genetically equipped for mercury methylation, demethylation, or Hg(II) reduction to volatile Hg(0) in these springs. Dissolved total and methylated mercury concentrations in two adjacent springs with different mercury speciation ranked among the highest reported from natural sources (250 to 16,000 ng liter -1 and 0.5 to 13.9 ng liter -1 , respectively). Total solid mercury concentrations in spring sediments ranged from 1,274 to 7,000 μg g -1 . In the context of such ultrahigh mercury levels, the geothermal microbiome was unexpectedly diverse and dominated by acidophilic and mesophilic sulfur- and iron-cycling bacteria, mercury- and arsenic-resistant bacteria, and thermophilic and acidophilic archaea. By integrating microbiome structure and metagenomic potential with geochemical constraints, we constructed a conceptual model for biogeochemical mercury cycling in geothermal springs. The model includes abiotic and biotic controls on mercury speciation and illustrates how geothermal mercury cycling may couple to microbial community dynamics and sulfur and iron biogeochemistry.

59 BASIC BIOLOGICAL SCIENCES↗

SPACEFLIGHT-INDUCED CHANGES IN MICROBIAL VIRULENCE AND THE IMPACT TO THE HOST IMMUNE RESPONSE

INTRODUCTION Over the past 50 years, microorganisms have displayed 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, and virulence. In parallel, astronaut studies have characterized a persistent spaceflight-induced dysregulation of the human immune system; consisting of altered leukocyte distribution, reductions in T and NK cell function, altered cytokine profiles, and reactivation of latent herpesviruses. Further, astronauts have some degree of clinical incidence, primarily infectious disease episodes and atopic dermatitis. The impact of the microgravity environment on host-pathogen interactions and potential for clinical disease remains understudied and poorly characterized. SPECIFIC AIMS In the Host-Microorganism, Microbial Response aspect of this study, the following Specific Aims are being investigated, using the microbial pathogens, Salmonella enterica Enteritidis, Pseudomonas aeruginosa, Burkholderia cepacia, Streptococcus pneumoniae, and enterohemorrhagic Escherichia coli. Aim 1: Characterize the effect of spaceflight analogue culture on microbial pathogenesis-related stress responses and in vitro host-pathogen interactions. Analysis will include microbial stress responses as well as colonization and viability following pathogen challenge of three-dimensional (3-D) tissue co-culture models containing immune cells. We specifically selected obligate and opportunistic pathogens that are medically important and have been or are likely to be found aboard spacecraft. Aim 2: Characterize the effect of spaceflight analogue culture on the virulence potential of pathogenic microorganisms. Changes in virulence will be assessed using a mouse model of infection. SIGNIFICANCE The goal of this study is to use spaceflight analogue conditions to gain insight into the breadth of medically-significant International Space Station microorganisms that have altered virulence and the impact of those changes on the immune response of the host, including astronaut immune cells. This information will provide critical understanding into the impact of microgravity on potential alterations in microbial virulence and associated infectious disease risk to crew health during spaceflight missions.

C. M. Ott↗