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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Direction of impact for explainable risk assessment modeling

Abstract Several graphical indicators have been recently introduced to help analysts visualize the marginal effects of inputs in complex models. The insights derived from such tools may help decision‐makers and risk analysts in designing interventions. However, we know little about the adequacy and consistency of different indicators. This work investigates popular marginal effect indicators to understand whether they yield indications consistent with the properties of the quantitative model under inspection. Specifically, we examine the notions of monotonicity, Lipschitz, and concavity consistency. Surprisingly, only PD functions satisfy all these notions of consistency. However, when selecting the indicators, in addition to consistency, analysts need to consider the risk of model extrapolation. For situations where such risk is under control, we utilize individual conditional expectations together with PD plots. Two applications, on a NASA space risk assessment model and a susceptible exposed infected recovered (SEIR) model for the COVID‐19 pandemic illustrate the insights obtained from these indicators.

Mathematical Methods In Social Sciences↗
DOE OSTI2020

Attached Jet Velocity Profiles in Mixing Tanks

Free jets have been studied in detail over much of the last century, but the theory for offset and attached jets remains incomplete. Attached jets differ from free jets in that they lose momentum to nearby surfaces, attenuating their velocities. The velocity profiles of free circular jets are nearly Gaussian, with quantitative mathematical descriptions derived from first principles by Goertler and Tollmien (Rajaratnam, 1976). In contrast, mathematical descriptions of three-dimensional attached jets from circular nozzles remain much less mature. Agelin-Chaab and Tachie (2011) used particle imaging velocimetry of a three-dimensional attached jet to show that the scaled velocity decays with scaled distance from the nozzle with a power law exponent between -1.15 and -1.21, which is larger in magnitude than that of a free jet. However, quantitative analytical expressions for the velocity profiles of attached jets similar to those of free jets remain elusive. This paper addresses this critical gap. Here we evaluate the velocity profiles of three-dimensional offset jets emerging from circular nozzles that that become attached jets. These jets lose momentum due to interactions with nearby surfaces and are important to evaluating flows in mixing vessels and to suspending solids and trapped gases in radioactive waste tanks. Despite the importance of attached jets, prior insight has been purely experimental, limited to overly simplistic analytical models, or restricted to computationally expensive computational fluid dynamics case studies. We compare the expression of Verhoff (1963) to experimental results to find reasonable quantitative agreement. As stated by Agelin-Chaab and Tachie (2011), “detailed velocity measurements of 3D offset jets are rare.” Such remains the case. This study adds to the literature by providing information at two additional Reynolds numbers (1.43 106 and 1.87 106) and evaluating simple but accurate expressions for velocity profiles. These Reynolds numbers are an order of magnitude higher than prior reports. The semi-empirical stream wise velocity profile perpendicular to the surface proposed by Verhoff (1963) is in approximate agreement with these velocity profiles, which is surprising because these attached jets are three-dimensional instead of two-dimensional as evaluated by Verhoff. However, additional work is necessary to fully describe these profiles quantitatively.

jet, attached jet, offset jet↗
DOE OSTI2021

LARGE PARTICLE SEPARATION FROM NON-NEWTONIAN SLURRIES USING BUMP ARRAYS

Here we evaluate the performance of bump arrays to separate large particles from non-Newtonian slurries with Bingham and Cross rheology. Bump arrays in deterministic lateral displacement devices separate large particles from small particles using arrays of staggered posts. Large particles, defined as those with radii larger than the distance between the edge of a post and the stagnation streamline from the next downstream post, must bump toward one side of the device, whereas particles smaller than this distance slalom from entrance to exit. Although these devices have been used to separate a wide variety of large particles from blood cells to sand, partition of large particles from non-Newtonian fluids remains unexplored. Yet, an important set of modestly concentrated slurries, including Hanford nuclear waste, displays non-Newtonian rheology. Here we evaluate the influence of non-Newtonian rheology on the large-small particle size cutoff in bump arrays using a model that explores the influence of yield stresses, ratios of zero and infinite shear viscosities, and Cross’s exponent under strictly laminar well-developed conditions. Surprisingly, we find that viscosity ratios and Cross’s exponent make no significant difference on the particle cutoffs between large particles that bump and small particles that slalom around the posts from entrance to exit. In contrast, we find that yield stresses do significantly affect the size cutoff. As the yield stress increases, the velocity profiles become more plug like lowering the size cutoff. For nuclear waste separations where removing large particles is a priority, increasing yield stresses is conservative.

slurry, solids removal, deterministic later displa↗
DOE OSTI2020

MoS 2 -supported Au 31 for CO hydrogenation: A first-principle study

While the basal plane of single-layer molybdenum disulphide (MoS 2 ) is inert, attempts have been made to functionalize it chemically through the creation of defects and/or addition of dopants. With nanoparticles as dopants, the authors present density functional theory-based calculations of the hydrogenation of CO on a 31-atom, bilayer Au cluster supported on single-layer MoS 2 (Au31/MoS 2 ). Not surprisingly, the adsorption and reaction of all species involved in the hydrogenation occur at the edges of the cluster—the regions at which the interaction between MoS 2 and the Au cluster is tracked to be the strongest. The authors find two possible mechanisms that lead to the formation of methanol: (1) CO* → CHO* → CH 2 O* → CH 3 O* → CH 3 OH* and (2) CO* → CHO* → HCOH* → CH2OH* → CH3OH*, where * indicates the adsorbed species. Detailed analysis of the reaction pathways, however, does not result in favoring one mechanism over the other. Rather, both mechanisms are facile. In addition, the rate-limiting step in each mechanism is found to be the formation of the formyl radical group (CO* + H* → CHO*).

2D materials↗
DOE OSTI2025

Ab initio prediction of rapid kinetics of Fe impurities in δ -Pu

Here, we study the formation energies of iron impurities in δ-Pu within spin–orbital-polarized density functional theory (SOP-DFT). The thermodynamic solubility limit of iron in δ-Pu is calculated, indicating low miscibility. We show that surprisingly, Fe impurities at equilibrium are almost equally likely to occupy octahedral interstitial sites or substitutional sites, with slight preference for the former. In contrast, we find the energy of the tetrahedral interstitial Fe to be nearly 1 eV higher than the octahedral one. We explore the energy landscape for Fe impurity hopping diffusion and conclude that Fe impurities in δ-Pu are divided into two populations: (i) Immobile substitutional Fe impurities and (ii) highly mobile interstitial Fe impurities. The latter, (ii), migrate between octahedral interstitial sites with an energy barrier of around 0.2 eV. The energy barrier for exchange between the two populations is calculated to exceed 0.7 eV. Finally, we discuss the role of magnetic order on the impurity energetics.

Atomic structure↗
DOE OSTI2020

More chemical detection through less sampling: amplifying chemical signals in hyperspectral data cubes through compressive sensing

Compressive sensing (CS) is a method of sampling which permits some classes of signals to be reconstructed with high accuracy even when they were sampled at sub-Nyquist rates. In this paper we explore a phenomenon in which bandwise CS sampling of a hyperspectral data cube followed by reconstruction can actually result in amplification of chemical signals contained in the cube. Perhaps most surprisingly, chemical signal amplification generally seems to increase as the level of sampling decreases. In some examples, the chemical signal is significantly stronger in a data cube reconstructed from 10% CS sampling than it is in the raw, 100% sampled data cube. We explore this phenomenon in two real-world datasets including the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset and the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset. Each of these datasets contains the release of a chemical simulant, such as glacial acetic acid, triethyl phospate, and sulfur hexafluoride, and in all cases we use the adaptive coherence estimator (ACE) to detect a target signal in the hyperspectral data cube. We end the paper by suggesting some theoretical justifications for why chemical signals would be amplified in CS sampled and reconstructed hyperspectral data cubes and discuss some practical implications.

Hyperspectral imagery, Compressive Sensing, single↗
DOE OSTI2022

Sterile Neutrinos: Are They Real?

Neutrinos are perhaps the least understood of the known denizens of the subatomic world. They have nearly no mass, interact only via the weak nuclear force and gravity, and, perhaps most surprising, the three known species of neutrinos can transform from one variant into another. This transformation, called neutrino oscillation, has been demonstrated only relatively recently and has led to speculation that there might be another, even more mysterious, neutrino variant, called the sterile neutrino. While the sterile neutrino remains a hypothetical particle, it is an interesting one and searches for it are a key research focus of the world’s neutrino scientist community.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Ferromagnetic order beyond the superconducting dome in a cuprate superconductor

According to conventional wisdom, the extraordinary properties of the cuprate high-temperature superconductors arise from doping a strongly correlated antiferromagnetic insulator. The highly overdoped cuprates—whose doping lies beyond the dome of superconductivity—are considered to be conventional Fermi liquid metals. We report the emergence of itinerant ferromagnetic order below 4 kelvin for doping beyond the superconducting dome in thin films of electron-doped La 2– x Ce x CuO 4 (LCCO). The existence of this ferromagnetic order is evidenced by negative, anisotropic, and hysteretic magnetoresistance, hysteretic magnetization, and the polar Kerr effect, all of which are standard signatures of itinerant ferromagnetism in metals. This surprising result suggests that the overdoped cuprates are strongly influenced by electron correlations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Directly visualizing the momentum-forbidden dark excitons and their dynamics in atomically thin semiconductors

Resolving momentum degrees of freedom of excitons, which are electron-hole pairs bound by the Coulomb attraction in a photoexcited semiconductor, has remained an elusive goal for decades. In atomically thin semiconductors, such a capability could probe the momentum-forbidden dark excitons, which critically affect proposed opto-electronic technologies but are not directly accessible using optical techniques. In this work, we probed the momentum state of excitons in a tungsten diselenide monolayer by photoemitting their constituent electrons and resolving them in time, momentum, and energy. We obtained a direct visual of the momentum-forbidden dark excitons and studied their properties, including their near degeneracy with bright excitons and their formation pathways in the energy-momentum landscape. These dark excitons dominated the excited-state distribution, a surprising finding that highlights their importance in atomically thin semiconductors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Improving Arsenic Tolerance of Pyrococcus furiosus by Heterologous Expression of a Respiratory Arsenate Reductase

Arsenate is a notorious toxicant that is known to disrupt multiple biochemical pathways. Many microorganisms have developed mechanisms to detoxify arsenate using the ArsC-type arsenate reductase, and some even use arsenate as a terminal electron acceptor for respiration involving arsenate respiratory reductase (Arr). ArsC-type reductases have been studied extensively, but the phylogenetically unrelated Arr system is less investigated and has not been characterized from Archaea. Here, we heterologously expressed the genes encoding Arr from the crenarchaeon Pyrobaculum aerophilum in the euryarchaeon Pyrococcus furiosus, both of which grow optimally near 100°C. Recombinant P. furiosus was grown on molybdenum (Mo)- or tungsten (W)-containing medium, and two types of recombinant Arr enzymes were purified, one containing Mo (Arr-Mo) and one containing W (Arr-W). Purified Arr-Mo had a 140-fold higher specific activity in arsenate [As(V)] reduction than Arr-W, and Arr-Mo also reduced arsenite [As(III)]. The P. furiosus strain expressing Arr-Mo (the Arr strain) was able to use arsenate as a terminal electron acceptor during growth on peptides. In addition, the Arr strain had increased tolerance compared to that of the parent strain to arsenate and also, surprisingly, to arsenite. Compared to the parent, the Arr strain accumulated intracellularly almost an order of magnitude more arsenic when cells were grown in the presence of arsenite. Furthermore, x-ray absorption spectroscopy (XAS) results suggest that the Arr strain of P. furiosus improves its tolerance to arsenite by increasing production of less-toxic arsenate and nontoxic methylated arsenicals compared to that by the parent.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Tailoring a Global Iron Regulon to a Uropathogen

Pathogenicity islands and plasmids bear genes for pathogenesis of various Escherichia coli pathotypes. Although there is a basic understanding of the contribution of these virulence factors to disease, less is known about variation in regulatory networks in determining disease phenotypes. Here, we dissected a regulatory network directed by the conserved iron homeostasis regulator, ferric uptake regulator (Fur), in uropathogenic E. coli (UPEC) strain CFT073. Comparing anaerobic genome-scale Fur DNA binding with Fur-dependent transcript expression and protein levels of the uropathogen to that of commensal E. coli K-12 strain MG1655 showed that the Fur regulon of the core genome is conserved but also includes genes within the pathogenicity/genetic islands. Unexpectedly, regulons indicative of amino acid limitation and the general stress response were also indirectly activated in the uropathogen fur mutant, suggesting that induction of the Fur regulon increases amino acid demand. Using RpoS levels as a proxy, addition of amino acids mitigated the stress. In addition, iron chelation increased RpoS to the same levels as in the fur mutant. The increased amino acid demand of the fur mutant or iron chelated cells was exacerbated by aerobic conditions, which could be partly explained by the O 2 -dependent synthesis of the siderophore aerobactin, encoded by an operon within a pathogenicity island. Taken together, these data suggest that in the iron-poor environment of the urinary tract, amino acid availability could play a role in the proliferation of this uropathogen, particularly if there is sufficient O 2 to produce aerobactin. IMPORTANCE Host iron restriction is a common mechanism for limiting the growth of pathogens. We compared the regulatory network controlled by Fur in uropathogenic E. coli (UPEC) to that of nonpathogenic E. coli K-12 to uncover strategies that pathogenic bacteria use to overcome iron limitation. Although iron homeostasis functions were regulated by Fur in the uropathogen as expected, a surprising finding was the activation of the stringent and general stress responses in the uropathogen fur mutant, which was rescued by amino acid addition. This coordinated global response could be important in controlling growth and survival under nutrient-limiting conditions and during transitions from the nutrient-rich environment of the lower gastrointestinal (GI) tract to the more restrictive environment of the urinary tract. The coupling of the response of iron limitation to increased demand for amino acids could be a critical attribute that sets UPEC apart from other E. coli pathotypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The global anaerobic metabolism regulator fnr is necessary for the degradation of food dyes and drugs by Escherichia coli

ABSTRACT The microbiome is an underappreciated contributor to intestinal drug metabolism with broad implications for drug efficacy and toxicity. While considerable progress has been made toward identifying the gut bacterial genes and enzymes involved, the role of environmental factors in shaping their activity remains poorly understood. Here, we focus on the gut bacterial reduction of azo bonds (R-N = N-R’), found in diverse chemicals in both food and drugs. Surprisingly, the canonical azoR gene in Escherichia coli was dispensable for azo bond reduction. Instead, azoreductase activity was controlled by the fumarate and nitrate reduction ( fnr ) regulator, consistent with a requirement for the anoxic conditions found within the gastrointestinal tract. Paired transcriptomic and proteomic analysis of the fnr regulon revealed that in addition to altering the expression of multiple reductases, FNR is necessary for the metabolism of L-Cysteine to hydrogen sulfide, enabling the degradation of azo bonds. Furthermore, we found that FNR indirectly regulates this process through the small noncoding regulatory RNA fnrS . Taken together, these results show how gut bacteria sense and respond to their intestinal environment to enable the metabolism of chemical groups found in both dietary and pharmaceutical compounds. IMPORTANCE This work has broad relevance due to the ubiquity of dyes containing azo bonds in food and drugs. We report that azo dyes can be degraded by human gut bacteria through both enzymatic and nonenzymatic mechanisms, even from a single gut bacterial species. Furthermore, we revealed that environmental factors, oxygen, and L-Cysteine control the ability of E. coli to degrade azo dyes due to their impacts on bacterial transcription and metabolism. These results open up new opportunities to manipulate the azoreductase activity of the gut microbiome through the manipulation of host diet, suggest that azoreductase potential may be altered in patients suffering from gastrointestinal disease, and highlight the importance of studying bacterial enzymes for drug metabolism in their natural cellular and ecological context.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Genome Streamlining, Proteorhodopsin, and Organic Nitrogen Metabolism in Freshwater Nitrifiers

Microbial nitrification is a critical process governing nitrogen availability in aquatic systems. Freshwater nitrifiers have received little attention, leaving many unanswered questions about their taxonomic distribution, functional potential, and ecological interactions. Here, we reconstructed genomes to infer the metabolism and ecology of free-living picoplanktonic nitrifiers across the Laurentian Great Lakes, a connected series of five of Earth’s largest lakes. Surprisingly, ammonia-oxidizing bacteria (AOB) related to Nitrosospira dominated over ammonia-oxidizing archaea (AOA) at nearly all stations, with distinct ecotypes prevailing in the transparent, oligotrophic upper lakes compared to Lakes Erie and Ontario. Unexpectedly, one ecotype of Nitrosospira encodes proteorhodopsin, which could enhance survival under conditions where ammonia oxidation is inhibited or substrate limited. Nitrite-oxidizing bacteria (NOB) “Candidatus Nitrotoga” and Nitrospira fluctuated in dominance, with the latter prevailing in deeper, less-productive basins. Genome reconstructions reveal highly reduced genomes and features consistent with genome streamlining, along with diverse adaptations to sunlight and oxidative stress and widespread capacity for organic nitrogen use. Our findings expand the known functional diversity of nitrifiers and establish their ecological genomics in large lake ecosystems. By elucidating links between microbial biodiversity and biogeochemical cycling, our work also informs ecosystem models of the Laurentian Great Lakes, a critical freshwater resource experiencing rapid environmental change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Time-resolved multi-omics reveals diverse metabolic strategies of Salmonella during diet-induced inflammation

With a rise in antibiotic resistance and chronic infection, the metabolic response of Salmonella enterica serovar Typhimurium to various dietary conditions over time remains an understudied avenue for novel, targeted therapeutics. Elucidating how enteric pathogens respond to dietary variation not only helps us decipher the metabolic strategies leveraged for expansion but also assists in proposing targets for therapeutic interventions. In this study, we use a multi-omics approach to identify the metabolic response of Salmonella enterica serovar Typhimurium in mice on both a fibrous diet and high-fat diet over time. When comparing Salmonella gene expression between diets, we found a preferential use of respiratory electron acceptors consistent with increased inflammation in high-fat diet mice. Looking at the high-fat diet over the course of infection, we noticed heterogeneity in samples based on Salmonella ribosomal activity, which is separated into three infection phases: early, peak, and late. We identified key respiratory, carbon, and pathogenesis gene expressions descriptive of each phase. Surprisingly, we identified genes associated with host cell entry expressed throughout infection, suggesting subpopulations of Salmonella or stress-induced dysregulation. Collectively, these results highlight not only the sensitivity of Salmonella to its environment but also identify phase-specific genes that may be used as therapeutic targets to reduce infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Predicting variable gene content in Escherichia coli using conserved genes

Having the ability to predict the protein-encoding gene content of an incomplete genome or metagenome-assembled genome is important for a variety of bioinformatic tasks. In this study, as a proof of concept, we built machine learning classifiers for predicting variable gene content in Escherichia coli genomes using only the nucleotide k-mers from a set of 100 conserved genes as features. Protein families were used to define orthologs, and a single classifier was built for predicting the presence or absence of each protein family occurring in 10%–90% of all E. coli genomes. The resulting set of 3,259 extreme gradient boosting classifiers had a per-genome average macro F1 score of 0.944 [0.943–0.945, 95% CI]. We show that the F1 scores are stable across multi-locus sequence types and that the trend can be recapitulated by sampling a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including “hypothetical proteins” was accurately predicted (F1 = 0.902 [0.898–0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions had slightly lower F1 scores but were still accurate (F1s = 0.895, 0.872, 0.824, and 0.841 for transposon, phage, plasmid, and antimicrobial resistance-related functions, respectively). Finally, using a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources, we observed an average per-genome F1 score of 0.880 [0.876–0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Heterotrophic Thaumarchaea with Small Genomes Are Widespread in the Dark Ocean

The Thaumarchaeota is a diverse archaeal phylum comprising numerous lineages that play key roles in global biogeochemical cycling, particularly in the ocean. To date, all genomically characterized marine thaumarchaea are reported to be chemolithoautotrophic ammonia oxidizers. In this study, we report a group of putatively heterotrophic marine thaumarchaea (HMT) with small genome sizes that is globally abundant in the mesopelagic, apparently lacking the ability to oxidize ammonia. We assembled five HMT genomes from metagenomic data and show that they form a deeply branching sister lineage to the ammonia-oxidizing archaea (AOA). We identify this group in metagenomes from mesopelagic waters in all major ocean basins, with abundances reaching up to 6% of that of AOA. Surprisingly, we predict the HMT have small genomes of ~1 Mbp, and our ancestral state reconstruction indicates this lineage has undergone substantial genome reduction compared to other related archaea. The genomic repertoire of HMT indicates a versatile metabolism for aerobic chemoorganoheterotrophy that includes a divergent form III-a RuBisCO, a 2M respiratory complex I that has been hypothesized to increase energetic efficiency, and a three-subunit heme-copper oxidase complex IV that is absent from AOA. We also identify 21 pyrroloquinoline quinone (PQQ)-dependent dehydrogenases that are predicted to supply reducing equivalents to the electron transport chain and are among the most highly expressed HMT genes, suggesting these enzymes play an important role in the physiology of this group. Our results suggest that heterotrophic members of the Thaumarchaeota are widespread in the ocean and potentially play key roles in global chemical transformations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Species-specific ribosomal RNA-FISH identifies interspecies cellular-material exchange, active-cell population dynamics and cellular localization of translation machinery in clostridial cultures and co-cultures

ABSTRACT The development of synthetic microbial consortia in recent years has revealed that complex interspecies interactions, notably the exchange of cytoplasmic material, exist even among organisms that originate from different ecological niches. Although morphogenetic characteristics, viable RNA and protein dyes, and fluorescent reporter proteins have played an essential role in exploring such interactions, we hypothesized that ribosomal RNA-fluorescence in situ hybridization (rRNA-FISH) could be adapted and applied to further investigate interactions in synthetic or semisynthetic consortia. Despite its maturity, several challenges exist in using rRNA-FISH as a tool to quantify individual species population dynamics and interspecies interactions using high-throughput instrumentation such as flow cytometry. In this work, we resolve such challenges and apply rRNA-FISH to double and triple co-cultures of Clostridium acetobutylicum, Clostridium ljungdahlii, and Clostridium kluyveri . In pursuing our goal to capture each organism’s population dynamics, we demonstrate dynamic rRNA, and thus ribosome, exchange between the three species leading to the formation of hybrid cells. We also characterize the localization patterns of the translation machinery in the three species, identifying distinct, dynamic localization patterns among them. Our data also support the use of rRNA-FISH to assess the culture’s health and expansion potential, and, here again, our data find surprising differences among the three species examined. Taken together, our study argues for rRNA-FISH as a valuable and accessible tool for quantitative exploration of interspecies interactions, especially in organisms which cannot be genetically engineered or in consortia where selective pressures to maintain recombinant species cannot be used. IMPORTANCE Though dyes and fluorescent reporter proteins have played an essential role in identifying microbial species in co-cultures, we hypothesized that ribosomal RNA-fluorescence in situ hybridization (rRNA-FISH) could be adapted and applied to quantitatively probe complex interactions between organisms in synthetic consortia. Despite its maturity, several challenges existed before rRNA-FISH could be used to study Clostridium co-cultures of interest. First, species-specific probes for Clostridium acetobutylicum and Clostridium ljungdahlii had not been developed. Second, “state-of-the-art” labeling protocols were tedious and often resulted in sample loss. Third, it was unclear if FISH was compatible with existing fluorescent reporter proteins. We resolved these key challenges and applied the technique to co-cultures of C. acetobutylicum , C. ljungdahlii , and Clostridium kluyveri . We demonstrate that rRNA-FISH is capable of identifying rRNA/ribosome exchange between the three organisms and characterized rRNA localization patterns in each. In combination with flow cytometry, rRNA-FISH can capture sub-population dynamics in co-cultures.

Hill, John D.↗
DOE OSTI2024

Metagenomic clustering links specific metabolic functions to globally relevant ecosystems

ABSTRACT Metagenomic sequencing has advanced our understanding of biogeochemical processes by providing an unprecedented view into the microbial composition of different ecosystems. While the amount of metagenomic data has grown rapidly, simple-to-use methods to analyze and compare across studies have lagged behind. Thus, tools expressing the metabolic traits of a community are needed to broaden the utility of existing data. Gene abundance profiles are a relatively low-dimensional embedding of a metagenome’s functional potential and are, thus, tractable for comparison across many samples. Here, we compare the abundance of KEGG Ortholog Groups (KOs) from 6,539 metagenomes from the Joint Genome Institute’s Integrated Microbial Genomes and Metagenomes (JGI IMG/M) database. We find that samples cluster into terrestrial, aquatic, and anaerobic ecosystems with marker KOs reflecting adaptations to these environments. For instance, functional clusters were differentiated by the metabolism of antibiotics, photosynthesis, methanogenesis, and surprisingly GC content. Using this functional gene approach, we reveal the broad-scale patterns shaping microbial communities and demonstrate the utility of ortholog abundance profiles for representing a rapidly expanding body of metagenomic data. IMPORTANCE Metagenomics, or the sequencing of DNA from complex microbiomes, provides a view into the microbial composition of different environments. Metagenome databases were created to compile sequencing data across studies, but it remains challenging to compare and gain insight from these large data sets. Consequently, there is a need to develop accessible approaches to extract knowledge across metagenomes. The abundance of different orthologs (i.e., genes that perform a similar function across species) provides a simplified representation of a metagenome’s metabolic potential that can easily be compared with others. In this study, we cluster the ortholog abundance profiles of thousands of metagenomes from diverse environments and uncover the traits that distinguish them. This work provides a simple to use framework for functional comparison and advances our understanding of how the environment shapes microbial communities.

54 ENVIRONMENTAL SCIENCES↗