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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Association of Diet and Antimicrobial Resistance in Healthy U.S. Adults

Antimicrobial resistance (AMR) represents a significant source of morbidity and mortality worldwide, with expectations that AMR-associated consequences will continue to worsen throughout the coming decades. Since resistance to antibiotics is encoded in the microbiome, interventions aimed at altering the taxonomic composition of the gut might allow us to prophylactically engineer microbiomes that harbor fewer antibiotic resistant genes (ARGs). Diet is one method of intervention, and yet little is known about the association between diet and antimicrobial resistance. To address this knowledge gap, we examined diet using the food frequency questionnaire (FFQ; habitual diet) and 24-h dietary recalls (Automated Self-Administered 24-h [ASA24 ® ] tool) coupled with an analysis of the microbiome using shotgun metagenome sequencing in 290 healthy adult participants of the United States Department of Agriculture (USDA) Nutritional Phenotyping Study. We found that aminoglycosides were the most abundant and prevalent mechanism of AMR in these healthy adults and that aminoglycoside-O-phosphotransferases (aph3-dprime) correlated negatively with total calories and soluble fiber intake. Individuals in the lowest quartile of ARGs (low-ARG) consumed significantly more fiber in their diets than medium- and high-ARG individuals, which was concomitant with increased abundances of obligate anaerobes, especially from the family Clostridiaceae, in their gut microbiota. Finally, we applied machine learning to examine 387 dietary, physiological, and lifestyle features for associations with antimicrobial resistance, finding that increased phylogenetic diversity of diet was associated with low-ARG individuals. These data suggest diet may be a potential method for reducing the burden of AMR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Towards durable resistance to Septoria stem canker and leaf spot: A molecular understanding of resistance (Final Technical Report)

To identify, validate, and functionally characterize alleles that confer resistance to Septoria canker and leaf spot in Populus. The proposed research will elucidate a major mechanism of resistance to Sphaerulina musiva, the major limiting factor to plantations in eastern North America. Genome-wide association mapping, CRISPR/Cas9, and protein-protein assays will be used, enabling marker-aided breeding, reducing costs, and accelerating development of resistant varieties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Predicting Drug Resistance Using Deep Mutational Scanning

Drug resistance is a major healthcare challenge, resulting in a continuous need to develop new inhibitors. The development of these inhibitors requires an understanding of the mechanisms of resistance for a critical mass of occurrences. Recent genome editing technologies based on high-throughput DNA synthesis and sequencing may help to predict mutations resulting in resistance by testing large mutagenesis libraries. Here we describe the rationale of this approach, with examples and relevance to drug development and resistance in malaria.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2009

Identification of Bacteria and Determination of Biological Indicators

The ultimate goal of planetary protection research is to develop superior strategies for inactivating resistance bearing micro-organisms like Rummeli - bacillus stabekisii. By first identifying the particular physiologic pathway and/or structural component of the cell/spore that affords it such elevated tolerance, eradication regimes can then be designed to target these resistance-conferring moieties without jeopardizing the structural integrity of spacecraft hardware. Furthermore, hospitals and government agencies frequently use biological indicators to ensure the efficacy of a wide range of sterilization processes. The spores of Rummelibacillus stabekisii, which are far more resistant to many of such perturbations, could likely serve as a more significant biological indicator for potential survival than those being used currently.

Venkateswaran, Kasthuri↗
NASA NTRS2016

Testing of Synthetic Biological Membranes for Forward Osmosis Applications

Commercially available forward osmosis membranes have been extensively tested for human space flight wastewater treatment. Despite the improvements achieved in the last decades, there is still a challenge to produce reliable membranes with anti-fouling properties, chemical resistance, and high flux and selectivity. Synthetic biological membranes that mimic the ones present in nature, which underwent millions of years of evolution, represent a potential solution for further development and progress in membrane technology. Biomimetic forward osmosis membranes based on a polymeric support filter and coated with surfactant multilayers have been engineered to investigate how different manufacturing processes impact the performance and structure of the membrane. However, initial results of the first generation prototype membranes tests reveal a high scatter in the data, due to the current testing apparatus set up. The testing apparatus has been upgraded to improve data collection, reduce errors, and to allow higher control of the testing process.

Forward osmosis↗
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 OSTI2022

Antibiotic resistance and host immune system-induced metal bactericidal control are key factors for microbial persistence in the developing human preterm infant gut microbiome

The human gut microbiome, which develops and stabilizes during the early stages of infant life, plays an essential role in host health through the production of metabolic resources and the stimulation and training of the immune system. To study colonization and community functional dynamics of the microbiota based on responses to host immune processes during the normal and dysbiotic establishment of the gut, metaproteomics was conducted on 91 fecal samples collected over the first 90 days of life from 17 hospitalized premature infants. Microbial responses to antibiotic administration and host-imposed metal bactericidal control correlated with community assembly and resiliency of microbes in the developing preterm gut. Specifically, proteins related to antibiotic resistance and metal homeostasis mechanisms were predominant in persisting members in the infant gut environment over the first several weeks of life. Overall, this metaproteomics study provides a unique approach to examine the temporal expansion and resilience of microbial colonization, as it allows simultaneous examination of both host and microbial metabolic activities. Understanding the interplay between host and microbes may elucidate the microbiome’s potential immunomodulatory roles relevant to necrotizing enterocolitis and other dysbiotic conditions in preterm infants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Targeted metagenomic assessment reflects critical colonization in battlefield injuries

Current diagnostics and clinical management strategies for combat wounds are based on decisions made by expert clinicians. However, even in the hands of experienced surgeons, wounds from combat injuries can exhibit failed healing and complications related to limitations in the rapid and comprehensive generation of diagnostic information. Previous studies have demonstrated the possible use of genomic sequencing approaches to detect microbial signatures involved in combat casualty care. While effective, whole metagenome sequencing is limited by the depth required to confidently detect all relevant signatures. To address this, we developed a targeted capture sequencing panel to detect microbial signatures relevant to wound healing. These targets include known microbial nosocomial pathogens, wound colonizers, and genes involved in virulence and antimicrobial resistance. A bioinformatics pipeline was built to identify genomic regions of interest and over 8,000 oligonucleotide probes were designed for capture. The panel was synthesized and validated using control reference genomes in human background and on wound-effluent samples from a cohort of combat-injured U.S. service members. Our panel was sensitive against wound-colonizing species, Acinetobacter baumannii and Pseudomonas aeruginosa, and was specific in detecting corresponding virulence and antimicrobial-resistance genes as well as other pathogenic species present in microflora mixtures. Random forest feature permutation confirmed the prevalence of Acinetobacter and Pseudomonas in critically colonized wounds and wounds that failed to heal, respectively. Our results demonstrate the capability of targeted sequencing tools and analysis platforms to profile and deliver information on pathogenic factors influencing wound progression, thereby guiding therapeutic intervention.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Structural and biochemical analysis of the metallo-β-lactamase L1 from emerging pathogen Stenotrophomonas maltophilia revealed the subtle but distinct di-metal scaffold for catalytic activity

Emergence of Enterobacteriaceae harboring metallo-beta-lactamases (MBL) has raised global threats due to their broad antibiotic resistance profiles and the lack of effective inhibitors against them. We have been studied one of the emerging environmental MBL, the L1 from Stenotrophomonas maltophilia K279a . We determined several crystal structures of L1 complexes with three different classes of beta-lactam antibiotics (penicillin G, moxalactam, meropenem, and imipenem), with the inhibitor captopril and different metal ions (Zn +2 , Cd +2 , and Cu +2 ). All hydrolyzed antibiotics and the inhibitor were found binding to two Zn +2 ions mainly through the opened lactam ring and some hydrophobic interactions with the binding pocket atoms. Without a metal ion, the active site is very similarly maintained as that of the native form with two Zn +2 ions, however, the protein does not bind the substrate moxalactam. When two Zn +2 ions were replaced with other metal ions, the same di-metal scaffold was maintained and the added moxalactam was found hydrolyzed in the active site. Differential scanning fluorimetry and isothermal titration calorimetry were used to study thermodynamic properties of L1 MBL compared with New Deli Metallo-beta-lactamase-1 (NDM-1). Both enzymes are significantly stabilized by Zn +2 and other divalent metals but showed different dependency. These studies also suggest that moxalactam and its hydrolyzed form may bind and dissociate with different kinetic modes with or without Zn +2 for each of L1 and NDM-1. Our analysis implicates metal ions, in forming a distinct di-metal scaffold, which is central to the enzyme stability, promiscuous substrate binding and versatile catalytic activity. Statement: The L1 metallo-beta-lactamase from an environmental multidrug-resistant opportunistic pathogen Stenotrophomonas maltophilia K279a has been studied by determining 3D structures of L1 enzyme in the complexes with several beta-lactam antibiotics and different divalent metals and characterizing its biochemical and ligand binding properties. We found that the two-metal center in the active site is critical in the enzymatic process including antibiotics recognition and binding, which explains the enzyme's activity toward diverse antibiotic substrates. This study provides the critical information for understanding the ligand recognition and for advanced drug development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Antibiotic Resistance in Plastisphere

Microbial life on plastic debris, called plastisphere, has invoked special attention on aquatic ecosystems as emerging habitats for antibiotic resistance genes (ARGs) and antibiotic-resistant bacteria (ARB). There is scarce information concerning how properties of plastics influence ARGs and ARB, the effect of biofilms on enrichment of ARGs and ARB, and, especially, the influence of plastic transformation on ARGs and ARB. Limited research has shown that microplastic (MP) surfaces influence proliferation of antibiotic resistance (AR), aged MPs exhibit increased toxicity due to more adsorption-desorption of AR, and MP transformation is correlated with disseminating AR. Prevention measures of AR include minimizing MP releasing into aquatic environments and sewage treatment plants. The future research should aim to identify the interface mechanisms of transformed MNPs and antibiotics alone, or mixed with other contaminants, property changes of MNPs, and associated toxicity evaluation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

PlasmidHostFinder: Prediction of Plasmid Hosts Using Random Forest

Plasmids play a major role facilitating the spread of antimicrobial resistance between bacteria. Understanding the host range and dissemination trajectories of plasmids is critical for surveillance and prevention of antimicrobial resistance. Identification of plasmid host ranges could be improved using automated pattern detection methods compared to homology-based methods due to the diversity and genetic plasticity of plasmids. In this study, we developed a method for predicting the host range of plasmids using machine learning—specifically, random forests. We trained the models with 8,519 plasmids from 359 different bacterial species per taxonomic level; the models achieved Matthews correlation coefficients of 0.662 and 0.867 at the species and order levels, respectively. Our results suggest that despite the diverse nature and genetic plasticity of plasmids, our random forest model can accurately distinguish between plasmid hosts. This tool is available online through the Center for Genomic Epidemiology (https://cge.cbs.dtu.dk/services/PlasmidHostFinder/).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Genome-wide fitness profiling reveals molecular mechanisms that bacteria use to interact with Trichoderma atroviride exometabolites

Trichoderma spp. are ubiquitous rhizosphere fungi capable of producing several classes of secondary metabolites that can modify the dynamics of the plant-associated microbiome. However, the bacterial-fungal mechanisms that mediate these interactions have not been fully characterized. Here, a random barcode transposon-site sequencing (RB-TnSeq) approach was employed to identify bacterial genes important for fitness in the presence of Trichoderma atroviride exudates. We selected three rhizosphere bacteria with RB-TnSeq mutant libraries that can promote plant growth: the nitrogen fixers Klebsiella michiganensis M5aI and Herbaspirillum seropedicae SmR1, and Pseudomonas simiae WCS417. As a non-rhizosphere species, Pseudomonas putida KT2440 was also included. From the RB-TnSeq data, nitrogen-fixing bacteria competed mainly for iron and required the siderophore transport system TonB/ExbB for optimal fitness in the presence of T . atroviride exudates. In contrast, P . simiae and P . putida were highly dependent on mechanisms associated with membrane lipid modification that are required for resistance to cationic antimicrobial peptides (CAMPs). A mutant in the Hog1-MAP kinase (Δ tmk 3) gene of T . atroviride showed altered expression patterns of many nonribosomal peptide synthetase (NRPS) biosynthetic gene clusters with potential antibiotic activity. In contrast to exudates from wild-type T . atroviride , bacterial mutants containing lesions in genes associated with resistance to antibiotics did not show fitness defects when RB-TnSeq libraries were exposed to exudates from the Δ tmk3 mutant. Unexpectedly, exudates from wild-type T . atroviride and the Δ tmk 3 mutant rescued purine auxotrophic mutants of H . seropedicae , K . michiganensis and P . simiae . Metabolomic analysis on exudates from wild-type T . atroviride and the Δ tmk 3 mutant showed that both strains excrete purines and complex metabolites; functional Tmk3 is required to produce some of these metabolites. This study highlights the complex interplay between Trichoderma -metabolites and soil bacteria, revealing both beneficial and antagonistic effects, and underscoring the intricate and multifaceted nature of this relationship.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A unique class of Zn 2+ -binding serine-based PBPs underlies cephalosporin resistance and sporogenesis in Clostridioides difficile

Treatment with β-lactam antibiotics, particularly cephalosporins, is a major risk factor for Clostridioides difficile infection. These broad-spectrum antibiotics irreversibly inhibit penicillin-binding proteins (PBPs), which are serine-based enzymes that assemble the bacterial cell wall. However, C. difficile has four different PBPs (PBP1-3 and SpoVD) with various roles in growth and spore formation, and their specific links to β-lactam resistance in this pathogen are underexplored. Here, we show that PBP2 (known to be essential for vegetative growth) is the primary bactericidal target for β-lactams in C. difficile. PBP2 is insensitive to cephalosporin inhibition, and this appears to be the main basis for cephalosporin resistance in this organism. We determine crystal structures of C. difficile PBP2, alone and in complex with β-lactams, revealing unique features including ligand-induced conformational changes and an active site Zn 2+ -binding motif that influences β-lactam binding and protein stability. The Zn 2+ -binding motif is also present in C. difficile PBP3 and SpoVD (which are known to be essential for sporulation), as well as in other bacterial taxa including species living in extreme environments and the human gut. We speculate that this thiol-containing motif and its cognate Zn 2+ might function as a redox sensor to regulate cell wall synthesis for survival in adverse or anaerobic environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The effect of enrofloxacin on enteric Escherichia coli : Fitting a mathematical model to in vivo data

Antimicrobial drugs administered systemically may cause the emergence and dissemination of antimicrobial resistance among enteric bacteria. To develop logical, research-based recommendations for food animal veterinarians, we must understand how to maximize antimicrobial drug efficacy while minimizing risk of antimicrobial resistance. Our objective is to evaluate the effect of two approved dosing regimens of enrofloxacin (a single high dose or three low doses) on Escherichia coli in cattle. We look specifically at bacteria above and below the epidemiological cutoff (ECOFF), above which the bacteria are likely to have an acquired or mutational resistance to enrofloxacin. We developed a differential equation model for the antimicrobial drug concentrations in plasma and colon, and bacteria populations in the feces. The model was fit to animal data of drug concentrations in the plasma and colon obtained using ultrafiltration probes. Fecal E. coli counts and minimum inhibitory concentrations were measured for the week after receiving the antimicrobial drug. We predict that the antimicrobial susceptibility of the bacteria above the ECOFF pre-treatment strongly affects the composition of the bacteria following treatment. Faster removal of the antimicrobial drugs from the colon throughout the study leads to improved clearance of bacteria above the ECOFF in the low dose regimen. If we assume a fitness cost is associated with bacteria above the ECOFF, the increased fitness costs leads to reduction of bacteria above the ECOFF in the low dose study. These results suggest the initial E. coli susceptibility is a strong indicator of how steers respond to antimicrobial drug treatment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Structures of ISCth4 transpososomes reveal the role of asymmetry in copy-out/paste-in DNA transposition

Copy-out/paste-in transposition is a major bacterial DNA mobility pathway. It contributes significantly to the emergence of antibiotic resistance, often by upregulating expression of downstream genes upon integration. Unlike other transposition pathways, it requires both asymmetric and symmetric strand transfer steps. Here, we report the first structural study of a copy-out/paste-in transposase and demonstrate its ability to catalyze all pathway steps in vitro. X-ray structures of ISCth4 transposase, a member of the IS256 family of insertion sequences, bound to DNA substrates corresponding to three sequential steps in the reaction reveal an unusual asymmetric dimeric transpososome. During transposition, an array of N-terminal domains binds a single transposon end while the catalytic domain moves to accommodate the varying substrates. These conformational changes control the path of DNA flanking the transposon end and the generation of DNA-binding sites. Our results explain the asymmetric outcome of the initial strand transfer and show how DNA binding is modulated by the asymmetric transposase to allow the capture of a second transposon end and to integrate a circular intermediate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Conformational restriction shapes the inhibition of a multidrug efflux adaptor protein

Abstract Membrane efflux pumps play a major role in bacterial multidrug resistance. The tripartite multidrug efflux pump system from Escherichia coli , AcrAB-TolC, is a target for inhibition to lessen resistance development and restore antibiotic efficacy, with homologs in other ESKAPE pathogens. Here, we rationalize a mechanism of inhibition against the periplasmic adaptor protein, AcrA, using a combination of hydrogen/deuterium exchange mass spectrometry, cellular efflux assays, and molecular dynamics simulations. We define the structural dynamics of AcrA and find that an inhibitor can inflict long-range stabilisation across all four of its domains, whereas an interacting efflux substrate has minimal effect. Our results support a model where an inhibitor forms a molecular wedge within a cleft between the lipoyl and αβ barrel domains of AcrA, diminishing its conformational transmission of drug-evoked signals from AcrB to TolC. This work provides molecular insights into multidrug adaptor protein function which could be valuable for developing antimicrobial therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy

Tuberculosis (TB) is the world’s deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism Mycobacterium tuberculosis (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen’s antibiotic susceptibility. Both rapid identification and rapid antibiotic susceptibility testing of Mtb are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the Mtb complex strain Bacillus Calmette-Guérin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin, and amikacin, as well as a pan-susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and on patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all five BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5,000. We show how this instrument and our machine learning model enable combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Classification of bacterial plasmid and chromosome derived sequences using machine learning

Plasmids are important genetic elements that facilitate horizonal gene transfer between bacteria and contribute to the spread of virulence and antimicrobial resistance. Most bacterial genome sequences in the public archives exist in draft form with many contigs, making it difficult to determine if a contig is of chromosomal or plasmid origin. Using a training set of contigs comprising 10,584 chromosomes and 10,654 plasmids from the PATRIC database, we evaluated several machine learning models including random forest, logistic regression, XGBoost, and a neural network for their ability to classify chromosomal and plasmid sequences using nucleotide k-mers as features. Based on the methods tested, a neural network model that used nucleotide 6-mers as features that was trained on randomly selected chromosomal and plasmid subsequences 5kb in length achieved the best performance, outperforming existing out-of-the-box methods, with an average accuracy of 89.38% ± 2.16% over a 10-fold cross validation. The model accuracy can be improved to 92.08% by using a voting strategy when classifying holdout sequences. In both plasmids and chromosomes, subsequences encoding functions involved in horizontal gene transfer—including hypothetical proteins, transporters, phage, mobile elements, and CRISPR elements—were most likely to be misclassified by the model. This study provides a straightforward approach for identifying plasmid-encoding sequences in short read assemblies without the need for sequence alignment-based tools.

59 BASIC BIOLOGICAL SCIENCES↗