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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

30S subunit recognition and G1405 modification by the aminoglycoside-resistance 16S ribosomal RNA methyltransferase RmtC

Acquired ribosomal RNA (rRNA) methylation has emerged as a significant mechanism of aminoglycoside resistance in pathogenic bacterial infections. Modification of a single nucleotide in the ribosome decoding center by the aminoglycoside-resistance 16S rRNA (m 7 G1405) methyltransferases effectively blocks the action of all 4,6-deoxystreptamine ring-containing aminoglycosides, including the latest generation of drugs. To define the molecular basis of 30S subunit recognition and G1405 modification by these enzymes, we used a S-adenosyl-L-methionine analog to trap the complex in a postcatalytic state to enable determination of a global 3.0 Å cryo-electron microscopy structure of the m 7 G1405 methyltransferase RmtC bound to the mature Escherichia coli 30S ribosomal subunit. This structure, together with functional analyses of RmtC variants, identifies the RmtC N-terminal domain as critical for recognition and docking of the enzyme on a conserved 16S rRNA tertiary surface adjacent to G1405 in 16S rRNA helix 44 (h44). To access the G1405 N7 position for modification, a collection of residues across one surface of RmtC, including a loop that undergoes a disorder-to order transition upon 30S subunit binding, induces significant distortion of h44. This distortion flips G1405 into the enzyme active site where it is positioned for modification by two almost universally conserved RmtC residues. Further, these studies expand our understanding of ribosome recognition by rRNA modification enzymes and present a more complete structural basis for future development of strategies to inhibit m 7 G1405 modification to resensitize bacterial pathogens to aminoglycosides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Computationally designed peptide macrocycle inhibitors of New Delhi metallo-β-lactamase 1

The rise of antibiotic resistance calls for new therapeutics targeting resistance factors such as the New Delhi metallo-β-lactamase 1 (NDM-1), a bacterial enzyme that degrades β-lactam antibiotics. We present structure-guided computational methods for designing peptide macrocycles built from mixtures of l - and d -amino acids that are able to bind to and inhibit targets of therapeutic interest. Our methods explicitly consider the propensity of a peptide to favor a binding-competent conformation, which we found to predict rank order of experimentally observed IC 50 values across seven designed NDM-1- inhibiting peptides. We were able to determine X-ray crystal structures of three of the designed inhibitors in complex with NDM-1, and in all three the conformation of the peptide is very close to the computationally designed model. In two of the three structures, the binding mode with NDM-1 is also very similar to the design model, while in the third, we observed an alternative binding mode likely arising from internal symmetry in the shape of the design combined with flexibility of the target. Although challenges remain in robustly predicting target backbone changes, binding mode, and the effects of mutations on binding affinity, our methods for designing ordered, binding-competent macrocycles should have broad applicability to a wide range of therapeutic targets.

42 ENGINEERING↗
DOE OSTI2020

Predicting antimicrobial susceptibility from the bacterial genome: A new paradigm for one health resistance monitoring

The laboratory identification of antibacterial resistance is a cornerstone of infectious disease medicine. In vitro antimicrobial susceptibility testing has long been based on the growth response of organisms in pure culture to a defined concentration of antimicrobial agents. By comparing individual isolates to wild type susceptibility patterns, strains with acquired resistance can be identified. Acquired resistance can also be detected genetically. After many decades of research, the inventory of genes underlying antimicrobial resistance (AMR) is well known for several pathogenic genera including zoonotic enteric organisms such as Salmonella and Campylobacter and continues to grow substantially for others. With the decline in costs for large scale DNA sequencing, it is now practicable to characterize bacteria using whole genome sequencing (WGS), including the carriage of resistance genes in individual microorganisms and those present in complex biological samples. With genomics we can generate comprehensive, detailed information on the bacterium, the mechanisms of antibiotic resistance, clues to its source, and the nature of mobile DNA elements by which resistance spreads. These developments point to a new paradigm for antimicrobial resistance detection and tracking for both clinical and public health purposes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Time-resolved β-lactam cleavage by L1 metallo-β-lactamase

Abstract Serial x-ray crystallography can uncover binding events, and subsequent chemical conversions occurring during enzymatic reaction. Here, we reveal the structure, binding and cleavage of moxalactam antibiotic bound to L1 metallo-β-lactamase (MBL) from Stenotrophomonas maltophilia . Using time-resolved serial synchrotron crystallography, we show the time course of β-lactam hydrolysis and determine ten snapshots (20, 40, 60, 80, 100, 150, 300, 500, 2000 and 4000 ms) at 2.20 Å resolution. The reaction is initiated by laser pulse releasing Zn 2+ ions from a UV-labile photocage. Two metal ions bind to the active site, followed by binding of moxalactam and the intact β-lactam ring is observed for 100 ms after photolysis. Cleavage of β-lactam is detected at 150 ms and the ligand is significantly displaced. The reaction product adjusts its conformation reaching steady state at 2000 ms corresponding to the relaxed state of the enzyme. Only small changes are observed in the positions of Zn 2+ ions and the active site residues. Mechanistic details captured here can be generalized to other MBLs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Deep mutational scanning reveals the molecular determinants of RNA polymerase-mediated adaptation and tradeoffs

RNA polymerase (RNAP) is emblematic of complex biological systems that control multiple traits involving trade-offs such as growth versus maintenance. Laboratory evolution has revealed that mutations in RNAP subunits, including RpoB, are frequently selected. However, we lack a systems view of how mutations alter the RNAP molecular functions to promote adaptation. We, therefore, measured the fitness of thousands of mutations within a region of rpoB under multiple conditions and genetic backgrounds, to find that adaptive mutations cluster in two modules. Mutations in one module favor growth over maintenance through a partial loss of an interaction associated with faster elongation. Mutations in the other favor maintenance over growth through a destabilized RNAP-DNA complex. The two molecular handles capture the versatile RNAP-mediated adaptations. Combining both interaction losses simultaneously improved maintenance and growth, challenging the idea that growth-maintenance tradeoff resorts only from limited resources, and revealing how compensatory evolution operates within RNAP.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Regional Differences in the Structure of Juglans nigra Phytobiome Reflect Geographical Differences in Thousand Cankers Disease Severity

Thousand cankers disease threatens Juglans nigra (Eastern Black Walnut) in urban and natural landscapes. Incidence and severity of thousand cankers disease is higher in the host’s introduced range in the western United States. We hypothesized that these differences are driven partly by geographical variation in the host phytobiome due to its roles in host stress tolerance, nutrient acquisition, and defense. To evaluate the role of the phytobiome in mediating thousand cankers disease, we characterized the J. nigra phytobiome of diseased and healthy trees in portions of its native (Indiana and Tennessee) and introduced (Washington) ranges. Grafted clones present in each state and open-pollinated populations were sampled. DNA was extracted from soil and branch (caulosphere) tissues and internal transcribed spacer and 16s regions were sequenced for characterization of fungal and bacterial communities. We found that microbial communities in the caulosphere and soil differ between native and introduced ranges of J. nigra and harbor different mutualistic and pathogenic microorganisms. Additionally, caulosphere microbial communities were more species rich and diverse in the native range of J. nigra, suggesting greater levels of functional redundancy and multifunctionality in the native-range phytobiome compared with the introduced range. We also found higher network complexity in the caulosphere of trees in the introduced range and evidence for two alternative stable community states associated with diseased and healthy trees. Our results provide support for the hypothesis that geographical variation in thousand cankers disease incidence and severity is partially driven by differences in the phytobiome of J. nigra in its introduced and native ranges.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Ecogenomics of Groundwater Phages Suggests Niche Differentiation Linked to Specific Environmental Tolerance

To our knowledge, this is the first study to identify the bacteriophage distribution in a groundwater ecosystem shedding light on their prevalence and distribution across metal-contaminated and background sites. Our study is uniquely based on selective sequencing of solely the extrachromosomal elements of a microbiome followed by analysis for viral signatures, thus establishing a more focused approach for phage identifications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Effect of biochanin A on the rumen microbial community of Holstein steers consuming a high fiber diet and subjected to a subacute acidosis challenge

Subacute rumen acidosis (SARA) occurs when highly fermentable carbohydrates are introduced into the diet, decreasing pH and disturbing the microbial ecology of the rumen. Rumen amylolytic bacteria rapidly catabolize starch, fermentation acids accumulate in the rumen and reduce environmental pH. Historically, antibiotics ( e . g ., monensin, MON) have been used in the prevention and treatment of SARA. Biochanin A (BCA), an isoflavone produced by red clover ( Trifolium pratense ), mitigates changes associated with starch fermentation ex vivo . The objective of the study was to determine the effect of BCA on amylolytic bacteria and rumen pH during a SARA challenge. Twelve rumen fistulated steers were assigned to 1 of 4 treatments: HF CON (high fiber control), SARA CON, MON (200 mg d -1 ), or BCA (6 g d -1 ). The basal diet consisted of corn silage and dried distiller’s grains ad libitum . The study consisted of a 2-wk adaptation, a 1-wk HF period, and an 8-d SARA challenge (d 1–4: 40% corn; d 5–8: 70% cracked corn). Samples for pH and enumeration were taken on the last day of each period (4 h). Amylolytic, cellulolytic, and amino acid/peptide-fermenting bacteria (APB) were enumerated. Enumeration data were normalized by log transformation and data were analyzed by repeated measures ANOVA using the MIXED procedure of SAS. The SARA challenge increased total amylolytics and APB, but decreased pH, cellulolytics, and in situ DMD of hay (P < 0.05). BCA treatment counteracted the pH, microbiological, and fermentative changes associated with SARA challenge (P < 0.05). Similar results were also observed with MON (P < 0.05). These results indicate that BCA may be an effective alternative to antibiotics for mitigating SARA in cattle production systems.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2005

The Influence of Ecological Isolation on the Structural and Functional Stability of Complex Microbial Communities

To help understand how the behavior of microorganisms and microbial communities in insular space habitats may differ from the behavior of these groups on Earth, long-term incubations (100+ days) were conducting using wastewater bioreactors (batch fed) designed to mimic "closed" and "open" ecological systems. The issue of immigration was considered, and the goal of the research was to determine whether the stability of microbial communities in space is reduced due to their prolonged isolation. Bioreactors were established by inoculating flasks of sterile synthetic wastewater with the microbial community obtained from a local treatment facility; each day, one-third of the medium in the flask was replaced with an equal volume of sterile artificial wastewater. Flasks were divided into two treatments: "closed" and "open" to recruitment of additional microorganisms. "Closed" flasks were maintained as described above, while the medium used to feed the "open" flasks was supplemented daily with a small amount of raw sewage (which provided a continuous source of new potential community members). Significant differences in microbial community structure and function developed in the two sets of communities, and the results suggest that the open community was more stable and better able to adjust to changing environmental conditions. Each community's resistance to environmental (temperature fluctuations) and biological stresses (starvation and invasion by an opportunistic pathogen Pseudomonas aeruginosa) was monitored. Experiments were also conducted to determine whether the effect of isolation changes depending on the microbial communities' initial diversity or composition; communities with a low(er) initial diversity were less stable. Overall, the results indicate that isolation will be an important factor influencing the activity of microbial communities on board spacecraft. A possible way of mitigating these effects would be to include communities with high initial diversity or to periodically re-inoculate the systems using diverse inocula transported from Earth.

Franklin, R. B.↗
DOE OSTI2021

Predicting Antimicrobial Resistance Using Partial Genome Alignments

Antimicrobial resistance (AMR) is an important global health threat that impacts millions of people worldwide each year. Developing methods that can detect and predict AMR phenotypes can help to mitigate the spread of AMR by informing clinical decision making and appropriate mitigation strategies. Many bioinformatic methods have been developed for predicting AMR phenotypes from whole-genome sequences and AMR genes, but recent studies have indicated that predictions can be made from incomplete genome sequence data. In order to more systematically understand this, we built random forest-based machine learning classifiers for predicting susceptible and resistant phenotypes for Klebsiella pneumoniae (1,640 strains), Mycobacterium tuberculosis (2,497 strains), and Salmonella enterica (1,981 strains). We started by building models from alignments that were based on a reference chromosome for each species. We then subsampled each chromosomal alignment and built models for the resulting subalignments, finding that very small regions, representing approximately 0.1 to 0.2% of the chromosome, are predictive. In K. pneumoniae, M. tuberculosis, and S. enterica, the subalignments are able to predict multiple AMR phenotypes with at least 70% accuracy, even though most do not encode an AMR-related function. We used these models to identify regions of the chromosome with high and low predictive signals. Finally, subalignments that retain high accuracy across larger phylogenetic distances were examined in greater detail, revealing genes and intergenic regions with potential links to AMR, virulence, transport, and survival under stress conditions. IMPORTANCE Antimicrobial resistance causes thousands of deaths annually worldwide. Understanding the regions of the genome that are involved in antimicrobial resistance is important for developing mitigation strategies and preventing transmission. Machine learning models are capable of predicting antimicrobial resistance phenotypes from bacterial genome sequence data by identifying resistance genes, mutations, and other correlated features. They are also capable of implicating regions of the genome that have not been previously characterized as being involved in resistance. In this study, we generated global chromosomal alignments for Klebsiella pneumoniae, Mycobacterium tuberculosis, and Salmonella enterica and systematically searched them for small conserved regions of the genome that enable the prediction of antimicrobial resistance phenotypes. In addition to known antimicrobial resistance genes, this analysis identified genes involved in virulence and transport functions, as well as many genes with no previous implication in antimicrobial resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Understanding the dynamics of vacuole trafficking and secretion for enhanced plant storage reserves

Vacuoles are essential in plants and serve roles in both protein and organelle degradation for reutilization and storage of high energy molecules such as storage proteins which are critical for seed germination under normal and stress conditions and impact biomass production and nutrition. In addition, plants secrete many different molecules such as cell wall components, lipids, waxes and others that are important for plant protection, structure and biomass. Vacuole accumulation and secretion are closely linked and highly regulated pathways within the endomembrane trafficking network. We have discovered many drug-like synthetic small molecules that can suppress vacuole trafficking and enhance secretion; other chemicals can enhance vacuole trafficking and suppress secretion. The ability of our compounds to modulate these pathways indicates that these pathways are tightly coupled and highly regulated. Thus, to achieve the goals of enhanced energy reserves or enhanced secretion it is essential to understand how this dynamic is controlled. Bioactive chemicals have provided us unique insight into natural mechanisms controlling the dynamics of vacuole trafficking and secretion that was not possible previously. One such compound, ES2, negatively modulates secretion while enhancing vacuole trafficking. This is the first compound discovered that targets an essential secretory complex known as the exocyst and will reveal important regulatory domains controlling secretion and vacuole trafficking. During the current funding period, we determined the structure of the EXO70A1 in plants and identifying its binding site. To understand the dynamics of vacuole trafficking it is key to have compounds that inhibit vacuole trafficking as well as enhancing it (ES2). We have used sophisticated image analysis to identify another novel compound ES17 that enhances secretion while negatively modulating vacuole trafficking (opposite of ES2). We have already made rapid progress. Our preliminary data indicates that ES17 very specifically targets a late stage of vesicle fusion with the tonoplast which is highly regulated. Thus, ES17 is an ideal compound to dissect the regulation of vacuole targeting dynamics. In addition, we have now synthesized a biotinylated version of ES17 that is fully functional, permitting the use of chemical proteomics to identify the cognate target with a high probability of success. We propose to investigate the ES17 target which can negatively modulate vacuole trafficking and combine this with knowledge of the ES2 target which can promote vacuole trafficking. Dissecting the mechanisms controlling the dynamics of secretion vs vacuole accumulation and the use of synthetic modulators will permit us to understand and regulate trafficking to enhance secretion to the plasma membrane and cell wall or the accumulation of biological energy reserves for increased biomass, nutritional value, stress resistance, and the secretion of specialized plant products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

How to Evaluate Non-Growing Cells—Current Strategies for Determining Antimicrobial Resistance of VBNC Bacteria

Thanks to the achievements in sanitation, hygiene practices, and antibiotics, we have considerably improved in our ongoing battle against pathogenic bacteria. However, with our increasing knowledge about the complex bacterial lifestyles and cycles and their plethora of defense mechanisms, it is clear that the fight is far from over. One of these resistance mechanisms that has received increasing attention is the ability to enter a dormancy state termed viable but non-culturable (VBNC). Bacteria that enter the VBNC state, either through unfavorable environmental conditions or through potentially lethal stress, lose their ability to grow on standard enrichment media, but show a drastically increased tolerance against antimicrobials including antibiotics. The inability to utilize traditional culture-based methods represents a considerable experimental hurdle to investigate their increased antimicrobial resistance and impedes the development and evaluation of effective treatments or interventions against bacteria in the VBNC state. Although experimental approaches were developed to detect and quantify VBNCs, only a few have been utilized for antimicrobial resistance screening and this review aims to provide an overview of possible methodological approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural insights into the mechanism of overcoming Erm-mediated resistance by macrolides acting together with hygromycin-A

The ever-growing rise of antibiotic resistance among bacterial pathogens is one of the top healthcare threats today. Although combination antibiotic therapies represent a potential approach to more efficiently combat infections caused by susceptible and drug-resistant bacteria, only a few known drug pairs exhibit synergy/cooperativity in killing bacteria. Here, we discover that well-known ribosomal antibiotics, hygromycin A (HygA) and macrolides, which target peptidyl transferase center and peptide exit tunnel, respectively, can act cooperatively against susceptible and drug-resistant bacteria. Remarkably, HygA slows down macrolide dissociation from the ribosome by 60-fold and enhances the otherwise weak antimicrobial activity of the newest-generation macrolide drugs known as ketolides against macrolide-resistant bacteria. By determining a set of high-resolution X-ray crystal structures of drug-sensitive wild-type and macrolide-resistant Erm-methylated 70S ribosomes in complex with three HygA-macrolide pairs, we provide a structural rationale for the binding cooperativity of these drugs and also uncover the molecular mechanism of overcoming Erm-type resistance by macrolides acting together with hygromycin A. Altogether our structural, biochemical, and microbiological findings lay the foundation for the subsequent development of synergistic antibiotic tandems with improved bactericidal properties against drug-resistant pathogens, including those expressing erm genes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Increasing accessibility to deep learning-based analytics for space biology: pretrained models, transfer learning, and analytics platform development

Biological systems react in complex ways to the stressors of spaceflight, and the data capturing these relationships is concomitantly high-dimensional and complex. Deep learning and machine learning approaches are increasingly popular as an analytical approach for space biosciences, due to their ability to model complex relationships in complex data. However, such approaches often require large datasets and extensive computational resources. New approaches that minimize data sizes and computational power needed to leverage machine learning, and resources that make these approaches accessible, are needed to increase accessibility and adoption of machine learning in the space biosciences. Transfer learning, in which a pretrained model of broad utility is trained on a large dataset, and subsequently reused on downstream applications for which data is more limited, is one approach to minimizing data and computational intensity of deep learning applications. This transfer learning approach results in more performant models in high-dimensional, low-sample-size settings such as space biology, as compared to training models on limited data from scratch. This presentation will outline efforts to generate pretrained models for the space biology community, and highlight transfer learning applications modeling microbial antibiotic resistance during spaceflight. Finally, in order to increase accessibility of these models and tools, as well as others, for the broader space biology community, we present a modeling and analysis platform facilitating machine learning applications in space biology. This platform streamlines machine learning training and analysis in a notebook format, facilitates download and use of space biology data from the NASA GeneLab database, and can be utilized on NASA-hosted servers or downloaded and hosted locally. This effort, as part of the AI4LS (Artificial Intelligence for Life in Space) working group, will increase accessibility, feasibility, and performance of machine learning approaches for the space biology community.

Adrienne Hoarfrost↗