SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Specific and broad-spectrum inhibitory peptides to CRISPR Cas9 variants (SpyCas9, SauCas9, and CjeCas9) are disclosed. A method of making and using these peptides with therapeutic CRISPR Cas9 (to improve desired targeting) or against harmful CRISPR Cas9 components (already active in a patient) is also disclosed. The peptides combined with a delivery system is also disclosed.
Drug discovery is a complex, costly process with high failure rates. A successful drug should bind to a target, be deliverable to an intended site of activity, and promote a desired pharmacological effect without causing toxicity. Typically, these factors are evaluated in series over the course of a pipeline where the number of candidates is sequentially whittled down from a very large initial pool. One promise of AI-driven discovery is the opportunity to evaluate multiple facets of drug performance in parallel. However, despite ML-driven advancements, current models for pharmacological property prediction are exclusively trained to predict molecular properties, ignoring important, dynamic biodistribution and bioactivity effects. Here, we present our progress towards incorporating quantitative systems physiology models into an AI-enabled drug design and molecular generation pipeline. Within a genetic algorithm, we include human-relevant physiologically based pharmacokinetic (PBPK) models. These PBPK models leverage properties that are predicted by a fine-tuned molecular language model. Together, these models will aid in capturing the mapping between molecules and therapeutic outcomes that is necessary to accelerate the drug discovery process.
Copper-67 is a radioisotope of interest for medical imaging and therapy as well as for under- standing stellar and interstellar evolution pertaining to the formation of proton-rich nuclei. Since 67 Cu decays 100% to 67 Zinc, understanding this reaction can shed light on the abundance of this and other p-nuclei elements in the universe. Here, the photonuclear production of 67 Cu from 71 Ga and natural gallium is examined as an alternative to its photoproduction from zinc. Two research and development production runs were performed at Thomas Jefferson National Accelerator Facility using an electron linac. During the first run, an 805-W, 30.9-MeV beam was used to irradiate a 1-mm tungsten radiator to create a bremsstrahlung flux. The resulting gamma photons irradiated 50.9 g of natural gallium encased in a graphite crucible for 24.2 h; 7.02 Bq/W∙s∙kg of 67 Cu activity was produced. During the second run, a 4380-W, 31.5-MeV beam was used for 12.0 h on the same target containing 60 g of natural gallium; 6.41 Bq/W∙s∙kg of 67 Cu activity was produced. Because of the difficulties in spectroscopically differentiating 67 Cu from 67 Ga, prior to each run, an isotopically pure 71 Ga disk was irradiated using a 100-W beam for 1 h, at the same respective energies. Finally, these baseline irradiations allowed for separation of 67 Cu from 67 Ga in the spectroscopic measurements of the natural gallium targets.
The long interspersed element-1 (LINE-1, hereafter L1) retrotransposon has generated nearly one-third of the human genome and serves as an active source of genetic diversity and human disease. L1 spreads through a mechanism termed target-primed reverse transcription, in which the encoded enzyme (ORF2p) nicks the target DNA to prime reverse transcription of its own or non-self RNAs. Here we purified full-length L1 ORF2p and biochemically reconstituted robust target-primed reverse transcription with template RNA and target-site DNA. We report cryo-electron microscopy structures of the complete human L1 ORF2p bound to structured template RNAs and initiating cDNA synthesis. The template polyadenosine tract is recognized in a sequence-specific manner by five distinct domains. Among them, an RNA-binding domain bends the template backbone to allow engagement of an RNA hairpin stem with the L1 ORF2p C-terminal segment. Moreover, structure and biochemical reconstitutions demonstrate an unexpected target-site requirement: L1 ORF2p relies on upstream single-stranded DNA to position the adjacent duplex in the endonuclease active site for nicking of the longer DNA strand, with a single nick generating a staggered DNA break. Our research provides insights into the mechanism of ongoing transposition in the human genome and informs the engineering of retrotransposon proteins for gene therapy.
High traffic touch surfaces such as doorknobs, countertops, and handrails can be transmission points for the spread of pathogens, emphasizing the need to develop materials that actively self-sanitize. Metals are frequently used for these surfaces due to their durability, but many metals also possess antimicrobial properties which function through a variety of mechanisms. This work investigates metallic alloys comprised of several metals which individually possess antimicrobial properties, with the target of achieving broad-spectrum, rapid sanitation through synergistic activity. An entropy-motivated stabilization paradigm is proposed to prepare scalable alloys of copper, silver, nickel and cobalt. Using combinatorial sputtering, thin-film alloys were prepared on 100 mm wafers with ≈50% compositional grading of each element across the wafer. The films were then annealed and investigated for alloy stability. Antimicrobial activity testing was performed on both the as-grown alloys and the annealed films using four microorganisms—Phi6, MS2, Bacillus subtilis and Escherichia coli —as surrogates for human viral and bacterial pathogens. Testing showed that after 30 s of contact with some of the test alloys, Phi6, an enveloped, single-stranded RNA bacteriophage that serves as a SARS-CoV-2 surrogate, was reduced up to 6.9 orders of magnitude (> 99.9999%). Additionally, the non-enveloped, double-stranded DNA bacteriophage MS2, and the Gram-negative E. coli and Gram-positive B. subtilis bacterial strains showed a 5.0, 6.4, and 5.7 log reduction in activity after 30, 20 and 10 min, respectively. Antimicrobial activity in the alloy samples showed a strong dependence on the composition, with the log reduction scaling directly with the Cu content. Concentration of Cu by phase separation after annealing improved activity in some of the samples. The results motivate a variety of themes which can be leveraged to design ideal antimicrobial surfaces.
The development of chemotherapies against eukaryotic pathogens is especially challenging because of both the evolutionary conservation of drug targets between host and parasite, and the evolution of strain-dependent drug resistance. There is a strong need for new nontoxic drugs with broad-spectrum activity against trypanosome parasites such as Leishmania and Trypanosoma. A relatively untested approach is to target macromolecular interactions in parasites rather than small molecular interactions, under the hypothesis that the features specifying macromolecular interactions diverge more rapidly through coevolution. We computed tRNA Class-Informative Features in humans and independently in eight distinct clades of trypanosomes, identifying parasite-specific informative features, including base pairs and base mis-pairs, that are broadly conserved over approximately 250 million years of trypanosome evolution. Validating these observations, we demonstrated biochemically that tRNA:aminoacyl-tRNA synthetase (aaRS) interactions are a promising target for anti-trypanosomal drug discovery. From a marine natural products extract library, we identified several fractions with inhibitory activity toward Leishmania major alanyl-tRNA synthetase (AlaRS) but no activity against the human homolog. These marine natural products extracts showed cross-reactivity towards Trypanosoma cruzi AlaRS indicating the broad-spectrum potential of our network predictions. We also identified Leishmania major threonyl-tRNA synthetase (ThrRS) inhibitors from the same library. We discuss why chemotherapies targeting multiple aaRSs should be less prone to the evolution of resistance than monotherapeutic or synergistic combination chemotherapies targeting only one aaRS.
The calmodulin-binding transcription activator (CAMTA) proteins of Arabidopsis thaliana play a major role in cold acclimation, contributing to the rapid induction of the C-REPEAT BINDING FACTOR (CBF) genes and other genes that impart freezing tolerance in plants exposed to cold temperature (4°C). The goal of this study was to better understand how the gene induction activity of CAMTA3 is modulated by temperature. Our results indicate that a severely truncated version of CAMTA3, CAMTA3 334 , which includes the N-terminal CG-1 DNA binding domain and a newly identified transcriptional activation domain (TAD), was able to rapidly induce the expression of CBF2 and two newly identified target genes, EXPANSIN-LIKE A1 (EXPL1) and NINE-CIS-EPOXYCAROTENOID DIOXYGENASE 3 (NCED3), in response to cold temperature. Additionally, CAMTA3 334 was able to restore freezing tolerance when expressed in a camta23 double mutant. The ability of CAMTA3 and CAMTA3 334 to induce target genes at cold temperature did not involve increased levels of these proteins or increased binding of these proteins to target gene promoters in cold-treated plants. Rather, domain-swapping experiments indicated that the CAMTA3 CG-1 domain conferred temperature dependence to the ability of the CAMTA3 TAD to induce gene expression. The CG-1 domain also enabled the TAD to induce the expression of target genes at a moderate temperature (22°C) in response to cycloheximide treatment, consistent with the TAD activity not being intrinsically temperature dependent. We propose a working model in which the temperature modulation of CAMTA3 gene induction activity occurs independently from the C-terminal calmodulin-binding domains that previously have been proposed to activate CAMTA3 transcriptional activity in response to cold temperature.
The Department of Energy (DOE) Water Power Technologies Office (WPTO) Triton Initiative works to reduce barriers to permitting of marine energy testing and installation through environmental monitoring research that can help inform decision-makers on potential environmental effects associated with these systems. Communications, outreach, and engagement efforts are critical to Triton's success, which involves facilitating the effective communication and dissemination of environmental monitoring research information and results to end-users and fostering collaborations between researchers and industry partners to address the most pressing needs of this emerging industry. The Triton Initiative's communications, outreach, and engagement (TCOE) foundational goals are to educate and raise awareness of ME and the role of Triton's environmental monitoring research in supporting the industry, build trust with audiences through transparent communications and outreach, and evaluate and refine TCOE tactics based on feedback and metrics. The TCOE FY 2024-specific objectives were to (1) refine and grow Triton's audience network by reaching new individuals and communities within Triton's target audience base, and (2) improve the strategy and evaluation of TCOE efforts to demonstrate the value of communications and outreach for the ME community. This report presents the results and analysis of communications activities from September 1, 2023 through August 31, 2024. We assess the TCOE target audiences, highlight notable successes and lessons learned from FY2024, and identify the most effective channels and activities used to connect with those audiences to achieve the TCOE goals.
Embryonic morphogenesis is strictly dependent on tight spatiotemporal control of developmental gene expression, which is typically achieved through the concerted activity of multiple enhancers driving cell type-specific expression of a target gene. Mammalian genomes are organized in topologically associated domains, providing a preferred environment and framework for interactions between transcriptional enhancers and gene promoters. While epigenomic profiling and three-dimensional chromatin conformation capture have significantly increased the accuracy of identifying enhancers, assessment of subregional enhancer activities via transgenic reporter assays in mice remains the gold standard for assigning enhancer activity in vivo. Once this activity is defined, the ideal method to explore the functional necessity of a transcriptional enhancer and its contribution to target gene dosage and morphological or physiological processes is deletion of the enhancer sequence from the mouse genome. Here we present detailed protocols for efficient introduction of enhancer-reporter transgenes and CRISPR-mediated genomic deletions into the mouse genome, including a step-by-step guide for pronuclear microinjection of fertilized mouse eggs. We provide instructions for the assembly and genomic integration of enhancer-reporter cassettes that have been used for validation of thousands of putative enhancer sequences accessible through the VISTA enhancer browser, including a recently published method for robust site-directed transgenesis at the H11 safe-harbor locus. Together, these methods enable rapid and large-scale assessment of enhancer activities and sequence variants in mice, which is essential to understand mammalian genome function and genetic diseases.
Soluble angiotensin-converting enzyme 2 (ACE2) constitutes an attractive antiviral capable of targeting a wide range of coronaviruses using ACE2 as their receptor. Using structure-guided approaches, we developed a series of bivalent ACE2-Fcs harboring functionally and structurally validated mutations that enhance severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor binding domain recognition by up to ~12-fold and remove angiotensin enzymatic activity. The lead variant M81 potently cross-neutralized SARS-CoV-2 variants of concern (VOCs), including Omicron, at subnanomolar half-maximal inhibitory concentration and was capable of robust Fc-effector functions, including antibody-dependent cellular cytotoxicity, phagocytosis, and complement deposition. When tested in a stringent K18-hACE2 mouse model, Fc-enhanced ACE2-Fc delayed death by 3 to 5 days or effectively resolved lethal SARS-CoV-2 infection in both prophylactic and therapeutic settings via the combined effects of neutralization and Fc-effector functions. These data add to the demonstrated utility of soluble ACE2 as a valuable SARS-CoV-2 antiviral and indicate that Fc-effector functions may constitute an important component of ACE2-Fc therapeutic activity.
Sunitinib resistance creates a major clinical challenge for the treatment of advanced clear cell renal cell carcinoma (ccRCC) and functional and metabolic changes linked to sunitinib resistance are not fully understood. We sought to characterize the molecular and metabolic changes induced by the development of sunitinib resistance in ccRCC by developing and characterizing two human ccRCC cell lines resistant to sunitinib. Consistent with the literature, sunitinib-resistant ccRCC cell lines presented an aberrant overexpression of Axl and PD-L1, as well as a metabolic rewiring characterized by enhanced OXPHOS and glutamine metabolism. Therapeutic challenges of sunitinib-resistant ccRCC cell lines in vitro using small molecule inhibitors targeting Axl, AMPK and p38, as well as using PD-L1 blocking therapeutic antibodies, showed limited CTL-mediated cytotoxicity in a co-culture model. However, the AMPK activator metformin appears to sensitize the effect of PD-L1 blocking therapeutic antibodies and to enhance CTLs’ cytotoxic effects on ccRCC cells. These effects were not broadly observed with the Axl and the p38 inhibitors. Taken together, these data suggest that targeting certain pathways aberrantly activated by sunitinib resistance such as the AMPK/PDL1 axis might sensitize ccRCC to immunotherapies as a second-line therapeutic approach.
Prebiotic fibers are non-digestible substrates that modulate the gut microbiome by promoting expansion of microbes having the genetic and physiological potential to utilize those molecules. Although several prebiotic substrates have been consistently shown to provide health benefits in human clinical trials, responder and non-responder phenotypes are often reported. These observations had led to interest in identifying, a priori, prebiotic responders and non-responders as a basis for personalized nutrition. In this study, we conducted in vitro fecal enrichments and applied shotgun metagenomics and machine learning tools to identify microbial gene signatures from adult subjects that could be used to predict prebiotic responders and non-responders. Using short chain fatty acids as a targeted response, we identified genetic features, consisting of carbohydrate active enzymes, transcription factors and sugar transporters, from metagenomic sequencing of in vitro fermentations for three prebiotic substrates: xylooligosacharides, fructooligosacharides, and inulin. A machine learning approach was then used to select substrate-specific gene signatures as predictive features. These features were found to be predictive for XOS responders with respect to SCFA production in an in vivo trial. Our results confirm the bifidogenic effect of commonly used prebiotic substrates along with inter-individual microbial responses towards these substrates. We successfully trained classifiers for the prediction of prebiotic responders towards XOS and inulin with robust accuracy (≥ AUC 0.9) and demonstrated its utility in a human feeding trial. Overall, the findings from this study highlight the practical implementation of pre-intervention targeted profiling of individual microbiomes to stratify responders and non-responders.
Predicting and understanding the chemical bond is one of the major challenges of computational quantum chemistry. Kohn–Sham density functional theory (KS-DFT) is the most common method, but approximate density functionals may not be able to describe systems where multiple electronic configurations are equally important. Multiconfigurational wave functions, on the other hand, can provide a detailed understanding of the electronic structures and chemical bonds of such systems. In the complete active space self-consistent field (CASSCF) method, one performs a full configuration interaction calculation in an active space consisting of active electrons and active orbitals. However, CASSCF and its variants require the selection of these active spaces. This choice is not black box; it requires significant experience and testing by the user, and thus active space methods are not considered particularly user-friendly and are employed only by a minority of quantum chemists. Our goal is to popularize these methods by making it easier to make good active space choices. Here, we present a machine learning protocol that performs an automated selection of active spaces for chemical bond dissociation calculations of main group diatomic molecules. The protocol shows high prediction performance for a given target system as long as a properly correlated system is chosen for training. Good active spaces are correctly predicted with a considerably better success rate than random guess (larger than 80% precision for most systems studied). Our automated machine learning protocol shows that a “black-box” mode is possible for facilitating and accelerating the large-scale calculations on multireference systems where single-reference methods such as KS-DFT cannot be applied.
Solubility prediction plays a crucial role in energy storage applications, such as redox flow batteries, because it directly affects the efficiency and reliability. Researchers have developed various methods that utilize quantum calculations and descriptors to predict the aqueous solubilities of organic molecules. Notably, machine learning models based on descriptors have shown promise for solubility prediction. As deep learning tools, graph neural networks (GNNs) have emerged to capture complex structure–property relationships for material property prediction. Specifically, MolGAT, a type of GNN model, was designed to incorporate n-dimensional edge attributes, enabling the modeling of intricacies in molecular graphs and enhancing the prediction capabilities. In a previous study, MolGAT successfully screened 23 467 promising redox-active molecules from a database of over 500 000 compounds, based on redox potential predictions. This study focused on applying the MolGAT model to predict the aqueous solubility (log S) of a broad range of organic compounds, including those previously screened for redox activity. The model was trained on a diverse sample of 8494 organic molecules from AqSolDB and benchmarked against literature data, demonstrating superior accuracy compared with other state of the art graph-based and descriptor-based models. Subsequently, the trained MolGAT model was employed to screen redox-active organic compounds identified in the first phase of high-throughput virtual screening, targeting favorable solubility in energy storage applications. The second round of screening, which considered solubility, yielded 12 332 promising redox-active and soluble organic molecules suitable for use in aqueous redox flow batteries. Thus, the two-phase high-throughput virtual screening approach utilizing MolGAT, specifically trained for redox potential and solubility, is an effective strategy for selecting suitable intrinsically soluble redox-active molecules from extensive databases, potentially advancing energy storage through reliable material development. This indicates that the model is reliable for predicting the solubility of various molecules and provides valuable insights for energy storage, pharmaceutical, environmental, and chemical applications.
Aedes mosquitoes (Diptera: Culicidae), principle vectors of several arboviruses, typically lay eggs in man-made water-filled containers located near human dwellings. Given the widespread emergence of insecticide resistance, stable and biofriendly alternatives for mosquito larviciding are needed. Laboratory studies have demonstrated that inactivated yeast interfering RNA tablets targeting key larval developmental genes can be used to facilitate effective larvicidal activity while also promoting selective gravid female oviposition behaviour. In this work, we examined the efficacy of transferring this technology toward development of lure-and-kill ovitraps targeting Aedes aegypti (L.) and Aedes albopictus (Skuse) female mosquitoes. Insectary, simulated field and semi-field experiments demonstrated that two mosquito-specific yeast interfering RNA pesticides induce high levels of mortality among larvae of both species in treated large volume containers. Small-scale field trials conducted in Trinidad, West Indies demonstrated that large volume ovitrap containers baited with inactivated yeast tablets lure significantly more gravid females than traps containing only water and were highly attractive to both A. aegypti and A. albopictus females. Finally, these studies indicate that development of biorational yeast interfering RNA-baited ovitraps may represent a new tool for control of Aedes mosquitoes, including deployment in existing lure-and-kill ovitrap technologies or traditional container larviciding programs.
The Plasminogen-Apple-Nematode (PAN) domain, with a core of four to six cysteine residues, is found in > 28,000 proteins across 959 genera. Still, its role in protein function is not fully understood. The PAN domain was initially characterized in numerous proteins, including HGF. Dysregulation of HGF-mediated signaling results in multiple deadly cancers. The binding of HGF to its cell surface receptor, c-MET, triggers all biological impacts. Here, we show that mutating four core cysteine residues in the HGF PAN domain reduces c-MET interaction, subsequent c-MET autophosphorylation, and phosphorylation of its downstream targets, perinuclear localization, cellular internalization of HGF, and its receptor, c-MET, and c-MET ubiquitination. Furthermore, transcriptional activation of HGF/c-MET signaling-related genes involved in cancer progression, invasion, metastasis, and cell survival were impaired. Thus, targeting the PAN domain of HGF may represent a mechanism for selectively regulating the binding and activation of the c-MET pathway.
The Material Plasma Exposure eXperiment (MPEX) project seeks to design a steady-state linear plasma facility at Oak Ridge National Laboratory that will be used to study plasma-material interactions (PMIs) at fusion prototypic levels, supporting the evaluation and development of materials for the next generation of fusion devices. This study is focused on PMI exposure of small-size neutron-irradiated specimens, which are clamped onto an actively cooled component. A thermohydraulic evaluation of a new MPEX target assembly design to assess the appropriate operation during MPEX operation is presented. To further guide the design and assess the structural integrity of the components under expected loads, preliminary thermomechanical stress analyses were also conducted. To ensure good thermal contact between the components, thermal interface materials, such as silver flexible graphite, were used in the assembly. It was found that the maximum target temperatures of 1572, 1463, and 1315 K were obtained for Grafoil thicknesses of 0.61, 0.38, and 0.25 mm, respectively. The distribution of the axial deformation at high heat fluxes showed that there are no gaps between components, indicating good contact at material interfaces. Moreover, the contact pressure between the target and other components indicated that very good contact was established at these interfaces. Furthermore, the stress-strain conditions for the target will be further used to assess the appropriate operation during MPEX experiments and gain insight into materials science phenomena during PMI experiments.
Abstract Successful acclimation to copper (Cu) deficiency involves a fine balance between Cu import and export. In the green alga Chlamydomonas reinhardtii, Cu import is dependent on a transcription factor, Copper Response Regulator 1 (CRR1), responsible for activating genes in Cu-deficient cells. Among CRR1 target genes are two Cu transporters belonging to the CTR/COPT gene family (CTR1 and CTR2) and a related soluble protein (CTR3). The ancestor of these green algal proteins was likely acquired from an ancient chytrid and contained conserved cysteine-rich domains (named the CTR-associated domains, CTRA) that are predicted to be involved in Cu acquisition. We show by reverse genetics that Chlamydomonas CTR1 and CTR2 are canonical Cu importers albeit with distinct affinities, while loss of CTR3 did not result in an observable phenotype under the conditions tested. Mutation of CTR1, but not CTR2, recapitulates the poor growth of crr1 in Cu-deficient medium, consistent with a dominant role for CTR1 in high-affinity Cu(I) uptake. On the other hand, the overaccumulation of Cu(I) (20 times the quota) in zinc (Zn) deficiency depends on CRR1 and both CTR1 and CTR2. CRR1-dependent activation of CTR gene expression needed for Cu over-accumulation can be bypassed by the provision of excess Cu in the growth medium. Over-accumulated Cu is sequestered into the acidocalcisome but can become remobilized by restoring Zn nutrition. This mobilization is also CRR1-dependent, and requires activation of CTR2 expression, again distinguishing CTR2 from CTR1 and consistent with the lower substrate affinity of CTR2. One sentence summary Regulation of Cu uptake and sequestration by members of the CTR family of proteins in Chlamydomonas.