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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

DNA-encoded chemistry technology yields expedient access to SARS-CoV-2 M pro inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed more than 4 million humans globally, but there is no bona fide Food and Drug Administration–approved drug-like molecule to impede the COVID-19 pandemic. The sluggish pace of traditional therapeutic discovery is poorly suited to producing targeted treatments against rapidly evolving viruses. Here, we used an affinity-based screen of 4 billion DNA-encoded molecules en masse to identify a potent class of virus-specific inhibitors of the SARS-CoV-2 main protease (M pro ) without extensive and time-consuming medicinal chemistry. CDD-1714, the initial three-building-block screening hit (molecular weight [MW] = 542.5 g/mol), was a potent inhibitor (inhibition constant [K i ] = 20 nM). CDD-1713, a smaller two-building-block analog (MW = 353.3 g/mol) of CDD-1714, is a reversible covalent inhibitor of M pro (K i = 45 nM) that binds in the protease pocket, has specificity over human proteases, and shows in vitro efficacy in a SARS-CoV-2 infectivity model. Subsequently, key regions of CDD-1713 that were necessary for inhibitory activity were identified and a potent (K i = 37 nM), smaller (MW = 323.4 g/mol), and metabolically more stable analog (CDD-1976) was generated. Thus, screening of DNA-encoded chemical libraries can accelerate the discovery of efficacious drug-like inhibitors of emerging viral disease targets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

An ultrapotent synthetic nanobody neutralizes SARS-CoV-2 by stabilizing inactive Spike

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus enters host cells via an interaction between its Spike protein and the host cell receptor angiotensin-converting enzyme 2 (ACE2). By screening a yeast surface-displayed library of synthetic nanobody sequences, we developed nanobodies that disrupt the interaction between Spike and ACE2. Cryo–electron microscopy (cryo-EM) revealed that one nanobody, Nb6, binds Spike in a fully inactive conformation with its receptor binding domains locked into their inaccessible down state, incapable of binding ACE2. Affinity maturation and structure-guided design of multivalency yielded a trivalent nanobody, mNb6-tri, with femtomolar affinity for Spike and picomolar neutralization of SARS-CoV-2 infection. mNb6-tri retains function after aerosolization, lyophilization, and heat treatment, which enables aerosol-mediated delivery of this potent neutralizer directly to the airway epithelia.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Phylogenetic analysis of anaerobic psychrophilic enrichment cultures obtained from a greenland glacier ice core

The examination of microorganisms in glacial ice cores allows the phylogenetic relationships of organisms frozen for thousands of years to be compared with those of current isolates. We developed a method for aseptically sampling a sediment-containing portion of a Greenland ice core that had remained at -9 degrees C for over 100,000 years. Epifluorescence microscopy and flow cytometry results showed that the ice sample contained over 6 x 10(7) cells/ml. Anaerobic enrichment cultures inoculated with melted ice were grown and maintained at -2 degrees C. Genomic DNA extracted from these enrichments was used for the PCR amplification of 16S rRNA genes with bacterial and archaeal primers and the preparation of clone libraries. Approximately 60 bacterial inserts were screened by restriction endonuclease analysis and grouped into 27 unique restriction fragment length polymorphism types, and 24 representative sequences were compared phylogenetically. Diverse sequences representing major phylogenetic groups including alpha, beta, and gamma Proteobacteria as well as relatives of the Thermus, Bacteroides, Eubacterium, and Clostridium groups were found. Sixteen clone sequences were closely related to those from known organisms, with four possibly representing new species. Seven sequences may reflect new genera and were most closely related to sequences obtained only by PCR amplification. One sequence was over 12% distant from its closest relative and may represent a novel order or family. These results show that phylogenetically diverse microorganisms have remained viable within the Greenland ice core for at least 100,000 years.

Evaluation Studies↗
NASA NTRS2000

Arabidopsis chloroplast chaperonin 10 is a calmodulin-binding protein

Calcium regulates diverse cellular activities in plants through the action of calmodulin (CaM). By using (35)S-labeled CaM to screen an Arabidopsis seedling cDNA expression library, a cDNA designated as AtCh-CPN10 (Arabidopsis thaliana chloroplast chaperonin 10) was cloned. Chloroplast CPN10, a nuclear-encoded protein, is a functional homolog of E. coli GroES. It is believed that CPN60 and CPN10 are involved in the assembly of Rubisco, a key enzyme involved in the photosynthetic pathway. Northern analysis revealed that AtCh-CPN10 is highly expressed in green tissues. The recombinant AtCh-CPN10 binds to CaM in a calcium-dependent manner. Deletion mutants revealed that there is only one CaM-binding site in the last 31 amino acids of the AtCh-CPN10 at the C-terminal end. The CaM-binding region in AtCh-CPN10 has higher homology to other chloroplast CPN10s in comparison to GroES and mitochondrial CPN10s, suggesting that CaM may only bind to chloroplast CPN10s. Furthermore, the results also suggest that the calcium/CaM messenger system is involved in regulating Rubisco assembly in the chloroplast, thereby influencing photosynthesis. Copyright 2000 Academic Press.

NASA Discipline Plant Biology↗
NASA NTRS2000

Molecular and biochemical evidence for the involvement of calcium/calmodulin in auxin action

The use of (35)S-labeled calmodulin (CaM) to screen a corn root cDNA expression library has led to the isolation of a CaM-binding protein, encoded by a cDNA with sequence similarity to small auxin up RNAs (SAURs), a class of early auxin-responsive genes. The cDNA designated as ZmSAUR1 (Zea mays SAURs) was expressed in Escherichia coli, and the recombinant protein was purified by CaM affinity chromatography. The CaM binding assay revealed that the recombinant protein binds to CaM in a calcium-dependent manner. Deletion analysis revealed that the CaM binding site was located at the NH(2)-terminal domain. A synthetic peptide of amino acids 20-45, corresponding to the potential CaM binding region, was used for calcium-dependent mobility shift assays. The synthetic peptide formed a stable complex with CaM only in the presence of calcium. The CaM affinity assay indicated that ZmSAUR1 binds to CaM with high affinity (K(d) approximately 15 nM) in a calcium-dependent manner. Comparison of the NH(2)-terminal portions of all of the characterized SAURs revealed that they all contain a stretch of the basic alpha-amphiphilic helix similar to the CaM binding region of ZmSAUR1. CaM binds to the two synthetic peptides from the NH(2)-terminal regions of Arabidopsis SAUR-AC1 and soybean 10A5, suggesting that this is a general phenomenon for all SAURs. Northern analysis was carried out using the total RNA isolated from auxin-treated corn coleoptile segments. ZmSAUR1 gene expression began within 10 min, increased rapidly between 10 and 60 min, and peaked around 60 min after 10 microM alpha-naphthaleneacetic acid treatment. These results indicate that ZmSAUR1 is an early auxin-responsive gene. The CaM antagonist N-(6-aminohexyl)5-chloro-1-naphthalenesulfonamide hydrochloride inhibited the auxin-induced cell elongation but not the auxin-induced expression of ZmSAUR1. This suggests that calcium/CaM do not regulate ZmSAUR1 at the transcriptional level. CaM binding to ZmSAUR1 in a calcium-dependent manner suggests that calcium/CaM regulate ZmSAUR1 at the post-translational level. Our data provide the first direct evidence for the involvement of calcium/CaM-mediated signaling in auxin-mediated signal transduction.

NASA Program Fundamental Space Biology↗
NASA NTRS1992

Identification of a mouse B-type cyclin which exhibits developmentally regulated expression in the germ line

To begin to examine the function of cyclins in mammalian germ cells, we have screened an adult mouse testis cDNA library for the presence of B-type cyclins. We have isolated cDNAs that encode a murine B-type cyclin, which has been designated cycB1. cycB1 was shown to be expressed in several adult tissues and in the midgestation mouse embryo. In the adult tissues, the highest levels of cycB1 transcripts were seen in the testis and ovary, which contain germ cells at various stages of differentiation. The major transcripts corresponding to cycB1 are 1.7 and 2.5 kb, with the 1.7 kb species being the predominant testicular transcript and the 2.5 kb species more abundant in the ovary. Examination of cDNAs corresponding to the 2.5 kb and 1.7 kb mRNAs revealed that these transcripts encode identical proteins, differing only in the polyadenylation signal used and therefore in the length of their 3' untranslated regions. Northern blot and in situ hybridization analyses revealed that the predominant sites of cycB1 expression in the testis and ovary were in the germinal compartment, particularly in early round spermatids in the testis and growing oocytes in the ovary. Thus cycB1 is expressed in both meiotic and postmeiotic cells. This pattern of cycB1 expression further suggests that cycB1 may have different functions in the two cell types, only one of which correlates with progression of the cell cycle.

NASA Discipline Developmental Biology↗
NASA NTRS2012

Visible Light Responsive Catalysts Using Quantum Dot-Modified Ti02 for Air and Water Purification

The method of photocatalysis utilizing titanium dioxide, TiO2, as the catalyst has been widely studied for trace contaminant control for both air and water applications because of its low energy consumption and use of a regenerable catalyst. Titanium dioxide requires ultraviolet light for activation due to its band gap energy of 3.2 eV. Traditionally, Hg-vapor fluorescent light sources are used in PCO reactors and are a setback for the technology for space application due to the possibility of Hg contamination. The development of a visible light responsive (VLR) TiO2-based catalyst could lead to the use of solar energy in the visible region (approx.45% of the solar spectrum lies in the visible region; > 400 nm) or highly efficient LEDs (with wavelengths > 400 nm) to make PCO approaches more efficient, economical, and safe. Though VLR catalyst development has been an active area of research for the past two decades, there are few commercially available VLR catalysts; those that are available still have poor activity in the visible region compared to that in the UV region. Thus, this study was aimed at the further development of VLR catalysts by a new method - coupling of quantum dots (QD) of a narrow band gap semiconductor (e.g., CdS, CdSe, PbS, ZnSe, etc.) to the TiO2 by two preparation methods: 1) photodeposition and 2) mechanical alloying using a high-speed ball mill. A library of catalysts was developed and screened for gas and aqueous phase applications, using ethanol and 4-chlorophenol as the target contaminants, respectively. Both target compounds are well studied in photocatalytic systems serve as model contaminants for this research. Synthesized catalysts were compared in terms of preparation method, type of quantum dots, and dosage of quantum dots.

Coutts, Janelle L.↗
NASA NTRS2014

Visible-Light-Responsive Catalysts Using Quantum Dot-Modified TiO2 for Air and Water Purification

Photocatalysis, the oxidation or reduction of contaminants by light-activated catalysts, utilizing titanium dioxide (TiO2) as the catalytic substrate has been widely studied for trace contaminant control in both air and water applications. The interest in this process is due primarily to its low energy consumption and capacity for catalyst regeneration. Titanium dioxide requires ultraviolet light for activation due to its relatively large band gap energy of 3.2 eV. Traditionally, Hg-vapor fluorescent light sources are used in PCO reactors; however, the use of mercury precludes the use of this PCO technology in a spaceflight environment due to concerns over crew Hg exposure. The development of a visible-light responsive (VLR) TiO2-based catalyst would eliminate the concerns over mercury contamination. Further, VLR development would allow for the use of ambient visible solar radiation or highly efficient LEDs, both of which would make PCO approaches more efficient, flexible, economical, and safe. Though VLR catalyst development has been an active area of research for the past two decades, there are few commercially available VLR catalysts. Those VLR catalysts that are commercially available do not have adequate catalytic activity, in the visible region, to make them competitive with those operating under UV irradiation. This study was initiated to develop more effective VLR catalysts through a novel method in which quantum dots (QD) consisting of narrow band gap semiconductors (e.g., CdS, CdSe, PbS, ZnSe, etc.) are coupled to TiO2 via two preparation methods: 1) photodeposition and 2) mechanical alloying using a high-speed ball mill. A library of catalysts was developed and screened for gas and aqueous phase applications using ethanol and 4-chlorophenol as the target contaminants, respectively. Both target compounds are well studied in photocatalytic systems and served as model contaminants for this research. Synthesized catalysts were compared in terms of preparation method, nature of the quantum dots, and dosage of quantum dots.

visible light↗
DOE OSTI2024

Challenges and Solutions for Leave-One-Out Biosensor Design in the Context of a Rugged Fitness Landscape

The leave-one-out (LOO) green fluorescent protein (GFP) approach to biosensor design combines computational protein design with split protein reconstitution. LOO-GFPs reversibly fold and gain fluorescence upon encountering the target peptide, which can be redefined by computational design of the LOO site. Such an approach can be used to create reusable biosensors for the early detection of emerging biological threats. Enlightening biophysical inferences for nine LOO-GFP biosensor libraries are presented, with target sequences from dengue, influenza, or HIV, replacing beta strands 7, 8, or 11. An initially low hit rate was traced to components of the energy function, manifesting in the over-rewarding of over-tight side chain packing. Also, screening by colony picking required a low library complexity, but designing a biosensor against a peptide of at least 12 residues requires a high-complexity library. This double-bind was solved using a “piecemeal” iterative design strategy. Also, designed LOO-GFPs fluoresced in the unbound state due to unwanted dimerization, but this was solved by fusing a fully functional prototype LOO-GFP to a fiber-forming protein, Drosophila ultrabithorax, creating a biosensor fiber. One influenza hemagglutinin biosensor is characterized here in detail, showing a shifted excitation/emission spectrum, a micromolar affinity for the target peptide, and an unexpected photo-switching ability.

Chemistry↗
DOE OSTI2025

Next-generation sequencing dataset of genome-scale CRISPRi in Synechococcus sp. PCC 7002 across seven conditions

A 33,298-member sgRNA library developed for Synechococus sp. PCC 7002 was screened with two replicates across seven growth conditions and sequenced with Illumina NextSeq (paired end, 2x150 bp) for a total of ~700M reads. The original plasmid library and the library after transformation into a dCas9-containing and dCas9-absent strain were also sequenced as a reference for initial sgRNA abundance.

genome- wide screens environmental acclimation spe↗
DOE OSTI2023

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows

Synthetic polymers are highly customizable with tailored structures and functionality, yet this versatility generates challenges in the design of advanced materials due to the size and complexity of the design space. Thus, exploration and optimization of polymer properties using combinatorial libraries has become increasingly common, which requires careful selection of synthetic strategies, characterization techniques, and rapid processing workflows to obtain fundamental principles from these large data sets. Herein, we provide guidelines for strategic design of macromolecule libraries and workflows to efficiently navigate these high-dimensional design spaces. We describe synthetic methods for multiple library sizes and structures as well as characterization methods to rapidly generate data sets, including tools that can be adapted from biological workflows. We further highlight relevant insights from statistics and machine learning to aid in data featurization, representation, and analysis. This Perspective acts as a “user guide” for researchers interested in leveraging high-throughput screening toward the design of multifunctional polymers and predictive modeling of structure–property relationships in soft materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

HDBind: encoding of molecular structure with hyperdimensional binary representations

Traditional methods for identifying “hit” molecules from a large collection of potential drug-like candidates rely on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have a significant limitation in that they require exceptional computing capabilities for even relatively small collections of molecules. Increasingly large and complex state-of-the-art deep learning approaches have gained popularity with the promise to improve the productivity of drug design, notorious for its numerous failures. However, as deep learning models increase in their size and complexity, their acceleration at the hardware level becomes more challenging. Hyperdimensional Computing (HDC) has recently gained attention in the computer hardware community due to its algorithmic simplicity relative to deep learning approaches. The HDC learning paradigm, which represents data with high-dimension binary vectors, allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas (computer vision, bioinformatics, mass spectrometery, remote sensing, edge devices, etc.). To the best of our knowledge, our work is the first to consider HDC for the task of fast and efficient screening of modern drug-like compound libraries. We also propose the first HDC graph-based encoding methods for molecular data, demonstrating consistent and substantial improvement over previous work. We compare our approaches to alternative approaches on the well-studied MoleculeNet dataset and the recently proposed LIT-PCBA dataset derived from high quality PubChem assays. We demonstrate our methods on multiple target hardware platforms, including Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), showing at least an order of magnitude improvement in energy efficiency versus even our smallest neural network baseline model with a single hidden layer. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools. We make our code publicly available at https://github.com/LLNL/hdbind.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Coupling High-Throughput and Targeted Screening for Identification of Nonobvious Metabolic Engineering Targets

Identification of metabolic engineering targets is a fundamental challenge in strain development programs. While high-throughput (HTP) genetic engineering methodologies capable of generating vast diversity are being developed at a rapid rate, a majority of industrially interesting molecules cannot be screened at sufficient throughput to leverage these techniques. We propose a workflow that couples HTP screening of common precursors (e.g., amino acids) that can be screened either directly or by artificial biosensors, with low-throughput targeted validation of the molecule of interest to uncover nonintuitive beneficial metabolic engineering targets and combinations hereof. Using this workflow, we identified several nonobvious novel targets for improving p-coumaric acid (p-CA) and L -DOPA production from two large 4k gRNA libraries each deregulating 1000 metabolic genes in the yeast Saccharomyces cerevisiae. We initially screened yeast cells transformed with gRNA library plasmids for individual regulatory targets improving the production of l-tyrosine-derived betaxanthins, identifying 30 targets that increased intracellular betaxanthin content 3.5–5.7 fold. Hereafter, we screened the targets individually in a high-producing p-CA strain, narrowing down the targets to six that increased the secreted titer by up to 15%. To investigate whether any of the six targets could be additively combined to improve p-CA production further, we created a gRNA multiplexing library and subjected it to our proposed coupled workflow. The combination of regulating PYC1 and NTH2 simultaneously resulted in the highest (threefold) improvement of the betaxanthin content, and an additive trend was also observed in the p-CA strain. Lastly, we tested the initial 30 targets in a L -DOPA producing strain, identifying 10 targets that increased the secreted titer by up to 89%, further validating our screening by proxy workflow. This coupled approach is useful for strain development in the absence of direct HTP screening assays for products of interest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Spin-Controllable Dynamics in Defect-Engineered Carbon Nanotubes as Single Photon Emitters: Data-Driven Modeling and Computations

Quantum technologies, such as quantum computing and sensing, require efficient single-photon emission (SPE) sources that operate at room temperature in telecom wavelengths. While several materials can serve as SPE sources, no single platform meets all the criteria for efficiency, ambient operation, and scalability. Single-walled carbon nanotubes (SWCNTs) with covalently attached molecules offer a promising solution. Their SPE can be easily tuned via modifications of the SWCNT's diameter, chirality, and bonded molecules, enabling emission across near-IR to telecom wavelengths at ambient conditions. However, to fully realize the potential of SWCNTs and unlock their quantum capabilities, a deeper understanding of how structural defects from molecular adducts affect their emission and competing photoexcited processes is essential. To address this gap in our knowledge, this project combined quantum chemistry calculations with data-driven methods of cheminformatics (QSAR) and machine learning (ML). The developed computational approaches have provided several design strategies for covalent functionalization of SWCNTs to improve their optical response. The collaboration with Los Alamos National Lab (LANL) enabled direct comparison of computational and experimental data, facilitating method validation. This partnership was enhanced through access to LANL's Center for Integrated Nanotechnologies (CINT) utilizing User Facility Program and summer internships, which provided three NDSU graduate students with hands-on experience at LANL. The outcomes of this project included (1) Advancing the current stage of computational methods in accurate modeling of non-adiabatic spin-dependent photoexcited dynamics and its applicability to nanosystems consisting of thousands of atoms, realized as open-access codes linked to existing DFT-based software; (2) Establishing the relationship between the structure of adducts and SWCNTs and intrinsic excitonic and spin properties of defect states for guiding novel synthetic strategies and experimental probes of chemically functionalized SWCNTs as near-IR emitting materials; (3) Generating virtual libraries of hypothetical functionalized SWCNTs for virtual screening of their chemical structures and optical properties, leveraging new functionalities of SWCNTs; (4) Offering a unique experience for NDSU graduate students that prepared them for future scientific careers related to materials modeling and big data processing. These results were summarized in 12 published journal papers and 3 recently submitted papers. One of a key finding is that the position of defect sites on the SWCNT surface primarily drives the emission redshift (up to 100 meV), while the polarity of the defect-inducing molecules has a much smaller effect (~10 meV). However, the electron-donating or withdrawing properties of a molecule influence selecting reactivity of defect sites. These insights important for optimizing synthetic protocols for desired emissions in SWCNTs. We also revealed that the interaction between two defects at various positions on the SWCNT enhances the redshift and optical activity of states, favoring strong near-IR emission. This suggests that manipulations in defect concentrations is a promising strategy for controlling efficient emission. Mostly important, the defect position was found controllable by the spin states of photoexcited intermediates: Excited aromatic molecules form ortho defects with SWCNTs at their singlet states in the presence of oxygen, while oxygen-free conditions favor para defects via the triplet-state mechanism. Additionally, a heat-activated [2+2] cycloaddition reaction facilitates divalent defect formation with fewer bonding positions that narrows emission bands. These groundbreaking findings have been experimentally validated and significantly advance our understanding of defect chemistry in SWCNTs. Using a novel encoding technique and 3D-MoRSE descriptors, we developed highly accurate ML/QSAR models to predict both the 3D structure and optical properties of SWCNTs with chemical defects. This model enabled the creation of a virtual library of 125,556 structures, providing new insights into the relationship between SWCNT-defect structure and emission.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Biophysical Screens Identify Fragments That Bind to the Viral DNA-Binding Proteins EBNA1 and LANA

The human gamma-herpesviruses Epstein–Barr virus (EBV) (HHV-4) and Kaposi’s sarcoma-associated herpesvirus (KSHV) (HHV-8) are responsible for a number of diseases, including various types of cancer. Epstein–Barr nuclear antigen 1 (EBNA1) from EBV and latency-associated nuclear antigen (LANA) from KSHV are viral-encoded DNA-binding proteins that are essential for the replication and maintenance of their respective viral genomes during latent, oncogenic infection. As such, EBNA1 and LANA are attractive targets for the development of small-molecule inhibitors. To this end, we performed a biophysical screen of EBNA1 and LANA using a fragment library by saturation transfer difference (STD)–NMR spectroscopy and surface plasmon resonance (SPR). We identified and validated a number of unique fragment hits that bind to EBNA1 or LANA. We also determined the high-resolution crystal structure of one fragment bound to EBNA1. Results from this screening cascade provide new chemical starting points for the further development of potent inhibitors for this class of viral proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Rutin is a potent senomorphic agent to target senescent cells and can improve chemotherapeutic efficacy

Aging is a major risk factor for most chronic disorders, for which cellular senescence is one of the central hallmarks. Senescent cells develop the pro-inflammatory senescence-associated secretory phenotype (SASP), which significantly contributes to organismal aging and age-related disorders. Development of senotherapeutics, an emerging class of therapeutic agents to target senescent cells, allows to effectively delay aging and alleviate chronic pathologies. Here we report preliminary outputs from screening of a natural medicinal agent (NMA) library for senotherapeutic candidates and validated several agents with prominent potential as senomorphics. Rutin, a phytochemical constituent found in a number of plants, showed remarkable capacity in targeting senescent cells by dampening expression of the full spectrum SASP. Further analysis indicated that rutin restrains the acute stress-associated phenotype (ASAP) by specifically interfering with the interactions of ATM with HIF1α, a master regulator of cellular and systemic homeostasis activated during senescence, and of ATM with TRAF6, part of a key signaling axis supporting the ASAP development toward the SASP. Conditioned media produced by senescent stromal cells enhanced the malignant phenotypes of prostate cancer cells, including in vitro proliferation, migration, invasion, and more importantly, chemoresistance, while rutin remarkably downregulated these gain-of-functions. Although classic chemotherapy reduced tumor progression, the treatment outcome was substantially improved upon combination of a chemotherapeutic agent with rutin. Our study provides a proof of concept for rutin as an emerging natural senomorphic agent, and presents an effective therapeutic avenue for alleviating age-related pathologies including cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Yeast Deletomics to Uncover Gadolinium Toxicity Targets and Resistance Mechanisms

Among the rare earth elements (REEs), a crucial group of metals for high-technologies. Gadolinium (Gd) is the only REE intentionally injected to human patients. The use of Gd-based contrasting agents for magnetic resonance imaging (MRI) is the primary route for Gd direct exposure and accumulation in humans. Consequently, aquatic environments are increasingly exposed to Gd due to its excretion through the urinary tract of patients following an MRI examination. The increasing number of reports mentioning Gd toxicity, notably originating from medical applications of Gd, necessitates an improved risk–benefit assessment of Gd utilizations. To go beyond toxicological studies, unravelling the mechanistic impact of Gd on humans and the ecosystem requires the use of genome-wide approaches. We used functional deletomics, a robust method relying on the screening of a knock-out mutant library of Saccharomyces cerevisiae exposed to toxic concentrations of Gd. The analysis of Gd-resistant and -sensitive mutants highlighted the cell wall, endosomes and the vacuolar compartment as cellular hotspots involved in the Gd response. Furthermore, we identified endocytosis and vesicular trafficking pathways (ESCRT) as well as sphingolipids homeostasis as playing pivotal roles mediating Gd toxicity. Finally, tens of yeast genes with human orthologs linked to renal dysfunction were identified as Gd-responsive. Therefore, the molecular and cellular pathways involved in Gd toxicity and detoxification uncovered in this study underline the pleotropic consequences of the increasing exposure to this strategic metal.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1996

A Potato cDNA Encoding a Homologue of Mammalian Multidrug Resistant P-Glycoprotein

A homologue of the multidrug resistance (MDR) gene was obtained while screening a potato stolon tip cDNA expression library with S-15-labeled calmodulin. The mammalian MDR gene codes for a membrane-bound P-glycoprotein (170-180 kDa) which imparts multidrug resistance to cancerous cells. The potato cDNA (PMDR1) codes for a polypeptide of 1313 amino acid residues (ca. 144 kDa) and its structural features are very similar to the MDR P-glycoprotein. The N-terminal half of the PMDR1-encoded protein shares striking homology with its C-terminal half, and each half contains a conserved ATP-binding site and six putative transmembrane domains. Southern blot analysis indicated that potato has one or two MDR-like genes. PMDR1 mRNA is constitutively expressed in all organs studied with higher expression in the stem and stolon tip. The PMDR1 expression was highest during tuber initiation and decreased during tuber development.

Wang, W.↗