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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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492 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Biophysical characterization and a roadmap towards the NMR solution structure of G0S2, a key enzyme in non-alcoholic fatty liver disease

In the United States non-alcoholic fatty liver disease (NAFLD) is the most common form of chronic liver disease, affecting an estimated 80 to 100 million people. It occurs in every age group, but predominantly in people with risk factors such as obesity and type 2 diabetes. NAFLD is marked by fat accumulation in the liver leading to liver inflammation, which may lead to scarring and irreversible damage progressing to cirrhosis and liver failure. In animal models, genetic ablation of the protein G0S2 leads to alleviation of liver damage and insulin resistance in high fat diets. The research presented in this paper aims to aid in rational based drug design for the treatment of NAFLD by providing a pathway for a solution state NMR structure of G0S2. Here we describe the expression of G0S2 in an E. coli system from two different constructs, both of which are confirmed to be functionally active based on the ability to inhibit the activity of Adipose Triglyceride Lipase. In one of the constructs, preliminary NMR spectroscopy measurements show dominant alpha-helical characteristics as well as resonance assignments on the N-terminus of G0S2, allowing for further NMR work with this protein. Additionally, the characterization of G0S2 oligomers are outlined for both constructs, suggesting that G0S2 may defensively exist in a multimeric state to protect and potentially stabilize the small 104 amino acid protein within the cell. This information presented on the structure of G0S2 will further guide future development in the therapy for NAFLD.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Modulation of sensory perception by hydrogen peroxide enables Caenorhabditis elegans to find a niche that provides both food and protection from hydrogen peroxide

Hydrogen peroxide (H 2 O 2 ) is the most common chemical threat that organisms face. Here, we show that H 2 O 2 alters the bacterial food preference of Caenorhabditis elegans , enabling the nematodes to find a safe environment with food. H 2 O 2 induces the nematodes to leave food patches of laboratory and microbiome bacteria when those bacterial communities have insufficient H 2 O 2 -degrading capacity. The nematode’s behavior is directed by H 2 O 2 -sensing neurons that promote escape from H 2 O 2 and by bacteria-sensing neurons that promote attraction to bacteria. However, the input for H 2 O 2 -sensing neurons is removed by bacterial H 2 O 2 -degrading enzymes and the bacteria-sensing neurons’ perception of bacteria is prevented by H 2 O 2 . The resulting cross-attenuation provides a general mechanism that ensures the nematode’s behavior is faithful to the lethal threat of hydrogen peroxide, increasing the nematode’s chances of finding a niche that provides both food and protection from hydrogen peroxide.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emerging viral threats requires substantial resources and time, and traditional development platforms for vaccines and antibodies are often too slow to combat continuously evolving immunological escape variants, reducing their efficacy over time. Previously, we designed a next-generation synthetic humanized nanobody (Nb) phage display library and demonstrated that this library could be used to rapidly identify highly specific and potent neutralizing heavy chain-only antibodies (HCAbs) with prophylactic and therapeutic efficacy in vivo against the original SARS-CoV-2. In this study, we used a combination of high throughput screening and machine learning (ML) models to identify HCAbs with potent efficacy against SARS-CoV-2 viral variants of interest (VOIs) and concern (VOCs). To start, we screened our highly diverse Nb phage display library against several pre-Omicron VOI and VOC receptor binding domains (RBDs) to identify panels of cross-reactive HCAbs. Using HCAb affinity for SARS-CoV-2 VOI and VOCs (pre-Omicron variants) and model features from other published data, we were able to develop a ML model that successfully identified HCAbs with efficacy against Omicron variants, independent of our experimental biopanning workflow. This biopanning informed ML approach reduced the experimental screening burden by 78% to 90% for the Omicron BA.5 and Omicron BA.1 variants, respectively. The combined approach can be applied to other emerging viruses with pandemic potential to rapidly identify effective therapeutic antibodies against emerging variants.

Antibodies↗
DOE OSTI2024

RNA-Seq analysis of nine tRNA-Modification deficient mutants in E. coli

We performed an RNA-Seq analysis of nine of E.coli single knockout strains from the Keio collection carrying deletions in tRNA modification genes (dusB, truA, truD, thiI, miaA, rlmN, mnmA, mnmC, mnmG) and wildtype. RNA was isolated from each of the different strains at grown in LB at 37˚C up to mid-exponential phase (OD(A600nm) ~0.6) in three biological replicates.

tRNA modification, transcriptomics, Escherichia co↗