The structural investigation of large RNP complexes by X-ray crystallography can be a difficult task due to the flexibility of the RNA and of the protein-RNA interfaces, which may hinder crystallization. In these cases, NMR spectroscopy is an attractive alternative to crystallography, although the large size of typical RNP complexes may limit the applicability of solution NMR. Solid-state NMR spectroscopy, however, is not subject to any intrinsic limitations with respect to the size of the object under investigation, with restrictions imposed solely by the sensitivity of the instrumentation. In addition, it does not require large, well-ordered crystals and can therefore be applied to flexible, partially disordered complexes. Here we show for the first time that solid-state NMR spectroscopy can be used to probe intermolecular interactions at the protein-RNA interface in RNP complexes. Distances between the (15)N nuclei of the protein backbone and the (31)P nuclei of the RNA backbone can be measured in TEDOR experiments and used as restraints in structure calculations. The distance measurement is accurate, as proven for the test case of the L7Ae-box C/D RNA complex, for which a crystal structure is available. The results presented here reveal the as yet unexplored potential of solid-state NMR spectroscopy in the investigation of large RNP complexes.
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http://dx.doi.org/10.1021/ja909723f | DOI Listing |
Nat Commun
December 2024
Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Lausanne, Switzerland.
While H-H J-couplings are the cornerstone of all spectral assignment methods in solution-state NMR, they are yet to be observed in solids. Here we observe H-H J-couplings in plastic crystals of (1S)-(-)-camphor in solid-state NMR at magic angle spinning (MAS) rates of 100 kHz and above. This is enabled in this special case because the intrinsic coherence lifetimes at fast MAS rates become longer than the inverse of the H-H J couplings.
View Article and Find Full Text PDFNat Commun
December 2024
Department of Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, 14476, Potsdam, Germany.
Neurodegeneration in Huntington's disease (HD) is accompanied by the aggregation of fragments of the mutant huntingtin protein, a biomarker of disease progression. A particular pathogenic role has been attributed to the aggregation-prone huntingtin exon 1 (HTTex1), generated by aberrant splicing or proteolysis, and containing the expanded polyglutamine (polyQ) segment. Unlike amyloid fibrils from Parkinson's and Alzheimer's diseases, the atomic-level structure of HTTex1 fibrils has remained unknown, limiting diagnostic and treatment efforts.
View Article and Find Full Text PDFNat Commun
December 2024
Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA.
Impaired muscle mitochondrial oxidative capacity is associated with future cognitive impairment, and higher levels of PET and blood biomarkers of Alzheimer's disease and neurodegeneration. Here, we examine its associations with up to over a decade-long changes in brain atrophy and microstructure. Higher in vivo skeletal muscle oxidative capacity via MR spectroscopy (post-exercise recovery rate, k) is associated with less ventricular enlargement and brain aging progression, and less atrophy in specific regions, notably primary sensorimotor cortex, temporal white and gray matter, thalamus, occipital areas, cingulate cortex, and cerebellum white matter.
View Article and Find Full Text PDFPediatr Rheumatol Online J
December 2024
Infection, Immunity and Global Health Theme, Murdoch Children's Research Institute, Parkville, VIC, 3052, Australia.
Background: Juvenile idiopathic arthritis (JIA) is challenging to classify and effectively monitor due to the lack of disease- and subtype-specific biomarkers. A robust molecular signature that tracks with specific JIA features over time is urgently required, and targeted plasma metabolomics may reveal such a signature. The primary aim of this study was to characterise the differences in the plasma metabolome between JIA patients and non-JIA controls and identify specific markers of JIA subtype.
View Article and Find Full Text PDFBMC Med Imaging
December 2024
Department of MRI, Xinxiang Central Hospital (The Fourth Clinical College of Xinxiang Medical University), 56 Jinsui Road, Xinxiang, Henan, 453000, China.
Background: To develop and validate an interpretable machine learning model based on intratumoral and peritumoral radiomics combined with clinicoradiological features and metabolic information from magnetic resonance spectroscopy (MRS), to predict clinically significant prostate cancer (csPCa, Gleason score ≥ 3 + 4) and avoid unnecessary biopsies.
Methods: This study retrospectively analyzed 350 patients with suspicious prostate lesions from our institution who underwent 3.0 Tesla multiparametric magnetic resonance imaging (mpMRI) prior to biopsy (training set, n = 191, testing set, n = 83, and a temporal validation set, n = 76).
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