Dataset Information

Structural changes caused by radiation-induced reduction and radiolysis: the effect of X-ray absorbed dose in a fungal multicopper oxidase.

ABSTRACT: X-ray radiation induces two main effects at metal centres contained in protein crystals: radiation-induced reduction and radiolysis and a resulting decrease in metal occupancy. In blue multicopper oxidases (BMCOs), the geometry of the active centres and the metal-to-ligand distances change depending on the oxidation states of the Cu atoms, suggesting that these alterations are catalytically relevant to the binding, activation and reduction of O(2). In this work, the X-ray-determined three-dimensional structure of laccase from the basidiomycete Coriolopsis gallica (Cg L), a high catalytic potential BMCO, is described. By combining spectroscopic techniques (UV-Vis, EPR and XAS) and X-ray crystallography, structural changes at and around the active copper centres were related to pH and absorbed X-ray dose (energy deposited per unit mass). Depletion of two of the four active Cu atoms as well as low occupancies of the remaining Cu atoms, together with different conformations of the metal centres, were observed at both acidic pH and high absorbed dose, correlating with more reduced states of the active coppers. These observations provide additional evidence to support the role of flexibility of copper sites during O(2) reduction. This study supports previous observations indicating that interpretations regarding redox state and metal coordination need to take radiation effects explicitly into account.

SUBMITTER: De la Mora E

PROVIDER: S-EPMC3335286 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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Structural changes caused by radiation-induced reduction and radiolysis: the effect of X-ray absorbed dose in a fungal multicopper oxidase.

De la Mora Eugenio E Lovett Janet E JE Blanford Christopher F CF Garman Elspeth F EF Valderrama Brenda B Rudino-Pinera Enrique E

Acta crystallographica. Section D, Biological crystallography 20120417 Pt 5

X-ray radiation induces two main effects at metal centres contained in protein crystals: radiation-induced reduction and radiolysis and a resulting decrease in metal occupancy. In blue multicopper oxidases (BMCOs), the geometry of the active centres and the metal-to-ligand distances change depending on the oxidation states of the Cu atoms, suggesting that these alterations are catalytically relevant to the binding, activation and reduction of O(2). In this work, the X-ray-determined three-dimens ...[more]

PMID: 22525754

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Project description:A Fourier-based iterative reconstruction technique, termed Equally Sloped Tomography (EST), is developed in conjunction with advanced mathematical regularization to investigate radiation dose reduction in x-ray CT. The method is experimentally implemented on fan-beam CT and evaluated as a function of imaging dose on a series of image quality phantoms and anonymous pediatric patient data sets. Numerical simulation experiments are also performed to explore the extension of EST to helical cone-beam geometry.EST is a Fourier based iterative algorithm, which iterates back and forth between real and Fourier space utilizing the algebraically exact pseudopolar fast Fourier transform (PPFFT). In each iteration, physical constraints and mathematical regularization are applied in real space, while the measured data are enforced in Fourier space. The algorithm is automatically terminated when a proposed termination criterion is met. Experimentally, fan-beam projections were acquired by the Siemens z-flying focal spot technology, and subsequently interleaved and rebinned to a pseudopolar grid. Image quality phantoms were scanned at systematically varied mAs settings, reconstructed by EST and conventional reconstruction methods such as filtered back projection (FBP), and quantified using metrics including resolution, signal-to-noise ratios (SNRs), and contrast-to-noise ratios (CNRs). Pediatric data sets were reconstructed at their original acquisition settings and additionally simulated to lower dose settings for comparison and evaluation of the potential for radiation dose reduction. Numerical experiments were conducted to quantify EST and other iterative methods in terms of image quality and computation time. The extension of EST to helical cone-beam CT was implemented by using the advanced single-slice rebinning (ASSR) method.Based on the phantom and pediatric patient fan-beam CT data, it is demonstrated that EST reconstructions with the lowest scanner flux setting of 39 mAs produce comparable image quality, resolution, and contrast relative to FBP with the 140 mAs flux setting. Compared to the algebraic reconstruction technique and the expectation maximization statistical reconstruction algorithm, a significant reduction in computation time is achieved with EST. Finally, numerical experiments on helical cone-beam CT data suggest that the combination of EST and ASSR produces reconstructions with higher image quality and lower noise than the Feldkamp Davis and Kress (FDK) method and the conventional ASSR approach.A Fourier-based iterative method has been applied to the reconstruction of fan-bean CT data with reduced x-ray fluence. This method incorporates advantageous features in both real and Fourier space iterative schemes: using a fast and algebraically exact method to calculate forward projection, enforcing the measured data in Fourier space, and applying physical constraints and flexible regularization in real space. Our results suggest that EST can be utilized for radiation dose reduction in x-ray CT via the readily implementable technique of lowering mAs settings. Numerical experiments further indicate that EST requires less computation time than several other iterative algorithms and can, in principle, be extended to helical cone-beam geometry in combination with the ASSR method.

Project description:BackgroundMolecular radiation biomarkers are an emerging tool in radiation research with applications for cancer radiotherapy, radiation risk assessment, and even human space travel. However, biomarker screening in genome-wide expression datasets using conventional tools is time-consuming and underlies analyst (human) bias. Machine Learning (ML) methods can improve the sensitivity and specificity of biomarker identification, increase analytical speed, and avoid multicollinearity and human bias.AimTo develop a resource-efficient ML framework for radiation biomarker discovery using gene expression data from irradiated normal tissues. Further, to identify biomarker panels predicting radiation dose with tissue specificity.MethodsA strategic search in the Gene Expression Omnibus database identified a transcriptomic dataset (GSE44762) for normal tissues radiation responses (murine kidney cortex and medulla) suited for biomarker discovery using an ML approach. The dataset was pre-processed in R and separated into train and test data subsets. High computational cost of Genetic Algorithm/k-Nearest Neighbor (GA/KNN) mandated optimization and 13 ML models were tested using the caret package in R. Biomarker performance was evaluated and visualized via Principal Component Analysis (PCA) and dose regression. The novelty of ML-identified biomarker panels was evaluated by literature search.ResultsCaret-based feature selection and ML methods vastly improved processing time over the GA approach. The KNN method yielded overall best performance values on train and test data and was implemented into the framework. The top-ranking genes were Cdkn1a, Gria3, Mdm2 and Plk2 in cortex, and Brf2, Ccng1, Cdkn1a, Ddit4l, and Gria3 in medulla. These candidates successfully categorized dose groups and tissues in PCA. Regression analysis showed that correlation between predicted and true dose was high with R2 of 0.97 and 0.99 for cortex and medulla, respectively.ConclusionThe caret framework is a powerful tool for radiation biomarker discovery optimizing performance with resource-efficiency for broad implementation in the field. The KNN-based approach identified Brf2, Ddit4l, and Gria3 mRNA as novel candidates that have been uncharacterized as radiation biomarkers to date. The biomarker panel showed good performance in dose and tissue separation and dose regression. Further training with larger cohorts is warranted to improve accuracy, especially for lower doses.

Dataset Information

Structural changes caused by radiation-induced reduction and radiolysis: the effect of X-ray absorbed dose in a fungal multicopper oxidase.

Publications

Structural changes caused by radiation-induced reduction and radiolysis: the effect of X-ray absorbed dose in a fungal multicopper oxidase.

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