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Deriving the ultrastructure of ?-crustacyanin using lower-resolution structural and biophysical methods.

ABSTRACT: The low-resolution structure of ?-crustacyanin has been determined to 30 Å resolution using negative-stain electron microscopy (EM) with single-particle averaging. The protein, which is an assembly of eight ?-crustacyanin dimers, appears asymmetrical and rather open in layout. A model was built to the EM map using the X-ray crystallographic structure of ?-crustacyanin guided by PISA interface analyses. The model has a theoretical sedimentation coefficient that matches well with the experimentally derived value from sedimentation velocity analytical ultracentrifugation. Additionally, the EM model has similarities to models calculated independently by rigid-body modelling to small-angle X-ray scattering (SAXS) data and extracted in silico from the ?-crustacyanin crystal lattice. Theoretical X-ray scattering from each of these models is in reasonable agreement with the experimental SAXS data and together suggest an overall design for the ?-crustacyanin assembly.

SUBMITTER: Rhys NH

PROVIDER: S-EPMC3004261 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Deriving the ultrastructure of α-crustacyanin using lower-resolution structural and biophysical methods.

Rhys Natasha H NH Wang Ming Chuan MC Jowitt Thomas A TA Helliwell John R JR Grossmann J Günter JG Baldock Clair C

Journal of synchrotron radiation 20101105 1

The low-resolution structure of α-crustacyanin has been determined to 30 Å resolution using negative-stain electron microscopy (EM) with single-particle averaging. The protein, which is an assembly of eight β-crustacyanin dimers, appears asymmetrical and rather open in layout. A model was built to the EM map using the X-ray crystallographic structure of β-crustacyanin guided by PISA interface analyses. The model has a theoretical sedimentation coefficient that matches well with the experimentall ...[more]

PMID: 21169698

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Project description:PURPOSE:To assess the validity of a derived algorithm, combining tri-axial accelerometry and heart rate (HR) data, compared to a research-grade multi-sensor physical activity device, for the estimation of ambulatory physical activity energy expenditure (PAEE) in individuals with traumatic lower-limb amputation. METHODS:Twenty-eight participants [unilateral (n = 9), bilateral (n = 10) with lower-limb amputations, and non-injured controls (n = 9)] completed eight activities; rest, ambulating at 5 progressive treadmill velocities (0.48, 0.67, 0.89, 1.12, 1.34m.s-1) and 2 gradients (3 and 5%) at 0.89m.s-1. During each task, expired gases were collected for the determination of [Formula: see text] and subsequent calculation of PAEE. An Actigraph GT3X+ accelerometer was worn on the hip of the shortest residual limb and, a HR monitor and an Actiheart (AHR) device were worn on the chest. Multiple linear regressions were employed to derive population-specific PAEE estimated algorithms using Actigraph GT3X+ outputs and HR signals (GT3X+HR). Mean bias±95% Limits of Agreement (LoA) and error statistics were calculated between criterion PAEE (indirect calorimetry) and PAEE predicted using GT3X+HR and AHR. RESULTS:Both measurement approaches used to predict PAEE were significantly related (P<0.01) with criterion PAEE. GT3X+HR revealed the strongest association, smallest LoA and least error. Predicted PAEE (GT3X+HR; unilateral; r = 0.92, bilateral; r = 0.93, and control; r = 0.91, and AHR; unilateral; r = 0.86, bilateral; r = 0.81, and control; r = 0.67). Mean±SD percent error across all activities were 18±14%, 15±12% and 15±14% for the GT3X+HR and 45±20%, 39±23% and 34±28% in the AHR model, for unilateral, bilateral and control groups, respectively. CONCLUSIONS:Statistically derived algorithms (GT3X+HR) provide a more valid estimate of PAEE in individuals with traumatic lower-limb amputation, compared to a proprietary group calibration algorithm (AHR). Outputs from AHR displayed considerable random error when tested in a laboratory setting in individuals with lower-limb amputation.

Dataset Information

Deriving the ultrastructure of ?-crustacyanin using lower-resolution structural and biophysical methods.

Publications

Deriving the ultrastructure of α-crustacyanin using lower-resolution structural and biophysical methods.

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