Coronary Computed Tomographic Angiography at 80 kVp and Knowledge-Based Iterative Model Reconstruction Is Non-Inferior to that at 100 kVp with Iterative Reconstruction

The aims of this study were to compare the image noise and quality of coronary computed tomographic angiography (CCTA) at 80 kVp with knowledge-based iterative model reconstruction (IMR) to those of CCTA at 100 kVp with hybrid iterative reconstruction (IR), and to evaluate the feasibility of a low-dose radiation protocol with IMR. Thirty subjects who underwent prospective electrocardiogram-gating CCTA at 80 kVp, 150 mAs, and IMR (Group A), and 30 subjects with 100 kVp, 150 mAs, and hybrid IR (Group B) were retrospectively enrolled after sample-size calculation. A BMI of less than 25 kg/m2 was required for inclusion. The attenuation value and image noise of CCTA were measured and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated at the proximal right coronary artery and left main coronary artery. The image noise was analyzed using a non-inferiority test. The CCTA images were qualitatively evaluated using a four-point scale. The radiation dose was significantly lower in Group A than Group B (0.69 ± 0.08 mSv vs. 1.39 ± 0.15 mSv, p < 0.001). The attenuation values were higher in Group A than Group B (p < 0.001). The SNR and CNR in Group A were higher than those of Group B. The image noise of Group A was non-inferior to that of Group B. Qualitative image quality of Group A was better than that of Group B (3.6 vs. 3.4, p = 0.017). CCTA at 80 kVp with IMR could reduce the radiation dose by about 50%, with non-inferior image noise and image quality than those of CCTA at 100 kVp with hybrid IR

TrpM, a Small Protein Modulating Tryptophan Biosynthesis and Morpho-Physiological Differentiation in Streptomyces coelicolor A3(2).

In the model actinomycete Streptomyces coelicolor A3(2), small open reading frames encoding proteins with unknown functions were identified in several amino acid biosynthetic gene operons, such as SCO2038 (trpX) in the tryptophan trpCXBA locus. In this study, the role of the corresponding protein in tryptophan biosynthesis was investigated by combining phenotypic and molecular analyses. The 2038KO mutant strain was characterized by delayed growth, smaller aerial hyphae and reduced production of spores and actinorhodin antibiotic, with respect to the WT strain. The capability of this mutant to grow on minimal medium was rescued by tryptophan and tryptophan precursor (serine and/or indole) supplementation on minimal medium and by gene complementation, revealing the essential role of this protein, here named TrpM, as modulator of tryptophan biosynthesis. His-tag pull-down and bacterial adenylate cyclase-based two hybrid assays revealed TrpM interaction with a putative leucyl-aminopeptidase (PepA), highly conserved component among various Streptomyces spp. In silico analyses showed that PepA is involved in the metabolism of serine, glycine and cysteine through a network including GlyA, CysK and CysM enzymes. Proteomic experiments suggested a TrpM-dependent regulation of metabolic pathways and cellular processes that includes enzymes such as GlyA, which is required for the biosynthesis of tryptophan precursors and key proteins participating in the morpho-physiological differentiation program. Altogether, these findings reveal that TrpM controls tryptophan biosynthesis at the level of direct precursor availability and, therefore, it is able to exert a crucial effect on the morpho-physiological differentiation program in S. coelicolor A3(2)

Actinorhodin antibiotic production of <i>S</i>. <i>coelicolor</i> 2038KO.

<p>Production of actinorhodin in 2038KO and WT on MM, and in 2038KO on MM-Trp after 4 days of incubation. Histograms report values from three different cultivations. Vertical bars represent standard deviations.</p

Protein SCO2179 (PepA) association network.

<p>(A) STRING interrogation showed PepA association with enzymes involved in amino acid metabolism: glycine hydroxymethyltransferase (GlyA); glutamate-cysteine ligase (GshA); cysteine synthases (CysK and CysM); glutathione hydrolase (GGT). (B) Representation of metabolic circuit involving PepA network partners.</p

Growth of <i>S</i>. <i>coelicolor</i> 2038KO mutant strain on solid MM.

<p>Growth of 2038KO (1) and WT (2) on solid MM after 24, 48 and 72 h (A) and solid MM-Trp (B). (C) Growth of WT (2) (1), 2038KO (2), pKC796Hyg (3), pKC796Hyg-<i>sco2038</i> (4) on solid MM with the antibiotic hygromycin.</p

<i>S</i>. <i>coelicolor</i> 2038KO growth on MM supplemented with tryptophan precursors serine and indole.

<p>(a) Growth of 2038KO (1) and WT (2) on MM-Pro (negative control); b) MM-serine; c) MM-indole; d) MM-serine-indole.</p

Global view of the metabolic pathways affected by <i>trpM</i> deletion.

<p>Metabolic pathways involving proteins over- and under-represented in 2038KO cultivated on MM <i>vs</i> WT cultivated on MM and in 2038KO cultivated on MM <i>vs</i> 2038KO cultivated on MM-Trp are shown with orange and blue bar color, respectively.</p

Structure and dynamics of dark-state bovine rhodopsin revealed by chemical cross-linking and high-resolution mass spectrometry

Recent work using chemical cross-linking to define interresidue distance constraints in proteins has shown that these constraints are useful for testing tertiary structural models. We applied this approach to the G-protein-coupled receptor bovine rhodopsin in its native membrane using lysine- and cysteine-targeted bifunctional cross-linking reagents. Cross-linked proteolytic peptides of rhodopsin were identified by combined liquid chromatography and FT-ICR mass spectrometry with automated data-reduction and assignment software. Tandem mass spectrometry was used to verify cross-link assignments and locate the exact sites of cross-link attachment. Cross-links were observed to form between 10 pairs of residues in dark-state rhodopsin. For each pair, cross-linkers with a range of linker lengths were tested to determine an experimental distance-of-closest-approach (DCA) between reactive side-chain atoms. In all, 28 cross-links were identified using seven different cross-linking reagents. Molecular mechanics procedures were applied to published crystal structure data to calculate energetically achievable theoretical DCAs between reactive atoms without altering the position of the protein backbone. Experimentally measured DCAs are generally in good agreement with the theoretical DCAs. However, a cross-link between C316 and K325 in the C-terminal region cannot be rationalized by DCA simulations and suggests that backbone reorientation relative to the crystal coordinates occurs on the timescale of cross-linking reactions. Biochemical and spectroscopic data from other studies have found that the C-terminal region is highly mobile in solution and not fully represented by X-ray crystallography data. Our results show that chemical cross-linking can provide reliable three-dimensional structural information and insight into local conformational dynamics in a membrane protein