Ablation of skeletal muscle triadin impairs FKBP12/RyR1 channel interactions essential for maintaining resting cytoplasmic Ca2+

Previously, we have shown that lack of expression of triadins in skeletal muscle cells results in significant increase of myoplasmic resting free Ca(2+) ([Ca(2+)](rest)), suggesting a role for triadins in modulating global intracellular Ca(2+) homeostasis. To understand this mechanism, we study here how triadin alters [Ca(2+)](rest), Ca(2+) release, and Ca(2+) entry pathways using a combination of Ca(2+) microelectrodes, channels reconstituted in bilayer lipid membranes (BLM), Ca(2+), and Mn(2+) imaging analyses of myotubes and RyR1 channels obtained from triadin-null mice. Unlike WT cells, triadin-null myotubes had chronically elevated [Ca(2+)](rest) that was sensitive to inhibition with ryanodine, suggesting that triadin-null cells have increased basal RyR1 activity. Consistently, BLM studies indicate that, unlike WT-RyR1, triadin-null channels more frequently display atypical gating behavior with multiple and stable subconductance states. Accordingly, pulldown analysis and fluorescent FKBP12 binding studies in triadin-null muscles revealed a significant impairment of the FKBP12/RyR1 interaction. Mn(2+) quench rates under resting conditions indicate that triadin-null cells also have higher Ca(2+) entry rates and lower sarcoplasmic reticulum Ca(2+) load than WT cells. Overexpression of FKBP12.6 reverted the null phenotype, reducing resting Ca(2+) entry, recovering sarcoplasmic reticulum Ca(2+) content levels, and restoring near normal [Ca(2+)](rest). Exogenous FKBP12.6 also reduced the RyR1 channel P(o) but did not rescue subconductance behavior. In contrast, FKBP12 neither reduced P(o) nor recovered multiple subconductance gating. These data suggest that elevated [Ca(2+)](rest) in triadin-null myotubes is primarily driven by dysregulated RyR1 channel activity that results in part from impaired FKBP12/RyR1 functional interactions and a secondary increased Ca(2+) entry at rest.     

Structure and Molecular Characterization of Streptococcus pneumoniae Capsular Polysaccharide 10F by Carbohydrate Engineering in Streptococcus oralis

Although closely related at the molecular level, the capsular polysaccharide (CPS) of serotype 10F Streptococcus pneumoniae and coaggregation receptor polysaccharide (RPS) of Streptococcus oralis C104 have distinct ecological roles. CPS prevents phagocytosis of pathogenic S. pneumoniae, whereas RPS of commensal S. oralis functions as a receptor for lectin-like adhesins on other members of the dental plaque biofilm community. Results from high resolution NMR identified the recognition region of S. oralis RPS (i.e. Galfβ1–6GalNAcβ1–3Galα) in the hexasaccharide repeat of S. pneumoniae CPS10F. The failure of this polysaccharide to support fimbriae-mediated adhesion of Actinomyces naeslundii was explained by the position of Galf, which occurred as a branch in CPS10F rather than within the linear polysaccharide chain, as in RPS. Carbohydrate engineering of S. oralis RPS with wzy from S. pneumoniae attributed formation of the Galf branch in CPS10F to the linkage of adjacent repeating units through sub terminal GalNAc in Galfβ1–6GalNAcβ1–3Galα rather than through terminal Galf, as in RPS. A gene (wcrD) from serotype 10A S. pneumoniae was then used to engineer a linear surface polysaccharide in S. oralis that was identical to RPS except for the presence of a β1–3 linkage between Galf and GalNAcβ1–3Galα. This polysaccharide also failed to support adhesion of A. naeslundii, thereby establishing the essential role of β1–6-linked Galf in recognition of adjacent GalNAcβ1–3Galα in wild-type RPS. These findings, which illustrate a molecular approach for relating bacterial polysaccharide structure to function, provide insight into the possible evolution of S. oralis RPS from S. pneumoniae CPS.     

How do red blood cells cause hypoxic vasodilation? The SNO-hemoglobin paradigm

One of the most intriguing areas of research in erythrocyte physiology is the interaction of hemoglobin with nitric oxide (NO). These two molecules independently fulfill diverse and complex physiological roles, while together they subtly modulate microvascular perfusion in response to second-by-second changes in local metabolic demand, contributing to hypoxic vasodilation. It is through an appreciation of the temporal and structural constraints of the microcirculation that the principal requirements of the physiological interplay between NO and hemoglobin are revealed, elucidating the role of the erythrocyte in hypoxic vasodilation. Among the candidate molecular mechanisms, only S-nitrosohemoglobin (SNO-hemoglobin) directly fulfills the physiological requirements. Thus, NO is transported by red blood cells to microvascular sites of action in protected form as an S-nitrosothiol on the highly conserved hemoglobin beta-93 Cys residue, invariant in birds and mammals. SNO-hemoglobin dispenses NO bioactivity to microvascular cells on the release of oxygen, physiologically coupling hemoglobin deoxygenation to vasodilation. SNO-hemoglobin is the archetype for the role of S-nitrosylation in a newly identified class of biological signals, and disturbances in SNO-hemoglobin activity are associated with the pathogenesis of several important vascular diseases.     

Selective spatiotemporal induction of matrix metalloproteinase-2 and matrix metalloproteinase-9 transcription after myocardial infarction

Myocardial remodeling after myocardial infarction (MI) is associated with increased levels of the matrix metalloproteinases (MMPs). Levels of two MMP species, MMP-2 and MMP-9, are increased after MI, and transgenic deletion of these MMPs attenuates post-MI left ventricular (LV) remodeling. This study characterized the spatiotemporal patterns of gene promoter induction for MMP-2 and MMP-9 after MI. MI was induced in transgenic mice in which the MMP-2 or MMP-9 promoter sequence was fused to the beta-galactosidase reporter, and reporter level was assayed up to 28 days after MI. Myocardial localization with respect to cellular sources of MMP-2 and MMP-9 promoter induction was examined. After MI, LV diameter increased by 70% (P < 0.05), consistent with LV remodeling. beta-Galactosidase staining in MMP-2 reporter mice was increased by 1 day after MI and increased further to 64 +/- 6% of LV epicardial area by 7 days after MI (P < 0.05). MMP-2 promoter activation occurred in fibroblasts and myofibroblasts in the MI region. In MMP-9 reporter mice, promoter induction was detected after 3 days and peaked at 7 days after MI (53 +/- 6%, P < 0.05) and was colocalized with inflammatory cells at the peri-infarct region. Although MMP-2 promoter activation was similarly distributed in the MI and border regions, activation of the MMP-9 promoter was highest at the border between the MI and remote regions. These unique findings visually demonstrated that activation of the MMP-2 and MMP-9 gene promoters occurs in a distinct spatial relation with reference to the MI region and changes in a characteristic time-dependent manner after MI.     

Anti-RANKL therapy for inflammatory bone disorders: Mechanisms and potential clinical applications

Focal bone loss around inflamed joints in patients with autoimmune disease, such as rheumatoid arthritis, remains a serious clinical problem. The recent elucidation of the RANK/RANK-ligand/OPG pathway and its role as the final effector of osteoclastogenesis and bone resorption has brought a tremendous understanding of the pathophysiology of inflammatory bone loss, and has heightened expectation of a novel intervention. Here, we review the etiology of inflammatory bone loss, the RANK/RANK-ligand/OPG pathway, and the clinical development of anti-RANK-ligand therapy.     

Single linkage group per chromosome genetic linkage map for the horse, based on two three-generation, full-sibling, crossbred horse reference families

A genetic linkage map of the horse consisting of 742 markers, which comprises a single linkage group for each of the autosomes and the X chromosome, is presented. The map has been generated from two three-generation full-sibling reference families, sired by the same stallion, in which there are 61 individuals in the F2 generation. Each linkage group has been assigned to a chromosome and oriented with reference to markers mapped by fluorescence in situ hybridization. The average interval between markers is 3.7 cM and the linkage groups collectively span 2772 cM. The 742 markers comprise 734 microsatellite and 8 gene-based markers. The utility of the microsatellite markers for comparative mapping has been significantly enhanced by comparing their flanking sequences with the human genome sequence; this enabled conserved segments between human and horse to be identified. The new map provides a valuable resource for genetically mapping traits of interest in the horse.     

Root and stem partitioning of Pinus taeda

We measured root and stem mass at three sites (Piedmont (P), Coastal Plain (C), and Sandhills (S)) in the southeastern United States. Stand density, soil texture and drainage, genetic makeup and environmental conditions varied with site while differences in tree size at each site were induced with fertilizer additions. Across sites, root mass was about one half of stem mass when estimated on a per hectare basis. Stem mass per hectare explained 91% of the variation in root mass per hectare, while mean tree diameter at breast height (D), site, and site by measurement year were significant variables explaining an additional 6% of the variation in root mass per hectare. At the S site, the root:stem ratio decreased from 0.7 to 0.5 when mean tree D increased from 10 to 22 cm. At the P and C sites, where mean root:stem ratios were 0.40 and 0.47, respectively, no significant slope in the root:stem to mean tree D relationship was found over a more narrow range in mean tree D (12–15 and 12–18 cm, respectively). Roots were observed in the deepest layers measured (190, 190, and 290 cm for the P, C, and S sites, respectively); however, the asymptotically decreasing root mass per layer indicated the bulk of roots were measured. Root growth relative to stem growth would need to change with increased mean tree D to explain the results observed here. While these changes in growth rate among plant components may differ across sites, stem mass alone does a good job of estimating root mass across sites.