Hormone-induced 14-3-3γ adaptor protein regulates steroidogenic acute regulatory protein activity and steroid biosynthesis in MA-10 Leydig cells

Cholesterol is the sole precursor of steroid hormones in the body. The import of cholesterol to the inner mitochondrial membrane, the rate-limiting step in steroid biosynthesis, relies on the formation of a protein complex that assembles at the outer mitochondrial membrane called the transduceosome. The transduceosome contains several mitochondrial and cytosolic components, including the steroidogenic acute regulatory protein (STAR). Human chorionic gonadotropin (hCG) induces de novo synthesis of STAR, a process shown to parallel maximal steroid production. In the hCG-dependent steroidogenic MA-10 mouse Leydig cell line, the 14-3-3γ protein was identified in native mitochondrial complexes by mass spectrometry and immunoblotting, and its levels increased in response to hCG treatment. The 14-3-3 proteins bind and regulate the activity of many proteins, acting via target protein activation, modification and localization. In MA-10 cells, cAMP induces 14-3-3γ expression parallel to STAR expression. Silencing of 14-3-3γ expression potentiates hormone-induced steroidogenesis. Binding motifs of 14-3-3γ were identified in components of the transduceosome, including STAR. Immunoprecipitation studies demonstrate a hormone-dependent interaction between 14-3-3γ and STAR that coincides with reduced 14-3-3γ homodimerization. The binding site of 14-3-3γ on STAR was identified to be Ser-194 in the STAR-related sterol binding lipid transfer (START) domain, the site phosphorylated in response to hCG. Taken together, these results demonstrate that 14-3-3γ negatively regulates steroidogenesis by binding to Ser-194 of STAR, thus keeping STAR in an unfolded state, unable to induce maximal steroidogenesis. Over time 14-3-3γ homodimerizes and dissociates from STAR, allowing this protein to induce maximal mitochondrial steroid formation.     

用胆固醇代谢的房室模型速率系数来分析动脉粥样硬化程度

理论上认为胆固醇逆向转运的速率与动脉粥样硬化程序呈负相关。但目前尚无完善的测试血浆脂蛋白－胆固醇体内代谢的方法。我们运用同位素＾３Ｈ－胆固醇示踪方法,建立房室模型,选取健康兔与ＡＳ兔对照,研究血浆脂蛋白转运胆固醇能力的差异,并结合ＡＳ兔主动脉斑块程度对比,结果验证了上述理论,此法如改用短半衰期同位素或稳定性同位素标记的胆固醇,就可用于人体,这可为临床判断ＡＳ程度提供一种无创性的新方法。     

壶腹周围憩室对胆总管结石患者结石成分及胆道菌群的影响

探究壶腹周围憩室(periampullary diverticulum, PAD)对胆总管结石成分及胆道菌群的影响。

收集我院行内镜下取石治疗患者44例, 其中14例伴有PAD、30例无PAD, 使用红外光谱法和分光光度法分析结石样本中胆固醇、胆红素含量。从入组患者中分别筛选8例伴有PAD的患者为PAD组, 8例无PAD的为对照组, 收集患者胆汁样本, 提取样本中菌群DNA进行扩增并构建细菌基因文库, 经Illumina MiSeq平台高通量测序后进行生物信息学分析。最后对差异菌群与胆红素、胆固醇进行相关性分析。

2组患者对比年龄、胆管直径、结石直径和总胆红素(TBIL)等资料差异均无统计学意义(均P > 0.05)。2组患者结石中胆固醇和胆红素含量[(39.77±13.00)%vs(61.80±26.00)%, Z=-2.973, P=0.003;(27.03±13.00)%vs(12.27±16.00)%, Z=-2.999, P=0.003)差异存在统计学意义。PAD组与对照组Alpha多样性差异无统计学意义(P > 0.05), 而在物种群落组成上存在差异。卟啉单胞菌属、嗜胆菌属等10种菌属在PAD组中的丰度高于对照组, 真杆菌属、乳杆菌属较对照组降低, 差异均有统计学意义(均P < 0.05)。相较于对照组, PAD组牛磺酸和次牛磺酸的代谢、钙信号通路等5条通路差异存在统计学意义(均P < 0.05)。嗜胆菌属和卟啉单胞菌属与胆红素具有相关性(R²=0.701 3, P < 0.000 1;R²=0.286 8, P=0.032 5)。

伴有PAD的患者结石含有更高的胆红素成分。PAD的存在改变胆道菌群多样性、构成及丰度, 并可能通过菌群变化影响结石成分。

     

Cholesterol trafficking and raft-like membrane domain composition mediate scavenger receptor class B type 1-dependent lipid sensing in intestinal epithelial cells

Scavenger receptor Class B type 1 (SR-B1) is a lipid transporter and sensor. In intestinal epithelial cells, SR-B1-dependent lipid sensing is associated with SR-B1 recruitment in raft-like/ detergent-resistant membrane domains and interaction of its C-terminal transmembrane domain with plasma membrane cholesterol. To clarify the initiating events occurring during lipid sensing by SR-B1, we analyzed cholesterol trafficking and raft-like domain composition in intestinal epithelial cells expressing wild-type SR-B1 or the mutated form SR-B1-Q445A, defective in membrane cholesterol binding and signal initiation. These features of SR-B1 were found to influence both apical cholesterol efflux and intracellular cholesterol trafficking from plasma membrane to lipid droplets, and the lipid composition of raft-like domains. Lipidomic analysis revealed likely participation of d18:0/16:0 sphingomyelin and 16:0/0:0 lysophosphatidylethanolamine in lipid sensing by SR-B1. Proteomic analysis identified proteins, whose abundance changed in raft-like domains during lipid sensing, and these included molecules linked to lipid raft dynamics and signal transduction. These findings provide new insights into the role of SR-B1 in cellular cholesterol homeostasis and suggest molecular links between SR-B1-dependent lipid sensing and cell cholesterol and lipid droplet dynamics.     

Biomarkers in critically ill patients with systemic inflammatory response syndrome or sepsis supplemented with high-dose selenium

ObjectiveLow levels of selenium (Se) and glutathione peroxidase (GSHPx), a key selenoenzyme, were documented in systemic inflammatory response syndrome (SIRS) and sepsis, both associated with high mortality. Se supplementation had mixed effects on outcome. We hypothesized that Se supplementation could have a different impact on biomarkers and 28-day mortality in patients with SIRS vs. sepsis.MethodsAdult patients with SIRS or sepsis were randomized to either high-dose (Se+, n = 75) or standard-dose (Se−, n = 75) Se supplementation. Plasma Se, whole blood GSHPx activity, C-reactive protein (CRP), procalcitonin (PCT), prealbumin, albumin and cholesterol levels were measured serially up to day 14.ResultsThere was no difference in mortality between Se− (24/75) vs. Se+ group (19/75; p = 0.367) or between SIRS and septic patients (8/26 vs. 35/124; p = 0.794). There was a trend to reduced mortality in SIRS patients in the Se+ vs. Se− group (p = 0.084). Plasma Se levels increased in the Se+ group only in patients with sepsis but not in patients with SIRS. Plasma Se levels correlated with GSHPx. In SIRS/Se+ group, Se correlated only with GSHPx. In SIRS/Se− group, Se correlated with cholesterol but not with other biomarkers. In sepsis patients, Se levels correlated with cholesterol, GSHPx and prealbumin. Cholesterol levels were higher in survivors in the Se− group.ConclusionsSe levels correlated with GSHPx activity and other nutritional biomarkers with significant differences between SIRS and sepsis groups. High-dose Se supplementation did not affect mortality but a strong trend to decreased mortality in SIRS patients warrants further studies in this population.     

The pore-lining regions in cytochrome c oxidases: A computational analysis of caveolin,cholesterol and transmembrane helix contributions to proton movement

Cytochrome c oxidase (CcO) is the terminal enzyme in the electron transfer chain. CcO catalyzes a four electron reduction of O₂ to water at a catalytic site formed by high-spin heme (a₃) and copper atoms (Cu_B). While it is recognized that proton movement is coupled to oxygen reduction, the proton channel(s) have not been well defined. Using computational methods developed to study protein topology, membrane channels and 3D packing arrangements within transmembrane (TM) helix arrays, we find that subunit-1 (COX-1), subunit-2 (COX-2) and subunit-3 (COX-3) contribute 139, 46 and 25 residues, respectively, to channel formation between the mitochondrial matrix and intermembrane space. Nine of 12 TM helices in COX-1, both helices in COX-2 and 5 of the 6 TM helices in COX-3 are pore-lining regions (possible channel formers). Heme a₃ and the Cu_B sites (as well as the Cu_A center of COX-2) are located within the channel that includes TM-6, TM-7, TM-10 and TM-11 of COX-1 and are associated with multiple cholesterol and caveolin-binding (CB) motifs. Sequence analysis identifies five CB motifs within COX-1, two within COX-2 and four within COX-3; each caveolin containing a pore-lining helix C-terminal to a TM helix–turn–helix. Channel formation involves interaction between multiple pore-lining regions within protein subunits and/or dimers. PoreWalker analysis lends support to the D-channel model of proton translocation. Under physiological conditions, caveolins may introduce channel formers juxtaposed to those in COX-1, COX-2 and COX-3, which together with cholesterol may form channel(s) essential for proton translocation through the inner mitochondrial membrane.     

Peroxisomal cholesterol biosynthesis and Smith-Lemli-Opitz syndrome

Smith-Lemli-Opitz syndrome (SLOS), caused by 7-dehydrocholesterol-reductase (DHCR7) deficiency, shows variable severity independent of DHCR7 genotype. To test whether peroxisomes are involved in alternative cholesterol synthesis, we used [1-(14)C]C24:0 for peroxisomal beta-oxidation to generate [1-(14)C]acetyl-CoA as cholesterol precursor inside peroxisomes. The HMG-CoA reductase inhibitor lovastatin suppressed cholesterol synthesis from [2-(14)C]acetate and [1-(14)C]C8:0 but not from [1-(14)C]C24:0, implicating a peroxisomal, lovastatin-resistant HMG-CoA reductase. In SLOS fibroblasts lacking DHCR7 activity, no cholesterol was formed from [1-(14)C]C24:0-derived [1-(14)C]acetyl-CoA, indicating that the alternative peroxisomal pathway also requires this enzyme. Our results implicate peroxisomes in cholesterol biosynthesis but provide no link to phenotypic variation in SLOS.     

Correlation between faecal microbial community structure and cholesterol-to-coprostanol conversion in the human gut

Intensity of the cholesterol-to-coprostanol conversion in the intestine, as assessed by the coprostanol-to-cholesterol ratio in faeces, was found highly variable among 15 human volunteers, ranging from absent to almost complete cholesterol conversion. The number of coprostanoligenic bacteria in the same faecal samples, as estimated by the most probable number method, was found to be less than 10(6) cellsg-1 of fresh stools in the low-to-inefficient converters and at least 10(8) cellsg-1 of fresh stools in the highest converters, indicating that the population level of cultivable faecal coprostanoligenic bacteria correlated with the intensity of cholesterol-to-coprostanol conversion in the human gut. Microbial communities of the samples were profiled by temporal temperature gradient gel electrophoresis (TTGE) of bacterial 16S rRNA gene amplicons. Dendrogram analysis of the TTGE profiles using the Pearson product moment correlation coefficient and a unweighted pair group method with arithmetic averages (UPGMA) algorithm clearly separated banding patterns from low-to-inefficient and high converters in two different clusters suggesting a relationship between TTGE profiles and coprostanoligenic activity. Principal components analysis further demonstrated that a large subset of bands rather than some individual bands contributed to this clustering.