Biosynthesis of rat insulin-like growth factor II. I. Immunochemical demonstration of a approximately 20-kilodalton biosynthetic precursor of rat insulin-like growth factor II in metabolically labeled BRL-3A rat liver cells

BRL-3A rat liver cells synthesize mature 7484-dalton rat insulin-like growth factor II (rIGF-II) as a approximately 22-kDa precursor, presumably prepro-rIGF-II. In the present study, we have biosynthetically labeled intact BRL-3A cells with [35S]cysteine and immunoprecipitated cell lysates and media with antisera to rIGF-II. A approximately 20-kDa protein was identified in immunoprecipitates of cell lysates having properties consistent with pro-rIGF-II. The approximately 20-kDa protein is precipitated by immune sera but not by nonimmune serum. Its immunoprecipitation is specifically inhibited by unlabeled rIGF-II but not by insulin. It is not precipitated from labeled lysates of a subclone of BRL-3A cells (BRL-3A2) that does not synthesize rIGF-II. The approximately 20-kDa protein is rapidly labeled intracellularly (10 min) but is not detected in BRL-3A media. In pulse-chase experiments, radioactivity in the approximately 20-kDa protein disappears during the chase and appears, at later times, in specifically immunoprecipitated approximately 19-, approximately 10-, approximately 8-, and approximately 7-kDa proteins in media and, to a limited extent, intracellularly. A protein with electrophoretic mobility identical to that of the approximately 20-kDa protein observed in cell lysates is immunoprecipitated from 35S-proteins whose synthesis is directed by BRL-3A RNA in a reticulocyte lysate cell-free translation system supplemented with microsomal membranes, and presumably arises by cotranslational removal of the signal peptide from approximately 22-kDa prepro-rIGF-II. Processing of the approximately 20-kDa protein in intact BRL-3A cells to intermediate and mature rIGF-II species appears to occur at the time of secretion and/or shortly thereafter, with the different forms appearing at approximately the same time.     

Comparative Analysis of Endogenous Hormones and Metabolite Profiles in Early-Spring Flowering Plants and Unflowered Plants Revealing the Strategy of Blossom

Journal of Plant Growth Regulation - Early-spring plants are a special type of plant that complete their life cycle promptly in cold, early spring. Very little effort has been made into researching...     

Pollen size-number trade-off and pollen-pistil relationships in Pedicularis (Orobanchaceae)

Current patterns of floral design in Pedicularis must have undergone an evolutionary process of interacting among components of floral traits, and then formed internal relationships among these traits. To detect such correlations, which may provide insight to understand flower evolution, 40 Pedicularis species representing all corolla types of the genus were studied. Results show that, interspecifically, pollen size correlates negatively with pollen number, but positively with pistil length. This suggests that plants evolve an optimal pollen size, which balances the advantages of large pollen size for gametophytic competition against the fecundity disadvantages of fewer pollen grains. In contrast to sex allocation theory, this study does not find a trade-off, but an interspecific positive correlation between pollen and ovule number. This is consistent with the hypothesis that genetic variation for resource acquisition may in part be responsible for the lack of negative correlation between male and female function.This work was supported by the State Key Basic Research and Development Plan, China (Grant No. G2000046804) to YHG. The authors would like to thank Peter K. Endress and two anonymous reviewers for providing critical comments and helpful suggestions, Qing-Feng Wang, Jing-Yuan Wang and Jin-Ming Chen for their helpful suggestions. Shi-Guo Sun, Jing Xia, and Qian Yu are thanked for their assistance in both the field work and laboratory phases of the project.     

Long noncoding RNA PTENP1 affects the recovery of spinal cord injury by regulating the expression of miR-19b and miR-21

Exosomes derived from differentiated P12 cells and MSCs were proved to suppress apoptosis of neuron cells, and phosphatase and tensin homolog pseudogene 1 (PTENP1) was reported to inhibit cell proliferation. In this study, we aimed to investigate the role of PTENP1 in the process of post-spinal cord injury (SCI) recovery, so as to evaluate the therapeutic effects of exosomes derived from MSCs transfected with PTENP1 short hairpin RNA (shRNA), as a type of novel biomarkers in the treatment of SCI. Electron microscopy was used to observe the morphology of different exosomes. Real-time polymerase chain reaction and western blot, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays, flow cytometry, Nissl staining, immunohistochemistry assay, and terminal deoxynucleotidyl transferase dUTP nick end labeling assay were conducted to investigate and validate the underlying molecular signaling pathway. PTENP1-shRNA downregulated PTENP1 and PTEN while upregulating miR-21 and miR-19b. PTENP1-shRNA also accelerated cell apoptosis and reduced cell viability. In addition, PTENP1 reduced the miR-21 and miR-19b expression by directly targeting miR-21 and miR-19b. Meanwhile, both miR-21 and miR-19b reduced the expression of PTEN by directly targeting the 3′-untranslated region of PTEN. Furthermore, PTEN level and apoptosis index of neuron cells was the highest in the SCI group, while the treatment with exosomes+PTENP1-shRNA reduced the PTEN expression to a level similar to that in the sham group. Finally, PTENP1 inhibited miR-21 and miR-19b expression but upregulated PTEN expression. The upregulation of miR-21/miR-19b also suppressed the apoptosis of neuron cells by downregulating the PTEN expression. PTENP1 is involved in the recovery of SCI by regulating the expression of miR-19b and miR-21, and exosomes from PTENP1-shRNA-transfected cells may be used as a novel biomarker in SCI treatment.     

Extracellular vesicles in bone and tooth: A state-of-art paradigm in skeletal regeneration

Bone and tooth, fundamental parts of the craniofacial skeleton, are anatomically and developmentally interconnected structures. Notably, pathological processes in these tissues underwent together and progressed in multilevels. Extracellular vesicles (EVs) are cell-released small organelles and transfer proteins and genetic information into cells and tissues. Although EVs have been identified in bone and tooth, particularly EVs have been identified in the bone formation and resorption, the concrete roles of EVs in bone and tooth development and diseases remain elusive. As such, we review the recent progress of EVs in bone and tooth to highlight the novel findings of EVs in cellular communication, tissue homeostasis, and interventions. This will enhance our comprehension on the skeletal biology and shed new light on the modulation of skeletal disorders and the potential of genetic treatment.     

Synthesis of a novel class of glycocluster with a cyclic α-(1→6)-octaglucoside as a scaffold and their binding abilities to concanavalin A

The synthesis of small glycoclusters with high affinity toward lectins is one of the important subjects in glycotechnology. Although cyclic α-(1→6)-d-octaglucoside (CI8) is an attractive scaffold on which to put glycosyl pendants, the compound has only secondary hydroxyl groups, which are relatively unreactive for substitution reactions. The oxidation of the vicinal diols of CI8 and reductive amination of the resultant dialdehydes with 2-aminoethyl mannoside gave mannose-CI8 conjugates with a variety of average mannose incorporation numbers (2-7). The average numbers were deduced from MALDI-TOF mass and ¹H NMR spectroscopy. The binding ability of mannose-CI8 conjugates to concanavalin A increased with the increasing numbers of average mannose incorporation, reaching a plateau at tetravalence, as estimated from a latex bead-based agglutination lectin assay. Toxicity tests demonstrated the biocompatibility of mannose-CI8 conjugates.     

Genetic diversity and population structure of Swertia tetraptera (Gentianaceae), an endemic species of Qinghai-Tibetan Plateau

Swertia tetraptera Maxim is an annual alpine herb endemic to the Qinghai-Tibetan Plateau (QTP). Its populations are locally scattered as isolated patches throughout this region. Genetic variation within and among thirty-four populations of this species was assessed using ISSR fingerprinting with 10 primers. High levels of genetic diversity exist within species (P = 98.9%, I = 0.3475; He = 0.2227), while the within-population diversity is low (P = 32.7%, I = 0.177; He = 0.12). High levels of genetic differentiation were detected among populations based on various statistics, including Nei’s genetic diversity analysis (G_ST = 0.4608), Bayesian analysis (θ^B = 0.476) and AMOVA (F_ST = 0.57). That is, populations shared low levels of genetic identity (I = 0.2622–0.0966). This genetic structure was probably due to severe genetic drift, breeding system and limited gene flow. The observed genetic structure of the populations implies that different populations across the distribution range of the species should be sampled to maintain high genetic diversity when a conservation strategy is implemented.     

Predicting Metabolic Pathways of Small Molecules and Enzymes Based on Interaction Information of Chemicals and Proteins

Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.