Nano rare-earth oxides induced size-dependent vacuolization: an independent pathway from autophagy

Four rare earth oxides have been shown to induce autophagy. Interestingly, we often noticed plentiful vacuolization, which was not always involved in this autophagic process. In this study, we investigated three other rare-earth elements, including Yttrium (Y), Ytterbium (Yb), and Lanthanum (La). Autophagic effect could be induced by all of them but only Y2O3 and Yb2O3 could cause massive vacuolization. Y2O3 and Yb2O3 treated by sonication or centrifugation to reduce particle size were used to test vacuolization level in HeLa cell lines. The results showed that rare earth oxides-induced vacuolization is size-dependent and differs from autophagic pathway. To further clarify the characteristics of this autophagic process, we used MEF Atg-5 (autophagy associated gene 5) knockout cell line, and the result showed that the autophagic process induced by rare earth oxides is Atg-5-dependent and the observed vacuolization was independent from autophagy. Similar results could also be observed in our tests on 3-methyladenine(3-MA), a well-known autophagy inhibitor. In conclusion, for the first time, we clarified the relationship between massive vacuolization and autophagic process induced by rare earth oxides and pointed out the size effect of rare earth oxides on the formation of vacuoles, which give clues to further investigation on the mechanisms underlying their biological effects

Induction of cyto-protective autophagy by paramontroseite VO2 nanocrystals

Chinese Ministry of Sciences 973 Program [2013CB933900]; Natural Science Foundation of China [30830036, 31170966, 31071211]; Fundamental Research Funds for the Central Universities [WK2070000008]A variety of inorganic nanomaterials have been shown to induce autophagy, a cellular degradation process critical for the maintenance of cellular homeostasis. The overwhelming majority of autophagic responses elicited by nanomaterials were detrimental to cell fate and contributed to increased cell death. A widely held view is that the inorganic nanoparticles, when encapsulated and trapped by autophagosomes, may compromise the normal autophagic process due to the inability of the cells to degrade these materials and thus they manifest a detrimental effect on the well-being of a cell. Here we show that, contrary to this notion, nano-sized paramontroseite VO2 nanocrystals (P-VO2) induced cyto-protective, rather than death-promoting, autophagy in cultured HeLa cells. P-VO2 also caused up-regulation of heme oxygenase-1 (HO-1), a cellular protein with a demonstrated role in protecting cells against death under stress situations. The autophagy inhibitor 3-methyladenine significantly inhibited HO-1 up-regulation and increased the rate of cell death in cells treated with P-VO2, while the HO-1 inhibitor protoporphyrin IX zinc (II) (ZnPP) enhanced the occurrence of cell death in the P-VO2-treated cells while having no effect on the autophagic response induced by P-VO2. On the other hand, Y2O3 nanocrystals, a control nanomaterial, induced death-promoting autophagy without affecting the level of expression of HO-1, and the pro-death effect of the autophagy induced by Y2O3. Our results represent the first report on a novel nanomaterial-induced cyto-protective autophagy, probably through up-regulation of HO-1, and may point to new possibilities for exploiting nanomaterial-induced autophagy for therapeutic applications

MiCroKit 3.0: an integrated database of midbody, centrosome and kinetochore

During cell division/mitosis, a specific subset of proteins is spatially and temporally assembled into protein super complexes in three distinct regions, i.e. centrosome/spindle pole, kinetochore/centromere and midbody/cleavage furrow/phragmoplast/bud neck, and modulates cell division process faithfully. Although many experimental efforts have been carried out to investigate the characteristics of these proteins, no integrated database was available. Here, we present the MiCroKit database (http://microkit.biocuckoo.org) of proteins that localize in midbody, centrosome and/or kinetochore. We collected into the MiCroKit database experimentally verified microkit proteins from the scientific literature that have unambiguous supportive evidence for subcellular localization under fluorescent microscope. The current version of MiCroKit 3.0 provides detailed information for 1489 microkit proteins from seven model organisms, including Saccharomyces cerevisiae, Schizasaccharomyces pombe, Caenorhabditis elegans, Drosophila melanogaster, Xenopus laevis, Mus musculus and Homo sapiens. Moreover, the orthologous information was provided for these microkit proteins, and could be a useful resource for further experimental identification. The online service of MiCroKit database was implemented in PHP + MySQL + JavaScript, while the local packages were developed in JAVA 1.5 (J2SE 5.0)

The Genomes of Oryza sativa: A History of Duplications

We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family

C60(Nd) nanoparticles enhance chemotherapeutic susceptibility of cancer cells by modulation of autophagy

Autophagy, an evolutionally conserved intracellular process degrading cytoplasmic proteins and organelles for recycling, has become one of the most remarkable strategies applied in cancer research. The fullerene C60 nanoparticle (nC60) has been shown to induce autophagy and sensitize chemotherapeutic killing of cancer cells, but the details still remain unknown. Here we show that a water-dispersed nanoparticle solution of derivatized fullerene C60, C60(Nd) nanoparticles (nC60(Nd)), has greater potential in inducing autophagy and sensitizing chemotherapeutic killing of both normal and drug-resistant cancer cells than nC60 does in an autophagy-dependent fashion. Additionally we further demonstrated that autophagy induced by nC60/C60(Nd) and Rapamycin had completely different roles in cancer chemotherapy. Our results, for the first time, revealed a novel and more potent derivative of the C60 nanoparticle in enhancing the cytotoxicity of chemotherapeutic agents and reducing drug resistance through autophagy modulation, which may ultimately lead to novel therapeutic strategies in cancer therapy

GPS 2.0, a Tool to Predict Kinase-specific Phosphorylation Sites in Hierarchy *S⃞

Identification of protein phosphorylation sites with their cognate protein kinases (PKs) is a key step to delineate molecular dynamics and plasticity underlying a variety of cellular processes. Although nearly 10 kinase-specific prediction programs have been developed, numerous PKs have been casually classified into subgroups without a standard rule. For large scale predictions, the false positive rate has also never been addressed. In this work, we adopted a well established rule to classify PKs into a hierarchical structure with four levels, including group, family, subfamily, and single PK. In addition, we developed a simple approach to estimate the theoretically maximal false positive rates. The on-line service and local packages of the GPS (Group-based Prediction System) 2.0 were implemented in Java with the modified version of the Group-based Phosphorylation Scoring algorithm. As the first stand alone software for predicting phosphorylation, GPS 2.0 can predict kinase-specific phosphorylation sites for 408 human PKs in hierarchy. A large scale prediction of more than 13,000 mammalian phosphorylation sites by GPS 2.0 was exhibited with great performance and remarkable accuracy. Using Aurora-B as an example, we also conducted a proteome-wide search and provided systematic prediction of Aurora-B-specific substrates including protein-protein interaction information. Thus, the GPS 2.0 is a useful tool for predicting protein phosphorylation sites and their cognate kinases and is freely available on line

GPS-SNO: computational prediction of protein S-nitrosylation sites with a modified GPS algorithm.

As one of the most important and ubiquitous post-translational modifications (PTMs) of proteins, S-nitrosylation plays important roles in a variety of biological processes, including the regulation of cellular dynamics and plasticity. Identification of S-nitrosylated substrates with their exact sites is crucial for understanding the molecular mechanisms of S-nitrosylation. In contrast with labor-intensive and time-consuming experimental approaches, prediction of S-nitrosylation sites using computational methods could provide convenience and increased speed. In this work, we developed a novel software of GPS-SNO 1.0 for the prediction of S-nitrosylation sites. We greatly improved our previously developed algorithm and released the GPS 3.0 algorithm for GPS-SNO. By comparison, the prediction performance of GPS 3.0 algorithm was better than other methods, with an accuracy of 75.80%, a sensitivity of 53.57% and a specificity of 80.14%. As an application of GPS-SNO 1.0, we predicted putative S-nitrosylation sites for hundreds of potentially S-nitrosylated substrates for which the exact S-nitrosylation sites had not been experimentally determined. In this regard, GPS-SNO 1.0 should prove to be a useful tool for experimentalists. The online service and local packages of GPS-SNO were implemented in JAVA and are freely available at: http://sno.biocuckoo.org/