Formation of the autophagosome requires significant membrane input from cellular organelles. However, no direct evidence has been developed to link autophagic factors and the mobilization of membranes to generate the phagophore. Previously, we established a cell-free LC3 lipidation reaction to identify the ER-Golgi intermediate compartment (ERGIC) as a membrane source for LC3 lipidation, a key step of autophagosome biogenesis (Ge et al., eLife 2013; 2:e00947). We now report that starvation activation of autophagic phosphotidylinositol-3 kinase (PI3K) induces the generation of small vesicles active in LC3 lipidation. Subcellular fractionation studies identified the ERGIC as the donor membrane in the generation of small lipidation-active vesicles. COPII proteins are recruited to the ERGIC membrane in starved cells, dependent on active PI3K. We conclude that starvation activates the autophagic PI3K, which in turn induces the recruitment of COPII to the ERGIC to bud LC3 lipidation-active vesicles as one potential membrane source of the autophagosome.

Formation of the autophagosome requires significant membrane input from cellular organelles. However, no direct evidence has been developed to link autophagic factors and the mobilization of membranes to generate the phagophore. Previously, we established a cell-free LC3 lipidation reaction to identify the ER-Golgi intermediate compartment (ERGIC) as a membrane source for LC3 lipidation, a key step of autophagosome biogenesis (Ge et al., eLife 2013; 2:e00947). We now report that starvation activation of autophagic phosphotidylinositol-3 kinase (PI3K) induces the generation of small vesicles active in LC3 lipidation. Subcellular fractionation studies identified the ERGIC as the donor membrane in the generation of small lipidation-active vesicles. COPII proteins are recruited to the ERGIC membrane in starved cells, dependent on active PI3K. We conclude that starvation activates the autophagic PI3K, which in turn induces the recruitment of COPII to the ERGIC to bud LC3 lipidation-active vesicles as one potential membrane source of the autophagosome.

Many machine learning algorithms depend on weights that quantify row and column similarities of a data matrix. The choice of weights can dramatically impact the effectiveness of the algorithm. Nonetheless, the problem of choosing weights has arguably not been given enough study. When a data matrix is completely observed, Gaussian kernel affinities can be used to quantify the local similarity between pairs of rows and pairs of columns. Computing weights in the presence of missing data, however, becomes challenging. In this paper, we propose a new method to construct row and column affinities even when data are missing by building off a co-clustering technique. This method takes advantage of solving the optimization problem for multiple pairs of cost parameters and filling in the missing values with increasingly smooth estimates. It exploits the coupled similarity structure among both the rows and columns of a data matrix. We show these affinities can be used to perform tasks such as data imputation, clustering, and matrix completion on graphs.

Autophagy is a catabolic process for bulk degradation of cytosolic materials mediated by double-membraned autophagosomes. The membrane determinant to initiate the formation of autophagosomes remains elusive. Here, we establish a cell-free assay based on LC3 lipidation to define the organelle membrane supporting early autophagosome formation. In vitro LC3 lipidation requires energy and is subject to regulation by the pathways modulating autophagy in vivo. We developed a systematic membrane isolation scheme to identify the endoplasmic reticulum-Golgi intermediate compartment (ERGIC) as a primary membrane source both necessary and sufficient to trigger LC3 lipidation in vitro. Functional studies demonstrate that the ERGIC is required for autophagosome biogenesis in vivo. Moreover, we find that the ERGIC acts by recruiting the early autophagosome marker ATG14, a critical step for the generation of preautophagosomal membranes. DOI:http://dx.doi.org/10.7554/eLife.00947.001.

The strong interaction between streptavidin (SA) and biotin is widely utilized in biotechnological applications. A SA variant, monovalent SA, was developed with a single and high affinity biotin-binding site within the intact tetramer. However, its structural characterization remains undetermined. Here, we seek to determine the crystal structure of monovalent SA at 1.7-Å resolution. We show that, in contrast to its 'close-state' in the only wild-type subunit, the L3,4 loops of three Dead SA subunits are free from crystal packing and remain in an 'open state', stabilized by a consistent H-bonding network involving S52. This H-bonding network also applies to the previously reported open state of the wild-type apo-SA. These results suggest that specific substitutions (N23A/S27D/S45A) at biotin-binding sites stabilize the open state of SA L3,4 loop, thereby further reducing biotin-binding affinity. The general features of the 'open state' SA among different SA variants may facilitate its rational design. The structural information of monovalent SA will be valuable for its applications across a wide range of biotechnological areas.

Abstract Background Pancreatic cancer is one of the most aggressive human tumors due to its high potential of local invasion and metastasis. The aim of this study was to characterize the membrane proteomes of pancreatic ductal adenocarcinoma (PDAC) cells of primary and metastatic origins, and to identify potential target proteins related to metastasis of pancreatic cancer. Methods Membrane/membrane-associated proteins were isolated from AsPC-1 and BxPC-3 cells and identified with a proteomic approach based on SDS-PAGE, in-gel tryptic digestion and liquid chromatography with tandem mass spectrometry (LC-MS/MS). X! Tandem was used for database searching against the SwissProt human protein database. Results We identified 221 & 208 proteins from AsPC-1 and BxPC-3 cells, respectively, most of which are membrane or membrane-associated proteins. A hundred and nine proteins were found in both cell lines while the others were present in either AsPC-1 or BxPC-3 cells. Differentially expressed proteins between two cell lines include modulators of cell adhesion, cell motility or tumor invasion as well as metabolic enzymes involved in glycolysis, tricarboxylic acid cycle, or nucleotide/lipid metabolism. Conclusion Membrane proteomes of AsPC-1 (metastatic) and BxPC-3 (primary) cells are remarkably different. The differentially expressed membrane proteins may serve as potential targets for diagnostic and therapeutic interventions.

p73, a p53 family tumor suppressor, is regulated by multiple mechanisms, including transcription and mRNA and protein stability. However, whether p73 expression is regulated via mRNA translation has not been explored. To test this, we examined whether ribosomal protein 26 (RPL26) plays a role in p73 expression. Here, we showed that p73 expression is controlled by RPL26 via protein stability and mRNA translation. To examine whether MDM2 mediates RPL26 to regulate p73 protein stability, we generated multiple MDM2-knockout cell lines by CRISPR-cas9. We found that in the absence of MDM2, the half-life of p73 protein is markedly increased. Interestingly, we also found that RPL26 is still capable of regulating p73 expression, albeit to a lesser extent, in MDM2-KO cells compared to that in isogenic control cells, suggesting that RPL26 regulates p73 expression via multiple mechanisms. Indeed, we found that RPL26 is necessary for efficient assembly of polysomes on p73 mRNA and de novo synthesis of p73 protein. Consistently, we found that RPL26 directly binds to p73 3' untranslated region (3'UTR) and that RPL26 is necessary for efficient expression of an eGFP reporter that carries p73 3'UTR. We also found that RPL26 interacts with cap-binding protein eIF4E and enhances the association of eIF4E with p73 mRNA, leading to increased p73 mRNA translation. Finally, we showed that knockdown of RPL26 promotes, whereas ectopic expression of RPL26 inhibits, cell growth in a TAp73-dependent manner. Together, our data indicate that RPL26 regulates p73 expression via two distinct mechanisms: protein stability and mRNA translation.

p73, a p53 family tumor suppressor, is regulated by multiple mechanisms, including transcription and mRNA and protein stability. However, whether p73 expression is regulated via mRNA translation has not been explored. To test this, we examined whether ribosomal protein 26 (RPL26) plays a role in p73 expression. Here, we showed that p73 expression is controlled by RPL26 via protein stability and mRNA translation. To examine whether MDM2 mediates RPL26 to regulate p73 protein stability, we generated multiple MDM2-knockout cell lines by CRISPR-cas9. We found that in the absence of MDM2, the half-life of p73 protein is markedly increased. Interestingly, we also found that RPL26 is still capable of regulating p73 expression, albeit to a lesser extent, in MDM2-KO cells compared to that in isogenic control cells, suggesting that RPL26 regulates p73 expression via multiple mechanisms. Indeed, we found that RPL26 is necessary for efficient assembly of polysomes on p73 mRNA and de novo synthesis of p73 protein. Consistently, we found that RPL26 directly binds to p73 3' untranslated region (3'UTR) and that RPL26 is necessary for efficient expression of an eGFP reporter that carries p73 3'UTR. We also found that RPL26 interacts with cap-binding protein eIF4E and enhances the association of eIF4E with p73 mRNA, leading to increased p73 mRNA translation. Finally, we showed that knockdown of RPL26 promotes, whereas ectopic expression of RPL26 inhibits, cell growth in a TAp73-dependent manner. Together, our data indicate that RPL26 regulates p73 expression via two distinct mechanisms: protein stability and mRNA translation.