Advances in structural and functional analysis of membrane proteins by electron crystallography

Electron crystallography is a powerful technique for the study of membrane protein structure and function in the lipid environment. When well-ordered two-dimensional crystals are obtained the structure of both protein and lipid can be determined and lipid-protein interactions analyzed. Protons and ionic charges can be visualized by electron crystallography and the protein of interest can be captured for structural analysis in a variety of physiologically distinct states. This review highlights the strengths of electron crystallography and the momentum that is building up in automation and the development of high throughput tools and methods for structural and functional analysis of membrane proteins by electron crystallography.     

Multilineage hemopoiesis induced by cloned stromal cells

Long-term hemopoiesis in culture depends upon the presence of an adherent layer composed of a variety of stromal cells. A subtype of endothelial-adipocytes from the bone marrow stroma (clone 14F1.1) was previously shown to induce long-term myelopoiesis and renewal of pluripotent stem cells. One of a series of stromal cell lines and clones from mouse thymus stroma (STAC-1.2) has now been found to support long-term hemopoiesis. These marrow- and thymus-derived stromal cell clones also have lymphopoietic activities: precursor T cells, or pre-B cells accumulated in co-cultures of thymus cells and the stromal clones, as indicated by cell surface markers, T cell receptor and immunoglobulin gene rearrangements. The predominance of a cell type in these cultures depended upon the serum used to supplement the medium. Recombinant interleukin 2 (IL-2) and the 14F1.1 clone synergistically promoted the proliferation of thymocytes, while a thymus hormone, THF-gamma 2, shifted the population to a relatively mature phenotype. It is proposed that one major function of stromal cells, whether from the bone marrow or thymus, is to restrain the maturation flow and preferentially support the accumulation of cells at early differentiation stages.     

Genome-scale analysis of translation elongation with a ribosome flow model

We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative ('non-physical') approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host.     

Unravelling the twists and turns of the serpinopathies

Members of the serine protease inhibitor (serpin) superfamily are found in all branches of life and play an important role in the regulation of enzymes involved in proteolytic cascades. Mutants of the serpins result in a delay in folding, with unstable intermediates being cleared by endoplasmic reticulum-associated degradation. The remaining protein is either fully folded and secreted or retained as ordered polymers within the endoplasmic reticulum of the cell of synthesis. This results in a group of diseases termed the serpinopathies, which are typified by mutations of α(1)-antitrypsin and neuroserpin in association with cirrhosis and the dementia familial encephalopathy with neuroserpin inclusion bodies, respectively. Current evidence strongly suggests that polymers of mutants of α(1)-antitrypsin and neuroserpin are linked by the sequential insertion of the reactive loop of one molecule into β-sheet A of another. The ordered structure of the polymers within the endoplasmic reticulum stimulates nuclear factor-kappa B by a pathway that is independent of the unfolded protein response. This chronic activation of nuclear factor-kappa B may contribute to the cell toxicity associated with mutations of the serpins. We review the pathobiology of the serpinopathies and the development of novel therapeutic strategies for treating the inclusions that cause disease. These include the use of small molecules to block polymerization, stimulation of autophagy to clear inclusions and stem cell technology to correct the underlying molecular defect.     

Serum apolipoproteins C-I and C-III are reduced in stomach cancer patients: results from MALDI-based peptidome and immuno-based clinical assays

Finding new peptide biomarkers for stomach cancer in human sera that can be implemented into a clinically practicable prediction method for monitoring of stomach cancer. We studied the serum peptidome from two different biorepositories. We first employed a C8-reverse phase liquid chromatography approach for sample purification, followed by mass-spectrometry analysis. These were applied onto serum samples from cancer-free controls and stomach cancer patients at various clinical stages. We then created a bioinformatics analysis pipeline and identified peptide signature discriminating stomach adenocarcinoma patients from cancer-free controls. Matrix Assisted Laser Desorption/Ionization-Time of Flight (MALDI-TOF) results from 103 samples revealed 9 signature peptides; with prediction accuracy of 89% in the training set and 88% in the validation set. Three of the discriminating peptides discovered were fragments of Apolipoproteins C-I and C-III (apoC-I and C-III); we further quantified their serum levels, as well as CA19-9 and CRP, employing quantitative commercial-clinical assays in 142 samples. ApoC-I and apoC-III quantitative results correlated with the MS results. We then employed apoB-100-normalized apoC-I and apoC-III, CA19-9 and CRP levels to generate rules set for stomach cancer prediction. For training, we used sera from one repository, and for validation, we used sera from the second repository. Prediction accuracies of 88.4% and 74.4% were obtained in the training and validation sets, respectively. Serum levels of apoC-I and apoC-III combined with other clinical parameters can serve as a basis for the formulation of a diagnostic score for stomach cancer patients.     

Composite effects of gene determinants on the translation speed and density of ribosomes

Background  

Translation is a central process of life, and its regulation is crucial for cell growth. In this article, focusing on two model organisms, Escherichia coli and Saccharomyces cerevisiae, we study how three major local features of a gene's coding sequence (its adaptation to the tRNA pool, its amino acid charge, and its mRNA folding energy) affect its translation elongation.