Tissue-specific autophagy alterations and increased tumorigenesis in mice deficient in Atg4C/autophagin-3

Atg4C/autophagin-3 is a member of a family of cysteine proteinases proposed to be involved in the processing and delipidation of the mammalian orthologues of yeast Atg8, an essential component of an ubiquitin-like modification system required for execution of autophagy. To date, the in vivo role of the different members of this family of proteinases remains unclear. To gain further insights into the functional relevance of Atg4 orthologues, we have generated mutant mice deficient in Atg4C/autophagin-3. These mice are viable and fertile and do not display any obvious abnormalities, indicating that they are able to develop the autophagic response required during the early neonatal period. However, Atg4C-/--starved mice show a decreased autophagic activity in the diaphragm as assessed by immunoblotting studies and by fluorescence microscopic analysis of samples from Atg4C-/- GFP-LC3 transgenic mice. In addition, animals deficient in Atg4C show an increased susceptibility to develop fibrosarcomas induced by chemical carcinogens. Based on these results, we propose that Atg4C is not essential for autophagy development under normal conditions but is required for a proper autophagic response under stressful conditions such as prolonged starvation. We also propose that this enzyme could play an in vivo role in events associated with tumor progression.     

Application of cationic conjugated polymers in microarrays using label-free DNA targets

A fluorescence-based microarray technique that does not require target DNA labeling is detailed. This 'label-free' approach utilizes a cationic, water-soluble conjugated polymer PFBT (poly[9,9'-bis(6'-(N,N,N-trimethylammonium)hexyl)fluorene-co-alt-4,7-(2,1,3-benzothiadiazole) dibromide]), and neutral PNA (peptide nucleic acid) hybridization probes. DNA hybridization to immobilized PNA spots results in a change in the net charge at that particular surface. Electrostatic interactions between the cationic polymer and negatively charged DNA bind the polymer to the hybrid DNA/PNA complex. By exciting the conjugated polymer at 488 nm on a commercial microarray scanner, the presence of the target is directly indicated by the fluorescence emission of the polymer. This feature eliminates the necessity of target labeling required in traditional microarray protocols. There are five steps involved in the procedure before scanning or imaging the array: (i) slide hydration, (ii) target hybridization, (iii) post-hybridization washing, (iv) polymer application and (v) polymer washing. Each step takes 20 min to 1 h. The overall protocol requires approximately 2-3 h.     

Short allele of serotonin transporter gene promoter is a risk factor for obesity in adolescents

Obesity and hypertension are increasing medical problems in adolescents. Serotonin transporter (5-HTT) is involved in mood and eating disturbances. Encoded by the gene SLC6A4, the promoter shows functional insertion/deletion alleles: long (L) and short (S). Because individuals who are carriers for the short version are known to be at risk for higher levels of anxiety, we hypothesized that this variant may be associated with overweight. Data and blood samples were collected from 172 adolescents out of a cross-sectional, population-based study of 934 high school students. To replicate the findings, we also included 119 outpatients from the Nutrition and Diabetes Section of the Children's County Hospital. We found that the S allele was associated with overweight (BMI > 85th percentile), being a risk factor for overweight independently of sex, age, and hypertension [odds ratio (OR): 1.85; 95% confidence interval (CI): 1.13, 3.05; p < 0.02]. Additionally, in the outpatient study, compared with the homozygous LL subjects, S allele carriers showed a higher BMI z-score (1.47 +/- 1.09 vs. 0.51 +/- 1.4; p < 0.002) and were more frequent in overweight children. In conclusion, the S allele of the SLC6A4 promoter variant is associated with overweight being an independent genetic risk factor for obesity.     

Effects of sample re-sequencing and trimming on the quality and size of assembled consensus sequences

The production of nucleic acid sequences by automatic DNA sequencer machines is always associated with some base-calling errors. In order to produce a high-quality DNA sequence from a molecule of interest, researchers normally sequence the same sample many times. Considering base-calling errors as rare events, re-sequencing the same molecule and assembling the reads produced are frequently thought to be a good way to generate reliable sequences. However, a relevant question on this issue is: how many times the sample needs to be re-sequenced to minimize costs and achieve a high-fidelity sequence? We examined how both the number of re-sequenced reads and PHRED trimming parameters affect the accuracy and size of final consensus sequences. Hundreds of single-pool reaction pUC18 reads were generated and assembled into consensus sequences with CAP3 software. Using local alignment against the published pUC18 cloning vector sequence, the position and number of errors in the consensus were identified and stored in MySQL databases. Stringent PHRED trimming parameters proved to be efficient for the reduction of errors; however, this procedure also decreased consensus size. Moreover, re-sequencing did not have a clear effect on the removal of consensus errors, although it was able to slightly increase consensus.     

Identification of novel bacterial plasminogen-binding proteins in the human pathogen Mycobacterium tuberculosis

Binding and activation of human plasminogen (Plg) to generate the proteolytic enzyme plasmin (Plm) have been associated with the invasive potential of certain bacteria. In this work, proteomic analysis together with ligand blotting assays identified several major Plg-binding spots in Mycobacterium tuberculosis soluble extracts (SEs) and culture filtrate proteins. The identity of 15 different proteins was deduced by N-terminal and/or MS and corresponded to DnaK, GroES, GlnA1, Ag85 complex, Mpt51, Mpt64, PrcB, MetK, SahH, Lpd, Icl, Fba, and EF-Tu. Binding of Plg to recombinant M. tuberculosis DnaK, GlnA1, and Ag85B was further confirmed by ELISA and ligand blotting assays. The binding was inhibited by epsilon-aminocaproic acid, indicating that the interaction involved lysine residues. Plg bound to recombinant mycobacterial proteins was activated to Plm by tissue-type Plg activator. In contrast with recombinant proteins, M. tuberculosis SE enhanced several times the Plg activation mediated by the activator. Interestingly, GlnA1 was able to bind the extracellular matrix (ECM) protein fibronectin. Together these results show that M. tuberculosis posses several Plg receptors suggesting that bound Plg to bacteria surface, can be activated to Plm, endowing bacteria with the ability to break down ECM and basal membranes proteins contributing to tissue injury in tuberculosis.     

Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells

Proteomics strategies based on nanoflow (nano-) LC-MS/MS allow the identification of hundreds to thousands of proteins in complex mixtures. When combined with protein isotopic labeling, quantitative comparison of the proteome from different samples can be achieved using these approaches. However, bioinformatics analysis of the data remains a bottleneck in large scale quantitative proteomics studies. Here we present a new software named Mascot File Parsing and Quantification (MFPaQ) that easily processes the results of the Mascot search engine and performs protein quantification in the case of isotopic labeling experiments using either the ICAT or SILAC (stable isotope labeling with amino acids in cell culture) method. This new tool provides a convenient interface to retrieve Mascot protein lists; sort them according to Mascot scoring or to user-defined criteria based on the number, the score, and the rank of identified peptides; and to validate the results. Moreover the software extracts quantitative data from raw files obtained by nano-LC-MS/MS, calculates peptide ratios, and generates a non-redundant list of proteins identified in a multisearch experiment with their calculated averaged and normalized ratio. Here we apply this software to the proteomics analysis of membrane proteins from primary human endothelial cells (ECs), a cell type involved in many physiological and pathological processes including chronic inflammatory diseases such as rheumatoid arthritis. We analyzed the EC membrane proteome and set up methods for quantitative analysis of this proteome by ICAT labeling. EC microsomal proteins were fractionated and analyzed by nano-LC-MS/MS, and database searches were performed with Mascot. Data validation and clustering of proteins were performed with MFPaQ, which allowed identification of more than 600 unique proteins. The software was also successfully used in a quantitative differential proteomics analysis of the EC membrane proteome after stimulation with a combination of proinflammatory mediators (tumor necrosis factor-alpha, interferon-gamma, and lymphotoxin alpha/beta) that resulted in the identification of a full spectrum of EC membrane proteins regulated by inflammation.