Label-free quantification and shotgun analysis of complex proteomes by one-dimensional SDS-PAGE/NanoLC-MS: evaluation for the large scale analysis of inflammatory human endothelial cells

To perform differential studies of complex protein mixtures, strategies for reproducible and accurate quantification are needed. Here, we evaluated a quantitative proteomic workflow based on nanoLC-MS/MS analysis on an LTQ-Orbitrap-VELOS mass spectrometer and label-free quantification using the MFPaQ software. In such label-free quantitative studies, a compromise has to be found between two requirements: repeatability of sample processing and MS measurements, allowing an accurate quantification, and high proteomic coverage of the sample, allowing quantification of minor species. The latter is generally achieved through sample fractionation, which may induce experimental bias during the label-free comparison of samples processed, and analyzed independently. In this work, we wanted to evaluate the performances of MS intensity-based label-free quantification when a complex protein sample is fractionated by one-dimensional SDS-PAGE. We first tested the efficiency of the analysis without protein fractionation and could achieve quite good quantitative repeatability in single-run analysis (median coefficient of variation of 5%, 99% proteins with coefficient of variation <48%). We show that sample fractionation by one-dimensional SDS-PAGE is associated with a moderate decrease of quantitative measurement repeatability while largely improving the depth of proteomic coverage. We then applied the method for a large scale proteomic study of the human endothelial cell response to inflammatory cytokines, such as TNFα, interferon γ, and IL1β, which allowed us to finely decipher at the proteomic level the biological pathways involved in endothelial cell response to proinflammatory cytokines.     

Cross-Sectional and Longitudinal Associations of Different Sedentary Behaviors with Cognitive Performance in Older Adults

Background

The deleterious health effects of sedentary behaviors, independent of physical activity, are increasingly being recognized. However, associations with cognitive performance are not known.

Purpose

To estimate the associations between different sedentary behaviors and cognitive performance in healthy older adults.

Methods

Computer use, time spent watching television (TV), time spent reading and habitual physical activity levels were self-reported twice (in 2001 and 2007) by participants in the SUpplémentation en Vitamines et MinérauX (SU.VI.MAX and SU.VI.MAX2) study. Cognitive performance was assessed at follow-up (in 2007–2009) via a battery of 6 neuropsychological tests used to derive verbal memory and executive functioning scores. Analyses (ANCOVA) were performed among 1425 men and 1154 women aged 65.6±4.5 at the time of the neuropsychological evaluation. We estimated mean differences with 95% confidence intervals (95%CI) in cognitive performance across categories of each type of sedentary behavior.

Results

In multivariable cross-sectional models, compared to non-users, participants using the computer for >1 h/day displayed better verbal memory (mean difference = 1.86; 95%CI: 0.95, 2.77) and executive functioning (mean difference = 2.15; 95%CI: 1.22, 3.08). A negative association was also observed between TV viewing and executive functioning. Additionally, participants who increased their computer use by more than 30 min between 2001 and 2007 showed better performance on both verbal memory (mean difference = 1.41; 95%CI: 0.55, 2.27) and executive functioning (mean difference = 1.41; 95%CI: 0.53, 2.28) compared to those who decreased their computer use during that period.

Conclusion

Specific sedentary behaviors are differentially associated with cognitive performance. In contrast to TV viewing, regular computer use may help maintain cognitive function during the aging process.

Clinical Trial Registration

clinicaltrial.gov (number {"type":"clinical-trial","attrs":{"text":"NCT00272428","term_id":"NCT00272428"}}NCT00272428).     

Acetaldehyde-induced mutational pattern in the tumour suppressor gene TP53 analysed by use of a functional assay, the FASAY (functional analysis of separated alleles in yeast)

Chronic alcohol consumption is a major risk factor for upper aero-digestive tract cancers, including cancer of the esophagus. Whereas alcohol as such is not thought to be directly carcinogenic, acetaldehyde, its first metabolite, has been proven genotoxic and mutagenic in the HPRT gene. As mutations in the tumour suppressor gene TP53 are the most common genetic alterations involved in human cancers, especially esophageal tumours, the aim of this work was to establish the mutational pattern induced by acetaldehyde in vitro on the TP53 gene, and to compare this pattern with that found in human alcohol-related tumours. For this purpose, we used a functional assay in yeast, the FASAY (functional analysis of separated alleles in yeast), after in vitro exposure of human normal fibroblasts AG1521 to acetaldehyde. We noted 35 mutations, of which 32 were single-nucleotide substitutions including 2 nonsense and 30 missense mutations. The pattern showed that the main mutations were G>A transitions (n=23, of which 14 in CpG sites), followed by G>T transversions (n=4), A>G transitions (n=2) and A>T transversions (n=2). Other mutations were one-base insertion and two deletions, leading to frameshifts. Eleven mutations (31%) were located in TP53 hot-spots in codons 245, 248, 249 and 273. Finally, we compared this pattern with that found for esophageal cancers in humans. These results support the notion that acetaldehyde plays a role in TP53 mutations in esophageal cancers. The key feature of this approach is that mutagenesis is directly studied in a key gene in human carcinogenesis, allowing direct comparison of mutational patterns with those in human tumours.     

The N-terminal domain of mammalian Lysyl-tRNA synthetase is a functional tRNA-binding domain.

Lysyl-tRNA synthetase from higher eukaryotes possesses a lysine-rich N-terminal polypeptide extension appended to a classical prokaryotic-like LysRS domain. Band shift analysis showed that this extra domain provides LysRS with nonspecific tRNA binding properties. A N-terminally truncated derivative of LysRS, LysRS-DeltaN, displayed a 100-fold lower apparent affinity for tRNA(3)Lys and a 3-fold increase in K(m) for tRNA(3)Lys in the aminoacylation reaction, as compared with the native enzyme. The isolated N-domain of LysRS also displayed weak affinity for tRNA, suggesting that the catalytic and N-domains of LysRS act synergistically to provide a high affinity binding site for tRNA. A more detailed analysis revealed that LysRS binds and specifically aminoacylates an RNA minihelix mimicking the amino acid acceptor stem-loop structure of tRNA(3)Lys, whereas LysRS-DeltaN did not. As a consequence, merging an additional RNA-binding domain into a bacterial-like LysRS increases the catalytic efficiency of the enzyme, especially at the low concentration of deacylated tRNA prevailing in vivo. Our results provide new insights into tRNA(Lys) channeling in eukaryotic cells and shed new light on the possible requirement of native LysRS for triggering tRNA(3)Lys packaging into human immunodeficiency virus, type 1 viral particles.     

The Arabidopsis BLAP75/Rmi1 Homologue Plays Crucial Roles in Meiotic Double-Strand Break Repair

In human cells and in Saccharomyces cerevisiae, BLAP75/Rmi1 acts together with BLM/Sgs1 and TopoIIIα/Top3 to maintain genome stability by limiting crossover (CO) formation in favour of NCO events, probably through the dissolution of double Holliday junction intermediates (dHJ). So far, very limited data is available on the involvement of these complexes in meiotic DNA repair. In this paper, we present the first meiotic study of a member of the BLAP75 family through characterisation of the Arabidopsis thaliana homologue. In A. thaliana blap75 mutants, meiotic recombination is initiated, and recombination progresses until the formation of bivalent-like structures, even in the absence of ZMM proteins. However, chromosome fragmentation can be detected as soon as metaphase I and is drastic at anaphase I, while no second meiotic division is observed. Using genetic and imunolocalisation studies, we showed that these defects reflect a role of A. thaliana BLAP75 in meiotic double-strand break (DSB) repair—that it acts after the invasion step mediated by RAD51 and associated proteins and that it is necessary to repair meiotic DSBs onto sister chromatids as well as onto the homologous chromosome. In conclusion, our results show for the first time that BLAP75/Rmi1 is a key protein of the meiotic homologous recombination machinery. In A. thaliana, we found that this protein is dispensable for homologous chromosome recognition and synapsis but necessary for the repair of meiotic DSBs. Furthermore, in the absence of BLAP75, bivalent formation can happen even in the absence of ZMM proteins, showing that in blap75 mutants, recombination intermediates exist that are stable enough to form bivalent structures, even when ZMM are absent.     

pyActigraphy: Open-source python package for actigraphy data visualization and analysis

Over the past 40 years, actigraphy has been used to study rest-activity patterns in circadian rhythm and sleep research. Furthermore, considering its simplicity of use, there is a growing interest in the analysis of large population-based samples, using actigraphy. Here, we introduce pyActigraphy, a comprehensive toolbox for data visualization and analysis including multiple sleep detection algorithms and rest-activity rhythm variables. This open-source python package implements methods to read multiple data formats, quantify various properties of rest-activity rhythms, visualize sleep agendas, automatically detect rest periods and perform more advanced signal processing analyses. The development of this package aims to pave the way towards the establishment of a comprehensive open-source software suite, supported by a community of both developers and researchers, that would provide all the necessary tools for in-depth and large scale actigraphy data analyses.     

Efficiency of genomic selection for tomato fruit quality

Fruit quality is polygenic; each component has variable heritability and is difficult to assess. Genomic selection, which allows the prediction of phenotypes based on the whole-genome genotype, could vastly help to improve fruit quality. The goal of this study is to evaluate the accuracy of genomic selection for several metabolomic and quality traits by cross-validation and to estimate the impact of different factors on its accuracy. We analyzed data from 45 phenotypic traits and genotypic data obtained from a previous study of genetic association on a collection of 163 tomato accessions. We tested the influence of (1) the size of training population, (2) the number and density of molecular markers and (3) individual relatedness on the accuracy of prediction. The prediction accuracy of phenotypic values was largely related to the heritability of the traits. The size of training population increased the accuracy of predictions. Using 122 accessions and 5995 single nucleotide polymorphisms (SNPs) was the optimal condition. The density of markers and their numbers also affected the accuracy of the prediction. Using 2313 SNP markers distributed 0.1 cM or more apart from each other reduced the accuracy of prediction, and no gain in prediction accuracy was found when more markers were used in the model. Additionally, the more accessions were related, the more accurate were the predictions. Finally, the structure of the population negatively affected the prediction accuracy. In conclusion, the results obtained by cross-validation illustrated the effect of several parameters on the accuracy of prediction and revealed the potential of genomic selection in tomato breeding programs.