Single muscle fiber proteomics reveals unexpected mitochondrial specialization

Mammalian skeletal muscles are composed of multinucleated cells termed slow or fast fibers according to their contractile and metabolic properties. Here, we developed a high-sensitivity workflow to characterize the proteome of single fibers. Analysis of segments of the same fiber by traditional and unbiased proteomics methods yielded the same subtype assignment. We discovered novel subtype-specific features, most prominently mitochondrial specialization of fiber types in substrate utilization. The fiber type-resolved proteomes can be applied to a variety of physiological and pathological conditions and illustrate the utility of single cell type analysis for dissecting proteomic heterogeneity

Detergents and Chaotropes for Protein Solubilization before Two-Dimensional Electrophoresis

Because of the outstanding separating capabilities of two-dimensional electrophoresis for complete proteins, it would be advantageous to be able to apply it to all types of proteins. Unfortunately, severe solubility problems hamper the analysis of many classes of proteins, but especially membrane proteins. These problems arise mainly in the extraction and isoelectric focusing steps, and solutions are sought to improve protein solubility under the conditions prevailing during isoelectric focusing. These solutions deal mainly with chaotropes and new detergents, which are both able to enhance protein solubility. The input of these compounds in proteomics analysis of membrane proteins is discussed, as well as future directions.Comment: link to publisher's site http://biomed.humanapress.com

Development of 'Redox Arrays' for identifying novel glutathionylated proteins in the secretome

Proteomics techniques for analysing the redox status of individual proteins in complex mixtures tend to identify the same proteins due to their high abundance. We describe here an array-based technique to identify proteins undergoing glutathionylation and apply it to the secretome and the proteome of human monocytic cells. The method is based on incorporation of biotinylated glutathione (GSH) into proteins, which can then be identified following binding to a 1000-protein antibody array. We thus identify 38 secreted and 55 intracellular glutathionylated proteins, most of which are novel candidates for glutathionylation. Two of the proteins identified in these experiments, IL-1 sRII and Lyn, were then confirmed to be susceptible to glutathionylation. Comparison of the redox array with conventional proteomic methods confirmed that the redox array is much more sensitive, and can be performed using more than 100-fold less protein than is required for methods based on mass spectrometry. The identification of novel targets of glutathionylation, particularly in the secretome where the protein concentration is much lower, shows that redox arrays can overcome some of the limitations of established redox proteomics techniques

Advances in computational immunology

Published versio

Comparison of Milk Fat Globule Membrane (MFGM) Proteins of Chianina and Holstein Cattle Breed Milk Samples Through Proteomics Methods

Identification of proteins involved in milk production is important to understand the biology of lactation. Many studies have advanced the understanding of mammary function and milk secretion, but the critical molecular mechanisms implicated in milk fat secretion is still incomplete. Milk Fat Globules are secreted from the apical surface of the mammary cells, surrounded by a thin membrane bilayer, the Milk Fat Globule Membrane (MFGM), formed by proteins which have been suggested to be holesterolemia-lowering factors, inhibitors of cancer cell growth, vitamin binders, bactericidal, suppressors of multiple sclerosis. Using a proteomic approach, we compared MFGM from milk samples of individuals belonging to two different cattle breeds, Chianina and Holstein,representative of selection for milk and meat traits, respectively. We were able to isolate some of the major MFGM proteins in the examined samples and to identify differences between the protein fractions of the two breeds. We detected differences in the amount of proteins linked to mammary gland development and lipid droplets formation, as well as host defence mechanisms. We have shown that proteomics is a suitable, unbiased method for the study of milk fractions proteins and a powerful tool in nutritional genomics

The impact of sequence database choice on metaproteomic results in gut microbiota studies

Background: Elucidating the role of gut microbiota in physiological and pathological processes has recently emerged as a key research aim in life sciences. In this respect, metaproteomics, the study of the whole protein complement of a microbial community, can provide a unique contribution by revealing which functions are actually being expressed by specific microbial taxa. However, its wide application to gut microbiota research has been hindered by challenges in data analysis, especially related to the choice of the proper sequence databases for protein identification. Results: Here, we present a systematic investigation of variables concerning database construction and annotation and evaluate their impact on human and mouse gut metaproteomic results. We found that both publicly available and experimental metagenomic databases lead to the identification of unique peptide assortments, suggesting parallel database searches as a mean to gain more complete information. In particular, the contribution of experimental metagenomic databases was revealed to be mandatory when dealing with mouse samples. Moreover, the use of a "merged" database, containing all metagenomic sequences from the population under study, was found to be generally preferable over the use of sample-matched databases. We also observed that taxonomic and functional results are strongly database-dependent, in particular when analyzing the mouse gut microbiota. As a striking example, the Firmicutes/Bacteroidetes ratio varied up to tenfold depending on the database used. Finally, assembling reads into longer contigs provided significant advantages in terms of functional annotation yields. Conclusions: This study contributes to identify host- and database-specific biases which need to be taken into account in a metaproteomic experiment, providing meaningful insights on how to design gut microbiota studies and to perform metaproteomic data analysis. In particular, the use of multiple databases and annotation tools has to be encouraged, even though this requires appropriate bioinformatic resources