The Redox Proteome

The redox proteome consists of reversible and irreversible covalent modifications that link redox metabolism to biologic structure and function. These modifications, especially of Cys, function at the molecular level in protein folding and maturation, catalytic activity, signaling, and macromolecular interactions and at the macroscopic level in control of secretion and cell shape. Interaction of the redox proteome with redox-active chemicals is central to macromolecular structure, regulation, and signaling during the life cycle and has a central role in the tolerance and adaptability to diet and environmental challenges.     

蛋白质组研究中的分析技术

蛋白质组分析技术已在生物科学各领域被广泛应用,蛋白质组的研究已成为目前国际上的前沿和研究热点。概述了蛋白质组研究中的常用分析技术,包括样品制备、双向凝胶电泳、凝胶图像分析、质谱鉴定及数据库检索等。直观地列出了蛋白质组研究的技术体系流程图。各种分析技术的连用和分析过程的自动化将是蛋白质组研究技术的发展方向。     

The Sarda Sheep Host Fecal Proteome

The first characterization of the sheep fecal microbiota was recently reported, as obtained by using a multi meta‐omic approach. Here, the mass spectra generated by single‐run LC/high‐resolution MS in the context of that study were reanalyzed using a host‐specific database, in order to gain insights for the first time into the host fecal proteome of healthy Sarda sheep. On the whole, 5349 non‐redundant tryptic peptide sequences were identified, belonging to 1046 different proteins. The “core” fecal proteome (common to all animals) comprised 431 proteins, mainly related to biological processes as immune response and proteolysis. Proteins involved in the immune/inflammatory response and peptidases were specifically investigated. This dataset provides novel insights into the repertoire of proteins secreted in the sheep intestinal lumen, and constitutes the basis for future shotgun and targeted proteomics studies aimed at monitoring changes in the sheep fecal proteome in response to production variables, infectious/inflammatory states, and variations in the gut microbiota. Data are available via ProteomeXchange with identifier PXD006145.     

The Escherichia coli Peripheral Inner Membrane Proteome

Biological membranes are essential for cell viability. Their functional characteristics strongly depend on their protein content, which consists of transmembrane (integral) and peripherally associated membrane proteins. Both integral and peripheral inner membrane proteins mediate a plethora of biological processes. Whereas transmembrane proteins have characteristic hydrophobic stretches and can be predicted using bioinformatics approaches, peripheral inner membrane proteins are hydrophilic, exist in equilibria with soluble pools, and carry no discernible membrane targeting signals. We experimentally determined the cytoplasmic peripheral inner membrane proteome of the model organism Escherichia coli using a multidisciplinary approach. Initially, we extensively re-annotated the theoretical proteome regarding subcellular localization using literature searches, manual curation, and multi-combinatorial bioinformatics searches of the available databases. Next we used sequential biochemical fractionations coupled to direct identification of individual proteins and protein complexes using high resolution mass spectrometry. We determined that the proposed cytoplasmic peripheral inner membrane proteome occupies a previously unsuspected ∼19% of the basic E. coli BL21(DE3) proteome, and the detected peripheral inner membrane proteome occupies ∼25% of the estimated expressed proteome of this cell grown in LB medium to mid-log phase. This value might increase when fleeting interactions, not studied here, are taken into account. Several proteins previously regarded as exclusively cytoplasmic bind membranes avidly. Many of these proteins are organized in functional or/and structural oligomeric complexes that bind to the membrane with multiple interactions. Identified proteins cover the full spectrum of biological activities, and more than half of them are essential. Our data suggest that the cytoplasmic proteome displays remarkably dynamic and extensive communication with biological membrane surfaces that we are only beginning to decipher.An in-depth understanding of cellular proteomes requires knowledge of protein subcellular topology, assembly in macromolecular complexes, and modification and degradation of poplypeptides. Escherichia coli, a model organism for many such studies, is by far the best studied. The genomes of strain K-12 derivatives MG1655 and W3110 have been sequenced (1, 2), and >75% of their genes have been functionally assigned (3). Almost 90% of the K-12 proteome has been identified experimentally, and >73% of its proteins have known structures (4, 5). Moreover, the genomes of another 38 E. coli strains have been determined (see EcoliWiki for details).In E. coli, like in all Gram-negative bacteria, the bacterial cell envelope comprises the plasma or inner membrane and the outer membrane, which are separated by the periplasmic space. The inner membrane encloses the cytoplasm and is a dynamic substructure. It harbors a wide variety of proteins that function in vital cell processes such as the trafficking of ions, molecules, and macromolecules; cell division; environmental sensing; lipid, polysaccharide, and peptidoglycan biosynthesis; and metabolism. Inner membrane proteins either fully span the lipid bilayer using one or more hydrophobic transmembrane helices (integral) or are bound either directly to phospholipid components or via protein–protein interactions to the surface of the membrane (peripheral) (6) (Fig. 1A). Peripheral inner membrane proteins exist on either side of the membrane and may be recruited in membrane-associated complexes on demand (7). Peripheral inner membrane proteins on the cytoplasmic side constitute a sub-proteome of central importance because of their interaction with the cytoplasmic proteome, the nucleoid, and most of the cell''s metabolism. Thanks to their soluble character and the nature of their interactions with the membrane (mostly electrostatic and moderate hydrophobic interactions (7)), peripheral inner membrane proteins can be extracted using high salt concentrations, extreme pH levels, or chaotropes without disrupting the lipid bilayer (8–11). In contrast, the solubilization of integral proteins requires amphiphilic detergents in order to displace the membrane phospholipids and maintain them as soluble in aqueous solutions (12).Open in a separate windowFig. 1.Bioinformatics and experimental workflow for characterizing peripheral inner membrane proteins. A, schematic representation of the subcellular localization of the E. coli inner membrane peripherome. Protein topology assignment is based on the cellular compartment: A, cytoplasmic; B, integral inner membrane proteins; F1, peripheral inner membrane proteome; r, ribosome. B, schematic diagram for PIM protein annotation. 130 cytoplasmic and PIM E. coli K-12 proteins were downloaded from Uniprot (November 2010) (81) and EchoLOCATION (23). A set of bioinformatics tools was used to predict topologies and features of the unassigned and differently assigned proteins and to further validate existing protein annotations (see supplemental text). For the annotation of additional peripheral membrane proteins, the literature was extensively searched. Additional, other E. coli K-12 databases containing gene ontology annotations (84, 85) and protein homologies through BLAST (44) were employed. Homologues of curated E. coli K-12 proteins were identified in E. coli BL21(DE3) (supplemental Table S1A). C, preparation strategy for detecting the E. coli inner membrane peripherome via nanoLC-MS/MS. Inverted membrane vesicles (IMVs) were isolated and washed extensively with the indicated chemical agents to extract cytoplasmic and PIM proteins (“IMVs washed”), and then their surface was trypsinized (gray arrow). Following digestion, soluble peptides were analyzed via nanoLC-MS/MS. D, protein enrichment at different sample preparation conditions. Top: Relative percentage of proteins detected with the proteolysis approach. Proteins are classified here in three major categories: cytoplasmic (A), ribosomal (r), and peripheral (F1). The bar graphs indicate the percentage of proteins in each category relative to the proteins in other categories at a given sample preparation condition. Bottom: Heat maps showing relative quantities of individual proteins at different sample preparation conditions. Perseus (version 1.2.0.16), a part of the MaxQuant bioinformatics platform, was used for the construction of the heat map (86). A top-three label-free quantitative method was employed (27). Individual protein values across the various treatments are given in supplemental Table S3B.Unlike the cytoplasmic proteome of E. coli, which has been extensively characterized (13), its membrane sub-proteome is still poorly defined. Of 1133 predicted integral inner membrane proteins, only half were experimentally identified through proteomics approaches (14). These figures are constantly being re-evaluated,² but most protein identifications appear robust. In contrast to integral inner membrane proteins, bioinformatics prediction of peripheral inner membrane proteins is currently not possible because they are not known to possess any specific features. Despite the occasional designation of partner proteins identified as peripheral in studies that target inner membrane complexes (15–21), no systematic effort has been undertaken to analyze the peripheral inner membrane proteome.Here we have used a multi-pronged strategy employing bioinformatics, biochemistry, proteomics, and complexomics to systematically determine the peripheral inner membrane proteome of E. coli. We focus exclusively on the peripheral inner membrane proteome that faces the cytoplasm, referred to hereinafter as PIM,¹ and do not analyze peripheral inner membrane proteins residing on the periplasm. Manually curated and re-evaluated topology of the E. coli K-12 proteome was extrapolated to the non-K-12 strain BL21(DE3) (95% proteome homology to K-12) (22). By combining various biochemical treatments, we determined experimentally that several cytoplasmic proteins are also novel PIM proteins, and many of them participate in protein complexes associated with the membrane. Collectively, we demonstrate that a significant, previously unsuspected percentage of the expressed polypeptides constitute the PIM proteome.     

The Proteome Folding Problem and Cellular Proteostasis

Stunning advances have been achieved in addressing the protein folding problem, providing deeper understanding of the mechanisms by which proteins navigate energy landscapes to reach their native states and enabling powerful algorithms to connect sequence to structure. However, the realities of the in vivo protein folding problem remain a challenge to reckon with. Here, we discuss the concept of the “proteome folding problem”—the problem of how organisms build and maintain a functional proteome—by admitting that folding energy landscapes are characterized by many misfolded states and that cells must deploy a network of chaperones and degradation enzymes to minimize deleterious impacts of these off-pathway species. The resulting proteostasis network is an inextricable part of in vivo protein folding and must be understood in detail if we are to solve the proteome folding problem. We discuss how the development of computational models for the proteostasis network’s actions and the relationship to the biophysical properties of the proteome has begun to offer new insights and capabilities.     

The Proteome of Cholesteryl-Ester-Enriched Versus Triacylglycerol-Enriched Lipid Droplets

Within cells, lipids are stored in the form of lipid droplets (LDs), consisting of a neutral lipid core, surrounded by a phospholipid monolayer and an outer layer of protein. LDs typically accumulate either triacylglycerol (TAG) and diacylglycerol or cholesteryl ester (CE), depending on the type of tissue. Recently, there has been an increased interest in the proteins that surround LDs. LD proteins have been found to be quite diverse, from structural proteins to metabolic enzymes, proteins involved in vesicular transport, and proteins that may play a role in LD formation. Previous proteomics analyses have focused on TAG-enriched LDs, whereas CE-enriched LDs have been largely ignored. Our study has compared the LD proteins from CE-enriched LDs to TAG-enriched LDs in steroidogenic cells. In primary rat granulosa cells loaded with either HDL to produce CE-enriched LDs or fatty acids to produce TAG-enriched LDs, 61 proteins were found to be elevated in CE-enriched LDs and 40 proteins elevated in TAG-enriched LDs with 278 proteins in similar amounts. Protein expression was further validated by selected reaction monitoring (SRM) mass spectrometry (MS). SRM verified expression of 25 of 27 peptides that were previously detected by tandem mass tagging MS. Several proteins were confirmed to be elevated in CE-enriched LDs by SRM including the intermediate filament vimentin. This study is the first to compare the proteins found on CE-enriched LDs with TAG-enriched LDs and constitutes the first step in creating a better understanding of the proteins found on CE-enriched LDs in steroidogenic cells.     

转录组与蛋白质组比较研究进展

转录组和蛋白质组比较研究发现,总体而言其间的相关性不高 . 根据数据的类型不同可以将现有的研究分为 4 类：单点比较、两点差异比较、多点时序比较和多点非时序比较 . 对其差异原因的研究和分析表明：除了由实验系统及数据类型不同导致的差异外,转录后蛋白质合成各步骤所受到的限制,以及在此过程中的分子调控也对其有重要的影响;而且不同基因,不同组织和细胞在不同状态下可能也会有差异 . 因此,结合转录组和蛋白质组的表达谱研究倾向于利用蛋白质组和转录组研究的差异和互补性,同时对生物体特定状态下的基因和蛋白质表达水平进行全方位度量,以获得表达谱的全景图,并挖掘受到转录后调控的基因 .     

Heart Mitochondrial Proteome Study Elucidates Changes in Cardiac Energy Metabolism and Antioxidant PRDX3 in Human Dilated Cardiomyopathy

Background

Dilated cardiomyopathy (DCM) is a public health problem with no available curative treatment, and mitochondrial dysfunction plays a critical role in its development. The present study is the first to analyze the mitochondrial proteome in cardiac tissue of patients with DCM to identify potential molecular targets for its therapeutic intervention.

Methods and Results

16 left ventricular (LV) samples obtained from explanted human hearts with DCM (n = 8) and control donors (n = 8) were extracted to perform a proteomic approach to investigate the variations in mitochondrial protein expression. The proteome of the samples was analyzed by quantitative differential electrophoresis and Mass Spectrometry. These changes were validated by classical techniques and by novel and precise selected reaction monitoring analysis and RNA sequencing approach increasing the total heart samples up to 25. We found significant alterations in energy metabolism, especially in molecules involved in substrate utilization (ODPA, ETFD, DLDH), energy production (ATPA), other metabolic pathways (AL4A1) and protein synthesis (EFTU), obtaining considerable and specific relationships between the alterations detected in these processes. Importantly, we observed that the antioxidant PRDX3 overexpression is associated with impaired ventricular function. PRDX3 is significantly related to LV end systolic and diastolic diameter (r = 0.73, p value<0.01; r = 0.71, p value<0.01), fractional shortening, and ejection fraction (r = −0.61, p value<0.05; and r = −0.62, p value<0.05, respectively).

Conclusion

This work could be a pivotal study to gain more knowledge on the cellular mechanisms related to the pathophysiology of this disease and may lead to the development of etiology-specific heart failure therapies. We suggest new molecular targets for therapeutic interventions, something that up to now has been lacking.