Building the power house: recent advances in mitochondrial studies through proteomics and systems biology

Biological mass spectrometry enables spatiotemporal 'omics: From tissues to cells to organelles

Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space-time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever-deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community-wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space-time.

Computational Modeling of Mitochondrial Function from a Systems Biology Perspective

The advent of "big data" in biology (e.g., genomics, proteomics, metabolomics), holding the promise to reveal the nature of the formidable complexity in cellular and organ makeup and function, has highlighted the compelling need for analytical and integrative computational methods to interpret and make sense of the patterns and changes in those complex networks. Computational models need to be built on sound physicochemical mechanistic principles in order to integrate, interpret, and simulate high-throughput experimental data. Energy transduction processes have been traditionally studied with thermodynamic, kinetic, or thermo-kinetic models, with the latter proving superior to understand the control and regulation of mitochondrial energy metabolism and its interactions with cytoplasmic and other cellular compartments. In this work, we survey the methods to be followed to build a computational model of mitochondrial energetics in isolation or integrated into a network of cellular processes. We describe the use of analytical tools such as elementary flux modes, linear optimization of metabolic models, and control analysis, to help refine our grasp of biologically meaningful behaviors and model reliability. The use of these tools should improve the design, building, and interpretation of steady-state behaviors of computational models while assessing validation criteria and paving the way to prediction.

Modeling metabolism of the human gut microbiome

The human gut microbiome plays an important part in human health. The complexity of the microbiome makes it difficult to determine the detailed metabolic functions and cross-talk occurs between the individual species. In silico systems biology studies of the microbiome can help to identify metabolite exchanges among gut microbes. Constraint-based reconstruction and analysis methods use biochemically accurate genome-scale metabolic networks of microorganisms to simulate metabolism between species in a given microbiome and help generate novel hypotheses on microbial interactions. Here, we review metabolic modeling studies that have investigated metabolic functions of the gut microbiome.

The human extended mitochondrial metabolic network: new hubs from lipids

Even if systems thinking is not new in biology, rationalizing the explosively growing amount of knowledge has been the compelling reason for the sudden rise and spreading of systems biology. Based on 'omics' data, several genome-scale metabolic networks have been reconstructed and validated. One of the most striking aspects of complex metabolic networks is the pervasive power-law appearance of metabolite connectivity. However, the combinatorial diversity of some classes of compounds, such as lipids, has been scarcely considered so far. In this work, a lipid-extended human mitochondrial metabolic network has been built and analyzed. It is shown that, considering combinatorial diversity of lipids and multipurpose enzymes, an intimate connection between membrane lipids and oxidative phosphorilation appears. This finding leads to some biomedical considerations on diseases involving mitochondrial enzymes. Moreover, the lipid-extended network still shows power-law features. Power-law distributions are intrinsic to metabolic network organization and evolution. Hubs in the lipid-extended mitochondrial network strongly suggest that the "RNA world" and the "lipid world" hypothesis are both correct.

Comparative mitochondrial proteomics: perspective in human diseases

Mitochondria are the most complex and the most important organelles of eukaryotic cells, which are involved in many cellular processes, including energy metabolism, apoptosis, and aging. And mitochondria have been identified as the "hot spot" by researchers for exploring relevant associated dysfunctions in many fields. The emergence of comparative proteomics enables us to have a close look at the mitochondrial proteome in a comprehensive and effective manner under various conditions and cellular circumstances. Two-dimensional electrophoresis combined with mass spectrometry is still the most popular techniques to study comparative mitochondrial proteomics. Furthermore, many new techniques, such as ICAT, MudPIT, and SILAC, equip researchers with more flexibilities inselecting proper methods. This article also reviews the recent development of comparative mitochondrial proteomics on diverse human diseases. And the results of mitochondrial proteomics enhance a better understanding of the pathogenesis associated with mitochondria and provide promising therapeutic targets.

Proteomic remodeling of mitochondria in heart failure

Heart failure (HF) is a common disease that has been attributed, in part, to deprivation of cardiac energy. As a result, the interplay between metabolism and adenosine triphosphate production is fundamental in determining the mechanisms driving the disease progression. Due to its central role in energy production, metabolism, calcium homeostasis, and oxidative stress, the mitochondrion has been suggested to play a pivotal role in the progression of the heart to failure. Nevertheless, the mitochondrion's specific role(s) and the proteins contributing to the development and progression of HF are not entirely clear. Thus, changes in mitochondrial proteomic make-up during HF have garnered great interest. With the continued development of advanced tools for assessing proteomic make-up, characterization of mitochondrial proteomic changes during disease states such as HF are being realized. These studies have begun to identify potential biomarkers of disease progression as well as protein targets that may provide an avenue for therapeutic intervention. The goal of this review is to highlight some of the changes in mitochondrial proteomic make-up that are associated with the development of HF in an effort to identify target axes and candidate proteins contributing to disease development. Results from a number of different HF models will be evaluated to gain insight into some of the similarities and differences in mitochondrial proteomic alterations associated with morphological and functional changes that result from the disease. Congest Heart Fail.

Modeling of mitochondria bioenergetics using a composable chemiosmotic energy transduction rate law: theory and experimental validation

Mitochondrial bioenergetic processes are central to the production of cellular energy, and a decrease in the expression or activity of enzyme complexes responsible for these processes can result in energetic deficit that correlates with many metabolic diseases and aging. Unfortunately, existing computational models of mitochondrial bioenergetics either lack relevant kinetic descriptions of the enzyme complexes, or incorporate mechanisms too specific to a particular mitochondrial system and are thus incapable of capturing the heterogeneity associated with these complexes across different systems and system states. Here we introduce a new composable rate equation, the chemiosmotic rate law, that expresses the flux of a prototypical energy transduction complex as a function of: the saturation kinetics of the electron donor and acceptor substrates; the redox transfer potential between the complex and the substrates; and the steady-state thermodynamic force-to-flux relationship of the overall electro-chemical reaction. Modeling of bioenergetics with this rate law has several advantages: (1) it minimizes the use of arbitrary free parameters while featuring biochemically relevant parameters that can be obtained through progress curves of common enzyme kinetics protocols; (2) it is modular and can adapt to various enzyme complex arrangements for both in vivo and in vitro systems via transformation of its rate and equilibrium constants; (3) it provides a clear association between the sensitivity of the parameters of the individual complexes and the sensitivity of the system's steady-state. To validate our approach, we conduct in vitro measurements of ETC complex I, III, and IV activities using rat heart homogenates, and construct an estimation procedure for the parameter values directly from these measurements. In addition, we show the theoretical connections of our approach to the existing models, and compare the predictive accuracy of the rate law with our experimentally fitted parameters to those of existing models. Finally, we present a complete perturbation study of these parameters to reveal how they can significantly and differentially influence global flux and operational thresholds, suggesting that this modeling approach could help enable the comparative analysis of mitochondria from different systems and pathological states. The procedures and results are available in Mathematica notebooks at http://www.igb.uci.edu/tools/sb/mitochondria-modeling.html.

Plant organelle proteomics: collaborating for optimal cell function

Organelle proteomics describes the study of proteins present in organelle at a particular instance during the whole period of their life cycle in a cell. Organelles are specialized membrane bound structures within a cell that function by interacting with cytosolic and luminal soluble proteins making the protein composition of each organelle dynamic. Depending on organism, the total number of organelles within a cell varies, indicating their evolution with respect to protein number and function. For example, one of the striking differences between plant and animal cells is the plastids in plants. Organelles have their own proteins, and few organelles like mitochondria and chloroplast have their own genome to synthesize proteins for specific function and also require nuclear-encoded proteins. Enormous work has been performed on animal organelle proteomics. However, plant organelle proteomics has seen limited work mainly due to: (i) inter-plant and inter-tissue complexity, (ii) difficulties in isolation of subcellular compartments, and (iii) their enrichment and purity. Despite these concerns, the field of organelle proteomics is growing in plants, such as Arabidopsis, rice and maize. The available data are beginning to help better understand organelles and their distinct and/or overlapping functions in different plant tissues, organs or cell types, and more importantly, how protein components of organelles behave during development and with surrounding environments. Studies on organelles have provided a few good reviews, but none of them are comprehensive. Here, we present a comprehensive review on plant organelle proteomics starting from the significance of organelle in cells, to organelle isolation, to protein identification and to biology and beyond. To put together such a systematic, in-depth review and to translate acquired knowledge in a proper and adequate form, we join minds to provide discussion and viewpoints on the collaborative nature of organelles in cell, their proper function and evolution.

Repercussion of Mitochondria Deformity Induced by Anti-Hsp90 Drug 17AAG in Human Tumor Cells

Inhibiting Hsp90 chaperone roles using 17AAG induces cytostasis or apoptosis in tumor cells through destabilization of several mutated cancer promoting proteins. Although mitochondria are central in deciding the fate of cells, 17AAG induced effects on tumor cell mitochondria were largely unknown. Here, we show that Hsp90 inhibition with 17AAG first affects mitochondrial integrity in different human tumor cells, neuroblastoma, cervical cancer and glial cells. Using human neuroblastoma tumor cells, we found the early effects associated with a change in mitochondrial membrane potential, elongation and engorgement of mitochondria because of an increased matrix vacuolization. These effects are specific to Hsp90 inhibition as other chemotherapeutic drugs did not induce similar mitochondrial deformity. Further, the effects are independent of oxidative damage and cytoarchitecture destabilization since cytoskeletal disruptors and mitochondrial metabolic inhibitors also do not induce similar deformity induced by 17AAG. The 1D PAGE LC MS/MS mitochondrial proteome analysis of 17AAG treated human neuroblastoma cells showed a loss of 61% proteins from membrane, metabolic, chaperone and ribonucleoprotein families. About 31 unmapped protein IDs were identified from proteolytic processing map using Swiss-Prot accession number, and converted to the matching gene name searching the ExPASy proteomics server. Our studies display that Hsp90 inhibition effects at first embark on mitochondria of tumor cells and compromise mitochondrial integrity.

Cardiovascular translational medicine (III). Genomics and proteomics in heart failure research

Heart failure is a complex syndrome and is one of the main causes of morbidity and mortality in developed countries. Despite considerable research effort in recent years, heart failure prevention and treatment strategies still suffer significant limitations. New theoretical and technical approaches are, therefore, required. It is in this context that the "omic" sciences have a role to play in heart failure. The incorporation of "omic" methodologies into the study of human disease has substantially changed biological approaches to disease and has given an enormous impetus to the search for new disease mechanisms, as well as for novel biomarkers and therapeutic targets. The application of genomics, proteomics and metabonomics to heart failure research could increase our understanding of the origin and development of the different processes contributing to this syndrome, thereby enabling the establishment of specific diagnostic profiles and therapeutic templates that could help improve the poor prognosis associated with heart failure. This brief review contains a short description of the fundamental principles of the "omic" sciences and an evaluation of how these new techniques are currently contributing to research into human heart failure. The focus is mainly on the analysis of gene expression microarrays in the field of genomics and on studies using two-dimensional electrophoresis with mass spectrometry in the area of proteomics.

Exploring mitochondrial evolution and metabolism organization principles by comparative analysis of metabolic networks

The endosymbiotic theory proposed that mitochondrial genomes are derived from an alpha-proteobacterium-like endosymbiont, which was concluded from sequence analysis. We rebuilt the metabolic networks of mitochondria and 22 relative species, and studied the evolution of mitochondrial metabolism at the level of enzyme content and network topology. Our phylogenetic results based on network alignment and motif identification supported the endosymbiotic theory from the point of view of systems biology for the first time. It was found that the mitochondrial metabolic network were much more compact than the relative species, probably related to the higher efficiency of oxidative phosphorylation of the specialized organelle, and the network is highly clustered around the TCA cycle. Moreover, the mitochondrial metabolic network exhibited high functional specificity to the modules. This work provided insight to the understanding of mitochondria evolution, and the organization principle of mitochondrial metabolic network at the network level.

Mapping gene associations in human mitochondria using clinical disease phenotypes

Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes.

An important prerequisite for successful disease gene identification is the assessment, with minimal ambiguity, of a particular clinical trait or phenotype. Even with years of experience, recognizing and diagnosing mitochondrial diseases is still a major hurdle in clinical medicine. Computational tools supporting clinicians not only help identify affected individuals, but also guide studies of the genetic and biological causes of these disorders. In this study we dissect and categorize individual clinical features, signs, and symptoms of 174 disease genes and then identify gene similarities based on their shared phenotypic features. We demonstrate that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. Our study of a large functional network of mitochondrial genes revealed distinct properties that differentiate disease and non-disease genes. Disease genes showed a lower average total connectivity but a tendency to interact with each other; a finding that we used to predict 168 high-probability disease candidates. The accompanying knowledgebase allows for easy navigation between disease and gene information. We believe the open source format will support and encourage further research that will benefit this and other human phenome projects.

Quantitative proteomic analysis of mitochondria in aging PS-1 transgenic mice

Accumulating evidence suggests mitochondrial alterations are intimately associated with the pathogenesis of Alzheimer's disease (AD). In order to determine if mutations of presenilin-1 (PS-1) affect levels of mitochondrial proteins at different ages we enriched mitochondrial fractions from 3-, 6-, 12-month-old knock-in mice expressing the M146V PS-1 mutation and identified, and quantified proteins using cleavable isotope-coded affinity tag labeling and two-dimensional liquid chromatography/tandem mass spectrometry (2D-LC/MS/MS). Using this approach, 165 non-redundant proteins were identified with 80 of them present in all three age groups. Specifically, at young ages (3 and 6 months), Na(+)/K(+) ATPase and several signal transduction proteins exhibited elevated levels, but dropped dramatically at 12 months. In contrast, components of the oxidative phosporylation pathway (OXPHOS), the mitochondrial permeability transition pore (MPTP), and energy metabolism proteins remained unchanged at 3 months but significantly increased with age. We propose that alterations in calcium homeostasis induced by the PS-1 mutation have a major impact in young animals by inhibiting the function of relevant proteins and inducing compensatory changes. However, in older mice combination of the PS-1 mutation and accumulated oxidative damage results in a functional suppression of OXPHOS and MPTP proteins requiring a compensatory increase in expression levels. In contrast, signal transduction proteins showed decreased levels due to a break down in the compensatory mechanisms. The dysfunction of Na(+)/K(+) ATPase and signal transduction proteins may induce impaired cognition and memory before neurodegeneration occurs.

MitoMiner, an integrated database for the storage and analysis of mitochondrial proteomics data

Mitochondria are a vital component of eukaryotic cells with functions that extend beyond energy production to include metabolism, signaling, cell growth, and apoptosis. Their dysfunction is implicated in a large number of metabolic, degenerative, and age-related human diseases. Therefore, it is important to characterize and understand the mitochondrion. Many experiments have attempted to define the mitochondrial proteome, resulting in large and complex data sets that are difficult to analyze. To address this, we developed a new public resource for the storage and investigation of this mitochondrial proteomics data, called MitoMiner, that uses a model to describe the proteomics data and associated biological information. The proteomics data of 33 publications from both mass spectrometry and green fluorescent protein tagging experiments were imported and integrated with protein annotation from UniProt and genome projects, metabolic pathway data from Kyoto Encyclopedia of Genes and Genomes, homology relationships from HomoloGene, and disease information from Online Mendelian Inheritance in Man. We demonstrate the strengths of MitoMiner by investigating these data sets and show that the number of different mitochondrial proteins that have been reported is about 3700, although the number of proteins common to both animals and yeast is about 1400, and membrane proteins appear to be underrepresented. Furthermore analysis indicated that enzymes of some cytosolic metabolic pathways are regularly detected in mitochondrial proteomics experiments, suggesting that they are associated with the outside of the outer mitochondrial membrane. The data and advanced capabilities of MitoMiner provide a framework for further mitochondrial analysis and future systems level modeling of mitochondrial physiology.

Chapter 15 Isolation of Saccharomyces cerevisiae mitochondria for Mössbauer, EPR, and electronic absorption spectroscopic analyses

Methods are presented to aid in the study of iron metabolism in isolated mitochondria. The "iron-ome" of mitochondria, including the type and concentration of all Fe-containing species in the organelle, is evaluated by integrating the results of four spectroscopic methods, including Mössbauer spectroscopy, electron paramagnetic resonance, electronic absorption spectroscopy, and inductively coupled plasma mass spectrometry. Although this systems biology approach only allows groups of Fe centers to be assessed, rather than individual species, it affords new and useful information. There are many considerations in executing this approach, and this chapter focuses on the practical methods that we have developed for this purpose. First, large quantities of mitochondria are required, and so published isolation methods must be scaled up. Second, mitochondria are isolated under strict anaerobic conditions to allow control of redox state and to protect O(2)-sensitive Fe-containing proteins from degradation. Third, the importance of packing mitochondria for both spectroscopic and analytical characterizations is developed. By measuring the volume of packed samples and the percentage of mitochondria contained within that volume, absolute Fe and protein concentrations within the organelle can be obtained. Packing samples into spectroscopy holders also affords maximal signal intensities, which are critical for these studies. Custom inserts designed for this purpose are described. Also described are the designs of a 25-L glass bioreactor, a mechanical cell homogenizer, a device for inserting short EPR tubes into the standard Oxford Instruments EPR cryostat, and a device for transferring samples from Mössbauer holders to EPR tubes while maintaining samples at liquid N(2) temperatures. A brief summary of what we have learned by use of these methods is included.

The mitochondrial proteome database: MitoP2

Defining the mitochondrial proteome is a prerequisite for fully understanding the organelles function as well as mechanisms underlying mitochondrial pathology. The core functions of mitochondria include oxidative phosphorylation, amino acid metabolism, fatty acid oxidation, and ion homeostasis. In addition to these well-known functions, many crucial properties in cell signaling, cell differentiation and cell death are only now being elucidated, and with them the proteins involved. With the wealth of information arriving from single protein studies and sophisticated genome-wide approaches, MitoP2 was designed and is maintained to consolidate knowledge on mitochondrial proteins in one comprehensive database, thus making all pertinent data readily accessible (http://www.mitop2.de). Although the identification of the human mitochondrial proteome is ultimately the prime objective, integration of other species includes Saccharomyces cerevisiae, mouse, Arabidopsis thaliana, and Neurospora crassa so orthology between these species can be interrogated. Data from genome-wide studies can be individually retrieved and are also processed by a support vector machine (SVM) to generate a score that indicates the likelihood of a candidate protein having a mitochondrial location. Manually validated proteins constitute the reference set of the database that contains over 590 yeast, 920 human, and 1020 mouse entries, and that is used for benchmarking the SVM score. Multiple search options allow for the interrogation of the reference set, candidates, disease related proteins, chromosome locations as well as availability of mouse models. Taken together, MitoP2 is a valuable tool for basic scientists, geneticists, and clinicians who are investigating mitochondrial physiology and dysfunction.

Complementary methods to assist subcellular fractionation in organellar proteomics

Organellar proteomics aims to describe the full complement of proteins of subcellular structures and organelles. When compared with whole-cell or whole-tissue proteomes, the more focused results from subcellular proteomic studies have yielded relatively simpler datasets from which biologically relevant information can be more easily extracted. In every proteomic study, the quality and purity of the biological sample to be investigated is of the utmost importance for a successful analysis. In organellar proteomics, one of the most crucial steps in sample preparation is the initial subcellular fractionation procedure by which the enriched preparation of the sought-after organelle is obtained. In nearly all available organellar proteomic studies, the method of choice relies on one or several rounds of density-based gradient centrifugation. Although this method has been recognized for decades as yielding relatively pure preparations of organelles, recent technological advances in protein separation and identification can now reveal even minute amounts of contamination, which in turn can greatly complicate data interpretation. The scope of this review focuses on recently published innovative complementary or alternative methods to perform subcellular fractionation, which can further refine the way in which sample preparation is accomplished in organellar proteomics.

mtDNA depletion confers specific gene expression profiles in human cells grown in culture and in xenograft

BACKGROUND

Interactions between the gene products encoded by the mitochondrial and nuclear genomes play critical roles in eukaryotic cellular function. However, the effects mitochondrial DNA (mtDNA) levels have on the nuclear transcriptome have not been defined under physiological conditions. In order to address this issue, we characterized the gene expression profiles of A549 lung cancer cells and their mtDNA-depleted rho0 counterparts grown in culture and as tumor xenografts in immune-deficient mice.

RESULTS

Cultured A549 rho0 cells were respiration-deficient and showed enhanced levels of transcripts relevant to metal homeostasis, initiation of the epithelial-mesenchymal transition, and glucuronidation pathways. Several well-established HIF-regulated transcripts showed increased or decreased abundance relative to the parental cell line. Furthermore, growth in culture versus xenograft has a significantly greater influence on expression profiles, including transcripts involved in mitochondrial structure and both aerobic and anaerobic energy metabolism. However, both in vitro and in vivo, mtDNA levels explained the majority of the variance observed in the expression of transcripts in glucuronidation, tRNA synthetase, and immune surveillance related pathways. mtDNA levels in A549 xenografts also affected the expression of genes, such as AMACR and PHYH, involved in peroxisomal lipid metabolic pathways.

CONCLUSION

We have identified mtDNA-dependent gene expression profiles that are shared in cultured cells and in xenografts. These profiles indicate that mtDNA-depleted cells could provide informative model systems for the testing the efficacy of select classes of therapeutics, such as anti-angiogenesis agents. Furthermore, mtDNA-depleted cells grown culture and in xenografts provide a powerful means to investigate possible relationships between mitochondrial activity and gene expression profiles in normal and pathological cells.

An overview of cardiac systems biology

The cardiac system has been a major target for intensive studies in the multi-scale modeling field for many years. Reproduction of the action potential and the ionic currents of single cardiomyocytes, as well as the construction of a whole organ model is well established. Still, there are major hurdles to overcome in creating a realistic and predictive functional cardiac model due to the lack of a profound understanding of the complex molecular interactions and their outcomes controlling both normal and pathological cardiophysiology. The recent advent of systems biology offers the conceptual and practical frameworks to tackle such biological complexities. This review provides an overview of major themes in the developing field of cardiac systems biology, summarizing some of the high-throughput experiments and strategies used to integrate the datasets, and various types of computational approaches used for developing useful quantitative models capable of predicting complex biological behavior.

Integration of 18O labeling and solution isoelectric focusing in a shotgun analysis of mitochondrial proteins

Forward and reverse (18)O labeling are integrated with solution isoelectric focusing and capillary LC-tandem mass spectrometry to evaluate a new strategy for quantitative proteomics and to study abundance changes in mitochondrial proteins associated with drug resistance in MCF-7 human cancer cells. Galectin-3 binding protein, which is involved in apoptosis, was detected only in the resistant cell line, as a result of reverse labeling. Among 278 proteins identified, 12 were detected with abundances altered at least 2-fold.

Differential proteomic profiling of mitochondria from Podospora anserina, rat and human reveals distinct patterns of age-related oxidative changes

According to the 'free radical theory of ageing', the generation and accumulation of reactive oxygen species are key events during ageing of biological systems. Mitochondria are a major source of ROS and prominent targets for ROS-induced damage. Whereas mitochondrial DNA and membranes were shown to be oxidatively modified with ageing, mitochondrial protein oxidation is not well understood. The purpose of this study was an unbiased investigation of age-related changes in mitochondrial proteins and the molecular pathways by which ROS-induced protein oxidation may disturb cellular homeostasis. In a differential comparison of mitochondrial proteins from young and senescent strains of the fungal ageing model Podospora anserina, from brains of young (5 months) vs. older rats (17 and 31 months), and human cells, with normal and chemically accelerated in vitro ageing, we found certain redundant posttranslationally modified isoforms of subunits of ATP synthase affected across all three species. These appear to represent general susceptible hot spot targets for oxidative chemical changes of proteins accumulating during ageing, and potentially initiating various age-related pathologies and processes. This type of modification is discussed using the example of SAM-dependent O-methyltransferase from P. anserina (PaMTH1), which surprisingly was found to be enriched in mitochondrial preparations of senescent cultures.