Sense and Nonsense of Pathway Analysis Software in Proteomics

Proteomics appending a complementary dimension to precision oncotherapy

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

A cluster of blood-based protein biomarkers associated with decreased cerebral blood flow relates to future cardiovascular events in patients with cardiovascular disease

Biological processes underlying decreased cerebral blood flow (CBF) in patients with cardiovascular disease (CVD) are largely unknown. We hypothesized that identification of protein clusters associated with lower CBF in patients with CVD may explain underlying processes. In 428 participants (74% cardiovascular diseases; 26% reference participants) from the Heart-Brain Connection Study, we assessed the relationship between 92 plasma proteins from the Olink® cardiovascular III panel and normal-appearing grey matter CBF, using affinity propagation and hierarchical clustering algorithms, and generated a Biomarker Compound Score (BCS). The BCS was related to cardiovascular risk and observed cardiovascular events within 2-year follow-up using Spearman correlation and logistic regression. Thirteen proteins were associated with CBF (ρSpearman range: -0.10 to -0.19, pFDR-corrected <0.05), and formed one cluster. The cluster primarily reflected extracellular matrix organization processes. The BCS was higher in patients with CVD compared to reference participants (pFDR-corrected <0.05) and was associated with cardiovascular risk (ρSpearman 0.42, p < 0.001) and cardiovascular events (OR 2.05, p < 0.01). In conclusion, we identified a cluster of plasma proteins related to CBF, reflecting extracellular matrix organization processes, that is also related to future cardiovascular events in patients with CVD, representing potential targets to preserve CBF and mitigate cardiovascular risk in patients with CVD.

Novel γ-sarcoglycan interactors in murine muscle membranes

BACKGROUND

The sarcoglycan complex (SC) is part of a network that links the striated muscle cytoskeleton to the basal lamina across the sarcolemma. The SC coordinates changes in phosphorylation and Ca⁺⁺-flux during mechanical deformation, and these processes are disrupted with loss-of-function mutations in gamma-sarcoglycan (Sgcg) that cause Limb girdle muscular dystrophy 2C/R5.

METHODS

To gain insight into how the SC mediates mechano-signaling in muscle, we utilized LC-MS/MS proteomics of SC-associated proteins in immunoprecipitates from enriched sarcolemmal fractions. Criteria for inclusion were co-immunoprecipitation with anti-Sgcg from C57BL/6 control muscle and under-representation in parallel experiments with Sgcg-null muscle and with non-specific IgG. Validation of interaction was performed in co-expression experiments in human RH30 rhabdomyosarcoma cells.

RESULTS

We identified 19 candidates as direct or indirect interactors for Sgcg, including the other 3 SC proteins. Novel potential interactors included protein-phosphatase-1-catalytic-subunit-beta (Ppp1cb, PP1b) and Na⁺-K⁺-Cl^--co-transporter NKCC1 (SLC12A2). NKCC1 co-localized with Sgcg after co-expression in human RH30 rhabdomyosarcoma cells, and its cytosolic domains depleted Sgcg from cell lysates upon immunoprecipitation and co-localized with Sgcg after detergent permeabilization. NKCC1 localized in proximity to the dystrophin complex at costameres in vivo. Bumetanide inhibition of NKCC1 cotransporter activity in isolated muscles reduced SC-dependent, strain-induced increases in phosphorylation of extracellular signal-regulated kinases 1 and 2 (ERK1/2). In silico analysis suggests that candidate SC interactors may cross-talk with survival signaling pathways, including p53, estrogen receptor, and TRIM25.

CONCLUSIONS

Results support that NKCC1 is a new SC-associated signaling protein. Moreover, the identities of other candidate SC interactors suggest ways by which the SC and NKCC1, along with other Sgcg interactors such as the membrane-cytoskeleton linker archvillin, may regulate kinase- and Ca⁺⁺-mediated survival signaling in skeletal muscle.

High-throughput analysis and functional interpretation of extracellular vesicle content in hematological malignancies

Extracellular vesicles (EVs) are membrane-coated particles secreted by virtually all cell types in response to different stimuli, both in physiological and pathological conditions. Their content generally reflects their biological functions and includes a variety of molecules, such as nucleic acids, proteins and cellular components. The role of EVs as signaling vehicles has been widely demonstrated. In particular, they are actively involved in the pathogenesis of several hematological malignancies (HM), mainly interacting with a number of target cells and inducing functional and epigenetic changes. In this regard, by releasing their cargo, EVs play a pivotal role in the bilateral cross-talk between tumor microenvironment and cancer cells, thus facilitating mechanisms of immune escape and supporting tumor growth and progression. Recent advances in high-throughput technologies have allowed the deep characterization and functional interpretation of EV content. In this review, the current knowledge on the high-throughput technology-based characterization of EV cargo in HM is summarized.

The Mechanism of the Selective Antiproliferation Effect of Guanine-Based Biomolecules and Its Compensation

As endogenous biomolecules, guanine, guanine-based nucleosides, and nucleotides are essential for cellular DNA/RNA synthesis, energy metabolism, and signal transduction. However, these biomolecules have been found to have a cell-specific antiproliferation effect at higher concentrations, and the mechanism is unclear. In this study, we demonstrate that guanine deaminase (GDA) is a major factor in determining the cell-type selectivity to the antiproliferation effect of guanine-based biomolecules. GDA catalyzes the deamination of guanine to xanthine, which is an essential part of the guanine degradation pathway. GDA deficient cells could not efficiently remove the excess guanine-based biomolecules. These excess molecules disturb the metabolism of adenine-, cytosine-, and thymine-based nucleotides; subsequently inhibit the DNA synthesis and cell growth; and eventually result in the apoptosis/death of GDA deficient cells. The inhibition of DNA synthesis could be relieved by simultaneous addition of adenine- and cytosine-based nucleosides, and the inhibited DNA synthesis could be restarted by post addition of them, which subsequently reduces the antiproliferation effect of guanine-based biomolecules or even totally restores the cell proliferation. These results provide important information for the development of guanine-based drugs or guanine-rich oligonucleotide drugs, as well as for the safety evaluation of food with a high level of guanine-based compounds.

Proteomics and phosphoproteomics in precision medicine: applications and challenges

Recent advances in proteomics allow the accurate measurement of abundances for thousands of proteins and phosphoproteins from multiple samples in parallel. Therefore, for the first time, we have the opportunity to measure the proteomic profiles of thousands of patient samples or disease model cell lines in a systematic way, to identify the precise underlying molecular mechanism and discover personalized biomarkers, networks and treatments. Here, we review examples of successful use of proteomics and phosphoproteomics data sets in as well as their integration other omics data sets with the aim of precision medicine. We will discuss the bioinformatics challenges posed by the generation, analysis and integration of such large data sets and present potential reasons why proteomics profiling and biomarkers are not currently widely used in the clinical setting. We will finally discuss ways to contribute to the better use of proteomics data in precision medicine and the clinical setting.

Bioinformatics Tools for Extracellular Vesicles Research

Extracellular vesicles (EVs) are a class of membranous vesicles that are released by multiple cell types into the extracellular environment. This unique class of extracellular organelles which play pivotal role in intercellular communication are conserved across prokaryotes and eukaryotes. Depending upon the cell origin and the functional state, the molecular cargo including proteins, lipids, and RNA within the EVs are modulated. Owing to this, EVs are considered as a subrepertoire of the host cell and are rich reservoirs of disease biomarkers. In addition, the availability of EVs in multiple bodily fluids including blood has created significant interest in biomarker and signaling research. With the advancement in high-throughput techniques, multiple EV studies have embarked on profiling the molecular cargo. To benefit the scientific community, existing free Web-based resources including ExoCarta, EVpedia, and Vesiclepedia catalog multiple datasets. These resources aid in elucidating molecular mechanism and pathophysiology underlying different disease conditions from which EVs are isolated. Here, the existing bioinformatics tools to perform integrated analysis to identify key functional components in the EV datasets are discussed.

Changes in DNA methylation in naïve T helper cells regulate the pathophysiological state in minimal-change nephrotic syndrome

Background

DNA methylation plays a crucial role in regulating transcription, and changes in DNA methylation affect gene expression and disease development. Minimal change nephrotic syndrome (MCNS) has been reported to involve immunological disturbances. Since the characteristic features of the disease include recurrent relapse and sex and age preference, the disease pathogenesis may be partly related to epigenetic changes. However, little is known about these changes.

Methods

We analyzed genome-wide DNA methylation using the microarray-based integrated analysis of methylation by isoschizomers method. This method was used to evaluate methylation in monocytes (patient number; n = 6) and naïve T helper cells (n = 4) from the peripheral blood of MCNS patients both in relapse and following remission and that of healthy controls (n = 5).

Results

In total, 85 co-occurring genes were identified in naïve T helper cells, while 4 such genes were identified in monocytes, which were common among the 3 following comparisons for changes in DNA methylation using sample pairs: (1) relapse versus remission, (2) relapse versus controls, and (3) remission versus controls. In 82 of 85 co-occurring genes (96.5%) in naïve T helper cells, the level of DNA methylation was altered according to disease activity, but was not related to disease activity in the 4 genes detected in monocytes.

Conclusions

Therefore, in 82 co-occurring genes in naïve T helper cells, the regulation of DNA methylation was well correlated with the clinical and pathophysiological state. Our genome-wide approach to analyze DNA methylation provides further insight into the pathogenesis of MCNS and indicates potential prediction and diagnostic tool for the disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-017-2719-1) contains supplementary material, which is available to authorized users.

SILAC-Based Quantitative Proteomic Analysis Unveils Arsenite-Induced Perturbation of Multiple Pathways in Human Skin Fibroblast Cells

Humans are exposed to arsenic species through inhalation, ingestion, and dermal contact, which may lead to skin, liver, and bladder cancers as well as cardiovascular and neurological diseases. The mechanisms underlying the cytotoxic and carcinogenic effects of arsenic species, however, remain incompletely understood. To exploit the mechanisms of toxicity of As(III), we employed stable isotope labeling by amino acids in cell culture (SILAC) together with LC/MS/MS analysis to quantitatively assess the As(III)-induced perturbation of the entire proteome of cultured human skin fibroblast cells. Shotgun proteomic analysis on an LTQ-Orbitrap Velos mass spectrometer facilitated the quantification of 3880 proteins, 130 of which were quantified in both forward and reverse SILAC-labeling experiments and displayed significant alterations (>1.5 fold) upon arsenite treatment. Targeted analysis on a triple-quadrupole mass spectrometer in multiple-reaction monitoring (MRM) mode confirmed the quantification results of some select proteins. Ingenuity pathway analysis revealed the arsenite-induced alteration of more than 10 biological pathways, including the Nrf2-mediated oxidative stress response pathway, which is represented by the upregulation of nine proteins in this pathway. In addition, arsenite induced changes in expression levels of a number of selenoproteins and metallothioneins. Together, the results from the present study painted a more complete picture regarding the biological pathways that are altered in human skin fibroblast cells upon arsenite exposure.

Pathway Analysis of Proteomics Profiles in Rabies Infection: Towards Future Biomarkers?

Rabies is a zoonotic viral disease that invariably leads to fatal encephalitis, which can be prevented provided post-exposure prophylaxis is initiated timely. Ante-mortem diagnostic tests are inconclusive, and rabies is nontreatable once the clinical signs appear. A large number of host factors are responsible for the altered neuronal functions observed in rabies; however their precise role remains uninvestigated. We therefore used two-dimensional electrophoresis and mass spectrometry analysis to identify differentially expressed host proteins in an experimental murine model of rabies. We identified 143 proteins corresponding to 45 differentially expressed spots (p < 0.05) in neuronal tissues of Swiss albino mice in response to infection with neurovirulent rabies strains. Time series analyses revealed that a majority of the alterations occur at 4 to 6 days post infection, in particular affecting the host's cytoskeletal architecture. Extensive pathway analysis and protein interaction studies using the bioinformatic tools such as Ingenuity Pathway Analysis and STRING revealed novel pathways and molecules (e.g., protein ubiquitination) unexplored hitherto. Further activation/inhibition studies of these pathway molecular leads would be relevant to identify novel biomarkers and mechanism-based therapeutics for rabies, a disease that continues to severely impact global health.

Systematic Analysis of Quantitative Logic Model Ensembles Predicts Drug Combination Effects on Cell Signaling Networks

A major challenge in developing anticancer therapies is determining the efficacies of drugs and their combinations in physiologically relevant microenvironments. We describe here our application of "constrained fuzzy logic" (CFL) ensemble modeling of the intracellular signaling network for predicting inhibitor treatments that reduce the phospho-levels of key transcription factors downstream of growth factors and inflammatory cytokines representative of hepatocellular carcinoma (HCC) microenvironments. We observed that the CFL models successfully predicted the effects of several kinase inhibitor combinations. Furthermore, the ensemble predictions revealed ambiguous predictions that could be traced to a specific structural feature of these models, which we resolved with dedicated experiments, finding that IL-1α activates downstream signals through TAK1 and not MEKK1 in HepG2 cells. We conclude that CFL-Q2LM (Querying Quantitative Logic Models) is a promising approach for predicting effective anticancer drug combinations in cancer-relevant microenvironments.

Body Management: Mesenchymal Stem Cells Control the Internal Regenerator

SummaryIt has been assumed that adult tissues cannot regenerate themselves. With the current understanding that every adult tissue has its own intrinsic progenitor or stem cell, it is now clear that almost all tissues have regenerative potential partially related to their innate turnover dynamics. Moreover, it appears that a separate class of local cells originating as perivascular cells appears to provide regulatory oversight for localized tissue regeneration. The management of this regeneration oversight has a profound influence on the use of specific cells for cell therapies as a health care delivery tool set. The multipotent mesenchymal stem cell (MSC), now renamed the medicinal signaling cell, predominantly arises from pericytes released from broken and inflamed blood vessels and appears to function as both an immunomodulatory and a regeneration mediator. MSCs are being tested for their management capabilities to produce therapeutic outcomes in more than 480 clinical trials for a wide range of clinical conditions. Local MSCs function by managing the body's primary repair and regeneration activities. Supplemental MSCs can be provided from either endogenous or exogenous sources of either allogeneic or autologous origin. This MSC-based therapy has the potential to change how health care is delivered. These medicinal cells are capable of sensing their surroundings. Also, by using its complex signaling circuitry, these cells organize site-specific regenerative responses as if these therapeutic cells were well-programmed modern computers. Given these facts, it appears that we are entering a new age of cellular medicine.

SIGNIFICANCE

This report is a perspective from an active scientist and an active entrepreneur and commercial leader. It is neither a comprehensive review nor a narrowly focused treatise. The broad themes and the analogy to the working component of a computer and that of a cell are meant to draw several important scientific principles and health care themes together into the thesis that regenerative medicine is a constant throughout life and its management is the next frontier of health care. Mesenchymal stem cells are used as the central connection in the broad theme, not as multipotent progenitors but rather as an important control element in the natural local regeneration process.

Viewing the proteome: how to visualize proteomics data?

Proteomics has become one of the main approaches for analyzing and understanding biological systems. Yet similar to other high-throughput analysis methods, the presentation of the large amounts of obtained data in easily interpretable ways remains challenging. In this review, we present an overview of the different ways in which proteomics software supports the visualization and interpretation of proteomics data. The unique challenges and current solutions for visualizing the different aspects of proteomics data, from acquired spectra via protein identification and quantification to pathway analysis, are discussed, and examples of the most useful visualization approaches are highlighted. Finally, we offer our ideas about future directions for proteomics data visualization.

Proteomics for systems toxicology

Current toxicology studies frequently lack measurements at molecular resolution to enable a more mechanism-based and predictive toxicological assessment. Recently, a systems toxicology assessment framework has been proposed, which combines conventional toxicological assessment strategies with system-wide measurement methods and computational analysis approaches from the field of systems biology. Proteomic measurements are an integral component of this integrative strategy because protein alterations closely mirror biological effects, such as biological stress responses or global tissue alterations. Here, we provide an overview of the technical foundations and highlight select applications of proteomics for systems toxicology studies. With a focus on mass spectrometry-based proteomics, we summarize the experimental methods for quantitative proteomics and describe the computational approaches used to derive biological/mechanistic insights from these datasets. To illustrate how proteomics has been successfully employed to address mechanistic questions in toxicology, we summarized several case studies. Overall, we provide the technical and conceptual foundation for the integration of proteomic measurements in a more comprehensive systems toxicology assessment framework. We conclude that, owing to the critical importance of protein-level measurements and recent technological advances, proteomics will be an integral part of integrative systems toxicology approaches in the future.

Combining bioinformatics and MS-based proteomics: clinical implications

Clinical proteomics research aims at i) discovery of protein biomarkers for screening, diagnosis and prognosis of disease, ii) discovery of protein therapeutic targets for improvement of disease prevention, treatment and follow-up, and iii) development of mass spectrometry (MS)-based assays that could be implemented in clinical chemistry, microbiology or hematology laboratories. MS has been increasingly applied in clinical proteomics studies for the identification and quantification of proteins. Bioinformatics plays a key role in the exploitation of MS data in several aspects such as the generation and curation of protein sequence databases, the development of appropriate software for MS data treatment and integration with other omics data and the establishment of adequate standard files for data sharing. In this article, we discuss the main MS approaches and bioinformatics solutions that are currently applied to accomplish the objectives of clinical proteomic research.

Bioinformatic analysis of proteomics data

Most biochemical reactions in a cell are regulated by highly specialized proteins, which are the prime mediators of the cellular phenotype. Therefore the identification, quantitation and characterization of all proteins in a cell are of utmost importance to understand the molecular processes that mediate cellular physiology. With the advent of robust and reliable mass spectrometers that are able to analyze complex protein mixtures within a reasonable timeframe, the systematic analysis of all proteins in a cell becomes feasible. Besides the ongoing improvements of analytical hardware, standardized methods to analyze and study all proteins have to be developed that allow the generation of testable new hypothesis based on the enormous pre-existing amount of biological information. Here we discuss current strategies on how to gather, filter and analyze proteomic data sates using available software packages.

Amyloid beta a4 precursor protein-binding family B member 1 (FE65) interactomics revealed synaptic vesicle glycoprotein 2A (SV2A) and sarcoplasmic/endoplasmic reticulum calcium ATPase 2 (SERCA2) as new binding proteins in the human brain

FE65 is a cytosolic adapter protein and an important binding partner of amyloid precursor protein. Dependent on Thr668 phosphorylation in amyloid precursor protein, which influences amyloidogenic amyloid precursor protein processing, FE65 undergoes nuclear translocation, thereby transmitting a signal from the cell membrane to the nucleus. As this translocation may be relevant in Alzheimer disease, and as FE65 consists of three protein-protein interaction domains able to bind and affect a variety of other proteins and downstream signaling pathways, the identification of the FE65 interactome is of central interest in Alzheimer disease research. In this study, we identified 121 proteins as new potential FE65 interacting proteins in a pulldown/mass spectrometry approach using human post-mortem brain samples as protein pools for recombinantly expressed FE65. Co-immunoprecipitation assays further validated the interaction of FE65 with the candidates SV2A and SERCA2. In parallel, we investigated the whole cell proteome of primary hippocampal neurons from FE65/FE65L1 double knockout mice. Notably, the validated FE65 binding proteins were also found to be differentially abundant in neurons derived from the FE65 knockout mice relative to wild-type control neurons. SERCA2 is an important player in cellular calcium homeostasis, which was found to be up-regulated in double knockout neurons. Indeed, knock-down of FE65 in HEK293T cells also evoked an elevated sensitivity to thapsigargin, a stressor specifically targeting the activity of SERCA2. Thus, our results suggest that FE65 is involved in the regulation of intracellular calcium homeostasis. Whereas transfection of FE65 alone caused a typical dot-like phenotype in the nucleus, co-transfection of SV2A significantly reduced the percentage of FE65 dot-positive cells, pointing to a possible role for SV2A in the modulation of FE65 intracellular targeting. Given that SV2A has a signaling function at the presynapse, its effect on FE65 intracellular localization suggests that the SV2A/FE65 interaction might play a role in synaptic signal transduction.

6-thioguanine induces mitochondrial dysfunction and oxidative DNA damage in acute lymphoblastic leukemia cells

Thiopurines are among the most successful chemotherapeutic agents used for treating various human diseases, including acute lymphoblastic leukemia and chronic inflammation. Although metabolic conversion and the subsequent incorporation of 6-thioguanine ((S)G) nucleotides into nucleic acids are considered important for allowing the thiopurine drugs to induce their cytotoxic effects, alternative mechanisms may also exist. We hypothesized that an unbiased analysis of (S)G-induced perturbation of the entire proteome might uncover novel mechanism(s) of action of the drug. We performed a quantitative assessment of global protein expression in control and (S)G-treated Jurkat T cells by employing stable isotope labeling by amino acids in cell culture and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. LC-MS/MS quantification results uncovered substantially decreased expression of a large number of proteins in the mitochondrial respiratory chain complex, and Ingenuity Pathway Analysis of the significantly altered proteins showed that (S)G treatment induced mitochondrial dysfunction. This was accompanied by diminished uptake of MitoTracker Deep Red and the elevated formation of oxidatively induced DNA lesions, including 8,5'-cyclo-2'-deoxyadenosine and 8,5'-cyclo-2'-deoxyguanosine. Together, our results suggested that (S)G may exert its cytotoxic effect by inducing mitochondrial dysfunction and reactive oxygen species formation in acute lymphoblastic leukemia cells.

The cellular interactome of the coronavirus infectious bronchitis virus nucleocapsid protein and functional implications for virus biology

The coronavirus nucleocapsid (N) protein plays a multifunctional role in the virus life cycle, from regulation of replication and transcription and genome packaging to modulation of host cell processes. These functions are likely to be facilitated by interactions with host cell proteins. The potential interactome of the infectious bronchitis virus (IBV) N protein was mapped using stable isotope labeling with amino acids in cell culture (SILAC) coupled to a green fluorescent protein-nanotrap pulldown methodology and liquid chromatography-tandem mass spectrometry. The addition of the SILAC label allowed discrimination of proteins that were likely to specifically bind to the N protein over background binding. Overall, 142 cellular proteins were selected as potentially binding to the N protein, many as part of larger possible complexes. These included ribosomal proteins, nucleolar proteins, translation initiation factors, helicases, and hnRNPs. The association of selected cellular proteins with IBV N protein was confirmed by immunoblotting, cosedimentation, and confocal microscopy. Further, the localization of selected proteins in IBV-infected cells as well as their activity during virus infection was assessed by small interfering RNA-mediated depletion, demonstrating the functional importance of cellular proteins in the biology of IBV. This interactome not only confirms previous observations made with other coronavirus and IBV N proteins with both overexpressed proteins and infectious virus but also provides novel data that can be exploited to understand the interaction between the virus and the host cell.

Networks in proteomics analysis of cancer

Proteomics provides direct biological information on proteins but is still a limited platform. Borrowing from genomics, its cancer-specific applications can be broadly categorized as (1) pure diagnostics, (2) biomarkers, (3) identification of root causes and (4) identification of cancer-specific network rewirings. Biological networks capture complex relationships between proteins and provide an appropriate means of contextualization. While playing significantly larger roles, especially in 1 and 3, progress in proteomics-specific network-based methods is lagging as compared to genomics. Rapid hardware advances and improvements in proteomic identification and quantification have given rise to much better quality data alongside advent of new network-based analysis methods. However, a tighter integration between analytics and hardware is still essential for network analysis to play more significant roles in proteomics analysis.

Interaction of proteins identified in human thyroid cells

Influence of gravity forces on the regulation of protein expression by healthy and malignant thyroid cells was studied with the aim to identify protein interactions. Western blot analyses of a limited number of proteins suggested a time-dependent regulation of protein expression by simulated microgravity. After applying free flow isoelectric focusing and mass spectrometry to search for differently expressed proteins by thyroid cells exposed to simulated microgravity for three days, a considerable number of candidates for gravi-sensitive proteins were detected. In order to show how proteins sensitive to microgravity could directly influence other proteins, we investigated all polypeptide chains identified with Mascot scores above 100, looking for groups of interacting proteins. Hence, UniProtKB entry numbers of all detected proteins were entered into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and processed. The program indicated that we had detected various groups of interacting proteins in each of the three cell lines studied. The major groups of interacting proteins play a role in pathways of carbohydrate and protein metabolism, regulation of cell growth and cell membrane structuring. Analyzing these groups, networks of interaction could be established which show how a punctual influence of simulated microgravity may propagate via various members of interaction chains.

FE65 regulates and interacts with the Bloom syndrome protein in dynamic nuclear spheres – potential relevance to Alzheimer's disease

The intracellular domain of the amyloid precursor protein (AICD) is generated following cleavage of the precursor by the γ-secretase complex and is involved in membrane to nucleus signaling, for which the binding of AICD to the adapter protein FE65 is essential. Here we show that FE65 knockdown causes a down regulation of the protein BLM and the MCM protein family and that elevated nuclear levels of FE65 result in stabilization of the BLM protein in nuclear mobile spheres. These spheres are able to grow and fuse, and potentially correspond to the nuclear domain 10. BLM plays a role in DNA replication and repair mechanisms and FE65 was also shown to play a role in the cell's response to DNA damage. A set of proliferation assays in our work revealed that FE65 knockdown cells exhibit reduced cell replication in HEK293T cells. On the basis of these results, we hypothesize that nuclear FE65 levels (nuclear FE65/BLM containing spheres) may regulate cell cycle re-entry in neurons due to increased interaction of FE65 with BLM and/or an increase in MCM protein levels. Thus, FE65 interactions with BLM and MCM proteins may contribute to the neuronal cell cycle re-entry observed in Alzheimer disease brains.

PROTEINCHALLENGE: crowd sourcing in proteomics analysis and software development

In large-scale proteomics studies there is a temptation, after months of experimental work, to plug resulting data into a convenient-if poorly implemented-set of tools, which may neither do the data justice nor help answer the scientific question. In this paper we have captured key concerns, including arguments for community-wide open source software development and "big data" compatible solutions for the future. For the meantime, we have laid out ten top tips for data processing. With these at hand, a first large-scale proteomics analysis hopefully becomes less daunting to navigate. However there is clearly a real need for robust tools, standard operating procedures and general acceptance of best practises. Thus we submit to the proteomics community a call for a community-wide open set of proteomics analysis challenges--PROTEINCHALLENGE--that directly target and compare data analysis workflows, with the aim of setting a community-driven gold standard for data handling, reporting and sharing.

A combined laser microdissection and mass spectrometry approach reveals new disease relevant proteins accumulating in aggregates of filaminopathy patients

Filaminopathy is a subtype of myofibrillar myopathy caused by mutations in FLNC, the gene encoding filamin C, and histologically characterized by pathologic accumulation of several proteins within skeletal muscle fibers. With the aim to get new insights in aggregate composition, we collected aggregates and control tissue from skeletal muscle biopsies of six myofibrillar myopathy patients harboring three different FLNC mutations by laser microdissection and analyzed the samples by a label-free mass spectrometry approach. A total of 390 proteins were identified, and 31 of those showed significantly higher spectral indices in aggregates compared with patient controls with a ratio >1.8. These proteins included filamin C, other known myofibrillar myopathy associated proteins, and a striking number of filamin C binding partners. Across the patients the patterns were extremely homogeneous. Xin actin-binding repeat containing protein 2, heat shock protein 27, nebulin-related-anchoring protein, and Rab35 could be verified as new filaminopathy biomarker candidates. In addition, further experiments identified heat shock protein 27 and Xin actin-binding repeat containing protein 2 as novel filamin C interaction partners and we could show that Xin actin-binding repeat containing protein 2 and the known interaction partner Xin actin-binding repeat containing protein 1 simultaneously associate with filamin C. Ten proteins showed significant lower spectral indices in aggregate samples compared with patient controls (ratio <0.56) including M-band proteins myomesin-1 and myomesin-2. Proteomic findings were consistent with previous and novel immunolocalization data. Our findings suggest that aggregates in filaminopathy have a largely organized structure of proteins also interacting under physiological conditions. Different filamin C mutations seem to lead to almost identical aggregate compositions. The finding that filamin C was detected as highly abundant protein in aggregates in filaminopathy indicates that our proteomic approach may be suitable to identify new candidate genes among the many MFM patients with so far unknown mutation.

Systems biology in physiology: the vasopressin signaling network in kidney

Over the past 80 years, physiological research has moved progressively in a reductionist direction, providing mechanistic information on a smaller and smaller scale. This trend has culminated in the present focus on "molecular physiology," which deals with the function of single molecules responsible for cellular function. There is a need to assemble the information from the molecular level into models that explain physiological function at cellular, tissue, organ, and whole organism levels. Such integration is the major focus of an approach called "systems biology." The genome sequencing projects provide a basis for a new kind of systems biology called "data-rich" systems biology that is based on large-scale data acquisition methods including protein mass spectrometry, DNA microarrays, and deep sequencing of nucleic acids. These techniques allow investigators to measure thousands of variables simultaneously in response to an external stimulus. My laboratory is applying such an approach to the question: "How does the peptide hormone vasopressin regulate water permeability in the renal collecting duct?" We are using protein mass spectrometry to identify and quantify the phosphoproteome of collecting duct cells. The response to vasopressin, presented in the form of a network model, includes a general downregulation of proline-directed kinases (MAP kinases and cyclin-dependent kinases) and upregulation of basophilic kinases (ACG kinases and calmodulin-dependent kinases). Further progress depends on characterization and localization of candidate protein kinases in these families. The ultimate goal is to use multivariate statistical techniques and differential equations to obtain predictive models describing vasopressin signaling in the renal collecting duct.

The amyloid precursor protein (APP) family members are key players in S-adenosylmethionine formation by MAT2A and modify BACE1 and PSEN1 gene expression-relevance for Alzheimer's disease

Central hallmark of Alzheimer's disease are senile plaques mainly composed of β-amyloid, which is a cleavage product of the amyloid precursor protein (APP). The physiological function of APP and its family members APLP1 and APLP2 is poorly understood. In order to fill this gap, we established a cell-culture based model with simultaneous knockdown of all members of the family. A comprehensive proteome study of the APP/APLP1/APLP2 knockdown cell lysates versus controls revealed significant protein abundance changes of more than 30 proteins. Targeted validation of selected candidates by immunoblotting supported the significant down-regulation of the methionine adenosyltransferase II, alpha (MAT2A) as well as of peroxiredoxin 4 in the knockdown cells. Moreover, MAT2A was significantly down-regulated at the mRNA level as well. MAT2A catalyzes the production of S-adenosylmethionine from methionine and ATP, which plays a pivotal role in the methylation of neurotransmitters, DNA, proteins, and lipids. MAT2A-dependent significant up-regulation of S-adenosylmethionine was also detectable in the knockdown cells compared with controls. Our results point to a role of the APP family proteins in cellular methylation mechanisms and fit to findings of disturbed S-adenosylmethionine levels in tissue and CSF of Alzheimer disease patients versus controls. Importantly, methylation plays a central role for neurotransmitter generation like acetylcholine pointing to a crucial relevance of our findings for Alzheimer's disease. In addition, we identified differential gene expression of BACE1 and PSEN1 in the knockdown cells, which is possibly a consequence of MAT2A deregulation and may indicate a self regulatory mechanism.

Label-free LC-MSMS analysis of vitreous from autoimmune uveitis reveals a significant decrease in secreted Wnt signalling inhibitors DKK3 and SFRP2

Equine recurrent uveitis is a severe and frequent blinding disease in horses which presents with auto-reactive invading T-cells, resulting in the destruction of the inner eye. Infiltration of inflammatory cells into the retina and vitreous is driven by currently unknown guidance cues, however surgical removal of the vitreous (vitrectomy) has proven therapeutically successful. Therefore, proteomic analyses of vitrectomy samples are likely to result in detection of proteins contributing to disease pathogenesis. Vitreous from healthy and ERU diseased horses were directly compared by quantitative mass spectrometry based on label-free quantification of peak intensities across samples. We found a significant upregulation of complement and coagulation cascades and downregulation of negative paracrine regulators of canonical Wnt signalling including the Wnt signalling inhibitors DKK3 and SFRP2. Based on immunohistochemistry, both proteins are expressed in equine retina and suggest localisation to retinal Müller glial cells (RMG), which may be the source cells for these proteins. Furthermore, retinal expression levels and patterns of DKK3 change in response to ERU. Since many other regulated proteins identified here are associated with RMG cells, these cells qualify as the prime responders to autoimmune triggers.