Identification of isomeric acylcarnitines.

(A) Shown are three isomeric metabolites in one combined LC-MS run and individually: (B) 2-methylbutyroylcarnitine (C4-methyl), (C) isovalerylcarnitine (C4-methyl), and (D) valerylcarnitine (C5). Following transitions were used: 381.2 / 220.1 (blue); 381.2 / 145.1 (red) and 381.2 / 84 Da (orange), a Gaussian smooth width of 2 was used.</p

Chemical structure and identified fragment ions generated in the collision cell of the mass spectrometer of a C6:0 acylcarnitine, derivatized by 3NPH.

Displayed are the four most common fragments found in all 3NPH-acylcarnitines.</p

Acylcarnitine profiling by low-resolution LC-MS - Fig 5

Volcano plots of acylcarnitines in mouse tissues and liquids: (A) heart versus liver, (B) serum versus blood, (C) brain versus fat, (D) muscle versus heart. The negative log10-transformed p-values of the Student's t-test are plotted against the log2 ratios of fold change between specimens. The solid lines represent the nominal significance level for the Student's t-test (FDR ≤ 0.05). Three biological replicates were used for each specimen.</p

A mass versus retention time plot of all repeatedly identified acylcarnitines (shown for liver) shows a linear regression, R² values close to 1, for each acylcarnitine class.

An increasing carbon number of the carbon chain shifts the elution time to the right, leading to a straight line of saturated acylcarnitines in the plot (green triangles). Carbon chains containing hydroxyl groups shifted in a parallel way to the left (purple cross), unsaturated species (red, black, and blue triangles) also to the left, but more apparent for longer carbon chain types. All dicarboxylic containing species eluted at very similar time points (blue diamonds), isotopically labeled internal standards are shown in orange triangles.</p

High-resolution fragment spectra (A-C) and low-resolution transitions (D-F) of 3NPH derivatized acylcarnitines.

MS2 spectra of the endogenous 3NPH acylcarnitines: (A) valerylcarnitine (C5:0), (B) octanoylcarnitine (C8:0), and (C) palmitoylcarnitine (C16:0). The three most intense transitions (220, 145, and 84 Da) of the same metabolite species, but isotopically labeled, were monitored by a low-resolution QTrap instrument: (D) isovalerylcarnitine-D9 (C5:0, 390.43 Da, RT 14.14), (E) octanoylcarnitine-D3 (C8:0, 426.47 Da, RT 18.47), and (F) palmitoylcarnitine-D3 (C16:0, 538.69 Da, RT 29.07). Following fragment masses were monitored: 220.1 (blue); 145.1 (red) and 84 Da (orange). No Gaussian smoothing was used.</p

Metabolome and Proteome Profiling of Complex I Deficiency Induced by Rotenone

Complex I (CI; NADH dehydrogenase) deficiency causes mitochondrial diseases, including Leigh syndrome. A variety of clinical symptoms of CI deficiency are known, including neurodegeneration. Here, we report an integrative study combining liquid chromatography–mass spectrometry (LC–MS)-based metabolome and proteome profiling in CI deficient HeLa cells. We report a rapid LC–MS-based method for the relative quantification of targeted metabolome profiling with an additional layer of confidence by applying multiple reaction monitoring (MRM) ion ratios for further identity confirmation and robustness. The proteome was analyzed by label-free quantification (LFQ). More than 6000 protein groups were identified. Pathway and network analyses revealed that the respiratory chain was highly deregulated, with metabolites such as FMN, FAD, NAD⁺, and ADP, direct players of the OXPHOS system, and metabolites of the TCA cycle decreased up to 100-fold. Synthesis of functional iron–sulfur clusters, which are of central importance for the electron transfer chain, and degradation products like bilirubin were also significantly reduced. Glutathione metabolism on the pathway level, as well as individual metabolite components such as NADPH, glutathione (GSH), and oxidized glutathione (GSSG), was downregulated. Overall, metabolome and proteome profiles in CI deficient cells correlated well, supporting our integrated approach

Integrative Analysis of Transcriptomics, Proteomics, and Metabolomics Data of White Adipose and Liver Tissue of High-Fat Diet and Rosiglitazone-Treated Insulin-Resistant Mice Identified Pathway Alterations and Molecular Hubs

The incidences of obesity and type 2 diabetes are rapidly increasing and have evolved into a global epidemic. In this study, we analyzed the molecular effects of high-fat diet (HFD)-induced insulin-resistance on mice in two metabolic target tissues, the white adipose tissue (WAT) and the liver. Additionally, we analyzed the effects of drug treatment using the specific PPARγ ligand rosiglitazone. We integrated transcriptome, proteome, and metabolome data sets for a combined holistic view of molecular mechanisms in type 2 diabetes. Using network and pathway analyses, we identified hub proteins such as SDHB and SUCLG1 in WAT and deregulation of major metabolic pathways in the insulin-resistant state, including the TCA cycle, oxidative phosphorylation, and branched chain amino acid metabolism. Rosiglitazone treatment resulted mainly in modulation via PPAR signaling and oxidative phosphorylation in WAT only. Interestingly, in HFD liver, we could observe a decrease of proteins involved in vitamin B metabolism such as PDXDC1 and DHFR and the according metabolites. Furthermore, we could identify sphingosine (Sph) and sphingosine 1-phosphate (SP1) as a drug-specific marker pair in the liver. In summary, our data indicate physiological plasticity gained by interconnected molecular pathways to counteract metabolic dysregulation due to high calorie intake and drug treatment

Quantitative Analysis of global Ubiquitination in HeLa Cells by Mass Spectrometry

Ubiquitination regulates a host of cellular processes by labeling proteins for degradation, but also by functioning as a regulatory, nonproteolytic posttranslational modification. Proteome-wide strategies to monitor changes in ubiquitination profiles are important to obtain insight into the various cellular functions of ubiquitination. Here we describe generation of stable cell lines expressing a tandem hexahistidine-biotin tag (HB-tag) fused to ubiquitin for two-step purification of the ubiquitinated proteome under fully denaturing conditions. Using this approach we identified 669 ubiquitinated proteins from HeLa cells, including 44 precise ubiquitin attachment sites on substrates and all seven possible ubiquitin chain-linkage types. To probe the dynamics of ubiquitination in response to perturbation of the ubiquitin/proteasome pathway, we combined ubiquitin profiling with quantitative mass spectrometry using the stable isotope labeling with amino acids in cell culture (SILAC) strategy. We compared untreated cells and cells treated with the proteasome inhibitor MG132 to identify ubiquitinated proteins that are targeted to the proteasome for degradation. A number of proteasome substrates were identified. In addition, the quantitative approach allowed us to compare proteasome targeting by different ubiquitin chain topologies in vivo. The tools and strategies described here can be applied to detect changes in ubiquitination dynamics in response to various changes in growth conditions and cellular stress and will contribute to our understanding of the ubiquitin/proteasome system

Quantitative Analysis of global Ubiquitination in HeLa Cells by Mass Spectrometry

Ubiquitination regulates a host of cellular processes by labeling proteins for degradation, but also by functioning as a regulatory, nonproteolytic posttranslational modification. Proteome-wide strategies to monitor changes in ubiquitination profiles are important to obtain insight into the various cellular functions of ubiquitination. Here we describe generation of stable cell lines expressing a tandem hexahistidine-biotin tag (HB-tag) fused to ubiquitin for two-step purification of the ubiquitinated proteome under fully denaturing conditions. Using this approach we identified 669 ubiquitinated proteins from HeLa cells, including 44 precise ubiquitin attachment sites on substrates and all seven possible ubiquitin chain-linkage types. To probe the dynamics of ubiquitination in response to perturbation of the ubiquitin/proteasome pathway, we combined ubiquitin profiling with quantitative mass spectrometry using the stable isotope labeling with amino acids in cell culture (SILAC) strategy. We compared untreated cells and cells treated with the proteasome inhibitor MG132 to identify ubiquitinated proteins that are targeted to the proteasome for degradation. A number of proteasome substrates were identified. In addition, the quantitative approach allowed us to compare proteasome targeting by different ubiquitin chain topologies in vivo. The tools and strategies described here can be applied to detect changes in ubiquitination dynamics in response to various changes in growth conditions and cellular stress and will contribute to our understanding of the ubiquitin/proteasome system

Quantitative Analysis of global Ubiquitination in HeLa Cells by Mass Spectrometry

Ubiquitination regulates a host of cellular processes by labeling proteins for degradation, but also by functioning as a regulatory, nonproteolytic posttranslational modification. Proteome-wide strategies to monitor changes in ubiquitination profiles are important to obtain insight into the various cellular functions of ubiquitination. Here we describe generation of stable cell lines expressing a tandem hexahistidine-biotin tag (HB-tag) fused to ubiquitin for two-step purification of the ubiquitinated proteome under fully denaturing conditions. Using this approach we identified 669 ubiquitinated proteins from HeLa cells, including 44 precise ubiquitin attachment sites on substrates and all seven possible ubiquitin chain-linkage types. To probe the dynamics of ubiquitination in response to perturbation of the ubiquitin/proteasome pathway, we combined ubiquitin profiling with quantitative mass spectrometry using the stable isotope labeling with amino acids in cell culture (SILAC) strategy. We compared untreated cells and cells treated with the proteasome inhibitor MG132 to identify ubiquitinated proteins that are targeted to the proteasome for degradation. A number of proteasome substrates were identified. In addition, the quantitative approach allowed us to compare proteasome targeting by different ubiquitin chain topologies in vivo. The tools and strategies described here can be applied to detect changes in ubiquitination dynamics in response to various changes in growth conditions and cellular stress and will contribute to our understanding of the ubiquitin/proteasome system