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Abstract Background Methylmalonic acidemia (MMA) is a rare inborn error of propionate metabolism caused by deficiency of the mitochondrial methylmalonyl-CoA mutase (MUT) enzyme. As matter of fact, MMA patients manifest impairment of the primary metabolic network with profound damages that involve several cell components, many of which have not been discovered yet. We employed cellular models and patients-derived fibroblasts to refine and uncover new pathologic mechanisms connected with MUT deficiency through the combination of multi-proteomics and bioinformatics approaches. Results Our data show that MUT deficiency is connected with profound proteome dysregulations, revealing molecular actors involved in lysosome and autophagy functioning. To elucidate the effects of defective MUT on lysosomal and autophagy regulation, we analyzed the morphology and functionality of MMA-lysosomes that showed deep alterations, thus corroborating omics data. Lysosomes of MMA cells present as enlarged vacuoles with low degradative capabilities. Notwithstanding, treatment with an anti-propionigenic drug is capable of totally rescuing lysosomal morphology and functional activity in MUT-deficient cells. These results indicate a strict connection between MUT deficiency and lysosomal-autophagy dysfunction, providing promising therapeutic perspectives for MMA. Conclusions Defective homeostatic mechanisms in the regulation of autophagy and lysosome functions have been demonstrated in MUT-deficient cells. Our data prove that MMA triggers such dysfunctions impacting on autophagosome-lysosome fusion and lysosomal activity.

Abstract Mouse is the mammalian model of choice to study human health and disease due to its size, ease of breeding and the natural occurrence of conditions mimicking human pathology. Here we design and validate multiple reaction monitoring mass spectrometry (MRM-MS) assays for quantitation of 2118 unique proteins in 20 murine tissues and organs. We provide open access to technical aspects of these assays to enable their implementation in other laboratories, and demonstrate their suitability for proteomic profiling in mice by measuring normal protein abundances in tissues from three mouse strains: C57BL/6NCrl, NOD/SCID, and BALB/cAnNCrl. Sex- and strain-specific differences in protein abundances are identified and described, and the measured values are freely accessible via our MouseQuaPro database: http://mousequapro.proteincentre.com . Together, this large library of quantitative MRM-MS assays established in mice and the measured baseline protein abundances represent an important resource for research involving mouse models.

Abstract Autonomous migration is essential for the function of immune cells such as neutrophils and plays an important role in numerous diseases. The ability to routinely measure or target it would offer a wealth of clinical applications. Video microscopy of live cells is ideal for migration analysis, but cannot be performed at sufficiently high-throughput (HT). Here we introduce ComplexEye, an array microscope with 16 independent aberration-corrected glass lenses spaced at the pitch of a 96-well plate to produce high-resolution movies of migrating cells. With the system, we enable HT migration analysis of immune cells in 96- and 384-well plates with very energy-efficient performance. We demonstrate that the system can measure multiple clinical samples simultaneously. Furthermore, we screen 1000 compounds and identify 17 modifiers of migration in human neutrophils in just 4 days, a task that requires 60-times longer with a conventional video microscope. ComplexEye thus opens the field of phenotypic HT migration screens and enables routine migration analysis for the clinical setting.

Background/Objectives: Acute myocardial infarction (AMI), characterized by irreversible heart muscle damage and impaired cardiac function caused by myocardial ischemia, is a leading cause of global mortality. The damage associated with reperfusion, particularly mitochondrial dysfunction and reactive oxygen species (ROS) formation, has emerged as a crucial factor in the pathogenesis of cardiac diseases, leading to the recognition of mitochondrial proteins as potential markers for myocardial damage. This study aimed to identify differentially expressed proteins based on the type of cardiac injury, in particular those with and without reperfusion. Methods: Male C57Bl/6J mice were either left untreated, sham-operated, received non-reperfused AMI, or reperfused AMI. Twenty-four hours after the procedures, left ventricular (LV) function and morphological changes including infarct size were determined using echocardiography and triphenyl tetrazolium chloride (TTC) staining, respectively. In addition, plasma was isolated and subjected to untargeted mass spectrometry and, further on, the ELISA-based validation of candidate proteins. Results: We identified mitochondrial creatine kinase 2 (Ckmt2) as a differentially regulated protein in plasma of mice with reperfused but not non-reperfused AMI. Elevated levels of Ckmt2 were significantly associated with infarct size and impaired LV function following reperfused AMI, suggesting a specific involvement in reperfusion damage. Conclusions: Our study highlights the potential of plasma Ckmt2 as a biomarker for assessing reperfusion injury and its impact on cardiac function and morphology in the acute phase of MI.

Abstract Background The growing interest in the field of proteomics has increased the demand for software tools and applications that process and analyze the resulting data. And even though the purpose of these tools can vary significantly, they usually share a basic set of features, including the handling of protein and peptide sequences, the visualization of (and interaction with) spectra and chromatograms, and the parsing of results from various proteomics search engines. Developers typically spend considerable time and effort implementing these support structures, which detracts from working on the novel aspects of their tool. Results In order to simplify the development of proteomics tools, we have implemented an open-source support library for computational proteomics, called compomics-utilities. The library contains a broad set of features required for reading, parsing, and analyzing proteomics data. compomics-utilities is already used by a long list of existing software, ensuring library stability and continued support and development. Conclusions As a user-friendly, well-documented and open-source library, compomics-utilities greatly simplifies the implementation of the basic features needed in most proteomics tools. Implemented in 100% Java, compomics-utilities is fully portable across platforms and architectures. Our library thus allows the developers to focus on the novel aspects of their tools, rather than on the basic functions, which can contribute substantially to faster development, and better tools for proteomics.

Abstract Background Cancer arises from normal cells through the stepwise accumulation of genetic alterations. Cancer development can be studied by direct genetic manipulation within experimental models of tumorigenesis. Thereby, confusion by the genetic heterogeneity of patients can be circumvented. Moreover, identification of the critical changes that convert a pre-malignant cell into a metastatic, therapy resistant tumor cell, however, is one necessary step to develop effective and selective anti-cancer drugs. Thus, for the current study a cell culture model for malignant transformation was used: Primary human fibroblasts of the BJ strain were sequentially transduced with retroviral vectors encoding the genes for hTERT (cell line BJ-T), simian virus 40 early region (SV40 ER, cell line BJ-TE) and H-Ras V12 (cell line BJ-TER). Results The stepwise malignant transformation of human fibroblasts was analyzed on the protein level by differential proteome analysis. We observed 39 regulated protein spots and therein identified 67 different proteins. The strongest change of spot patterns was detected due to integration of SV40 ER. Among the proteins being significantly regulated during the malignant transformation process well known proliferating cell nuclear antigen (PCNA) as well as the chaperones mitochondrial heat shock protein 75 kDa (TRAP-1) and heat shock protein HSP90 were identified. Moreover, we find out, that TRAP-1 is already up-regulated by means of SV40 ER expression instead of H-Ras V12. Furthermore Peroxiredoxin-6 (PRDX6), Annexin A2 (p36), Plasminogen activator inhibitor 2 (PAI-2) and Keratin type II cytoskeletal 7 (CK-7) were identified to be regulated. For some protein candidates we confirmed our 2D-PAGE results by Western Blot. Conclusion These findings give further hints for intriguing interactions between the p16-RB pathway, the mitochondrial chaperone network and the cytoskeleton. In summary, using a cell culture model for malignant transformation analyzed with 2D-PAGE, proteome and cellular changes can be related to defined steps of tumorigenesis.

Abstract Background Mass spectrometry based quantification of peptides can be performed using the iTRAQ™ reagent in conjunction with mass spectrometry. This technology yields information about the relative abundance of single peptides. A method for the calculation of reliable quantification information is required in order to obtain biologically relevant data at the protein expression level. Results A method comprising sound error estimation and statistical methods is presented that allows precise abundance analysis plus error calculation at the peptide as well as at the protein level. This yields the relevant information that is required for quantitative proteomics. Comparing the performance of our method named Quant with existing approaches the error estimation is reliable and offers information for precise bioinformatic models. Quant is shown to generate results that are consistent with those produced by ProQuant™, thus validating both systems. Moreover, the results are consistent with that of Mascot™ 2.2. The MATLAB® scripts of Quant are freely available via http://www.protein-ms.de and http://sourceforge.net/projects/protms/, each under the GNU Lesser General Public License. Conclusion The software Quant demonstrates improvements in protein quantification using iTRAQ™. Precise quantification data can be obtained at the protein level when using error propagation and adequate visualization. Quant integrates both and additionally provides the possibility to obtain more reliable results by calculation of wise quality measures. Peak area integration has been replaced by sum of intensities, yielding more reliable quantification results. Additionally, Quant allows the combination of quantitative information obtained by iTRAQ™ with peptide and protein identifications from popular tandem MS identification tools. Hence Quant is a useful tool for the proteomics community and may help improving analysis of proteomic experimental data. In addition, we have shown that a lognormal distribution fits the data of mass spectrometry based relative peptide quantification.

Abstract Background Mascot™ is a commonly used protein identification program for MS as well as for tandem MS data. When analyzing huge shotgun proteomics datasets with Mascot™'s native tools, limits of computing resources are easily reached. Up to now no application has been available as open source that is capable of converting the full content of Mascot™ result files from the original MIME format into a database-compatible tabular format, allowing direct import into database management systems and efficient handling of huge datasets analyzed by Mascot™. Results A program called mres2x is presented, which reads Mascot™ result files, analyzes them and extracts either selected or all information in order to store it in a single file or multiple files in formats which are easier to handle downstream of Mascot™. It generates different output formats. The output of mres2x in tab format is especially designed for direct high-performance import into relational database management systems using native tools of these systems. Having the data available in database management systems allows complex queries and extensive analysis. In addition, the original peak lists can be extracted in DTA format suitable for protein identification using the Sequest™ program, and the Mascot™ files can be split, preserving the original data format. During conversion, several consistency checks are performed. mres2x is designed to provide high throughput processing combined with the possibility to be driven by other computer programs. The source code including supplement material and precompiled binaries is available via http://www.protein-ms.de and http://sourceforge.net/projects/protms/. Conclusion The database upload allows regrouping of the MS/MS results using a database management system and complex analyzing queries using SQL without the need to run new Mascot™ searches when changing grouping parameters.

Abstract Background: Biological Mass Spectrometry is used to analyse peptides and proteins. A mass spectrum generates a list of measured mass to charge ratios and intensities of ionised peptides, which is called a peak-list. In order to classify the underlying amino acid sequence, the acquired spectra are usually compared with synthetic ones. Development of suitable methods of direct peak-list comparison may be advantageous for many applications. Results: The pairwise peak-list comparison is a multistage process composed of matching of peaks embedded in two peak-lists, normalisation, scaling of peak intensities and dissimilarity measures. In our analysis, we focused on binary and intensity based measures. We have modified the measures in order to comprise the mass spectrometry specific properties of mass measurement accuracy and non-matching peaks. We compared the labelling of peak-list pairs, obtained using different factors of the pairwise peak-list comparison, as being the same or different to those determined by sequence database searches. In order to elucidate how these factors influence the peak-list comparison we adopted an analysis of variance type method with the partial area under the ROC curve as a dependent variable. Conclusion: The analysis of variance provides insight into the relevance of various factors influencing the outcome of the pairwise peak-list comparison. For large MS/MS and PMF data sets the outcome of ANOVA analysis was consistent, providing a strong indication that the results presented here might be valid for many various types of peptide mass measurements.

Dolichyl phosphates (DolP) are ubiquitous lipids that are present in almost all eukaryotic membranes. They play a key role in several protein glycosylation pathways and the formation of glycosylphosphatidylinositol anchors. These lipids constitute only ~0.1% of total phospholipids, and their analysis by reverse phase (RP) liquid chromatography–high-resolution mass spectrometry (LC–HRMS) is challenging due to their high lipophilicity (log P > 20), poor ionization efficiency, and relatively low abundance. To overcome these challenges, we have introduced a new approach for DolP analysis by combining trimethylsilyldiazomethane (TMSD)-based phosphate methylation and HRMS analysis. The analytical method was validated for its reproducibility, sensitivity, and accuracy. The established workflow was successfully applied for the simultaneous characterization and quantification of DolP species with different isoprene units in lipid extracts of HeLa and Saccharomyces cerevisiae cells.

Abstract Background Mass spectrometry based proteomics result in huge amounts of data that has to be processed in real time in order to efficiently feed identification algorithms and to easily integrate in automated environments. We present wiff2dta, a tool created to convert MS/MS data obtained using Applied Biosystem's QStar and QTrap 2000 and 4000 series. Results Comparing the performance of wiff2dta with the standard tools, we find wiff2dta being the fastest solution for extracting spectrum data from ABIs raw file format. wiff2dta is at least 10% faster than the standard tools. It is also capable of batch processing and can be easily integrated in high throughput environments. The program is freely available via http://www.protein-ms.de, http://sourceforge.net/projects/protms/ and is also available from Applied Biosystems. Conclusions wiff2dta offers the possibility to run as stand-alone application or within a batch process as command-line tool integrated in automation and high-throughput environments. It is more efficient than the state-of-the-art tools provided.

The primary prevention, early detection, and treatment of cardiovascular disease (CVD) have been long-standing scientific research goals worldwide. In the past decades, traditional blood lipid profiles have been routinely used in clinical practice to estimate the risk of CVDs such as atherosclerotic cardiovascular disease (ASCVD) and as treatment targets for the primary prevention of adverse cardiac events. These blood lipid panel tests often fail to fully predict all CVD risks and thus need to be improved. A comprehensive analysis of molecular species of lipids and metabolites (defined as lipidomics and metabolomics, respectively) can provide molecular insights into the pathophysiology of the disease and could serve as diagnostic and prognostic indicators of disease. Mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based lipidomics and metabolomics analysis have been increasingly used to study the metabolic changes that occur during CVD pathogenesis. In this review, we provide an overview of various MS-based platforms and approaches that are commonly used in lipidomics and metabolomics workflows. This review summarizes the lipids and metabolites in human plasma/serum that have recently (from 2018 to December 2022) been identified as promising CVD biomarkers. In addition, this review describes the potential pathophysiological mechanisms associated with candidate CVD biomarkers. Future studies focused on these potential biomarkers and pathways will provide mechanistic clues of CVD pathogenesis and thus help with the risk assessment, diagnosis, and treatment of CVD.

In orthopedics, musculoskeletal disorders, i.e., non-union of bone fractures or osteoporosis, can have common histories and symptoms related to pathological hypoxic conditions induced by aging, trauma or metabolic disorders. Here, we observed that hypoxic conditions (2% O2) suppressed the osteogenic differentiation of human bone marrow-derived mesenchymal cells (hBMSC) in vitro and simultaneously increased reactive oxygen species (ROS) production. We assumed that cellular origin and cargo of extracellular vesicles (EVs) affect the osteogenic differentiation capacity of hBMSCs cultured under different oxygen pressures. Proteomic analysis revealed that EVs isolated from osteogenic differentiated hBMSC cultured under hypoxia (hypo-osteo EVs) or under normoxia (norm-osteo EVs) contained distinct protein profiles. Extracellular matrix (ECM) components, antioxidants and pro-osteogenic proteins were decreased in hypo-osteo EVs. The proteomic analysis in our previous study revealed that under normoxic culture conditions, pro-osteogenic proteins and ECM components have higher concentrations in norm-osteo EVs than in EVs derived from naïve hBMSCs (norm-naïve EVs). When selected for further analysis, five anti-hypoxic proteins were significantly upregulated (response to hypoxia) in norm-osteo EVs. Three of them are characterized as antioxidant proteins. We performed qRT-PCR to verify the corresponding gene expression levels in the norm-osteo EVs’ and norm-naïve EVs’ parent cells cultured under normoxia. Moreover, we observed that norm-osteo EVs rescued the osteogenic ability of naïve hBMSCs cultured under hypoxia and reduced hypoxia-induced elevation of ROS production in osteogenic differentiated hBMSCs, presumably by inducing expression of anti-hypoxic/ antioxidant and pro-osteogenic genes.