Multispecies Benchmark Analysis for LC-MS/MS Validation and Performance Evaluation in Bottom-Up Proteomics.

We present an instrument-independent benchmark procedure and software (LFQ_bout) for the validation and comparative evaluation of the performance of LC-MS/MS and data processing workflows in bottom-up proteomics. The procedure enables a back-to-back comparison of common and emerging workflows, e.g., diaPASEF or ScanningSWATH, and evaluates the impact of arbitrary and inadequately documented settings or black-box data processing algorithms. It enhances the overall performance and quantification accuracy by recognizing and reporting common quantification errors.

Mitochondrial proteome analysis reveals that an augmented cytochrome c oxidase assembly and activity potentiates respiratory capacity in sarcoma.

Mitochondrial oxidative phosphorylation (OXPHOS) is an obligatory process in sarcoma. Despite that, the metabolic programming of sarcoma mitochondria is still unknown. To obtain a comprehensive metabolic insight of mitochondria, we developed a mouse fibrosarcoma model by injecting 3-methylcholanthrene and compared mitochondrial proteomes between sarcoma and its contralateral normal muscle using mass spectrometry. Our study identified ∼449 proteins listed in the SwissProt databases, and all the data sets are available via ProteomeXchange with the identifier PXD044903. In sarcoma, 49 mitochondrial proteins were found differentially expressed, including 36 proteins up-regulated and 13 proteins down-regulated, with the significance of p-value <0.05 and the log2[fold change] > 1 and < -1 as compared to normal muscle. Our data revealed that various anaplerotic reactions actively replenish the TCA cycle in sarcoma. The comparative expression profile and Western blotting analysis of OXPHOS subunits showed that complex-IV subunits, MT-CO3 and COX6A1, were significantly up-regulated in sarcoma vs. normal muscle. Further, biochemical and physiological assays confirmed enhanced complex-IV specific enzymatic and supercomplex activities with a concomitant increase of oxygen consumption rate in sarcoma mitochondria compared to normal muscle. Validation with human post-operative sarcoma tissues also confirms an increased MT-CO3 expression compared to normal tissue counterparts. Thus, our data comprehensively analyses the mitochondrial proteome and identifies augmented complex-IV assembly and activity in sarcoma.

Multimerin 1 aids in the progression of ovarian cancer possibly via modulation of DNA damage response and repair pathways.

Ovarian cancer is one of the leading causes of deaths among women. Despite advances in the treatment regimes, a high rate of diagnosis in the advanced stage makes it almost an incurable malignancy. Thus, more research efforts are required to identify potential molecular markers for early detection of the disease and therapeutic targets to augment the survival rate of ovarian cancer patients. Previously, in this context, we identified dysregulated expression of multimerin 1 (MMRN1) in ovarian cancer. To elucidate the relationship between MMRN1 expression and ovarian cancer progression, siRNA-based MMRN1 knockdown was employed and various cell assays were performed to study its effect on ovarian cancer cells. In addition, network of dysregulated proteins was identified by quantitative proteomics and associated pathways were explored by bioinformatics analysis. MMRN1 silencing showed a significant reduction in cell viability, adhesion, migration, and invasion and a high frequency of cell apoptosis. Label-free quantitative proteomics and in-depth statistical analysis identified 448 dysregulated proteins, majority of which were overexpressed in MMRN1 knockdown cells. The pathways overrepresented in ovarian cancer were DNA replication, mismatch repair, nucleotide excision repair, and cell cycle regulation. Conclusively, the findings of this study suggest that MMRN1 aids in the progression of ovarian cancer via modulation of DNA damage response and repair pathways.

Parasite and Pesticide Impacts on the Bumblebee (Bombus terrestris) Haemolymph Proteome.

Pesticides pose a potential threat to bee health, especially in combination with other stressors, such as parasites. However, pesticide risk assessment tests pesticides in isolation from other stresses, i.e., on otherwise healthy bees. Through molecular analysis, the specific impacts of a pesticide or its interaction with another stressor can be elucidated. Molecular mass profiling by MALDI BeeTyping® was used on bee haemolymph to explore the signature of pesticidal and parasitic stressor impacts. This approach was complemented by bottom-up proteomics to investigate the modulation of the haemoproteome. We tested acute oral doses of three pesticides-glyphosate, Amistar and sulfoxaflor-on the bumblebee Bombus terrestris, alongside the gut parasite Crithidia bombi. We found no impact of any pesticide on parasite intensity and no impact of sulfoxaflor or glyphosate on survival or weight change. Amistar caused weight loss and 19-41% mortality. Haemoproteome analysis showed various protein dysregulations. The major pathways dysregulated were those involved in insect defences and immune responses, with Amistar having the strongest impact on these dysregulated pathways. Our results show that even when no response can be seen at a whole organism level, MALDI BeeTyping® can detect effects. Mass spectrometry analysis of bee haemolymph provides a pertinent tool to evaluate stressor impacts on bee health, even at the level of individuals.

Proteomics analysis: inhibiting the expression of P62 protein by chloroquine combined with dacarbazine can reduce the malignant progression of uveal melanoma.

BACKGROUND: Although uveal melanoma (UM) at the early stage is controllable to some extent, it inevitably ultimately leads to death due to its metastasis. At present, the difficulty is that there is no way to effectively tackle the metastasis. It is hypothesized that these will be treated by target molecules, but the recognized target molecule has not yet been found. In this study, the target molecule was explored through proteomics. METHODS: Transgenic enhanced green fluorescent protein (EGFP) inbred nude mice, which spontaneously display a tumor microenvironment (TME), were used as model animal carriers. The UM cell line 92.1 was inoculated into the brain ventricle stimulating metastatic growth of UM, and a graft re-cultured Next, the UM cell line 92.1-A was obtained through monoclonal amplification, and a differential proteomics database, between 92.1 and ectopic 92.1-A, was established. Finally, bioinformatics methodologies were adopted to optimize key regulatory proteins, and in vivo and in vitro functional verification and targeted drug screening were performed. RESULTS: Cells and tissues displaying green fluorescence in animal models were determined as TME characteristics provided by hosts. The data of various biological phenotypes detected proved that 92.1-A were more malignant than 92.1. Besides this malignancy, the key protein p62 (SQSTM1), selected from 5267 quantifiable differential proteomics databases, was a multifunctional autophagy linker protein, and its expression could be suppressed by chloroquine and dacarbazine. Inhibition of p62 could reduce the malignancy degree of 92.1-A. CONCLUSIONS: As the carriers of human UM orthotopic and ectopic xenotransplantation, transgenic EGFP inbred nude mice clearly display the characteristics of TME. In addition, the p62 protein optimized by the proteomics is the key protein that increases the malignancy of 92.1 cells, which therefore provides a basis for further exploration of target molecule therapy for refractory metastatic UM.

Effects of Physiological and Pathological Urea Concentrations on Human Microvascular Endothelial Cells.

Urea is the uremic toxin accumulating with the highest concentration in the plasma of chronic kidney disease (CKD) patients, not being completely cleared by dialysis. Urea accumulation is reported to exert direct and indirect side effects on the gastrointestinal tract, kidneys, adipocytes, and cardiovascular system (CVS), although its pathogenicity is still questioned since studies evaluating its side effects lack homogeneity. Here, we investigated the effects of physiological and pathological urea concentrations on a human endothelial cell line from the microcirculation (Human Microvascular Endothelial Cells-1, HMEC-1). Urea (5 g/L) caused a reduction in the proliferation rate after 72 h of exposure and appeared to be a potential endothelial-to-mesenchymal transition (EndMT) stimulus. Moreover, urea induced actin filament rearrangement, a significant increase in matrix metalloproteinases 2 (MMP-2) expression in the medium, and a significant up- or down-regulation of other EndMT biomarkers (keratin, fibrillin-2, and collagen IV), as highlighted by differential proteomic analysis. Among proteins whose expression was found to be significantly dysregulated following exposure of HMEC-1 to urea, dimethylarginine dimethylaminohydrolase (DDAH) and vasorin turned out to be down-regulated. Both proteins have been directly linked to cardiovascular diseases (CVD) by in vitro and in vivo studies. Future experiments will be needed to deepen their role and investigate the signaling pathways in which they are involved to clarify the possible link between CKD and CVD.

Differential proteomics reveals main determinants for the improved pectinase activity in UV-mutagenized Aspergillus niger strain.

OBJECTIVES: To reveal the potential mechanism and key determinants that contributed to the improved pectinase activity in Aspergillus niger mutant EIMU2, which was previously obtained by UV-mutagenesis from the wild-type A. niger EIM-6. RESULTS: Proteomic analysis for Aspergillus niger EIMU2 by two-dimensional electrophoresis demonstrated that mutant EIMU2 harbored a multiple enzyme system for the degradation of pectin, mainly constituting by main-chain-cleaving enzymes polygalacturonase, pectate lyase, pectinesterase, and some accessory enzymes rhamnogalacturonan lyase and arabinofuranosidase. Further quantitatively differential proteomic analysis revealed that the quantities of four proteins, pectinesterase, rhamnogalacturonan lyase A, DNA-directed RNA polymerase A, and a hypothetical protein in strain EIMU2 were much higher than those in EIM-6. PCR amplification, sequencing and alignment analysis of genes for the two main members of pectin-degrading enzymes, pectate lyase and polygalacturonase showed that their sequences were completely consistent in A. niger EIM-6 and mutant EIMU2. CONCLUSIONS: The result demonstrated that the improved pectinase activity by UV-mutagenesis in A. niger EIMU2 was probably contributed to the up-regulated expression of rhamnogalacturonan lyase, or pectinesterase, which resulted in the optimization of synergy amongst different components of pectin-degrading enzymes.

[Mechanism of paeonol combined with paeoniflorin against myocardial ischemia injury:based on proteomics].

The study aims to investigate the effect of the compatibility of paeonol and paeoniflorin(hereinafter referred to as the compatibility) on the expression of myocardial proteins in rats with myocardial ischemia injury and explore the underlying mechanism of the compatibility against myocardial ischemia injury. First, the acute myocardial infarction rat model was established by ligation of the anterior descending branch of the left coronary artery. The model rats were given(ig) paeonol and paeoniflorin. Then protein samples were collected from rat cardiac tissue and quantified by tandem mass tags(TMT) to explore the differential proteins after drug intervention. The experimental results showed that differential proteins mainly involved phagocytosis engulfment, extracellular space, and antigen binding, as well as Kyoto encyclopedia of genes and genomes(KEGG) pathways of complement and coagulation cascades, syste-mic lupus erythematosus, and ribosome. In this study, the target proteins and related signaling pathways identified by differential proteomics may be the biological basis of the compatibility against myocardial ischemia injury in rats.

[Method and application of proteomics in study of targets of traditional Chinese medicines].

The study on the targets of traditional Chinese medicine is an important part of researchers using modern scientific language to clarify the mechanism of traditional Chinese medicine. However, the research on the targets of Chinese medicine is full of challenges due to the complexity of active ingredients. As a branch of systems biology, proteomics focus on specific proteins in living organisms from a holistic perspective, which significantly improves the efficiency of targets discovery and has obvious advantages in the research of targets of Chinese medicine. Based on relevant literature and different methods used in targets of Chinese medicine, proteomics can be divided into chemical proteomics, differential proteomics and quantitative proteomics. The applications of the above three methods are illustrated in this paper as well, which will provide new methods and ideas for the study of the mechanism of Chinese medicine in the future.

"Differential Visual Proteomics": Enabling the Proteome-Wide Comparison of Protein Structures of Single-Cells.

Proteins are involved in all tasks of life, and their characterization is essential to understand the underlying mechanisms of biological processes. We present a method called "differential visual proteomics" geared to study proteome-wide structural changes of proteins and protein-complexes between a disturbed and an undisturbed cell or between two cell populations. To implement this method, the cells are lysed and the lysate is prepared in a lossless manner for single-particle electron microscopy (EM). The samples are subsequently imaged in the EM. Individual particles are computationally extracted from the images and pooled together, while keeping track of which particle originated from which specimen. The extracted particles are then aligned and classified. A final quantitative analysis of the particle classes found identifies the particle structures that differ between positive and negative control samples. The algorithm and a graphical user interface developed to perform the analysis and to visualize the results were tested with simulated and experimental data. The results are presented, and the potential and limitations of the current implementation are discussed. We envisage the method as a tool for the untargeted profiling of the structural changes in the proteome of single-cells as a response to a disturbing force.

Elucidation of protein biomarkers in plasma and urine for epsilon toxin exposure in mouse model.

Epsilon toxin (ETX) is the major virulence determinant of C. perfringens type B or type D strains, causing diseases in animals, besides being a listed biological and toxin warfare (BTW) agent. Keeping in mind the high lethality and the rapid onset of clinical manifestations, early diagnosis of epsilon toxin exposure is of paramount importance for implementation of appropriate medical countermeasures. Using a 2DE-MS approach, the present study is the first comprehensive proteomic elucidation of ETX-induced protein markers in the mouse model, providing putative targets for early diagnosis of ETX exposure. A total of 52 unique proteins showing ETX-induced modulations were identified in plasma and urine samples. Fibrinogen, apolipoprotein, serum amyloid protein, plasminogen, serum albumin, glutathione peroxidase, transferrin, major urinary protein 2, haptoglobin, transthyretin, and vitamin D-binding protein were among the proteins observed in more than one dataset with altered abundance after the ETX-intoxication. The predicted localization, function, and interaction of the ETX-modulated proteins in the plasma and urine indicated involvement of multiple pathways; extracellular proteins, followed by macromolecular complexes associated with blood coagulation and plasminogen activating cascade, being the most prominent among others. The putative markers elucidated here warrants further validation and can be of immense value for the early diagnosis of ETX exposure.

Identification of Immune-Responsive Gene 1 (IRG1) as a Target of A20.

A20 is a negative regulator of NF-κB signaling; it controls inflammatory responses and ensures tissue homeostasis. A20 is thought to restrict NF-κB activation both by its ubiquitin-editing activity as well as by its nonenzymatic activities. Besides its role in NF-κB signaling, A20 also acts as a protective factor inhibiting apoptosis and necroptosis. Because of the ability of A20 to both ubiquitinate and deubiquitinate substrates, and its involvement in many cellular processes, we hypothesized that deletion of A20 might generally impact on protein levels, thereby disrupting cellular signaling. We performed a differential proteomics study on bone marrow-derived macrophages (BMDMs) from control and myeloid-specific A20 knockout mice, both in untreated conditions and after LPS or TNF treatment, and demonstrated A20-dependent changes in protein expression. Several inflammatory proteins were found up-regulated in the absence of A20, even without an inflammatory stimulus, but, depending on the treatment and the treatment time, more proteins were found regulated. Together these protein changes may affect normal signaling events, which may disturb tissue homeostasis and induce (autoimmune) inflammation, in agreement with A20s proposed identity as a susceptibility gene for inflammatory disease. We further verify that immune-responsive gene 1 (IRG1) is up-regulated in the absence of A20 and that its levels are transcriptionally regulated.

Differential Proteomic Analysis of Dimethylnitrosamine (DMN)-Induced Liver Fibrosis.

Liver fibrosis is a common pathological feature of many chronic liver diseases. To characterize the entire panorama of proteome changes in dimethylnitrosamine (DMN)-induced liver fibrosis, isobaric tags for relative and absolute quantitation (iTRAQ)-based differential proteomic analysis is performed with DMN-induced liver fibrosis rats. A total of 4155 confidently identified proteins are found, with 365 proteins showing significant changes (fold changes of >1.5 or < 0.67, p < 0.05). In metabolic activation, proteins assigned to drug metabolism enzymes (e.g., CYP2D1) change, suggesting that the liver protection mechanism is activated to relieve DMN toxicity. In addition, the altered proteins of immune response and oxidative stress may activate hepatic stellate cells. Glucose metabolism disorder in DMN model rats is demonstrated by a decrease in key enzymes (e.g., ACSL1) in fatty acid metabolism, a tricabolic acid cycle-related enzyme (SDH), glycogenolysis enzyme, and gluconeogenesis enzymes (PC, PCKGC) and by an increase in glycolysis enzymes (e.g., HXK1). Meanwhile, alterations in iron and calcium ion homeostasis proteins are observed. Our results also show that mitochondrial dysfunction may be involved in DMN hepatotoxicity. In conclusion, these altered liver proteins in the DMN model and control rats provide data for understanding the functional mechanism of liver fibrosis.

Classical Galactosemia: Insight into Molecular Pathomechanisms by Differential Membrane Proteomics of Fibroblasts under Galactose Stress.

Classical galactosemia, a hereditary metabolic disease caused by the deficiency of galactose-1-phosphate uridyltransferase (GALT; EC 2.7.712), results in an impaired galactose metabolism and serious long-term developmental affection of the CNS and ovaries, potentially related in part to endogenous galactose-induced protein dysglycosylation. In search for galactose-induced changes in membrane raft proteomes of GALT-deficient cells, we performed differential analyses of lipid rafts from patient-derived (Q) and sex- and age-matched control fibroblasts (H) in the presence or absence of the stressor. Label-based proteomics revealed of the total 454 (female) or 678 (male) proteins a proportion of ∼12% in at least one of four relevant ratios as fold-changed. GALT(-) cell-specific effects in the absence of stressor revealed cell-model-dependent affection of biological processes related to protein targeting to the plasma membrane (female) or to cellular migration (male). However, a series of common galactose-induced effects were observed, among them the strongly increased ER-stress marker GRP78 and calreticulin involved in N-glycoprotein quality control. The membrane-anchored N-glycoprotein receptor CD109 was concertedly decreased under galactose-stress together with cadherin-13, GLIPR1, glypican-1, and semaphorin-7A. A series of proteins showed opposite fold-changes in the two cell models, whereas others fluctuated in only one of the two models.

Probabilistic Generation of Mass Spectrometry Molecular Abundance Variance for Case and Control Replicates.

Shotgun differential mass spectrometry, the untargeted discovery of statistically significant differences between two or more samples, is a popular application with potential to advance biomarker detection, disease diagnostics, and other health objectives. Although many methods have been proposed, few have been quantitatively evaluated. The lack of ground truth data for shotgun difference detection limits quantitative evaluation and algorithmic advancement. While public mass-spectrometry data sets of single samples abound, data sets with more than one sample are rare, and data sets with the thousands of samples necessary to capture the complexity of real world populations are nonexistent due to technological and cost limitations. We present MSabundanceSIM, novel software for simulating any number of molecular samples based on one or a few real world data sets. The software uses a probabilistic model to generate case and control populations, with intuitive user parameters for tuning. We demonstrate variability by comparing to a real world data set over a range of abundances with differing biological and experimental variation coefficients. MSabundanceSIM is implemented in Ruby, is freely available, requires no external dependencies, and is suitable for a range of applications.

A Pipeline for Differential Proteomics in Unsequenced Species.

Shotgun proteomics experiments often take the form of a differential analysis, where two or more samples are compared against each other. The objective is to identify proteins that are either unique to a specific sample or a set of samples (qualitative differential proteomics), or that are significantly differentially expressed in one or more samples (quantitative differential proteomics). However, the success depends on the availability of a reliable protein sequence database for each sample. To perform such an analysis in the absence of a database, we here propose a novel, generic pipeline comprising an adapted spectral similarity score derived from database search algorithms that compares samples at the spectrum level to detect unique spectra. We applied our pipeline to compare two parasitic tapeworms: Taenia solium and Taenia hydatigena, of which only the former poses a threat to humans. Furthermore, because the genome of T. solium recently became available, we were able to prove the effectiveness and reliability of our pipeline a posteriori.

Differential Proteomics of Urinary Exovesicles from Classical Galactosemic Patients Reveals Subclinical Kidney Insufficiency.

Classical galactosemia is caused by a nearly complete deficiency of galactose-1-phosphate uridyltransferase (GALT; EC 2.7.712), resulting in a severely impaired galactose metabolism with galactose-1-phosphate and galactitol accumulation. Even on a galactose-restricted diet, patients develop serious long-term complications of the central nervous system and ovaries that may result from chronic cell-toxic effects exerted by endogenous galactose. To address the question of whether disease-associated cellular perturbations could affect the kidney function of the patients, we performed differential proteomics of detergent-resistant membranes from urinary exovesicles. Galactosemic samples (showing drastic shifts from high-mannose to complex-type N-glycosylation on exosomal N-glycoproteins) and healthy, sex-matched controls were analyzed in quadruplex iTRAQ experiments performed in biological and technical replicates. Particularly in the female patient group, the most striking finding was a drastic increase of abundant serum (glyco)proteins, like albumin, leucine-rich α-2-glycoprotein, fetuin, immunoglobulins, prostaglandin H2 d-isomerase, and α-1-microglobulin protein (AMBP), pointing to a subclinical failure of kidney filter function in galactosemic patients and resulting in a heavy overload of exosomal membranes with adsorbed serum (glyco)proteins. Several of these proteins are connected to TBMN and IgAN, proteinuria, and renal damage. The impairment of renal protein filtration was also indicated by increased protein contents derived from extracellular matrices and lysosomes.

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts.

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm ). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Comparative proteomic analysis reveals alterations in development and photosynthesis-related proteins in diploid and triploid rice.

BACKGROUND: Polyploidy has pivotal influences on rice (Oryza sativa L.) morphology and physiology, and is very important for understanding rice domestication and improving agricultural traits. Diploid (DP) and triploid (TP) rice shows differences in morphological parameters, such as plant height, leaf length, leaf width and the physiological index of chlorophyll content. However, the underlying mechanisms determining these morphological differences are remain to be defined. To better understand the proteomic changes between DP and TP, tandem mass tags (TMT) mass spectrometry (MS)/MS was used to detect the significant changes to protein expression between DP and TP. RESULTS: Results indicated that both photosynthesis and metabolic pathways were highly significantly associated with proteomic alteration between DP and TP based on biological process and pathway enrichment analysis, and 13 higher abundance chloroplast proteins involving in these two pathways were identified in TP. Quantitative real-time PCR analysis demonstrated that 5 of the 13 chloroplast proteins ATPF, PSAA, PSAB, PSBB and RBL in TP were higher abundance compared with those in DP. CONCLUSIONS: This study integrates morphology, physiology and proteomic profiling alteration of DP and TP to address their underlying different molecular mechanisms. Our finding revealed that ATPF, PSAA, PSAB, PSBB and RBL can induce considerable expression changes in TP and may affect the development and growth of rice through photosynthesis and metabolic pathways.

Summarization vs Peptide-Based Models in Label-Free Quantitative Proteomics: Performance, Pitfalls, and Data Analysis Guidelines.

Quantitative label-free mass spectrometry is increasingly used to analyze the proteomes of complex biological samples. However, the choice of appropriate data analysis methods remains a major challenge. We therefore provide a rigorous comparison between peptide-based models and peptide-summarization-based pipelines. We show that peptide-based models outperform summarization-based pipelines in terms of sensitivity, specificity, accuracy, and precision. We also demonstrate that the predefined FDR cutoffs for the detection of differentially regulated proteins can become problematic when differentially expressed (DE) proteins are highly abundant in one or more samples. Care should therefore be taken when data are interpreted from samples with spiked-in internal controls and from samples that contain a few very highly abundant proteins. We do, however, show that specific diagnostic plots can be used for assessing differentially expressed proteins and the overall quality of the obtained fold change estimates. Finally, our study also illustrates that imputation under the "missing by low abundance" assumption is beneficial for the detection of differential expression in proteins with low abundance, but it negatively affects moderately to highly abundant proteins. Hence, imputation strategies that are commonly implemented in standard proteomics software should be used with care.