In silico instrumental response correction improves precision of label-free proteomics and accuracy of proteomics-based predictive models

Electric Field-Modulated Electrospray Ionization Mass Spectrometry for Quantity Calibration and Mass Tracking

Analyses conducted by electrospray ionization (ESI) mass spectrometry (MS) typically entail performing a number of preparatory steps, which include quantity calibration and mass calibration. Quantity calibration can be affected by signal noise, while mass calibration can be affected by instrumental drift if analyses are performed over an extended period of time. Here, we present two methods for achieving these calibrations using modulation of electrospray plume by alternating electric fields and demodulating the resulting MS ion currents. For this purpose, we use an ESI source fitted with three ring electrodes between the electrospray emitter and the mass spectrometer's inlet. One of these electrodes is supplied with a sine electric signal. Optionally, a nanoESI emitter is also placed between the ring electrodes and the mass spectrometer's orifice to supply calibrant ions. The ion currents, recorded with this setup, present wave-like features. In the first variant, using a triple quadrupole mass analyzer, the ion currents are subjected to data treatment by fast Fourier transform (FFT), and the resulting FFT magnitudes are correlated with analyte concentrations to produce a calibration plot. In the second variant, using a quadrupole time-of-flight mass analyzer, the mass spectra recorded at the analyte ion current maxima are mass-checked using the m/z value of the internal standard (injected via nanoESI emitter), which appears predominantly in the time intervals corresponding to the analyte ion current minima. The setup has been characterized using simulation software and optimized. Overall, the method enables the preparation of quantity calibration plots and monitoring (minor) m/z drifts during prolonged analyses.

Comparing and integrating TMT-SPS-MS3 and label-free quantitative approaches for proteomics scrutiny in recalcitrant Mango (Mangifera indica L.) peel tissue during postharvest period

Despite substantial advances in the use of proteomic technologies, their widespread application in fruit tissues of non-model and recalcitrant species remains limited. This hampers the understanding of critical molecular events during the postharvest period of fleshy tropical fruits. Therefore, we evaluated label-free quantitation (LFQ) and TMT-SPS-MS3 (TMT) approaches to analyse changes in the protein profile of mango peels during postharvest period. We compared two extraction methods (phenol and chloroform/methanol) and two peptide fractionation schemes (SCX and HPRP). We accurately identified 3065 proteins, of which, 1492 were differentially accumulated over at 6 days after harvesting (DAH). Both LFQ and TMT approaches share 210 differential proteins including cell wall proteins associated with fruit softening, as well as aroma and flavour-related proteins, which were increased during postharvest period. The phenolic protein extraction and the high-pH reverse-phase peptide fractionation was the most effective pipeline for relative quantification. Nevertheless, the information provided by the other tested strategies was significantly complementary. Besides, LFQ spectra allowed us to track down intact N-glycopeptides corroborating N-glycosylations on the surface of a desiccation-related protein. This work represents the largest proteomic comparison of mango peels during postharvest period made so far, shedding light on the molecular foundation of edible fruit during ripening.

SpotLight proteomics identifies variable sequences of blood antibodies specific against deamidated human serum albumin

Spontaneous deamidation of asparaginyl residues in proteins, if not repaired or cleared, can set in motion a cascade that leads to deteriorated health. Previously, we have discovered that deamidated human serum albumin (HSA) is elevated in blood of patients with Alzheimer's disease and other neurodegenerative diseases, while the level of endogenous antibodies against deamidated HSA is significantly diminished, creating an imbalance between the risk factor and the defense against it. Endogenous antibodies against deamidated proteins are still unexplored. In the current study, we employed the SpotLight proteomics approach to identify novel amino acid sequences in antibodies specific to deamidated HSA. The results provide new insights into the clearance mechanism of deamidated proteins, a possible avenue for prevention of neurodegeneration.

Panomics reveals patient individuality as the major driver of colorectal cancer progression

BACKGROUND

Colorectal cancer (CRC) is one of the most prevalent cancers, with over one million new cases per year. Overall, prognosis of CRC largely depends on the disease stage and metastatic status. As precision oncology for patients with CRC continues to improve, this study aimed to integrate genomic, transcriptomic, and proteomic analyses to identify significant differences in expression during CRC progression using a unique set of paired patient samples while considering tumour heterogeneity.

METHODS

We analysed fresh-frozen tissue samples prepared under strict cryogenic conditions of matched healthy colon mucosa, colorectal carcinoma, and liver metastasis from the same patients. Somatic mutations of known cancer-related genes were analysed using Illumina's TruSeq Amplicon Cancer Panel; the transcriptome was assessed comprehensively using Clariom D microarrays. The global proteome was evaluated by liquid chromatography-coupled mass spectrometry (LC‒MS/MS) and validated by two-dimensional difference in-gel electrophoresis. Subsequent unsupervised principal component clustering, statistical comparisons, and gene set enrichment analyses were calculated based on differential expression results.

RESULTS

Although panomics revealed low RNA and protein expression of CA1, CLCA1, MATN2, AHCYL2, and FCGBP in malignant tissues compared to healthy colon mucosa, no differentially expressed RNA or protein targets were detected between tumour and metastatic tissues. Subsequent intra-patient comparisons revealed highly specific expression differences (e.g., SRSF3, OLFM4, and CEACAM5) associated with patient-specific transcriptomes and proteomes.

CONCLUSION

Our research results highlight the importance of inter- and intra-tumour heterogeneity as well as individual, patient-paired evaluations for clinical studies. In addition to changes among groups reflecting CRC progression, we identified significant expression differences between normal colon mucosa, primary tumour, and liver metastasis samples from individuals, which might accelerate implementation of precision oncology in the future.

DirectMS1Quant: Ultrafast Quantitative Proteomics with MS/MS-Free Mass Spectrometry

Recently, we presented the DirectMS1 method of ultrafast proteome-wide analysis based on minute-long LC gradients and MS1-only mass spectra acquisition. Currently, the method provides the depth of human cell proteome coverage of 2500 proteins at a 1% false discovery rate (FDR) when using 5 min LC gradients and 7.3 min runtime in total. While the standard MS/MS approaches provide 4000-5000 protein identifications within a couple of hours of instrumentation time, we advocate here that the higher number of identified proteins does not always translate into better quantitation quality of the proteome analysis. To further elaborate on this issue, we performed a one-on-one comparison of quantitation results obtained using DirectMS1 with three popular MS/MS-based quantitation methods: label-free (LFQ) and tandem mass tag quantitation (TMT), both based on data-dependent acquisition (DDA) and data-independent acquisition (DIA). For comparison, we performed a series of proteome-wide analyses of well-characterized (ground truth) and biologically relevant samples, including a mix of UPS1 proteins spiked at different concentrations into an Echerichia coli digest used as a background and a set of glioblastoma cell lines. MS1-only data was analyzed using a novel quantitation workflow called DirectMS1Quant developed in this work. The results obtained in this study demonstrated comparable quantitation efficiency of 5 min DirectMS1 with both TMT and DIA methods, yet the latter two utilized a 10-20-fold longer instrumentation time.

Equilibration for Electrospray Ionization Mass Spectrometry in Quantitative Analysis

Electrospray ionization mass spectrometry (ESI-MS) is widely used in drug development, therapeutic drug monitoring, and other fields. However, unstable mass spectral signals, especially during the initial stages of instrument operation, plague analysts. Generally, in quantitative experiments, the stability of response can be achieved by running the analytical system for some time. However, the equilibration time required for the responses of different compounds to stabilize has been elusive. To investigate the response stability of the ESI-MS system, 72 compounds with different physicochemical properties were employed on three systems, and flow injection analysis was performed in positive ion mode. With the use of 5.00% (response stable factor, RSF) as the stability limit, about 80% of the compounds were stable within 60 min. Under a 2.00% criterion, the stabilization time was significantly longer. The stabilization time varies with different instruments and physicochemical properties of the compounds. When positive ion detection is performed in an acidic mobile phase, the octanol-water partition coefficient (Log P), molecular weight, and molar volume can all affect the time required to stabilize the response. In general, it is necessary to balance the ESI-MS system for an appropriate time before sample detection, especially for the analysis of compounds with strong hydrophilicity, small molecular weight, or small molar volume under the conditions above.

Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications

INTRODUCTION

Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids.

AREAS COVERED

We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics.

EXPERT OPINION

While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.

First Immunoassay for Measuring Isoaspartate in Human Serum Albumin

Isoaspartate (isoAsp) is a damaging amino acid residue formed in proteins mostly as a result of spontaneous deamidation of asparaginyl residues. An association has been found between isoAsp in human serum albumin (HSA) and Alzheimer’s disease (AD). Here we report on a novel monoclonal antibody (mAb) 1A3 with excellent specificity to isoAsp in the functionally important domain of HSA. Based on 1A3 mAb, an indirect enzyme-linked immunosorbent assay (ELISA) was developed, and the isoAsp occupancy in 100 healthy plasma samples was quantified for the first time, providing the average value of (0.74 ± 0.13)%. These results suggest potential of isoAsp measurements for supplementary AD diagnostics as well as for assessing the freshness of stored donor blood and its suitability for transfusion.

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies

Label-free quantification (LFQ) with a specific and sequentially integrated workflow of acquisition technique, quantification tool and processing method has emerged as the popular technique employed in metaproteomic research to provide a comprehensive landscape of the adaptive response of microbes to external stimuli and their interactions with other organisms or host cells. The performance of a specific LFQ workflow is highly dependent on the studied data. Hence, it is essential to discover the most appropriate one for a specific data set. However, it is challenging to perform such discovery due to the large number of possible workflows and the multifaceted nature of the evaluation criteria. Herein, a web server ANPELA (https://idrblab.org/anpela/) was developed and validated as the first tool enabling performance assessment of whole LFQ workflow (collective assessment by five well-established criteria with distinct underlying theories), and it enabled the identification of the optimal LFQ workflow(s) by a comprehensive performance ranking. ANPELA not only automatically detects the diverse formats of data generated by all quantification tools but also provides the most complete set of processing methods among the available web servers and stand-alone tools. Systematic validation using metaproteomic benchmarks revealed ANPELA's capabilities in 1 discovering well-performing workflow(s), (2) enabling assessment from multiple perspectives and (3) validating LFQ accuracy using spiked proteins. ANPELA has a unique ability to evaluate the performance of whole LFQ workflow and enables the discovery of the optimal LFQs by the comprehensive performance ranking of all 560 workflows. Therefore, it has great potential for applications in metaproteomic and other studies requiring LFQ techniques, as many features are shared among proteomic studies.

Application of Mass Spectrometry-Based Proteomics to Barley Research

Barley (Hordeum vulgare) is the fourth most cultivated crop in the world in terms of production volume, and it is also the most important raw material of the malting and brewing industries. Barley belongs to the grass (Poaceae) family and plays an important role in food security and food safety for both humans and livestock. With the global population set to reach 9.7 billion by 2050, but with less available and/or suitable land for agriculture, the use of biotechnology tools in breeding programs are of considerable importance in the quest to meet the growing food gap. Proteomics as a member of the "omics" technologies has become popular for the investigation of proteins in cereal crops and particularly barley and its related products such as malt and beer. This technology has been applied to study how proteins in barley respond to adverse environmental conditions including abiotic and/or biotic stresses, how they are impacted during food processing including malting and brewing, and the presence of proteins implicated in celiac disease. Moreover, proteomics can be used in the future to inform breeding programs that aim to enhance the nutritional value and broaden the application of this crop in new food and beverage products. Mass spectrometry analysis is a valuable tool that, along with genomics and transcriptomics, can inform plant breeding strategies that aim to produce superior barley varieties. In this review, recent studies employing both qualitative and quantitative mass spectrometry approaches are explored with a focus on their application in cultivation, manufacturing, processing, quality, and the safety of barley and its related products.

Highly accurate and precise quantification strategy using stable isotope dimethyl labeling coupled with GeLC-MS/MS

Shotgun proteomics is a powerful method for comprehensively identifying and quantifying tryptic peptides, but it is difficult to analyze proteolytic events. One-dimensional gel and liquid chromatography-tandem mass spectrometry (GeLC-MS/MS) enables the separation of proteolytic fragments using SDS-PAGE followed by identification using LC-MS/MS. GeLC-MS/MS is thus an excellent method for identifying fragmentation. However, the lower reproducibility of gel extraction and nano flow LC-MS/MS can produce inaccurate results in comparative analyses of protein quantification among samples. In this study, a novel GeLC-MS/MS method coupled with stable isotope dimethyl labeling was developed. In the method, a mixture of light- and heavy-labeled samples is loaded onto an SDS-PAGE gel, and proteins with different isotopes in one extracted band are quantitatively analyzed by one-shot injection. This procedure enables accurate determination of the abundance ratio of peptides between two samples, even in cases of low peptide abundance, and it is not affected by the reproducibility of the gel extraction or LC-MS procedures. Therefore, our new GeLC-MS/MS method coupled with stable isotope dimethyl labeling provides high accuracy and comprehensive peptide comparisons, enabling the detection of proteolysis events caused by disease or physiological processes.

Advances in Current Diabetes Proteomics: From the Perspectives of Label- free Quantification and Biomarker Selection

BACKGROUND

Due to its prevalence and negative impacts on both the economy and society, the diabetes mellitus (DM) has emerged as a worldwide concern. In light of this, the label-free quantification (LFQ) proteomics and diabetic marker selection methods have been applied to elucidate the underlying mechanisms associated with insulin resistance, explore novel protein biomarkers, and discover innovative therapeutic protein targets.

OBJECTIVE

The purpose of this manuscript is to review and analyze the recent computational advances and development of label-free quantification and diabetic marker selection in diabetes proteomics.

METHODS

Web of Science database, PubMed database and Google Scholar were utilized for searching label-free quantification, computational advances, feature selection and diabetes proteomics.

RESULTS

In this study, we systematically review the computational advances of label-free quantification and diabetic marker selection methods which were applied to get the understanding of DM pathological mechanisms. Firstly, different popular quantification measurements and proteomic quantification software tools which have been applied to the diabetes studies are comprehensively discussed. Secondly, a number of popular manipulation methods including transformation, pretreatment (centering, scaling, and normalization), missing value imputation methods and a variety of popular feature selection techniques applied to diabetes proteomic data are overviewed with objective evaluation on their advantages and disadvantages. Finally, the guidelines for the efficient use of the computationbased LFQ technology and feature selection methods in diabetes proteomics are proposed.

CONCLUSION

In summary, this review provides guidelines for researchers who will engage in proteomics biomarker discovery and by properly applying these proteomic computational advances, more reliable therapeutic targets will be found in the field of diabetes mellitus.

Integrating multiple omics to identify common and specific molecular changes occurring in Arabidopsis under chronic nitrate and sulfate limitations

Plants have fundamental dependences on nitrogen and sulfur and frequently have to cope with chronic limitations when their supply is sub-optimal. This study aimed at characterizing the metabolomic, proteomic, and transcriptomic changes occurring in Arabidopsis leaves under chronic nitrate (Low-N) and chronic sulfate (Low-S) limitations in order to compare their effects, determine interconnections, and examine strategies of adaptation. Metabolite profiling globally revealed opposite effects of Low-S and Low-N on carbohydrate and amino acid accumulations, whilst proteomic data showed that both treatments resulted in increases in catabolic processes, stimulation of mitochondrial and cytosolic metabolism, and decreases in chloroplast metabolism. Lower abundances of ribosomal proteins and translation factors under Low-N and Low-S corresponded with growth limitation. At the transcript level, the major and specific effect of Low-N was the enhancement of expression of defence and immunity genes. The main effect of chronic Low-S was a decrease in transcripts of genes involved in cell division, DNA replication, and cytoskeleton, and an increase in the expression of autophagy genes. This was consistent with a role of target-of-rapamycin kinase in the control of plant metabolism and cell growth and division under chronic Low-S. In addition, Low-S decreased the expression of several NLP transcription factors, which are master actors in nitrate sensing. Finally, both the transcriptome and proteome data indicated that Low-S repressed glucosinolate synthesis, and that Low-N exacerbated glucosinolate degradation. This showed the importance of glucosinolate as buffering molecules for N and S management.

Deciphering the Infectious Process of Colletotrichum lupini in Lupin through Transcriptomic and Proteomic Analysis

The fungal phytopathogen Colletotrichum lupini is responsible for lupin anthracnose, resulting in significant yield losses worldwide. The molecular mechanisms underlying this infectious process are yet to be elucidated. This study proposes to evaluate C. lupini gene expression and protein synthesis during lupin infection, using, respectively, an RNAseq-based transcriptomic approach and a mass spectrometry-based proteomic approach. Patterns of differentially-expressed genes in planta were evaluated from 24 to 84 hours post-inoculation, and compared to in vitro cultures. A total of 897 differentially-expressed genes were identified from C. lupini during interaction with white lupin, of which 520 genes were predicted to have a putative function, including carbohydrate active enzyme, effector, protease or transporter-encoding genes, commonly described as pathogenicity factors for other Colletotrichum species during plant infection, and 377 hypothetical proteins. Simultaneously, a total of 304 proteins produced during the interaction were identified and quantified by mass spectrometry. Taken together, the results highlight that the dynamics of symptoms, gene expression and protein synthesis shared similarities to those of hemibiotrophic pathogens. In addition, a few genes with unknown or poorly-described functions were found to be specifically associated with the early or late stages of infection, suggesting that they may be of importance for pathogenicity. This study, conducted for the first time on a species belonging to the Colletotrichum acutatum species complex, presents an opportunity to deepen functional analyses of the genes involved in the pathogenicity of Colletotrichum spp. during the onset of plant infection.

FRET-Based Sorting of Live Cells Reveals Shifted Balance between PLK1 and CDK1 Activities During Checkpoint Recovery

Cells recovering from the G2/M DNA damage checkpoint rely more on Aurora A-PLK1 signaling than cells progressing through an unperturbed G2 phase, but the reason for this discrepancy is not known. Here, we devised a method based on a FRET reporter for PLK1 activity to sort cells in distinct populations within G2 phase. We employed mass spectroscopy to characterize changes in protein levels through an unperturbed G2 phase and validated that ATAD2 levels decrease in a proteasome-dependent manner. Comparing unperturbed cells with cells recovering from DNA damage, we note that at similar PLK1 activities, recovering cells contain higher levels of Cyclin B1 and increased phosphorylation of CDK1 targets. The increased Cyclin B1 levels are due to continuous Cyclin B1 production during a DNA damage response and are sustained until mitosis. Whereas partial inhibition of PLK1 suppresses mitotic entry more efficiently when cells recover from a checkpoint, partial inhibition of CDK1 suppresses mitotic entry more efficiently in unperturbed cells. Our findings provide a resource for proteome changes during G2 phase, show that the mitotic entry network is rewired during a DNA damage response, and suggest that the bottleneck for mitotic entry shifts from CDK1 to PLK1 after DNA damage.

IL-16 processing in sentinel node regulatory T cells is a factor in bladder cancer immunity

In the effort of developing new immunotherapies, the sentinel node (SN) has proven a promising source from which to harness an effective antitumour T cell response. However, tumour immune escape, a process in which regulatory T cells (Tregs) play a central role, remains a major limiting factor. Therefore, there is a clear need to increase the knowledge of Treg function and signalling in sentinel nodes. Here, we set out to explore whether the proteome in SN-resident T cells is altered by the tumour and to identify key proteins in SN T cell signalling, focusing on Tregs. Five patients with muscle-invasive urothelial bladder cancer were prospectively included. Mass spectrometry was performed on two patients, with validation and functional studies being performed on three additional patients and four healthy donors. At cystectomy, SN, non-SN lymph nodes and peripheral blood samples were collected from the patients and T cell subsets isolated through flow cytometry before downstream experiments. Proteomic analysis indicated that growth and immune signalling pathways are upregulated in SN-resident Tregs. Furthermore, centrality analysis identified the cytokine IL-16 to be central in the SN-Treg signalling network. We show that tumour-released factors, through activating caspase-3, increase Treg IL-16 processing into bioactive forms, reinforcing Treg suppressive capacity. In conclusion, we provide evidence that Tregs exposed to secreted factors from bladder tumours show increased immune and growth signalling and altered IL-16 processing which translates to enhanced Treg suppressive function, indicating altered IL-16 signalling as a novel tumour immune escape mechanism.

Changes in the plasma microvesicle proteome during the ovarian hyperstimulation phase of assisted reproductive technology

The incidence of pulmonary and venous thromboembolism is increased during the first trimester of pregnancies after assisted reproductive technology (ART) compared to spontaneous conception. We previously found that haemostatic plasma variables changed but within normal limits during controlled ovarian hyperstimulation (COH) concomitant with a major increase in plasma microvesicles (MVs) and markers indicating cell activation. We now explored the proteome of these MVs. Thirty-one women undergoing ART were blood sampled at down-regulation (DR) of oestrogen and at high level stimulation (HLS) with its 10–100-fold increased oestrogen level. Samples were analysed by liquid chromatography and tandem mass spectrometry to identify and quantify the proteome. We identified 306 proteins in the MVs and 72 had changed significantly at HLS compared to DR and more than 20% of them were associated with haemostasis. Thus, proteins related to both haemostasis and complement activation altered in plasma MVs in parallel with MV activation during COH. This needs to be further explored in the clinical context.

Expression of genes of the Pho regulon is altered in Streptomyces coelicolor

Most currently used antibiotics originate from Streptomycetes and phosphate limitation is an important trigger of their biosynthesis. Understanding the molecular processes underpinning such regulation is of crucial importance to exploit the great metabolic diversity of these bacteria and get a better understanding of the role of these molecules in the physiology of the producing bacteria. To contribute to this field, a comparative proteomic analysis of two closely related model strains, Streptomyces lividans and Streptomyces coelicolor was carried out. These strains possess identical biosynthetic pathways directing the synthesis of three well-characterized antibiotics (CDA, RED and ACT) but only S. coelicolor expresses them at a high level. Previous studies established that the antibiotic producer, S. coelicolor, is characterized by an oxidative metabolism and a reduced triacylglycerol content compared to the none producer, S. lividans, characterized by a glycolytic metabolism. Our proteomic data support these findings and reveal that these drastically different metabolic features could, at least in part, due to the weaker abundance of proteins of the two component system PhoR/PhoP in S. coelicolor compared to S. lividans. In condition of phosphate limitation, PhoR/PhoP is known to control positively and negatively, respectively, phosphate and nitrogen assimilation and our study revealed that it might also control the expression of some genes of central carbon metabolism. The tuning down of the regulatory role of PhoR/PhoP in S. coelicolor is thus expected to be correlated with low and high phosphate and nitrogen availability, respectively and with changes in central carbon metabolic features. These changes are likely to be responsible for the observed differences between S. coelicolor and S. lividans concerning energetic metabolism, triacylglycerol biosynthesis and antibiotic production. Furthermore, a novel view of the contribution of the bio-active molecules produced in this context, to the regulation of the energetic metabolism of the producing bacteria, is proposed and discussed.

Signal Drift in Liquid Chromatography Tandem Mass Spectrometry and Its Internal Standard Calibration Strategy for Quantitative Analysis

The present project studied the signal drift in liquid chromatography tandem mass spectrometry (LC-MS/MS) and proposed a strategy for compensating such drift. In the study, four 4-component groups were repeatedly run on different LC-MS/MS systems for over 12 h to investigate the dependence of signal drift on time and hardware systems. The 4-component groups each consisted of (1) an analyte, (2) a stable isotope labeled analyte, (3) a compound with similar structure to the analyte, and (4) a compound with dissimilar structure. All of the species showed significant signal drift, generally more than 25% over 12 h. The analyte and its stable isotope labeled analog always have the same drifting pattern including the trends and direction from one LC-MS/MS system to another. Signal drift was also found to be concentration dependent. Our experiments further proved that a conventional stable isotope labeled internal standard in LC-MS/MS quantification would not compensate the variations caused by concentration-dependent signal drift. An ideal internal standard for LC-MS/MS has both identical structure and similar concentration to the analyte. For that, we proposed a new internal standard strategy, pseudo internal standard (Pseudo IS), for LC-MS/MS quantification. Pseudo IS could effectively compensate signal drift in spite of its significant time, system, and concentration dependencies.

Proteomic and lipidomic analyses of the Arabidopsis atg5 autophagy mutant reveal major changes in endoplasmic reticulum and peroxisome metabolisms and in lipid composition

Autophagy is a universal mechanism in eukaryotic cells that facilitates the degradation of unwanted cell constituents and is essential for cell homeostasis and nutrient recycling. The salicylic acid-independent effects of autophagy defects on leaf metabolism were determined through large-scale proteomic and lipidomic analyses of atg5 and atg5/sid2 mutants under different nitrogen and sulfur growth conditions. Results revealed that irrespective of the growth conditions, plants carrying the atg5 mutation presented all the characteristics of endoplasmic reticulum (ER) stress. Increases in peroxisome and ER proteins involved in very long chain fatty acid synthesis and β-oxidation indicated strong modifications of lipid metabolism. Lipidomic analyses revealed changes in the concentrations of sphingolipids, phospholipids and galactolipids. Significant accumulations of phospholipids and ceramides and changes in GIPCs (glycosyl-inositol-phosphoryl-ceramides) in atg5 mutants indicated large modifications in endomembrane-lipid and especially plasma membrane-lipid composition. Decreases in chloroplast proteins and galactolipids in atg5 under low nutrient conditions, indicated that chloroplasts were used as lipid reservoirs for β-oxidation in atg5 mutants. In conclusion, this report demonstrates the strong impact of autophagy defect on ER stress and reveals the role of autophagy in the control of plant lipid metabolism and catabolism, influencing both lipid homeostasis and endomembrane composition.

Methodologies and Applications of Proteomics for Study of Yeast Strains: An Update

Yeasts are one of the mostly used microorganisms as models in several studies. A wide range of applications in different processes can be attributed to their intrinsic characteristics. They are eukaryotes and therefore valuable expression hosts that require elaborate post-translational modifications. Their arsenal of proteins has become a valuable biochemical tool for the catalysis of several reactions of great value to the food (beverages), pharmaceutical and energy industries. Currently, the main challenge in systemic yeast biology is the understanding of the expression, function and regulation of the protein pool encoded by such microorganisms. In this review, we will provide an overview of the proteomic methodologies used in the analysis of yeasts. This research focuses on the advantages and improvements in their most recent applications with an understanding of the functionality of the proteins of these microorganisms, as well as an update of the advances of methodologies employed in mass spectrometry.

Posttranslational Targeting of a Recombinant Protein Promotes Its Efficient Secretion into the Escherichia coli Periplasm

Many recombinant proteins that are produced in Escherichia coli have to be targeted to the periplasm to be functional. N-terminal signal peptides can be used to direct recombinant proteins to the membrane-embedded Sec translocon, a multiprotein complex that translocates proteins across the membrane into the periplasm. We have recently shown that the cotranslational targeting of the single-chain variable antibody fragment BL1 saturates the capacity of the Sec translocon leading to impaired translocation of secretory proteins and protein misfolding/aggregation in the cytoplasm. In turn, protein production yields and biomass formation were low. Here, we study the consequences of targeting BL1 posttranslationally to the Sec translocon. Notably, the posttranslational targeting of BL1 does not saturate the Sec translocon capacity, and both biomass formation and protein production yields are increased. Analyzing the proteome of cells producing the posttranslationally targeted BL1 indicates that the decreased synthesis of endogenous secretory and membrane proteins prevents a saturation of the Sec translocon capacity. Furthermore, in these cells, highly abundant chaperones and proteases can clear misfolded/aggregated proteins from the cytoplasm, thereby improving the fitness of these cells. Thus, the posttranslational targeting of BL1 enables its efficient production in the periplasm due to a favorable adaptation of the E. coli proteome. We envisage that our observations can be used to engineer E. coli for the improved production of recombinant secretory proteins.IMPORTANCE The bacterium Escherichia coli is widely used to produce recombinant proteins. To fold properly, many recombinant proteins have to be targeted to the E. coli periplasm, but so far the impact of the targeting pathway of a recombinant protein to the periplasm has not been extensively investigated. Here, we show that the targeting pathway of a recombinant antibody fragment has a tremendous impact on cell physiology, ultimately affecting protein production yields in the periplasm and biomass formation. This indicates that studying the targeting and secretion of proteins into the periplasm could be used to design strategies to improve recombinant protein production yields.

Multi-omics Analysis Reveals Sequential Roles for ABA during Seed Maturation

Abscisic acid (ABA) is an important hormone for seed development and germination whose physiological action is modulated by its endogenous levels. Cleavage of carotenoid precursors by 9-cis epoxycarotenoid dioxygenase (NCED) and inactivation of ABA by ABA 8'-hydroxylase (CYP707A) are key regulatory metabolic steps. In Arabidopsis (Arabidopsis thaliana), both enzymes are encoded by multigene families, having distinctive expression patterns. To evaluate the genome-wide impact of ABA deficiency in developing seeds at the maturation stage when dormancy is induced, we used a nced2569 quadruple mutant in which ABA deficiency is mostly restricted to seeds, thus limiting the impact of maternal defects on seed physiology. ABA content was very low in nced2569 seeds, similar to the severe mutant aba2; unexpectedly, ABA Glc ester was detected in aba2 seeds, suggesting the existence of an alternative metabolic route. Hormone content in nced2569 seeds compared with nced259 and wild type strongly suggested that specific expression of NCED6 in the endosperm is mainly responsible for ABA production. In accordance, transcriptome analyses revealed broad similarities in gene expression between nced2569 and either wild-type or nced259 developing seeds. Gene ontology enrichments revealed a large spectrum of ABA activation targets involved in reserve storage and desiccation tolerance, and repression of photosynthesis and cell cycle. Proteome and metabolome profiles in dry nced2569 seeds, compared with wild-type and cyp707a1a2 seeds, also highlighted an inhibitory role of ABA on remobilization of reserves, reactive oxygen species production, and protein oxidation. Down-regulation of these oxidative processes by ABA may have an essential role in dormancy control.

Citrullination Controls Dendritic Cell Transdifferentiation into Osteoclasts

An increased repertoire of potential osteoclast (OC) precursors could accelerate the development of bone-erosive OCs and the consequent bone damage in rheumatoid arthritis (RA). Immature dendritic cells (DCs) can develop into OCs, however, the mechanisms underlying this differentiation switch are poorly understood. We investigated whether protein citrullination and RA-specific anti-citrullinated protein Abs (ACPAs) could regulate human blood-derived DC-OC transdifferentiation. We show that plasticity toward the OC lineage correlated with peptidyl arginine deiminase (PAD) activity and protein citrullination in DCs. Citrullinated actin and vimentin were present in DCs and DC-derived OCs, and both proteins were deposited on the cell surface, colocalizing with ACPAs binding to the cells. ACPAs enhanced OC differentiation from monocyte-derived or circulating CD1c⁺ DCs by increasing the release of IL-8. Blocking IL-8 binding or the PAD enzymes completely abolished the stimulatory effect of ACPAs, whereas PAD inhibition reduced steady-state OC development, as well, suggesting an essential role for protein citrullination in DC-OC transdifferentiation. Protein citrullination and ACPA binding to immature DCs might thus promote differentiation plasticity toward the OC lineage, which can facilitate bone erosion in ACPA-positive RA.

Cationic gold nanoparticles elicit mitochondrial dysfunction: a multi-omics study

Systems biology is increasingly being applied in nanosafety research for observing and predicting the biological perturbations inflicted by exposure to nanoparticles (NPs). In the present study, we used a combined transcriptomics and proteomics approach to assess the responses of human monocytic cells to Au-NPs of two different sizes with three different surface functional groups, i.e., alkyl ammonium bromide, alkyl sodium carboxylate, or poly(ethylene glycol) (PEG)-terminated Au-NPs. Cytotoxicity screening using THP-1 cells revealed a pronounced cytotoxicity for the ammonium-terminated Au-NPs, while no cell death was seen after exposure to the carboxylated or PEG-modified Au-NPs. Moreover, Au-NR3+ NPs, but not the Au-COOH NPs, were found to trigger dose-dependent lethality in vivo in the model organism, Caenorhabditis elegans. RNA sequencing combined with mass spectrometry-based proteomics predicted that the ammonium-modified Au-NPs elicited mitochondrial dysfunction. The latter results were validated by using an array of assays to monitor mitochondrial function. Au-NR3+ NPs were localized in mitochondria of THP-1 cells. Moreover, the cationic Au-NPs triggered autophagy in macrophage-like RFP-GFP-LC3 reporter cells, and cell death was aggravated upon inhibition of autophagy. Taken together, these studies have disclosed mitochondria-dependent effects of cationic Au-NPs resulting in the rapid demise of the cells.

CDK and MAPK Synergistically Regulate Signaling Dynamics via a Shared Multi-site Phosphorylation Region on the Scaffold Protein Ste5

We report an unanticipated system of joint regulation by cyclin-dependent kinase (CDK) and mitogen-activated protein kinase (MAPK), involving collaborative multi-site phosphorylation of a single substrate. In budding yeast, the protein Ste5 controls signaling through a G1 arrest pathway. Upon cell-cycle entry, CDK inhibits Ste5 via multiple phosphorylation sites, disrupting its membrane association. Using quantitative time-lapse microscopy, we examined Ste5 membrane recruitment dynamics at different cell-cycle stages. Surprisingly, in S phase, where Ste5 recruitment should be blocked, we observed an initial recruitment followed by a steep drop-off. This delayed inhibition revealed a requirement for both CDK activity and negative feedback from the pathway MAPK Fus3. Mutagenesis, mass spectrometry, and electrophoretic analyses suggest that the CDK and MAPK modify shared sites, which are most extensively phosphorylated when both kinases are active and able to bind their docking sites on Ste5. Such collaborative phosphorylation can broaden regulatory inputs and diversify output dynamics of signaling pathways.

Patients with anti-Jo1 antibodies display a characteristic IgG Fc-glycan profile which is further enhanced in anti-Jo1 autoantibodies

IgG Fc-glycans affect IgG function and are altered in autoimmune diseases and autoantibodies. Anti-histidyl tRNA synthetase autoantibodies (anti-Jo1) are frequent in patients with idiopathic inflammatory myopathies (IIM) and anti-synthetase syndrome (ASS) with associated interstitial lung disease (ILD). Thus, we hypothesized that the total-IgG Fc-glycans from Jo1⁺ versus Jo1⁻ patients and anti-Jo1-IgG would show characteristic differences, and that particular Fc-glycan features would be associated with specific clinical manifestations. By proteomics based mass spectrometry we observed a high abundance of agalactosylated IgG₁ Fc-glycans in ASS/IIM patients (n = 44) compared to healthy age matched controls (n = 24). Using intra-individual normalization of the main agalactosylated glycan (FA2) of IgG₁ vs FA2-IgG₂, ASS/IIM and controls were distinguished with an area under the curve (AUC) of 79 ± 6%. For Jo1⁺ patients (n = 19) the AUCs went up to 88 ± 6%. Bisected and afucosylated Fc-glycans were significantly lower in Jo1⁺ compared to Jo1⁻ patients. Anti-Jo1-IgG enriched from eleven patients contained even significantly lower abundances of bisected, afucosylated and galactosylated forms compared to matched total-IgG. ASS and ILD diagnosis, as well as lysozyme and thrombospondin correlated with Jo1⁺ characteristic Fc-glycan features. These results suggest that the anti-Jo1⁺ patient Fc-glycan profile contains phenotype specific features which may underlie the pathogenic role of Jo1 autoantibodies.

Dynamic Proteomics Reveals High Plasticity of Cellular Proteome: Growth-Related and Drug-Induced Changes in Cancer Cells are Comparable

In chemical proteomics, the changes occurring in cellular proteomes upon drug treatment are used to identify the drug targets and the mechanism of action. However, proteomes of cultured cells undergo also natural alteration associated with changes in the media, attaining a degree of confluence as well as due to cell division and cell metabolism. These changes are implicitly assumed to be smaller in magnitude than the drug-induced changes that ultimately lead to cell demise. In this study, it is shown that growth-related proteome changes in the untreated control group are comparable in magnitude to drug-induced changes over the course of 48 h treatment. In two well-characterized cancer cell lines, growth-related effects assessed with deep proteomics analysis (10 481 proteins quantified with at least two peptides) show common trends, the steady downregulation of cell division processes, and the upregulation of metabolism-related pathways. The magnitude of these variations, which are present even before reaching 100% confluence reveals unexpectedly high plasticity of the cellular proteome. This finding reinforces the need, generally accepted in theory but not always followed in practice, to use a time-matched control when measuring drug-induced proteome changes.

Peptide filtering differently affects the performances of XIC-based quantification methods

In bottom-up proteomics, data are acquired on peptides resulting from proteolysis. In XIC-based quantification, the quality of the estimation of protein abundance depends on how peptide data are filtered and on which quantification method is used to express peptide intensity as protein abundance. So far, these two questions have been addressed independently. Here, we studied to what extent the relative performances of the quantification methods depend on the filters applied to peptide intensity data. To this end, we performed a spike-in experiment using Universal Protein Standard to evaluate the performances of five quantification methods in five datasets obtained after application of four peptide filters. Estimated protein abundances were not equally affected by filters depending on the computation mode and the type of data for quantification. Furthermore, we found that filters could have contrasting effects depending on the quantification objective. Intensity modeling proved to be the most robust method, providing the best results in the absence of any filter. However, the different quantification methods can achieve similar performances when appropriate peptide filters are used. Altogether, our findings provide insights into how best to handle intensity data according to the quantification objective and the experimental design. SIGNIFICANCE: We believe that our results are of major importance because they address, as far as we know for the first time, the crossed-effects of peptide intensity data filtering and XIC-based quantification methods on protein quantification. While previous papers have dealt with peptide filtering independently of the quantification method, here we combined four peptide filters (based on peptide sharing between proteins, retention time variability, peptides occurrence and peptide intensity profiles) with five XIC-based quantification methods representing different modes of calculating protein abundances from peptide intensities. For these different combinations, we analyzed the quality of protein quantification in terms of precision, accuracy and linearity of response to increasing protein concentration using a spike-in experiment. We showed that not only filters effect on the estimation of protein abundances depend on the quantification methods but also that quantification methods can reach similar performances when appropriate peptide filters are used. Also, depending on the quantification objective, i.e. absolute or relative, filters can have contrasting effects and we demonstrated that protein quantification by the peptide intensity modeling was the most robust method.

Optimizing Recombinant Protein Production in the Escherichia coli Periplasm Alleviates Stress

In Escherichia coli, many recombinant proteins are produced in the periplasm. To direct these proteins to this compartment, they are equipped with an N-terminal signal sequence so that they can traverse the cytoplasmic membrane via the protein-conducting Sec translocon. Recently, using the single-chain variable antibody fragment BL1, we have shown that harmonizing the target gene expression intensity with the Sec translocon capacity can be used to improve the production yields of a recombinant protein in the periplasm. Here, we have studied the consequences of improving the production of BL1 in the periplasm by using a proteomics approach. When the target gene expression intensity is not harmonized with the Sec translocon capacity, the impaired translocation of secretory proteins, protein misfolding/aggregation in the cytoplasm, and an inefficient energy metabolism result in poor growth and low protein production yields. The harmonization of the target gene expression intensity with the Sec translocon capacity results in normal growth, enhanced protein production yields, and, surprisingly, a composition of the proteome that is-besides the produced target-the same as that of cells with an empty expression vector. Thus, the single-chain variable antibody fragment BL1 can be efficiently produced in the periplasm without causing any notable detrimental effects to the production host. Finally, we show that under the optimized conditions, a small fraction of the target protein is released into the extracellular milieu via outer membrane vesicles. We envisage that our observations can be used to design strategies to further improve the production of secretory recombinant proteins in E. coliIMPORTANCE The bacterium Escherichia coli is widely used to produce recombinant proteins. Usually, trial-and-error-based screening approaches are used to identify conditions that lead to high recombinant protein production yields. Here, for the production of an antibody fragment in the periplasm of E. coli, we show that an optimization of its production is accompanied by the alleviation of stress. This indicates that the monitoring of stress responses could be used to facilitate enhanced recombinant protein production yields.

Evaluation of Optimized Tube-Gel Methods of Sample Preparation for Large-Scale Plant Proteomics

The so-called tube-gel method is a sample preparation protocol allowing for management of SDS for protein solubilization through in-gel protein trapping. Because of its simplicity, we assumed that once miniaturized, this method could become a standard for large scale experiments. We evaluated the performances of two variants of the miniaturized version of the tube-gel method based on different solubilization buffers (Tris-SDS or urea-SDS). To this end, we compared them to two other digestion methods: (i) liquid digestion after protein solubilization in the absence of SDS (liquid method) and (ii) filter-aided sample preparation (FASP). As large-scale experiments may require long term gel storage, we also examined to which extent gel aging affected the results of the proteomics analysis. We showed that both tube-gel and FASP methods extracted membrane proteins better than the liquid method, while the latter allowed the identification and quantification of a greater number of proteins. All methods were equivalent regarding quantitative stability. However, important differences were observed regarding post-translational modifications. In particular, methionine oxidation was higher with the tube-gel method than with the other methods. Based on these results, and considering time, simplicity, and cost aspects, we conclude that the miniaturized tube-gel method is suitable for sample preparation in the context of large-scale experiments.

Gender proteomics I. Which proteins in non-sexual organs

Differences related to gender have long been neglected but recent investigations show that they are widespread and may be recognized with all types of omics approaches, both in tissues and in biological fluids. Our review compiles evidence collected with proteomics techniques in our species, mainly focusing on baseline parameters in non-sexual organs in healthy men and women. Data from human specimens had to be replaced with information from other mammals every time invasive procedures of sample procurement were involved.

SIGNIFICANCE

As our knowledge, and the methods to build it, get refined, gender differences need to receive more and more attention, as they influence the outcome of all aspects in lifestyle, including diet, exercise and environmental factors. In turn this background modulates a differential susceptibility to some disease, or a different pathogenetic mechanism, depending on gender, and a different response to pharmacological therapy. Preparing this review we meant to raise awareness about the gender issue. We anticipate that more and more often, in the future, separate evaluations will be carried out on male and female subjects as an alternative - and an upgrade - to the current approach of reference and test groups being 'matched for age and sex'.

IgG Fc galactosylation predicts response to methotrexate in early rheumatoid arthritis

BACKGROUND

Methotrexate (MTX) is the standard first-line therapy in rheumatoid arthritis (RA) with variable clinical efficacy that is difficult to predict. The glycosylation status of immunoglobulin G (IgG) is altered in RA and influenced by MTX treatment. We aimed to further investigate if IgG glycosylation in untreated early RA can predict therapeutic response to MTX.

METHODS

We used a shotgun proteomic approach to screen for the Fc glycopeptides in the serum of 12 control subjects and 59 untreated patients with early RA prior to and following MTX initiation. MTX treatment response was defined according to the European League Against Rheumatism at a median of 14 weeks (range 13-15) after treatment initiation. Seropositive patients were defined as those testing positive for anticitrullinated protein antibodies and/or rheumatoid factor at baseline (n = 44). Data analysis was performed using uni- and multivariate statistics.

RESULTS

We could confirm a low abundance of galactosylated glycans in untreated patients with early RA compared with control subjects that was partially restored by MTX treatment. This was more evident among future nonresponders than among responders to MTX treatment. Results were further validated and confirmed by multivariate statistical analysis of the baseline Fc glycan, proteomic, and clinical data. We found that the ratio between the main agalactosylated (FA2) and main mono- and di-galactosylated Fc glycans (FA2G1 and FA2G2) of IgG1 ranked as the most prominent factor distinguishing responders from nonresponders. A low baseline ratio of FA2/[FA2G1 + FA2G2]-IgG1 was associated with nonresponse (OR 5.3 [1.6-17.0]) and was able to discriminate future nonresponders from responders to MTX therapy with a sensitivity of 70% (95% CI 46-88%) and a specificity of 69% (95% CI 52-83%). For seropositive patients (n = 44), this trend was improved with a sensitivity of 73% (95% CI 45-92%) for nonresponse and a specificity of 79% (95% CI 60-92%).

CONCLUSIONS

We show that the FA2/[FA2G1 + FA2G2] of IgG1 is a biomarker candidate that is significantly associated with nonresponding patients and has potential value for prediction of MTX clinical response.

Expression proteomics study to determine metallodrug targets and optimal drug combinations

The emerging technique termed functional identification of target by expression proteomics (FITExP) has been shown to identify the key protein targets of anti-cancer drugs. Here, we use this approach to elucidate the proteins involved in the mechanism of action of two ruthenium(II)-based anti-cancer compounds, RAPTA-T and RAPTA-EA in breast cancer cells, revealing significant differences in the proteins upregulated. RAPTA-T causes upregulation of multiple proteins suggesting a broad mechanism of action involving suppression of both metastasis and tumorigenicity. RAPTA-EA bearing a GST inhibiting ethacrynic acid moiety, causes upregulation of mainly oxidative stress related proteins. The approach used in this work could be applied to the prediction of effective drug combinations to test in cancer chemotherapy clinical trials.

Self-assembly of Deinococcus radiodurans supports nanocell scenario of life origin

In many origin-of-life scenarios, first a kit of elements and simple compounds emerges, then a primitive membrane and then a nanocell with a minimal genome is self-assembled, which then proceeds to multiply by copying itself while mutating. Testing this scenario, we selected Deinococcus Radiodurans known for its exceptional self-repair properties as a model system, separated its bacterial lysis into DNA, RNA and protein fractions, while lipids were used for liposome formation. The fractions were sealed in glass tubes individually and in combinations and stored for three weeks. Upon seeding on Petri dishes, the fractions containing liposomes together with nucleic acid and/or proteins gave in total 19 colonies of Deinococcus radiodurans (confirmed by proteomics), while liposome-free fractions as well as liposome-only fractions gave no colonies. The self-assembly of viable cells from essentially dead mixtures validates the lyposome-based origin-of-life scenario.

Comparative evaluation of label-free quantification methods for shotgun proteomics

RATIONALE

Label-free quantification (LFQ) is a popular strategy for shotgun proteomics. A variety of LFQ algorithms have been developed recently. However, a comprehensive comparison of the most commonly used LFQ methods is still rare, in part due to a lack of clear metrics for their evaluation and an annotated and quantitatively well-characterized data set.

METHODS

Five LFQ methods were compared: spectral counting based algorithms SI_N , emPAI, and NSAF, and approaches relying on the extracted ion chromatogram (XIC) intensities, MaxLFQ and Quanti. We used three criteria for performance evaluation: coefficient of variation (CV) of protein abundances between replicates; analysis of variance (ANOVA); and the root-mean-square error of logarithmized calculated concentration ratios, referred to as standard quantification error (SQE). Comparison was performed using a quantitatively annotated publicly available data set.

RESULTS

The best results in terms of inter-replicate reproducibility were observed for MaxLFQ and NSAF, although they exhibited larger standard quantification errors. Using NSAF, all quantitatively annotated proteins were correctly identified in the Bonferronni-corrected results of the ANOVA test. SI_N was found to be the most accurate in terms of SQE. Finally, the current implementations of XIC-based LFQ methods did not outperform the methods based on spectral counting for the data set used in this study.

CONCLUSIONS

Surprisingly, the performances of XIC-based approaches measured using three independent metrics were found to be comparable with more straightforward and simple MS/MS-based spectral counting approaches. The study revealed no clear leader among the latter. Copyright © 2017 John Wiley & Sons, Ltd.

Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences

Most implementations of mass spectrometry-based proteomics involve enzymatic digestion of proteins, expanding the analysis to multiple proteolytic peptides for each protein. Currently, there is no consensus of how to summarize peptides' abundances to protein concentrations, and such efforts are complicated by the fact that error control normally is applied to the identification process, and do not directly control errors linking peptide abundance measures to protein concentration. Peptides resulting from suboptimal digestion or being partially modified are not representative of the protein concentration. Without a mechanism to remove such unrepresentative peptides, their abundance adversely impacts the estimation of their protein's concentration. Here, we present a relative quantification approach, Diffacto, that applies factor analysis to extract the covariation of peptides' abundances. The method enables a weighted geometrical average summarization and automatic elimination of incoherent peptides. We demonstrate, based on a set of controlled label-free experiments using standard mixtures of proteins, that the covariation structure extracted by the factor analysis accurately reflects protein concentrations. In the 1% peptide-spectrum match-level FDR data set, as many as 11% of the peptides have abundance differences incoherent with the other peptides attributed to the same protein. If not controlled, such contradicting peptide abundance have a severe impact on protein quantifications. When adding the quantities of each protein's three most abundant peptides, we note as many as 14% of the proteins being estimated as having a negative correlation with their actual concentration differences between samples. Diffacto reduced the amount of such obviously incorrectly quantified proteins to 1.6%. Furthermore, by analyzing clinical data sets from two breast cancer studies, our method revealed the persistent proteomic signatures linked to three subtypes of breast cancer. We conclude that Diffacto can facilitate the interpretation and enhance the utility of most types of proteomics data.

Cytotoxic and Proinflammatory Effects of Metal-Based Nanoparticles on THP-1 Monocytes Characterized by Combined Proteomics Approaches

Thorough characterization of toxic effects of nanoparticles (NP) is desirable due to the increasing risk of potential environmental contamination by NP. In the current study, we combined three recently developed proteomics approaches to assess the effects of Au, CuO, and CdTe NP on the innate immune system. The human monocyte cell line THP-1 was employed as a model. The anticancer drugs camptothecin and doxorubicin were used as positive controls for cell death, and lipopolysaccharide was chosen as a positive control for proinflammatory activation. Despite equivalent overall toxicity effect (50 ± 10% dead cells), the three NP induced distinctly different proteomics signatures, with the strongest effect being induced by CdTe NP, followed by CuO and gold NP. The CdTe toxicity mechanism involves down-regulation of topoisomerases. The effect of CuO NP is most reminiscent of oxidative stress and involves up-regulation of proteins involved in heat response. The gold NP induced up-regulation of the inflammatory mediator, NF-κB, and its inhibitor TIPE2 was identified as a direct target of gold NP. Furthermore, gold NP triggered activation of NF-κB as evidenced by phosphorylation of the p65 subunit. Overall, the combined proteomics approach described here can be used to characterize the effects of NP on immune cells.

Functional and Structural Characterization of a Novel HLA-DRB1*04:01-Restricted α-Enolase T Cell Epitope in Rheumatoid Arthritis

Antibodies to citrullinated proteins, common in rheumatoid arthritis (RA) patients, are strongly associated to a specific set of HLA-DR alleles including HLA-DRB1*04:01, *04:04, and *01:01. Here, we first demonstrate that autoantibody levels toward the dominant citrullinated B cell epitope from α-enolase are significantly elevated in HLA-DRB1*04:01-positive RA patients. Furthermore, we identified α-enolase-derived T cell epitopes and demonstrated that native and citrullinated versions of several peptides bind with different affinities to HLA-DRB1*04:01, *04:04, and *01:01. The citrulline residues in the eight identified peptides are distributed throughout the entire length of the presented epitopes and more specifically, localized at peptide positions p-2, p2, p4, p6, p7, p10, and p11. Importantly, in contrast to its native version peptide 26 (TSKGLFRAAVPSGAS), the HLA-DRB1*04:01-restricted citrullinated peptide Cit26 (TSKGLFCitAAVPSGAS) elicited significant functional T cell responses in primary cells from RA patients. Comparative analysis of the crystal structures of HLA-DRB1*04:01 in complex with peptide 26 or Cit26 demonstrated that the posttranslational modification did not alter the conformation of the peptide. And since citrullination is the only structural difference between the two complexes, this indicates that the neo-antigen Cit26 is recognized by T cells with high specificity to the citrulline residue.

Isolation and characterization of autoantibodies against human cystatin C

Hereditary cystatin C amyloid angiopathy (HCCAA) is a severe neurodegenerative disorder related to the point mutation in cystatin C gene resulting in human cystatin C (hCC) L68Q variant. One of the potential immunotherapeutic approaches to HCCAA treatment is based on naturally occurring antibodies against cystatin C. A recent growing interest in autoantibodies, especially in the context of neurodegenerative diseases, emerges from their potential use as valuable diagnostic markers and for controlling protein aggregation. In this work, we present characteristics of natural anti-hCC antibodies isolated from the IgG fraction of human serum by affinity chromatography. The electrophoresis (1-D and 2-D) results demonstrated that the isolated NAbs are a polyclonal mixture, but their electrophoretic properties did not allow to classify the new autoantibodies to any particular type of IgG. The Fc-glycan status of the studied autoantibodies was assessed using mass spectrometry analysis. For the isolated NAbs, the epitopic fragments in hCC sequence were identified by MS-assisted proteolytic excision of the immune complex and compared with the ones predicted theoretically. The knowledge of hCC fragments binding to NAbs and other ligands may contribute to the search for new diagnostic methods for amyloidosis of different types and the search for their treatment.

How well can morphology assess cell death modality? A proteomics study

While the focus of attempts to classify cell death programs has finally shifted in 2010s from microscopy-based morphological characteristics to biochemical assays, more recent discoveries have put the underlying assumptions of many such assays under severe stress, mostly because of the limited specificity of the assays. On the other hand, proteomics can quantitatively measure the abundances of thousands of proteins in a single experiment. Thus proteomics could develop a modern alternative to both semiquantitative morphology assessment as well as single-molecule biochemical assays. Here we tested this hypothesis by analyzing the proteomes of cells dying after been treated with various chemical agents. The most striking finding is that, for a multivariate model based on the proteome changes in three cells lines, the regulation patterns of the 200–500 most abundant proteins typically attributed to household type more accurately reflect that of the proteins directly interacting with the drug than any other protein subset grouped by common function or biological process, including cell death. This is in broad agreement with the 'rigid cell death mechanics' model where drug action mechanism and morphological changes caused by it are bijectively linked. This finding, if confirmed, will open way for a broad use of proteomics in death modality assessment.

Phosphorylation of Leukotriene C4 Synthase at Serine 36 Impairs Catalytic Activity

Leukotriene C4 synthase (LTC4S) catalyzes the formation of the proinflammatory lipid mediator leukotriene C4 (LTC4). LTC4 is the parent molecule of the cysteinyl leukotrienes, which are recognized for their pathogenic role in asthma and allergic diseases. Cellular LTC4S activity is suppressed by PKC-mediated phosphorylation, and recently a downstream p70S6k was shown to play an important role in this process. Here, we identified Ser(36) as the major p70S6k phosphorylation site, along with a low frequency site at Thr(40), using an in vitro phosphorylation assay combined with mass spectrometry. The functional consequences of p70S6k phosphorylation were tested with the phosphomimetic mutant S36E, which displayed only about 20% (20 μmol/min/mg) of the activity of WT enzyme (95 μmol/min/mg), whereas the enzyme activity of T40E was not significantly affected. The enzyme activity of S36E increased linearly with increasing LTA4 concentrations during the steady-state kinetics analysis, indicating poor lipid substrate binding. The Ser(36) is located in a loop region close to the entrance of the proposed substrate binding pocket. Comparative molecular dynamics indicated that Ser(36) upon phosphorylation will pull the first luminal loop of LTC4S toward the neighboring subunit of the functional homotrimer, thereby forming hydrogen bonds with Arg(104) in the adjacent subunit. Because Arg(104) is a key catalytic residue responsible for stabilization of the glutathione thiolate anion, this phosphorylation-induced interaction leads to a reduction of the catalytic activity. In addition, the positional shift of the loop and its interaction with the neighboring subunit affect active site access. Thus, our mutational and kinetic data, together with molecular simulations, suggest that phosphorylation of Ser(36) inhibits the catalytic function of LTC4S by interference with the catalytic machinery.

Molecular profiling of prostate cancer derived exosomes may reveal a predictive signature for response to docetaxel

Docetaxel is a cornerstone treatment for metastatic, castration resistant prostate cancer (CRPC) which remains a leading cause of cancer-related deaths, worldwide. The clinical usage of docetaxel has resulted in modest gains in survival, primarily due to the development of resistance. There are currently no clinical biomarkers available that predict whether a CRPC patient will respond or acquire resistance to this therapy. Comparative proteomics analysis of exosomes secreted from DU145 prostate cancer cells that are sensitive (DU145 Tax-Sen) or have acquired resistance (DU145 Tax-Res) to docetaxel, demonstrated significant differences in the amount of exosomes secreted and in their molecular composition. A panel of proteins was identified by proteomics to be differentially enriched in DU145 Tax-Res compared to DU145 Tax-Sen exosomes and was validated by western blotting. Importantly, we identified MDR-1, MDR-3, Endophilin-A2 and PABP4 that were enriched only in DU145 Tax-Res exosomes. We validated the presence of these proteins in the serum of a small cohort of patients. DU145 cells that have uptaken DU145 Tax-Res exosomes show properties of increased matrix degradation. In summary, exosomes derived from DU145 Tax-Res cells may be a valuable source of biomarkers for response to therapy.

Establishing a Proteomics-Based Monocyte Assay To Assess Differential Innate Immune Activation Responses

Innate immune cells are complex systems that can be simultaneously activated in a variety of ways. Common methods currently used to estimate the response of innate immune cells to stimuli are usually biased toward a single mode of activation. The aim of this study was to assess the possibility of designing an assay based on unbiased proteome analysis that would be capable of predicting the complex response of the innate immune system to various challenges. Monocytes were used as representative cells of the innate immune system. The underlying hypothesis was that their proteome response to different activating molecules would reflect the immunogenicity of these molecules. To identify the main modes of response, we treated the human monocytic THP-1 cell line with nine different stimuli. Differentiation and activation were determined to be the two major modes of monocyte response, with PMA causing the strongest differentiation and Pam3CSK4 causing the strongest proinflammatory activation. The established assay was applied to characterize the monocyte response to epidermal growth factor peptide containing isoaspartate, which induced differentiation but not proinflammatory activation. Because of its versatility, robustness, and specificity, this new assay is likely to find a niche among the more established immunological methods.

Sister Chromatid Cohesion Establishment Factor ESCO1 Operates by Substrate-Assisted Catalysis

Sister chromatid cohesion, formed by the cohesin protein complex, is essential for chromosome segregation. In order for cohesion to be established, the cohesin subunit SMC3 needs to be acetylated by a homolog of the ESCO1/Eco1 acetyltransferases, the enzymatic mechanism of which has remained unknown. Here we report the crystal structure of the ESCO1 acetyltransferase domain in complex with acetyl-coenzyme A, and show by SAXS that ESCO1 is a dimer in solution. The structure reveals an active site that lacks a potential catalytic base side chain. However, mutation of glutamate 789, a surface residue that is close to the automodification target lysine 803, strongly reduces autoacetylation of ESCO1. Moreover, budding yeast Smc3 mutated at the conserved residue D114, adjacent to the cohesion-activating acetylation site K112,K113, cannot be acetylated in vivo. This indicates that ESCO1 controls cohesion through substrate-assisted catalysis. Thus, this study discloses a key mechanism for cohesion establishment.

Release of Active Peptidyl Arginine Deiminases by Neutrophils Can Explain Production of Extracellular Citrullinated Autoantigens in Rheumatoid Arthritis Synovial Fluid

Objective

In the majority of patients with rheumatoid arthritis (RA), antibodies specifically recognize citrullinated autoantigens that are generated by peptidylarginine deiminases (PADs). Neutrophils express high levels of PAD and accumulate in the synovial fluid (SF) of RA patients during disease flares. This study was undertaken to test the hypothesis that neutrophil cell death, induced by either NETosis (extrusion of genomic DNA–protein complexes known as neutrophil extracellular traps [NETs]) or necrosis, can contribute to production of autoantigens in the inflamed joint.

Methods

Extracellular DNA was quantified in the SF of patients with RA, patients with osteoarthritis (OA), and patients with psoriatic arthritis (PsA). Release of PAD from neutrophils was investigated by Western blotting, mass spectrometry, immunofluorescence staining, and PAD activity assays. PAD2 and PAD4 protein expression, as well as PAD enzymatic activity, were assessed in the SF of patients with RA and those with OA.

Results

Extracellular DNA was detected at significantly higher levels in RA SF than in OA SF (P < 0.001) or PsA SF (P < 0.05), and its expression levels correlated with neutrophil concentrations and PAD activity in RA SF. Necrotic neutrophils released less soluble extracellular DNA compared to NETotic cells in vitro (P < 0.05). Higher PAD activity was detected in RA SF than in OA SF (P < 0.05). The citrullinated proteins PAD2 and PAD4 were found attached to NETs and also freely diffused in the supernatant. PAD enzymatic activity was detected in supernatants of neutrophils undergoing either NETosis or necrosis.

Conclusion

Release of active PAD isoforms into the SF by neutrophil cell death is a plausible explanation for the generation of extracellular autoantigens in RA.

DeMix-Q: Quantification-Centered Data Processing Workflow

For historical reasons, most proteomics workflows focus on MS/MS identification but consider quantification as the end point of a comparative study. The stochastic data-dependent MS/MS acquisition (DDA) gives low reproducibility of peptide identifications from one run to another, which inevitably results in problems with missing values when quantifying the same peptide across a series of label-free experiments. However, the signal from the molecular ion is almost always present among the MS(1)spectra. Contrary to what is frequently claimed, missing values do not have to be an intrinsic problem of DDA approaches that perform quantification at the MS(1)level. The challenge is to perform sound peptide identity propagation across multiple high-resolution LC-MS/MS experiments, from runs with MS/MS-based identifications to runs where such information is absent. Here, we present a new analytical workflow DeMix-Q (https://github.com/userbz/DeMix-Q), which performs such propagation that recovers missing values reliably by using a novel scoring scheme for quality control. Compared with traditional workflows for DDA as well as previous DIA studies, DeMix-Q achieves deeper proteome coverage, fewer missing values, and lower quantification variance on a benchmark dataset. This quantification-centered workflow also enables flexible and robust proteome characterization based on covariation of peptide abundances.