Simulating and validating proteomics data and search results

8-OxoG-Dependent Regulation of Global Protein Responses Leads to Mutagenesis and Stress Survival in Bacillus subtilis

The guanine oxidized (GO) system of Bacillus subtilis, composed of the YtkD (MutT), MutM and MutY proteins, counteracts the cytotoxic and genotoxic effects of the oxidized nucleobase 8-OxoG. Here, we report that in growing B. subtilis cells, the genetic inactivation of GO system potentiated mutagenesis (HPM), and subsequent hyperresistance, contributes to the damaging effects of hydrogen peroxide (H2O2) (HPHR). The mechanism(s) that connect the accumulation of the mutagenic lesion 8-OxoG with the ability of B. subtilis to evolve and survive the noxious effects of oxidative stress were dissected. Genetic and biochemical evidence indicated that the synthesis of KatA was exacerbated, in a PerR-independent manner, and the transcriptional coupling repair factor, Mfd, contributed to HPHR and HPM of the ΔGO strain. Moreover, these phenotypes are associated with wider pleiotropic effects, as revealed by a global proteome analysis. The inactivation of the GO system results in the upregulated production of KatA, and it reprograms the synthesis of the proteins involved in distinct types of cellular stress; this has a direct impact on (i) cysteine catabolism, (ii) the synthesis of iron-sulfur clusters, (iii) the reorganization of cell wall architecture, (iv) the activation of AhpC/AhpF-independent organic peroxide resistance, and (v) increased resistance to transcription-acting antibiotics. Therefore, to contend with the cytotoxic and genotoxic effects derived from the accumulation of 8-OxoG, B. subtilis activates the synthesis of proteins belonging to transcriptional regulons that respond to a wide, diverse range of cell stressors.

Evaluation of acquisition modes for semi-quantitative analysis by targeted and untargeted mass spectrometry

RATIONALE

Analyte quantitation by mass spectrometry underpins a diverse range of scientific endeavors. The fast-growing field of mass spectrometer development has resulted in several targeted and untargeted acquisition modes suitable for these applications. By characterizing the acquisition methods available on an ion mobility (IM)-enabled orthogonal acceleration time-of-flight (oa-ToF) instrument, the optimum modes for analyte semi-quantitation can be deduced.

METHODS

Serial dilutions of commercial metabolite, peptide, or cross-linked peptide analytes were prepared in matrices of human urine or Escherichia coli digest. Each analyte dilution was introduced into an IM separation-enabled oa-ToF mass spectrometer by reversed-phase liquid chromatography and electrospray ionization. Data were acquired for each sample in duplicate using nine different acquisition modes, including four IM-enabled acquisitions modes, available on the mass spectrometer.

RESULTS

Five (metabolite) or seven (peptide/cross-linked peptide) point calibration curves were prepared for analytes across each of the acquisition modes. A nonlinear response was observed at high concentrations for some modes, attributed to saturation effects. Two correction methods, one MS1 isotope-correction and one MS2 ion intensity-correction, were applied to address this observation, resulting in an up to twofold increase in dynamic range. By averaging the semi-quantitative results across analyte classes, two parameters, linear dynamic range (LDR) and lower limit of quantification (LLOQ), were determined to evaluate each mode.

CONCLUSION

A comparison of the acquisition modes revealed that data-independent acquisition and parallel reaction monitoring methods are most robust for semi-quantitation when considering achievable LDR and LLOQ. IM-enabled modes exhibited sensitivity increases, but a simultaneous reduction in dynamic range required correction methods to recover. These findings will assist users in identifying the optimum acquisition mode for their analyte quantitation needs, supporting a diverse range of applications and providing guidance for future acquisition mode developments.

Differential Expression of Proteins in an Atypical Presentation of Autoimmune Lymphoproliferative Syndrome

Autoimmune lymphoproliferative syndrome (ALPS) is a rare disease defined as a defect in the lymphocyte apoptotic pathway. Currently, the diagnosis of ALPS is based on clinical aspects, defective lymphocyte apoptosis and mutations in Fas, FasL and Casp 10 genes. Despite this, ALPS has been misdiagnosed. The aim of this work was to go one step further in the knowledge of the disease, through a molecular and proteomic analysis of peripheral blood mononuclear cells (PBMCs) from two children, a 13-year-old girl and a 6-year-old boy, called patient 1 and patient 2, respectively, with clinical data supporting the diagnosis of ALPS. Fas, FasL and Casp10 genes from both patients were sequenced, and a sample of the total proteins from patient 1 was analyzed by label-free proteomics. Pathway analysis of deregulated proteins from PBMCs was performed on the STRING and PANTHER bioinformatics databases. A mutation resulting in an in-frame premature stop codon and protein truncation was detected in the Fas gene from patient 2. From patient 1, the proteomic analysis showed differences in the level of expression of proteins involved in, among other processes, cell cycle, regulation of cell cycle arrest and immune response. Noticeably, the most down-regulated protein is an important regulator of the cell cycle process. This could be an explanation of the disease in patient 1.

Proteomics Reveals an Increase in the Abundance of Glycolytic and Ethanolic Fermentation Enzymes in Developing Sugarcane Culms During Sucrose Accumulation

Sugarcane is an economically important crop contributing to the sugar and ethanol production of the world with 80 and 40%, respectively. Despite its importance as the main crop for sugar production, the mechanisms involved in the regulation of sucrose accumulation in sugarcane culms are still poorly understood. The aim of this work was to compare the quantitative changes of proteins in juvenile and maturing internodes at three stages of plant development. Label-free shotgun proteomics was used for protein profiling and quantification in internodes 5 (I₅) and 9 (I₉) of 4-, 7-, and 10-month-old-plants (4M, 7M, and 10M, respectively). The I₉/I₅ ratio was used to assess the differences in the abundance of common proteins at each stage of internode development. I₉ of 4M plants showed statistically significant increases in the abundance of several enzymes of the glycolytic pathway and proteoforms of alcohol dehydrogenase (ADH) and pyruvate decarboxylase (PDC). The changes in content of the enzymes were followed by major increases of proteins related to O₂ transport like hemoglobin 2, ROS scavenging enzymes, and enzymes involved in the ascorbate/glutatione system. Besides, intermediates from tricarboxylic acid cycle (TCA) were reduced in I₉-4M, indicating that the increase in abundance of several enzymes involved in glycolysis, pentose phosphate cycle, and TCA, might be responsible for higher metabolic flux, reducing its metabolites content. The results observed in I₉-4M indicate that hypoxia might be the main cause of the increased flux of glycolysis and ethanolic fermentation to supply ATP and reducing power for plant growth, mitigating the reduction in mitochondrial respiration due to the low oxygen availability inside the culm. As the plant matured and sucrose accumulated to high levels in the culms, the proteins involved in glycolysis, ethanolic fermentation, and primary carbon metabolism were significantly reduced.

Quantitative Proteomic Analysis of MARC-145 Cells Infected with a Mexican Porcine Reproductive and Respiratory Syndrome Virus Strain Using a Label-Free Based DIA approach

Porcine reproductive and respiratory syndrome (PRRS) is an infectious disease characterized by severe reproductive failure in sows, acute respiratory disorders in growing pigs, and high mortality in piglets. The causative agent of this syndrome is the PRRS virus (PRRSV), an RNA virus belonging to the Arteriviridae family. To date, several quantitative approaches of proteomics have been applied to analyze the gene expression profiles during PRRSV infection in PAMs and MARC-145 cells, and few proteins have been consistent among independent studies, probably due to the differences in the levels of virulence of different PRRSV strains used and/or due to analytical conditions. In this study, total proteins isolated from noninfected and infected MARC-145 cells with a Mexican PRRSV strain were relatively quantified using label-free based DIA approach in combination with ion-mobility separation. As a result, 1456 quantified proteins were found to be shared between the control and infected samples. Afterward, these proteins were filtered, and 699 of them were considered without change. Also, 17 proteins were up-regulated and 19 proteins were down-regulated during the PRSSV infection. Bioinformatic analysis revealed that many of the differentially expressed proteins are involved in processes like antigen processing, presentation of antigens, response to viruses, response to IFNs, and innate immune response, among others. The present work is the first one which provides a detailed proteomic analysis through label-free based DIA approach in MARC-145 cells during the infection with a Mexican PRRSV strain.

Protein Phosphorylation in Serine Residues Correlates with Progression from Precancerous Lesions to Cervical Cancer in Mexican Patients

Protein phosphorylation is a posttranslational modification that is essential for normal cellular processes; however, abnormal phosphorylation is one of the prime causes for alteration of many structural, functional, and regulatory proteins in disease conditions. In cancer, changes in the states of protein phosphorylation in tyrosine residues have been more studied than phosphorylation in threonine or serine residues, which also undergo alterations with greater predominance. In general, serine phosphorylation leads to the formation of multimolecular signaling complexes that regulate diverse biological processes, but in pathological conditions such as tumorigenesis, anomalous phosphorylation may result in the deregulation of some signaling pathways. Cervical cancer (CC), the main neoplasm associated with human papillomavirus (HPV) infection, is the fourth most frequent cancer worldwide. Persistent infection of the cervix with high-risk human papillomaviruses produces precancerous lesions starting with low-grade squamous intraepithelial lesions (LSIL), progressing to high-grade squamous intraepithelial lesions (HSIL) until CC is generated. Here, we compared the proteomic profile of phosphorylated proteins in serine residues from healthy, LSIL, HSIL, and CC samples. Our data show an increase in the number of phosphorylated proteins in serine residues as the grade of injury rises. These results provide a support for future studies focused on phosphorylated proteins and their possible correlation with the progression of cervical lesions.

Intestinal response to dietary manganese depletion inDrosophila

Metabolic adaptations to manganese deficiency.

Simplifying the Proteome: Analytical Strategies for Improving Peak Capacity

The diversity of biological samples and dynamic range of analytes being analyzed can prove to be an analytical challenge and is particularly prevalent to proteomic studies. Maximizing the peak capacity of the workflow employed can extend the dynamic range and increase identification rates. The focus of this chapter is to present means of achieving this for various analytical techniques such as liquid chromatography, mass spectrometry and ion mobility. A combination of these methods can be used as part of a data independent acquisition strategy, thereby limiting issues such as chimericy when analyzing regions of extreme analyte density.

Immune Response Resetting in Ongoing Sepsis

Cure of severe infections, sepsis, and septic shock with antimicrobial drugs is a challenge because morbidity and mortality in these conditions are essentially caused by improper immune response. We have tested the hypothesis that repeated reactivation of established memory to pathogens may reset unfavorable immune responses. We have chosen for this purpose a highly stringent mouse model of polymicrobial sepsis by cecum ligation and puncture. Five weeks after priming with a diverse Ag pool, high-grade sepsis was induced in C57BL/6j mice that was lethal in 24 h if left untreated. Antimicrobial drug (imipenem) alone rescued 9.7% of the animals from death, but >5-fold higher cure rate could be achieved by combining imipenem and two rechallenges with the Ag pool (p < 0.0001). Antigenic stimulation fine-tuned the immune response in sepsis by contracting the total CD3+ T cell compartment in the spleen and disengaging the hyperactivation state in the memory T subsets, most notably CD8+ T cells, while preserving the recovery of naive subsets. Quantitative proteomics/lipidomics analyses revealed that the combined treatment reverted the molecular signature of sepsis for cytokine storm, and deregulated inflammatory reaction and proapoptotic environment, as well as the lysophosphatidylcholine/phosphatidylcholine ratio. Our results showed the feasibility of resetting uncontrolled hyperinflammatory reactions into ordered hypoinflammatory responses by memory reactivation, thereby reducing morbidity and mortality in antibiotic-treated sepsis. This beneficial effect was not dependent on the generation of a pathogen-driven immune response itself but rather on the reactivation of memory to a diverse Ag pool that modulates the ongoing response.

Increased Sensitivity of Mass Spectrometry by Alkaline Two-Dimensional Liquid Chromatography: Deep Cover of the Human Proteome in Gene-Centric Mode

Currently, great interest is paid to the identification of "missing" proteins that have not been detected in any biological material at the protein level (PE1). In this paper, using the Universal Proteomic Standard sets 1 and 2 (UPS1 and UPS2, respectively) as an example, we characterized mass spectrometric approaches from the point of view of sensitivity (Sn), specificity (Sp), and accuracy (Ac). The aim of the paper was to show the utility of a mass spectra approach for protein detection. This sets consists of 48 high-purity human proteins without single aminoacid polymorphism (SAP) or post translational modification (PTM). The UPS1 set consists of the same 48 proteins at 5 pmols each, and in UPS2, proteins were grouped into 5 groups in accordance with their molar concentration, ranging from 10^-11 to 10^-6 M. Single peptides from the 92% and 96% of all sets of proteins could be detected in a pure solution of UPS2 and UPS1, respectively, by selected reaction monitoring with stable isotope-labeled standards (SRM-SIS). We also found that, in the presence of a biological matrix such as Escherichia coli extract or human blood plasma (HBP), SRM-SIS makes it possible to detect from 63% to 79% of proteins in the UPS2 set (sensitivity) with the highest specificity (∼100%) and an accuracy of 80% by increasing the sensitivity of shotgun and selected reaction monitoring combined with a stable-isotope-labeled peptide standard (SRM-SIS technology) by fractionating samples using reverse-phase liquid chromatography under alkaline conditions (2D-LC_alk). It is shown that this technique of sample fractionation allows the SRM-SIS to detect 98% of the single peptides from the proteins present in the pure solution of UPS2 (47 out of 48 proteins). When the extracts of E. coli or Pichia pastoris are added as biological matrixes to the UPS2, 46, and 45 out of 48 proteins (∼95%) can be detected, respectively, using the SRM-SIS combined with 2D-LC_alk. The combination of the 2D-LC_alk SRM-SIS and shotgun technologies allows us to increase the sensitivity up to 100% in the case of the proteins of the UPS2 set. The usage of that technology can be a solution for identifying the so-called "missing" proteins and, eventually, creating the deep proteome of a particular chromosome of tissue or organs. Experimental data have been deposited in the PeptideAtlas SRM Experiment Library with the dataset identifier PASS01192 and the PRIDE repository with the dataset identifier PXD007643.

Proteomic Cinderella: Customized analysis of bulky MS/MS data in one night

Proteomic challenges, stirred up by the advent of high-throughput technologies, produce large amount of MS data. Nowadays, the routine manual search does not satisfy the "speed" of modern science any longer. In our work, the necessity of single-thread analysis of bulky data emerged during interpretation of HepG2 proteome profiling results for proteoforms searching. We compared the contribution of each of the eight search engines (X!Tandem, MS-GF[Formula: see text], MS Amanda, MyriMatch, Comet, Tide, Andromeda, and OMSSA) integrated in an open-source graphical user interface SearchGUI ( http://searchgui.googlecode.com ) into total result of proteoforms identification and optimized set of engines working simultaneously. We also compared the results of our search combination with Mascot results using protein kit UPS2, containing 48 human proteins. We selected combination of X!Tandem, MS-GF[Formula: see text] and OMMSA as the most time-efficient and productive combination of search. We added homemade java-script to automatize pipeline from file picking to report generation. These settings resulted in rise of the efficiency of our customized pipeline unobtainable by manual scouting: the analysis of 192 files searched against human proteome (42153 entries) downloaded from UniProt took 11[Formula: see text]h.

Multi-mode acquisition (MMA): An MS/MS acquisition strategy for maximizing selectivity, specificity and sensitivity of DIA product ion spectra

In proteomics studies, it is generally accepted that depth of coverage and dynamic range is limited in data-directed acquisitions. The serial nature of the method limits both sensitivity and the number of precursor ions that can be sampled. To that end, a number of data-independent acquisition (DIA) strategies have been introduced with these methods, for the most part, immune to the sampling issue; nevertheless, some do have other limitations with respect to sensitivity. The major limitation with DIA approaches is interference, i.e., MS/MS spectra are highly chimeric and often incapable of being identified using conventional database search engines. Utilizing each available dimension of separation prior to ion detection, we present a new multi-mode acquisition (MMA) strategy multiplexing both narrowband and wideband DIA acquisitions in a single analytical workflow. The iterative nature of the MMA workflow limits the adverse effects of interference with minimal loss in sensitivity. Qualitative identification can be performed by selected ion chromatograms or conventional database search strategies.

Label-Free Proteome Analysis of Plasma from Patients with Breast Cancer: Stage-Specific Protein Expression

Breast cancer is one of the most commonly diagnosed types of cancer among women. Breast cancer mortality rates remain high probably because its diagnosis is hampered by inaccurate detection methods. Since changes in protein expression as well as modifications in protein glycosylation have been frequently reported in cancer development, the aim of this work was to study the differential expression as well as modifications of glycosylation of proteins from plasma of women with breast cancer at different stages of disease (n = 30) compared to healthy women (n = 10). A proteomics approach was used that depleted albumin and IgG from plasma followed by glycoprotein enrichment using immobilized Moraceae lectin (frutalin)-affinity chromatography and data-independent label-free mass spectrometric analysis. Data are available via ProteomeXchange with identifier PXD003106. As result, 57,016 peptides and 4,175 proteins among all samples were identified. From this, 40 proteins present in unbound (PI—proteins that did not interact with lectin) and bound (PII—proteins that interacted with lectin) fractions were differentially expressed. High levels of apolipoprotein A-II were detected here that were elevated significantly in the early and advanced stages of the disease. Apolipoprotein C-III was detected in both fractions, and its level was increased slightly in the PI fraction of patients with early-stage breast cancer and expressed at higher levels in the PII fraction of patients with early and intermediate stages. Clusterin was present at higher levels in both fractions of patients with early and intermediate stages of breast cancer. Our findings reveal a correlation between alterations in protein glycosylation, lipid metabolism, and the progression of breast cancer.

LC-MSE, Multiplex MS/MS, Ion Mobility, and Label-Free Quantitation in Clinical Proteomics

Proteomic tools can only be implemented in clinical settings if high-throughput, automated, sensitive, and accurate methods are developed. This has driven researchers to the edge of mass spectrometry (MS)-based proteomics capacity. Here we provide an overview of recent achievements in mass spectrometric technologies and instruments. This includes development of high and ultra definition-MS^E (HDMS^E and UDMS^E) through implementation of ion mobility (IM) MS towards sensitive and accurate label-free proteomics using ultra performance liquid chromatography (UPLC). Label free UPLC-HDMS^E is less expensive than labeled-based quantitative proteomics and has no limits regarding the number of samples that can be analyzed and compared, which is an important requirement for supporting clinical applications.

Clinical proteomics in cancer: Where we are

Proteomics has emerged as a promising field in the post-genomic era. Notwithstanding the great advances provided by gene expression analysis in cancer, the lack of a correlation between gene expression and protein levels has highlighted the need for a proteomic focus on cancer. Although the increasing knowledge regarding cancer biology, a reliable marker to improve diagnosis, prognosis and treatment for cancer patients is not a reality at present. In this review, we address the main considerations regarding proteomics-based studies and their clinical applications on cancer research, highlighting some considerations related to strengths and limitations of proteomics-based studies and its application to clinical practice.

Insight into Trypsin Miscleavage: Comparison of Kinetic Constants of Problematic Peptide Sequences

Trypsin, a high fidelity protease, is the most widely used enzyme for protein digestion in proteomic research. Optimal digestion conditions are well-known and so are the expected cleavage products. However, missed cleavage sites are frequently observed when acidic amino acids, aspartic and glutamic acids, are present near the cleavage site. Also, the sequence motifs with successive lysine and/or arginine residues represent a source of missed cleaved sites. In spite of an adverse role of missed cleaved peptides on proteomic research, the digestion kinetics of these problematic sequences is not well-known. In this work, synthetic peptides with various sequence motifs were used as trypsin substrates. Cleavage products were analyzed with reversed-phase high performance liquid chromatography, and the kinetic constants for selected missed cleavage sites were calculated. Relative digestion speed for lysine and arginine sites is compared, including the digestion motifs flanked with aspartic and glutamic acid. Our findings show that DK and DTR motifs are cleaved by trypsin with 3 orders of magnitude lower speed than the arginine site. These motifs are likely to produce missed cleavage peptides in protein tryptic digests even at prolonged digestion times.

SuperQuant: A Data Processing Approach to Increase Quantitative Proteome Coverage

SuperQuant is a quantitative proteomics data processing approach that uses complementary fragment ions to identify multiple coisolated peptides in tandem mass spectra allowing for their quantification. This approach can be applied to any shotgun proteomics data set acquired with high mass accuracy for quantification at the MS(1) level. The SuperQuant approach was developed and implemented as a processing node within the Thermo Proteome Discoverer 2.x. The performance of the developed approach was tested using dimethyl-labeled HeLa lysate samples having a ratio between channels of 10(heavy):4(medium):1(light). Peptides were fragmented with collision-induced dissociation using isolation windows of 1, 2, and 4 Th while recording data both with high-resolution and low-resolution. The results obtained using SuperQuant were compared to those using the conventional ion trap-based approach (low mass accuracy MS(2) spectra), which is known to achieve high identification performance. Compared to the common high-resolution approach, the SuperQuant approach identifies up to 70% more peptide-spectrum matches (PSMs), 40% more peptides, and 20% more proteins at the 0.01 FDR level. It identifies more PSMs and peptides than the ion trap-based approach. Improvements in identifications resulted in up to 10% more PSMs, 15% more peptides, and 10% more proteins quantified on the same raw data. The developed approach does not affect the accuracy of the quantification and observed coefficients of variation between replicates of the same proteins were close to the values typical for other precursor ion-based quantification methods. The raw data is deposited to ProteomeXchange (PXD001907). The developed node is available for testing at https://github.com/caetera/SuperQuantNode.

Mechanisms of kidney repair by human mesenchymal stromal cells after ischemia: a comprehensive view using label-free MS(E)

Acute kidney injury (AKI) is one of the more frequent and lethal pathological conditions seen in intensive care units. Currently available treatments are not totally effective but stem cell-based therapies are emerging as promising alternatives, especially the use of mesenchymal stromal cells (MSC), although the signaling pathways involved in their beneficial actions are not fully understood. The objective of this study was to identify signaling networks and key proteins involved in the repair of ischemia by MSC. Using an in vitro model of AKI to investigate paracrine interactions and label-free high definition 2D-NanoESI-MS(E) , differentially expressed proteins were identified in a human renal proximal tubule cell lineage (HK-2) exposed to human MSC (hMSC) after an ischemic insult. In silico analysis showed that hMSC stimulated antiapoptotic activity, normal ROS handling, energy production, cytoskeleton organization, protein synthesis, and cell proliferation. The proteomic data were validated by parallel experiments demonstrating reduced apoptosis in HK-2 cells and recovery of intracellular ATP levels. qRT-PCR for proteins implicated in the above processes revealed that hMSC exerted their effects by stimulating translation, not transcription. Western blotting of proteins associated with ROS and energy metabolism confirmed their higher abundance in HK-2 cells exposed to hMSC.

Multiple enzymatic digestions and ion mobility separation improve quantification of bacterial ribosomal proteins by data independent acquisition liquid chromatography-mass spectrometry

Mass spectrometry-based quantification of ribosomal proteins (r-proteins) associated with mature ribosomes and ribosome assembly complexes is typically accomplished by relative quantification strategies. These strategies provide information on the relative stoichiometry of proteins within the complex compared to a wild-type strain. Here we have evaluated the applicability of a label-free approach, enhanced liquid chromatography–mass spectrometry (LC–MS^E), for absolute “ribosome-centric” quantification of r-proteins in Escherichia coli mature ribosomes. Because the information obtained in this experiment is related to the number of peptides identified per protein, experimental conditions that allow accurate and reproducible quantification of r-proteins were found. Using an additional dimension of gas-phase separation through ion mobility and the use of multiple endoproteinase digestion significantly improved quantification of proteins associated with mature ribosomes. The actively translating ribosomes (polysomes) contain amounts of proteins consistent with their known stoichiometry within the complex. These measurements exhibited technical and biological reproducibilities at %CV less than 15% and 35%, respectively. The improved LC–MS^E approach described here can be used to characterize in vivo ribosome assembly complexes captured during ribosome biogenesis and assembly under different perturbations (e.g., antibiotics, deletion mutants of assembly factors, oxidative stress, nutrient deprivation). Quantitative analysis of these captured complexes will provide information relating to the interplay and dynamics of how these perturbations interfere with the assembly process.

Discovering the infectome of human endothelial cells challenged with Aspergillus fumigatus applying a mass spectrometry label-free approach

Blood vessel invasion is a key feature of invasive aspergillosis. This angioinvasion process contributes to tissue thrombosis, which can impair the access of leukocytes and antifungal drugs to the site of infection. It has been demonstrated that human umbilical vein endothelial cells (HUVECs) are activated and assume a prothrombotic phenotype following contact with Aspergillus fumigatus hyphae or germlings, a process that is independent of fungus viability. However, the molecular mechanisms by which this pathogen can activate endothelial cells, together with the endothelial pathways that are involved in this process, remain unknown. Using a label-free approach by High Definition Mass Spectrometry (HDMS(E)), differentially expressed proteins were identified during HUVEC-A. fumigatus interaction. Among these, 89 proteins were determined to be up- or down-regulated, and another 409 proteins were exclusive to one experimental condition: the HUVEC control or HUVEC:AF interaction. The in silico predictions provided a general view of which biological processes and/or pathways were regulated during HUVEC:AF interaction, and they mainly included cell signaling, immune response and hemostasis pathways. This work describes the first global proteomic analysis of HUVECs following interaction with A. fumigatus germlings, the fungus morphotype that represents the first step of invasion and dissemination within the host.

BIOLOGICAL SIGNIFICANCE

A. fumigatus causes the main opportunistic invasive fungal infection related to neutropenic hematologic patients. One of the key steps during the establishment of invasive aspergillosis is angioinvasion but the mechanism associated with the interaction of A. fumigatus with the vascular endothelium remains unknown. The identification of up- and down-regulated proteins expressed by human endothelial cells in response to the fungus infection can contribute to reveal the mechanism of endothelial response and, to understand the physiopathology of this high mortality disease. This article is part of a Special Issue entitled: Trends in Microbial Proteomics.

Effects of traveling wave ion mobility separation on data independent acquisition in proteomics studies

qTOF mass spectrometry and traveling wave ion mobility separation (TWIMS) hybrid instruments (q-TWIMS-TOF) have recently become commercially available. Ion mobility separation allows an additional dimension of precursor separation inside the instrument, without incurring an increase in instrument time. We comprehensively investigated the effects of TWIMS on data-independent acquisition on a Synapt G2 instrument. We observed that if fragmentation is performed post TWIMS, more accurate assignment of fragment ions to precursors is possible in data independent acquisition. This allows up to 60% higher proteome coverage and higher confidence of protein and peptide identifications. Moreover, the majority of peptides and proteins identified upon application of TWIMS span the lower intensity range of the proteome. It has also been demonstrated in several studies that employing IMS results in higher peak capacity of separation and consequently more accurate and precise quantitation of lower intensity precursor ions. We observe that employing TWIMS results in an attenuation of the detected ion current. We postulate that this effect is binary; sensitivity is reduced due to ion scattering during transfer into a high pressure "IMS zone", sensitivity is reduced due to the saturation of detector digitizer as a result of the IMS concentration effect. This latter effect limits the useful linear range of quantitation, compromising quantitation accuracy of high intensity peptides. We demonstrate that the signal loss from detector saturation and transmission loss can be deconvoluted by investigation of the peptide isotopic envelope. We discuss the origin and extent of signal loss and suggest methods to minimize these effects on q-TWIMS-TOF instrument in the light of different experimental designs and other IMS/MS platforms described previously.

Improving qualitative and quantitative performance for MS(E)-based label-free proteomics

Label-free quantitation by data independent methods (for instance MS(E)) is growing in popularity due to the high technical reproducibility of mass spectrometry analysis. The recent introduction of Synapt hybrid instruments capable of incorporating ion mobility separation within mass spectrometry analysis now allows acquisition of high definition MS(E) data (HDMS(E)). HDMS(E) enables deeper proteome coverage and more confident peptide identifications when compared to MS(E), while the latter offers a higher dynamic range for quantitation. We have developed synapter as, a versatile tool to better evaluate the results of data independent acquisitions on Waters instruments. We demonstrate that synapter can be used to combine HDMS(E) and MS(E) data to achieve deeper proteome coverage delivered by HDMS(E) and more accurate quantitation for high intensity peptides, delivered by MS(E). For users who prefer to run samples exclusively in one mode, synapter allows other useful functionality like false discovery rate estimation, filtering on peptide match type and mass error, and filling missing values. Our software integrates with existing tools, thus permitting us to easily combine peptide quantitation information into protein quantitation by a range of different approaches.

Data processing methods and quality control strategies for label-free LC-MS protein quantification

Protein quantification using different LC-MS techniques is becoming a standard practice. However, with a multitude of experimental setups to choose from, as well as a wide array of software solutions for subsequent data processing, it is non-trivial to select the most appropriate workflow for a given biological question. In this review, we highlight different issues that need to be addressed by software for quantitative LC-MS experiments and describe different approaches that are available. With focus on label-free quantification, examples are discussed both for LC-MS/MS and LC-SRM data processing. We further elaborate on current quality control methodology for performing accurate protein quantification experiments. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

Design and application of a data-independent precursor and product ion repository

The functional design and application of a data-independent LC-MS precursor and product ion repository for protein identification, quantification, and validation is conceptually described. The ion repository was constructed from the sequence search results of a broad range of discovery experiments investigating various tissue types of two closely related mammalian species. The relative high degree of similarity in protein complement, ion detection, and peptide and protein identification allows for the analysis of normalized precursor and product ion intensity values, as well as standardized retention times, creating a multidimensional/orthogonal queryable, qualitative, and quantitative space. Peptide ion map selection for identification and quantification is primarily based on replication and limited variation. The information is stored in a relational database and is used to create peptide- and protein-specific fragment ion maps that can be queried in a targeted fashion against the raw or time aligned ion detections. These queries can be conducted either individually or as groups, where the latter affords pathway and molecular machinery analysis of the protein complement. The presented results also suggest that peptide ionization and fragmentation efficiencies are highly conserved between experiments and practically independent of the analyzed biological sample when using similar instrumentation. Moreover, the data illustrate only minor variation in ionization efficiency with amino acid sequence substitutions occurring between species. Finally, the data and the presented results illustrate how LC-MS performance metrics can be extracted and utilized to ensure optimal performance of the employed analytical workflows.

A computational tool to detect and avoid redundancy in selected reaction monitoring

Selected reaction monitoring (SRM), also called multiple reaction monitoring, has become an invaluable tool for targeted quantitative proteomic analyses, but its application can be compromised by nonoptimal selection of transitions. In particular, complex backgrounds may cause ambiguities in SRM measurement results because peptides with interfering transitions similar to those of the target peptide may be present in the sample. Here, we developed a computer program, the SRMCollider, that calculates nonredundant theoretical SRM assays, also known as unique ion signatures (UIS), for a given proteomic background. We show theoretically that UIS of three transitions suffice to conclusively identify 90% of all yeast peptides and 85% of all human peptides. Using predicted retention times, the SRMCollider also simulates time-scheduled SRM acquisition, which reduces the number of interferences to consider and leads to fewer transitions necessary to construct an assay. By integrating experimental fragment ion intensities from large scale proteome synthesis efforts (SRMAtlas) with the information content-based UIS, we combine two orthogonal approaches to create high quality SRM assays ready to be deployed. We provide a user friendly, open source implementation of an algorithm to calculate UIS of any order that can be accessed online at http://www.srmcollider.org to find interfering transitions. Finally, our tool can also simulate the specificity of novel data-independent MS acquisition methods in Q1-Q3 space. This allows us to predict parameters for these methods that deliver a specificity comparable with that of SRM. Using SRM interference information in addition to other sources of information can increase the confidence in an SRM measurement. We expect that the consideration of information content will become a standard step in SRM assay design and analysis, facilitated by the SRMCollider.