Defining, comparing, and improving iTRAQ quantification in mass spectrometry proteomics data

Tissue Inhibitor of Metalloproteinase 3 (TIMP3) mutations increase glycolytic activity and dysregulate glutamine metabolism in RPE cells

OBJECTIVES

Mutations in Tissue Inhibitor of Metalloproteinases 3 (TIMP3) cause Sorsby's Fundus Dystrophy (SFD), a dominantly inherited, rare form of macular degeneration that results in vision loss. TIMP3 is synthesized primarily by retinal pigment epithelial (RPE) cells, which constitute the outer blood-retinal barrier. One major function of RPE is the synthesis and transport of vital nutrients, such as glucose, to the retina. Recently, metabolic dysfunction in RPE cells has emerged as an important contributing factor in retinal degenerations. We set out to determine if RPE metabolic dysfunction was contributing to SFD pathogenesis.

METHODS

Quantitative proteomics was conducted on RPE of mice expressing the S179C variant of TIMP3, known to be causative of SFD in humans. Proteins found to be differentially expressed (P < 0.05) were analyzed using statistical overrepresentation analysis to determine enriched pathways, processes, and protein classes using g:profiler and PANTHER Gene Ontology. We examined the effects of mutant TIMP3 on RPE metabolism using human ARPE-19 cells expressing mutant S179C TIMP3 and patient-derived induced pluripotent stem cell-derived RPE (iRPE) carrying the S204C TIMP3 mutation. RPE metabolism was directly probed using isotopic tracing coupled with GC/MS analysis. Steady state [U-13C6] glucose isotopic tracing was preliminarily conducted on S179C ARPE-19 followed by [U-13C6] glucose and [U-13C5] glutamine isotopic tracing in SFD iRPE cells.

RESULTS

Quantitative proteomics and enrichment analysis conducted on RPE of mice expressing mutant S179C TIMP3 identified differentially expressed proteins that were enriched for metabolism-related pathways and processes. Notably these results highlighted dysregulated glycolysis and glucose metabolism. Stable isotope tracing experiments with [U-13C6] glucose demonstrated enhanced glucose utilization and glycolytic activity in S179C TIMP3 APRE-19 cells. Similarly, [U-13C6] glucose tracing in SFD iRPE revealed increased glucose contribution to glycolysis and the TCA cycle. Additionally, [U-13C5] glutamine tracing found evidence of altered malic enzyme activity.

CONCLUSIONS

This study provides important information on the dysregulation of RPE glucose metabolism in SFD and implicates a potential commonality with other retinal degenerative diseases, emphasizing RPE cellular metabolism as a therapeutic target.

A Causal Model of Ion Interference Enables Assessment and Correction of Ratio Compression in Multiplex Proteomics

Multiplex proteomics using isobaric labeling tags has emerged as a powerful tool for the simultaneous relative quantification of peptides and proteins across multiple experimental conditions. However, the quantitative accuracy of the approach is largely compromised by ion interference, a phenomenon that causes fold changes to appear compressed. The degree of compression is generally unknown, and the contributing factors are poorly understood. In this study, we thoroughly characterized ion interference at the MS2 level using a defined two-proteome experimental system with known ground-truth. We discovered remarkably poor agreement between the apparent precursor purity in the isolation window and the actual level of observed reporter ion interference in MS2 scans-a discrepancy that we found resolved by considering cofragmentation of peptide ions hidden within the spectral "noise" of the MS1 isolation window. To address this issue, we developed a regression modeling strategy to accurately predict reporter ion interference in any dataset. Finally, we demonstrate the utility of our procedure for improved fold change estimation and unbiased PTM site-to-protein normalization. All computational tools and code required to apply this method to any MS2 TMT dataset are documented and freely available.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

The Two Weapons against Bacterial Biofilms: Detection and Treatment

Bacterial biofilms are defined as complex aggregates of bacteria that grow attached to surfaces or are associated with interfaces. Bacteria within biofilms are embedded in a self-produced extracellular matrix made of polysaccharides, nucleic acids, and proteins. It is recognized that bacterial biofilms are responsible for the majority of microbial infections that occur in the human body, and that biofilm-related infections are extremely difficult to treat. This is related with the fact that microbial cells in biofilms exhibit increased resistance levels to antibiotics in comparison with planktonic (free-floating) cells. In the last years, the introduction into the market of novel compounds that can overcome the resistance to antimicrobial agents associated with biofilm infection has slowed down. If this situation is not altered, millions of lives are at risk, and this will also strongly affect the world economy. As such, research into the identification and eradication of biofilms is important for the future of human health. In this sense, this article provides an overview of techniques developed to detect and imaging biofilms as well as recent strategies that can be applied to treat biofilms during the several biofilm formation steps.

Quantitative Proteomics Using Isobaric Labeling: A Practical Guide

In the past decade, relative proteomic quantification using isobaric labeling technology has developed into a key tool for comparing the expression of proteins in biological samples. Although its multiplexing capacity and flexibility make this a valuable technology for addressing various biological questions, its quantitative accuracy and precision still pose significant challenges to the reliability of its quantification results. Here, we give a detailed overview of the different kinds of isobaric mass tags and the advantages and disadvantages of the isobaric labeling method. We also discuss which precautions should be taken at each step of the isobaric labeling workflow, to obtain reliable quantification results in large-scale quantitative proteomics experiments. In the last section, we discuss the broad applications of the isobaric labeling technology in biological and clinical studies, with an emphasis on thermal proteome profiling and proteogenomics.

Enhanced Biosynthesis of Fatty Acids Is Associated with the Acquisition of Ciprofloxacin Resistance in Edwardsiella tarda

Misuse and overuse of antibiotics drive the selection and spread of antibiotic-resistant bacteria. Although genetic mutations have been well defined for different types of antibiotic resistance, ways to revert antibiotic resistance are largely unexplored. Here, we adopted a proteomics approach to investigate the mechanism underlying ciprofloxacin resistance in Edwardsiella tarda, a representative pathogen that infects both economic animal species and human beings. By comparing the protein expression profiles of ciprofloxacin-sensitive and -resistant E. tarda, a total of 233 proteins of differential abundance were identified, where 53 proteins belong to the functional categories of metabolism, featuring a disrupted pyruvate cycle and decreased energy metabolism but increased fatty acid biosynthesis. The altered pyruvate cycle and energy metabolism were confirmed by gene expression and biochemical assays. Furthermore, the role of fatty acid biosynthesis and quinolone resistance were explored. The expression level and enzymatic activity of acetyl coenzyme A (acetyl-CoA) carboxylase, the first step of fatty acid biosynthesis, were increased in ciprofloxacin-resistant E. tarda. Treatment of ciprofloxacin-resistant E. tarda with acetyl-CoA carboxylase and 3-oxoacyl-[acyl carrier protein] synthase II inhibitors, 2-aminooxazole and triclosan, respectively, reduced the expression of fatty acid biosynthesis and promoted quinolone-mediated killing efficacy to antibiotic-resistant bacteria. Similar results were obtained in clinically isolated E. tarda strains. Our study suggests that energy metabolism has been reprogramed in ciprofloxacin-resistant bacteria that favor the biosynthesis of fatty acid, presenting a novel target to tackle antibiotic-resistant bacteria.

IMPORTANCEEdwardsiella tarda is the causative agent of edwardsiellosis, which imposes huge challenges on clinics and aquaculture. Due to the overuse of antibiotics, the emergence and spread of antibiotic-resistant E. tarda threaten human health and animal farming. However, the mechanism of ciprofloxacin resistance in E. tarda is still lacking. Here, iTRAQ (isobaric tags for relative and absolute quantification)-based proteomics was performed to identify a differential proteome between ciprofloxacin-sensitive and -resistant E. tarda. The fluctuated pyruvate cycle and reduced energy metabolism and elevated fatty acid biosynthesis are metabolic signatures of ciprofloxacin resistance. Moreover, inhibition of biosynthesis of fatty acids promotes quinolone-mediated killing efficacy in both lab-evolved and clinically isolated strains. This study reveals that a ciprofloxacin resistance mechanism is mediated by the elevated biosynthesis of fatty acids and the depressed pyruvate metabolism and energy metabolism in E. tarda. These findings provide a novel understanding for the ciprofloxacin resistance mechanism in E. tarda.

Thirteen-week nose-only inhalation exposures of propylene glycol aerosols in Sprague Dawley rats with a lung systems toxicology analysis

The objectives of this study were to increase PG exposure above concentrations tested by Suber et al. and use systems toxicology analysis of lung tissue to understand molecular events. Sprague Dawley rats were exposed to filtered air (sham), propylene glycol/water (PG/W; 90:10) or a propylene glycol/vegetable glycerin/water (PG/VG/W; 50:40:10) reference. The reference group was added at the high dose to observe any changes that might be associated with a carrier more in line with e-vapor products. Macroscopic examinations and terminal organ weights revealed no observations associated with exposure to PG/W or reference. Food consumption and body weights were unaffected by PG/W or reference when compared to sham. No exposure related alterations were observed in serum chemistry, hematology, coagulation, urinalysis or BALF cytology and clinical chemistry. Although clinical observations of dried red material around the nose in the high dose PG/W group were reported, histopathology showed no nasal hemorrhaging which was previously reported by Suber et al. Non-adverse PG/W and reference related findings of minimal mucous cell hyperplasia were noted in nasal cavity section II. No other exposure-related findings were noted in the primary or recovery necropsies. A systems toxicology analysis on lung tissue showed no statistically significant differentially expressed transcripts or proteins compared to the sham group. The endpoints measured from the PG/W high dose group did not differ significantly from those in the more common carrier PG/VG/W. As anticipated, exposure to PG aerosols was slightly irritating but well tolerated. Accordingly, the highest PG exposure (5 mg/L, 6 hrs/day) was regarded as the NOAEC, corresponding to a PG delivered dose of 1,152 mg/kg/day in rats.

Proteomics of Primary Uveal Melanoma: Insights into Metastasis and Protein Biomarkers

Uveal melanoma metastases are lethal and remain incurable. A quantitative proteomic analysis of 53 metastasizing and 47 non-metastasizing primary uveal melanoma (pUM) was pursued for insights into UM metastasis and protein biomarkers. The metastatic status of the pUM specimens was defined based on clinical data, survival histories, prognostic analyses, and liver histopathology. LC MS/MS iTRAQ technology, the Mascot search engine, and the UniProt human database were used to identify and quantify pUM proteins relative to the normal choroid excised from UM donor eyes. The determined proteomes of all 100 tumors were very similar, encompassing a total of 3935 pUM proteins. Proteins differentially expressed (DE) between metastasizing and non-metastasizing pUM (n = 402) were employed in bioinformatic analyses that predicted significant differences in the immune system between metastasizing and non-metastasizing pUM. The immune proteins (n = 778) identified in this study support the immune-suppressive nature and low abundance of immune checkpoint regulators in pUM, and suggest CDH1, HLA-DPA1, and several DE immune kinases and phosphatases as possible candidates for immune therapy checkpoint blockade. Prediction modeling identified 32 proteins capable of predicting metastasizing versus non-metastasizing pUM with 93% discriminatory accuracy, supporting the potential for protein-based prognostic methods for detecting UM metastasis.

Disease-specific platelet signaling defects in idiopathic pulmonary arterial hypertension

Idiopathic pulmonary arterial hypertension (IPAH) is a rapidly progressive disease with several treatment options. Long-term mortality remains high with great heterogeneity in treatment response. Even though most of the pathology of IPAH is observed in the lung, there is systemic involvement. Platelets from patients with IPAH have characteristic metabolic shifts and defects in activation; therefore, we investigated whether they could be used to identify other disease-specific abnormalities. We used proteomics to investigate protein expression changes in platelets from patients with IPAH compared with healthy controls. Key abnormalities of nitric oxide pathway were tested in platelets from a larger cohort of unique patients with IPAH. Platelets showed abnormalities in the prostacyclin and nitric oxide pathways, which are dysregulated in IPAH and hence targets of therapy. We detected reduced expression of G protein αs and increased expression of the regulatory subunits of the cAMP-dependent protein kinase (PKA) type II isoforms, supporting an overall decrease in the activation of the prostacyclin pathway. We noted reduced levels of the soluble guanylate cyclase (sGC) subunits and increased expression of the phosphodiesterase type 5 A (PDE5A), conditions that affect the response to nitric oxide. Ensuing analysis of 38 unique patients with IPAH demonstrated considerable variation in the levels and specific activity of sGC, a finding with novel implications for personalized therapy. Platelets have some of the characteristic vasoactive signal abnormalities seen in IPAH and may provide comprehensive ex vivo mechanistic information to direct therapeutic decisions.

Impact of whole-body versus nose-only inhalation exposure systems on systemic, respiratory, and cardiovascular endpoints in a 2-month cigarette smoke exposure study in the ApoE-/- mouse model

Cigarette smoking is one major modifiable risk factor in the development and progression of chronic obstructive pulmonary disease and cardiovascular disease. To characterize and compare cigarette smoke (CS)-induced disease endpoints after exposure in either whole-body (WB) or nose-only (NO) exposure systems, we exposed apolipoprotein E-deficient mice to filtered air (Sham) or to the same total particulate matter (TPM) concentration of mainstream smoke from 3R4F reference cigarettes in NO or WB exposure chambers (EC) for 2 months. At matching TPM concentrations, we observed similar concentrations of carbon monoxide, acetaldehyde, and acrolein, but higher concentrations of nicotine and formaldehyde in NOEC than in WBEC. In both exposure systems, CS exposure led to the expected adaptive changes in nasal epithelia, altered lung function, lung inflammation, and pronounced changes in the nasal epithelial transcriptome and lung proteome. Exposure in the NOEC caused generally more severe histopathological changes in the nasal epithelia and a higher stress response as indicated by body weight decrease and lower blood lymphocyte counts compared with WB exposed mice. Erythropoiesis, and increases in total plasma triglyceride levels and atherosclerotic plaque area were observed only in CS-exposed mice in the WBEC group but not in the NOEC group. Although the composition of CS in the breathing zone is not completely comparable in the two exposure systems, the CS-induced respiratory disease endpoints were largely confirmed in both systems, with a higher magnitude of severity after NO exposure. CS-accelerated atherosclerosis and other pro-atherosclerotic factors were only significant in WBEC.

A 7-month inhalation toxicology study in C57BL/6 mice demonstrates reduced pulmonary inflammation and emphysematous changes following smoking cessation or switching to e-vapor products

Cigarette smoking causes serious diseases, including lung cancer, atherosclerotic coronary artery disease, peripheral vascular disease, chronic bronchitis, and emphysema. While cessation remains the most effective approach to minimize smoking-related disease, alternative non-combustible tobacco-derived nicotine-containing products may reduce disease risks among those unable or unwilling to quit. E-vapor aerosols typically contain significantly lower levels of smoke-related harmful and potentially harmful constituents; however, health risks of long-term inhalation exposures are unknown. We designed a 7-month inhalation study in C57BL/6 mice to evaluate long-term respiratory toxicity of e-vapor aerosols compared to cigarette smoke and to assess the impact of smoking cessation (Cessation group) or switching to an e-vapor product (Switching group) after 3 months of exposure to 3R4F cigarette smoke (CS). There were no significant changes in in-life observations (body weights, clinical signs) in e-vapor groups compared to the Sham Control. The 3R4F CS group showed reduced respiratory function during exposure and had lower body weight and showed transient signs of distress post-exposure. Following 7 months of exposure, e-vapor aerosols resulted in no or minimal increase in pulmonary inflammation, while exposure to 3R4F CS led to impairment of lung function and caused marked lung inflammation and emphysematous changes. Biological changes observed in the Switching group were similar to the Cessation group. 3R4F CS exposure dysregulated the lung and nasal tissue transcriptome, while these molecular effects were substantially lower in the e-vapor group. Results from this study demonstrate that in comparison with 3R4F CS, e-vapor aerosols induce substantially lower biological responses including pulmonary inflammation and emphysematous changes, and that complete switching from CS to e-vapor products significantly reduces biological changes associated with CS in C57BL/6 mice.

Multi-Q 2 software facilitates isobaric labeling quantitation analysis with improved accuracy and coverage

Mass spectrometry-based proteomics using isobaric labeling for multiplex quantitation has become a popular approach for proteomic studies. We present Multi-Q 2, an isobaric-labeling quantitation tool which can yield the largest quantitation coverage and improved quantitation accuracy compared to three state-of-the-art methods. Multi-Q 2 supports identification results from several popular proteomic data analysis platforms for quantitation, offering up to 12% improvement in quantitation coverage for accepting identification results from multiple search engines when compared with MaxQuant and PatternLab. It is equipped with various quantitation algorithms, including a ratio compression correction algorithm, and results in up to 336 algorithmic combinations. Systematic evaluation shows different algorithmic combinations have different strengths and are suitable for different situations. We also demonstrate that the flexibility of Multi-Q 2 in customizing algorithmic combination can lead to improved quantitation accuracy over existing tools. Moreover, the use of complementary algorithmic combinations can be an effective strategy to enhance sensitivity when searching for biomarkers from differentially expressed proteins in proteomic experiments. Multi-Q 2 provides interactive graphical interfaces to process quantitation and to display ratios at protein, peptide, and spectrum levels. It also supports a heatmap module, enabling users to cluster proteins based on their abundance ratios and to visualize the clustering results. Multi-Q 2 executable files, sample data sets, and user manual are freely available at http://ms.iis.sinica.edu.tw/COmics/Software_Multi-Q2.html.

Ceramide ratios are affected by cigarette smoke but not heat-not-burn or e-vapor aerosols across four independent mouse studies

AIMS

Smoking is an important risk factor for the development of chronic obstructive pulmonary disease and cardiovascular diseases. This study aimed to further elucidate the role of ceramides, as a key lipid class dysregulated in disease states.

MAIN METHODS

In this article we developed and validated LC-MS/MS method for ceramides (Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0) and Cer(d18:1/24:1(15Z)) for the absolute quantification. We deployed it together with proteomics and transcriptomic analysis to assess the effects of cigarette smoke (CS) from the reference cigarette as well as aerosols from heat-not-burn (HnB) tobacco and e-vapor products in apolipoprotein E-deficient (ApoE^-/-) mice over several time points.

KEY FINDINGS

In the lungs, CS exposure substantially elevated the ratios of Cer(d18:1/24:0) and Cer(d18:1/24:1) to Cer(d18:1/18:0) in two independent ApoE^-/- mouse inhalation studies. Data from previous studies, in both ApoE^-/- and wild-type mice, further confirmed the reproducibility of this finding. Elevation of these ceramide ratios was also observed in plasma/serum, the liver, and-for the Cer(d18:1/24:1(15Z)) to Cer(d18:1/18:0) ratio-the abdominal aorta. Also, the levels of acid ceramidase (Asah1) and glucocerebrosidase (Gba)-lysosomal enzymes involved in the hydrolysis of glucosylceramides-were consistently elevated in the lungs after CS exposure. In contrast, exposure to HnB tobacco product and e-vapor aerosols did not induce significant changes in the ceramide profiles or associated enzymes.

SIGNIFICANCE

Our work in mice contributes to the accumulating evidence on the importance of ceramide ratios as biologically relevant markers for respiratory disorders, adding to their already demonstrated role in cardiovascular disease risk assessment in humans.

Quantitative proteomic comparison of myofibroblasts derived from bone marrow and cornea

Myofibroblasts are fibroblastic cells that function in wound healing, tissue repair and fibrosis, and arise from bone marrow (BM)-derived fibrocytes and a variety of local progenitor cells. In the cornea, myofibroblasts are derived primarily from stromal keratocytes and from BM-derived fibrocytes after epithelial-stromal and endothelial-stromal injuries. Quantitative proteomic comparison of mature alpha-smooth muscle actin (α-SMA)+ myofibroblasts (verified by immunocytochemistry for vimentin, α-SMA, desmin, and vinculin) generated from rabbit corneal fibroblasts treated with transforming growth factor (TGF) beta-1 or generated directly from cultured BM treated with TGF beta-1 was pursued for insights into possible functional differences. Paired cornea-derived and BM-derived α-SMA+ myofibroblast primary cultures were generated from four New Zealand white rabbits and confirmed to be myofibroblasts by immunocytochemistry. Paired cornea- and BM-derived myofibroblast specimens from each rabbit were analyzed by LC MS/MS iTRAQ technology using an Orbitrap Fusion Lumos Tribrid mass spectrometer, the Mascot search engine, the weighted average quantification method and the UniProt rabbit and human databases. From 2329 proteins quantified with ≥ 2 unique peptides from ≥ 3 rabbits, a total of 673 differentially expressed (DE) proteins were identified. Bioinformatic analysis of DE proteins with Ingenuity Pathway Analysis implicate progenitor-dependent functional differences in myofibroblasts that could impact tissue development. Our results suggest BM-derived myofibroblasts may be more prone to the formation of excessive cellular and extracellular material that are characteristic of fibrosis.

DEqMS: A Method for Accurate Variance Estimation in Differential Protein Expression Analysis

Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all data sets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several data sets including E. coli proteome spike-in data, using both label-free and TMT-labeled quantification. Compared with previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared with other statistical methods in both label-free and labeled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.

HyperQuant-A Computational Pipeline for Higher Order Multiplexed Quantitative Proteomics

Quantitative proteomics has evolved considerably over the last decade with the advent of higher order multiplexing (HOM) techniques. With the development of methods such as-multitagging, cPILOT, hyperplexing, BONPlex, and MITNCAT, the HOM technique is rapidly taking the center stage in multiplexed quantitative proteomics. These studies combined MS¹ and MS² labels in a single experiment enabling higher sample throughput. While HOM is highly promising, the computational analysis is still a big challenge, as the available tools cannot harness its power completely. We have developed a new quantitative pipeline, HyperQuant to aid in accurately quantitating complex HOM data. The pipeline uses identification results from either MaxQuant or any other search engine and quantitation results from QuantWiz^IQ. The Mapper and Combiner modules of HyperQuant allow facile integration of the labeled data, along with peptide spectrum match (PSM) intensity/ratio integration for proteins, respectively, for each PSM label combination. This also includes appropriate combination of replicates/fractions before summarizing the protein intensity/ratio, leading to robust quantitation. To the best of our knowledge, this is the first tool for the quantitation of HOM data with flexibility for any combination of MS¹ and MS² labels. We demonstrate its utility in analyzing two 18-plex data sets from the hyperplexing and the BONplex studies. The tool is open source and freely available for noncommercial use. HyperQuant is a highly valuable tool that will help in advancing the field of multiplexed quantitative proteomics.

Learning and Imputation for Mass-spec Bias Reduction (LIMBR)

MOTIVATION

Decreasing costs are making it feasible to perform time series proteomics and genomics experiments with more replicates and higher resolution than ever before. With more replicates and time points, proteome and genome-wide patterns of expression are more readily discernible. These larger experiments require more batches exacerbating batch effects and increasing the number of bias trends. In the case of proteomics, where methods frequently result in missing data this increasing scale is also decreasing the number of peptides observed in all samples. The sources of batch effects and missing data are incompletely understood necessitating novel techniques.

RESULTS

Here we show that by exploiting the structure of time series experiments, it is possible to accurately and reproducibly model and remove batch effects. We implement Learning and Imputation for Mass-spec Bias Reduction (LIMBR) software, which builds on previous block-based models of batch effects and includes features specific to time series and circadian studies. To aid in the analysis of time series proteomics experiments, which are often plagued with missing data points, we also integrate an imputation system. By building LIMBR for imputation and time series tailored bias modeling into one straightforward software package, we expect that the quality and ease of large-scale proteomics and genomics time series experiments will be significantly increased.

AVAILABILITY AND IMPLEMENTATION

Python code and documentation is available for download at https://github.com/aleccrowell/LIMBR and LIMBR can be downloaded and installed with dependencies using 'pip install limbr'.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

mRNA display with library of even-distribution reveals cellular interactors of influenza virus NS1

A comprehensive examination of protein-protein interactions (PPIs) is fundamental for the understanding of cellular machineries. However, limitations in current methodologies often prevent the detection of PPIs with low abundance proteins. To overcome this challenge, we develop a mRNA display with library of even-distribution (md-LED) method that facilitates the detection of low abundance binders with high specificity and sensitivity. As a proof-of-principle, we apply md-LED to IAV NS1 protein. Complementary to AP-MS, md-LED enables us to validate previously described PPIs as well as to identify novel NS1 interactors. We show that interacting with FASN allows NS1 to directly regulate the synthesis of cellular fatty acids. We also use md-LED to identify a mutant of NS1, D92Y, results in a loss of interaction with CPSF1. The use of high-throughput sequencing as the readout for md-LED enables sensitive quantification of interactions, ultimately enabling massively parallel experimentation for the investigation of PPIs.

Multi-omics systems toxicology study of mouse lung assessing the effects of aerosols from two heat-not-burn tobacco products and cigarette smoke

•

Multi-omics systems toxicology study, comprising five omics data modalities.

•

Multi-Omics Factor Analysis and multi-modality functional network interpretation.

•

Cigarettes smoke (CS) induced complex immunoregulatory interactions across molecular layers.

•

Aerosols from two heat-not-burn tobacco products had less impact on lungs than CS.

Cigarette smoke (CS) causes adverse health effects and, for smoker who do not quit, modified risk tobacco products (MRTPs) can be an alternative to reduce the risk of developing smoking-related diseases. Standard toxicological endpoints can lack sensitivity, with systems toxicology approaches yielding broader insights into toxicological mechanisms. In a 6-month systems toxicology study on ApoE^−/− mice, we conducted an integrative multi-omics analysis to assess the effects of aerosols from the Carbon Heated Tobacco Product (CHTP) 1.2 and Tobacco Heating System (THS) 2.2—a potential and a candidate MRTP based on the heat-not-burn (HnB) principle—compared with CS at matched nicotine concentrations. Molecular exposure effects in the lungs were measured by mRNA/microRNA transcriptomics, proteomics, metabolomics, and lipidomics. Integrative data analysis included Multi-Omics Factor Analysis and multi-modality functional network interpretation. Across all five data modalities, CS exposure was associated with an increased inflammatory and oxidative stress response, and lipid/surfactant alterations. Upon HnB aerosol exposure these effects were much more limited or absent, with reversal of CS-induced effects upon cessation and switching to CHTP 1.2. Functional network analysis revealed CS-induced complex immunoregulatory interactions across the investigated molecular layers (e.g., itaconate, quinolinate, and miR-146) and highlighted the engagement of the heme–Hmox–bilirubin oxidative stress axis by CS. This work exemplifies how multi-omics approaches can be leveraged within systems toxicology studies and the generated multi-omics data set can facilitate the development of analysis methods and can yield further insights into the effects of toxicological exposures on the lung of mice.

6-OH-BDE-47 exposure-induced Parkinson's disease pathology in Sprague Dawley rat

6-Hydroxy-BDE-47 (6-OH-BDE-47) is an important in vivo metabolite derived from 2,2',4,4'-tetrabromodiphenyl ether (BDE-47), a ubiquitous environmental pollutant. The chemical has been widely detected in environmental and biological samples. However, as a potential neurotoxin, whether 6-OH-BDE-47 could promote the development of typical neurodegenerative diseases such as Parkinson's disease (PD) is still unknown. Here, we tested the potential PD-related neurotoxic effect of 6-OH-BDE-47 in rat. The chemical with levels of 0.1, 1 and 10 µg was stereotaxically injected into the right midbrain regions of rat where contain abundant dopaminergic neurons. The resulting deteriorated motor function and decreased levels of striatal dopamine and nigrostriatal tyrosine hydroxylase indicate the dopaminergic neuron loss after the injection. Proteomics study revealed that protein degradation pathways were affected. Western blot analysis confirmed that 6-OH-BDE-47 could inhibit ubiquitination and autophagy, resulting in the increased formation of α-synuclein (α-syn) aggregate, an important pathological hallmark of PD. Overall, our study demonstrated that the 6-OH-BDE-47 administration could induce motor defect by impairing dopaminergic system and promote α-syn aggregation by inhibiting ubiquitination and autophagy, suggesting that the occurrence of 6-OH-BDE-47 in brain could be a risk for developing PD.

The depressed P cycle contributes to the acquisition of ampicillin resistance in Edwardsiella piscicida

Antibiotic-resistant bacteria are an increasingly serious threat to human health and aquaculture. To further explore bacterial antibiotic resistance mechanism, iTRAQ is used to identify a differential proteome in ampicillin-resistant LTB4 (LTB4-R_AMP), a strain of Edwardsiella piscicida. A total of 102 differentially proteins with 50 upregulation and 52 downregulation are identified. Since many of these changes are related to metabolism, interactive pathways explorer(iPath) is used to understand a global differentially metabolic response in LTB4-R_AMP. This analysis identifies a global depressed metabolic modulation as the most characteristic feature of LTB4-R_AMP. Lower membrane potential and ATP in LTB4-R_AMP than control support that the central carbon metabolism and energy metabolism are reduced. Since the pyruvate cycle (the P cycle) plays a key role in the central carbon metabolism and energy metabolism, further investigation focuses on the P cycle and shows that expression of genes and activity of enzymes in the P cycle are decreased in LTB4-R_AMP. These results support the conclusion that the depressed P cycle contributes to the acquisition of ampicillin resistance in E.piscicida. These findings indicate that the combination of proteomics and iPath analysis can provide a global metabolic profile, which helps us better understand the correlation between ampicillin resistance and cellular metabolism. SIGNIFICANCE: The present study uses iTRAQ to explore ampicillin resistance mechanism in Edwardsiella piscicida and finds many of these differential abundances of proteins are related to metabolism. IPath further identifies a global depressed metabolic modulation and characterizes the reduced pyruvate cycle as the most characteristic feature of the ampicillin-resistant E. piscicida, which is supported by reduced expression of genes and activity of enzymes in the pyruvate cycle. Consisitently, lower membrane potential and ATP are detetced. These results reveal the metabolic mechanism of ampicillin resistance and provide a solid proof to revert the resistance by reprogramming metabolomics.

Study of BDE-47 induced Parkinson's disease-like metabolic changes in C57BL/6 mice by integrated metabolomic, lipidomic and proteomic analysis

As the predominant congener of polybrominated diphenyl ethers (PBDEs) detected in human serum, 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) has been reported to induce neurotoxicity. However, the possible linkage between BDE-47 and typical neurodegenerative diseases such as Parkinson's disease (PD) is still unclear. Here we carried out omics studies using liquid chromatography-orbitrap mass spectrometry (LC-orbitrap MS) to depict the BDE-47 induced metabolic changes in C57BJ/L mice to explore the possible contribution of BDE-47 exposure to PD pathology. BDE-47 dissolved in corn oil was orally administered to mice for 30 consecutive days. Results of metabolomics and lipidomics studies of PD-related brain regions revealed significant metabolite changes in pathways involved in oxidative stress and neurotransmitter production. Moreover, isobaric tags for relative and absolute quantitation (iTRAQ) proteomics study of the striatum, which is the part of brain that is most intensively studied in PD pathogenesis, revealed that BDE-47 could induce neurotransmitter system disturbance, abnormal phosphorylation, mitochondrial dysfunction and oxidative stress. Overall, this study depicts the possible contribution of BDE-47 exposure to PD pathology and highlights the powerfulness of omics platforms to deepen the mechanistic understanding of environmental pollutant-caused toxicity.

Sum of peak intensities outperforms peak area integration in iTRAQ protein expression measurement by LC-MS/MS using a TripleTOF 5600+ platform

In the field of quantitative proteomics, the Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) technology has demonstrated efficacy for proteome monitoring despite its lack of a consensus for data handling. In the present study, after peptide and protein identification, we compared the widespread quantitation method based on the calculation of MS/MS reporter ion peaks areas ratios (ProteinPilot) to the alternative method based on the calculation of ratios of the sum of peak intensities (jTRAQx [Quant]) and we processed output data with the in-house Customizable iTRAQ Ratios Calculator (CiR-C) algorithm. Quantitation based on peak area ratios displayed no significant linear correlation with Western blot quantitation. In contrast, quantitation based on the sum of peak intensities displayed a significant linear association with Western blot quantitation (non-zero slope; Pearson correlation coefficient test, r = 0.296, P=0.010**) with an average bias of 0.087 ± 0.500 and 95% Limits of Agreement from −0.893 to 1.068. We proposed the Mascot-jTRAQx-CiR-C strategy as a simple yet powerful data processing adjunct to the iTRAQ technology.

Quantitative Early Auxin Root Proteomics Identifies GAUT10, a Galacturonosyltransferase, as a Novel Regulator of Root Meristem Maintenance

Auxin induces rapid gene expression changes throughout root development. How auxin-induced transcriptional responses relate to changes in protein abundance is not well characterized. This report identifies early auxin responsive proteins in roots at 30 min and 2 h after hormone treatment using a quantitative proteomics approach in which 3,514 proteins were reliably quantified. A comparison of the >100 differentially expressed proteins at each the time point showed limited overlap, suggesting a dynamic and transient response to exogenous auxin. Several proteins with established roles in auxin-mediated root development exhibited altered abundance, providing support for this approach. While novel targeted proteomics assays demonstrate that all six auxin receptors remain stable in response to hormone. Additionally, 15 of the top responsive proteins display root and/or auxin response phenotypes, demonstrating the validity of these differentially expressed proteins. Auxin signaling in roots dictates proteome reprogramming of proteins enriched for several gene ontology terms, including transcription, translation, protein localization, thigmatropism, and cell wall modification. In addition, we identified auxin-regulated proteins that had not previously been implicated in auxin response. For example, genetic studies of the auxin responsive protein galacturonosyltransferase 10 demonstrate that this enzyme plays a key role in root development. Altogether these data complement and extend our understanding of auxin response beyond that provided by transcriptome studies and can be used to uncover novel proteins that may mediate root developmental programs.

A Review on Quantitative Multiplexed Proteomics

Over the last few decades, mass spectrometry-based proteomics has become an increasingly powerful tool that is now able to routinely detect and quantify thousands of proteins. A major advance for global protein quantification was the introduction of isobaric tags, which, in a single experiment, enabled the global quantification of proteins across multiple samples. Herein, these methods are referred to as multiplexed proteomics. The principles, advantages, and drawbacks of various multiplexed proteomics techniques are discussed and compared with alternative approaches. We also discuss how the emerging combination of multiplexing with targeted proteomics might enable the reliable and high-quality quantification of very low abundance proteins across multiple conditions. Lastly, we suggest that fusing multiplexed proteomics with data-independent acquisition approaches might enable the comparison of hundreds of different samples without missing values, while maintaining the superb measurement precision and accuracy obtainable with isobaric tag quantification.

Interleukin-1 in cerebrospinal fluid for evaluating the neurological outcome in traumatic brain injury

Objective Severe traumatic brain injury (TBI) is associated with unfavorable outcomes secondary to injury from activation of the inflammatory cascade, the release of excitotoxic neurotransmitters, and changes in the reactivity of cerebral vessels, causing ischemia. Inflammation induced by TBI is complex, individual-specific, and associated with morbidity and mortality. The aim of the present study was to discover the differentially expressed cerebrospinal fluid (CSF) proteins and identify which can improve the clinical outcomes in TBI patients.

Methods In the present study, we reported 145 patients with TBI and found the change in patients’ leukocytes in serum and interleukin-1 (IL-1) in CSF, which strongly correlated with the neurological outcome. In terms of results of leukocytes in blood and IL-1 in CSF, we retained the patient’s CSF specimens and conducted a proteomic analysis.

Results A total of 119 differentially expressed proteins were detected between samples of TBI and the normal, which were commonly expressed in all samples, indicating the differentially expressed proteins. When the patients’ Glasgow outcome score (GOS) improved, IL-1 was down-regulated, and when the patients’ GCS score deteriorated, IL-1 was up-regulated accompanied with the progression in TBI.

Conclusion The differentially expressed proteins in CSF may be the novel therapeutic targets for TBI treatment. The leukocytes in blood samples and the IL-1 in CSF may be two important indicators for predicting the prognosis of TBI patients.

iTRAQ-Based Quantitative Proteomic Analysis Reveals Proteomic Changes in Mycelium of Pleurotus ostreatus in Response to Heat Stress and Subsequent Recovery

High temperature is a key limiting factor for mycelium growth and development in Pleurotus ostreatus. Thermotolerance includes the direct response to heat stress and the ability to recover from heat stress. To better understand the mechanism of thermotolerance in P. ostreatus, we used morphological and physiological analysis combined with an iTRAQ-based proteomics analysis of P. ostreatus subjected to 40°C for 48 h followed by recovery at 25°C for 3 days. High temperature increased the concentrations of thiobarbituric acid reactive substances (TBARS) indicating that the mycelium of P. ostreatus were damaged by heat stress. However, these physiological changes rapidly returned to control levels during the subsequent recovery phase from heat stress. In comparison to unstressed controls, a total of 204 proteins were changed during heat stress and/or the recovery phase. Wherein, there were 47 proteins that responded to both stress and recovery conditions, whereas 84 and 73 proteins were responsive to only heat stress or recovery conditions, respectively. Furthermore, quantitative real-time PCR (qRT-PCR) confirmed differential expression of nine candidate genes revealed that some of the proteins, such as a mitogen-activated protein kinase (MAPK), phenylalanine ammonia-lyase (PAL), and heat shock protein (HSP), were also regulated by heat stress at the level of transcription. These differentially expressed proteins (DEPs) in mycelium of P. ostreatus under heat stress were from 13 biological processes. Moreover, protein-protein interaction analysis revealed that proteins involved in carbohydrate and energy metabolism, signal transduction, and proteins metabolism could be assigned to three heat stress response networks. On the basis of these findings, we proposed that effective regulatory protein expression related to MAPK-pathway, antioxidant enzymes, HSPs, and other stress response proteins, and glycolysis play important roles in enhancing P. ostreatus adaptation to and recovery from heat stress. Of note, this study provides useful information for understanding the thermotolerance mechanism for basidiomycetes.

A 90-day OECD TG 413 rat inhalation study with systems toxicology endpoints demonstrates reduced exposure effects of the aerosol from the carbon heated tobacco product version 1.2 (CHTP1.2) compared with cigarette smoke. II. Systems toxicology assessment

Modified risk tobacco products (MRTPs) have the potential to reduce smoking-related health risks. The Carbon Heated Tobacco Product 1.2 (CHTP1.2) is a potential MRTP that uses a pressed carbon heat source to generate an aerosol by heating tobacco. Here, we report the results from the systems toxicology arm of a 90-day rat inhalation study (OECD test guideline 413) to assess the effects of CHTP1.2 aerosol compared with cigarette smoke (CS). Transcriptomics, proteomics, and lipidomics analyses complemented the standard endpoints. In the respiratory nasal epithelium, CS induced an adaptive tissue and inflammatory response, which was much weaker after CHTP1.2 aerosol exposure, mostly limited to the highest CHTP1.2 concentration (at twice the 3R4F CS concentration: 50 vs. 23 μg nicotine/L), in female rats. In the lungs, the effects of CS exposure included inflammatory and cellular stress responses, which were absent or much lower after CHTP1.2 aerosol exposure. Outside of the respiratory tract, CS and CHTP1.2 aerosol induced effects that were previously associated with exposure to any nicotine-containing aerosol, e.g., lower lipid concentrations in serum. Overall, this systems toxicology analysis complements and confirms the results from classical toxicological endpoints and further suggests potentially reduced respiratory health risks of CHTP1.2.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assess the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we derived a quantification confidence score based on the quality of each peptide-spectrum match to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS data sets collected over a 7-month period. This study provides the first quality assessment on long-term stability and technical considerations for study design of a large-scale clinical proteomics project.

Comparative systems toxicology analysis of cigarette smoke and aerosol from a candidate modified risk tobacco product in organotypic human gingival epithelial cultures: A 3-day repeated exposure study

Smoking is one of the major lifestyle-related risk factors for periodontal diseases. Modified risk tobacco products (MRTP) offer a promising alternative in the harm reduction strategy for adult smokers unable to quit. Using a systems toxicology approach, we investigated and compared the exposure effects of a reference cigarette (3R4F) and a heat-not-burn technology-based candidate MRTP, the Tobacco Heating System (THS) 2.2. Human gingival epithelial organotypic cultures were repeatedly exposed (3 days) for 28 min at two matching concentrations of cigarette smoke (CS) or THS2.2 aerosol. Results showed only minor histopathological alterations and minimal cytotoxicity upon THS2.2 aerosol exposure compared to CS (1% for THS2.2 aerosol vs. 30% for CS, at the high concentration). Among the 14 proinflammatory mediators analyzed, only 5 exhibited significant alterations with THS2.2 exposure compared with 11 upon CS exposure. Transcriptomic and metabolomic analysis indicated a general reduction of the impact in THS2.2 aerosol-exposed samples with respect to CS (∼79% lower biological impact for the high THS2.2 aerosol concentration compared to CS, and 13 metabolites significantly perturbed for THS2.2 vs. 181 for CS). This study indicates that exposure to THS2.2 aerosol had a lower impact on the pathophysiology of human gingival organotypic cultures than CS.

Quantitative proteomic analysis exploring progression of colorectal cancer: Modulation of the serpin family

Colorectal cancer (CRC) remains a major cause of cancer related-death in developed countries. The mortality risk is correlated with the stage of CRC determined at the primary diagnosis and early diagnosis is associated with enhanced survival rate. Currently, only faecal occult blood tests are used to screen for CRC. Consequently, there is an incentive to identify specific markers of CRC. We used quantitative proteomic analysis of serum samples to characterize protein profiles in adenoma, CRC and healthy control samples. We identified 89 distinct proteins modulated between normal, colorectal adenoma and carcinoma patients. This list emphasizes proteins involved in enzyme regulator activities and in particular the serpin family. In serum samples, protein profiles of three members of the serpin family (SERPINA1, SERPINA3 and SERPINC1) were confirmed by ELISA assays. We obtained sensitivity/specificity values of 95%/95% for both SERPINA1 and SERPINC1, and 95%/55% for SERPINA3. This study supports the idea that serum proteins can discriminate adenoma and CRC patients from unaffected patients and reveals a panel of regulated proteins that might be useful for selecting patients for colonoscopy. By evaluating SERPINA1, SERPINA3 and SERPINC1, we highlight the potential role of the serpin family during the development and progression of CRC.

SIGNIFICANCE

Colorectal cancer (CRC) remains a major cause of cancer mortality throughout the world. However, very few CRC biomarkers have satisfactory sensitivity and specificity in clinical practice. To the best of our knowledge our study is the first to profile sera proteomes between adenoma, CRC and healthy patients. We report a comprehensive list of proteins that may be used as early diagnostic biomarkers of CRC. It is noteworthy that 17% of these modulated proteins have been previously described as candidate biomarkers in CRC. Enzyme regulator activity was found to be the main molecular function among these proteins and, in particular, there was an enrichment of members of the serpin family. The subsequent verification on a new cohort by ELISA demonstrates that these serpins could be useful to discriminate healthy from colorectal carcinoma patients with a high sensitivity and specificity. The combination of these biomarkers should increase predictive powers of CRC diagnosis. The remaining candidates form a reserve for further evaluation of additional biomarkers for CRC diagnosis.

Comprehensive Proteomic Analysis of Mesenchymal Stem Cell Exosomes Reveals Modulation of Angiogenesis via Nuclear Factor-KappaB Signaling

Mesenchymal stem cells (MSC) are known to facilitate healing of ischemic tissue related diseases through proangiogenic secretory proteins. Recent studies further show that MSC derived exosomes function as paracrine effectors of angiogenesis, however, the identity of which components of the exosome proteome responsible for this effect remains elusive. To address this we used high-resolution isoelectric focusing coupled liquid chromatography tandem mass spectrometry, an unbiased high throughput proteomics approach to comprehensively characterize the proteinaceous contents of MSCs and MSC derived exosomes. We probed the proteome of MSCs and MSC derived exosomes from cells cultured under expansion conditions and under ischemic tissue simulated conditions to elucidate key angiogenic paracrine effectors present and potentially differentially expressed in these conditions. In total, 6,342 proteins were identified in MSCs and 1,927 proteins in MSC derived exosomes, representing to our knowledge the first time these proteomes have been probed comprehensively. Multilayered analyses identified several putative paracrine effectors of angiogenesis present in MSC exosomes and increased in expression in MSCs exposed to ischemic tissue-simulated conditions; these include platelet derived growth factor, epidermal growth factor, fibroblast growth factor, and most notably nuclear factor-kappaB (NFkB) signaling pathway proteins. NFkB signaling was identified as a key mediator of MSC exosome induced angiogenesis in endothelial cells by functional in vitro validation using a specific inhibitor. Collectively, the results of our proteomic analysis show that MSC derived exosomes contain a robust profile of angiogenic paracrine effectors, which have potential for the treatment of ischemic tissue-related diseases.

Sensing Small Changes in Protein Abundance: Stimulation of Caco-2 Cells by Human Whey Proteins

Mass spectrometry (MS)-based proteomic approaches have largely facilitated our systemic understanding of cellular processes and biological functions. Cutoffs in protein expression fold changes (FCs) are often arbitrarily determined in MS-based quantification with no demonstrable determination of small magnitude changes in protein expression. Therefore, many biological insights may remain veiled due to high FC cutoffs. Herein, we employ the intestinal epithelial cell (IEC) line Caco-2 as a model system to demonstrate the dynamicity of tandem-mass-tag (TMT) labeling over a range of 5-40% changes in protein abundance, with the variance controls of ± 5% FC for around 95% of TMT ratios when sampling 9-12 biological replicates. We further applied this procedure to examine the temporal proteome of Caco-2 cells upon exposure to human whey proteins (WP). Pathway assessments predict subtle effects due to WP in moderating xenobiotic metabolism, promoting proliferation and various other cellular functions in differentiating enterocyte-like Caco-2 cells. This demonstration of a sensitive MS approach may open up new perspectives in the system-wide exploration of elusive or transient biological effects by facilitating scrutiny of narrow windows of proteome abundance changes. Furthermore, we anticipate this study will encourage more investigations of WP on infant gastrointestinal tract development.

iPQF: a new peptide-to-protein summarization method using peptide spectra characteristics to improve protein quantification

MOTIVATION

Isobaric labelling techniques such as iTRAQ and TMT are popular methods for relative protein abundance estimation in proteomic studies. However, measurements are assessed at the peptide spectrum level and exhibit substantial heterogeneity per protein. Hence, clever summarization strategies are required to infer protein ratios. So far, current methods rely exclusively on quantitative values, while additional information on peptides is available, yet it is not considered in these methods.

METHODS

We present iPQF ( I: sobaric P: rotein Q: uantification based on F: eatures) as a novel peptide-to-protein summarization method, which integrates peptide spectra characteristics as well as quantitative values for protein ratio estimation. We investigate diverse features characterizing spectra reliability and reveal significant correlations to ratio accuracy in spectra. As a result, we developed a feature-based weighting of peptide spectra.

RESULTS

A performance evaluation of iPQF in comparison to nine different protein ratio inference methods is conducted on five published MS2 and MS3 datasets with predefined ground truth. We demonstrate the benefit of using peptide feature information to improve protein ratio estimation. Compared to purely quantitative approaches, our proposed strategy achieves increased accuracy by addressing peptide spectra reliability.

AVAILABILITY AND IMPLEMENTATION

The iPQF algorithm is available within the established R/Bioconductor package MSnbase (version ≥ 1.17.8).

CONTACT

renardB@rki.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

iTRAQ as a method for optimization: enhancing peptide recovery after gel fractionation

At the dawn of a new era in label-free quantitation on high-resolution MS instruments, classical methods such as iTRAQ continue to provide very useful insights in comparative proteomics. The potential to multiplex samples makes this reporter-based labeling technique highly suited for method optimization as demonstrated here by a set of standard series. Instead of studying ratios of annotated proteins, we propose an alternative method, based on the analysis of the average reporter ratios of all the spectra from a sample or a large distinct subset herein. This strategy circumvents the bias, associated with the annotation and iTRAQ quantitation, leading to increased adequacy in measuring yield differences between workflows. As gel electrophoresis prior to MS analysis is highly beneficial, for example, as a fractionation step, the approach was applied to evaluate the influence of several parameters of the established in-gel digestion protocol. We quantified the negative effect of SYPRO Ruby staining and the positive effect of gel fixation prior to digestion on peptide yield. Finally, we emphasize the benefits of adding CaCl2 and ACN to a tryptic in-gel digest, resulting in an up to tenfold enhanced peptide recovery and fewer trypsin missed cleavages.