Relative Protein Quantification Research Articles

A Mass Spectrometry Strategy for Protein Quantification Based on the Differential Alkylation of Cysteines Using Iodoacetamide and Acrylamide.

Mass spectrometry has become the most prominent yet evolving technology in quantitative proteomics. Today, a number of label-free and label-based approaches are available for the relative and absolute quantification of proteins and peptides. However, the label-based methods rely solely on the employment of stable isotopes, which are expensive and often limited in availability. Here we propose a label-based quantification strategy, where the mass difference is identified by the differential alkylation of cysteines using iodoacetamide and acrylamide. The alkylation reactions were performed under identical experimental conditions; therefore, the method can be easily integrated into standard proteomic workflows. Using high-resolution mass spectrometry, the feasibility of this approach was assessed with a set of tryptic peptides of human serum albumin. Several critical questions, such as the efficiency of labeling and the effect of the differential alkylation on the peptide retention and fragmentation, were addressed. The concentration of the quality control samples calculated against the calibration curves were within the ±20% acceptance range. It was also demonstrated that heavy labeled peptides exhibit a similar extraction recovery and matrix effect to light ones. Consequently, the approach presented here may be a viable and cost-effective alternative of stable isotope labeling strategies for the quantification of cysteine-containing proteins.

The Effects of Artificial Diets on the Expression of Molecular Marker Genes Related to Honey Bee Health.

Honey bees are commonly used to study metabolic processes, yet the molecular mechanisms underlying nutrient transformation, particularly proteins and their effects on development, health, and diseases, still evoke varying opinions among researchers. To address this gap, we investigated the digestibility and transformation of water-soluble proteins from four artificial diets in long-lived honey bee populations (Apis mellifera ligustica), alongside their impact on metabolism and DWV relative expression ratio, using transcriptomic and protein quantification methods. Diet 2, characterized by its high protein content and digestibility, was selected for further analysis from the other studied diets. Subsequently, machine learning was employed to identify six diet-related molecular markers: SOD1, Trxr1, defensin2, JHAMT, TOR1, and vg. The expression levels of these markers were found to resemble those of honey bees who were fed with Diet 2 and bee bread, renowned as the best natural food. Notably, honey bees exhibiting chalkbrood symptoms (Control-N) responded differently to the diet, underscoring the unique nutritional effects on health-deficient bees. Additionally, we proposed a molecular model to elucidate the transition of long-lived honey bees from diapause to development, induced by nutrition. These findings carry implications for nutritional research and beekeeping, underscoring the vital role of honey bees in agriculture.

ProTInSeq: transposon insertion tracking by ultra-deep DNA sequencing to identify translated large and small ORFs

Identifying open reading frames (ORFs) being translated is not a trivial task. ProTInSeq is a technique designed to characterize proteomes by sequencing transposon insertions engineered to express a selection marker when they occur in-frame within a protein-coding gene. In the bacterium Mycoplasma pneumoniae, ProTInSeq identifies 83% of its annotated proteins, along with 5 proteins and 153 small ORF-encoded proteins (SEPs; ≤100 aa) that were not previously annotated. Moreover, ProTInSeq can be utilized for detecting translational noise, as well as for relative quantification and transmembrane topology estimation of fitness and non-essential proteins. By integrating various identification approaches, the number of initially annotated SEPs in this bacterium increases from 27 to 329, with a quarter of them predicted to possess antimicrobial potential. Herein, we describe a methodology complementary to Ribo-Seq and mass spectroscopy that can identify SEPs while providing other insights in a proteome with a flexible and cost-effective DNA ultra-deep sequencing approach.

Temporal Quantitative Proteomic and Phosphoproteomic Profiling of SH-SY5Y and IMR-32 Neuroblastoma Cells during All-Trans-Retinoic Acid-Induced Neuronal Differentiation.

The human neuroblastoma cell lines SH-SY5Y and IMR-32 can be differentiated into neuron-like phenotypes through treatment with all-trans-retinoic acid (ATRA). After differentiation, these cell lines are extensively utilized as in vitro models to study various aspects of neuronal cell biology. However, temporal and quantitative profiling of the proteome and phosphoproteome of SH-SY5Y and IMR-32 cells throughout ATRA-induced differentiation has been limited. Here, we performed relative quantification of the proteomes and phosphoproteomes of SH-SY5Y and IMR-32 cells at multiple time points during ATRA-induced differentiation. Relative quantification of proteins and phosphopeptides with subsequent gene ontology analysis revealed that several biological processes, including cytoskeleton organization, cell division, chaperone function and protein folding, and one-carbon metabolism, were associated with ATRA-induced differentiation in both cell lines. Furthermore, kinase-substrate enrichment analysis predicted altered activities of several kinases during differentiation. Among these, CDK5 exhibited increased activity, while CDK2 displayed reduced activity. The data presented serve as a valuable resource for investigating temporal protein and phosphoprotein abundance changes in SH-SY5Y and IMR-32 cells during ATRA-induced differentiation.

Exoproteome analysis of Pseudomonas aeruginosa response to high alkane stress.

Microbial biodegradation serves as an effective approach to treat oil pollution. However, the application of such methods for the degrading long-chain alkanes still encounters significant challenges. Comparative proteomics has extensively studied the intracellular proteins of bacteria that degrade short- and medium-chain alkanes, but the role and mechanism of extracellular proteins in many microorganism remain unclear. To enhance our understanding of the roles of extracellular proteins in the adaptation to long-chain alkanes, a label-free LC-MS/MS strategy was applied for the relative quantification of extracellular proteins of Pseudomonas aeruginosa SJTD-1-M (ProteomeXchange identifier PXD014638). 444 alkane-sentitive proteins were acquired and their cell localization analysis was performed using the Pseudomonas Genome Database. Among them, 111 proteins were found to be located in extracellular or Outer Membrane Vesicles (OMVs). The alkane-induced abundance of 11 extracellular or OMV target proteins was confirmed by parallel reaction monitoring (PRM). Furthermore, we observed that the expression levels of three proteins (Pra, PA2815, and FliC) were associated with the carbon chain length of the added alkane in the culture medium. The roles of these proteins in cell mobility, alkane emulsification, assimilation, and degradation were further discussed. OMVs were found to contain a number of enzymes involved in alkane metabolism, fatty acid beta-oxidation, and the TCA cycle, suggesting their potential as sites for facilitated alkane degradation. In this sense, this exoproteome analysis contributes to a better understanding of the role of extracellular proteins in the hydrocarbon treatment process.

Identification of Differentially Expressed Proteins in Rats with Early Subacute Spinal Cord Injury using an iTRAQ-based Quantitative Analysis.

Injuries to the central nervous system (CNS), such as spinal cord injury (SCI), may devastate families and society. Subacute SCI may majorly impact secondary damage during the transitional period between the acute and subacute phases. A range of CNS illnesses has been linked to changes in the level of protein expression. However, the importance of proteins during the early subacute stage of SCI remains unknown. The role of proteins in the early subacute phase of SCI has not been established yet. SCI-induced damage in rats was studied using isobaric tagging for relative and absolute protein quantification (iTRAQ) to identify proteins that differed in expression 3 days after the injury, as well as proteins that did not alter in expression. Differentially expressed proteins (DEPs) were analyzed employing Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to discover the biological processes, cell components, and molecular functions of the proteins. We also performed Gene Set Enrichment Analysis (GSEA) software BP pathway and KEGG analysis on all proteins to further identify their functions. In addition, the first 15 key nodes of a protein-protein interaction (PPI) system were found. During the early subacute stage of SCI, we identified 176 DEPs in total between the control and damage groups, with 114 (64.77%) being up-regulated and 62 (35.23%) being downregulated. As a result of this study, we discovered the most important cellular components and molecular activities, as well as biological processes and pathways, in the early subacute phase of SCI. The top 15 high-degree core nodes were Alb, Plg, F2, Serpina1, Fgg, Apoa1, Vim, Hpx, Apoe, Agt, Ambp, Pcna, Gc, F12, and Gfap. Our study could provide new views on regulating the pathogenesis of proteins in the early subacute phase after SCI, which provides a theoretical basis for exploring more effective therapeutic targets for SCI in the future.

Tissue-based absolute quantification using large-scale TMT and LFQ experiments.

Relative and absolute intensity-based protein quantification across cell lines, tissue atlases and tumour datasets is increasingly available in public datasets. These atlases enable researchers to explore fundamental biological questions, such as protein existence, expression location, quantity and correlation with RNA expression. Most studies provide MS1 feature-based label-free quantitative (LFQ) datasets; however, growing numbers of isobaric tandem mass tags (TMT) datasets remain unexplored. Here, we compare traditional intensity-based absolute quantification (iBAQ) proteome abundance ranking to an analogous method using reporter ion proteome abundance ranking with data from an experiment where LFQ and TMT were measured on the same samples. This new TMT method substitutes reporter ion intensities for MS1 feature intensities in the iBAQ framework. Additionally, we compared LFQ-iBAQ values to TMT-iBAQ values from two independent large-scale tissue atlas datasets (one LFQ and one TMT) using robust bottom-up proteomic identification, normalisation and quantitation workflows.

Statistical Detection of Differentially Abundant Proteins in Experiments with Repeated Measures Designs and Isobaric Labeling.

Repeated measures experimental designs, which quantify proteins in biological subjects repeatedly over multiple experimental conditions or times, are commonly used in mass spectrometry-based proteomics. Such designs distinguish the biological variation within and between the subjects and increase the statistical power of detecting within-subject changes in protein abundance. Meanwhile, proteomics experiments increasingly incorporate tandem mass tag (TMT) labeling, a multiplexing strategy that gains both relative protein quantification accuracy and sample throughput. However, combining repeated measures and TMT multiplexing in a large-scale investigation presents statistical challenges due to unique interplays of between-mixture, within-mixture, between-subject, and within-subject variation. This manuscript proposes a family of linear mixed-effects models for differential analysis of proteomics experiments with repeated measures and TMT multiplexing. These models decompose the variation in the data into the contributions from its sources as appropriate for the specifics of each experiment, enable statistical inference of differential protein abundance, and recognize a difference in the uncertainty of between-subject versus within-subject comparisons. The proposed family of models is implemented in the R/Bioconductor package MSstatsTMT v2.2.0. Evaluations of four simulated datasets and four investigations answering diverse biological questions demonstrated the value of this approach as compared to the existing general-purpose approaches and implementations.

How the West(ern) was won: Solutions for immunoblotting large and small proteins

Relative protein quantification is a well-established technique in the vast majority of molecular biology laboratories. However, western blot standard protocols may not detect proteins of certain sizes. When the molecular weight of protein of interest is out of the 10–250 kDa range, its migration through the gel or transfer to the membrane is compromised, making its detection difficult. Here, we present a set of modifications of the standard working procedure for western blotting based on the experience working with small VCP-interacting protein and MAX-gene-associated protein, whose molecular weights are 8 and 350 kDa, respectively. We expect that these adaptations may help researchers to improve their experiments in a cost-effective manner.

Proteomic-based identification of APCS as candidate protein for diagnosis of patients exhibiting anti-tubercular drug induced liver injury

Traditional markers evaluate anti-tubercular drug-induced liver injury (AT-DILI). However, these markers have certain limitations and studies are in progress to characterize AT-DILI at an early stage. In the present study, 40 patients were categorized and equally distributed into healthy controls, newly diagnosed tuberculosis (TB), TB without hepatotoxicity and TB with hepatotoxicity groups based on their conventional liver function tests. Relative protein quantification was performed on depleted pooled serum samples of each representative group by LC–MS/MS, and validation of shortlisted protein was done by ELISA. Levels of all analysed biochemical parameters showed a statistical increment in the hepatotoxicity group compared to the other three groups, representing AT-DILI. Comparative proteomic analysis between TB with hepatotoxicity versus TB without hepatotoxicity groups highlighted 24 significant differentially expressed proteins, including PROS1, KNG1, CFH, LCAT, APCS and ADIPOQ. Identified proteins were involved in complement activation, triglyceride-rich lipoprotein particle remodelling and pathways comprising complement, coagulation cascades and cholesterol metabolism. Based on functional relevance, the serum amyloid P component (APCS) was shortlisted for validation, and it showed a similar trend as observed in the discovery phase with 100% sensitivity and 87% specificity; however, findings need exploration in larger cohorts.

Quantitative Mass Spectrometry Analysis of Cerebrospinal Fluid Protein Biomarkers in Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common form of dementia, with cerebrospinal fluid (CSF) β-amyloid (Aβ), total Tau, and phosphorylated Tau (pTau) providing the most sensitive and specific biomarkers for diagnosis. However, these diagnostic biomarkers do not reflect the complex changes in AD brain beyond amyloid (A) and Tau (T) pathologies. Here, we report a selected reaction monitoring mass spectrometry (SRM-MS) method with isotopically labeled standards for relative protein quantification in CSF. Biomarker positive (AT+) and negative (AT−) CSF pools were used as quality controls (QCs) to assess assay precision. We detected 62 peptides (51 proteins) with an average coefficient of variation (CV) of ~13% across 30 QCs and 133 controls (cognitively normal, AT−), 127 asymptomatic (cognitively normal, AT+) and 130 symptomatic AD (cognitively impaired, AT+). Proteins that could distinguish AT+ from AT− individuals included SMOC1, GDA, 14-3-3 proteins, and those involved in glycolysis. Proteins that could distinguish cognitive impairment were mainly neuronal proteins (VGF, NPTX2, NPTXR, and SCG2). This demonstrates the utility of SRM-MS to quantify CSF protein biomarkers across stages of AD.

Prolfqua: A Comprehensive R-Package for Proteomics Differential Expression Analysis

Mass spectrometry is widely used for quantitative proteomics studies, relative protein quantification, and differential expression analysis of proteins. There is a large variety of quantification software and analysis tools. Nevertheless, there is a need for a modular, easy-to-use application programming interface in R that transparently supports a variety of well principled statistical procedures to make applying them to proteomics data, comparing and understanding their differences easy. The prolfqua package integrates essential steps of the mass spectrometry-based differential expression analysis workflow: quality control, data normalization, protein aggregation, statistical modeling, hypothesis testing, and sample size estimation. The package makes integrating new data formats easy. It can be used to model simple experimental designs with a single explanatory variable and complex experiments with multiple factors and hypothesis testing. The implemented methods allow sensitive and specific differential expression analysis. Furthermore, the package implements benchmark functionality that can help to compare data acquisition, data preprocessing, or data modeling methods using a gold standard data set. The application programmer interface of prolfqua strives to be clear, predictable, discoverable, and consistent to make proteomics data analysis application development easy and exciting. Finally, the prolfqua R-package is available on GitHub https://github.com/fgcz/prolfqua, distributed under the MIT license. It runs on all platforms supported by the R free software environment for statistical computing and graphics.

No-stain protein labeling as a potential normalization marker for small extracellular vesicle proteins

Western blot analysis of relative protein expression relies on appropriate reference proteins for data normalization. Small extracellular vesicles (sEVs), or exosomes, are increasingly recognized as potential indicators of the physiological state of cells due to their protein composition. Therefore, accurate relative sEVs protein quantification is crucial for disease detection and prognosis applications. Currently, no documented ubiquitous reference proteins are identified for precise normalization of a protein of interest in sEVs. Here we showed the use of total protein staining method for sEVs protein normalization in western blots of samples where conventional housekeeping proteins like β-actin and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) are not always detected in the sEVs western blots. The No-Stain™ Protein Labeling (NSPL) method showed high sensitivity in sEVs-protein labeling and facilitated quantitative evaluation of changes in the expression pattern of the protein of interest. Further, to show the robustness of NSPL for expression analysis, the results were compared with quantitative mass spectroscopy analysis results. Here, we outline a comprehensive method for protein normalization in sEVs that will increase the value of protein expression study of therapeutically significant sEVs.

Super-SILAC Quantitative Proteome Profiling of Zebrafish Larvae.

The super-SILAC approach enables the quantitative proteome profiling of highly complex samples such as biological tissues or whole organisms. In this approach, a super-SILAC mix consisting of heavy isotope-labeled cells representative of the tissue or organism to be analyzed is mixed with the unlabeled samples of interest, such that the labeled proteins act as a spike-in standard, thus allowing the relative quantification of proteins between the samples of interest. In this chapter, we thoroughly describe the protocol to carry out the super-SILAC approach using a common in vivo model such as zebrafish larvae.

Increased levels of cell wall degrading enzymes and peptidases are associated with aggressiveness in a virulent isolate of Pyrenophora teres f. maculata

Pyrenophora teres f. maculata (Ptm) is a fungal pathogen that causes the spot form of net blotch on barley and leads to economic losses in many of the world's barley-growing regions. Isolates of Ptm exhibit varying levels of aggressiveness that result in quantifiable changes in the severity of the disease. Previous research on plant-pathogen interactions has shown that such divergence is reflected in the proteome and secretome of the pathogen, with certain classes of proteins more prominent in aggressive isolates. Here we have made a detailed comparative analysis of the secretomes of two Ptm isolates, GPS79 and E35 (highly and mildly aggressive, respectively) using a proteomics-based approach. The secretomes were obtained in vitro using media amended with barley leaf sections. Secreted proteins therein were harvested, digested with trypsin, and fractionated offline by HPLC prior to LC-MS in a high-resolution instrument to obtain deep coverage of the proteome. The subsequent analysis used a label-free quantitative proteomics approach with relative quantification of proteins based on precursor ion intensities. A total of 1175 proteins were identified, 931 from Ptm and 244 from barley. Further analysis revealed 160 differentially abundant proteins with at least a two-fold abundance difference between the isolates, with the most enriched in the aggressive GPS79 secretome. These proteins were mainly cell-wall (carbohydrate) degrading enzymes and peptidases, with some oxidoreductases and other pathogenesis-related proteins also identified, suggesting that aggressiveness is associated with an improved ability of GPS79 to overcome cell wall barriers and neutralize host defense responses.

Target formation in muscle fibres indicates reinnervation - A proteomic study in muscle samples from peripheral neuropathies.

Target skeletal muscle fibres - defined by different concentric areas in oxidative enzyme staining - can occur in patients with neurogenic muscular atrophy. Here, we used our established hypothesis-free proteomic approach with the aim of deciphering the protein composition of targets. We also searched for potential novel interactions between target proteins. Targets and control areas were laser microdissected from skeletal muscle sections of 20 patients with neurogenic muscular atrophy. Samples were analysed by a highly sensitive mass spectrometry approach, enabling relative protein quantification. The results were validated by immunofluorescence studies. Protein interactions were investigated by yeast two-hybrid assays, coimmunoprecipitation experiments and bimolecular fluorescence complementation. More than 1000 proteins were identified. Among these, 55 proteins were significantly over-represented and 40 proteins were significantly under-represented in targets compared to intraindividual control samples. The majority of over-represented proteins were associated with the myofibrillar Z-disc and actin dynamics, followed by myosin and myosin-associated proteins, proteins involved in protein biosynthesis and chaperones. Under-represented proteins were mainly mitochondrial proteins. Functional studies revealed that the LIM domain of the over-represented protein LIMCH1 interacts with isoform A of Xin actin-binding repeat-containing protein 1 (XinA). In particular, proteins involved in myofibrillogenesis are over-represented in target structures, which indicate an ongoing process of sarcomere assembly and/or remodelling within this specific area of the muscle fibres. We speculate that target structures are the result of reinnervation processes in which filamin C-associated myofibrillogenesis is tightly regulated by the BAG3-associated protein quality system.

Relative Quantification of Proteins in Formalin-Fixed Paraffin-Embedded Breast Cancer Tissue Using Multiplexed Mass Spectrometry Assays

The identification of clinically relevant biomarkers represents an important challenge in oncology. This problem can be addressed with biomarker discovery and verification studies performed directly in tumor samples using formalin-fixed paraffin-embedded (FFPE) tissues. However, reliably measuring proteins in FFPE samples remains challenging. Here, we demonstrate the use of liquid chromatography coupled to multiple reaction monitoring mass spectrometry (LC-MRM/MS) as an effective technique for such applications. An LC-MRM/MS method was developed to simultaneously quantify hundreds of peptides extracted from FFPE samples and was applied to the targeted measurement of 200 proteins in 48 triple-negative, 19 HER2-overexpressing, and 20 luminal A breast tumors. Quantitative information was obtained for 185 proteins, including known markers of breast cancer such as HER2, hormone receptors, Ki-67, or inflammation-related proteins. LC-MRM/MS results for these proteins matched immunohistochemistry or chromogenic in situ hybridization data. In addition, comparison of our results with data from the literature showed that several proteins representing potential biomarkers were identified as differentially expressed in triple-negative breast cancer samples. These results indicate that LC-MRM/MS assays can reliably measure large sets of proteins using the analysis of surrogate peptides extracted from FFPE samples. This approach allows to simultaneously quantify the expression of target proteins from various pathways in tumor samples. LC-MRM/MS is thus a powerful tool for the relative quantification of proteins in FFPE tissues and for biomarker discovery.

Effects of lncRNA MTC on protein expression in skin fibroblasts of Liaoning Cashmere goat based on iTRAQ technique

Existing experiments have found a new intergenic lncRNA activated by melatonin, which is called lncRNA MTC. However, the regulatory mechanism of lncRNA MTC in Liaoning Cashmere goat skin fibroblasts has not been clarified. Specific knockdown of lncRNA MTC inhibits cell proliferation and increases apoptosis. iTRAQ reagent was used for relative and absolute quantification of proteins in lncRNA MTC-KD and NC groups to evaluate changes in protein expression during dermal fibroblast development following lncRNA MTC deletion. A total of 5931 proteins were found in Liaoning Cashmere goat skin fibroblasts, of which 123 were differentially expressed, including 32 up-regulated proteins and 91 down-regulated proteins. Of the 91 down-regulated proteins, 32 act mainly through related pathways (e.g., cell cycle, mitochondrial function, ribosomal structure, vesicular transport, cytoskeletal components and skin morphogenesis). LncRNA MTC facilitates the proliferation of Liaoning Cashmere goat skin fibroblasts by regulating ITGB5, TlN2, CTSS, POLG, RAP1B, CHAF1A, CDCA8 and other proteins involved in cell proliferation. The results of this study provide some candidate proteins for the in-depth investigation of the molecular mechanism of lncRNA MTC, which facilitates hair growth in cashmere goats and provides more insights into their regulatory networks and biochemical pathways.

Local burn wound environment versus systemic response: Comparison of proteins and metabolites.

In this study, paired blood plasma (BP) and blister fluid (BF) samples from five paediatric burn patients were analysed using mass spectrometry to compare their protein and metabolite composition. The relative quantification of proteins was achieved through a label‐free data independent acquisition mode. The relative quantification of metabolites was achieved using a Shimadzu Smart Metabolite Database gas chromatography mass spectrometry (GCMS) targeted assay. In total, 562 proteins and 141 individual metabolites were identified in the samples. There was 81% similarity in the proteins present in the BP and BF, with 50 and 54 unique proteins found in each sample type respectively. BF contained keratinocyte proliferation‐related proteins and blood plasma contained abundant blood clotting proteins and apolipoproteins. BF contained more carbohydrates and less alpha‐hydroxy acid metabolites than the BP. In this study, there were unique proteins and metabolites in BF and BP which were reflective of the local wound environment and systemic environments respectively. The results from this study demonstrate that the biomolecule content of BF is mostly the same as blood, but it also contains information specific to the local wound environment.

Computer-Aided Design of DNA Self-Limited Assembly for Relative Quantification of Membrane Proteins.

Immunofluorescence imaging of cells plays a vital role in biomedical research and clinical diagnosis. However, when it is applied to relative quantification of proteins, it suffers from insufficient fluorescence intensity or partial overexposure, resulting in inaccurate relative quantification. Herein, we report a computer-aided design of DNA self-limited assembly (CAD-SLA) technology and apply it for relative quantification of membrane proteins, a concept proposed for the first time. CAD-SLA can achieve exponential cascade signal amplification in one pot and terminate at any desired level. By conjugating CAD-SLA with immunofluorescence, in situ imaging of cell membrane proteins is achieved with a controllable amplification level. Besides, comprehensive fluorescence intensity information from fluorescent images can be obtained, accurately showing relative quantitative information. Slight protein expression differences previously indistinguishable by immunofluorescence or Western blotting can now be discriminated, making fluorescence imaging-based relative quantification a promising tool for membrane protein analysis. From the perspectives of both DNA self-assembly technology and immunofluorescence technology, this work has solved difficult problems and provided important reference for future development.