Immuno-Mass Spectrometry Workflow for Quantification of Serum α-Fetoprotein Using Antibody-Immobilized Magnetic Beads and Modified Eluents.

Immuno-mass spectrometry (MS) is a powerful method for the quantitative analysis of low-abundance proteins in biological specimens. In these procedures, collecting specifically and efficiently the target protein antigens from the antigen-antibody complex generated on the surface of nanocarrier beads is crucial and can be performed by hydrolyzing the proteins directly on the beads or after elution. Herein, we optimized the conditions of the immunoaffinity purification via elution using serum α-fetoprotein (AFP) as a model and its specific antibody immobilized covalently on magnetic beads. Antibody-coated beads were incubated with human serum spiked with standard AFP for antigen-antibody reaction. AFP was then eluted from the beads using various eluents, including organic solvents, to optimize the elution conditions. After proteolytically hydrolyzing the eluted protein, stable isotope-labeled standard peptides were added to the hydrolysate to quantify the eluted AFP via liquid chromatography-tandem MS. Using an optimized workflow for quantitative analysis afforded a correlation between the amount of spiked AFP and heavy to light ratios calculated based on peptide ion peak areas, from which an endogenous AFP concentration of 2.3±0.6 ng/mL was determined in normal serum; this is consistent with previous reports using radioimmunoassay methods. The present immuno-MS workflow could apply to the detection and quantitation of other low-abundance biofluid biomarkers.

Immuno-MALDI-MS for Accurate Quantitation of Targeted Peptides from Volume-Restricted Samples.

The immuno-MALDI-MS method can be used to quantify low-abundance proteins from clinical samples that offer only a limited amount of material for analysis. An internal standard, in the form of a stable isotope-labeled peptide, is used to ensure reproducible and absolute quantitation. The protocol described here was optimized for the quantitation of AKT1 and AKT2, but we offer instructions on how to adapt the method to target other proteins. The described workflow is compatible with automation via a liquid handling robot for high-throughput applications.

Multiplex LC-MS/MS Testing for Early Detection of Kidney Injury: A Next-Generation Alternative to Conventional Immunoassays?

BACKGROUND: LC-MS/MS has enabled the translation of many novel biomarkers to the clinical laboratory, but its potential for measurement of urinary proteins is still unexplored. In this study we examined the correlation and agreement between immunoassay and LC-MS/MS in the quantitation of kidney injury biomarkers and evaluated the application of technical LC-MS/MS meta-data assessment to ensure test result validity. METHODS: NGAL, IGFBP7, TIMP2, and KIM-1 were quantified in 345 urine samples with one multiplex lab-developed test that combines immunocapture with mass spectrometry read-out and 4 singleplex sandwich-type immunoassays. Assay performance and imprecision were monitored by 2 urine-based quality controls. Ion ratios, signal intensity, and retention time were monitored over all study samples. RESULTS: The LC-MS/MS retention time drift was ≤1.2%, ion ratios were within 20% of the target values at concentrations of >100 pmol/L, and peptides originating from the same protein were in agreement (slopes between 1.03 and 1.41). The interassay CV was between 9.3% and 19.1% for LC-MS/MS analysis and between 4.2% and 10.9% for immunoassay. Direct LC-MS/MS analysis was correlated with immunoassay in the quantitation of NGAL (r = 0.93; range: 0.01-37 nmol/L), IGFBP7 (r = 0.80; range: 0.01-2.6 nmol/L), TIMP2 (r = 0.85; range: 0.01-6.3 nmol/L), and KIM-1 (r = 0.70; range 0.01-0.4 nmol/L), but the analytical methodologies differed in measurands and calibration strategies. CONCLUSIONS: LC-MS/MS is explored as a next-generation technology for multiplex urinary protein measurement. It has great potential to overcome nonselectivity and lack of standardization because of its capability of directly measuring well-defined molecular proteins.

Absolute Quantitation of Proteins by Acid Hydrolysis Combined with Amino Acid Detection by Mass Spectrometry.

Amino acid analysis is among the most accurate methods for absolute quantification of proteins and peptides. Here we combine acid hydrolysis with the addition of isotopically labeled standard amino acids and analysis by mass spectrometry for accurate and sensitive protein quantitation. Quantitation of less than 10 fmol of protein standards with errors below 10% has been demonstrated using this method.

Amino Acid Analysis by Means of MALDI TOF Mass Spectrometry or MALDI TOF/TOF Tandem Mass Spectrometry.

Here we describe two different AAA protocols based on application of matrix-assisted laser desorption ionization time-of-flight (MALDI TOF) mass spectrometry (MS). First protocol describes a MALDI TOF MS-based method for a routine simultaneous qualitative and quantitative analysis of free amino acids and protein hydrolysates. Linear responses between the amino acid concentration and the peak intensity ratio of corresponding amino acid to internal standard were observed for all amino acids analyzed in the range of concentrations from 20 to 300 µM. Limit of quantitation varied from 0.03 µM for arginine to 3.7 µM for histidine and homocysteine. This method has one inherent limitation: the analysis of isomeric and isobaric amino acids. To solve this problem, a second protocol based on the use of MALDI TOF/TOF MS/MS for qualitative analysis of amino and organic acids was developed. This technique is capable of distinguishing isobaric and isomeric compounds. Both methods do not require amino acid derivatization or chromatographic separation, and the data acquisition time is decreased to several seconds for a single sample.

Determination of Rate-Limiting Factor for Formation of Beta-Catenin Destruction Complexes Using Absolute Protein Quantification.

Wnt/ß-catenin signaling plays important roles in both ontogenesis and development. In the absence of a Wnt stimulus, ß-catenin is degraded by a multiprotein "destruction complex" that includes Axin, APC, GSK3B, and FBXW11. Although the key molecules required for transducing Wnt signals have been identified, a quantitative understanding of this pathway has been lacking. Here, we calculated the absolute number of ß-catenin destruction complexes by absolute protein quantification using LC-MS/MS. Similar amounts of destruction complex-constituting proteins and ß-catenin interacted, and the number of destruction complexes was calculated to be about 1468 molecules/cell. We demonstrated that the calculated number of destruction complexes was valid for control of the ß-catenin destruction rate under steady-state conditions. Interestingly, APC had the minimum expression level among the destruction complex components at about 2233 molecules/cell, and this number approximately corresponded to the calculated number of destruction complexes. Decreased APC expression by siRNA transfection decreased the number of destruction complexes, resulting in ß-catenin accumulation and stimulation of the transcriptional activity of T-cell factor. Taken together, our results suggest that the amount of APC expression is the rate-limiting factor for the constitution of ß-catenin destruction complexes.

Label-Free Quantitative Analysis of Mitochondrial Proteomes Using the Multienzyme Digestion-Filter Aided Sample Preparation (MED-FASP) and "Total Protein Approach".

Determination of proteome composition and measuring of changes in protein titers provide important information with a substantial value for studying mitochondria.This chapter describes a workflow for the quantitative analysis of mitochondrial proteome with a focus on sample preparation and quantitative analysis of the data. The workflow involves the multienzyme digestion-filter aided sample preparation (MED-FASP) protocol enabling efficient extraction of proteins and high rate of protein-to-peptide conversion. Consecutive protein digestion with Lys C and trypsin enables generation of peptide fractions with minimal overlap, largely increases the number of identified proteins, and extends their sequence coverage. Abundances of proteins identified by multiple peptides can be assessed by the "Total Protein Approach."

Label-Free and Standard-Free Absolute Quantitative Proteomics Using the "Total Protein" and "Proteomic Ruler" Approaches.

Understanding biological systems and their variation upon stimuli requires knowledge on their composition, primarily including information on organization and dynamics of proteomes. The total protein approach (TPA) is a label- and standard-free method for absolute protein quantitation of proteins using large-scale proteomic data. The method relies on the assumption that the total MS signal from all identified proteins in the dataset reflects-in a biochemical sense-the total protein and the MS signal from a single protein corresponds its abundance in the studied sample. The method offers an easy way to quantify thousands of protein per sample. A related method, the "Proteomic Ruler," enables conversion of the protein abundance data calculated by TPA to compute numbers of protein copies per cell. TPA and the Proteomic Ruler are powerful tools for studying dynamics of cell architecture.

Integrating Proteomics and Enzyme Kinetics Reveals Tissue-Specific Types of the Glycolytic and Gluconeogenic Pathways.

Glycolysis is the core metabolic pathway supplying energy to cells. Whereas the vast majority of studies focus on specific aspects of the process, global analyses characterizing simultaneously all enzymes involved in the process are scarce. Here, we demonstrate that quantitative label- and standard-free proteomics allows accurate determination of titers of metabolic enzymes and enables simultaneous measurements of titers and maximal enzymatic activities (Amax) of all glycolytic enzymes and the gluconeogenic fructose 1,6-bisphosphatase in mouse brain, liver and muscle. Despite occurrence of tissue-specific isoenzymes bearing different kinetic properties, the enzyme titers often correlated well with the Amax values. To provide a more general picture of energy metabolism, we analyzed titers of the enzymes in additional 7 mouse organs and in human cells. Across the analyzed samples, we identified two basic profiles: a "fast glucose uptake" one in brain and heart, and a "gluconeogenic rich" one occurring in liver. In skeletal muscles and other organs, we found intermediate profiles. Obtained data highlighted the glucose-flux-limiting role of hexokinase which activity was always 10- to 100-fold lower than the average activity of all other glycolytic enzymes. A parallel determination of enzyme titers and maximal enzymatic activities allowed determination of kcat values without enzyme purification. Results of our in-depth proteomic analysis of the mouse organs did not support the concepts of regulation of glycolysis by lysine acetylation.

Absolute quantitative profiling of the key metabolic pathways in slow and fast skeletal muscle.

Slow and fast skeletal muscles are composed of, respectively, mainly oxidative and glycolytic muscle fibers, which are the basic cellular motor units of the motility apparatus. They largely differ in excitability, contraction mechanism, and metabolism. Because of their pivotal role in body motion and homeostasis, the skeletal muscles have been extensively studied using biochemical and molecular biology approaches. Here we describe a simple analytical and computational approach to estimate titers of enzymes of basic metabolic pathways and proteins of the contractile machinery in the skeletal muscles. Proteomic analysis of mouse slow and fast muscles allowed estimation of the titers of enzymes involved in the carbohydrate, lipid, and energy metabolism. Notably, we observed that differences observed between the two muscle types occur simultaneously for all proteins involved in a specific process such as glycolysis, free fatty acid catabolism, Krebs cycle, or oxidative phosphorylation. These differences are in a good agreement with the well-established biochemical picture of the muscle types. We show a correlation between maximal activity and the enzyme titer, suggesting that change in enzyme concentration is a good proxy for its catalytic potential in vivo. As a consequence, proteomic profiling of enzyme titers can be used to monitor metabolic changes in cells. Additionally, quantitative data of structural proteins allowed studying muscle type specific cell architecture and its remodeling. The presented proteomic approach can be applied to study metabolism in any other tissue or cell line.

Absolute protein quantification allows differentiation of cell-specific metabolic routes and functions.

Total protein approach (TPA) is a proteomic method that allows calculation of concentrations of individual proteins and groups of functionally related proteins in any protein mixture without spike-in standards. Using the two-step digestion-filter-aided sample preparation method and LC-MS/MS analysis, we generated comprehensive quantitative datasets of mouse intestinal mucosa, liver, red muscle fibers, brain, and of human plasma, erythrocytes, and tumor cells lines. We show that the TPA-based quantitative data reflect well-defined and specific physiological functions of different organs and cells, for example nutrient absorption and transport in intestine, amino acid catabolism and bile secretion in liver, and contraction of muscle fibers. Focusing on key metabolic processes, we compared metabolic capacities in different tissues and cells. In addition, we demonstrate quantitative differences in the mitochondrial proteomes. Providing insight into the abundances of mitochondrial metabolite transporters, we demonstrate that their titers are well tuned to cell-specific metabolic requirements. This study provides for the first time a comprehensive overview of the protein hardware mediating metabolism in different mammalian organs and cells. The presented approach can be applied to any other system to study biological processes. All MS data have been deposited in the ProteomeXchange with identifier PXD001352 (http://proteomecentral.proteomexchange.org/dataset/PXD001352).