HOTMAQ: A Multiplexed Absolute Quantification Method for Targeted Proteomics

Single Isotopologue for In-Sample Calibration and Absolute Quantitation by LC-MS/MS

Targeted mass spectrometry (MS)-based absolute quantitative analysis has been increasingly used in biomarker discovery. The ability to accurately measure the masses by MS enabled the use of isotope-incorporated surrogates having virtually identical physiochemical properties with the target analytes as calibrators. Such a unique capacity allowed for accurate in-sample calibration. Current in-sample calibration uses multiple isotopologues or structural analogues for both the surrogate and the internal standard. Here, we simplified this common practice by using endogenous light peptides as the internal standards and used a mathematical deduction of "heavy matching light, HML" to directly quantify an endogenous analyte. This method provides all necessary assay performance parameters in the authentic matrix, including the lower limit of quantitation (LLOQ) and intercept of the calibration curve, by using only a single isotopologue of the analyte. This method can be applied to the quantitation of proteins, peptides, and small molecules. Using this method, we quantified the efficiency of heart tissue digestion and recovery using sodium deoxycholate as a detergent and two spiked exogenous proteins as mimics of heart proteins. The results demonstrated the robustness of the assay.

Evaluating cPILOT Data toward Quality Control Implementation

Multiplexing enables the monitoring of hundreds to thousands of proteins in quantitative proteomics analyses and increases sample throughput. In most mass-spectrometry-based proteomics workflows, multiplexing is achieved by labeling biological samples with heavy isotopes via precursor isotopic labeling or isobaric tagging. Enhanced multiplexing strategies, such as combined precursor isotopic labeling and isobaric tagging (cPILOT), combine multiple technologies to afford an even higher sample throughput. Critical to enhanced multiplexing analyses is ensuring that analytical performance is optimal and that missingness of sample channels is minimized. Automation of sample preparation steps and use of quality control (QC) metrics can be incorporated into multiplexing analyses and reduce the likelihood of missing information, thus maximizing the amount of usable quantitative data. Here, we implemented QC metrics previously developed in our laboratory to evaluate a 36-plex cPILOT experiment that encompassed 144 mouse samples of various tissue types, time points, genotypes, and biological replicates. The evaluation focuses on the use of a sample pool generated from all samples in the experiment to monitor the daily instrument performance and to provide a means for data normalization across sample batches. Our results show that tracking QC metrics enabled the quantification of ∼7000 proteins in each sample batch, of which ∼70% had minimal missing values across up to 36 sample channels. Implementation of QC metrics for future cPILOT studies as well as other enhanced multiplexing strategies will help yield high-quality data sets.

Recent advances in mass spectrometry analysis of neuropeptides

Due to their involvement in numerous biochemical pathways, neuropeptides have been the focus of many recent research studies. Unfortunately, classic analytical methods, such as western blots and enzyme-linked immunosorbent assays, are extremely limited in terms of global investigations, leading researchers to search for more advanced techniques capable of probing the entire neuropeptidome of an organism. With recent technological advances, mass spectrometry (MS) has provided methodology to gain global knowledge of a neuropeptidome on a spatial, temporal, and quantitative level. This review will cover key considerations for the analysis of neuropeptides by MS, including sample preparation strategies, instrumental advances for identification, structural characterization, and imaging; insightful functional studies; and newly developed absolute and relative quantitation strategies. While many discoveries have been made with MS, the methodology is still in its infancy. Many of the current challenges and areas that need development will also be highlighted in this review.

Recent advances in isobaric labeling and applications in quantitative proteomics

Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine abundances of proteins and peptides in complex biological samples. Several methods have been developed and adapted for accurate quantification based on chemical isotopic labeling. Among various chemical isotopic labeling techniques, isobaric tagging approaches rely on the analysis of peptides from MS2-based quantification rather than MS1-based quantification. In this review, we will provide an overview of several isobaric tags along with some recent developments including complementary ion tags, improvements in sensitive quantitation of analytes with lower abundance, strategies to increase multiplexing capabilities, and targeted analysis strategies. We will also discuss limitations of isobaric tags and approaches to alleviate these restrictions through bioinformatic tools and data acquisition methods. This review will highlight several applications of isobaric tags, including biomarker discovery and validation, thermal proteome profiling, cross-linking for structural investigations, single-cell analysis, top-down proteomics, along with applications to different molecules including neuropeptides, glycans, metabolites, and lipids, while providing considerations and evaluations to each application.

Boost-DiLeu: Enhanced Isobaric N,N-Dimethyl Leucine Tagging Strategy for a Comprehensive Quantitative Glycoproteomic Analysis

Intact glycopeptide analysis has been of great interest because it can elucidate glycosylation site information and glycan structural composition at the same time. However, mass spectrometry (MS)-based glycoproteomic analysis is hindered by the low abundance and poor ionization efficiency of glycopeptides. Relatively large amounts of starting materials are needed for the enrichment, which makes the identification and quantification of intact glycopeptides from samples with limited quantity more challenging. To overcome these limitations, we developed an improved isobaric labeling strategy with an additional boosting channel to enhance N,N-dimethyl leucine (DiLeu) tagging-based quantitative glycoproteomic analysis, termed as Boost-DiLeu. With the integration of a one-tube sample processing workflow and high-pH fractionation, 3514 quantifiable N-glycopeptides were identified from 30 μg HeLa cell tryptic digests with reliable quantification performance. Furthermore, this strategy was applied to human cerebrospinal fluid (CSF) samples to differentiate N-glycosylation profiles between Alzheimer's disease (AD) patients and non-AD donors. The results revealed processes and pathways affected by dysregulated N-glycosylation in AD, including platelet degranulation, cell adhesion, and extracellular matrix, which highlighted the involvement of N-glycosylation aberrations in AD pathogenesis. Moreover, weighted gene coexpression network analysis (WGCNA) showed nine modules of glycopeptides, two of which were associated with the AD phenotype. Our results demonstrated the feasibility of using this strategy for in-depth glycoproteomic analysis of size-limited clinical samples. Taken together, we developed and optimized a strategy for the enhanced comprehensive quantitative intact glycopeptide analysis with DiLeu labeling, showing significant promise for identifying novel therapeutic targets or biomarkers in biological systems with a limited sample quantity.

Isotopic N,N-dimethyl leucine tags for absolute quantification of clusterin and apolipoprotein E in Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia and one of the leading causes of death in the United States. In the past decades, extensive efforts have been devoted to biomarker discovery for early diagnosis and treatment of AD. Herein, this study aims to quantify clusterin (CLU) and apolipoprotein E (APOE) in blood samples from AD patients and evaluate these two proteins as potential biomarkers in AD diagnosis. In-house synthesized 5-plex isotopic N,N-dimethyl leucine (iDiLeu) tags were used to label target peptide standards at different concentrations to construct standard curves. Our study revealed that the levels of CLU and APOE exhibited clear differences in male vs. female AD groups but not in male vs. female non-AD groups. In contrast, the levels of serum CLU and APOE did not show statistically significant differences in the AD groups and non-AD groups. Principal component analysis (PCA) with CLU and APOE showed some separation between the AD and non-AD participants. Significance: Dissecting CLU and APOE heterogeneity in AD pathogenesis may therefore facilitate delineating the pathological relevance for sex-related pathways, leading to personalized medicine in the future. Collectively, this study introduces a cost-effective absolute quantitative proteomics strategy for target protein quantitation and lays the foundation for future investigation of CLU and APOE as potential biomarkers for AD. SIGNIFICANCE STATEMENT: As blood-based biomarkers for AD diagnosis are cost-effective and introduce less invasiveness, discovery and validation of biomarkers in the blood samples of AD patients have become a hot topic in Alzheimer's and dementia research. Thus far, amyloid β (Aβ), total-tau and phosphorylated tau (p-tau) in blood show great accuracy and specificity in diagnosis of AD. However, the underlying mechanism of AD pathology remains to be elusive and complex. Besides these well studied proteins, many other proteins, such as clusterin (CLU) and apolipoprotein E (APOE) have also been found to be related to AD development. It has been implicated that these two proteins are involved in Aβ clearance and deposition. In this study, we measure the absolute concentrations of these two proteins in blood and shed some light on the potential roles of CLU and APOE in AD pathology. Dissecting CLU and APOE heterogeneity in AD pathogenesis may therefore facilitate delineating the pathological relevance for specific pathways between different genders, leading to personalized medicine in the future. Collectively, this study introduces a cost-effective absolute quantitative proteomics strategy for target protein quantitation and lays the foundation for future investigation of CLU and APOE as potential biomarkers for AD.

Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research

Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.

In-depth Site-specific Analysis of N-glycoproteome in Human Cerebrospinal Fluid and Glycosylation Landscape Changes in Alzheimer's Disease

As the body fluid that directly interchanges with the extracellular fluid of the central nervous system (CNS), cerebrospinal fluid (CSF) serves as a rich source for CNS-related disease biomarker discovery. Extensive proteome profiling has been conducted for CSF, but studies aimed at unraveling site-specific CSF N-glycoproteome are lacking. Initial efforts into site-specific N-glycoproteomics study in CSF yield limited coverage, hindering further experimental design of glycosylation-based disease biomarker discovery in CSF. In the present study, we have developed an N-glycoproteomic approach that combines enhanced N-glycopeptide sequential enrichment by hydrophilic interaction chromatography (HILIC) and boronic acid enrichment with electron transfer and higher-energy collision dissociation (EThcD) for large-scale intact N-glycopeptide analysis. The application of the developed approach to the analyses of human CSF samples enabled identifications of a total of 2893 intact N-glycopeptides from 511 N-glycosites and 285 N-glycoproteins. To our knowledge, this is the largest site-specific N-glycoproteome dataset reported for CSF to date. Such dataset provides molecular basis for a better understanding of the structure-function relationships of glycoproteins and their roles in CNS-related physiological and pathological processes. As accumulating evidence suggests that defects in glycosylation are involved in Alzheimer's disease (AD) pathogenesis, in the present study, a comparative in-depth N-glycoproteomic analysis was conducted for CSF samples from healthy control and AD patients, which yielded a comparable N-glycoproteome coverage but a distinct expression pattern for different categories of glycoforms, such as decreased fucosylation in AD CSF samples. Altered glycosylation patterns were detected for a number of N-glycoproteins including alpha-1-antichymotrypsin, ephrin-A3 and carnosinase CN1 etc., which serve as potentially interesting targets for further glycosylation-based AD study and may eventually lead to molecular elucidation of the role of glycosylation in AD progression.

Recent Advances in Analytical Approaches for Glycan and Glycopeptide Quantitation

Growing implications of glycosylation in physiological occurrences and human disease have prompted intensive focus on revealing glycomic perturbations through absolute and relative quantification. Empowered by seminal methodologies and increasing capacity for detection, identification, and characterization, the past decade has provided a significant increase in the number of suitable strategies for glycan and glycopeptide quantification. Mass-spectrometry-based strategies for glycomic quantitation have grown to include metabolic incorporation of stable isotopes, deposition of mass difference and mass defect isotopic labels, and isobaric chemical labeling, providing researchers with ample tools for accurate and robust quantitation. Beyond this, workflows have been designed to harness instrument capability for label-free quantification, and numerous software packages have been developed to facilitate reliable spectrum scoring. In this review, we present and highlight the most recent advances in chemical labeling and associated techniques for glycan and glycopeptide quantification.

Mass Defect-Based DiLeu Tagging for Multiplexed Data-Independent Acquisition

The unbiased selection of peptide precursors makes data-independent acquisition (DIA) an advantageous alternative to data-dependent acquisition (DDA) for discovery proteomics, but traditional multiplexed quantification approaches employing mass difference labeling or isobaric tagging are incompatible with DIA. Here, we describe a strategy that permits multiplexed quantification by DIA using mass defect-based N,N-dimethyl leucine (mdDiLeu) tags and high-resolution tandem mass spectrometry (MS2) analysis. Millidalton mass differences between mdDiLeu isotopologues produce fragment ion multiplet peaks separated in mass by as little as 5.8 mDa, enabling up to 4-plex quantification in DIA MS2 spectra. Quantitative analysis of yeast samples displayed comparable accuracy and precision for MS2-based DIA and MS1-based DDA methods. Multiplexed DIA analysis of cerebrospinal fluid revealed the dynamic proteome changes in Alzheimer's disease, demonstrating its utility for discovery of potential clinical biomarkers. We show that the mdDiLeu tagging approach for multiplexed DIA is a viable methodology for investigating proteome changes, particularly for low-abundance proteins, in different biological matrices.

Isobaric Labeling Strategy Utilizing 4-Plex N,N-Dimethyl Leucine (DiLeu) Tags Reveals Proteomic Changes Induced by Chemotherapy in Cerebrospinal Fluid of Children with B-Cell Acute Lymphoblastic Leukemia

The use of mass spectrometry for protein identification and quantification in cerebrospinal fluid (CSF) is at the forefront of research efforts to identify and explore biomarkers for the early diagnosis and prognosis of neurologic disorders. Here we implemented a 4-plex N,N-dimethyl leucine (DiLeu) isobaric labeling strategy in a longitudinal study aiming to investigate protein dynamics in children with B-cell acute lymphoblastic leukemia (B-cell ALL) undergoing chemotherapy. The temporal profile of CSF proteome during chemotherapy treatment at weeks 5, 10-14, and 24-28 highlighted many differentially expressed proteins, such as neural cell adhesion molecule, neuronal growth regulator 1, and secretogranin-3, all of which play important roles in neurodegenerative diseases. A total of 63 proteins were significantly altered across all of the time points investigated. The most over-represented biological processes from gene ontology analysis included platelet degranulation, complement activation, cell adhesion, fibrinolysis, neuron projection, regeneration, and regulation of neuron death. We expect that results from this and future studies will provide a means to monitor neurotoxicity and develop strategies to prevent central nervous system injury in response to chemotherapy in children.

Enhancing Data Reliability in TOMAHAQ for Large-Scale Protein Quantification

The analytical scale of most mass-spectrometry-based targeted proteomics assays is usually limited by assay performance and instrument utilization. A recently introduced method, called triggered by offset, multiplexed, accurate mass, high resolution, and absolute quantitation (TOMAHAQ), combines both peptide and sample multiplexing to simultaneously improve analytical scale and quantitative performance. In the present work, critical technical requirements and data analysis considerations for successful implementation of the TOMAHAQ technique based on the study of a total of 185 target peptides across over 200 clinical plasma samples are discussed. Importantly, it is observed that significant interference originate from the TMTzero reporter ion used for the synthetic trigger peptides. This interference is not expected because only TMT10plex reporter ions from the target peptides should be observed under typical TOMAHAQ conditions. In order to unlock the great promise of the technique for high throughput quantification, here a post-acquisition data correction strategy to deconvolute the reporter ion superposition and recover reliable data is proposed.

Progress and pitfalls of using isobaric mass tags for proteome profiling

Introduction: Quantitative proteomics using mass spectrometry is performed via label-free or label-based approaches. Labeling strategies rely on the incorporation of stable heavy isotopes by metabolic, enzymatic, or chemical routes. Isobaric labeling uses chemical labels of identical masses but of different fragmentation behaviors to allow the relative quantitative comparison of peptide/protein abundances between biological samples.Areas covered: We have carried out a systematic review on the use of isobaric mass tags in proteomic research since their inception in 2003. We focused on their quantitative performances, their multiplexing evolution, as well as their broad use for relative quantification of proteins in pre-clinical models and clinical studies. Current limitations, primarily linked to the quantitative ratio distortion, as well as state-of-the-art and emerging solutions to improve their quantitative readouts are discussed.Expert opinion: The isobaric mass tag technology offers a unique opportunity to compare multiple protein samples simultaneously, allowing higher sample throughput and internal relative quantification for improved trueness and precision. Large studies can be performed when shared reference samples are introduced in multiple experiments. The technology is well suited for proteome profiling in the context of proteomic discovery studies.

In Depth Quantification of Extracellular Matrix Proteins from Human Pancreas

Extracellular matrix (ECM) is an important component of the pancreatic microenvironment which regulates β cell proliferation, differentiation, and insulin secretion. Protocols have recently been developed for the decellularization of the human pancreas to generate functional scaffolds and hydrogels. In this work, we characterized human pancreatic ECM composition before and after decellularization using isobaric dimethylated leucine (DiLeu) labeling for relative quantification of ECM proteins. A novel correction factor was employed in the study to eliminate the bias introduced during sample preparation. In comparison to the commonly employed sample preparation methods (urea and FASP) for proteomic analysis, a recently developed surfactant and chaotropic agent assisted sequential extraction/on pellet digestion (SCAD) protocol has provided an improved strategy for ECM protein extraction of human pancreatic ECM matrix. The quantitative proteomic results revealed the preservation of matrisome proteins while most of the cellular proteins were removed. This method was compared with a well-established label-free quantification (LFQ) approach which rendered similar expressions of different categories of proteins (collagens, ECM glycoproteins, proteoglycans, etc.). The distinct expression of ECM proteins was quantified comparing adult and fetal pancreas ECM, shedding light on the correlation between matrix composition and postnatal β cell maturation. Despite the distinct profiles of different subcategories in the native pancreas, the distribution of matrisome proteins exhibited similar trends after the decellularization process. Our method generated a large data set of matrisome proteins from a single tissue type. These results provide valuable insight into the possibilities of constructing a bioengineered pancreas. It may also facilitate better understanding of the potential roles that matrisome proteins play in postnatal β cell maturation.

High-Resolution Enabled 5-plex Mass Defect-Based N, N-Dimethyl Leucine Tags for Quantitative Proteomics

A mass defect-based labeling strategy provides high accuracy as an MS¹-centric quantification method, avoiding the ratio compression that affects isobaric label-based reporter ion quantification. We have developed cost-effective 5-plex mass defect N, N-dimethyl leucine (mdDiLeu) tags for quantification of various biological samples with increased multiplexing at a given resolving power afforded by the addition of mass difference isotopologues. The combination of mass difference and mass defect produces two labeled peak clusters separated by 5 Da in MS¹ spectra that are detected as five isotopic peaks at high resolution with mass differences of 15, 17, and 18 mDa per tag. Synthesis of each of the 5-plex mdDiLeu tags is accomplished by a single straightforward reaction step, making it accessible to any lab. To demonstrate 5-plex mdDiLeu for quantitative proteomics, we perform proof-of-principle experiments of mdDiLeu-labeled Saccharomyces cerevisiae lysate digest on an Orbitrap Fusion Lumos mass spectrometer.