Accurate Protein Quantification Research Articles

Absolute protein quantification based on calibrated particle counting using electrospray-differential mobility analysis

The traceability of in vitro diagnostics or drug products is based on the accurate quantification of proteins. In this study, we developed an absolute quantification approach for proteins. This method is based on calibrated particle counting using electrospray-differential mobility analysis (ES-DMA) coupled with a condensation particle counter (CPC). The absolute concentration of proteins was quantified with the observed protein particle number measured with ES-DMA-CPC, and the detection efficiency was determined by calibrators. The measurement performance and quantitative level were verified using two certificated reference materials, BSA and NIMCmAb. The linear regression fit for the detection efficiency values of three reference materials and one highly purified protein (myoglobin, BSA, NIMCmAb and fibrinogen) indicated that the detection efficiency and the particle size distribution of these proteins exhibited a linear relationship. Moreover, to explore the suitability of the detection efficiency-particle size curve for protein quantification, the concentrations of three typical proteinaceous particles, including two high molecular weight proteins (NIST reference material 8671 and D-dimer) and one protein complex (glutathione S-transferase dimer), were determined. This work suggests that this calibrated particle counting method is an efficient approach for nondestructive, rapid and accurate quantification of proteins, especially for measuring proteinaceous particles with tremendous size and without reference standards.

Quantification of AMPA receptor subunits and RNA editing-related proteins in the J20 mouse model of Alzheimer's disease by capillary western blotting.

Accurate modelling of molecular changes in Alzheimer's disease (AD) dementia is crucial for understanding the mechanisms driving neuronal pathology and for developing treatments. Synaptic dysfunction has long been implicated as a mechanism underpinning memory dysfunction in AD and may result in part from changes in adenosine deaminase acting on RNA (ADAR) mediated RNA editing of the GluA2 subunit of AMPA receptors and changes in AMPA receptor function at the post synaptic cleft. However, few studies have investigated changes in proteins which influence RNA editing and notably, AD studies that focus on studying changes in protein expression, rather than changes in mRNA, often use traditional western blotting. Here, we demonstrate the value of automated capillary western blotting to investigate the protein expression of AMPA receptor subunits (GluA1-4), the ADAR RNA editing proteins (ADAR1-3), and proteins known to regulate RNA editing (PIN1, WWP2, FXR1P, and CREB1), in the J20 AD mouse model. We describe extensive optimisation and validation of the automated capillary western blotting method, demonstrating the use of total protein to normalise protein load, in addition to characterising the optimal protein/antibody concentrations to ensure accurate protein quantification. Following this, we assessed changes in proteins of interest in the hippocampus of 44-week-old J20 AD mice. We observed an increase in the expression of ADAR1 p110 and GluA3 and a decrease in ADAR2 in the hippocampus of 44-week-old J20 mice. These changes signify a shift in the balance of proteins that play a critical role at the synapse. Regression analysis revealed unique J20-specific correlations between changes in AMPA receptor subunits, ADAR enzymes, and proteins that regulate ADAR stability in J20 mice, highlighting potential mechanisms mediating RNA-editing changes found in AD. Our findings in J20 mice generally reflect changes seen in the human AD brain. This study underlines the importance of novel techniques, like automated capillary western blotting, to assess protein expression in AD. It also provides further evidence to support the hypothesis that a dysregulation in RNA editing-related proteins may play a role in the initiation and/or progression of AD.

Precise Control of Trypsin Immobilization by a Programmable DNA Tetrahedron Designed for Ultrafast Proteome Digestion and Accurate Protein Quantification.

In proteomics research, with advantages including short digestion times and reusable applications, immobilized enzyme reactors (IMERs) have been paid increasing attention. However, traditional IMERs ignore the reasonable spatial arrangement of trypsin on the supporting matrixes, resulting in the partial overlapping of the active domain on trypsin and reducing digesting efficiency. In this work, a DNA tetrahedron (DNA TET)-based IMER Fe3O4-GO-AuNPs-DNA TET-Trypsin was designed and prepared. The distance between vertices of DNA TETs effectively controls the distribution of trypsin on the nanomaterials; thus, highly efficient protein digestion and accurate quantitative results can be achieved. Compared to the in-solution digestion (12-16 h), the sequence coverage of bovine serum albumin was up to 91% after a 2-min digestion by the new IMER. In addition, 3328 proteins and 18,488 peptides can be identified from HeLa cell protein extract after a 20-min digestion. For the first time, human growth hormone reference material was rapidly and accurately quantified after a 4-h digestion by IMER. Therefore, this new IMER has great application potential in proteomics research and SI traceable quantification.

Data-Driven Optimization of DIA Mass Spectrometry by DO-MS.

Mass spectrometry (MS) enables specific and accurate quantification of proteins with ever-increasing throughput and sensitivity. Maximizing this potential of MS requires optimizing data acquisition parameters and performing efficient quality control for large datasets. To facilitate these objectives for data-independent acquisition (DIA), we developed a second version of our framework for data-driven optimization of MS methods (DO-MS). The DO-MS app v2.0 (do-ms.slavovlab.net) allows one to optimize and evaluate results from both label-free and multiplexed DIA (plexDIA) and supports optimizations particularly relevant to single-cell proteomics. We demonstrate multiple use cases, including optimization of duty cycle methods, peptide separation, number of survey scans per duty cycle, and quality control of single-cell plexDIA data. DO-MS allows for interactive data display and generation of extensive reports, including publication of quality figures that can be easily shared. The source code is available at github.com/SlavovLab/DO-MS.

Single-cell proteomics: quantifying post-transcriptional regulation during development with mass-spectrometry.

Many developmental processes are regulated post-transcriptionally. Such post-transcriptional regulatory mechanisms can now be analyzed by robust single-cell mass spectrometry methods that allow accurate quantification of proteins and their modification in single cells. These methods can enable quantitative exploration of protein synthesis and degradation mechanisms that contribute to developmental cell fate specification. Furthermore, they may support functional analysis of protein conformations and activities in single cells, and thus link protein functions to developmental processes. This Spotlight provides an accessible introduction to single-cell mass spectrometry methods and suggests initial biological questions that are ripe for investigation.

Development of a potential primary method for protein quantification via electrospray differential mobility analysis

Accurate protein quantification is the basis for establishing the metrological traceability of in vitro diagnostics or drug products. In this study, we established and validated a potential primary method for protein quantification based on electrospray-differential mobility analysis coupled with a condensation particle counter (ES-DMA-CPC). The analytical performance of this method was assessed using the certified reference material NIMCmAb, and the uncertainty of measurement was evaluated. The method was applied to the quantification of three other protein reference materials and one highly purified protein, including myoglobin, bovine serum albumin, IgG monoclonal antibody, and one highly purified fibrinogen, with a molecular weight range between 17 kDa and 340 kDa. In addition, when compared with isotope dilution mass spectrometry (IDMS) and UV‒VIS spectrophotometry approaches, the ES-DMA-CPC method showed good agreement with IDMS method for the quantification of these protein reference materials. Our proposed method provided an accurate quantification of proteins, especially those with large molecular weights. Moreover, our method could be a potential primary method for protein quantification and serve as a complement to IDMS method.

Proximity Sequencing Enables Measurement of Protein Complexes in Single Cells.

Advances in single-cell sequencing technology have transformed our understanding of cellular heterogeneity and identity, providing insight on topics ranging from the diversity of microbial ecosystems to tumor biological behaviors. However, accurate measurement of protein complexes in single cells remains challenging as relatively few proteins can form large numbers of complexes that must be distinguished accurately. The inability to accurately differentiate protein complexes hinders in-depth study of critical biological functions such as immune signaling and cellular differentiation. In a recent article in Nature Methods, Vistain et al. (1) present a solution to this problem by combining proximity ligation assay (PLA) with single-cell RNA sequencing (scRNA-seq). This method, which they call proximity sequencing (Prox-seq), can measure hundreds of protein complexes and mRNAs in single cells simultaneously. Prox-seq introduces pairs of DNA-conjugated antibodies to single-cell sequencing methods. When proteins enter a complex, the DNA oligomers on the antibodies come into proximity and are ligated. These ligated DNA oligomers (PLA products) are then sequenced to retrieve protein complex information. Prox-seq also generates transcriptome data through mRNA sequencing, allowing multimodal analyses of single cells. To validate this assay, the authors first demonstrated Prox-seq’s ability to differentiate T and B cells in a mixed population using probes designed for 11 cell-specific protein targets. Prox-seq measurements showed that T and B cells could be accurately differentiated using mRNAs, proteins, or total PLA products. An orthogonal method of flow cytometry was used to confirm that the enriched PLA products in each cell type were cell-specific proteins. This confirmed that PLA products can be measured using scRNA-seq, and PLA data displays cell type-specific differences in protein expression. Quantification of protein expression analysis in the same cell types with a different panel of 13 Prox-seq probes showed high correlation with flow cytometry which confirmed accurate protein characterization and quantification by Prox-seq in single cells. The authors also tested Prox-seq’s ability to measure large numbers of protein complexes in 8700 human peripheral blood mononuclear cells with a panel of probe pairs targeting 38 immune cell markers, and up to 741 unique protein complexes. The data showed 37 protein complexes and measurements identifying the expected cell types. In addition, they identified a novel CD8 and CD9 interaction in naïve CD8 T cells. Lastly, authors demonstrated that the assay can identify variability of receptor components in individual human macrophages after activation of an innate immunity signaling pathway by measuring PLA products detected within a panel designed for 15 pathway-specific protein targets.

Advanced mass spectrometry workflows for accurate quantification of trace-level host cell proteins in drug products: Benefits of FAIMS separation and gas-phase fractionation DIA.

Therapeutic monoclonal antibodies (mAb) production relies on multiple purification steps before release as a drug product (DP). A few host cell proteins (HCPs) may co-purify with the mAb. Their monitoring is crucial due to the considerable risk they represent for mAb stability, integrity, and efficacy and their potential immunogenicity. Enzyme-linked immunosorbent assays (ELISA) commonly used for global HCP monitoring present limitations in terms of identification and quantification of individual HCPs. Therefore, liquid chromatography tandem mass spectrometry (LC-MS/MS) has emerged as a promising alternative. Challenging DP samples show an extreme dynamic range requiring high performing methods to detect and reliably quantify trace-level HCPs. Here, we investigated the benefits of adding high-field asymmetric ion mobility spectrometry (FAIMS) separation and gas phase fractionation (GPF) prior to data independent acquisition (DIA). FAIMS LC-MS/MS analysis allowed the identification of 221 HCPs among which 158 were reliably quantified for a global amount of 880ng/mg of NIST mAb Reference Material. Our methods have also been successfully applied to two FDA/EMA approved DPs and allowed digging deeper into the HCP landscape with the identification and quantification of a few tens of HCPs with sensitivity down to the sub-ng/mg of mAb level.

Bringing synapses into focus: Recent advances in synaptic imaging and mass-spectrometry for studying synaptopathy.

Synapses are integral for healthy brain function and are becoming increasingly recognized as key structures in the early stages of brain disease. Understanding the pathological processes driving synaptic dysfunction will unlock new therapeutic opportunities for some of the most devastating diseases of our time. To achieve this we need a solid repertoire of imaging and molecular tools to interrogate synaptic biology at greater resolution. Synapses have historically been examined in small numbers, using highly technical imaging modalities, or in bulk, using crude molecular approaches. However, recent advances in imaging techniques are allowing us to analyze large numbers of synapses, at single-synapse resolution. Furthermore, multiplexing is now achievable with some of these approaches, meaning we can examine multiple proteins at individual synapses in intact tissue. New molecular techniques now allow accurate quantification of proteins from isolated synapses. The development of increasingly sensitive mass-spectrometry equipment means we can now scan the synaptic molecular landscape almost in totality and see how this changes in disease. As we embrace these new technical developments, synapses will be viewed with clearer focus, and the field of synaptopathy will become richer with insightful and high-quality data. Here, we will discuss some of the ways in which synaptic interrogation is being facilitated by methodological advances, focusing on imaging, and mass spectrometry.

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.

Strategies for Increasing the Depth and Throughput of Protein Analysis by plexDIA.

Accurate protein quantification is key to identifying protein markers, regulatory relationships between proteins, and pathophysiological mechanisms. Realizing this potential requires sensitive and deep protein analysis of a large number of samples. Toward this goal, proteomics throughput can be increased by parallelizing the analysis of both precursors and samples using multiplexed data independent acquisition (DIA) implemented by the plexDIA framework: https://plexDIA.slavovlab.net. Here we demonstrate the improved precisions of retention time estimates within plexDIA and how this enables more accurate protein quantification. plexDIA has demonstrated multiplicative gains in throughput, and these gains may be substantially amplified by improving the multiplexing reagents, data acquisition, and interpretation. We discuss future directions for advancing plexDIA, which include engineering optimized mass-tags for high-plexDIA, introducing isotopologous carriers, and developing algorithms that utilize the regular structures of plexDIA data to improve sensitivity, proteome coverage, and quantitative accuracy. These advances in plexDIA will increase the throughput of functional proteomic assays, including quantifying protein conformations, turnover dynamics, modifications states and activities. The sensitivity of these assays will extend to single-cell analysis, thus enabling functional single-cell protein analysis.

Pre-analytical sample handling effects on tear fluid protein levels

Tear fluid is emerging as a source of non-invasive biomarkers, both for ocular and systemic conditions. Accurate quantification of tear proteins can be improved by standardizing methods to collect and process tear fluid. The aim of this study was to determine sample handling factors that may influence the tear protein biomarker profile. Tear fluid was collected using Schirmer’s strips. Tear proteins were extracted by elution through centrifugation. Total protein content was determined using the bicinchoninic acid assay. Key concepts that apply to the entire sample processing cycle are tear sampling, tear storage, protein extraction and data normalization. Differences in wetting or migration length were observed between Schirmer’s strips from different manufacturers, and between protein-free and protein-rich solutions. One unit of migration length (mm) did not correspond to one unit of volume (µL). A positive correlation (r = 0.6671, p < 0.0001) was observed between migration length and total tear protein content. The most beneficial storage conditions were strips that were not stored (+ 21.8%), or underwent ‘wet’ storage (+ 11.1%). Protein recovery was the highest in 400 µL extraction buffer and independent of protein molecular weight. This study helps to explain inter- and intra-variability that is often seen with tear biomarker research. This information is critical to ensure accuracy of test results, as tear biomarkers will be used for patient management and in clinical trials in the near future. This study also highlights the need for standardization of Schirmer’s strip manufacturing, tear fluid processing and analyte concentration normalization.

An Isobaric Labeling Approach to Enhance Detection and Quantification of Tissue-Derived Plasma Proteins as Potential Early Disease Biomarkers.

The proteomic analysis of plasma holds great promise to advance precision medicine and identify biomarkers of disease. However, it is likely that many potential biomarkers circulating in plasma originate from other tissues and are only present in low abundances in the plasma. Accurate detection and quantification of low abundance proteins by standard mass spectrometry approaches remain challenging. In addition, it is difficult to link low abundance plasma proteins back to their specific tissues or organs of origin with confidence. To address these challenges, we developed a mass spectrometry approach based on the use of tandem mass tags (TMT) and a tissue reference sample. By applying this approach to nonhuman primate plasma samples, we were able to identify and quantify 820 proteins by using a kidney tissue homogenate as reference. On average, 643 ± 16 proteins were identified per plasma sample. About 58% of proteins identified in replicate experiments were identified both times. A ratio of 50 μg kidney protein to 10 μg plasma protein, and the use of the TMT label with the highest molecular weight (131) for the kidney reference yielded the largest number of proteins in the analysis, and identified low abundance proteins in plasma that are prominently found in the kidney. Overall, this methodology promises efficient quantification of plasma proteins potentially released from specific tissues, thereby increasing the number of putative disease biomarkers for future study.

Fast and straightforward simultaneous quantification of multiple apolipoproteins in human serum on a high-throughput LC-MS/MS platform.

Apolipoprotein monitoring is useful for diagnosing cardiovascular diseases, as they are risk factors of arteriosclerosis and other neutral fat-related diseases. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is advantageous for simultaneous apolipoprotein quantification, differentiation, and standardization including their isoforms. However, fast and straightforward sample preparation that retains quantification accuracy remains challenging in clinical MS. We developed a simultaneous assay for serum apolipoprotein A-I (ApoA-I), apolipoprotein B100 family, and apolipoprotein C-III (ApoC-III) using a high-throughput LC-MS/MS platform coupled with a BRAVO system. The assay was simplified by using sodium deoxycholate and trypsin/lys-C without reduction and alkylation steps. Simple sample preparation reduced turnaround time by 1.5h and neat goat serum was chosen as an optimal calibration matrix for accurate protein quantification. Assay precision, linearity, correlation, accuracy, limit of detection (LOD), limit of quantitation (LOQ), and carryover were validated according to CLSI guidelines over 41days using more than 100 human serum samples. Good correlation compared with turbidimetric immunoassay (TIA) was observed by Deming regression for all analytes. A high-throughput LC-MS/MS and BRAVO assay for simultaneous apolipoprotein analysis was validated using a simple preparation method with a human serum calibrator in goat serum matrix. The assay is readily expandable to include other target serum proteins and/or their isoforms.

Highly Accurate and Robust Absolute Quantification of Target Proteins in Formalin-Fixed Paraffin-Embedded (FFPE) Tissues by LC-MS.

Accurate, absolute liquid chromatography-mass spectrometry (LC-MS)-based quantification of target proteins in formalin-fixed paraffin-embedded (FFPE) tissues would greatly expand sample availability for pharmaceutical/clinical investigations but remains challenging owing to the following issues: (i) efficient/quantitative recovery of target signature peptides from FFPE tissues is essential but an optimal procedure for targeted, absolute quantification is lacking; (ii) most FFPE samples are long-term-stored; severe immunohistochemistry (IHC) signal losses of target proteins during storage were widely reported, while the effect of storage on LC-MS-based methods was unknown; and (iii) the proper strategy to prepare calibration/quality-control samples to ensure accurate targeted protein analysis in FFPE tissues remained elusive. Using targeted quantification of monoclonal antibody (mAb), antigen, and 40 tissue markers in FFPE tissues as a model system, we extensively investigate those issues and develope an LC-MS-based strategy enabling accurate and precise targeted protein quantification in FFPE samples. First, we demonstrated a surfactant cocktail-based procedure (f-SEPOD), providing high/reproducible recovery of target signature peptides from FFPE tissues. Second, a heat-accelerated degradation study within a roughly estimated 5 year storage period recapitulated the loss of protein IHC signals while LC-MS signals of all targets remained constant. This indicates that the storage of FFPE tissues mainly causes decreased immunoreactivity but unlikely chemical degradation of proteins, which strongly suggests that the storage of FFPE tissues does not cause significant quantitative bias for LC-MS-based methods. Third, while a conventional spike-and-extract approach for calibration caused substantial negative biases, a novel approach, using FFPE-treated calibration standards, enabled accurate and precise quantification. With the pipeline, we conducted the first-ever pharmacokinetics measurement of mAb and its target in FFPE tissues, where time courses by FFPE vs fresh tissues showed excellent correlation.

GwAAP: A genome-wide amino acid coding-decoding quantitative proteomics system.

Mass spectrometry-based proteomic technology has greatly improved and has been widely applied in various biological science fields. However, proteome-wide accurate quantification of proteins in signaling pathways remains challenging. Here, we report a genome-wide amino acid coding-decoding quantitative proteomic (GwAAP) system to facilitate precise proteome quantification. For each protein, a unique code peptide was assigned and incorporated into the N-terminus of the targeted protein and used for identification and quantification. As a proof of principle, we systematically tagged 40 yeast proteins with codes and employed mass spectrometry to decode. We successfully recovered all 40 code peptides with a large and consistent quantitative dynamic range (CV slope <10%, R2>0.8). We further verified the alteration of the glucose and galactose metabolism pathways in yeast under different carbon source conditions. The GwAAP system could potentially provide a strategy to achieve absolute quantification of the entire yeast proteome without bias.

Prediction of Protein Concentration in Pea (Pisum sativum L.) Using Near-Infrared Spectroscopy (NIRS) Systems.

Breeding for increased protein concentration is a priority in field peas. Having a quick, accurate, and non-destructive protein quantification method is critical for screening breeding materials, which the near-infrared spectroscopy (NIRS) system can provide. Partial least square regression (PLSR) models to predict protein concentration were developed and compared for DA7250 and FT9700 NIRS systems. The reference protein data were accurate and exhibited a wider range of variation (15.3-29.8%). Spectral pre-treatments had no clear advantage over analyses based on raw spectral data. Due to the large number of samples used in this study, prediction accuracies remained similar across calibration sizes. The final PLSR models for the DA7250 and FT9700 systems required 10 and 13 latent variables, respectively, and performed well and were comparable (R2 = 0.72, RMSE = 1.22, and bias = 0.003 for DA7250; R2 = 0.79, RMSE = 1.23, and bias = 0.055 for FT9700). Considering three groupings for protein concentration (Low: &lt;20%, Medium: ≥20%, but ≤25%, and High: &gt;25%), none of the entries changed from low to high or vice versa between the observed and predicted values for the DA7250 system. Only a single entry moved from a low category in the observed data to a high category in the predicted data for the FT9700 system in the calibration set. Although the FT9700 system outperformed the DA7250 system by a small margin, both systems had the potential to predict protein concentration in pea seeds for breeding purposes. Wavelengths between 950 nm and 1650 nm accounted for most of the variation in pea protein concentration.

Data-independent acquisition proteomics methods for analyzing post-translational modifications.

Protein post-translational modifications (PTMs) increase the functional diversity of the cellular proteome. Accurate and high throughput identification and quantification of protein PTMs is a key task in proteomics research. Recent advancements in data-independent acquisition (DIA) mass spectrometry (MS) technology have achieved deep coverage and accurate quantification of proteins and PTMs. This review provides an overview of DIA data processing methods that cover three aspects of PTMs analysis, that is, detection of PTMs, site localization, and characterization of complex modification moieties, such as glycosylation. In addition, a survey of deep learning methods that boost DIA-based PTMs analysis is presented, including in silico spectral library generation, as well as feature scoring and error rate control. The limitations and future directions of DIA methods for PTMs analysis are also discussed. Novel data analysis methods will take advantage of advanced MS instrumentation techniques to empower DIA MS for in-depth and accurate PTMs measurements.

Surrogate peptide selection and internal standardization for accurate quantification of endogenous proteins.

Relative quantification techniques have dominated the field of proteomics. However, biomarker discovery, mathematical model development and studies on transporter-mediated drug disposition still need absolute quantification of proteins. The quality of data of trace-level protein quantification is solely dependent on the specific selection of surrogate peptides. Selection of surrogate peptides has a major impact on the accuracy of the method. In this article, the advanced approaches for selection of surrogate peptides, which can provide absolute quantification of the proteinsare discussed. In addition, internal standardization, which accounts for variations in the quantitation processto achieve absolute protein quantification is discussed.

Hydrogel-backed nanopores in proteomic studies

Accurate identification and quantification of proteins in a solution using nanopores is technologically challenging in part because of the large fraction of missed translocation events due to short event times and limitations of conventional current amplifiers. Previously, we have shown that a nanopore interfaced with PEG(1000)-DMA hydrogel significantly enhances protein residence time inside the nanopore, reducing the number of missed events. (Acharya, ACS Sensors 2020) Following up on this work, we also have demonstrated the sensitivity of the hydrogel-backed nanopores to measure unlabeled proteins as small as 5.5 kD in size and 10 fM in concentration.