Advances in quadrupole and time-of-flight mass spectrometry for peptide MRM based translational research analysis

Predicting ion mobility collision cross sections and assessing prediction variation by combining conventional and data driven modeling

The use of collision cross section (CCS) values derived from ion mobility studies is proving to be an increasingly important tool in the characterization and identification of molecules detected in complex mixtures. Here, a novel machine learning (ML) based method for predicting CCS integrating both molecular modeling (MM) and ML methodologies has been devised and shown to be able to accurately predict CCS values for singly charged small molecular weight molecules from a broad range of chemical classes. The model performed favorably compared to existing models, improving compound identifications for isobaric analytes in terms of ranking and assigning identification probability values to the annotation. Furthermore, charge localization was seen to be correlated with CCS prediction accuracy and with gas-phase proton affinity demonstrating the potential to provide a proxy for prediction error based on chemical structural properties. The presented approach and findings represent a further step towards accurate prediction and application of computationally generated CCS values.

A high throughput immuno-affinity mass spectrometry method for detection and quantitation of SARS-CoV-2 nucleoprotein in human saliva and its comparison with RT-PCR, RT-LAMP, and lateral flow rapid antigen test

OBJECTIVES

Many reverse transcription polymerase chain reaction (RT-PCR) methods exist that can detect SARS-CoV-2 RNA in different matrices. RT-PCR is highly sensitive, although viral RNA may be detected long after active infection has taken place. SARS-CoV-2 proteins have shorter detection windows hence their detection might be more meaningful. Given salivary droplets represent a main source of transmission, we explored the detection of viral RNA and protein using four different detection platforms including SISCAPA peptide immunoaffinity liquid chromatography-mass spectrometry (SISCAPA-LC-MS) using polyclonal capture antibodies.

METHODS

The SISCAPA-LC MS method was compared to RT-PCR, RT-loop-mediated isothermal amplification (RT-LAMP), and a lateral flow rapid antigen test (RAT) for the detection of virus material in the drool saliva of 102 patients hospitalised after infection with SARS-CoV-2. Cycle thresholds (Ct) of RT-PCR (E gene) were compared to RT-LAMP time-to-positive (TTP) (NE and Orf1a genes), RAT optical densitometry measurements (test line/control line ratio) and to SISCAPA-LC-MS for measurements of viral protein.

RESULTS

SISCAPA-LC-MS showed low sensitivity (37.7 %) but high specificity (89.8 %). RAT showed lower sensitivity (24.5 %) and high specificity (100 %). RT-LAMP had high sensitivity (83.0 %) and specificity (100.0 %). At high initial viral RNA loads (<20 Ct), results obtained using SISCAPA-LC-MS correlated with RT-PCR (R2 0.57, p-value 0.002).

CONCLUSIONS

Detection of SARS-CoV-2 nucleoprotein in saliva was less frequent than the detection of viral RNA. The SISCAPA-LC-MS method allowed processing of multiple samples in <150 min and was scalable, enabling high throughput.

The Edge Effect in High-Throughput Proteomics: A Cautionary Tale

In order for mass spectrometry to continue to grow as a platform for high-throughput clinical and translational research, careful consideration must be given to quality control by ensuring that the assay performs reproducibly and accurately and precisely. In particular, the throughput required for large cohort clinical validation in biomarker discovery and diagnostic screening has driven the growth of multiplexed targeted liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) assays paired with sample preparation and analysis in multiwell plates. However, large scale MS-based proteomics studies are often plagued by batch effects: sources of technical variation in the data, which can arise from a diverse array of sources such as sample preparation batches, different reagent lots, or indeed MS signal drift. These batch effects can confound the detection of true signal differences, resulting in incorrect conclusions being drawn about significant biological effects or lack thereof. Here, we present an intraplate batch effect termed the edge effect arising from temperature gradients in multiwell plates, commonly reported in preclinical cell culture studies but not yet reported in a clinical proteomics setting. We present methods herein to ameliorate the phenomenon including proper assessment of heating techniques for multiwell plates and incorporation of surrogate standards, which can normalize for intraplate variation.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Mass spectrometric detection of KRAS protein mutations using molecular imprinting

Cancer is a disease of cellular evolution where single base changes in the genetic code can have significant impact on the translation of proteins and their activity. Thus, in cancer research there is significant interest in methods that can determine mutations and identify the significant binding sites (epitopes) of antibodies to proteins in order to develop novel therapies. Nano molecularly imprinted polymers (nanoMIPs) provide an alternative to antibodies as reagents capable of specifically capturing target molecules depending on their structure. In this study, we used nanoMIPs to capture KRAS, a critical oncogene, to identify mutations which when present are indicative of oncological progress. Herein, coupling nanoMIPs (capture) and liquid chromatography-mass spectrometry (detection), LC-MS has allowed us to investigate mutational assignment and epitope discovery. Specifically, we have shown epitope discovery by generating nanoMIPs to a recombinant KRAS protein and identifying three regions of the protein which have been previously assigned as epitopes using much more time-consuming protocols. The mutation status of the released tryptic peptide was identified by LC-MS following capture of the conserved region of KRAS using nanoMIPS, which were tryptically digested, thus releasing the sequence of a non-conserved (mutated) region. This approach was tested in cell lines where we showed the effective genotyping of a KRAS cell line and in the plasma of cancer patients, thus demonstrating its ability to diagnose precisely the mutational status of a patient. This work provides a clear line-of-sight for the use of nanoMIPs to its translation from research into diagnostic and clinical utility.

Advances in Cardiovascular Biomarker Discovery

Cardiovascular diseases are the leading causes of mortality worldwide. Among them, hypertension and its pathological complications pose a major risk for the development of other cardiovascular diseases, including heart failure and stroke. Identifying novel and early stage biomarkers of hypertension and other cardiovascular diseases is of paramount importance in predicting and preventing the major morbidity and mortality associated with these diseases. Biomarkers of such diseases or predisposition to their development are identified by changes in a specific indicator’s expression between healthy individuals and patients. These include changes in protein and microRNA (miRNA) levels. Protein profiling using mass spectrometry and miRNA screening utilizing microarray and sequencing have facilitated the discovery of proteins and miRNA as biomarker candidates. In this review, we summarized some of the different, promising early stage protein and miRNA biomarker candidates as well as the currently used biomarkers for hypertension and other cardiovascular diseases. Although a number of promising markers have been identified, it is unlikely that a single biomarker will unambiguously aid in the classification of these diseases. A multi-marker panel-strategy appears useful and promising for classifying and refining risk stratification among patients with cardiovascular disease.

Proteomic Characterization of Circulating Molecular Perturbations Associated With Pancreatic Adenocarcinoma Following Intravenous ω-3 Fatty Acid and Gemcitabine Administration: A Pilot Study

BACKGROUND

Administration of intravenous ω-3 fatty acid (ω-3FA) in advanced pancreatic adenocarcinoma patients receiving gemcitabine chemotherapy shows disease stabilization and improved progression-free survival. Using high-definition plasma proteomics, the underlying biological mechanisms responsible for these clinical effects are investigated.

METHODS AND RESULTS

A pilot study involving plasma that was collected at baseline from 13 patients with histologically confirmed, unresectable pancreatic adenocarcinoma (baseline group) after 1-month treatment with intravenous gemcitabine and ω-3FA (treatment group) and intravenous gemcitabine only (control group) and was prepared for proteomic analysis. A 2-arm study comparing baseline vs treatment and treatment vs control was performed. Proteins were isolated from plasma with extensive immunodepletion, then digested and labeled with isobaric tandem mass tag peptide tags. Samples were then combined, fractionated, and injected into a QExactive-Orbitrap Mass-Spectrometer and analyzed on Proteome Discoverer and Scaffold with ensuing bioinformatics analysis. Selective reaction monitoring analysis was performed for verification. In total, 3476 proteins were identified. Anti-inflammatory markers (C-reactive protein, haptoglobin, and serum amyloid-A1) were reduced in the treatment group. Enrichment analysis showed angiogenesis downregulation, complement immune systems upregulation, and epigenetic modifications on histones. Pathway analysis identified direct action via the Pi3K-AKT pathway. Serum amyloid-A1 significantly reduced (P < .001) as a potential biomarker of efficacy for ω-3FA.

CONCLUSIONS

This pilot study demonstrates administration of ω-3FA has potential anti-inflammatory, antiangiogenic, and proapoptotic effects via direct interaction with cancer-signaling pathways in patients with advanced pancreatic adenocarcinoma. Further studies in a larger sample size is required to validate the clinical correlation found in this preliminary study.

Analytical techniques for multiplex analysis of protein biomarkers

INTRODUCTION

The importance of biomarkers for pharmaceutical drug development and clinical diagnostics is more significant than ever in the current shift toward personalized medicine. Biomarkers have taken a central position either as companion markers to support drug development and patient selection, or as indicators aiming to detect the earliest perturbations indicative of disease, minimizing therapeutic intervention or even enabling disease reversal. Protein biomarkers are of particular interest given their central role in biochemical pathways. Hence, capabilities to analyze multiple protein biomarkers in one assay are highly interesting for biomedical research.

AREAS COVERED

We here review multiple methods that are suitable for robust, high throughput, standardized, and affordable analysis of protein biomarkers in a multiplex format. We describe innovative developments in immunoassays, the vanguard of methods in clinical laboratories, and mass spectrometry, increasingly implemented for protein biomarker analysis. Moreover, emerging techniques are discussed with potentially improved protein capture, separation, and detection that will further boost multiplex analyses.

EXPERT COMMENTARY

The development of clinically applied multiplex protein biomarker assays is essential as multi-protein signatures provide more comprehensive information about biological systems than single biomarkers, leading to improved insights in mechanisms of disease, diagnostics, and the effect of personalized medicine.

A multiple reaction monitoring method for determining peanut (Arachis hypogea) allergens in serum using quadrupole and time-of-flight mass spectrometry

Peanut is a major cause of severe IgE-mediated food allergic reactions, which can be exacerbated by factors, such as exercise, that may increase allergen uptake into the circulation. Enzyme-linked immunosorbent assays (ELISAs) have been used to determine allergen uptake into serum, but there are concerns over their specificity and a confirmatory method is required. Mass spectrometry (MS) methods have the potential to provide rigorous alternatives for allergen determination. A suite of peptide targets representing the major clinically relevant peanut allergens previously applied in food analysis were used to develop a targeted multiple reaction monitoring (MRM) method for determination of peanut in serum. Depletion of serum using affinity chromatography was found to be essential to allow detection of the peptide targets. A comparison of triple quadrupole and Q-TOF methods showed that one Ara h 2 peptide was only detected by the Q-TOF, the other peptide targets giving similar assay sensitivities with both MS platforms, although transitions for all the peptides were detected more consistently with the Q-TOF. The Q-TOF MRM assay detected peanut from spiked serum more effectively than the triple quadrupole assay, with Ara h 3 being detected down to 3 mg total peanut protein/L of serum, comparable with an Ara h 3-specific ELISA. The poor recoveries observed for both methods are likely due to loss of peanut immune complexes during the serum depletion process. Nevertheless, the Q-TOF MRM method has much promise to confirm the uptake of peanut proteins in serum samples providing immune complexes can be disrupted effectively prior to depletion. Graphical abstract.

An Analytical Perspective on Protein Analysis and Discovery Proteomics by Ion Mobility-Mass Spectrometry

Ion mobility combined with mass spectrometry (IM-MS) is a powerful technique for the analysis of biomolecules and complex mixtures. This chapter reviews the current state-of-the-art in ion mobility technology and its application to biology, protein analysis, and quantitative discovery proteomics in particular, from an analytical perspective. IM-MS can be used as a technique to separate mixtures, to determine structural information (rotationally averaged cross-sectional area) and to enhance MS duty cycle and sensitivity. Moreover, IM-MS is ideally suited for hyphenating with liquid chromatography, or other front-end separation techniques such as, GC, microcolumn LC, capillary electrophoresis, and direct analysis, including MALDI and DESI, providing an semiorthogonal layer of separation, which affords the more unambiguous and confident detection of a wide range of analytes. To illustrate these enhancements, as well as recent developments, the principle of in-line IM separation and hyphenation to orthogonal acceleration time-of-flight mass spectrometers are discussed, in addition to the enhancement of biophysical MS-based analysis using typical proteomics and related application examples.

A cost-effective method for purification and characterization of human urinary albumin

We describe a simplified approach for the purification and characterization of urinary albumin, a key biomarker currently used for understanding the onset and prognosis of microalbuminuria. Urinary albumin was purified from human urine collected from diabetic kidney disease patients by using 2-stage tangential flow filtration process and set of column chromatography steps. The relative molecular mass of urinary albumin is 66,871 Da (SYNAPT G2 High Definition Mass Spectrometry System). Isolated urinary albumin was analyzed by SDS-PAGE, Western blotting, immunoelectrophoresis, Ouchterlony double-immunodiffusion, single radial immunodiffusion, size-exclusion HPLC and peptide mass fingerprint analysis. The size-exclusion HPLC elution profile of the purified urinary albumin was similar to that of a reference form of native albumin. Peptide mass fingerprint analysis of the purified urinary albumin yielded peptides that partially matched with known sequence of ALBU_HUMAN (P02768). This is the first report of purification and validation of immunochemically reactive form of urinary albumin from a large volume of urine of diabetic kidney disease patients. In this purification approach, the cost of the purified albumin is significantly lower.

An HS-MRM Assay for the Quantification of Host-cell Proteins in Protein Biopharmaceuticals by Liquid Chromatography Ion Mobility QTOF Mass Spectrometry

The analysis of low-level (1-100 ppm) protein impurities (e.g., host-cell proteins (HCPs)) in protein biotherapeutics is a challenging assay requiring high sensitivity and a wide dynamic range. Mass spectrometry-based quantification assays for proteins typically involve protein digestion followed by the selective reaction monitoring/multiple reaction monitoring (SRM/MRM) quantification of peptides using a low-resolution (Rs ~1,000) tandem quadrupole mass spectrometer. One of the limitations of this approach is the interference phenomenon observed when the peptide of interest has the "same" precursor and fragment mass (in terms of m/z values) as other co-eluting peptides present in the sample (within a 1-Da window). To avoid this phenomenon, we propose an alternative mass spectrometric approach, a high selectivity (HS) MRM assay that combines the ion mobility separation of peptide precursors with the high-resolution (Rs ~30,000) MS detection of peptide fragments. We explored the capabilities of this approach to quantify low-abundance peptide standards spiked in a monoclonal antibody (mAb) digest and demonstrated that it has the sensitivity and dynamic range (at least 3 orders of magnitude) typically achieved in HCP analysis. All six peptide standards were detected at concentrations as low as 0.1 nM (1 femtomole loaded on a 2.1-mm ID chromatographic column) in the presence of a high-abundance peptide background (2 µg of a mAb digest loaded on-column). When considering the MW of rabbit phosphorylase (97.2 kDa), from which the spiked peptides were derived, the LOQ of this assay is lower than 50 ppm. Relative standard deviations (RSD) of peak areas (n = 4 replicates) were less than 15% across the entire concentration range investigated (0.1-100 nM or 1-1,000 ppm) in this study.