Clinical applications of MS-based protein quantification

Tutorial review for peptide assays: An ounce of pre-analytics is worth a pound of cure

The recent increase in peptidomimetic-based medications and the growing interest in peptide hormones has brought new attention to the quantification of peptides for diagnostic purposes. Indeed, the circulating concentrations of peptide hormones in the blood provide a snapshot of the state of the body and could eventually lead to detecting a particular health condition. Although extremely useful, the quantification of such molecules, preferably by liquid chromatography coupled to mass spectrometry, might be quite tricky. First, peptides are subjected to hydrolysis, oxidation, and other post-translational modifications, and, most importantly, they are substrates of specific and nonspecific proteases in biological matrixes. All these events might continue after sampling, changing the peptide hormone concentrations. Second, because they include positively and negatively charged groups and hydrophilic and hydrophobic residues, they interact with their environment; these interactions might lead to a local change in the measured concentrations. A phenomenon such as nonspecific adsorption to lab glassware or materials has often a tremendous effect on the concentration and needs to be controlled with particular care. Finally, the circulating levels of peptides might be low (pico- or femtomolar range), increasing the impact of the aforementioned effects and inducing the need for highly sensitive instruments and well-optimized methods. Thus, despite the extreme diversity of these peptides and their matrixes, there is a common challenge for all the assays: the need to keep concentrations unchanged from sampling to analysis. While significant efforts are often placed on optimizing the analysis, few studies consider in depth the impact of pre-analytical steps on the results. By working through practical examples, this solution-oriented tutorial review addresses typical pre-analytical challenges encountered during the development of a peptide assay from the standpoint of a clinical laboratory. We provide tips and tricks to avoid pitfalls as well as strategies to guide all new developments. Our ultimate goal is to increase pre-analytical awareness to ensure that newly developed peptide assays produce robust and accurate results.

Proteomics approaches: A review regarding an importance of proteome analyses in understanding the pathogens and diseases

Proteomics is playing an increasingly important role in identifying pathogens, emerging and re-emerging infectious agents, understanding pathogenesis, and diagnosis of diseases. Recently, more advanced and sophisticated proteomics technologies have transformed disease diagnostics and vaccines development. The detection of pathogens is made possible by more accurate and time-constrained technologies, resulting in an early diagnosis. More detailed and comprehensive information regarding the proteome of any noxious agent is made possible by combining mass spectrometry with various gel-based or short-gun proteomics approaches recently. MALDI-ToF has been proved quite useful in identifying and distinguishing bacterial pathogens. Other quantitative approaches are doing their best to investigate bacterial virulent factors, diagnostic markers and vaccine candidates. Proteomics is also helping in the identification of secreted proteins and their virulence-related functions. This review aims to highlight the role of cutting-edge proteomics approaches in better understanding the functional genomics of pathogens. This also underlines the limitations of proteomics in bacterial secretome research.

Diagnosing pleural effusions using mass spectrometry-based multiplexed targeted proteomics quantitating mid- to high-abundance markers of cancer, infection/inflammation and tuberculosis

Pleural effusion (PE) is excess fluid in the pleural cavity that stems from lung cancer, other diseases like extra-pulmonary tuberculosis (TB) and pneumonia, or from a variety of benign conditions. Diagnosing its cause is often a clinical challenge and we have applied targeted proteomic methods with the aim of aiding the determination of PE etiology. We developed a mass spectrometry (MS)-based multiple reaction monitoring (MRM)-protein-panel assay to precisely quantitate 53 established cancer-markers, TB-markers, and infection/inflammation-markers currently assessed individually in the clinic, as well as potential biomarkers suggested in the literature for PE classification. Since MS-based proteomic assays are on the cusp of entering clinical use, we assessed the merits of such an approach and this marker panel based on a single-center 209 patient cohort with established etiology. We observed groups of infection/inflammation markers (ADA2, WARS, CXCL10, S100A9, VIM, APCS, LGALS1, CRP, MMP9, and LDHA) that specifically discriminate TB-PEs and other-infectious-PEs, and a number of cancer markers (CDH1, MUC1/CA-15-3, THBS4, MSLN, HPX, SVEP1, SPINT1, CK-18, and CK-8) that discriminate cancerous-PEs. Some previously suggested potential biomarkers did not show any significant difference. Using a Decision Tree/Multiclass classification method, we show a very good discrimination ability for classifying PEs into one of four types: cancerous-PEs (AUC: 0.863), tuberculous-PEs (AUC of 0.859), other-infectious-PEs (AUC of 0.863), and benign-PEs (AUC: 0.842). This type of approach and the indicated markers have the potential to assist in clinical diagnosis in the future, and help with the difficult decision on therapy guidance.

Towards Precision Dermatology: Emerging Role of Proteomic Analysis of the Skin

BACKGROUND

The skin is the largest organ in the human body and serves as a multilayered protective shield from the environment as well as a sensor and thermal regulator. However, despite its importance, many details about skin structure and function at the molecular level remain incompletely understood. Recent advances in liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics have enabled the quantification and characterization of the proteomes of a number of clinical samples, including normal and diseased skin.

SUMMARY

Here, we review the current state of the art in proteomic analysis of the skin. We provide a brief overview of the technique and skin sample collection methodologies as well as a number of recent examples to illustrate the utility of this strategy for advancing a broader understanding of the pathology of diseases as well as new therapeutic options.

KEY MESSAGES

Proteomic studies of healthy skin and skin diseases can identify potential molecular biomarkers for improved diagnosis and patient stratification as well as potential targets for drug development. Collectively, efforts such as the Human Skinatlas offer improved opportunities for enhancing clinical practice and patient outcomes.

After another decade: LC-MS/MS became routine in clinical diagnostics

Tandem mass spectrometry - especially in combination with liquid chromatography (LC-MS/MS) - is applied in a multitude of important diagnostic niches of laboratory medicine. It is unquestioned in its routine use and is often unreplaceable by alternative technologies. This overview illustrates the development in the past decade (2009-2019) and intends to provide insight into the current standing and future directions of the field. The instrumentation matured significantly, the applications are well understood, and the in vitro diagnostics (IVD) industry is shaping the market by providing assay kits, certified instruments, and the first laboratory automated LC-MS/MS instruments as an analytical core. In many settings the application of LC-MS/MS is still burdensome with locally lab developed test (LDT) designs relying on highly specialized staff. The current routine applications cover a wide range of analytes in therapeutic drug monitoring, endocrinology including newborn screening, and toxicology. The tasks that remain to be mastered are, for example, the quantification of proteins by means of LC-MS/MS and the transition from targeted to untargeted omics approaches relying on pattern recognition/pattern discrimination as a key technology for the establishment of diagnostic decisions.

Accurate Detection of the Four Most Prevalent Carbapenemases in E. coli and K. pneumoniae by High-Resolution Mass Spectrometry

Background

At present, phenotypic growth inhibition techniques are used in routine diagnostic microbiology to determine antimicrobial resistance of bacteria. Molecular techniques such as PCR are often used for confirmation but are indirect as they detect particular resistance genes. A direct technique would be able to detect the proteins of the resistance mechanism itself. In the present study targeted high resolution mass spectrometry assay was developed for the simultaneous detection of KPC, OXA-48-like, NDM, and VIM carbapenemases.

Methods

Carbapenemase specific target peptides were defined by comparing available sequences in GenBank. Selected peptide sequences were validated using 62 Klebsiella pneumoniae and Escherichia coli isolates containing: 16 KPC, 21 OXA-48-like, 16 NDM, 13 VIM genes, and 21 carbapenemase negative isolates.

Results

For each carbapenemase, two candidate peptides were validated. Method validation was performed in a blinded manner for all 83 isolates. All carbapenemases were detected. The majority was detected by both target peptides. All target peptides were 100% specific in the tested isolates and no peptide carry-over was detected.

Conclusion

The applied targeted bottom-up mass spectrometry technique is able to accurately detect the four most prevalent carbapenemases in a single analysis.

Needle lost in the haystack: multiple reaction monitoring fails to detect Treponema pallidum candidate protein biomarkers in plasma and urine samples from individuals with syphilis

Background: Current syphilis diagnostic strategies are lacking a sensitive manner of directly detecting Treponema pallidum antigens. A diagnostic test that could directly detect T. pallidum antigens in individuals with syphilis would be of considerable clinical utility, especially for the diagnosis of reinfections and for post-treatment serological follow-up.

Methods: In this study, 11 candidate T. pallidum biomarker proteins were chosen according to their physiochemical characteristics, T. pallidum specificity and predicted abundance. Thirty isotopically labelled proteotypic surrogate peptides (hPTPs) were synthesized and incorporated into a scheduled multiple reaction monitoring assay. Protein extracts from undepleted/unenriched plasma (N = 18) and urine (N = 4) samples from 18 individuals with syphilis in various clinical stages were tryptically digested, spiked with the hPTP mixture and analysed with a triple quadruple mass spectrometer.

Results: No endogenous PTPs corresponding to the eleven candidate biomarkers were detected in any samples analysed. To estimate the Limit of Detection (LOD) of a comparably sensitive mass spectrometer (LTQ-Orbitrap), two dilution series of rabbit cultured purified T. pallidum were prepared in PBS. Polyclonal anti- T. pallidum antibodies coupled to magnetic Dynabeads were used to enrich one sample series; no LOD improvement was found compared to the unenriched series. The estimated LOD of MS instruments is 300 T. pallidum/ml in PBS.

Conclusions: Biomarker protein detection likely failed due to the low (femtomoles/liter) predicted concentration of T. pallidum proteins. Alternative sample preparation strategies may improve the detectability of T. pallidum proteins in biofluids.

Pediatric endocrine and metabolic diseases and proteomics

The principles of Predictive, Preventive and Personalized Medicine (PPPM) dictate the need to recognize individual susceptibility to disease in a timely fashion and to offer targeted preventive interventions and treatments. Proteomics is a state-of-the art technology- driven science aiming at expanding our understanding of the pathophysiologic mechanisms that underlie disease, but also at identifying accurate predictive, diagnostic and therapeutic biomarkers, that will eventually promote the implementation of PPPM. In this review, we summarize the wide spectrum of the applications of Mass Spectrometry-based proteomics in the various fields of Pediatric Endocrinology, including Inborn Errors of Metabolism, type 1 diabetes, Adrenal Disease, Metabolic Syndrome and Thyroid disease, ranging from neonatal screening to early recognition of specific at-risk populations for disease manifestations or complications in adult life and to monitoring of disease progression and response to treatment.

SIGNIFICANCE

Proteomics is a state-of-the art technology- driven science aiming at expanding our understanding of the pathophysiologic mechanisms that underlie disease, but also at identifying accurate predictive, diagnostic and therapeutic biomarkers that will eventually lead to successful, targeted, patient-centric, individualized approach of each patient, as dictated by the principles of Predictive, Preventive and Personalized Medicine. In this review, we summarize the wide spectrum of the applications of Mass Spectrometry-based proteomics in the various fields of Pediatric Endocrinology, including Inborn Errors of Metabolism, type 1 diabetes, Adrenal Disease, Metabolic Syndrome and Thyroid disease, ranging from neonatal screening, accurate diagnosis, early recognition of specific at-risk populations for the prevention of disease manifestation or future complications.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

Serum Steroid Ratio Profiles in Prostate Cancer: A New Diagnostic Tool Toward a Personalized Medicine Approach

BACKGROUND

Serum steroids are crucial molecules altered in prostate cancer (PCa). Mass spectrometry (MS) is currently the elected technology for the analysis of steroids in diverse biological samples. Steroids have complex biological pathways and stoichiometry and it is important to evaluate their quantitative ratio. MS applications to patient hormone profiling could lead to a diagnostic approach.

METHODS

Here, we employed the Surface Activated Chemical Ionization-Electrospray-NIST (SANIST) developed in our laboratories, to obtain quantitative serum steroid ratio relationship profiles with a machine learning Bayesian model to discriminate patients with PCa. The approach is focused on steroid relationship profiles and disease association.

RESULTS

A pilot study on patients affected by PCa, benign prostate hypertrophy (BPH), and control subjects [prostate-specific antigen (PSA) lower than 2.5 ng/mL] was done in order to investigate the classification performance of the SANIST platform. The steroid profiles of 71 serum samples (31 controls, 20 patients with PCa and 20 subjects with benign prostate hyperplasia) were evaluated. The levels of 10 steroids were quantitated on the SANIST platform: Aldosterone, Corticosterone, Cortisol, 11-deoxycortisol, Androstenedione, Testosterone, dehydroepiandrosterone, dehydroepiandrosterone sulfate (DHEAS), 17-OH-Progesterone and Progesterone. We performed both traditional and a machine learning analysis.

CONCLUSION

We show that the machine learning approach based on the steroid relationships developed here was much more accurate than the PSA, DHEAS, and direct absolute value match method in separating the PCa, BPH and control subjects, increasing the sensitivity to 90% and specificity to 84%. This technology, if applied in the future to a larger number of samples will be able to detect the individual enzymatic disequilibrium associated with the steroid ratio and correlate it with the disease. This learning machine approach could be valid in a personalized medicine setting.

Plasma protein absolute quantification by nano-LC Q-TOF UDMSE for clinical biomarker verification

Background and aims

Proteome-based biomarker studies are targeting proteins that could serve as diagnostic, prognosis, and prediction molecules. In the clinical routine, immunoassays are currently used for the absolute quantification of such biomarkers, with the major limitation that only one molecule can be targeted per assay. The aim of our study was to test a mass spectrometry based absolute quantification method for the verification of plasma protein sets which might serve as reliable biomarker panels for the clinical practice.

Methods

Six EDTA plasma samples were analyzed after tryptic digestion using a high throughput data independent acquisition nano-LC Q-TOF UDMS^E proteomics approach. Synthetic Escherichia coli standard peptides were spiked in each sample for the absolute quantification. Data analysis was performed using ProgenesisQI v2.0 software (Waters Corporation).

Results

Our method ensured absolute quantification of 242 non redundant plasma proteins in a single run analysis. The dynamic range covered was 105. 86% were represented by classical plasma proteins. The overall median coefficient of variation was 0.36, while a set of 63 proteins was found to be highly stable. Absolute protein concentrations strongly correlated with values reviewed in the literature.

Conclusions

Nano-LC Q-TOF UDMS^E proteomic analysis can be used for a simple and rapid determination of absolute amounts of plasma proteins. A large number of plasma proteins could be analyzed, while a wide dynamic range was covered with low coefficient of variation at protein level. The method proved to be a reliable tool for the quantification of protein panel for biomarker verification in the clinical practice.

Multiplexed MRM-Based Protein Quantitation Using Two Different Stable Isotope-Labeled Peptide Isotopologues for Calibration

When quantifying endogenous plasma proteins for fundamental and biomedical research - as well as for clinical applications - precise, reproducible, and robust assays are required. Targeted detection of peptides in a bottom-up strategy is the most common and precise mass spectrometry-based quantitation approach when combined with the use of stable isotope-labeled peptides. However, when measuring protein in plasma, the unknown endogenous levels prevent the implementation of the best calibration strategies, since no blank matrix is available. Consequently, several alternative calibration strategies are employed by different laboratories. In this study, these methods were compared to a new approach using two different stable isotope-labeled standard (SIS) peptide isotopologues for each endogenous peptide to be quantified, enabling an external calibration curve as well as the quality control samples to be prepared in pooled human plasma without interference from endogenous peptides. This strategy improves the analytical performance of the assay and enables the accuracy of the assay to be monitored, which can also facilitate method development and validation.

Polyion oligonucleotide-decorated gold nanoparticles with tunable surface charge density for amplified signal output of potentiometric immunosensor

Methods based on nanostructures have been developed for potentiometric immunosensors, but most involve low sensitivity or weak signal output and are unsuitable for routine use in diagnosis. Herein, we devise an in-situ signal-amplification strategy for enhanced electrical readout of potentiometric immunosensor toward target prostate-specific antigen (PSA, one kind of cancer biomarkers), based on polyion oligonucleotide-labeled gold nanoparticles (AuNPs). To decrease the background signal, monoclonal anti-human PSA capture antibody was covalently conjugated onto an activated glassy carbon electrode via typical carbodiimide coupling. AuNPs heavily functionalized with the polyion oligonucleotides and polyclonal anti-PSA detection antibodies (pAb₂-AuNP-DNA) were utilized as the signal-generation nanotags. In the presence of target PSA, a sandwich-type immunoreaction was executed between capture antibody and detection antibody on the electrode. The detectable signal derived from the shift in the electric potential as a result of the change in the surface charge before and after the antigen-antibody reaction. With target PSA increased, the captured pAb₂-AuNP-DNA to the electrode accompanying detection antibody increased, thereby resulting in the change of the electrode potential. Due to numerous polyion oligonucleotides with the negative charge, the signal readout amplified. Under the optimal conditions, the shift in the output potential was proportional to the logarithm of target PSA concentration and displayed a dynamic linear range from 0.05 to 20 ng mL^-1 with a detection limit of 13.6 pg mL^-1. An intermediate precision of ≤13.2% was accomplished with the batch-to-batch identification. The selectivity was acceptable. The method accuracy was evaluated for human serum specimens, and gave the consistent results between the potentiometric immunosensor and the referenced enzyme-linked immunosorbent assay (ELISA).

Error analysis in newborn screening: can quotients support the absolute values?

Newborn screening is performed using modern tandem mass spectrometry, which can simultaneously detect a variety of analytes, including several amino acids and fatty acids. Tandem mass spectrometry measures the diagnostic parameters as absolute concentrations and produces fragments which are used as markers of specific substances. Several prominent quotients can also be derived, which are quotients of two absolute measured concentrations. In this study, we determined the precision of both the absolute concentrations and the derived quotients. First, the measurement error of the absolute concentrations and the measurement error of the ratios were practically determined. Then, the Gaussian theory of error calculation was used. Finally, these errors were compared with one another. The practical analytical accuracies of the quotients were significantly higher (e.g., coefficient of variation (CV) = 5.1% for the phenylalanine to tyrosine (Phe/Tyr) quotient and CV = 5.6% for the Fisher quotient) than the accuracies of the absolute measured concentrations (mean CVs = 12%). According to our results, the ratios are analytically correct and, from an analytical point of view, can support the absolute values in finding the correct diagnosis.

Proteomics progresses in microbial physiology and clinical antimicrobial therapy

Clinical microbial identification plays an important role in optimizing the management of infectious diseases and provides diagnostic and therapeutic support for clinical management. Microbial proteomic research is aimed at identifying proteins associated with microbial activity, which has facilitated the discovery of microbial physiology changes and host–pathogen interactions during bacterial infection and antimicrobial therapy. Here, we summarize proteomic-driven progresses of host–microbial pathogen interactions at multiple levels, mass spectrometry-based microbial proteome identification for clinical diagnosis, and antimicrobial therapy. Proteomic technique progresses pave new ways towards effective prevention and drug discovery for microbial-induced infectious diseases.

Personalized Proteomics: The Future of Precision Medicine

Medical diagnostics and treatment has advanced from a one size fits all science to treatment of the patient as a unique individual. Currently, this is limited solely to genetic analysis. However, epigenetic, transcriptional, proteomic, posttranslational modifications, metabolic, and environmental factors influence a patient’s response to disease and treatment. As more analytical and diagnostic techniques are incorporated into medical practice, the personalized medicine initiative transitions to precision medicine giving a holistic view of the patient’s condition. The high accuracy and sensitivity of mass spectrometric analysis of proteomes is well suited for the incorporation of proteomics into precision medicine. This review begins with an overview of the advance to precision medicine and the current state of the art in technology and instrumentation for mass spectrometry analysis. Thereafter, it focuses on the benefits and potential uses for personalized proteomic analysis in the diagnostic and treatment of individual patients. In conclusion, it calls for a synthesis between basic science and clinical researchers with practicing clinicians to design proteomic studies to generate meaningful and applicable translational medicine. As clinical proteomics is just beginning to come out of its infancy, this overview is provided for the new initiate.

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.