Sample preparation for serum/plasma profiling and biomarker identification by mass spectrometry

Raman spectroscopic analysis of human blood serum of glaucoma patients supplemented with macular pigment carotenoids

As all major dietary carotenoids are contained in blood, it is a suitable substrate to evaluate their content, in vivo. Following 18-month supplementation of open-angle glaucoma patients with macula-pigment carotenoids (Lutein, Zeaxanthin and Meso-Zeaxanthin) in the European Nutrition in Glaucoma Management trial, Raman spectroscopic analysis of the carotenoid content of pre- and post-supplementation participant blood serum was carried out, to investigate the systemic impact of the supplementation regimen and explore a more direct way of quantifying this impact using routine blood tests. Using a 532 nm laser source for optimal response, a consistent increase in serum carotenoid concentration was observed in the supplemented serum, highest in patients with initial high baseline carotenoid content. A shift in the 1519 cm-1 carotenoid peak also revealed differences in the carotenoid structural profile of the two groups. The findings highlight the potential of Raman spectroscopy toquantify and differentiate carotenoids directly in blood serum.

Phosphoproteomics analysis of serum from dogs affected with pulmonary hypertension secondary to degenerative mitral valve disease

Pulmonary hypertension (PH), a common complication in dogs affected by degenerative mitral valve disease (DMVD), is a progressive disorder characterized by increased pulmonary arterial pressure (PAP) and pulmonary vascular remodeling. Phosphorylation of proteins, impacting vascular function and cell proliferation, might play a role in the development and progression of PH. Unlike gene or protein studies, phosphoproteomic focuses on active proteins that function as end-target proteins within signaling cascades. Studying phosphorylated proteins can reveal active contributors to PH development. Early diagnosis of PH is crucial for effective management and improved clinical outcomes. This study aimed to identify potential serum biomarkers for diagnosing PH in dogs affected with DMVD using a phosphoproteomic approach. Serum samples were collected from healthy control dogs (n = 28), dogs with DMVD (n = 24), and dogs with DMVD and PH (n = 29). Phosphoproteins were enriched from the serum samples and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Data analysis was performed to identify uniquely expressed phosphoproteins in each group and differentially expressed phosphoproteins among groups. Phosphoproteomic analysis revealed nine uniquely expressed phosphoproteins in the serum of dogs in the DMVD+PH group and 15 differentially upregulated phosphoproteins in the DMVD+PH group compared to the DMVD group. The phosphoproteins previously implicated in PH and associated with pulmonary arterial remodeling, including small nuclear ribonucleoprotein G (SNRPG), alpha-2-macroglobulin (A2M), zinc finger and BTB domain containing 42 (ZBTB42), hemopexin (HPX), serotransferrin (TRF) and complement C3 (C3), were focused on. Their unique expression and differential upregulation in the serum of DMVD dogs with PH suggest their potential as biomarkers for PH diagnosis. In conclusion, this phosphoproteomic study identified uniquely expressed and differentially upregulated phosphoproteins in the serum of DMVD dogs with PH. Further studies are warranted to validate the diagnostic utility of these phosphoproteins.

Metabolomic insights into the therapeutic mechanisms of costus (Saussurea costus (Falc.) Lipsch.) root extract in propylthiouracil-induced hypothyroidism rat model

ETHNOPHARMACOLOGICAL RELEVANCE

Saussurea costus (Falc.) Lipschitz. is one of the most reputed medicinal plants as a traditional medicine in the Arab and Middle East regions in the treatment of thyroid disorders, however, more investigations are needed to fully understand its effectiveness and mechanism of action.

AIM OF THE STUDY

The primary objective of the study was to assess the impact of Saussurea costus (COST) on the metabolic profiles of propylthiouracil (PTU)-induced hypothyroidism in rats. This involves a comprehensive examination of serum metabolites using UPLC/QqQ-MS analysis aiming to identify differential metabolites, elucidate underlying mechanisms, and evaluate the potential pharmacological effect of COST in restoring metabolic homeostasis.

MATERIALS AND METHODS

Hypothyroidism was induced in female Sprague-Dawley rats by oral administration of propylthiouracil (PTU). UPLC/QqQ MS analysis of serum samples from normal, PTU, and PTU + COST rats was utilized for annotation of intrinsic metabolites with the aid of online Human metabolome database (HMDB) and extensive literature surfing. Multivariate statistical analyses, including orthogonal partial least squares discriminant analysis (OPLS-DA), discerned variations between the different groups. Serum levels of T3, T4 and TSH in addition to arachidonic acid (ARA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) levels in thyroid gland tissues; Phospholipase A2 group IIA (PLA2G2A), and lipoprotein lipase (LPL) in liver tissues were assessed by specific ELISA kits. Gene expression for key proteins of the primary evolved pathwayswere quantified by one-step qRT-PCR technique. Histopathological evaluation of thyroid gland tissue was performed by an investigator blinded to the experimental group using light microscope.

RESULTS

Distinct clustering in multivariate statistical analysis models indicated significant variations in serum chemical profiles among normal, disease, and treated groups. VIP values guided the selection of differential metabolites, revealing significant changes in metabolite concentrations. Subsequent to COST treatment, 43 differential intrinsic metabolites exhibited a notable tendency to revert towards normal levels. Annotated metabolites, such as lysophosphatidylcholine (LPC), L-acetylcarnitine, gamma-glutamylserine, and others, showed differential regulation in response to PTU and subsequent S. costus treatment. Notably, 21 metabolites were associated with polyunsaturated fatty acids (PUFAs) biosynthesis, arachidonic acid (ARA) metabolism, and glycerophospholipid metabolism exhibited significant changes on conducting metabolic pathway analysis.

CONCLUSIONS

COST improves PTU-induced hypothyroidism by regulating biosynthesis of PUFAs signified by n-3/n-6, ARA and glycerophospholipid metabolism. The study provides us a novel mechanism to explain the improvement of hypothyroidism and associated dyslipidemia by COST, depicts a metabolic profile of hypothyroidism, and gives us another point cut for further exploring the biomarkers and pathogenesis of hypothyroidism.

Proteomic analysis of the serum in dogs with pulmonary hypertension secondary to myxomatous mitral valve disease: the preliminary study

Background

Pulmonary hypertension (PH) is a common complication in dogs with myxomatous mitral valve disease (MMVD), characterized by elevated blood pressure in pulmonary artery. Echocardiography is a reliable technique for PH diagnosis in veterinary medicine. However, it is limited to use as an early detection method. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has found extensive application in the discovery of serum protein biomarkers for various diseases. The objective of this study was to identify serum proteins in healthy control dogs and MMVD dogs both with and without PH using LC-MS/MS.

Materials and methods

In this research, a total of 81 small-breed dogs participated, and they were categorized into three groups: the control (n = 28), MMVD (n = 24) and MMVD+PH (n = 29) groups. Serum samples were collected and analyzed by LC-MS/MS.

Results

Differentially expressed proteins were identified, and the upregulated and downregulated proteins in MMVD+PH group including Myomesin 1 (MYOM1) and Histone deacetylase 7 (HDAC7), Pleckstrin homology domain containing M3 (PLEKHM3), Diacylglycerol lipase alpha (DAGLA) and Tubulin tyrosine ligase like 6 (TTLL6) were selected as proteins of interest in MMVD dogs with PH.

Conclusion

Different types of proteins have been identified in healthy dogs and MMVD dogs with and without PH. Additional studies are needed to investigate the potential of these proteins as biomarkers for PH in dogs with MMVD.

Proteomics of prostate cancer serum and plasma using low and high throughput approaches

Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations in biomarker and disease studies. In this work, we used cutting-edge proteomics technologies to construct label-based and label-free workflows, capable of quantifying approximately 2,000 proteins in biofluids. With 70µL of blood and a single depletion strategy, we conducted an analysis of a homogenous cohort (n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) to healthy donors. The results revealed dozens of differentially expressed proteins in both plasma and serum. We identified the upregulation of Prostate Specific Antigen (PSA), a well-known biomarker for prostate cancer, in the serum of cancer cohort. Further bioinformatics analysis highlighted noteworthy proteins which appear to be differentially secreted into the bloodstream, making them good candidates for further exploration.

3D Superclusters with Hybrid Bioinks for Early Detection in Breast Cancer

The surface-enhanced Raman scattering (SERS) technique has garnered significant interest due to its ultrahigh sensitivity, making it suitable for addressing the growing demand for disease diagnosis. In addition to its sensitivity and uniformity, an ideal SERS platform should possess characteristics such as simplicity in manufacturing and low analyte consumption, enabling practical applications in complex diagnoses including cancer. Furthermore, the integration of machine learning algorithms with SERS can enhance the practical usability of sensing devices by effectively classifying the subtle vibrational fingerprints produced by molecules such as those found in human blood. In this study, we demonstrate an approach for early detection of breast cancer using a bottom-up strategy to construct a flexible and simple three-dimensional (3D) plasmonic cluster SERS platform integrated with a deep learning algorithm. With these advantages of the 3D plasmonic cluster, we demonstrate that the 3D plasmonic cluster (3D-PC) exhibits a significantly enhanced Raman intensity through detection limit down to 10-6 M (femtomole-(10-17 mol)) for p-nitrophenol (PNP) molecules. Afterward, the plasma of cancer subjects and healthy subjects was used to fabricate the bioink to build 3D-PC structures. The collected SERS successfully classified into two clusters of cancer subjects and healthy subjects with high accuracy of up to 93%. These results highlight the potential of the 3D plasmonic cluster SERS platform for early breast cancer detection and open promising avenues for future research in this field.

Improved Screening of Monoclonal Gammopathy Patients by MALDI-TOF Mass Spectrometry

Monoclonal gammopathies are a group of blood diseases characterized by presence of abnormal immunoglobulins in peripheral blood and/or urine of patients. Multiple myeloma and plasma cell leukemia are monoclonal gammopathies with unclear etiology, caused by malignant transformation of bone marrow plasma cells. Mass spectrometry with matrix-assisted laser desorption/ionization and time-of-flight detection is commonly used for investigation of the peptidome and small proteome of blood plasma with high accuracy, robustness, and cost-effectivity. In addition, mass spectrometry coupled with advanced statistics can be used for molecular profiling, classification, and diagnosis of liquid biopsies and tissue specimens in various malignancies. Despite the fact there have been fully optimized protocols for mass spectrometry of normal blood plasma available for decades, in monoclonal gammopathy patients, the massive alterations of biophysical and biochemical parameters of peripheral blood plasma often limit the mass spectrometry measurements. In this paper, we present a new two-step extraction protocol and demonstrated the enhanced resolution and intensity (>50×) of mass spectra obtained from extracts of peripheral blood plasma from monoclonal gammopathy patients. When coupled with advanced statistics and machine learning, the mass spectra profiles enabled the direct identification, classification, and discrimination of multiple myeloma and plasma cell leukemia patients with high accuracy and precision. A model based on PLS-DA achieved the best performance with 71.5% accuracy (95% confidence interval, CI = 57.1-83.3%) when the 10× repeated 5-fold CV was performed. In summary, the two-step extraction protocol improved the analysis of monoclonal gammopathy peripheral blood plasma samples by mass spectrometry and provided a tool for addressing the complex molecular etiology of monoclonal gammopathies.

Comparative targeted metabolomic profiles of porcine plasma and serum

Metabolomics has been used to characterise many biological matrices and obtain detailed pictures of biological systems based on many metabolites. Plasma and serum are two blood-derived biofluids commonly used to assess and monitor the organismal metabolism and obtain information on the physiological and health conditions of an animal. Plasma is the supernatant that is separated from the cellular components after centrifugation of the blood that is first added with an anticoagulant. Serum is obtained after centrifugation of the blood that has been coagulated. The choice of one or the other biofluid for metabolomic analyses is related to specific analytical needs and technical issues, to problems derived by the collection and preparation steps, in particular when specimens are sampled from animals involved in field studies. Thus far, most of the metabolomic studies that compared plasma and serum have been carried out in humans and very little is known on the pigs. In this study, we used a targeted metabolomic platform that can detect about 180 metabolites of five biochemical classes to compare plasma and serum profiles of samples collected from 24 pigs. To also obtain a cross-species comparative metabolomic analysis, information for human plasma and serum derived from the same platform was retrieved from previous studies. Statistical analyses included univariate and multivariate approaches aimed at identifying stable and/or differentially abundant metabolites between the two porcine biofluids. A total of 154 (∼83%) metabolites passed the initial quality control, indicating a good repeatability of the analytical platform in pigs. Discarded metabolites included aspartate and biogenic amines that were already reported to be unstable in human studies. More than 80% of the metabolites had similar profiles in both porcine biofluids (average correlation was 0.75). Concentrations were usually higher in serum than in plasma, in agreement with what was already reported in humans. The univariate analysis identified 44 metabolites that had statistically different concentrations between porcine plasma and serum, of which 28 metabolites were also confirmed by the multivariate analysis. The obtained picture described similarities and differences between these two biofluids in pigs and the related human-pig comparisons. The obtained information can be useful for the choice of one or the other matrix for the implementation of metabolomic studies in this livestock species. The results can also provide useful hints to valuing the pig as animal model, in particular when metabolite-derived physiological states are relevant.

Mitochondrial N-formyl methionine peptides contribute to exaggerated neutrophil activation in patients with COVID-19

Neutrophil dysregulation is well established in COVID-19. However, factors contributing to neutrophil activation in COVID-19 are not clear. We assessed if N-formyl methionine (fMet) contributes to neutrophil activation in COVID-19. Elevated levels of calprotectin, neutrophil extracellular traps (NETs) and fMet were observed in COVID-19 patients (n = 68), particularly in critically ill patients, as compared to HC (n = 19, p < 0.0001). Of note, the levels of NETs were higher in ICU patients with COVID-19 than in ICU patients without COVID-19 (p < 0.05), suggesting a prominent contribution of NETs in COVID-19. Additionally, plasma from COVID-19 patients with mild and moderate/severe symptoms induced in vitro neutrophil activation through fMet/FPR1 (formyl peptide receptor-1) dependent mechanisms (p < 0.0001). fMet levels correlated with calprotectin levels validating fMet-mediated neutrophil activation in COVID-19 patients (r = 0.60, p = 0.0007). Our data indicate that fMet is an important factor contributing to neutrophil activation in COVID-19 disease and may represent a potential target for therapeutic intervention.

Assessing variations in manual pipetting: An under-investigated requirement of good laboratory practice

Pipettes are essential tools for biomedical and analytical laboratories, analogous to workstations for computer scientists. Variation in pipetting is a known unknown, as it is generally accepted that variations exist, but thus far, there have been limited studies on the extent of these variations in practice. In this mini-review, we highlight how manual pipetting is a key technique in the laboratory, and, although simple, inaccuracy and imprecision exist. If variations are not adequately addressed, errors can be compounded and consequently compromise data quality. Determination of the accuracy and precision of manual pipetting is straightforward, and here we review two common approaches that use gravimetry and spectrophotometry as readouts. We also provide detailed protocols for determination of accuracy and precision using manual single and multi-channel pipettes. These simple-to-use methods can be used by any laboratory for competency training and regular checks. Having a common protocol for evaluation of variation will also enable cross-laboratory comparison and potentially facilitate establishment of a reference value of acceptable ranges for operator error. Such a value could be of relevance to the scientific community for benchmarking and assuring good laboratory practice.

Multiomic Approaches for Cancer Biomarker Discovery in Liquid Biopsies: Advances and Challenges

Cancer is a complex and heterogeneous disease that poses a significant threat to global health. Early diagnosis and treatment are critical for improving patient outcomes, and the use of liquid biopsies has emerged as a promising approach for cancer detection and monitoring. Traditionally, cancer diagnosis has relied on invasive tissue biopsies, the collection of which can prove challenging for patients and the results of which may not always provide accurate results due to tumor heterogeneity. Liquid biopsies have gained increasing attention as they provide a non-invasive and accessible source of cancer biomarkers, which can be used to diagnose cancer, monitor treatment response, and detect relapse. The integration of -omics technologies, such as proteomics, genomics, and metabolomics, has further enhanced the capabilities of liquid biopsies by introducing precision oncology and enabling the tailoring of treatment for individual patients based on their unique tumor biology. In this review, we will discuss the challenges and advances in the field of cancer liquid biopsies and the integration of -omics technologies for different types of liquid biopsies, including blood, tear, urine, sweat, saliva, and cerebrospinal fluid.

Urinary Proteomics for Discovery of Gastric Cancer Biomarkers to Enable Precision Clinical Oncology

For precision in clinical oncology practice, detection of tumor-derived peptides and proteins in urine offers an attractive and noninvasive alternative for diagnostic or screening purposes. In this study, we report comparative quantitative proteomic profiling of urine samples from patients with gastric cancer and healthy controls using tandem mass tags-based multiplexed mass spectrometry approach. We identified 1504 proteins, of which 246 were differentially expressed in gastric cancer cases. Notably, ephrin A1 (EFNA1), pepsinogen A3 (PGA3), sortilin 1 (SORT1), and vitronectin (VTN) were among the upregulated proteins, which are known to play crucial roles in the progression of gastric cancer. We also found other overexpressed proteins, including shisa family member 5 (SHISA5), mucin like 1 (MUCL1), and leukocyte cell derived chemotaxin 2 (LECT2), which had not previously been linked to gastric cancer. Using a novel approach for targeted proteomics, SureQuant, we validated changes in abundance of a subset of proteins discovered in this study. We confirmed the overexpression of vitronectin and sortilin 1 in an independent set of urine samples. Altogether, this study provides molecular candidates for biomarker development in gastric cancer, and the findings also support the promise of urinary proteomics for noninvasive diagnostics and personalized/precision medicine in the oncology clinic.

Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis

Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.

Offline Peptide Fractionation and Parallel Reaction Monitoring MS for the Quantitation of Low-Abundance Plasma Proteins

Mass spectrometry (MS)-based protein quantitation is an attractive means for research and diagnostics due to its high specificity, precision, sensitivity, versatility, and the ability to develop multiplexed assays for the "absolute" quantitation of virtually any protein target. However, due to the large dynamic range of protein concentrations in blood, high abundance proteins in blood plasma hinder the detectability and quantification of lower-abundance proteins which are often relevant in the context of different diseases. Here we outline a streamlined method involving offline high-pH reversed-phase fractionation of human plasma samples followed by the quantitative analysis of specific fractions using nanoLC-parallel reaction monitoring (PRM) on a Q Exactive Plus mass spectrometer for peptide detection and quantitation with increased sensitivity. Because we use a set of synthetic peptide standards, we can more efficiently determine the precise retention times of the target peptides in the first-dimensional separation and specifically collect eluting fractions of interest for the subsequent targeted MS quantitation, making the analysis faster and easier. An eight-point standard curve was generated by serial dilution of a mixture of previously validated unlabeled ("light") synthetic peptides of interest at known concentrations. The corresponding heavy stable-isotope-labeled standard (SIS) analogues were used as normalizers to account for losses during sample processing and analysis. Using this method, we were able to improve the sensitivity of plasma protein quantitation by up to 50-fold compared to using nanoLC-PRM alone.

Investigation of native and aggregated therapeutic proteins in human plasma with asymmetrical flow field-flow fractionation and mass spectrometry

Physiochemical degradation of therapeutic proteins in vivo during plasma circulation after administration can have a detrimental effect on their efficacy and safety profile. During drug product development, in vivo animal studies are necessary to explore in vivo protein behaviour. However, these studies are very demanding and expensive, and the industry is working to decrease the number of in vivo studies. Consequently, there is considerable interest in the development of methods to pre-screen the behaviour of therapeutic proteins in vivo using in vitro analysis. In this work, asymmetrical flow field-flow fractionation (AF4) and liquid chromatography-mass spectrometry (LC-MS) were combined to develop a novel analytical methodology for predicting the behaviour of therapeutic proteins in vivo. The method was tested with two proteins, a monoclonal antibody and a serum albumin binding affibody. After incubation of the proteins in plasma, the method was successfully used to investigate and quantify serum albumin binding, analyse changes in monoclonal antibody size, and identify and quantify monoclonal antibody aggregates.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

Site-specific N-glycosylation characterization of micro monoclonal immunoglobulins based on EThcD-sceHCD-MS/MS

Monoclonal immunoglobulin produced by clonal plasma cells is the main cause in multiple myeloma and monoclonal gammopathy of renal significance. Because of the complicated purification method and the low stoichiometry of purified protein and glycans, site-specific N-glycosylation characterization for monoclonal immunoglobulin is still challenging. To profile the site-specific N-glycosylation of monoclonal immunoglobulins is of great interest. Therefore, in this study, we presented an integrated workflow for micro monoclonal IgA and IgG purification from patients with multiple myeloma in the HYDRASYS system, in-agarose-gel digestion, LC-MS/MS analysis without intact N-glycopeptide enrichment, and compared the identification performance of different mass spectrometry dissociation methods (EThcD-sceHCD, sceHCD, EThcD and sceHCD-pd-ETD). The results showed that EThcD-sceHCD was a better choice for site-specific N-glycosylation characterization of micro in-agarose-gel immunoglobulins (~2 μg) because it can cover more unique intact N-glycopeptides (37 and 50 intact N-glycopeptides from IgA1 and IgG2, respectively) and provide more high-quality spectra than sceHCD, EThcD and sceHCD-pd-ETD. We demonstrated the benefits of the alternative strategy in site-specific N-glycosylation characterizing micro monoclonal immunoglobulins obtained from bands separated by electrophoresis. This work could promote the development of clinical N-glycoproteomics and related immunology.

Comprehensive Plasma N-Glycoproteome Profiling Based on EThcD-sceHCD-MS/MS

Glycoproteins are involved in a variety of biological processes. More than one-third of the plasma protein biomarkers of tumors approved by the FDA are glycoproteins, and could improve the diagnostic specificity and/or sensitivity. Therefore, it is of great significance to perform the systematic characterization of plasma N-glycoproteome. In previous studies, we developed an integrated method based on the combinatorial peptide ligand library (CPLL) and stepped collision energy/higher energy collisional dissociation (sceHCD) for comprehensive plasma N-glycoproteome profiling. Recently, we presented a new fragmentation method, EThcD-sceHCD, which outperformed sceHCD in the accuracy of identification. Herein, we integrated the combinatorial peptide ligand library (CPLL) into EThcD-sceHCD and compared the performance of different mass spectrometry dissociation methods (EThcD-sceHCD, EThcD, and sceHCD) in the intact N-glycopeptide analysis of prostate cancer plasma. The results illustrated that EThcD-sceHCD was better than EThcD and sceHCD in the number of identified intact N-glycopeptides (two-folds). A combination of sceHCD and EThcD-sceHCD methods can cover almost all glycoproteins (96.4%) and intact N-glycopeptides (93.6%), indicating good complementarity between the two. Our study has great potential for medium- and low-abundance plasma glycoprotein biomarker discovery.

The promise of graphene-based transistors for democratizing multiomics studies

As biological research has synthesized genomics, proteomics, metabolomics, and transcriptomics into systems biology, a new multiomics approach to biological research has emerged. Today, multiomics studies are challenging and expensive. An experimental platform that could unify the multiple omics approaches to measurement could increase access to multiomics data by enabling more individual labs to successfully attempt multiomics studies. Field effect biosensing based on graphene transistors have gained significant attention as a potential unifying technology for such multiomics studies. This review article highlights the outstanding performance characteristics that makes graphene field effect transistor an attractive sensing platform for a wide variety of analytes important to system biology. In addition to many studies demonstrating the biosensing capabilities of graphene field effect transistors, they are uniquely suited to address the challenges of multiomics studies by providing an integrative multiplex platform for large scale manufacturing using the well-established processes of semiconductor industry. Furthermore, the resulting digital data is readily analyzable by machine learning to derive actionable biological insight to address the challenge of data compatibility for multiomics studies. A critical stage of systems biology will be democratizing multiomics study, and the graphene field effect transistor is uniquely positioned to serve as an accessible multiomics platform.

A comparative study of data-dependent acquisition and data-independent acquisition in proteomics analysis of clinical lung cancer tissues constrained by blood contamination

Proteomics analysis is often troubled by high-abundance proteins in samples such as plasma. However, many surgical tissue samples inevitably have got contaminated with blood before cryopreservation. Selection of an appropriate method to minimize the effect of high-abundance proteins is important for proteomics analysis of blood contaminated tissues. Here, we investigated and compared the abilities of data-independent acquisition (DIA) and data-dependent acquisition (DDA) strategies for the proteomics analysis of blood contaminated clinical tissue samples. Twelve pairs of carcinoma and para-carcinoma tissue samples from lung cancer patients were used for proteomics assays separately by DIA and DDA, and the blood contamination level in samples was evaluated by contamination index (CI). Compared with the DDA strategy, DIA in whole exhibited much better analytical capabilities in proteomics analysis of these samples with more identified protein groups and a higher discovery of differential proteins. With CI value increasing, whether DIA or DDA showed decreasing analysis ability. However, for samples with high CI values, the DIA strategy still shows acceptable analytical capability and indicates better blood pollution resistance than the DDA strategy. Our results implied that for clinical tissue samples, particularly for those contaminated with blood, DIA strategy should be a preferred method in proteomics studies.

Non-Antibody-Based Binders for the Enrichment of Proteins for Analysis by Mass Spectrometry

There is often a need to isolate proteins from body fluids, such as plasma or serum, prior to further analysis with (targeted) mass spectrometry. Although immunoglobulin or antibody-based binders have been successful in this regard, they possess certain disadvantages, which stimulated the development and validation of alternative, non-antibody-based binders. These binders are based on different protein scaffolds and are often selected and optimized using phage or other display technologies. This review focuses on several non-antibody-based binders in the context of enriching proteins for subsequent liquid chromatography-mass spectrometry (LC-MS) analysis and compares them to antibodies. In addition, we give a brief introduction to approaches for the immobilization of binders. The combination of non-antibody-based binders and targeted mass spectrometry is promising in areas, like regulated bioanalysis of therapeutic proteins or the quantification of biomarkers. However, the rather limited commercial availability of these binders presents a bottleneck that needs to be addressed.

The Known Unknowns: An Overview of the State of Blood-Based Protein Biomarkers of Mild Traumatic Brain Injury

Blood-based protein biomarkers have revolutionized several fields of medicine by enabling molecular level diagnosis, as well as monitoring disease progression and treatment efficacy. Traumatic brain injury (TBI) so far has benefitted only moderately from using protein biomarkers to improve injury outcome. Because of its complexity and dynamic nature, TBI, especially its most prevalent mild form (mild TBI; mTBI), presents unique challenges toward protein biomarker discovery and validation given that blood is frequently obtained and processed outside of the clinical laboratory (e.g., athletic fields, battlefield) under variable conditions. As it stands, the field of mTBI blood biomarkers faces a number of outstanding questions. Do elevated blood levels of currently used biomarkers-ubiquitin carboxy-terminal hydrolase L1, glial fibrillary acidic protein, neurofilament light chain, and tau/p-tau-truly mirror the extent of parenchymal damage? Do these different proteins represent distinct injury mechanisms? Is the blood-brain barrier a "brick wall"? What is the relationship between intra- versus extracranial values? Does prolonged elevation of blood levels reflect de novo release or extended protein half-lives? Does biological sex affect the pathobiological responses after mTBI and thus blood levels of protein biomarkers? At the practical level, it is unknown how pre-analytical variables-sample collection, preparation, handling, and stability-affect the quality and reliability of biomarker data. The ever-increasing sensitivity of assay systems and lack of quality control of samples, combined with the almost complete reliance on antibody-based assay platforms, represent important unsolved issues given that false-negative results can lead to false clinical decision making and adverse outcomes. This article serves as a commentary on the state of mTBI biomarkers and the landscape of significant challenges. We highlight and discusses several biological and methodological "known unknowns" and close with some practical recommendations.

Recent advance in the discovery of tyrosinase inhibitors from natural sources via separation methods

Tyrosinase (TYR) inhibitors are in great demand in the food, cosmetic and medical industrials due to their important roles. Therefore, the discovery of high-quality TYR inhibitors is always pursued. Natural products as one of the most important sources of bioactive compounds discovery have been increasingly used for TYR inhibitors screening. However, due to their complex compositions, it is still a great challenge to rapid screening and identification of biologically active components from them. In recent years, with the help of separation technologies and the affinity and intrinsic activity of target enzymes, two advanced approaches including affinity screening and inhibition profiling showed great promises for a successful screening of bioactive compounds from natural sources. This review summarises the recent progress of separation-based methods for TYR inhibitors screening, with an emphasis on the principle, application, advantage, and drawback of each method along with perspectives in the future development of these screening techniques and screened hit compounds.

Associations between the thyroid panel and serum protein concentrations across pregnancy

Establishing any characteristic associations between the serum parameters of thyroid function and serum proteins in pregnancy may aid in elucidating the role of the thyroid gland in the regulation of pregnancy-specific metabolic processes and in selecting candidate biomarkers for use in their clinical assessment. Concentrations of thyroid stimulating hormone (TSH), free tri-iodothyronine (fT3) and free thyroxine (fT4), six electrophoretically separated protein fractions (albumin, alpha-1-, alpha2-, beta-1-, beta-2- and gamma-globulins), representative proteins—albumin (ALB), transferrin (TRF), alpha-2-macroglobulin (AMG) and ceruloplasmin (CER) were measured in 136 serum samples from 65 women in their consecutive trimesters of pregnancy. The concentrations of TSH, fT4 and fT3 were significantly correlated (p < 0.05) with the concentrations of the albumin, alpha-2- and beta-1 globulin fractions. Significant correlations (p < 0.05) which were positive between fT4 and ALB and negative between fT4 and TRF were established throughout pregnancy. Significant negative correlations (p < 0.05) were demonstrated for fT3 with alpha-2-globulin, AMG and CER. Changes in the serum concentrations of thyroid hormones seen between the trimesters were found to correlate with the concentrations of high-abundance serum proteins. Opposite directions of correlations between fT4 and ALB and fT4 and TRF observed throughout pregnancy may indicate the shared biological role of these parameters in maintaining maternal homeostasis and they suggest their potential use in the clinic as a simple biomarker panel. A negative correlation of fT3 with CER in the second trimester possibly reflects their involvement in the active regulation of metabolic processes.

Optimization and Standardization of Human Saliva Collection for MALDI-TOF MS

SARS-CoV-2 outbreak led to unprecedented innovative scientific research to preclude the virus dissemination and limit its impact on life expectancy. Waiting for the collective immunity by vaccination, mass-testing, and isolation of positive cases remain essential. The development of a diagnosis method requiring a simple and non-invasive sampling with a quick and low-cost approach is on demand. We hypothesized that the combination of saliva specimens with MALDI-TOF MS profiling analyses could be the winning duo. Before characterizing MS saliva signatures associated with SARS-CoV-2 infection, optimization and standardization of sample collection, preparation and storage up to MS analyses appeared compulsory. In this view, successive experiments were performed on saliva from healthy healthcare workers. Specimen sampling with a roll cotton of Salivette^® devices appeared the most appropriate collection mode. Saliva protein precipitation with organic buffers did not improved MS spectra profiles compared to a direct loading of samples mixed with acetonitrile/formic acid buffer onto MS plate. The assessment of sample storage conditions and duration revealed that saliva should be stored on ice until MS analysis, which should occur on the day of sampling. Kinetic collection of saliva highlighted reproducibility of saliva MS profiles over four successive days and also at two-week intervals. The intra-individual stability of saliva MS profiles should be a key factor in the future investigation for biomarkers associated with SARS-CoV-2 infection. However, the singularity of MS profiles between individuals will require the development of sophisticated bio-statistical analyses such as machine learning approaches. MALDI-TOF MS profiling of saliva could be a promising PCR-free tool for SARS-CoV-2 screening.

Recent Progress in FD-LC-MS/MS Proteomics Method

Through the course of our bio-analytical chemistry studies, we developed a novel proteomics analysis method, FD-LC-MS/MS (fluorogenic derivatization-liquid chromatography-tandem mass spectrometry). This method consists of fluorogenic derivatization (FD), LC separation, and detection/quantification of the derivatized proteins, followed by isolation, tryptic digestion of the isolated proteins, and final identification of the isolated proteins using electrospray ionization nano-LC-MS/MS of the generated peptide mixtures with a probability-based protein identification algorithm. In this review, we will present various examples where this method has been used successfully to identify expressed proteins in individual human cells. FD-LC-MS/MS is also suitable for differential proteomics analysis. Here, two biological samples are treated by the same steps mentioned above, and the two chromatograms obtained are compared to identify peaks with different intensities (variation in protein levels). Associated peak fractions are then isolated, and the differentially expressed proteins between the two samples are identified by LC-MS/MS. Several biomarkers for cancers have been identified by FD-LC-MS/MS. For more efficient separation, nano-flow LC with a phenyl-bonded monolithic silica-based capillary column was adopted for cell-expressed intact protein analysis. The derivatized human cell proteins (K562) and yeast cell (Saccharomyces cerevisiae) proteins as model intact cell proteins were analyzed by nano-flow LC with fluorescence detection. More than 1,300 protein peaks were separated/detected from both cells. For straightforward comparison of multiple peak separation profiles, a novel type of chromatogram display, termed the “spiderweb” chromatogram, was developed. A nano-LC-FD-LC-mass spectrometry trial for molecular weight estimation of FD proteins has also been conducted.

Analytical potential of total reflection X-ray fluorescence spectrometry for simultaneous determination of iron, copper and zinc in human blood serum and plasma

Due to many roles of trace elements such as Fe, Cu and Zn in various physiological and pathophysiological processes, their determination in serum and plasma is of high clinical relevance. In the present study, for the first time, the effect of serum and plasma preparation parameters (dilution factor and sample deposition volume) on the quality of results obtained by TXRF analysis was evaluated by means of experimental design tools (response surface analysis). It was found that the best strategy was the direct analysis of both human fluids without a previous dilution step. The accuracy and precision of the proposed methods were evaluated by analysis of reference materials (ClinChek® Plasma Control Level II and Seronorm™ Trace Elements Serum L-1). TXRF results agreed with the reference values and no significant differences at 95% confidence level were found. Limits of detection for the elements of interest were also adequate, taking into account their typical concentration ranges in real serum and plasma samples. Finally, the developed TXRF methods were applied to a set of serum and plasma samples from patients with different genders, ages and diagnoses, previously analysed by ICP-OES and ICP-MS techniques. The results showed good agreement between both analytical approaches. These results suggest that the proposed TXRF method provides reliable results thus being suitable for plasma and serum analysis, but in a simpler and more sustainable way.

Can variability of serum electrophoretic fractions during pregnancy provide knowledge about maternal and fetal health

AIM

Characteristics of variability of concentrations total protein and its electrophoretic fractions in serum of healthy pregnant women between successive trimesters and post-partum for initial classification of proteins involved in specific metabolic processes associated with pregnancy.

METHODS

Total serum protein concentrations were measured by biuret method and serum protein fractions were electrophoretically separated in 166 serum samples collected from healthy pregnant women in three trimesters of pregnancy (1st, n = 55; 2nd, n = 42; 3rd, n = 39) and in post-partum (n = 30), and in 20 samples from nonpregnant controls.

RESULTS

Across pregnancy, there were gradual, but occurring at different rates, decreases over time in serum total protein, albumin and gamma globulins compared to controls (P < 0.05). In 1st trimester, serum concentrations of total protein, albumin and gamma globulins were <10% lower than in nonpregnant state, with further decreases in 2nd and 3rd trimesters and in post-partum. The concentrations of alpha-1-, alpha-2-, beta-1- and beta-2-globulins were elevated compared to controls (P < 0.05) with different dynamics of change and with the highest percentage increase for alpha-1-globulin.

CONCLUSION

Pregnancy-associated alterations in the serum concentrations of total protein and in its individual electrophoretic protein fractions in each trimester of pregnancy and differences versus normal ranges in nonpregnant healthy females could be a simple screening method for classification useful laboratory parameters that help obstetricians and gynecologists to make multidirectional judgments about the state of health of pregnant women.

Biomolecular and bioanalytical applications of infrared spectroscopy - A review

Infrared (IR; or mid-infrared, MIR; 4000-400 cm^-1; 2500-25,000 nm) spectroscopy has become one of the most powerful and versatile tools at the disposal of modern bioscience. Because of its high molecular specificity, applicability to wide variety of samples, rapid measurement and non-invasivity, IR spectroscopy forms a potent approach to elucidate qualitative and quantitative information from various kinds of biological material. For these reasons, it became an established bioanalytical technique with diverse applications. This work aims to be a comprehensive and critical review of the recent accomplishments in the field of biomolecular and bioanalytical IR spectroscopy. That progress is presented on a wider background, with fundamental characteristics, the basic principles of the technique outlined, and its scientific capability directly compared with other methods being used in similar fields (e.g. near-infrared, Raman, fluorescence). The article aims to present a complete examination of the topic, as it touches the background phenomena, instrumentation, spectra processing and data analytical methods, spectra interpretation and related information. To suit this goal, the article includes a tutorial information essential to obtain a thorough perspective of bio-related applications of the reviewed methodologies. The importance of the fundamental factors to the final performance and applicability of IR spectroscopy in various areas of bioscience is explained. This information is interpreted in critical way, with aim to gain deep understanding why IR spectroscopy finds extraordinarily intensive use in this remarkably diverse and dynamic field of research and utility. The major focus is placed on the diversity of the applications in which IR biospectroscopy has been established so far and those onto which it is expanding nowadays. This includes qualitative and quantitative analytical spectroscopy, spectral imaging, medical diagnosis, monitoring of biophysical processes, and studies of physicochemical properties and dynamics of biomolecules. The application potential of IR spectroscopy in light of the current accomplishments and the future prospects is critically evaluated and its significance in the progress of bioscience is comprehensively presented.

Paradigm Shift in the Arena of Sample Preparation and Bioanalytical Approaches Involving Liquid Chromatography Mass Spectroscopic Technique

Sample preparation is a highly important and integral part of bioanalysis for cleaning up the complex biological matrices and thereby minimizing matrix effect. Matrix effect can jeopardize the precise quantification and adversely affect the reliability of liquid chromatography-mass spectrometry-based analytical results by alteration of analyte ionization. Matrix components result in suppression or enhancement of the intensity of analyte response. In spite of the high specificity and selectivity of tandem mass spectrometry, a relatively higher concentration of coeluted matrix elements present in biofluids may alter the efficiency of quantification of a bioanalytical method. Numerous literature reports different types of sample preparation techniques employed in bioanalysis. In this review, the strategies for selection of the appropriate sample clean-up technique in bioanalysis are discussed extensively. A paradigm shift in the arena of sample preparation and bioanalytical approaches involving the liquid chromatography-mass spectroscopic technique has been scrutinized. Current trends and possible future advancements in the field of biological sample extraction methods, including instrumental techniques are analyzed in detail.

Isolation and characterization of glycosylated neuropeptides

Glycosylation is one of the most ubiquitous and complex post-translational modifications (PTMs). It plays pivotal roles in various biological processes. Studies at the glycopeptide level are typically considered as a downstream work resulting from enzymatic digested glycoproteins. Less attention has been focused on glycosylated endogenous signaling peptides due to their low abundance, structural heterogeneity and the lack of enabling analytical tools. Here, protocols are presented to isolate and characterize glycosylated neuropeptides utilizing nanoflow liquid chromatography coupled with mass spectrometry (LC-MS). We first demonstrate how to extract neuropeptides from raw tissues and perform further separation/cleanup before MS analysis. Then we describe hybrid MS methods for glycosylated neuropeptide profiling and site-specific analysis. We also include recommendations for data analysis to identify glycosylated neuropeptides in crustaceans where a complete neuropeptide database is still lacking. Other strategies and future directions are discussed to provide readers with alternative approaches and further unravel biological complexity rendered by glycosylation.

Screening techniques for the identification of bioactive compounds in natural products

Natural products (NPs) have a long history of clinical use and are rich source of bioactive compounds. The development of tools and techniques for identifying and analyzing NP bioactive compounds to ensure their quality and discover new drugs is thus very important and still in demand. Screening techniques have proven highly useful for screening and analyzing active components in complex mixtures, which rely on cell culture, dialysis, ultrafiltration, chromatographic methods and target molecule immobilization, using biological targets to identify the active compounds. The recent progress in biological screening techniques in the field of natural products is reviewed here. This includes a review on the strategy and application of the screening methods, their detailed description and discussion of their existing limitations of the different models along with prospective in future development of screening techniques.

Analysis of bodily fluids using vibrational spectroscopy: a direct comparison of Raman scattering and infrared absorption techniques for the case of glucose in blood serum

Analysis of biomarkers present in the blood stream can potentially deliver crucial information on patient health and indicate the presence of numerous pathologies.

Raman spectroscopic screening of high and low molecular weight fractions of human serum

This study explores the suitability of Raman spectroscopy as a bioanalytical tool, when coupled with ultra-filtration and multivariate analysis, to detect imbalances in both high molecular weight and low molecular weight fractions of the same samples of human patient serum, in the native liquid form.

Quantification of ondansetron, granisetron and tropisetron in goat plasma using hydrophilic interaction liquid chromatography-solid phase extraction coupled with hydrophilic interaction liquid chromatography-triple quadrupole tandem mass spectrometry

An assay method to quantify ondansetron (OND), granisetron (GRA) and tropisetron (TRO) in goat plasma has been successfully developed and validated. This method procedure for the analysis of OND, GRA and TRO was involved of extracting samples with hydrophilic interaction liquid chromatography (HILIC) solid phase extraction (SPE) and determination by liquid chromatography coupled to tandem mass spectroscopy. An SPE method for the simultaneous extraction of OND, GRA and TRO with high efficiency and selectivity was developed. Prior to HPLC-MS/MS analysis, most of the sources of interference present in the supernatant after protein precipitation of plasma proteins was efficiently removed from the samples by the HILIC SPE treatment. For the quantification of OND, GRA and TRO in the samples, tandem mass spectrometry operating in positive electrospray ionization mode with multiple reaction monitoring was used. The calibration curve was performed in the range of 0.2-20 ng/mL for the target OND, GRA and TRO in goat plasma samples. The precision of the intra- and inter-day assay for OND, GRA and TRO were 1.84-6.23% and 3.89-5.31%, 2.63-6.29% and 3.76-5.31%, 1.99-5.67% and 2.64-4.70%, respectively. The accuracy of the intra- and inter-day assay for OND, GRA and TRO were 89.15-97.39% and 89.46-95.17%, 91.08-100.82% and 91.24-99.47%, 92.30-100.74% and 94.21-97.90%, respectively. For the determination of OND, GRA and TRO in plasma samples, no significant matrix effects were observed. The mean absolute recoveries were 103-150%, 115-121%, and 98-141% for OND, GRA and TRO, respectively. Furthermore, the mean process efficiency values of silica SPE were 98-135%, 92-124%, and 72-109% for OND, GRA and TRO, respectively.

Mixed-mode ion exchange-based integrated proteomics technology for fast and deep plasma proteome profiling

Plasma proteome profiling by LC-MS based proteomics has drawn great attention recently for biomarker discovery from blood liquid biopsy. Due to standard multi-step sample preparation could potentially cause plasma protein degradation and analysis variation, integrated proteomics sample preparation technologies became promising solution towards this end. Here, we developed a fully integrated proteomics sample preparation technology for both fast and deep plasma proteome profiling under its native pH. All the sample preparation steps, including protein digestion and two-dimensional fractionation by both mixed-mode ion exchange and high-pH reversed phase mechanism were integrated into one spintip device for the first time. The mixed-mode ion exchange beads design achieved the sample loading at neutral pH and protein digestion within 30 min. Potential sample loss and protein degradation by pH changing could be voided. 1 μL of plasma sample with depletion of high abundant proteins was processed by the developed technology with 12 equally distributed fractions and analyzed with 12 h of LC-MS gradient time, resulting in the identification of 862 proteins. The combination of the Mixed-mode-SISPROT and data-independent MS method achieved fast plasma proteome profiling in 2 h with high identification overlap and quantification precision for a proof-of-concept study of plasma samples from 5 healthy donors. We expect that the Mixed-mode-SISPROT become a generally applicable sample preparation technology for clinical oriented plasma proteome profiling.

Assessment by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry of the Effects of Preanalytical Variables on Serum Peptidome Profiles Following Long-Term Sample Storage

PURPOSE

Human serum and plasma are often used as clinical specimens in proteomics analyses, and peptidome profiling of human serum is a promising tool for identifying novel disease-associated biomarkers. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is widely used for peptidomic biomarker discovery. Careful sample collection and handling are required as either can have a profound impact on serum peptidome patterns, yet the effects of preanalytical variables on serum peptidome profiles have not been completely elucidated. The present study investigated the effects of preanalytical variables, including storage temperature, duration (up to 12 months), and thawing methods, on MALDI-TOF MS-based serum peptidome patterns.

EXPERIMENTAL DESIGN

Aliquots of serum samples were pretreated with weak cation exchanger magnetic beads using an automated ClinProtRobot system and then analyzed by MALDI-TOF MS.

RESULTS

A number of significant differences in peak intensities were observed depending on sample processing variables.

CONCLUSIONS AND CLINICAL RELEVANCE

These peaks can be used as sample quality markers to assess the effects of long-term storage on serum peptidome profiles using MALDI-TOF MS.

Direct Assessment of Plasma/Serum Sample Quality for Proteomics Biomarker Investigation

Blood proteome analysis for biomarker discovery represents one of the most challenging tasks to be achieved through clinical proteomics due to the sample complexity, such as the extreme heterogeneity of proteins in very dynamic concentrations, and to the observation of proper sampling and storage conditions. Quantitative and qualitative proteomics profiling of plasma and serum could be useful both for the early detection of diseases and for the evaluation of pathological status. Two main sources of variability can affect the precision and accuracy of the quantitative experiments designed for biomarker discovery and validation. These sources are divided into two categories, pre-analytical and analytical, and are often ignored; however, they can contribute to consistent errors and misunderstanding in biomarker research. In this chapter, we review critical pre-analytical and analytical variables that can influence quantitative proteomics. According to guidelines accepted by proteomics community, we propose some recommendations and strategies for a proper proteomics analysis addressed to biomarker studies.

Liquid biomarkers in melanoma: detection and discovery

A vast array of tumor-derived genetic, proteomic and cellular components are constantly released into the circulation of cancer patients. These molecules including circulating tumor DNA and RNA, proteins, tumor and immune cells are emerging as convenient and accurate liquid biomarkers of cancer. Circulating cancer biomarkers provide invaluable information on cancer detection and diagnosis, prognosticate patient outcomes, and predict treatment response. In this era of effective molecular targeted treatments and immunotherapies, there is now an urgent need to implement use of these circulating biomarkers in the clinic to facilitate personalized therapy. In this review, we present recent findings in circulating melanoma biomarkers, examine the challenges and promise of evolving technologies used for liquid biomarker discovery, and discuss future directions and perspectives in melanoma biomarker research.

High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis

Mass spectrometry (MS)-based serum proteome analysis is extremely challenging due to its high complexity and dynamic range of protein abundances. Developing high throughput and accurate serum proteomic profiling approach capable of analyzing large cohorts is urgently needed for biomarker discovery. Herein, we report a streamlined workflow for fast and accurate proteomic profiling from 1μL of blood serum. The workflow combined an integrated technique for highly sensitive and reproducible sample preparation and a new data-independent acquisition (DIA)-based MS method. Comparing with standard data dependent acquisition (DDA) approach, the optimized DIA method doubled the number of detected peptides and proteins with better reproducibility. Without protein immunodepletion and prefractionation, the single-run DIA analysis enables quantitative profiling of over 300 proteins with 50min gradient time. The quantified proteins span more than five orders of magnitude of abundance range and contain over 50 FDA-approved disease markers. The workflow allowed us to analyze 20 serum samples per day, with about 358 protein groups per sample being identified. A proof-of-concept study on renal cell carcinoma (RCC) serum samples confirmed the feasibility of the workflow for large scale serum proteomic profiling and disease-related biomarker discovery.

BIOLOGICAL SIGNIFICANCE

Blood serum or plasma is the predominant specimen for clinical proteomic studies while the analysis is extremely challenging for its high complexity. Many efforts had been made in the past for serum proteomics for maximizing protein identifications, whereas few have been concerned with throughput and reproducibility. Here, we establish a rapid, robust and high reproducible DIA-based workflow for streamlined serum proteomic profiling from 1μL serum. The workflow doesn't need protein depletion and pre-fractionation, while still being able to detect disease-relevant proteins accurately. The workflow is promising in clinical application, because the usage of small sample amounts makes blood testing much less invasive, the fully integrated sample preparation by the SISPROT technology greatly improve sample preparation throughput and reproducibility, and the scan feature of DIA method provides a way to convert nonrenewable clinical specimens into permanent digital proteome maps which could be easily reanalyzed.

Revisiting biomarker discovery by plasma proteomics

Clinical analysis of blood is the most widespread diagnostic procedure in medicine, and blood biomarkers are used to categorize patients and to support treatment decisions. However, existing biomarkers are far from comprehensive and often lack specificity and new ones are being developed at a very slow rate. As described in this review, mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous "triangular strategies" aimed at discovering single biomarker candidates in small cohorts, followed by classical immunoassays in much larger validation cohorts. We propose a "rectangular" plasma proteome profiling strategy, in which the proteome patterns of large cohorts are correlated with their phenotypes in health and disease. Translating such concepts into clinical practice will require restructuring several aspects of diagnostic decision-making, and we discuss some first steps in this direction.

Ultra-filtration of human serum for improved quantitative analysis of low molecular weight biomarkers using ATR-IR spectroscopy

Monitoring of changes in the concentrations of the low molecular weight constituents enhanced by abundant proteins depletion.

Screening the low molecular weight fraction of human serum using ATR-IR spectroscopy

Vibrational spectroscopic techniques can detect small variations in molecular content, linked with disease, showing promise for screening and early diagnosis. Biological fluids, particularly blood serum, are potentially valuable for diagnosis purposes. The so-called Low Molecular Weight Fraction (LMWF) contains the associated peptidome and metabolome and has been identified as potentially the most relevant molecular population for disease-associated biomarker research. Although vibrational spectroscopy can deliver a specific chemical fingerprint of the samples, the High Molecular Weight Fraction (HMWF), composed of the most abundant serum proteins, strongly dominates the response and ultimately makes the detection of minor spectral variations a challenging task. Spectroscopic detection of potential serum biomarkers present at relatively low concentrations can be improved using pre-analytical depletion of the HMWF. In the present study, human serum fractionation by centrifugal filtration was used prior to analysis by Attenuated Total Reflection infrared spectroscopy. Using a model sample based on glycine spiked serum, it is demonstrated that the screening of the LMWF can be applied to quantify blinded concentrations up to 50 times lower. Moreover, the approach is easily transferable to different bodily fluids which would support the development of more efficient and suitable clinical protocols exploring vibrational spectroscopy based ex-vivo diagnostic tools. Revealing serum LMWF for spectral serological diagnostic applications.