The application of quantification techniques in proteomics for biomedical research

Exploring novel protein-based biomarkers for advancing breast cancer diagnosis: A review

This review provides a contemporary examination of the evolving landscape of breast cancer (BC) diagnosis, focusing on the pivotal role of novel protein-based biomarkers. The overview begins by elucidating the multifaceted nature of BC, exploring its prevalence, subtypes, and clinical complexities. A critical emphasis is placed on the transformative impact of proteomics, dissecting the proteome to unravel the molecular intricacies of BC. Navigating through various sources of samples crucial for biomarker investigations, the review underscores the significance of robust sample processing methods and their validation in ensuring reliable outcomes. The central theme of the review revolves around the identification and evaluation of novel protein-based biomarkers. Cutting-edge discoveries are summarised, shedding light on emerging biomarkers poised for clinical application. Nevertheless, the review candidly addresses the challenges inherent in biomarker discovery, including issues of standardisation, reproducibility, and the complex heterogeneity of BC. The future direction section envisions innovative strategies and technologies to overcome existing challenges. In conclusion, the review summarises the current state of BC biomarker research, offering insights into the intricacies of proteomic investigations. As precision medicine gains momentum, the integration of novel protein-based biomarkers emerges as a promising avenue for enhancing the accuracy and efficacy of BC diagnosis. This review serves as a compass for researchers and clinicians navigating the evolving landscape of BC biomarker discovery, guiding them toward transformative advancements in diagnostic precision and personalised patient care.

Proteomics: Its Promise and Pitfalls in Shaping Precision Medicine in Solid Organ Transplantation

Solid organ transplantation is an established treatment of choice for end-stage organ failure. However, all transplant patients are at risk of developing complications, including allograft rejection and death. Histological analysis of graft biopsy is still the gold standard for evaluation of allograft injury, but it is an invasive procedure and prone to sampling errors. The past decade has seen an increased number of efforts to develop minimally invasive procedures for monitoring allograft injury. Despite the recent progress, limitations such as the complexity of proteomics-based technology, the lack of standardization, and the heterogeneity of populations that have been included in different studies have hindered proteomic tools from reaching clinical transplantation. This review focuses on the role of proteomics-based platforms in biomarker discovery and validation in solid organ transplantation. We also emphasize the value of biomarkers that provide potential mechanistic insights into the pathophysiology of allograft injury, dysfunction, or rejection. Additionally, we forecast that the growth of publicly available data sets, combined with computational methods that effectively integrate them, will facilitate a generation of more informed hypotheses for potential subsequent evaluation in preclinical and clinical studies. Finally, we illustrate the value of combining data sets through the integration of 2 independent data sets that pinpointed hub proteins in antibody-mediated rejection.

Ecotoxicological significance of bio-corona formation on micro/nanoplastics in aquatic organisms

The unsustainable manufacturing, utilization and inadequate handling of plastics have led to a surge in global plastic pollution. In recent times, there has been increasing concern about the plausible hazards associated with exposure to micro/nanoplastics (M/NPs). As aquatic systems are considered to be the likely sink for M/NPs, it is crucial to comprehend their environmental behavior. The bioavailability, toxicity and fate of M/NPs in the environment are predominantly dictated by their surface characteristics. In the aquatic environment, M/NPs are prone to be internalized by aquatic organisms. This may facilitate their interaction with a diverse array of biomolecules within the organism, resulting in the formation of a biocorona (BC). The development of BC causes modifications in the physicochemical attributes of the M/NPs including changes to their size, stability, surface charge and other properties. This review details the concept of BC formation and its underlying mechanism. It provides insight on the analytical techniques employed for characterizing BC formation and addresses the associated challenges. Further, the eco-toxicological implications of M/NPs and the role of BC in modifying their potential toxicity on aquatic organisms is specified. The impact of BC formation on the fate and transport of M/NPs is discussed. A concise outlook on the future perspectives is also presented.

Mass Spectrometry Analysis of DNA and Protein Adducts as Biomarkers in Human Exposure to Cigarette Smoking: Acrolein as an Example

Acrolein is a major component in cigarette smoke and a product of endogenous lipid peroxidation. It is difficult to distinguish human exposure to acrolein from exogenous sources versus endogenous causes, as components in cigarette smoke can stimulate lipid peroxidation in vivo. Therefore, analysis of acrolein-induced DNA and protein adducts by the highly accurate, sensitive, and specific mass spectrometry-based methods is vital to estimate the degree of damage by this IARC Group 2A carcinogen. This Perspective reviews the analyses of acrolein-induced DNA and protein adducts in humans by mass spectrometry focusing on samples accessible for biomonitoring, including DNA from leukocytes and oral cells and abundant proteins from blood, i.e., hemoglobin and serum albumin.

Absolute Quantitative Targeted Proteomics Assays for Plasma Proteins

Preclinical and clinical trials require rapid, precise, and multiplexed analytical methods to characterize the complex samples and to allow high-throughput biomarker monitoring with low consumption of sample material. Targeted proteomics has been used to address these challenges when quantifying protein abundances in complex biological matrices. In many of these studies, blood plasma is collected either as the main research or diagnostic sample or in combination with other specimens. Mass spectrometry (MS)-based targeted proteomics using multiple reaction monitoring (MRM) or parallel reaction monitoring (PRM) with stable isotope-labeled internal standard (SIS) peptides allows robust characterization of blood plasma protein via absolute quantification. Compared to other commonly used technologies like enzyme-linked immunosorbent assay (ELISA), targeted proteomics is faster, more sensitive, and more cost-effective. Here we describe a protocol for the quantification of proteins in blood plasma using targeted MRM proteomics with heavy-labeled internal standards. The 270-protein panel allows rapid and robust absolute quantitative proteomic characterization of blood plasma in a 1 h gradient. The method we describe here works for non-depleted plasma, which makes it simple and easy to implement. Moreover, the protocol works with the two most commonly used blood plasma collection methods used in practice, namely, either K₂EDTA or sodium citrate as anticoagulants.

Reproducibility Evaluation of Urinary Peptide Detection Using CE-MS

In recent years, capillary electrophoresis coupled to mass spectrometry (CE-MS) has been increasingly applied in clinical research especially in the context of chronic and age-associated diseases, such as chronic kidney disease, heart failure and cancer. Biomarkers identified using this technique are already used for diagnosis, prognosis and monitoring of these complex diseases, as well as patient stratification in clinical trials. CE-MS allows for a comprehensive assessment of small molecular weight proteins and peptides (<20 kDa) through the combination of the high resolution and reproducibility of CE and the distinct sensitivity of MS, in a high-throughput system. In this study we assessed CE-MS analytical performance with regards to its inter- and intra-day reproducibility, variability and efficiency in peptide detection, along with a characterization of the urinary peptidome content. To this end, CE-MS performance was evaluated based on 72 measurements of a standard urine sample (60 for inter- and 12 for intra-day assessment) analyzed during the second quarter of 2021. Analysis was performed per run, per peptide, as well as at the level of biomarker panels. The obtained datasets showed high correlation between the different runs, low variation of the ten highest average individual log2 signal intensities (coefficient of variation, CV < 10%) and very low variation of biomarker panels applied (CV close to 1%). The findings of the study support the analytical performance of CE-MS, underlining its value for clinical application.

Survival analysis in breast cancer using proteomic data from four independent datasets

Breast cancer clinical treatment selection is based on the immunohistochemical determination of four protein biomarkers: ESR1, PGR, HER2, and MKI67. Our aim was to correlate immunohistochemical results to proteome-level technologies in measuring the expression of these markers. We also aimed to integrate available proteome-level breast cancer datasets to identify and validate new prognostic biomarker candidates. We searched studies involving breast cancer patient cohorts with published survival and proteomic information. Immunohistochemistry and proteomic technologies were compared using the Mann-Whitney test. Receiver operating characteristics (ROC) curves were generated to validate discriminative power. Cox regression and Kaplan-Meier survival analysis were calculated to assess prognostic power. False Discovery Rate was computed to correct for multiple hypothesis testing. We established a database integrating protein expression data and survival information from four independent cohorts for 1229 breast cancer patients. In all four studies combined, a total of 7342 unique proteins were identified, and 1417 of these were identified in at least three datasets. ESR1, PGR, and HER2 protein expression levels determined by RPPA or LC-MS/MS methods showed a significant correlation with the levels determined by immunohistochemistry (p < 0.0001). PGR and ESR1 levels showed a moderate correlation (correlation coefficient = 0.17, p = 0.0399). An additional panel of candidate proteins, including apoptosis-related proteins (BCL2,), adhesion markers (CDH1, CLDN3, CLDN7) and basal markers (cytokeratins), were validated as prognostic biomarkers. Finally, we expanded our previously established web tool designed to validate survival-associated biomarkers by including the proteomic datasets analyzed in this study ( https://kmplot.com/ ). In summary, large proteomic studies now provide sufficient data enabling the validation and ranking of potential protein biomarkers.

Molecular Portrait of an Athlete

Sequencing of the human genome and further developments in "omics" technologies have opened up new possibilities in the study of molecular mechanisms underlying athletic performance. It is expected that molecular markers associated with the development and manifestation of physical qualities (speed, strength, endurance, agility, and flexibility) can be successfully used in the selection systems in sports. This includes the choice of sports specialization, optimization of the training process, and assessment of the current functional state of an athlete (such as overtraining). This review summarizes and analyzes the genomic, proteomic, and metabolomic studies conducted in the field of sports medicine.

Proteomic Profiling and Monitoring of Training Distress and Illness in University Swimmers During a 25-Week Competitive Season

Purpose

To evaluate relationships of proteomics data, athlete-reported illness, athlete training distress (TDS), and coaches’ ratings of distress and performance over the course of the competitive season.

Methods

Thirty-five NCAA Division II swimmers were recruited to the study (male n = 19, female n = 16; age 19.1 ± 1.6 years). Athletes provided fingerprick dried blood spot (DBS) samples, illness symptoms, and TDS every Monday for 19 of 25 weeks in their season. Coaches monitored performance and rated visual signs of distress. DBS samples were analyzed for a targeted panel of 12 immune-related proteins using liquid chromatography/mass spectrometry (LC/MS).

Results

Thirty-two swimmers completed the protocol. The data were grouped in 2–3 weeks segments to facilitate interpretation and analysis of the data. TDS scores varied between athletes, and were highest during the early fall conditioning ramp up period (8.9 ± 1.6 at baseline to a peak of 22.6 ± 2.0). The percent of athletes reporting illness was high throughout the season (50–78%). Analysis of TDS using Principle Component Analysis (PCA) revealed that 40.5% of the variance (PC1) could be attributed to illness prevalence, and TDS scores for the athletes reporting illness and no illness were different across the season (P < 0.001). The coaches’ ratings of swim performance and swimmer’s distress, sex, and racing distance (sprinters, middle distance, long distance) were not correlated with PC1. Linear Discriminant Analysis (LDA) analysis of the data showed a separation of the baseline weeks from exam weeks with or without competitions, and with competitions alone (p < 0.001). Seven of the 12 proteins monitored over the course of training were upregulated, and the addition of the protein data to LDA analysis enhanced the separation between these groups of weeks.

Conclusion

TDS and illness were related in this group of 32 collegiate swimmers throughout the competitive season, and expression of immune proteins improved the statistical separation of baseline weeks from the most stressful weeks. TDS data provided by the swimmers did not match their coaches’ ratings of distress and swim performance. The importance of the immune system in the reaction to internal and external stress in athletes should be an area of further research.

Protein Expression Profiling Identifies Key Proteins and Pathways Involved in Growth Inhibitory Effects Exerted by Guggulsterone in Human Colorectal Cancer Cells

Colorectal cancer (CRC) is a leading killer cancer worldwide and one of the most common malignancies with increasing incidences of mortality. Guggulsterone (GS) is a plant sterol used for treatment of various ailments such as obesity, hyperlipidemia, diabetes, and arthritis. In the current study, anti-cancer effects of GS in human colorectal cancer cell line HCT 116 was tested, potential targets identified using mass spectrometry-based label-free shotgun proteomics approach and key pathways validated by proteome profiler antibody arrays. Comprehensive proteomic profiling identified 14 proteins as significantly dysregulated. Proteins involved in cell proliferation/migration, tumorigenesis, cell growth, metabolism, and DNA replication were downregulated while the protein with functional role in exocytosis/tumor suppression was found to be upregulated. Our study evidenced that GS treatment altered expression of Bcl-2 mediated the mitochondrial release of cytochrome c which triggered the formation of apoptosome as well as activation of caspase-3/7 leading to death of HCT 116 cells via intrinsic apoptosis pathway. GS treatment also induced expression of p53 protein while p21 expression was unaltered with no cell cycle arrest. In addition, GS was found to inhibit NF-kB signaling in colon cancer cells by quelling the expression of its regulated gene products Bcl-2, cIAP-1, and survivin.

Absolute quantification of targeted meat and allergenic protein additive peptide markers in meat products

We present an implementation of the absolute quantification (AQUA) method for monitoring of peptide abundance in complex mixtures of processed proteins. Specific peptide markers from meats (chicken, duck, goose, pork and beef) and common protein allergenic additives (soy, milk and egg white preparations) were chosen and synthesised with stable isotopes (13C and 15N) for use as internal standards. A wide range of food samples, from cooked or raw meat to sterilised pâté, was analysed by a triggered multiple reaction monitoring mode experiment and triple quadrupole mass spectrometry for the direct measure of tryptic peptides representing the amounts of specific proteins. Considerable differences among the abundances of meat and non-meat proteins were observed, and illegal addition and replacement of ingredients were discovered, i.e. undeclared addition of pork and egg white proteins, and illegal substitution of veal, goose and duck meat with cheaper pork.

Supramolecular Polymeric Assemblies for the Selective Depletion of Abundant Acidic Proteins in Serum

The analysis of low-level protein biomarkers in serum is precluded by the presence of other highly abundant serum proteins. Hence, the preliminary removal of serum albumin along with other abundant proteins in serum (i.e., immunoglobulins, transferrin, haptoglobin, α-2-macroglobulin, and apolipoproteins) is often a requirement prior to any biomarker analysis. In this work, we take advantage of the low isoelectric points (pI's) of these highly abundant proteins to selectively deplete them from serum by extraction using functionalized amphiphilic polymeric nanoassemblies. The selectivity of extraction is dependent on the pI of the protein and the extraction pH, which holds true even for extremely complex protein mixtures like serum. High extraction capacity is achieved by optimizing the extraction conditions and is found to be comparable to currently available methods for depletion. Depletion of these abundant acidic proteins allows for the enhanced detection of higher pI proteins and enables a 3 orders of magnitude increase in detection sensitivity for a putative cancer biomarker, demonstrating the utility of these polymeric assemblies for enhancing the analysis of the serum proteome.

Quantification of species-specific meat proteins in cooked and smoked sausages using infusion mass spectrometry

Label-free quantification combined with high-resolution infusion-based mass spectrometry (MS) was evaluated to authenticate ‘horse sausages’ made from horse meat and pork. Four types of industrially processed sausages, including cooked horse meat, pork and beef, and their mixtures were analysed. Quantitation and evaluation of the species composition were based on a set of 11 species-specific meat proteins and 14 unique heat-stable peptide markers. Using infusion MS, the highest distinguishing value was found in four proteins, namely, horse myosin-7 (MYH7_HORSE) and horse myoglobin (MYG_HORSE), porcine myosin-4 (MYH4_PIG) and bovine myoglobin (MYG_BOVIN). The limit of detection was 5% (w/w) for pork and beef in the three-component matrix and 1% (w/w) for horse meat. The proteins’ abundance was computed using a peak intensity measurement technique for precursor ions, based on the extracted ion currents/intensities of precursor ions. The procedure enabled discrimination between horse meat, pork and beef proteins, as well as estimation of the relative changes in protein abundance in all the examined samples. Substantial differences in the abundance of specific proteins were obtained from the pure meat samples, three-component mixtures and commercial sausages. The method may be useful in the preliminary screening of protein-rich food samples, aimed at fraud detection and estimation of the overall level of adulteration.

Detection of Functional Overreaching in Endurance Athletes Using Proteomics

No reliable biomarkers exist to identify athletes in various training states including functional overreaching (FOR), non-functional overreaching (NFOR), and overtraining syndrome (OTS). Participants (N = 10, age 38.3 ± 3.4 years) served as their own controls and in random, counterbalanced order either ran/cycled 2.5 h (70.0 ± 3.7% VO_2max) three days in a row (FOR) or sat in the lab (rest) (separated by three weeks; 7:00–9:30 am, overnight fasted state). Participants provided fingerprick samples for dried blood spot samples (DBS) pre- and post-exercise/rest, and then during two recovery days. DBS proteins were measured with nanoLC-MS in data-independent acquisition (DIA) mode, and 593 proteins were identified and quantified. Proteins were considered for the FOR cluster if they were elevated during one of the two recovery days but not more than one of the exercise days (compared to rest). The generalized estimating equation (GEE) was used to identify proteins linked to FOR. A total of 13 proteins was linked to FOR and most were associated with the acute phase response and innate immune system activation. This study used a system-wide proteomics approach to define a targeted panel of blood proteins related to FOR that could form the basis of future NFOR- and OTS-based studies.

ExSTA: External Standard Addition Method for Accurate High-Throughput Quantitation in Targeted Proteomics Experiments

PURPOSE

Targeted proteomics using MRM with stable-isotope-labeled internal-standard (SIS) peptides is the current method of choice for protein quantitation in complex biological matrices. Better quantitation can be achieved with the internal standard-addition method, where successive increments of synthesized natural form (NAT) of the endogenous analyte are added to each sample, a response curve is generated, and the endogenous concentration is determined at the x-intercept. Internal NAT-addition, however, requires multiple analyses of each sample, resulting in increased sample consumption and analysis time.

EXPERIMENTAL DESIGN

To compare the following three methods, an MRM assay for 34 high-to-moderate abundance human plasma proteins is used: classical internal SIS-addition, internal NAT-addition, and external NAT-addition-generated in buffer using NAT and SIS peptides. Using endogenous-free chicken plasma, the accuracy is also evaluated.

RESULTS

The internal NAT-addition outperforms the other two in precision and accuracy. However, the curves derived by internal vs. external NAT-addition differ by only ≈3.8% in slope, providing comparable accuracies and precision with good CV values.

CONCLUSIONS AND CLINICAL RELEVANCE

While the internal NAT-addition method may be "ideal", this new external NAT-addition can be used to determine the concentration of high-to-moderate abundance endogenous plasma proteins, providing a robust and cost-effective alternative for clinical analyses or other high-throughput applications.

Quantitative Proteomic Analysis of the Human Nucleolus

Recent years have witnessed spectacular progress in the field of mass spectrometry (MS)-based quantitative proteomics, including advances in instrumentation, chromatography, sample preparation methods, and experimental design for multidimensional analyses. It is now possible not only to identify most of the protein components of a cell proteome in a single experiment, but also to describe additional proteome dimensions, such as protein turnover rates, posttranslational modifications, and subcellular localization. Furthermore, by comparing the proteome at different time points, it is possible to create a "time-lapse" view of proteome dynamics. By combining high-throughput quantitative proteomics with detailed subcellular fractionation protocols and data analysis techniques it is also now possible to characterize in detail the proteomes of specific subcellular organelles, providing important insights into cell regulatory mechanisms and physiological responses. In this chapter we present a reliable workflow and protocol for MS-based analysis and quantitation of the proteome of nucleoli isolated from human cells. The protocol presented is based on a SILAC analysis of human MCF10A-Src-ER cells with analysis performed on a Q-Exactive Plus Orbitrap MS instrument (Thermo Fisher Scientific). The subsequent chapter describes how to process the resulting raw MS files from this experiment using MaxQuant software and data analysis procedures to evaluate the nucleolar proteome using customized R scripts.

Distance-of-Flight Mass Spectrometry: What, Why, and How?

Distance-of-flight mass spectrometry (DOFMS) separates ions of different mass-to-charge (m/z) by the distance they travel in a given time after acceleration. Like time-of-flight mass spectrometry (TOFMS), separation and mass assignment are based on ion velocity. However, DOFMS is not a variant of TOFMS; different methods of ion focusing and detection are used. In DOFMS, ions are driven orthogonally, at the detection time, onto an array of detectors parallel to the flight path. Through the independent detection of each m/z, DOFMS can provide both wider dynamic range and increased throughput for m/z of interest compared with conventional TOFMS. The iso-mass focusing and detection of ions is achieved by constant-momentum acceleration (CMA) and a linear-field ion mirror. Improved energy focus (including turn-around) is achieved in DOFMS, but the initial spatial dispersion of ions remains unchanged upon detection. Therefore, the point-source nature of surface ionization techniques could put them at an advantage for DOFMS. To date, three types of position-sensitive detectors have been used for DOFMS: a microchannel plate with a phosphorescent screen, a focal plane camera, and an IonCCD array; advances in detector technology will likely improve DOFMS figures-of-merit. In addition, the combination of CMA with TOF detection has provided improved resolution and duty factor over a narrow m/z range (compared with conventional, single-pass TOFMS). The unique characteristics of DOFMS can enable the intact collection of large biomolecules, clusters, and organisms. DOFMS might also play a key role in achieving the long-sought goal of simultaneous MS/MS. Graphical Abstract ᅟ.

Modifications to the composition of the hyphal outer layer of Aspergillus fumigatus modulates HUVEC proteins related to inflammatory and stress responses

Aspergillus fumigatus, the main etiologic agent causing invasive aspergillosis, can induce an inflammatory response and a prothrombotic phenotype upon contact with human umbilical vein endothelial cells (HUVECs). However, the fungal molecules involved in this endothelial response remain unknown. A. fumigatus hyphae produce an extracellular matrix composed of galactomannan, galactosaminogalactan and α-(1,3)-glucan. In this study, we investigated the consequences of UGM1 gene deletion in A. fumigatus, which produces a mutant with increased galactosaminogalactan production. The ∆ugm1 mutant exhibited an HUVEC-hyperadhesive phenotype and induced increased endothelial TNF-α secretion and tissue factor mRNA overexpression in this "semi-professional" immune host cell. Using a shotgun proteomics approach, we show that the A. fumigatus ∆ugm1 strain can modulate the levels of proteins in important endothelial pathways related to the inflammatory response mediated by TNF-α and to stress response pathways. Furthermore, a purified galactosaminogalactan fraction was also able to induce TNF-α secretion and the coincident HUVEC pathways regulated by the ∆ugm1 mutant, which overexpresses this component, as demonstrated by fluorescence microscopy. This work contributes new data regarding endothelial mechanisms in response to A. fumigatus infection.

SIGNIFICANCE

Invasive aspergillosis is the main opportunistic fungal infection described in neutropenic hematologic patients. One important clinical aspect of this invasive fungal infection is vascular thrombosis, which could be related, at least in part, to the activation of endothelial cells, as shown in previous reports from our group. It is known that direct contact between the A. fumigatus hyphal cell wall and the HUVEC cell surface is necessary to induce an endothelial prothrombotic phenotype and secretion of pro-inflammatory cytokines, though the cell surface components of this angioinvasive fungus that trigger this endothelial response are unknown. The present work employs a discovery-driven proteomics approach to reveal the role of one important cell wall polysaccharide of A. fumigatus, galactosaminogalactan, in the HUVEC interaction and the consequent mechanisms of endothelial activation. This is the first report of the overall panel of proteins related to the HUVEC response to a specific and purified cell wall component of the angioinvasive fungus A. fumigatus.

Mass Spectrometry-Based Bacterial Proteomics: Focus on Dermatologic Microbial Pathogens

The composition of human skin acts as a natural habitat for various bacterial species that function in a commensal and symbiotic fashion. In a healthy individual, bacterial flora serves to protect the host. Under certain conditions such as minor trauma, impaired host immunity, or environmental factors, the risk of developing skin infections is increased. Although a large majority of bacterial associated skin infections are common, a portion can potentially manifest into clinically significant morbidity. For example, Gram-positive species that typically reside on the skin such as Staphylococcus and Streptococcus can cause numerous epidermal (impetigo, ecthyma) and dermal (cellulitis, necrotizing fasciitis, erysipelas) skin infections. Moreover, the increasing incidence of bacterial antibiotic resistance represents a serious challenge to modern medicine and threatens the health care system. Therefore, it is critical to develop tools and strategies that can allow us to better elucidate the nature and mechanism of bacterial virulence. To this end, mass spectrometry (MS)-based proteomics has been revolutionizing biomedical research, and has positively impacted the microbiology field. Advances in MS technologies have paved the way for numerous bacterial proteomes and their respective post translational modifications (PTMs) to be accurately identified and quantified in a high throughput and robust fashion. This technological platform offers critical information with regards to signal transduction, adherence, and microbial–host interactions associated with bacterial pathogenesis. This mini-review serves to highlight the current progress proteomics has contributed toward the understanding of bacteria that are associated with skin related diseases, infections, and antibiotic resistance.

The application of targeted mass spectrometry-based strategies to the detection and localization of post-translational modifications

This review describes some of the more interesting and imaginative ways in which mass spectrometry has been utilized to study a number of important post-translational modifications over the past two decades; from circa 1990 to 2013. A diverse range of modifications is covered, including citrullination, sulfation, hydroxylation and sumoylation. A summary of the biological role of each modification described, along with some brief mechanistic detail, is also included. Emphasis has been placed on strategies specifically aimed at detecting target modifications, as opposed to more serendipitous modification discovery approaches, which rely upon straightforward product ion scanning methods. The authors have intentionally excluded from this review both phosphorylation and glycosylation since these major modifications have been extensively reviewed elsewhere.

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Absolute quantification of target proteins within complex biological samples is critical to a wide range of research and clinical applications. This protocol provides step-by-step instructions for the development and application of quantitative assays using selected reaction monitoring (SRM) mass spectrometry (MS). First, likely quantotypic target peptides are identified based on numerous criteria. This includes identifying proteotypic peptides, avoiding sites of posttranslational modification, and analyzing the uniqueness of the target peptide to the target protein. Next, crude external peptide standards are synthesized and used to develop SRM assays, and the resulting assays are used to perform qualitative analyses of the biological samples. Finally, purified, quantified, heavy isotope labeled internal peptide standards are prepared and used to perform isotope dilution series SRM assays. Analysis of all of the resulting MS data is presented. This protocol was used to accurately assay the absolute abundance of proteins of the chemotaxis signaling pathway within RAW 264.7 cells (a mouse monocyte/macrophage cell line). The quantification of Gi2 (a heterotrimeric G-protein α-subunit) is described in detail.

Applying multiple proteases to direct digestion of hundred-scale cell samples for proteome analysis

RATIONALE

Analyzing the proteome on the scale of only several hundred cells with mass spectrometry has great significance for applications with limited sample amounts. We applied multiple proteases to the direct digestion of cells and compared the identified proteins both qualitatively and quantitatively.

METHODS

Three hundred cells were directly digested by trypsin, chymotrypsin, or the combination of trypsin and chymotrypsin. The peptides were identified using a LTQ-Orbitrap XL, and data were analyzed using MaxQuant software.

RESULTS

Different proteases produced different identified protein numbers. Trypsin proved to be the best choice for generating the largest protein number, while other proteases complemented the identification results of trypsin by increasing protein sequence coverage. Concerning the quantitative perspective, using trypsin would produce the biggest number of proteins quantifiable by intensity-based absolute quantification (iBAQ).

CONCLUSIONS

When hundred-scale cell samples are analyzed, an optimum choice of proteases should be made to realize different analytical objectives.

Proteomics in cancer research: Are we ready for clinical practice?

Although genomics has delivered major advances in cancer prognostics, treatment and diagnostics, it still only provides a static image of the situation. To study more dynamic molecular entities, proteomics has been introduced into the cancer research field more than a decade ago. Currently, however, the impact of clinical proteomics on patient management and clinical decision-making is low and the implementations of scientific results in the clinic appear to be scarce. The search for cancer-related biomarkers with proteomics however, has major potential to improve risk assessment, early detection, diagnosis, prognosis, treatment selection and monitoring. In this review, we provide an overview of the transition of oncoproteomics towards translational oncology. We describe which lessons are learned from currently approved protein biomarkers and previous proteomic studies, what the pitfalls and challenges are in clinical proteomics applications, and how proteomic research can be successfully translated into medical practice.

Discovery and Validation of Predictive Biomarkers of Survival for Non-small Cell Lung Cancer Patients Undergoing Radical Radiotherapy: Two Proteins With Predictive Value

Lung cancer is the most frequent cause of cancer-related death world-wide. Radiotherapy alone or in conjunction with chemotherapy is the standard treatment for locally advanced non-small cell lung cancer (NSCLC). Currently there is no predictive marker with clinical utility to guide treatment decisions in NSCLC patients undergoing radiotherapy. Identification of such markers would allow treatment options to be considered for more effective therapy. To enable the identification of appropriate protein biomarkers, plasma samples were collected from patients with non-small cell lung cancer before and during radiotherapy for longitudinal comparison following a protocol that carries sufficient power for effective discovery proteomics. Plasma samples from patients pre- and during radiotherapy who had survived > 18 mo were compared to the same time points from patients who survived < 14 mo using an 8 channel isobaric tagging tandem mass spectrometry discovery proteomics platform. Over 650 proteins were detected and relatively quantified. Proteins which showed a change during radiotherapy were selected for validation using an orthogonal antibody-based approach. Two of these proteins were verified in a separate patient cohort: values of CRP and LRG1 combined gave a highly significant indication of extended survival post one week of radiotherapy treatment.

Analytical platforms in vitreoretinal proteomics

Current proteomic technologies can effectively be used to study the proteins of the vitreous body and retina in health and disease. The use of appropriate samples, analytical platform and bioinformatic method are essential factors to consider when undertaking such studies. Certain proteins may hinder the detection and evaluation of more relevant proteins associated with pathological processes if not carefully considered, particularly in the sample preparation and data analysis stages. The utilization of more than one quantification technique and database search program to expand the level of proteome coverage and analysis will help to generate more robust and worthwhile results. This review discusses important aspects of sample processing and the use of label and label-free quantitative proteomics strategies applied to the vitreous and retina.

Inflammation decreases keratin level in ulcerative colitis; inadequate restoration associates with increased risk of colitis-associated cancer

Background

Keratins are intermediate filament (IF) proteins, which form part of the epithelial cytoskeleton and which have been implicated pathology of inflammatory bowel diseases (IBD).

Methods

In this study biopsies were obtained from IBD patients grouped by disease duration and subtype into eight categories based on cancer risk and inflammatory status: quiescent recent onset (<5 years) UC (ROUC); UC with primary sclerosing cholangitis; quiescent long-standing pancolitis (20–40 years) (LSPC); active colitis and non-inflamed proximal colonic mucosa; pancolitis with dysplasia-both dysplastic lesions (DT) and distal rectal mucosa (DR); control group without pathology. Alterations in IF protein composition across the groups were determined by quantitative proteomics. Key protein changes were validated by western immunoblotting and immunohistochemical analysis.

Result

Acute inflammation resulted in reduced K8, K18, K19 and VIM (all p<0.05) compared to controls and non inflamed mucosa; reduced levels of if– associated proteins were also seen in DT and DR. Increased levels of keratins in LSPC was noted relative to controls or ROUC (K8, K18, K19 and VIM, p<0.05). Multiple K8 forms were noted on immunoblotting, with K8 phosphorylation reduced in progressive disease along with an increase in VIM:K8 ratio. K8 levels and phosphorylation are reduced in acute inflammation but appear restored or elevated in subjects with clinical and endoscopic remission (LSPC) but not apparent in subjects with elevated risk of cancer.

Conclusions

These data suggest that keratin regulation in remission may influence subsequent cancer risk.

Ribosomal proteomics: Strategies, approaches, and perspectives

Over the past few decades, proteomic research has seen unprecedented development due to technological advancement. However, whole-cell proteomics still has limitations with respect to sample complexity and the accuracy of determining protein locations. To deal with these limitations, several subcellular proteomic studies have been initiated. Nevertheless, compared to other subcellular proteomic fields, such as mitochondrial proteomics, ribosomal proteomics has lagged behind due to the long-held idea that the ribosome is just a translation machine. Recently, with the proposed ribosome filter hypothesis and subsequent studies of ribosome-specific regulatory capacity, ribosomal proteomics has become a promising chapter for both proteomic and ribosomal research. In this review, we discuss the current strategies and approaches in ribosomal proteomics and the efficacies as well as disadvantages of individual approaches for further improvement.

Multi-functional MBIT for peptide tandem mass spectrometry

Isobaric tags have been widely used for the identification and quantification of proteins in mass spectrometry-based proteomics. The mass-balanced, (1) H/(2) H isotope-coded dipeptide tag (MBIT) is a multifunctional isobaric tag based on N-acetyl-Ala-Ala dipeptide containing an amine-reactive linker that conjugates the tag to the primary amines of proteolytic peptides. MBITs provide a pair of isotope-coded quantitation signals separated by 3 Da, which enables 2-plex quantification and identification of proteins in the 15-250 fmol range. Various MBITs diversified at the N-acetyl group or at the side chain of the first alanine provide a pair of bs ions as low-mass quantitation signals in a distinct mass window. Thus, a combination of different MBITs allows multiplex quantification of proteins in a single liquid chromatography-mass spectrometry experiment. Unlike other isobaric tags, MBITs also offer a pair of ys ions as high-mass quantitation signals in a noise-free region, facilitating protein quantification in quadrupole ion trap mass spectrometers. Uniquely, bS ions, forming N-protonated oxazolone, undergo unimolecular dissociation and generate the secondary low-mass quantitation signals, aS ions. The yield of aS ions derived from bS ions can be used to measure the temperature of bS ions, which enables a reproducible acquisition of the peptide tandem mass spectra. Thus, MBITs enable multiplexed quantitation of proteins and the concurrent measurement of ion temperature using bS and aS signal ions as well as the isobaric protein quantitation in resonance-type ion trap using yS (complement of bS ) signal ions. This review provides an overview of MBITs with a focus on the multi-functionality that has been successfully demonstrated in the peptide tandem mass spectrometry.

Choice of LC-MS methods for the absolute quantification of drug-metabolizing enzymes and transporters in human tissue: a comparative cost analysis

The quantification of drug-metabolizing enzymes and transporters is important for in vitro-in vivo extrapolation (IVIVE) of xenobiotic clearance, which has become an integral part of drug development. There are different mass spectrometry-based techniques used for quantitative proteomics, and as more laboratories are opting for the use of these methods, selecting the most appropriate tool is becoming a concern. For the first time, we attempt to determine the significance of cost of different LC-MS methods of quantitative analysis of these proteins and to present a framework to objectively assess the choice of the techniques. Based on our analysis, quantification using labeled internal standards is more expensive per sample but provides higher quality data than label-free quantification. Quantification using absolute quantification synthetic peptides is the approach of choice for analyzing less than nine proteins, whereas when quantifying a defined set of proteins (10-50), such as enzymes, in a reasonably large number of samples (20-100), the quantification concatemer technique is more economical, followed by label-free quantification. When analyzing proteomes or sub-proteomes (≥500 proteins), label-free quantification is more cost-effective than the use of labeled internal standards. A cost-benefit approach is described to assess the choice of the most appropriate mass spectrometry-based approach for the quantification of proteins relevant to IVIVE.

Label-free quantitative mass spectrometry reveals a panel of differentially expressed proteins in colorectal cancer

To identify potential biomarkers involved in CRC, a shotgun proteomic method was applied to identify soluble proteins in three CRCs and matched normal mucosal tissues using high-performance liquid chromatography and mass spectrometry. Label-free protein profiling of three CRCs and matched normal mucosal tissues were then conducted to quantify and compare proteins. Results showed that 67 of the 784 identified proteins were linked to CRC (28 upregulated and 39 downregulated). Gene Ontology and DAVID databases were searched to identify the location and function of differential proteins that were related to the biological processes of binding, cell structure, signal transduction, cell adhesion, and so on. Among the differentially expressed proteins, tropomyosin-3 (TPM3), endoplasmic reticulum resident protein 29 (ERp29), 18 kDa cationic antimicrobial protein (CAMP), and heat shock 70 kDa protein 8 (HSPA8) were verified to be upregulated in CRC tissue and seven cell lines through western blot analysis. Furthermore, the upregulation of TPM3, ERp29, CAMP, and HSPA8 was validated in 69 CRCs byimmunohistochemistry (IHC) analysis. Combination of TPM3, ERp29, CAMP, and HSPA8 can identify CRC from matched normal mucosal achieving an accuracy of 73.2% using IHC score. These results suggest that TPM3, ERp29, CAMP, and HSPA8 are great potential IHC diagnostic biomarkers for CRC.

Qualis-SIS: automated standard curve generation and quality assessment for multiplexed targeted quantitative proteomic experiments with labeled standards

Multiplexed targeted quantitative proteomics typically utilizes multiple reaction monitoring and allows the optimized quantification of a large number of proteins. One challenge, however, is the large amount of data that needs to be reviewed, analyzed, and interpreted. Different vendors provide software for their instruments, which determine the recorded responses of the heavy and endogenous peptides and perform the response-curve integration. Bringing multiplexed data together and generating standard curves is often an off-line step accomplished, for example, with spreadsheet software. This can be laborious, as it requires determining the concentration levels that meet the required accuracy and precision criteria in an iterative process. We present here a computer program, Qualis-SIS, that generates standard curves from multiplexed MRM experiments and determines analyte concentrations in biological samples. Multiple level-removal algorithms and acceptance criteria for concentration levels are implemented. When used to apply the standard curve to new samples, the software flags each measurement according to its quality. From the user's perspective, the data processing is instantaneous due to the reactivity paradigm used, and the user can download the results of the stepwise calculations for further processing, if necessary. This allows for more consistent data analysis and can dramatically accelerate the downstream data analysis.

Antibody-based proteomics and biomarker research - current status and limitations

Antibody-based proteomics play a very important role in biomarker discovery and validation, facilitating the high-throughput evaluation of candidate markers. Most proteomics-driven discovery is nowadays based on the use of MS. MS has many advantages, including its suitability for hypothesis-free biomarker discovery, since information on protein content of a sample is not required prior to analysis. However, MS presents one main caveat which is the limited sensitivity in complex samples, especially for body fluids, where protein expression covers a huge dynamic range. Antibody-based technologies remain the main solution to address this challenge since they reach higher sensitivity. In this article, we review the benefits and limitations of antibody-based proteomics in preclinical and clinical biomarker research for discovery and validation in body fluids and tissue. The combination of antibodies and MS, utilizing the best of both worlds, opens new avenues in biomarker research.

Hold or fold--proteins in advanced heart failure and myocardial recovery

Advanced heart failure (AHF) describes the subset of heart failure patients refractory to conventional medical therapy. For some AHF patients, the use of mechanical circulatory support (MCS) provides an intermediary "bridge" step for transplant-eligible patients or an alternative therapy for transplant-ineligible patients. Over the past 20 years, clinical observations have revealed that approximately 1% of patients with MCS undergo significant reverse remodeling to the point where the device can be explanted. Unfortunately, it is unclear why some patients experience durable, sustained myocardial remission, while others redevelop heart failure (i.e. which hearts "hold" and which hearts "fold"). In this review, we outline unmet clinical needs related to treating patients with MCS, provide an overview of protein dynamics in the reverse-remodeling process, and propose specific areas where we expect MS and proteomic analyses will have significant impact on our understanding of disease progression, molecular mechanisms of recovery, and provide new markers with prognostic value that can positively impact patient care. Complimentary perspectives are provided with the goal of making this important topic accessible and relevant to both a clinical and basic science audience, as the intersection of these disciplines is required to advance the field.

Farm animal serum proteomics and impact on human health

Due to the incompleteness of animal genome sequencing, the analysis and characterization of serum proteomes of most farm animals are still in their infancy, compared to the already well-documented human serum proteome. This review focuses on the implications of the farm animal serum proteomics in order to identify novel biomarkers for animal welfare, early diagnosis, prognosis and monitoring of infectious disease treatment, and develop new vaccines, aiming at determining the reciprocal benefits for humans and animals.

Protein-centric N-glycoproteomics analysis of membrane and plasma membrane proteins

The advent of proteomics technology has transformed our understanding of biological membranes. The challenges for studying membrane proteins have inspired the development of many analytical and bioanalytical tools, and the techniques of glycoproteomics have emerged as an effective means to enrich and characterize membrane and plasma-membrane proteomes. This Review summarizes the development of various glycoproteomics techniques to overcome the hurdles formed by the unique structures and behaviors of membrane proteins with a focus on N-glycoproteomics. Example contributions of N-glycoproteomics to the understanding of membrane biology are provided, and the areas that require future technical breakthroughs are discussed.

Quantitative proteomic analysis of hepatocyte-secreted extracellular vesicles reveals candidate markers for liver toxicity

Extracellular vesicles have created great interest as possible source of biomarkers for different biological processes and diseases. Although the biological function of these vesicles is not fully understood, it is clear that they participate in the removal of unnecessary cellular material and act as carriers of various macromolecules and signals between the cells. In this report, we analyzed the proteome of extracellular vesicles secreted by primary hepatocytes. We used one- and two-dimensional liquid chromatography combined with data-independent mass spectrometry. Employing label-free quantitative proteomics, we detected significant changes in vesicle protein expression levels in this in vitro model after exposure to well-known liver toxins (galactosamine and Escherichia coli-derived lipopolysaccharide). The results allowed us to identify candidate markers for liver injury. We validated a number of these markers in vivo, providing the basis for the development of novel methods to evaluate drug toxicity. This report strongly supports the application of proteomics in the study of extracellular vesicles released by well-controlled in vitro cellular systems. Analysis of such systems should help to identify specific markers for various biological processes and pathological conditions.

BIOLOGICAL SIGNIFICANCE

Identification of low invasive candidate marker for hepatotoxicity. Support to apply proteomics in the study of extracellular vesicles released by well-controlled in vitro cellular systems to identify low invasive markers for diseases.

SILAC labeling coupled to shotgun proteomics analysis of membrane proteins of liver stem/hepatocyte allows to candidate the inhibition of TGF-beta pathway as causal to differentiation

BACKGROUND

Despite extensive research on hepatic cells precursors and their differentiated states, much remains to be learned about the mechanism underlying the self-renewal and differentiation.

RESULTS

We apply the SILAC (stable isotope labeling by amino acids in cell culture) approach to quantitatively compare the membrane proteome of the resident liver stem cells (RLSCs) and their progeny spontaneously differentiated into epithelial/hepatocyte (RLSCdH). By means of nanoLC-MALDI-TOF/TOF approach, we identified and quantified 248 membrane proteins and 57 of them were found modulated during hepatocyte differentiation. Functional clustering of differentially expressed proteins by Ingenuity Pathway Analysis revealed that the most of membrane proteins found to be modulated are involved in cell-to-cell signaling/interaction pathways. Moreover, the upstream prediction analysis of proteins involved in cell-to-cell signaling and interaction unveiled that the activation of the mesenchymal to epithelial transition (MET), by the repression of TGFB1/Slug signaling, may be causal to hepatocyte differentiation.

CONCLUSIONS

Taken together, this study increases the understanding of the underlying mechanisms modulating the complex biological processes of hepatic stem cell proliferation and differentiation.

Lysine and arginine content of proteins: computational analysis suggests a new tool for solubility design

Prediction and engineering of protein solubility is an important but imprecise area. While some features are routinely used, such as the avoidance of extensive non-polar surface area, scope remains for benchmarking of sequence and structural features with experimental data. We study properties in the context of experimental solubilities, protein gene expression levels, and families of abundant proteins (serum albumin and myoglobin) and their less abundant paralogues. A common feature that emerges for proteins with elevated solubility and at higher expression and abundance levels is an increased ratio of lysine content to arginine content. We suggest that the same properties of arginine that give rise to its recorded propensity for specific interaction surfaces also lead to favorable interactions at nonspecific contacts, and thus lysine is favored for proteins at relatively high concentration. A survey of protein therapeutics shows that a significant subset possesses a relatively low lysine to arginine ratio, and therefore may not be favored for high protein concentration. We conclude that modulation of lysine and arginine content could prove a useful and relatively simple addition to the toolkit available for engineering protein solubility in biotechnological applications.