Advantageous uses of mass spectrometry for the quantification of proteins

Downregulation of Dystrophin Expression Occurs across Diverse Tumors, Correlates with the Age of Onset, Staging and Reduced Survival of Patients

Altered dystrophin expression was found in some tumors and recent studies identified a developmental onset of Duchenne muscular dystrophy (DMD). Given that embryogenesis and carcinogenesis share many mechanisms, we analyzed a broad spectrum of tumors to establish whether dystrophin alteration evokes related outcomes. Transcriptomic, proteomic, and mutation datasets from fifty tumor tissues and matching controls (10,894 samples) and 140 corresponding tumor cell lines were analyzed. Interestingly, dystrophin transcripts and protein expression were found widespread across healthy tissues and at housekeeping gene levels. In 80% of tumors, DMD expression was reduced due to transcriptional downregulation and not somatic mutations. The full-length transcript encoding Dp427 was decreased in 68% of tumors, while Dp71 variants showed variability of expression. Notably, low expression of dystrophins was associated with a more advanced stage, older age of onset, and reduced survival across different tumors. Hierarchical clustering analysis of DMD transcripts distinguished malignant from control tissues. Transcriptomes of primary tumors and tumor cell lines with low DMD expression showed enrichment of specific pathways in the differentially expressed genes. Pathways consistently identified: ECM-receptor interaction, calcium signaling, and PI3K-Akt are also altered in DMD muscle. Therefore, the importance of this largest known gene extends beyond its roles identified in DMD, and certainly into oncology.

Single Cerebral Organoid Mass Spectrometry of Cell-Specific Protein and Glycosphingolipid Traits

Cerebral organoids are a prolific research topic and an emerging model system for neurological diseases in human neurobiology. However, the batch-to-batch reproducibility of current cultivation protocols is challenging and thus requires a high-throughput methodology to comprehensively characterize cerebral organoid cytoarchitecture and neural development. We report a mass spectrometry-based protocol to quantify neural tissue cell markers, cell surface lipids, and housekeeping proteins in a single organoid. Profiled traits probe the development of neural stem cells, radial glial cells, neurons, and astrocytes. We assessed the cell population heterogeneity in individually profiled organoids in the early and late neurogenesis stages. Here, we present a unifying view of cell-type specificity of profiled protein and lipid traits in neural tissue. Our workflow characterizes the cytoarchitecture, differentiation stage, and batch cultivation variation on an individual cerebral organoid level.

Advances in High Throughput Proteomics Profiling in Establishing Potential Biomarkers for Gastrointestinal Cancer

Gastrointestinal cancers (GICs) remain the most diagnosed cancers and accounted for the highest cancer-related death globally. The prognosis and treatment outcomes of many GICs are poor because most of the cases are diagnosed in advanced metastatic stages. This is primarily attributed to the deficiency of effective and reliable early diagnostic biomarkers. The existing biomarkers for GICs diagnosis exhibited inadequate specificity and sensitivity. To improve the early diagnosis of GICs, biomarkers with higher specificity and sensitivity are warranted. Proteomics study and its functional analysis focus on elucidating physiological and biological functions of unknown or annotated proteins and deciphering cellular mechanisms at molecular levels. In addition, quantitative analysis of translational proteomics is a promising approach in enhancing the early identification and proper management of GICs. In this review, we focus on the advances in mass spectrometry along with the quantitative and functional analysis of proteomics data that contributes to the establishment of biomarkers for GICs including, colorectal, gastric, hepatocellular, pancreatic, and esophageal cancer. We also discuss the future challenges in the validation of proteomics-based biomarkers for their translation into clinics.

Mass spectrometry-based methods for robust measurement of Alzheimer's disease biomarkers in biological fluids

Alzheimer's disease (AD) is the most common form of dementia affecting 60%-70% of people afflicted with this disease. Accurate antemortem diagnosis is urgently needed for early detection of AD to enable reliable estimation of prognosis, intervention, and monitoring of the disease. The National Institute on Aging/Alzheimer's Association sponsored the 'Research Framework: towards a biological definition of AD', which recommends using different biomarkers in living persons for a biomarker-based definition of AD regardless of clinical status. Fluid biomarkers represent one of key groups of them. Since cerebrospinal fluid (CSF) is in direct contact with brain and many proteins present in the brain can be detected in CSF, this fluid has been regarded as the best biofluid in which to measure AD biomarkers. Recently, technological advancements in protein detection made possible the effective study of plasma AD biomarkers despite their significantly lower concentrations versus to that in CSF. This and other challenges that face plasma-based biomarker measurements can be overcome by using mass spectrometry. In this review, we discuss AD biomarkers which can be reliably measured in CSF and plasma using targeted mass spectrometry coupled to liquid chromatography (LC/MS/MS). We describe progress in LC/MS/MS methods' development, emphasize the challenges, and summarize major findings. We also highlight the role of mass spectrometry and progress made in the process of global standardization of the measurement of Aβ42/Aβ40. Finally, we briefly describe exploratory proteomics which seek to identify new biomarkers that can contribute to detection of co-pathological processes that are common in sporadic AD.

Tandem Mass Tag-Based Serum Proteome Profiling for Biomarker Discovery in Young Duchenne Muscular Dystrophy Boys

Blood-accessible molecular biomarkers are becoming highly attractive tools to assess disease progression and response to therapies in Duchenne muscular dystrophy (DMD) especially in very young patients for whom other outcome measures remain subjective and challenging. In this study, we have standardized a highly specific and reproducible multiplexing mass spectrometry method using the tandem mass tag (TMT) strategy in combination with depletion of abundant proteins from serum and high-pH reversed-phase peptide fractionation. Differential proteome profiling of 4 year-old DMD boys (n = 9) and age-matched healthy controls (n = 9) identified 38 elevated and 50 decreased serum proteins (adjusted P < 0.05, FDR <0.05) in the DMD group relative to the healthy control group. As expected, we confirmed previously reported biomarkers but also identified novel biomarkers. These included novel muscle injury-associated biomarkers such as telethonin, smoothelin-like protein 1, cofilin-1, and plectin, additional muscle-specific enzymes such as UTP-glucose-1-phosphate uridylyltransferase, aspartate aminotransferase, pyruvate kinase PKM, lactotransferrin, tissue alpha-l-fucosidase, pantetheinase, and ficolin-1, and some pro-inflammatory and cell adhesion-associated biomarkers such as leukosialin, macrophage receptor MARCO, vitronectin, galectin-3-binding protein, and ProSAAS. The workflow including serum depletion, sample processing, and mass spectrometry analysis was found to be reproducible and stable over time with CV < 20%. Furthermore, the method was found to be superior in terms of specificity compared to other multiplexing affinity-based methods. These findings demonstrate the specificity and reliability of TMT-based mass spectrometry methods in detection and identification of serum biomarkers in presymptomatic young DMD patients.

A proteome-wide immuno-mass spectrometric identification of serum autoantibodies

Background

Autoantibodies are produced when tolerance to self-antigens is broken and they can be mediators of tissue injury and systemic inflammation. They are excellent biomarkers because they are minimally invasive to screen and are highly abundant in serum due to limited proteolysis and slow clearance. Conventionally used methods of identifying autoantibodies in patient sera include indirect immunofluorescence, enzyme-linked immunoabsorbent assays (ELISAs) and protein microarrays. Here we present a novel proteome-wide immuno-mass spectrometric method to identify serum autoantibody targets.

Methods

Serum samples from patients with inflammatory bowel disease (IBD) were analyzed by ELISA for the presence of autoantibodies to CUB and zona pellucida-like domain-containing protein 1 (CUZD1). Protein was extracted from the human pancreas as well as 16 other human tissues to make a complex tissue lysate protein mixture. Antibodies in patient sera were immobilized and purified on protein G magnetic beads and subsequently incubated with pancreatic lysate containing CUZD1 or the aforementioned complex tissue lysate. After extensive washing, antibody-bound protein antigens were trypsin-digested and identified using shotgun mass spectrometry.

Results

The protocol was optimized for the immunoaffinity purification of autoantibody targets from tissue lysate, using CUZD1 from pancreatic lysate and anti-CUZD1 autoantibodies present in IBD patient serum as a proof-of-concept. Pancreatic secretory granule membrane major glycoprotein 2, whose autoantibodies are a known biomarker of Crohn’s disease, was also immunoprecipitated from IBD patient serum, as an additional internal positive control.

Conclusions

This study demonstrates the effectiveness of a proteomic approach to identify serum autoantibody targets, using immunoaffinity purification followed by tandem mass spectrometry. Our methodology is applicable for proteome-wide analysis of autoantibody targets in a wide variety of clinical settings.

Electronic supplementary material

The online version of this article (10.1186/s12014-019-9246-0) contains supplementary material, which is available to authorized users.

Liquid Biopsies in Lung Cancer: Four Emerging Technologies and Potential Clinical Applications

Background: Liquid biopsies offer a promising alternative to tissue samples, providing non-invasive diagnostic approaches or serial monitoring of disease evolution. However, certain challenges remain, and the full potential of liquid biopsies has yet to be reached. Here we report several methodological approaches to interrogate liquid biopsies using circulating tumour cell (CTC) enumeration and characterisation, transcriptomics, Raman spectroscopy, and copy number instability (CNI) scores using blood samples of lung cancer (LC) patients. Methods: We choose LC; since it still is the most common cause of cancer-related mortality worldwide, and therefore there is a need for development of new non-invasive diagnostic/prognostic technologies. Changes in gene expression were assessed using RNA-seq, and in CTCs using ImageStream, an imaging flow-cytometer. CNI scores, from paired tissue/ctDNA were also explored. Raman spectroscopy was used to provide chemical fingerprints of plasma samples. Results: CTCs were detected in all LC patients (n = 10). We observed a significant increase in CTC levels in LC patients (n = 10) compared to controls (n = 21). A similar CNI was noted in the tissue and plasma of 2 patients, where higher CNI scores corresponded with poorer outcome. Significant changes in Raman spectra (carotenoid concentrations) were noted in LC patients (n = 20) compared to controls (n = 10). RNA-seq revealed differential expression of 21 genes between LC cases and controls in both LC tissue and blood samples. Conclusions: Liquid biopsies can potentially provide a more comprehensive picture of the disease compared to a single tissue biopsy. CTC enumeration is feasible and sensitive for LC patients. Molecular profiling of CTCs is also possible from total blood. CNI scores and Raman spectra require further investigation. Further work is being undertaken to explore these methods of detection in a larger LC cohort.

Mass spectrometry: A platform for biomarker discovery and validation for Alzheimer's and Parkinson's diseases

Accurate, reliable, and objective biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), and related age-associated neurodegenerative disorders are urgently needed to assist in both diagnosis, particularly at early stages, and monitoring of disease progression. Technological advancements in protein detection platforms over the last few decades have resulted in a plethora of reported molecular biomarker candidates for both AD and PD; however, very few of these candidates are developed beyond the discovery phase of the biomarker development pipeline, a reflection of the current bottleneck within the field. In this review, the expanded use of selected reaction monitoring (SRM) targeted mass spectrometry will be discussed in detail as a platform for systematic verification of large panels of protein biomarker candidates prior to costly validation testing. We also advocate for the coupling of discovery-based proteomics with modern targeted MS-based approaches (e.g., SRM) within a single study in future workflows to expedite biomarker development and validation for AD and PD. It is our hope that improving the efficiency within the biomarker development process by use of an SRM pipeline may ultimately hasten the development of biomarkers that both decrease misdiagnosis of AD and PD and ultimately lead to detection at early stages of disease and objective assessment of disease progression. This article is part of the special issue "Proteomics".

Analysis of significant protein abundance from multiple reaction-monitoring data

Background

Discovering reliable protein biomarkers is one of the most important issues in biomedical research. The ELISA is a traditional technique for accurate quantitation of well-known proteins. Recently, the multiple reaction-monitoring (MRM) mass spectrometry has been proposed for quantifying newly discovered protein and has become a popular alternative to ELISA. For the MRM data analysis, linear mixed modeling (LMM) has been used to analyze MRM data. MSstats is one of the most widely used tools for MRM data analysis that is based on the LMMs. However, LMMs often provide various significance results, depending on model specification. Sometimes it would be difficult to specify a correct LMM method for the analysis of MRM data. Here, we propose a new logistic regression-based method for Significance Analysis of Multiple Reaction Monitoring (LR-SAM).

Results

Through simulation studies, we demonstrate that LMM methods may not preserve type I error, thus yielding high false- positive errors, depending on how random effects are specified. Our simulation study also shows that the LR-SAM approach performs similarly well as LMM approaches, in most cases. However, LR-SAM performs better than the LMMs, particularly when the effects sizes of peptides from the same protein are heterogeneous. Our proposed method was applied to MRM data for identification of proteins associated with clinical responses of treatment of 115 hepatocellular carcinoma (HCC) patients with the tyrosine kinase inhibitor sorafenib. Of 124 candidate proteins, LMM approaches provided 6 results varying in significance, while LR-SAM, by contrast, yielded 18 significant results that were quite reproducibly consistent.

Conclusion

As exemplified by an application to HCC data set, LR-SAM more effectively identified proteins associated with clinical responses of treatment than LMM did.

Protein detection in blood via a chimeric aptafluorescence assay: toward point-of-care diagnostic devices

Paper-based analytics allows building portable and disposable devices for point-of-care (POC) diagnosis. Conventional methods for quantifying proteins exhibit substantial disadvantages related to costs and difficulty of the technique when used in settings where fast and cost-effective assays are needed. We report the successful application of a simple, rapid, easy to use, and label-free aptasensor strategy based on the selective fluorescence of the NMM IX dye. For the probe design, the three-dimensional (3-D) structures of the DNA components were carefully analyzed using software for the 3-D visualization of crystallographic structures. The chimeric aptafluorescence molecule consists of two modules, a detection aptamer and a transduction sequence that induces the specific fluorescence of NMM IX. In the presence of thrombin, a fluorescent spot visible to the naked eye can be observed. The fluorescent response is directly proportional to protein concentration and can be easily quantified colorimetrically using a low-cost microscopy system. The recognition probe design might be adaptable to other relevant biological analytes by changing the sequence of the aptamer. This proof of principle represents a contribution to the development of useful, cheap, reliable, and simple protein quantification assays for POC testing.

In vitro secretomics study of pterygium-derived fibroblasts by iTRAQ-based quantitative proteomics strategy

Pterygium is a triangular shaped ocular fibrous surface lesion growing from conjunctiva towards central cornea, causing ocular irritation, astigmatism, and visual disturbance. The condition is characterized by epithelial proliferation, fibrovascular growth, chronic inflammation, and prominent extracellular matrix remodeling. Studies have suggested that aberrant extracellular proteins secreted by fibroblasts lead to abnormal matrix production and tissue invasion contributing to the development of the disease. In this study, secreted proteins collected from paired pterygium and conjunctival fibroblasts in vitro were identified and quantified by LC-MS iTRAQ-based analysis, in which 433 proteins common to all samples were identified. Among these proteins, 48.0% (208) were classified as classically secreted proteins, 17.1% (74) were exported out of the cells via non-classical secretion pathways, and 31.2% (135) were exosome proteins. A minority (3.7%) was not previously known to be secreted, or might be contaminants. 31 and 27 proteins were found up- or down-regulated in the conditioned media of pterygium fibroblasts relative to the media of control cells, respectively. Molecular function analysis showed that these proteins either belonged to catalytic proteins, structural molecules or were involved with receptor activities and protein binding. Further pathway analysis revealed that these proteins were involved in ECM-receptor interaction, focal adhesion, cancer-related, p53 signaling, complement and coagulation, and TGF-beta signaling pathways. These molecules identified may serve as extracellular ligands to activate intracellular pathways, possibly serving as potential therapeutic targets.

Clinical protein mass spectrometry

Quantitative protein analysis is routinely performed in clinical chemistry laboratories for diagnosis, therapeutic monitoring, and prognosis. Today, protein assays are mostly performed either with non-specific detection methods or immunoassays. Mass spectrometry (MS) is a very specific analytical method potentially very well suited for clinical laboratories. Its unique advantage relies in the high specificity of the detection. Any protein sequence variant, the presence of a post-translational modification or degradation will differ in mass and structure, and these differences will appear in the mass spectrum of the protein. On the other hand, protein MS is a relatively young technique, demanding specialized personnel and expensive instrumentation. Many scientists and opinion leaders predict MS to replace immunoassays for routine protein analysis, but there are only few protein MS applications routinely used in clinical chemistry laboratories today. The present review consists of a didactical introduction summarizing the pros and cons of MS assays compared to immunoassays, the different instrumentations, and various MS protein assays that have been proposed and/or are used in clinical laboratories. An important distinction is made between full length protein analysis (top-down method) and peptide analysis after enzymatic digestion of the proteins (bottom-up method) and its implication for the protein assay. The document ends with an outlook on what type of analyses could be used in the future, and for what type of applications MS has a clear advantage compared to immunoassays.

Can Saliva Proteins Be Used to Predict the Onset of Acute Myocardial Infarction among High-Risk Patients?

Human saliva plays a pivotal role in digesting food and maintaining oral hygiene. The presence of electrolytes, mucus, glycoproteins, enzymes, antibacterial compounds, and gingival crevicular fluid in saliva ensures the optimum condition of oral cavity and general health condition. Saliva collection has been proven non-invasive, convenient, and inexpensive compared to conventional venipuncture procedure. These distinctive advantages provide a promising potential of saliva as a diagnostic fluid. Through comprehensive analysis, an array of salivary proteins and peptides may be beneficial as biomarkers in oral and systemic diseases. In this review, we discuss the utility of human salivary proteomes and tabulate the recent salivary biomarkers found in subjects with acute myocardial infarction as well as respective methods employed. In a clinical setting, since acute myocardial infarction contributes to large cases of mortality worldwide, an early intervention using these biomarkers will provide an effective solution to reduce global heart attack incidence particularly among its high-risk group of type-2 diabetes mellitus patients. The utility of salivary biomarkers will make the prediction of this cardiac event possible due to its reliability hence improve the quality of life of the patients. Current challenges in saliva collection are also addressed to improve the quality of saliva samples and produce robust biomarkers for future use in clinical applications.

Absolute quantification of protein NP24 in tomato fruit by liquid chromatography/tandem mass spectrometry using stable isotope-labelled tryptic peptide standard

Protein NP24 is a thaumatin-like protein contained in tomato (Lycopersicon esculentum Mill.). This protein is reported to be a putative tomato allergen and is listed as a food allergen in Structural Database of Allergenic Proteins (SDAP). In this research, we developed the quantitative analysis of NP24 by employing the protein absolute quantification (AQUA) technology composed of stable isotope-labelled internal standard (SIIS) peptide (GQTWVINAPR[(13)C6,(15)N4]) and liquid chromatography/tandem mass spectrometry (LC/MS/MS). A linear relationship (r(2)>0.99) was found throughout the concentration range (2.0-500 fmol/μL). The coefficients of variation (CVs) measured on each of the five days when NP24 contained in the tomato skin was analysed did not exceed 13%. Our developed assay of NP24 will contribute to the allergological examination of tomato and its derived products.