Mass spectrometry-based targeted quantitative proteomics: achieving sensitive and reproducible detection of proteins

Reproducible protein quantitation of 270 human proteins at increased depth using nanoparticle-based fractionation and multiple reaction monitoring mass spectrometry with stable isotope-labelled internal standards

Here we show that when using a mix of 274 light synthetic peptide standards (NAT) as surrogates for 270 human plasma proteins, as well as stable isotope-labelled standards (SIS) as normalizers (both from MRM Proteomics Inc.) for targeted quantitative analysis by liquid chromatography multiple reaction monitoring mass spectrometry (LC/MRM-MS), the Seer Proteograph™ platform allowed for the enrichment and absolute quantitation of up to an additional 62 targets (median) compared to two standard proteomic workflows without enrichment, representing an increase of 44%. The nanoparticle-based fractionation workflow resulted in improved reproducibility compared to a traditional proteomic workflow with no fractionation (median 8.3% vs. 13.1% CV). As expected, the protein concentrations in nanoparticle coronas were higher and had more compressed dynamic range in comparison to the concentrations determined either by a 3-hour Trypsin/LysC or overnight tryptic digestion methods. As the nanoparticle-based fractionation technology gains popularity, additional steps such as establishing technique-specific protein reference ranges across plasma samples and comparisons to well-established protein quantitation methods like enzyme-linked immunosorbent assay (ELISA) and LC/MRM-MS may be explored to enable absolute quantification of plasma proteins based on nanoparticle-based fractionation data.

A Proteomics Pipeline for Generating Clinical Grade Biomarker Candidates from Data-Independent Acquisition Mass Spectrometry (DIA-MS) Discovery

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package that uses data-independent acquisition analysis from a discovery cohort to select precursors, peptides, and proteins that adhere to analytical criteria required for established targeted assays. TEAQ was applied to DIA-MS data from plasma samples acquired on a new high resolution accurate mass (HRAM) mass spectrometry platform where precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation based on 8- or 11-point loading curves at three throughputs. This data can be used as a general resource for developing other targeted assays. TEAQ analysis of data from a case and control cohort for inflammatory bowel disease (n=492) identified 1110 signature peptides for 326 quantifiable proteins from the 1179 identified proteins. Applying TEAQ analysis to discovery data will streamline targeted assay development and the transition to validation and clinical studies.

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an Orbitrap™ Astral™ MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.

Development and application of a multiple reaction monitoring method for the simultaneous quantification of sodium channels Nav 1.1, Nav 1.2, and Nav 1.6 in solubilized membrane proteins from stable HEK293 cell lines, rodents, and human brain tissues

RATIONALE

Nav 1.1, 1.2, and 1.6 are transmembrane proteins acting as voltage-gated sodium channels implicated in various forms of epilepsy. There is a need for knowing their actual concentration in target tissues during drug development.

METHODS

Unique peptides for Nav 1.1, Nav 1.2, and Nav 1.6 were selected as quantotropic peptides for each protein and used for their quantification in membranes from stably transfected HEK293 cells and rodent and human brain samples using ultra-high-performance liquid chromatography-electrospray ionization tandem mass spectrometry.

RESULTS

Nav 1.1, 1.2, and 1.6 protein expressions in three stably individually transfected HEK293 cell lines were found to be 2.1 ± 0.2, 6.4 ± 1.2, and 4.0 ± 0.6 fmol/μg membrane protein, respectively. In brains, Nav 1.2 showed the highest expression, with approximately three times higher (P < 0.003) in rodents than in humans at 3.05 ± 0.57, with 3.35 ± 0.56 in mouse and rat brains and 1.09 ± 0.27 fmol/μg in human brain. Both Nav 1.1 and 1.6 expressions were much lower in the brains, with approximately 40% less expression in human Nav 1.1 than rodent Nav 1.1 at 0.49 ± 0.1 (mouse), 0.43 ± 0.3 (rat), and 0.28 ± 0.04 (humans); whereas Nav 1.6 had approximately 60% less expression in humans than rodents at 0.27 ± 0.09 (mouse), 0.26 ± 0.06 (rat), and 0.11 ± 0.02 (humans) fmol/μg membrane proteins.

CONCLUSIONS

Multiple reaction monitoring was used to quantify sodium channels Nav 1.1, 1.2, and 1.6 expressed in stably transfected HEK293 cells and brain tissues from mice, rats, and humans. We found significant differences in the expression of these channels in mouse, rat, and human brains. Nav expression ranking among the three species was Nav 1.2 ≫ Nav 1.1 > Nav 1.6, with the human brain expressing much lower concentrations overall compared to rodent brain.

Enhancing protein trapping efficiency of graphene oxide-polybutylene succinate nanofiber membrane via molecular imprinting

Filtration of biological liquids has been widely employed in biological, medical, and environmental investigations due to its convenience; many could be performed without energy and on-site, particularly protein separation. However, most available membranes are universal protein absorption or sub-fractionation due to molecule sizes or properties. SPMA, or syringe-push membrane absorption, is a quick and easy way to prepare biofluids for protein evaluation. The idea of initiating SPMA was to filter proteins from human urine for subsequent proteomic analysis. In our previous study, we developed nanofiber membranes made from polybutylene succinate (PBS) composed of graphene oxide (GO) for SPMA. In this study, we combined molecular imprinting with our developed PBS fiber membranes mixed with graphene oxide to improve protein capture selectivity in a lock-and-key fashion and thereby increase the efficacy of protein capture. As a model, we selected albumin from human serum (ABH), a clinically significant urine biomarker, for proteomic application. The nanofibrous membrane was generated utilizing the electrospinning technique with PBS/GO composite. The PBS/GO solution mixed with ABH was injected from a syringe and transformed into nanofibers by an electric voltage, which led the fibers to a rotating collector spinning for fiber collection. The imprinting process was carried out by removing the albumin protein template from the membrane through immersion of the membrane in a 60% acetonitrile solution for 4 h to generate a molecular imprint on the membrane. Protein trapping ability, high surface area, the potential for producing affinity with proteins, and molecular-level memory were all evaluated using the fabricated membrane morphology, protein binding capacity, and quantitative protein measurement. This study revealed that GO is a controlling factor, increasing electrical conductivity and reducing fiber sizes and membrane pore areas in PBS-GO-composites. On the other hand, the molecular imprinting did not influence membrane shape, nanofiber size, or density. Human albumin imprinted membrane could increase the PBS-GO membrane's ABH binding capacity from 50 to 83%. It can be indicated that applying the imprinting technique in combination with the graphene oxide composite technique resulted in enhanced ABH binding capabilities than using either technique individually in membrane fabrication. The suitable protein elution solution is at 60% acetonitrile with an immersion time of 4 h. Our approach has resulted in the possibility of improving filter membranes for protein enrichment and storage in a variety of biological fluids.

Bioinformatics Tools and Knowledgebases to Assist Generating Targeted Assays for Plasma Proteomics

In targeted proteomics experiments, selecting the appropriate proteotypic peptides as surrogate for the target protein is a crucial pre-acquisition step. This step is largely a bioinformatics exercise that involves integrating information on the peptides and proteins and using various software tools and knowledgebases. We present here a few resources that automate and simplify the selection process to a great degree. These tools and knowledgebases were developed primarily to streamline targeted proteomics assay development and include PeptidePicker, PeptidePickerDB, MRMAssayDB, MouseQuaPro, and PeptideTracker. We have used these tools to develop and document thousands of targeted proteomics assays, many of them for plasma proteins with focus on human and mouse. An important aspect in all these resources is the integrative approach on which they are based. Using these tools in the first steps of designing a singleplexed or multiplexed targeted proteomic experiment can reduce the necessary experimental steps tremendously. All the tools and knowledgebases we describe here are Web-based and freely accessible so scientists can query the information conveniently from the browser. This chapter provides an overview of these software tools and knowledgebases, their content, and how to use them for targeted plasma proteomics. We further demonstrate how to use them with the results of the HUPO Human Plasma Proteome Project to produce a new database of 3.8 k targeted assays for known human plasma proteins. Upon experimental validation, these assays should help in the further quantitative characterizing of the plasma proteome.

Dietary-Nutraceutical Properties of Oat Protein and Peptides

Oats are considered the healthiest grain due to their high content of phytochemicals, dietary fibers, and protein. In recent years, oat protein and peptides have gained popularity as possible therapeutic or nutraceutical candidates. Generally, oat peptides with bioactive properties can be obtained by the enzymatic hydrolysis of proteins and are known to have a variety of regulatory functions. This review article focused on the nutraceutical worth of oat proteins and peptides and also describes the application of oat protein as a functional ingredient. Outcomes of this study indicated that oat protein and peptides present various therapeutical properties, including antidiabetic, antioxidant, antihypoxic, antihypertensive, antithrombotic, antifatigue, immunomodulatory, and hypocholestrolaemic. However, most of the conducted studies are limited to in vitro conditions and less data is available on assessing the effectiveness of the oat peptides in vivo. Future efforts should be directed at performing systematic animal studies; in addition, clinical trials also need to be conducted to fully support the development of functional food products, nutraceutical, and therapeutical applications.

Comparative proteomic analysis of spleen reveals key immune-related proteins in the yak (Bos grunniens) at different growth stages

Spleen plays an indispensable role in the immune system as the largest lymphatic organ in the body. The spleens of yaks at three developmental stages (1 day fetal yak, 15 months juvenile yak and 5 years old adult yak) were sampled and the Tandem mass tag (TMT) quantification method was employed in spleen proteomic analysis. The results showed that 6576 proteins and 529 differentially expressed proteins (DEPs) were identified in the yak spleens at three growth stages. Gene ontology (GO) analysis of DEPs indicated that DEPs were enriched in Oxygen transport, Actin filament movement, DNA replication, Cell cycle process, and Cell macromolecule biosynthesis process, which was conducive to high altitude breathing, protein synthesis and organ growth in yaks. These were indispensable for yak spleen growth and cell metabolism, high altitude adaptation. Those DEPs were further analyzed based on Kyoto encyclopedia of genes and genomes (KEGG) pathways, which principally participated in Th1 and Th2 cell differentiation, NF-kappa B signaling pathway, Phagosome, and Glutathione metabolism. Those pathways were associated with some animal life activities in defense against microbial antigens, indicating that with age, the immune function of the yak's spleen continued to increase. Hemoglobin, Tumor necrosis factor receptor associated factor 1 (TRAF1), T cell receptor (TCR), Macrophage receptor, Fc receptors (FcR), and Gamma-glutamyl transferase (GGT) of DEPs played roles in immune function in yak spleen directly or indirectly. The dynamic changes of Toll like receptor 2 (TLR2), TRAF1 and Heat shock protein 27 (HSP27 or HSPB1) detected by Immunohistochemistry were consistent with those obtained from TMT proteomic. In conclusion, this study provides extensive and functional analyses of the spleen proteome at three developmental stages and will offer a new insight into key proteins involved in the immune function of yak spleen.

Synthetic DNA spike-ins (SDSIs) enable sample tracking and detection of inter-sample contamination in SARS-CoV-2 sequencing workflows

The global spread and continued evolution of SARS-CoV-2 has driven an unprecedented surge in viral genomic surveillance. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine laboratory processes and results. This challenge will increase with the expanding global production of sequences across a variety of laboratories for epidemiological and clinical interpretation, as well as for genomic surveillance of emerging diseases in future outbreaks. We present SDSI + AmpSeq, an approach that uses 96 synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination throughout the sequencing workflow. We apply SDSIs to the ARTIC Consortium's amplicon design, demonstrate their utility and efficiency in a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases and validate them across 6,676 diagnostic samples at multiple laboratories. We establish that SDSI + AmpSeq provides increased confidence in genomic data by detecting and correcting for relatively common, yet previously unobserved modes of error, including spillover and sample swaps, without impacting genome recovery.

Targeted mass spectrometry-based assays enable multiplex quantification of receptor tyrosine kinase, MAP Kinase, and AKT signaling

SUMMARY

A primary goal of the US National Cancer Institute's Ras initiative at the Frederick National Laboratory for Cancer Research is to develop methods to quantify RAS signaling to facilitate development of novel cancer therapeutics. We use targeted proteomics technologies to develop a community resource consisting of 256 validated multiple reaction monitoring (MRM)-based, multiplexed assays for quantifying protein expression and phosphorylation through the receptor tyrosine kinase, MAPK, and AKT signaling networks. As proof of concept, we quantify the response of melanoma (A375 and SK-MEL-2) and colorectal cancer (HCT-116 and HT-29) cell lines to BRAF inhibition by PLX-4720. These assays replace over 60 Western blots with quantitative mass spectrometry-based assays of high molecular specificity and quantitative precision, showing the value of these methods for pharmacodynamic measurements and mechanism of action studies. Methods, fit-for-purpose validation, and results are publicly available as a resource for the community at assays.cancer.gov.

MOTIVATION

A lack of quantitative, multiplexable assays for phosphosignaling limits comprehensive investigation of aberrant signaling in cancer and evaluation of novel treatments. To alleviate this limitation, we sought to develop assays using targeted mass spectrometry for quantifying protein expression and phosphorylation through the receptor tyrosine kinase, MAPK, and AKT signaling networks. The resulting assays provide a resource for replacing over 60 Western blots in examining cancer signaling and tumor biology with high molecular specificity and quantitative rigor.

Silica nanoparticle induces pulmonary fibroblast transdifferentiation via macrophage route: Potential mechanism revealed by proteomic analysis

Recently, more and more attention has been focused on silica nanoparticles (SiNPs) as they are increasingly used in various fields. Yet, their biological effects, especially on human beings, largely remain unknown. This study was implanted to assess the biological responses in vitro elicited by human macrophages exposed to the SiNPs and to explore its toxicity and fibrosis biomarker. We found that SiNPs suppressed the viability of THP-1 cells in a dose-dependent manner while they triggered apoptosis and promoted the secretion of inflammatory factors. Next, SiNPs-induced macrophage supernatant was used to act on fibroblast (MRC-5), indicating that the expression of hydroxyproline (Hyp), α-SMA, and collagonIin MRC-5 increased after SiNPs treatment. To further explore the biomarker of fibrosis, Liquid-mass spectrometry facilitated quantitative proteomics, identified 3247 proteins, of which 791 proteins were expressed differentially in human embryonic lung fibroblasts after treated with SiNPs. In conclusion, our observations suggest that SiNPs induced THP-1-derived macrophage damage and apoptosis. Moreover, SiNPs induced macrophages to secrete cytokines that promote fibroblasts' proliferation and differentiation and changed protein expression in MRC-5 cells, regulating biological processes such as apoptosis, protein synthesis, and cell growth. Among these results, our findings could provide a basis for determining fibrosis biomarkers of silica nanoparticle exposure.

Reduced Level of Tear Antimicrobial and Immunomodulatory Proteins as a Possible Reason for Higher Ocular Infections in Diabetic Patients

(1) Background: Diabetes mellitus is one of the most common metabolic disorders and a risk factor for bacterial ocular infections. Our aim was to examine the antibacterial activity of tears from patients with diabetes mellitus with and without diabetic retinopathy and to link this activity to the level of tear proteins. (2) Methods: Non-stimulated basal tears were collected from 39 eyes of 35 subjects. The antibacterial activity of tear pools was tested against pathogenic Staphylococcus aureus ATCC 29213, Escherichia coli ATCC 26922 and Pseudomonas aeruginosa ATCC 27853 strains. The levels of 10 antimicrobial and immunomodulatory proteins were analyzed in the individual tear samples of the studied groups by SRM-based targeted mass spectrometry analysis. (3) Results: Disease stage-specific antimicrobial effect was observed in case of Staphylococcus aureus ATCC 29213 strain, and a non-disease specific inhibitory effect was observed in case of Pseudomonas aeruginosa ATCC 27853 strain. Changes in the levels of the studied antimicrobial and immunomodulatory proteins in the tears of the studied groups were also observed. (4) Conclusions: The higher ocular infection rate observed in diabetic patients may be the consequence of the decreased antimicrobial activity of tears possibly caused by the changes in the levels of antimicrobial and immunomodulatory proteins.

DNA spike-ins enable confident interpretation of SARS-CoV-2 genomic data from amplicon-based sequencing

The rapid global spread and continued evolution of SARS-CoV-2 has highlighted an unprecedented need for viral genomic surveillance and clinical viral sequencing. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine lab processes and results. This challenge will only increase with expanding global production of sequences by diverse research groups for epidemiological and clinical interpretation. We present an approach which uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination through a sequencing workflow. Applying this approach to the ARTIC Consortium's amplicon design, we define a series of best practices for Illumina-based sequencing and provide a detailed characterization of approaches to increase sensitivity for low-viral load samples incorporating the SDSIs. We demonstrate the utility and efficiency of the SDSI method amidst a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.

Process and Workflow for Preparation of Disparate Mouse Tissues for Proteomic Analysis

We investigated the effect of homogenization strategy and protein precipitation on downstream protein quantitation using multiple reaction monitoring mass spectrometry (MRM-MS). Our objective was to develop a workflow capable of processing disparate tissue types with high throughput, minimal variability, and maximum purity. Similar abundances of endogenous proteins were measured in nine different mouse tissues regardless of the homogenization method used; however, protein precipitation had strong positive effects on several targets. The best throughput was achieved by lyophilizing tissues to dryness, followed by homogenization via bead-beating without sample buffer. Finally, the effect of tissue perfusion prior to dissection and collection was explored in 20 mouse tissues. MRM-MS showed decreased abundances of blood-related proteins in perfused tissues; however, complete removal was not achieved. Concentrations of nonblood proteins were largely unchanged, although significantly higher variances were observed for proteins from the perfused lung, indicating that perfusion may not be suitable for this organ. We present a simple yet effective tissue processing workflow consisting of harvest of fresh nonperfused tissue, novel lyophilization and homogenization by bead-beating, and protein precipitation. This workflow can be applied to a range of mouse tissues with the advantages of simplicity, minimal manual manipulation of samples, use of commonly available equipment, and high sample quality.

A Fast and Memory-Efficient Spectral Library Search Algorithm Using Locality-Sensitive Hashing

With the accumulation of MS/MS spectra collected in spectral libraries, the spectral library searching approach emerges as an important approach for peptide identification in proteomics, complementary to the commonly used protein database searching approach, in particular for the proteomic analyses of well-studied model organisms, such as human. Existing spectral library searching algorithms compare a query MS/MS spectrum with each spectrum in the library with matched precursor mass and charge state, which may become computationally intensive with the rapidly growing library size. Here, the software msSLASH, which implements a fast spectral library searching algorithm based on the Locality-Sensitive Hashing (LSH) technique, is presented. The algorithm first converts the library and query spectra into bit-strings using LSH functions, and then computes the similarity between the spectra with highly similar bit-string. Using the spectral library searching of large real-world MS/MS spectra datasets, it is demonstrated that the algorithm significantly reduced the number of spectral comparisons, and as a result, achieved 2-9X speedup in comparison with existing spectral library searching algorithm SpectraST. The spectral searching algorithm is implemented in C/C++, and is ready to be used in proteomic data analyses.

Development of a Parallel Reaction Monitoring Mass Spectrometry Assay for the Detection of SARS-CoV-2 Spike Glycoprotein and Nucleoprotein

There is an urgent need for robust and high-throughput methods for SARS-CoV-2 detection in suspected patient samples to facilitate disease management, surveillance, and control. Although nucleic acid detection methods such as reverse transcription polymerase chain reaction (RT-PCR) are the gold standard, during the current pandemic, the deployment of RT-PCR tests has been extremely slow, and key reagents such as PCR primers and RNA extraction kits are at critical shortages. Rapid point-of-care viral antigen detection methods have been previously employed for the diagnosis of respiratory viruses such as influenza and respiratory syncytial viruses. Therefore, the direct detection of SARS-CoV-2 viral antigens in patient samples could also be used for diagnosis of active infection, and alternative methodologies for specific and sensitive viral protein detection should be explored. Targeted mass spectrometry techniques have enabled the identification and quantitation of a defined subset of proteins/peptides at single amino acid resolution with attomole level sensitivity and high reproducibility. Herein, we report a targeted mass spectrometry assay for the detection of SARS-CoV-2 spike protein and nucleoprotein in a relevant biological matrix. Recombinant full-length spike protein and nucleoprotein were digested and proteotypic peptides were selected for parallel reaction monitoring (PRM) quantitation using a high-resolution Orbitrap instrument. A spectral library, which contained seven proteotypic peptides (four from spike protein and three from nucleoprotein) and the top three to four transitions, was generated and evaluated. From the original spectral library, we selected two best performing peptides for the final PRM assay. The assay was evaluated using mock test samples containing inactivated SARS-CoV-2 virions, added to in vitro derived mucus. The PRM assay provided a limit of detection of ∼200 attomoles and a limit of quantitation of ∼ 390 attomoles. Extrapolating from the test samples, the projected titer of virus particles necessary for the detection of SARS-CoV-2 spike and nucleoprotein detection was approximately 2 × 105 viral particles/mL, making it an attractive alternative to RT-PCR assays. Potentially, mass spectrometry-based methods for viral antigen detection may deliver higher throughput and could serve as a complementary diagnostic tool to RT-PCR. Furthermore, this assay could be used to evaluate the presence of SARS-CoV-2 in archived or recently collected biological fluids, in vitro-derived research materials, and wastewater samples.

Analysis of Narrow-Leaf Lupin Proteins in Lupin-Enriched Pasta by Untargeted and Targeted Mass Spectrometry

The supplementation of different food items with grain legumes and, in particular, with lupin has been demonstrated to provide useful health benefits, especially in the area of cardiovascular disease prevention. In this work, label free quantitative untargeted and targeted approaches based on liquid chromatography−electrospray ionization−tandem mass spectrometry (LC−ESI−MS/MS) for investigating the protein profile of three pasta samples containing different percentages of narrow-leaf lupin flour were carried out. The untargeted method permitted the identification of the main acidic globulins (α-conglutin, β-conglutin, and δ-conglutin) and the comparison of their profile with raw lupin flour. The targeted method, based on High-performance liquid chromatography electrospray ionization tandem mass spectrometry HPLC-Chip-Multiple Reaction Monitoring (MRM) mode, allowed the quantification of γ-conglutin, the main hypoglycemic component of lupin protein: its concentration was around 2.25 mg/g in sample A, 2.16 mg/g in sample D, and 0.57 mg/g in sample F.

Harmonization of quality metrics and power calculation in multi-omic studies

Multi-omic studies combine measurements at different molecular levels to build comprehensive models of cellular systems. The success of a multi-omic data analysis strategy depends largely on the adoption of adequate experimental designs, and on the quality of the measurements provided by the different omic platforms. However, the field lacks a comparative description of performance parameters across omic technologies and a formulation for experimental design in multi-omic data scenarios. Here, we propose a set of harmonized Figures of Merit (FoM) as quality descriptors applicable to different omic data types. Employing this information, we formulate the MultiPower method to estimate and assess the optimal sample size in a multi-omics experiment. MultiPower supports different experimental settings, data types and sample sizes, and includes graphical for experimental design decision-making. MultiPower is complemented with MultiML, an algorithm to estimate sample size for machine learning classification problems based on multi-omic data.

Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)-Based Proteomics of Drug-Metabolizing Enzymes and Transporters

Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics is a powerful tool for identifying and quantifying proteins in biological samples, outperforming conventional antibody-based methods in many aspects. LC-MS/MS-based proteomics studies have revealed the protein abundances of many drug-metabolizing enzymes and transporters (DMETs) in tissues relevant to drug metabolism and disposition. Previous studies have consistently demonstrated marked interindividual variability in DMET protein expression, suggesting that varied DMET function is an important contributing factor for interindividual variability in pharmacokinetics (PK) and pharmacodynamics (PD) of medications. Moreover, differential DMET expression profiles were observed across different species and in vitro models. Therefore, caution must be exercised when extrapolating animal and in vitro DMET proteomics findings to humans. In recent years, DMET proteomics has been increasingly utilized for the development of physiologically based pharmacokinetic models, and DMET proteins have also been proposed as biomarkers for prediction of the PK and PD of the corresponding substrate drugs. In sum, despite the existence of many challenges in the analytical technology and data analysis methods of LC-MS/MS-based proteomics, DMET proteomics holds great potential to advance our understanding of PK behavior at the individual level and to optimize treatment regimens via the DMET protein biomarker-guided precision pharmacotherapy.

THE PRESENT AND FUTURE OF THE MASS SPECTROMETRY-BASED INVESTIGATION OF THE EXOSOME LANDSCAPE

Exosomes are critical intercellular messengers released upon the fusion of multivesicular bodies with the cellular plasma membrane that deliver their cargo in the form of extracellular vesicles. Containing numerous nonrandomly packed functional proteins, lipids, and RNAs, exosomes are vital intercellular messengers that contribute to the physiologic processes of the healthy organism. During the post-genome era, exosome-oriented proteomics have garnered great interest. Since its establishment, mass spectrometry (MS) has been indispensable for the field of proteomics research and has advanced rapidly to interrogate biological samples at a higher resolution and sensitivity. Driven by new methodologies and more advanced instrumentation, MS-based approaches have revolutionized our understanding of protein biology. As the access to online proteomics database platforms has blossomed, experimental data processing occurs with more speed and accuracy. Here, we review recent advances in the technological progress of MS-based proteomics and several new detection strategies for MS-based proteomics research. We also summarize the use of integrated online databases for proteomics research in the era of big data. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

SCREENED: A Multistage Model of Thyroid Gland Function for Screening Endocrine-Disrupting Chemicals in a Biologically Sex-Specific Manner

Endocrine disruptors (EDs) are chemicals that contribute to health problems by interfering with the physiological production and target effects of hormones, with proven impacts on a number of endocrine systems including the thyroid gland. Exposure to EDs has also been associated with impairment of the reproductive system and incidence in occurrence of obesity, type 2 diabetes, and cardiovascular diseases during ageing. SCREENED aims at developing in vitro assays based on rodent and human thyroid cells organized in three different three-dimensional (3D) constructs. Due to different levels of anatomical complexity, each of these constructs has the potential to increasingly mimic the structure and function of the native thyroid gland, ultimately achieving relevant features of its 3D organization including: 1) a 3D organoid based on stem cell-derived thyrocytes, 2) a 3D organoid based on a decellularized thyroid lobe stromal matrix repopulated with stem cell-derived thyrocytes, and 3) a bioprinted organoid based on stem cell-derived thyrocytes able to mimic the spatial and geometrical features of a native thyroid gland. These 3D constructs will be hosted in a modular microbioreactor equipped with innovative sensing technology and enabling precise control of cell culture conditions. New superparamagnetic biocompatible and biomimetic particles will be used to produce "magnetic cells" to support precise spatiotemporal homing of the cells in the 3D decellularized and bioprinted constructs. Finally, these 3D constructs will be used to screen the effect of EDs on the thyroid function in a unique biological sex-specific manner. Their performance will be assessed individually, in comparison with each other, and against in vivo studies. The resulting 3D assays are expected to yield responses to low doses of different EDs, with sensitivity and specificity higher than that of classical 2D in vitro assays and animal models. Supporting the "Adverse Outcome Pathway" concept, proteogenomic analysis and biological computational modelling of the underlying mode of action of the tested EDs will be pursued to gain a mechanistic understanding of the chain of events from exposure to adverse toxic effects on thyroid function. For future uptake, SCREENED will engage discussion with relevant stakeholder groups, including regulatory bodies and industry, to ensure that the assays will fit with purposes of ED safety assessment. In this project review, we will briefly discuss the current state of the art in cellular assays of EDs and how our project aims at further advancing the field of cellular assays for EDs interfering with the thyroid gland.

Degradomics in Biomarker Discovery

The upregulation of protease expression and proteolytic activity is implicated in numerous pathological conditions such as neurodegeneration, cancer, cardiovascular and autoimmune diseases, and bone degeneration. During disease progression, various proteases form characteristic patterns of cleaved proteins and peptides, which can affect disease severity and course of progression. It has been shown that qualitative and quantitative monitoring of cleaved protease substrates can provide relevant prognostic, diagnostic, and therapeutic information. As proteolytic fragments and peptides generated in the affected tissue are commonly translocated to blood, urine, and other proximal fluids, their possible application as biomarkers is the subject of ongoing research. The field of degradomics has been established to enable the global identification of proteolytic events on the organism level, utilizing proteomic approaches and sample preparation techniques that facilitate the detection of proteolytic processing of protease substrates in complex biological samples. In this review, some of the latest developments in degradomic methodologies used for the identification and validation of biologically relevant proteolytic events and their application in the search for clinically relevant biomarker candidates are presented. The current state of degradomics in clinics is discussed and the future perspectives of the field are outlined.

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".

Application of immobilized ATP to the study of NLRP inflammasomes

The NLRP proteins are a subfamily of the NOD-like receptor (NLR) innate immune sensors that possess an ATP-binding NACHT domain. As the most well studied member, NLRP3 can initiate the assembly process of a multiprotein complex, termed the inflammasome, upon detection of a wide range of microbial products and endogenous danger signals and results in the activation of pro-caspase-1, a cysteine protease that regulates multiple host defense pathways including cytokine maturation. Dysregulated NLRP3 activation contributes to inflammation and the pathogenesis of several chronic diseases, and the ATP-binding properties of NLRPs are thought to be critical for inflammasome activation. In light of this, we examined the utility of immobilized ATP matrices in the study of NLRP inflammasomes. Using NLRP3 as the prototypical member of the family, P-linked ATP Sepharose was determined to be a highly-effective capture agent. In subsequent examinations, P-linked ATP Sepharose was used as an enrichment tool to enable the effective profiling of NLRP3-biomarker signatures with selected reaction monitoring-mass spectrometry (SRM-MS). Finally, ATP Sepharose was used in combination with a fluorescence-linked enzyme chemoproteomic strategy (FLECS) screen to identify potential competitive inhibitors of NLRP3. The identification of a novel benzo[d]imidazol-2-one inhibitor that specifically targets the ATP-binding and hydrolysis properties of the NLRP3 protein implies that ATP Sepharose and FLECS could be applied other NLRPs as well.

Selected reaction monitoring for colorectal cancer diagnosis using a set of five serum peptides identified by BLOTCHIP®-MS analysis

BACKGROUND

Colorectal cancer (CRC) is one of the most predominant types of cancer, and it is the fourth most common cause of cancer-related death and it is important to diagnose CRC in early stage to decrease the mortality by CRC. In our previous study, we identified a combination of five peptides as a biomarker candidate to diagnose CRC by BLOTCHIP^®-MS analysis using a set of healthy control subjects and CRC patients (stage II-IV). The aim of the present study was to validate the serum biomarker peptides reported in our previous study using a second cohort and to establish their potential usefulness in CRC diagnosis.

METHODS

A total of 56 patients with CRC (n = 14 each of stages I-IV), 60 healthy controls, and 60 patients with colonic adenoma were included in this study. The five peptides were extracted and analyzed by selected reaction monitoring using ProtoKey^® Colorectal Cancer Risk Test Kit (Protosera, Inc., Amagasaki, Japan).

RESULTS

The results clearly showed that the four CRC groups, stages I-IV, could be sufficiently discriminated from the control group and colonic polyp group. This five-peptide set could identify CRC at each stage compared to the control population in this validation cohort, including those with early-stage disease. The AUC values for each stage of CRC compared to the control population were 0.779, 0.946, 0.852, and 0.973 for stages I, II, III, and IV, respectively.

CONCLUSIONS

In this case-control validation study, we confirmed high diagnostic performance for CRC using five peptides that were identified in our previous study as serum biomarker candidates for the detection of CRC.

Ceruloplasmin, transferrin and apolipoprotein A-II play important role in treatment's follow-up of paracoccidioidomycosis patients

Paracoccidioidomycosis (PCM) is a systemic disease caused by thermodymorphic fungi of the Paracoccidioides brasiliensis complex, (Paracoccidioides spp.). Patients with PCM reveal specific cellular immune impairment. Despite the effective treatment, quiescent fungi can lead to relapse, usually late, the serological diagnosis of which has been deficient. The present study was carried out with the objective of investigating a biomarker for the identification of PCM relapse and another molecule behaving as an immunological recovery biomarker; therefore, it may be used as a cure criterion. In the evolutionary analysis of the proteins identified in PCM patients, comparing those that presented with those that did not reveal relapse, 29 proteins were identified. The interactions observed between the proteins, using transferrin and haptoglobin, as the main binding protein, were strong with all the others. Patient follow-up suggests that cerulosplamin may be a marker of relapse and that transferrin and apolipoprotein A-II may contribute to the evaluation of the treatment efficacy and avoiding a premature decision.

Species Differentiation and Quantification of Processed Animal Proteins and Blood Products in Fish Feed Using an 8-Plex Mass Spectrometry-Based Immunoassay

With the reintroduction of nonruminant processed animal proteins (PAPs) for use in aquaculture in 2013, there is a suitable alternative to replace expensive fish meal in fish feed. Nevertheless, since the bovine spongiform encephalopathy (BSE) crisis, the use of PAPs in feed is strictly regulated. To date, light microscopy and polymerase chain reaction are the official methods for proving the absence of illegal PAPs in feed. Due to their limitations, alternative methods for the quantitative species differentiation are needed. To address this issue, we developed and validated an 8-plex mass spectrometry-based immunoassay. The workflow comprises a tryptic digestion of PAPs and blood products in suspension, a cross-species immunoaffinity enrichment of 8 species-specific alpha-2-macroglobulin peptides using a group-specific antibody, and a subsequent analysis by ultrahigh-performance liquid chromatography coupled to tandem mass spectrometry for species identification and quantification. This workflow can be used to quantitatively determine the species origin in future feed authentication studies.

Utilizing proteomics to understand and define hypertension: where are we and where do we go?

INTRODUCTION

Hypertension is a complex and multifactorial cardiovascular disorder. With different mechanisms contributing to a different extent to an individual's blood pressure, the discovery of novel pathogenetic principles of hypertension is challenging. However, there is an urgent and unmet clinical need to improve prevention, detection, and therapy of hypertension in order to reduce the global burden associated with hypertension-related cardiovascular diseases. Areas covered: Proteomic techniques have been applied in reductionist experimental models including angiotensin II infusion models in rodents and the spontaneously hypertensive rat in order to unravel mechanisms involved in blood pressure control and end organ damage. In humans proteomic studies mainly focus on prediction and detection of organ damage, particularly of heart failure and renal disease. While there are only few proteomic studies specifically addressing human primary hypertension, there are more data available in hypertensive disorders in pregnancy, such as preeclampsia. We will review these studies and discuss implications of proteomics on precision medicine approaches. Expert commentary: Despite the potential of proteomic studies in hypertension there has been moderate progress in this area of research. Standardized large-scale studies are required in order to make best use of the potential that proteomics offers in hypertension and other cardiovascular diseases.

The building blocks of successful translation of proteomics to the clinic

Recently, the first two multiplexed tests using selective reaction monitoring (SRM-MS) mass spectrometry have entered clinical practice. Despite different areas of indication, risk stratification in lung cancer and preterm birth, they share multiple steps in their development strategies. Here we review these strategies and their implications for successful translation of biomarkers to clinical practice. We believe that the identification of blood protein panels for the identification of disease phenotypes is now a reproducible and standard (albeit complex) process.

Recent advances in mass spectrometry-based glycoproteomics

Protein glycosylation plays fundamental roles in many biological processes as one of the most common, and the most complex, posttranslational modification. Alterations in glycosylation profile are now known to be associated with many diseases. As a result, the discovery and detailed characterization of glycoprotein disease biomarkers is a primary interest of biomedical research. Advances in mass spectrometry (MS)-based glycoproteomics and glycomics are increasingly enabling qualitative and quantitative approaches for site-specific structural analysis of protein glycosylation. While the complexity presented by glycan heterogeneity and the wide dynamic range of clinically relevant samples like plasma, serum, cerebrospinal fluid, and tissue make comprehensive analyses of the glycoproteome a challenging task, the ongoing efforts into the development of glycoprotein enrichment, enzymatic digestion, and separation strategies combined with novel quantitative MS methodologies have greatly improved analytical sensitivity, specificity, and throughput. This review summarizes current MS-based glycoproteomics approaches and highlights recent advances in its application to cancer biomarker and neurodegenerative disease research.

Discovery and Longitudinal Evaluation of Candidate Biomarkers for Ischaemic Stroke by Mass Spectrometry-Based Proteomics

Application of acute therapies such as thrombolysis for ischaemic stroke (IS) is constrained because of diagnostic uncertainty and the dynamic nature of stroke biology. To investigate changes in blood proteins after stroke and as a result of thrombolysis treatment we performed label-free quantitative proteomics on serum samples using high-resolution mass spectrometry and long high-performance liquid chromatography gradient (5 hours) combined with a 50-cm column to optimise the peptide separation. We identified (false discovery rate [FDR]: 1%) and quantified a total of 574 protein groups from a total of 92 samples from 30 patients. Ten patients were treated by thrombolysis as part of a randomised placebo-controlled trial and up to 5 samples were collected from each individual at different time points after stroke. We identified 26 proteins differently expressed by treatment group (FDR: 5%) and significant changes of expression over time for 23 proteins (FDR: 10%). Molecules such as fibrinogen and C-reactive protein showed expression profiles with a high-potential clinical utility in the acute stroke setting. Protein expression profiles vary acutely in the blood after stroke and have the potential to allow the construction of a stroke clock and to have an impact on IS treatment decision making.

Quantitative Multiple-Reaction Monitoring Proteomic Analysis of Gβ and Gγ Subunits in C57Bl6/J Brain Synaptosomes

Gβγ dimers are one of the essential signaling units of activated G protein-coupled receptors (GPCRs). There are five Gβ and 12 Gγ subunits in humans; numerous studies have demonstrated that different Gβ and Gγ subunits selectively interact to form unique Gβγ dimers, which in turn may target specific receptors and effectors. Perturbation of Gβγ signaling can lead to impaired physiological responses. Moreover, previous targeted multiple-reaction monitoring (MRM) studies of Gβ and Gγ subunits have shown distinct regional and subcellular localization patterns in four brain regions. Nevertheless, no studies have quantified or compared their individual protein levels. In this study, we have developed a quantitative MRM method not only to quantify but also to compare the protein abundance of neuronal Gβ and Gγ subunits. In whole and fractionated crude synaptosomes, we were able to identify the most abundant neuronal Gβ and Gγ subunits and their subcellular localizations. For example, Gβ₁ was mostly localized at the membrane while Gβ₂ was evenly distributed throughout synaptosomal fractions. The protein expression levels and subcellular localizations of Gβ and Gγ subunits may affect the Gβγ dimerization and Gβγ-effector interactions. This study offers not only a new tool for quantifying and comparing Gβ and Gγ subunits but also new insights into the in vivo distribution of Gβ and Gγ subunits, and Gβγ dimer assembly in normal brain function.

Recent advances in quantitative and chemical proteomics for autophagy studies

Macroautophagy/autophagy is an evolutionarily well-conserved cellular degradative process with important biological functions that is closely implicated in health and disease. In recent years, quantitative mass spectrometry-based proteomics and chemical proteomics have emerged as important tools for the study of autophagy, through large-scale unbiased analysis of the proteome or through highly specific and accurate analysis of individual proteins of interest. At present, a variety of approaches have been successfully applied, including (i) expression and interaction proteomics for the study of protein post-translational modifications, (ii) investigating spatio-temporal dynamics of protein synthesis and degradation, and (iii) direct determination of protein activity and profiling molecular targets in the autophagic process. In this review, we attempted to provide an overview of principles and techniques relevant to the application of quantitative and chemical proteomics methods to autophagy, and outline the current landscape as well as future outlook of these methods in autophagy research.

Current trends in quantitative proteomics - an update

Proteins can provide insights into biological processes at the functional level, so they are very promising biomarker candidates. The quantification of proteins in biological samples has been routinely used for the diagnosis of diseases and monitoring the treatment. Although large-scale protein quantification in complex samples is still a challenging task, a great amount of effort has been made to advance the technologies that enable quantitative proteomics. Seven years ago, in 2009, we wrote an article about the current trends in quantitative proteomics. In writing this current paper, we realized that, today, we have an even wider selection of potential tools for quantitative proteomics. These tools include new derivatization reagents, novel sampling formats, new types of analyzers and scanning techniques, and recently developed software to assist in assay development and data analysis. In this review article, we will discuss these innovative methods, and their current and potential applications in proteomics. Copyright © 2017 John Wiley & Sons, Ltd.

Database of Optimized Proteomic Quantitative Methods for Human Drug Disposition-Related Proteins for Applications in Physiologically Based Pharmacokinetic Modeling

The purpose of this study was to create an open access repository of validated liquid chromatography tandem mass spectrometry (LC‐MS/MS) multiple reaction monitoring (MRM) methods for quantifying 284 important proteins associated with drug absorption, distribution, metabolism, and excretion (ADME). Various in silico and experimental approaches were used to select surrogate peptides and optimize instrument parameters for LC‐MS/MS quantification of the selected proteins. The final methods were uploaded to an online public database (QPrOmics; www.qpromics.uw.edu/qpromics/assay/), which provides essential information for facile method development in triple quadrupole mass spectrometry (MS) instruments. To validate the utility of the methods, the differential tissue expression of 107 key ADME proteins was characterized in the tryptic digests of the pooled subcellular fractions of human liver, kidneys, intestines, and lungs. These methods and the data are critical for development of physiologically based pharmacokinetic (PBPK) models to predict xenobiotic disposition.

A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

Multiplexed Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry Quantification of Cancer Signaling Proteins

Quantitative evaluation of protein expression across multiple cancer-related signaling pathways (e.g., Wnt/β-catenin, TGF-β, receptor tyrosine kinases (RTK), MAP kinases, NF-κB, and apoptosis) in tumor tissues may enable the development of a molecular profile for each individual tumor that can aid in the selection of appropriate targeted cancer therapies. Here, we describe the development of a broadly applicable protocol to develop and implement quantitative mass spectrometry assays using cell line models and frozen tissue specimens from colon cancer patients. Cell lines are used to develop peptide-based assays for protein quantification, which are incorporated into a method based on SDS-PAGE protein fractionation, in-gel digestion, and liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM/MS). This analytical platform is then applied to frozen tumor tissues. This protocol can be broadly applied to the study of human disease using multiplexed LC-MRM assays.

Blood and Plasma Proteomics: Targeted Quantitation and Posttranslational Redox Modifications

Proteome profiling using mass spectrometry is extensively utilized to understand the physiological characteristics of cells, tissues, fluids, and many other biological matrices. From the earliest days of the proteomics era, exploratory analyses of the blood protein complement have attracted a great deal of interest, owing to the pivotal importance of blood cells and biofluids (serum, plasma) for research and biomedical purposes. Once challenged by the high dynamic range of protein concentrations, low sensitivity of mass spectrometers, and poor annotation of proteomics databases, the techniques in this field have quickly evolved in recent years, particularly in the areas of absolute quantification of proteins and in mapping of posttranslational modifications. Here we describe (a) the design and production of heavy isotope-labeled peptides used as reporter internal standards for absolute protein quantification and (b) a redox proteomics approach to optimize sample preparation and database searching to elucidate oxidative modifications to protein amino acids. The two methods achieve complimentary goals in the field of blood research and pave the way for future translation of next-generation proteomics technologies into clinical practice.

Label-Based and Label-Free Strategies for Protein Quantitation

The precise quantification of changes between various physiological states in a biological system is highly complex in nature. Over the past few years, in combination with classical methods, mass spectrometry based approaches have become an indispensable tool in deciphering exact abundance of proteins in composite mixtures. The technique is now well established and employs both label-based and label-free quantitation strategies. Label-based quantitation methods utilize stable isotope labels which are incorporated within the peptides, introducing an expectable mass difference within the two or more experimental conditions. In contrast, label-free proteomics quantitates both relative and absolute protein quantity by utilizing signal intensity and spectral counting of peptides. This chapter focuses on the commonly used quantitative mass spectrometry methods for high-throughput proteomic analysis.

Targeted Enlargement of Aptamer Functionalized Gold Nanoparticles for Quantitative Protein Analysis

The ability to selectively amplify the detection signals for targets over interferences is crucial when analyzing proteins in a complicated sample matrix. Here, we describe a targeted enlargement strategy that can amplify the light-scattering signal from aptamer-functionalized gold nanoparticles (Apt-AuNP) with high specificity for quantitative protein analysis. This strategy is achieved by labeling target proteins with competitively protected Apt-AuNP probes and enlarging the probes with gold enhancement. This competitive protection strategy could effectively eliminate nonspecific protein adsorptions from a sample matrix, leading to a highly specific labeling of the target protein. As a result, the subsequent amplification of the light-scattering signal by gold enhancement only occurs in the presence of the target protein. This strategy was successfully demonstrated by analyzing human α-thrombin in human serum samples in a Western blot format.

Salivary and pellicle proteome: A datamining analysis

We aimed to comprehensively compare two compartmented oral proteomes, the salivary and the dental pellicle proteome. Systematic review and datamining was used to obtain the physico-chemical, structural, functional and interactional properties of 1,515 salivary and 60 identified pellicle proteins. Salivary and pellicle proteins did not differ significantly in their aliphatic index, hydrophaty, instability index, or isoelectric point. Pellicle proteins were significantly more charged at low and high pH and were significantly smaller (10–20 kDa) than salivary proteins. Protein structure and solvent accessible molecular surface did not differ significantly. Proteins of the pellicle were more phosphorylated and glycosylated than salivary proteins. Ion binding and enzymatic activities also differed significantly. Protein-protein-ligand interaction networks relied on few key proteins. The identified differences between salivary and pellicle proteins could guide proteome compartmentalization and result in specialized functionality. Key proteins could be potential targets for diagnostic or therapeutic application.

Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study

BACKGROUND

Prostate cancer (PCa) is the most common male cancer in the United Kingdom and we aimed to identify clinically relevant biomarkers corresponding to stage progression of the disease.

METHODS

We used enhanced proteomic profiling of PCa progression using iTRAQ 3D LC mass spectrometry on high-quality serum samples to identify biomarkers of PCa.

RESULTS

We identified >1000 proteins. Following specific inclusion/exclusion criteria we targeted seven proteins of which two were validated by ELISA and six potentially interacted forming an 'interactome' with only a single protein linking each marker. This network also includes accepted cancer markers, such as TNF, STAT3, NF-κB and IL6.

CONCLUSIONS

Our linked and interrelated biomarker network highlights the potential utility of six of our seven markers as a panel for diagnosing PCa and, critically, in determining the stage of the disease. Our validation analysis of the MS-identified proteins found that SAA alongside KLK3 may improve categorisation of PCa than by KLK3 alone, and that TSR1, although not significant in this model, might also be a clinically relevant biomarker.