The use of selected reaction monitoring in quantitative proteomics

Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias

Neurodegenerative dementias are progressive diseases that cause neuronal network breakdown in different brain regions often because of accumulation of misfolded proteins in the brain extracellular matrix, such as amyloids or inside neurons or other cell types of the brain. Several diagnostic protein biomarkers in body fluids are being used and implemented, such as for Alzheimer's disease. However, there is still a lack of biomarkers for co-pathologies and other causes of dementia. Such biofluid-based biomarkers enable precision medicine approaches for diagnosis and treatment, allow to learn more about underlying disease processes, and facilitate the development of patient inclusion and evaluation tools in clinical trials. When designing studies to discover novel biofluid-based biomarkers, choice of technology is an important starting point. But there are so many technologies to choose among. To address this, we here review the technologies that are currently available in research settings and, in some cases, in clinical laboratory practice. This presents a form of lexicon on each technology addressing its use in research and clinics, its strengths and limitations, and a future perspective.

RecJ3/4-aRNase J form a Ubl-associated nuclease complex functioning in survival against DNA damage in Haloferax volcanii

Nucleases are strictly regulated and often localized in the cell to avoid the uncontrolled degradation of DNA and RNA. Here, a new type of nuclease complex, composed of RecJ3, RecJ4, and aRNase J, was identified through its ATP-dependent association with the ubiquitin-like SAMP1 and AAA-ATPase Cdc48a. The complex was discovered in Haloferax volcanii, an archaeon lacking an RNA exosome. Genetic analysis revealed aRNase J to be essential and RecJ3, RecJ4, and Cdc48a to function in the recovery from DNA damage including genotoxic agents that generate double-strand breaks. The RecJ3:RecJ4:aRNase J complex (isolated in 2:2:1 stoichiometry) functioned primarily as a 3'-5' exonuclease in hydrolyzing RNA and ssDNA, with the mechanism non-processive for ssDNA. aRNase J could also be purified as a homodimer that catalyzed endoribonuclease activity and, thus, was not restricted to the 5'-3' exonuclease activity typical of aRNase J homologs. Moreover, RecJ3 and RecJ4 could be purified as a 560-kDa subcomplex in equimolar subunit ratio with nuclease activities mirroring the full RecJ3/4-aRNase J complex. These findings prompted reconstitution assays that suggested RecJ3/4 could suppress, alter, and/or outcompete the nuclease activities of aRNase J. Based on the phenotypic results, this control mechanism of aRNase J by RecJ3/4 is not necessary for cell growth but instead appears important for DNA repair. IMPORTANCE Nucleases are critical for various cellular processes including DNA replication and repair. Here, a dynamic type of nuclease complex is newly identified in the archaeon Haloferax volcanii, which is missing the canonical RNA exosome. The complex, composed of RecJ3, RecJ4, and aRNase J, functions primarily as a 3'-5' exonuclease and was discovered through its ATP-dependent association with the ubiquitin-like SAMP1 and Cdc48a. aRNase J alone forms a homodimer that has endonuclease function and, thus, is not restricted to 5'-3' exonuclease activity typical of other aRNase J enzymes. RecJ3/4 appears to suppress, alter, and/or outcompete the nuclease activities of aRNase J. While aRNase J is essential for growth, RecJ3/4, Cdc48a, and SAMPs are important for recovery against DNA damage. These biological distinctions may correlate with the regulated nuclease activity of aRNase J in the RecJ3/4-aRNaseJ complex.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

The Edge Effect in High-Throughput Proteomics: A Cautionary Tale

In order for mass spectrometry to continue to grow as a platform for high-throughput clinical and translational research, careful consideration must be given to quality control by ensuring that the assay performs reproducibly and accurately and precisely. In particular, the throughput required for large cohort clinical validation in biomarker discovery and diagnostic screening has driven the growth of multiplexed targeted liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) assays paired with sample preparation and analysis in multiwell plates. However, large scale MS-based proteomics studies are often plagued by batch effects: sources of technical variation in the data, which can arise from a diverse array of sources such as sample preparation batches, different reagent lots, or indeed MS signal drift. These batch effects can confound the detection of true signal differences, resulting in incorrect conclusions being drawn about significant biological effects or lack thereof. Here, we present an intraplate batch effect termed the edge effect arising from temperature gradients in multiwell plates, commonly reported in preclinical cell culture studies but not yet reported in a clinical proteomics setting. We present methods herein to ameliorate the phenomenon including proper assessment of heating techniques for multiwell plates and incorporation of surrogate standards, which can normalize for intraplate variation.

Stereochemical Assignment and Absolute Abundance of Nonproteinogenic Amino Acid Homoarginine in Marine Sponges

Together with arginine, the nonproteinogenic amino acid homoarginine is a substrate for the production of vasodilator nitric oxide in the human body. In marine sponges, homoarginine has been postulated to serve as a precursor for the biosynthesis of pyrrole-imidazole alkaloid and bromotyrosine alkaloid classes of natural products. The absolute abundance of homoarginine, its abundance relative to arginine, and its stereochemical assignment in marine sponges are not known. Here, using stable isotope dilution mass spectrometry, we quantify the absolute abundances of homoarginine and arginine in marine sponges. We find that the abundance of homoarginine is highly variable and can far exceed the concentration of arginine, even in sponges where incorporation of homoarginine in natural products cannot be rationalized. The [homoarginine]/[arginine] ratio in marine sponges is greater than that in human analytes. By derivatization of sponge extracts with Marfey's reagent and comparison with authentic standards, we determine the l-isomer of homoarginine to be exclusively present in sponges. Our results shed light on the presence of the high abundance of homoarginine in marine sponge metabolomes and provide the foundation to investigate the biosynthetic routes and physiological roles of this nonproteinogenic amino acid in sponge physiology.

Quantitation of thrombin-activatable fibrinolysis inhibitor in human plasma by isotope dilution mass spectrometry

Measurement of Thrombin-activatable fibrinolysis inhibitor (TAFI) in human plasma is dependent on reproducible assays. To date, standards for measuring TAFI are frequently calibrated relative to pooled normal human plasma and arbitrarily assigned a potency of 100% TAFI, despite variation in TAFI concentrations between plasma pools. Alternatively, TAFI calibrators can be assigned a value in SI units but the approach used for value assignment is not consistent and furthermore, if purified TAFI is used to determine TAFI concentration in plasma, may be adversely affected by matrix effects. A TAFI plasma standard in mass units with traceability to the SI unit of mass is desirable. We report here the establishment of a quantitative mass spectrometry method for TAFI in plasma. Traceability is obtained by reference to calibrators that consist of blank plasma spiked with a defined amount of purified TAFI, value assigned by amino acid analysis. The calibrators are run alongside the samples, using the same preparation steps and conditions; an acetonitrile assisted tryptic digestion and multi-dimensional liquid chromatography (LC) separation followed by SRM-MS analysis. We measured the TAFI quantitatively in human plasma with reproducibility, reliability and precision, and demonstrated the applicability of this approach for value assigning a common reference standard.

Recent advances in proteomics and its implications in pituitary endocrine disorders

Pituitary adenoma is considered as one of the most frequent intracranial tumors having salient impact on human health such as mass effects, hypopituitarism and visual defects etc. During the past few decades, there has been enormous advancement in mass spectrometry (MS)-based proteomics. However, very little is known about the molecular pathogenesis of pituitary adenomas in the context of proteomics. In this review article, we have focused on the provenance of pituitary tumors and their pathogenesis with the help of MS-based proteomics approaches. Recent advancements in quantitative proteomic approaches are outlined here that would be useful in the near pituitary adenoma proteomics research. This review discusses the enormous potential of pituitary adenomas research through proteomics with a common aim of deciphering disease pathobiology and identifying the work done in studying pituitary tumors during past decade.

Proteomic approaches to assist in diagnosis and prognosis of oral cancer

Introduction: Oral squamous cell carcinoma (OSCC) ranks among the top 10 leading causes of cancer worldwide, with 5-year survival rate of about 50%, high lymph node metastasis, and relapse rates. The OSCC diagnosis, prognosis, and treatment are mostly based on the clinical TNM classification. There is an urgent need for the discovery of biomarkers and therapeutic targets to assist in the clinical decision-making process.Areas covered: We summarize proteomic studies of the OSCC tumor, immune microenvironment, potential liquid biopsy sites, and post-translational modifications trying to retrieve information in the discovery and verification or (pre)validation phases. The search strategy was based on the combination of MeSH terms and expert refinement.Expert opinion: Untargeted combined with targeted proteomics are strategies that provide reliable and reproducible quantitation of proteins and are the methods of choice of many groups worldwide. Undoubtedly, proteomics has been contributing to the understanding of OSCC progression and uncovers potential candidates as biomarker or therapeutic targets. Nevertheless, none of these targets are available in the clinical practice yet. The scientific community needs to overcome the limitations by investing in robust experimental designs to strengthen the value of the findings, leveraging the translation of knowledge, and further supporting clinical decisions.

SWATH Based Quantitative Proteomics Reveals Significant Lipid Metabolism in Early Myopic Guinea Pig Retina

Most of the previous myopic animal studies employed a single-candidate approach and lower resolution proteomics approaches that were difficult to detect minor changes, and generated limited systems-wide biological information. Hence, a complete picture of molecular events in the retina involving myopic development is lacking. Here, to investigate comprehensive retinal protein alternations and underlying molecular events in the early myopic stage, we performed a data-independent Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH) based proteomic analysis coupled with different bioinformatics tools in pigmented guinea pigs after 4-day lens-induced myopia (LIM). Myopic eyes compared to untreated contralateral control eyes caused significant changes in refractive error and choroid thickness (p < 0.05, n = 5). Relative elongation of axial length and the vitreous chamber depth were also observed. Using pooled samples from all individuals (n = 10) to build a species-specific retinal ion library for SWATH analysis, 3202 non-redundant proteins (with 24,616 peptides) were identified at 1% global FDR. For quantitative analysis, the 10 individual retinal samples (5 pairs) were analyzed using a high resolution Triple-TOF 6600 mass spectrometry (MS) with technical replicates. In total, 37 up-regulated and 21 down-regulated proteins were found significantly changed after LIM treatment (log2 ratio (T/C) > 0.26 or < -0.26; p ≤ 0.05). Data are accepted via ProteomeXchange with identifier PXD025003. Through Ingenuity Pathways Analysis (IPA), "lipid metabolism" was found as the top function associated with the differentially expressed proteins. Based on the protein abundance and peptide sequences, expression patterns of two regulated proteins (SLC6A6 and PTGES2) identified in this pathway were further successfully validated with high confidence (p < 0.05) using a novel Multiple Reaction Monitoring (MRM) assay on a QTRAP 6500+ MS. In summary, through an integrated discovery and targeted proteomic approach, this study serves as the first report to detect and confirm novel retinal protein changes and significant biological functions in the early LIM mammalian guinea pigs. The study provides new workflow and insights for further research to myopia control.

Tailoring to Search Engines: Bottom-Up Proteomics with Collision Energies Optimized for Identification Confidence

Bottom-up proteomics relies on identification of peptides from tandem mass spectra, usually via matching against sequence databases. Confidence in a peptide–spectrum match can be characterized by a score value given by the database search engines, and it depends on the information content and the quality of the spectrum. The latter are influenced by experimental parameters, of which the collision energy is the most important one in the case of collision-induced dissociation. We examined how the identification score of the Byonic and Andromeda (MaxQuant) engines varies with collision energy for more than a thousand individual peptides from a HeLa tryptic digest on a QTof instrument. We thereby extended our earlier study on Mascot scores and corroborated its findings on the potential bimodal nature of this energy dependence. Optimal energies as a function of m/z show comparable linear trends for the three engines. On the basis of peptide-level results, we designed methods with one or two liquid chromatography–tandem mass spectrometry (LC-MS/MS) runs and various collision energy settings and assessed their practical performance in peptide and protein identification from the HeLa standard sample. A 10–40% gain in various measures, such as the number of identified proteins or sequence coverage, was obtained over the factory default settings. Best performing methods differ for the three engines, suggesting that the experimental parameters should be fine-tuned to the choice of the engine. We also recommend a simple approach and provide reference data to ease the transfer of the optimized methods to other mass spectrometers relevant for proteomics. We demonstrate the utility of this approach on an Orbitrap instrument. Data sets can be accessed via the MassIVE repository (MSV000086379).

Analysis of Protein-Protein Interaction Networks through Computational Approaches

The interactions among proteins and genes are extremely important for cellular functions. Molecular interactions at protein or gene levels can be used to construct interaction networks in which the interacting species are categorized based on direct interactions or functional similarities. Compared with the limited experimental techniques, various computational tools make it possible to analyze, filter, and combine the interaction data to get comprehensive information about the biological pathways. By the efficient way of integrating experimental findings in discovering PPIs and computational techniques for prediction, the researchers have been able to gain many valuable data on PPIs, including some advanced databases. Moreover, many useful tools and visualization programs enable the researchers to establish, annotate, and analyze biological networks. We here review and list the computational methods, databases, and tools for protein-protein interaction prediction.

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Simple Summary

The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications.

Abstract

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

Targeted mass spectrometry for Serum Amyloid A (SAA) isoform profiling in sequential blood samples from experimentally Staphylococcus aureus infected pigs

Serum amyloid A (SAA) is a well-described acute phase protein induced during the acute phase response (APR) to infection. Four isoform specific genes are found in most mammals. Depending on species, SAA3 and SAA4 are generally preferentially expressed extrahepatically whereas SAA1 and SAA2 are hepatic isoforms dominating the SAA serum pool. Little is known about how specific infections affect the serum SAA isoform profile, as SAA isoform discriminating antibodies are not generally available. An antibody independent, quantitative targeted MS method (Selected Reaction Monitoring, SRM) based on available information on porcine SAA isoform genes was developed and used to profile SAA in serum samples from pigs experimentally infected with Staphylococcus aureus (Sa). While results suggest SAA2 as the main circulating porcine SAA isoform, induced around 10 times compared to non-infected controls, total SAA serum concentrations reached only around 4 μg/mL, much lower than established previously by immunoassays. This might suggest that SAA isoform variants not detected by the SRM method might be present in porcine serum. The assay allows monitoring host responses to experimental infections, infectious diseases and inflammation states in the pig at an unprecedented level of detail. It can also be used in a non-calibrated (relative quantification) format. SIGNIFICANCE: We developed an SRM MS method which for the first time allowed the specific quantification of each of the circulating porcine SAA isoforms (SAA2, SAA3, SAA4). It was found that SAA2 is the dominating circulating isoform of SAA in the pig and that, during the acute phase response to Sa infection SAA2, SAA3 and SAA4 are induced approx. 10, 15 and 2 times, respectively. Absolute levels of the isoforms as determined by SRM MS were much lower than reported previously for total SAA quantified by immunosassays, suggesting the existence of hitherto non-described SAA variants. SRM MS holds great promise for the study of the basic biology of SAA isoforms with the potential to study an even broader range of SAA variants.

Unraveling the Composition of Insecticidal Crystal Proteins in Bacillus thuringiensis: a Proteomics Approach

Bacillus thuringiensis (Bt) is the most widely used active ingredient for biological insecticides. The composition of δ-endotoxins (Cry and Cyt proteins) in the parasporal crystal determines the toxicity profile of each Bt strain. However, a reliable method for their identification and quantification has not been available, due to the high sequence identity of the genes that encode the δ-endotoxins and the toxins themselves. Here, we have developed an accurate and reproducible mass spectrometry-based method (liquid chromatography-tandem mass spectrometry-multiple reaction monitoring [LC-MS/MS-MRM]) using isotopically labeled proteotypic peptides for each protein in a particular mixture to determine the relative proportion of each δ-endotoxin within the crystal. To validate the method, artificial mixtures containing Cry1Aa, Cry2Aa, and Cry6Aa were analyzed. Determination of the relative abundance of proteins (in molarity) with our method was in good agreement with the expected values. This method was then applied to the most common commercial Bt-based products, DiPel DF, XenTari GD, VectoBac 12S, and Novodor, in which between three and six δ-endotoxins were identified and quantified in each product. This novel approach is of great value for the characterization of Bt-based products, not only providing information on host range, but also for monitoring industrial crystal production and quality control and product registration for Bt-based insecticides.IMPORTANCE Bacillus thuringiensis (Bt)-based biological insecticides are used extensively to control insect pests and vectors of human diseases. Bt-based products provide greater specificity and biosafety than broad-spectrum synthetic insecticides. The biological activity of this bacterium resides in spores and crystals comprising complex mixtures of toxic proteins. We developed and validated a fast, accurate, and reproducible method for quantitative determination of the crystal components of Bt-based products. This method will find clear applications in the improvement of various aspects of the industrial production process of Bt. An important aspect of the production of Bt-based insecticides is its quality control. By specifically quantifying the relative proportion of each of the toxins that make up the crystal, our method represents the most consistent and repeatable evaluation procedure in the quality control of different batches produced in successive fermentations. This method can also contribute to the design of specific culture media and fermentation conditions that optimize Bt crystal composition across a range of Bt strains that target different pestiferous insects. Quantitative information on crystal composition should also prove valuable to phytosanitary product registration authorities that oversee the safety and efficacy of crop protection products.

Absolute proteomic quantification reveals design principles of sperm flagellar chemosensation

Cilia serve as cellular antennae that translate sensory information into physiological responses. In the sperm flagellum, a single chemoattractant molecule can trigger a Ca2+ rise that controls motility. The mechanisms underlying such ultra-sensitivity are ill-defined. Here, we determine by mass spectrometry the copy number of nineteen chemosensory signaling proteins in sperm flagella from the sea urchin Arbacia punctulata. Proteins are up to 1,000-fold more abundant than the free cellular messengers cAMP, cGMP, H+ , and Ca2+ . Opto-chemical techniques show that high protein concentrations kinetically compartmentalize the flagellum: Within milliseconds, cGMP is relayed from the receptor guanylate cyclase to a cGMP-gated channel that serves as a perfect chemo-electrical transducer. cGMP is rapidly hydrolyzed, possibly via "substrate channeling" from the channel to the phosphodiesterase PDE5. The channel/PDE5 tandem encodes cGMP turnover rates rather than concentrations. The rate-detection mechanism allows continuous stimulus sampling over a wide dynamic range. The textbook notion of signal amplification-few enzyme molecules process many messenger molecules-does not hold for sperm flagella. Instead, high protein concentrations ascertain messenger detection. Similar mechanisms may occur in other small compartments like primary cilia or dendritic spines.

Selection of Collision Energies in Proteomics Mass Spectrometry Experiments for Best Peptide Identification: Study of Mascot Score Energy Dependence Reveals Double Optimum

Collision energy is a key parameter determining the information content of beam-type collision induced dissociation tandem mass spectrometry (MS/MS) spectra, and its optimal choice largely affects successful peptide and protein identification in MS-based proteomics. For an MS/MS spectrum, quality of peptide match based on sequence database search, often characterized in terms of a single score, is a complex function of spectrum characteristics, and its collision energy dependence has remained largely unexplored. We carried out electrospray ionization-quadrupole-time of flight (ESI-Q-TOF)-MS/MS measurements on 2807 peptides from tryptic digests of HeLa and E. coli at 21 different collision energies. Agglomerative clustering of the resulting Mascot score versus energy curves revealed that only few of them display a single, well-defined maximum; rather, they feature either a broad plateau or two clear peaks. Nonlinear least-squares fitting of one or two Gaussian functions allowed the characteristic energies to be determined. We found that the double peaks and the plateaus in Mascot score can be associated with the different energy dependence of b- and y-type fragment ion intensities. We determined that the energies for optimum Mascot scores follow separate linear trends for the unimodal and bimodal cases with rather large residual variance even after differences in proton mobility are taken into account. This leaves room for experiment optimization and points to the possible influence of further factors beyond m/ z.

Integrated SWATH-based and targeted-based proteomics provide insights into the retinal emmetropization process in guinea pig

Myopia is generally regarded as a failure of normal emmetropization process, however, its underlying molecular mechanisms are unclear. To investigate the retinal protein profile changes during emmetropization, we studied differential protein expressions of ocular growth in young guinea pigs at 3 and 21 days old respectively, when significant axial elongation was detected (P < 0.001, n = 10). Independent pooled retinal samples of both eyes were subjected to SWATH mass spectrometry (MS) followed by bioinformatics analysis using cloud-based platforms. A comprehensive retina SWATH ion-library consisting of 3138 (22,871) unique proteins (peptides) at 1% FDR was constructed. 40 proteins were found to be significantly up-regulated and 8 proteins down-regulated during emmetropization (≥log2 of 0.43 with ≥2 peptides matched per protein; P < 0.05). Using pathway analysis, the most significant pathway identifiable was 'phototransduction' (P = 1.412e-4). Expression patterns of 7 proteins identified in this pathway were further validated and confirmed (P < 0.05) with high-resolution Multiple Reaction Monitoring (MRM-HR) MS. Combining discovery and targeted proteomics approaches, this study for the first time comprehensively profiled protein changes in the guinea pig retina during normal emmetropization-associated eye growth. The findings of this study are also relevant to the myopia development, which is the result of failed emmetropization.

SIGNIFICANCE

Myopia is considered as a failure of emmetropization. However, the underlying biochemical mechanism of emmetropization, a visually guided process in which eye grows towards the optimal optical state of clear vision during early development, is not well understood. Retina is known as the key tissue to regulate this active eye growth. we studied eye growth of young guinea pigs and harvested their retinal tissues. A comprehensive SWATH ion library with identification of a total 3138 unique proteins were established, in which 48 proteins exhibited significant differential expressions between 3 and 21 days old. After MRM-HR confirmation, 'phototransduction' were found as the most active pathway during emmetropic eye growth. This study is the first in discovering key retinal protein players and pathways which are presumably orchestrated by biological mechanism(s) underlying emmetropization.

Dynamic phosphorylation of RelA on Ser42 and Ser45 in response to TNFα stimulation regulates DNA binding and transcription

The NF-κB signalling module controls transcription through a network of protein kinases such as the IKKs, as well as inhibitory proteins (IκBs) and transcription factors including RelA/p65. Phosphorylation of the NF-κB subunits is critical for dictating system dynamics. Using both non-targeted discovery and quantitative selected reaction monitoring-targeted proteomics, we show that the cytokine TNFα induces dynamic multisite phosphorylation of RelA at a number of previously unidentified residues. Putative roles for many of these phosphorylation sites on RelA were predicted by modelling of various crystal structures. Stoichiometry of phosphorylation determination of Ser45 and Ser42 revealed preferential early phosphorylation of Ser45 in response to TNFα. Quantitative analyses subsequently confirmed differential roles for pSer42 and pSer45 in promoter-specific DNA binding and a role for both of these phosphosites in regulating transcription from the IL-6 promoter. These temporal dynamics suggest that RelA-mediated transcription is likely to be controlled by functionally distinct NF-κB proteoforms carrying different combinations of modifications, rather than a simple ‘one modification, one effect’ system.

Development of a UHPLC-MS/MS (SRM) method for the quantitation of endogenous glucagon and dosed GLP-1 from human plasma

AIM

The performance of glucagon and GLP-1 immunoassays is often poor, but few sensitive LC-MS/MS methods exist as alternatives.

EXPERIMENTAL

A multiplexed LC-MS/MS method using a 2D extraction technique was developed.

RESULTS

The method was established for the quantitation of endogenous glucagon (LLOQ: 15 pg/ml) and dosed GLP-1 (LLOQ: 25 pg/ml) in human plasma, and is the first such method avoiding immunoenrichment. Specificity of endogenous glucagon quantitation was assured using a novel approach with a supercharging mobile phase additive to access a sensitive qualifier SRM. Endogenous glucagon concentrations were within the expected range, and showed good reproducibility after extended sample storage. A cross-validation against established immunoassays using physiological study samples demonstrated some similarities between methods.

CONCLUSION

The LC-MS/MS method offers a viable alternative to immunoassays for quantitation of endogenous glucagon, dosed glucagon and/or dosed GLP-1.

DOSCATs: Double standards for protein quantification

The two most common techniques for absolute protein quantification are based on either mass spectrometry (MS) or on immunochemical techniques, such as western blotting (WB). Western blotting is most often used for protein identification or relative quantification, but can also be deployed for absolute quantification if appropriate calibration standards are used. MS based techniques offer superior data quality and reproducibility, but WB offers greater sensitivity and accessibility to most researchers. It would be advantageous to apply both techniques for orthogonal quantification, but workflows rarely overlap. We describe DOSCATs (DOuble Standard conCATamers), novel calibration standards based on QconCAT technology, to unite these platforms. DOSCATs combine a series of epitope sequences concatenated with tryptic peptides in a single artificial protein to create internal tryptic peptide standards for MS as well as an intact protein bearing multiple linear epitopes. A DOSCAT protein was designed and constructed to quantify five proteins of the NF-κB pathway. For three target proteins, protein fold change and absolute copy per cell values measured by MS and WB were in excellent agreement. This demonstrates that DOSCATs can be used as multiplexed, dual purpose standards, readily deployed in a single workflow, supporting seamless quantitative transition from MS to WB.

Mass-Spectrometry-Based Method To Quantify in Parallel Tau and Amyloid β 1-42 in CSF for the Diagnosis of Alzheimer's Disease

Alzheimer's disease (AD), the most common form of dementia, afflicts about 50 million people worldwide. Currently, AD diagnosis is primarily based on psychological evaluation and can only be confirmed post-mortem. Reliable and objective biomarkers for prognosis and diagnosis have been sought for years. Together, tau and amyloid β 1-42 (Aβ₄₂) in cerebrospinal fluid (CSF) have been shown to provide good diagnostic sensitivity and specificity. Additionally, phosphorylated forms of tau, such as tau pS181, have also shown promising results. However, the measurement of such markers currently relies on antibody-based immunoassays that have shown variability, leading to discrepant results across laboratories. To date, mass spectrometry methods developed to evaluate CSF tau and Aβ₄₂ are not compatible. We present in this article the development of a mass-spectrometry-based method of quantification for CSF tau and Aβ₄₂ in parallel. The absolute concentrations of tau and Aβ₄₂ we measured are on average 50 ng/mL (7-130 ng/mL) and 7.1 ng/mL (3-13 ng/mL), respectively. Analyses of CSF tau and Aβ₄₂, in a cohort of patients with AD, mild cognitive impairment, and healthy controls (30 subjects), provide significant group differences evaluated with ROC curves (AUC_(control-AD) and AUC_{(control-MCI)} = 1, AUC_(MCI-AD) = 0.76), with at least equivalent diagnostic utility to immunoassay measurements in the same sample set. Finally, a significant and negative correlation was found between the tau and Aβ peptides ratio and the disease severity.

Absolute quantification of myosin heavy chain isoforms by selected reaction monitoring can underscore skeletal muscle changes in a mouse model of amyotrophic lateral sclerosis

Skeletal muscle fibers contain different isoforms of myosin heavy chain (MyHC) that define distinctive contractile properties. In light of the muscle capacity to adapt MyHC expression to pathophysiological conditions, a rapid and quantitative assessment of MyHC isoforms in small muscle tissue quantities would represent a valuable diagnostic tool for (neuro)muscular diseases. As past protocols did not meet these requirements, in the present study we applied a targeted proteomic approach based on selected reaction monitoring that allowed the absolute quantification of slow and fast MyHC isoforms in different mouse skeletal muscles with high reproducibility. This mass-spectrometry-based method was validated also in a pathological specimen, by comparison of the MyHC expression profiles in different muscles from healthy mice and a genetic mouse model of amyotrophic lateral sclerosis (ALS) expressing the SOD1(G93A) mutant. This analysis showed that terminally ill ALS mice have a fast-to-slow shift in the fiber type composition of the tibialis anterior and gastrocnemius muscles, as previously reported. These results will likely open the way to accurate and rapid diagnoses of human (neuro)muscular diseases by the proposed method. Graphical Abstract Methods for myosin heavy chain (MyHC) quantification: a comparison of classical methods and selected reaction monitoring (SRM)-based mass spectrometry approaches.

Protein turnover measurement using selected reaction monitoring-mass spectrometry (SRM-MS)

Protein turnover represents an important mechanism in the functioning of cells, with deregulated synthesis and degradation of proteins implicated in many diseased states. Therefore, proteomics strategies to measure turnover rates with high confidence are of vital importance to understanding many biological processes. In this study, the more widely used approach of non-targeted precursor ion signal intensity (MS1) quantification is compared with selected reaction monitoring (SRM), a data acquisition strategy that records data for specific peptides, to determine if improved quantitative data would be obtained using a targeted quantification approach. Using mouse liver as a model system, turnover measurement of four tricarboxylic acid cycle proteins was performed using both MS1 and SRM quantification strategies. SRM outperformed MS1 in terms of sensitivity and selectivity of measurement, allowing more confident determination of protein turnover rates. SRM data are acquired using cheaper and more widely available tandem quadrupole mass spectrometers, making the approach accessible to a larger number of researchers than MS1 quantification, which is best performed on high mass resolution instruments. SRM acquisition is ideally suited to focused studies where the turnover of tens of proteins is measured, making it applicable in determining the dynamics of proteins complexes and complete metabolic pathways.This article is part of the themed issue 'Quantitative mass spectrometry'.

Analysis of Intrinsic Peptide Detectability via Integrated Label-Free and SRM-Based Absolute Quantitative Proteomics

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC-MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472.

Absolute protein quantification of the yeast chaperome under conditions of heat shock

Chaperones are fundamental to regulating the heat shock response, mediating protein recovery from thermal-induced misfolding and aggregation. Using the QconCAT strategy and selected reaction monitoring (SRM) for absolute protein quantification, we have determined copy per cell values for 49 key chaperones in Saccharomyces cerevisiae under conditions of normal growth and heat shock. This work extends a previous chemostat quantification study by including up to five Q-peptides per protein to improve confidence in protein quantification. In contrast to the global proteome profile of S. cerevisiae in response to heat shock, which remains largely unchanged as determined by label-free quantification, many of the chaperones are upregulated with an average two-fold increase in protein abundance. Interestingly, eight of the significantly upregulated chaperones are direct gene targets of heat shock transcription factor-1. By performing absolute quantification of chaperones under heat stress for the first time, we were able to evaluate the individual protein-level response. Furthermore, this SRM data was used to calibrate label-free quantification values for the proteome in absolute terms, thus improving relative quantification between the two conditions. This study significantly enhances the largely transcriptomic data available in the field and illustrates a more nuanced response at the protein level.

RePLiCal: A QconCAT Protein for Retention Time Standardization in Proteomics Studies

This study introduces a new reversed-phase liquid chromatography retention time (RT) standard, RePLiCal (Reversed-phase liquid chromatography calibrant), produced using QconCAT technology. The synthetic protein contains 27 lysine-terminating calibrant peptides, meaning that the same complement of standards can be generated using either Lys-C or trypsin-based digestion protocols. RePLiCal was designed such that each constituent peptide is unique with respect to all eukaryotic proteomes, thereby enabling integration into a wide range of proteomic analyses. RePLiCal has been benchmarked against three commercially available peptide RT standard kits and outperforms all in terms of LC gradient coverage. RePLiCal also provides a higher number of calibrant points for chromatographic retention time standardization and normalization. The standard provides stable RTs over long analysis times and can be readily transferred between different LC gradients and nUHPLC instruments. Moreover, RePLiCal can be used to predict RTs for other peptides in a timely manner. Furthermore, it is shown that RePLiCal can be used effectively to evaluate trapping column performance for nUHPLC instruments using trap-elute configurations, to optimize gradients to maximize peptide and protein identification rates, and to recalibrate the m/z scale of mass spectrometry data post-acquisition.

Allergen relative abundance in several wheat varieties as revealed via a targeted quantitative approach using MS

Food allergy has become a major health issue in developed countries, therefore there is an urgent need to develop analytical methods able to detect and quantify with a good sensitivity and reliability some specific allergens in complex food matrices. In this paper, we present a targeted MS/MS approach to compare the relative abundance of the major recognized wheat allergens in the salt-soluble (albumin/globulin) fraction of wheat grains. Twelve allergens were quantified in seven wheat varieties, selected from three Triticum species: T. aestivum (bread wheat), T. durum (durum wheat), and T. monococcum. The allergens were monitored from one or two proteotypic peptides and their relative abundance was deduced from the intensity of one fragment measured in MS/MS. Whereas the abundance of some of the targeted allergens was quite stable across the genotypes, others like alpha-amylase inhibitors showed clear differences according to the wheat species, in accordance with the results of earlier functional studies. This study enriches the scarce knowledge available on allergens content in wheat genotypes, and brings new perspectives for food safety and plant breeding.

Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring

Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800 Saccharomyces cerevisiae proteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a “gold-standard” reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies.

The use of turbulent flow chromatography for rapid, on-line analysis of tryptic digests

RATIONALE

Following digestion of proteins with trypsin, digests are typically subjected to further 'clean-up' prior to liquid chromatography/mass spectometry (LC/MS) analysis, in order to reduce the complexity of the digested matrix, as well as helping to remove residual denaturants and reduction/alkylation reagents prior to injection onto the analytical HPLC column. Often, this is carried out using off-line techniques, and is not ideally suited to high-throughput workloads, for example in clinical laboratories.

METHODS

Bovine serum albumin (BSA) was used as a model protein. Following denaturation with urea, reduction/alkylation, and digestion with trypsin, the analytical recovery of a selection of proteotypic BSA peptides was assessed using a two-dimensional, turbulent flow chromatography method. Peptides were identified using a Q Exactive™ mass spectometer operating in full-scan mode.

RESULTS

Total analysis time (including the on-line sample clean-up) was 15 min per injection. Aside from the most hydrophilic peptide selected, ATEEQLK, recovery using the turbulent flow chromatography systems was greater than 30% for all remaining peptides (N = 17), and exceeded 50% for 12 of the 18 peptides studied. There was a broad correlation between the hydrophobicity factor and the observed recovery.

CONCLUSIONS

This study suggests that turbulent flow chromatography offers a rapid, on-line alternative to solid-phase extraction for the analysis of peptide digests by LC/MS. A wide range of column chemistries are available, and the technique can be further optimised for analyses which are targetted to specific peptides. As with turbulent flow chromatography for small-molecule workflows, this approach may be ideally suited to high-throughput applications, such as those which are emerging from within clinical laboratories.

Relative quantification of human β-defensins by a proteomics approach based on selected reaction monitoring

RATIONALE

A targeted proteomics method based on selected reaction monitoring (SRM) is a relevant approach for the analysis of multiple analytes in biological samples. Defensins are phylogenetically conserved small antimicrobial peptides contributing to innate host defense and exhibiting low immunogenicity, resistance to proteolysis and a broad range of antimicrobial activities. The goal of the present study was to develop and optimize SRM-based targeted proteomics methods for the detection of human β-defensins 1-4 in various biological fluids.

METHODS

An SRM-based targeted proteomics method was developed and validated for the detection of human β-defensins 1-4. The supernatants of resting and IL-1β-stimulated Caco2, HT-29 and SW-1116 colonic epithelial cells (CEC), cell lysates of CECs and tear samples of human healthy individuals were analyzed and the feasibility of the developed method was validated by ELISA and dot-blot analysis complemented by RT-qPCR.

RESULTS

Our results demonstrate that the developed SRM method offers an alternative approach for the cost-effective and rapid analysis of human β-defensins in samples with biological relevance.

CONCLUSIONS

A semi-quantitative targeted mass spectrometry method was developed and validated for the relative quantification of β-defensins 1-4 in cell culture supernatants and body fluid analyses.

Ecological venomics: How genomics, transcriptomics and proteomics can shed new light on the ecology and evolution of venom

Animal venom is a complex cocktail of bioactive chemicals that traditionally drew interest mostly from biochemists and pharmacologists. However, in recent years the evolutionary and ecological importance of venom is realized as this trait has direct and strong influence on interactions between species. Moreover, venom content can be modulated by environmental factors. Like many other fields of biology, venom research has been revolutionized in recent years by the introduction of systems biology approaches, i.e., genomics, transcriptomics and proteomics. The employment of these methods in venom research is known as 'venomics'. In this review we describe the history and recent advancements of venomics and discuss how they are employed in studying venom in general and in particular in the context of evolutionary ecology. We also discuss the pitfalls and challenges of venomics and what the future may hold for this emerging scientific field.

The role of proteomics in studies of protein moonlighting

The increasing acceptance that proteins may exert multiple functions in the cell brings with it new analytical challenges that will have an impact on the field of proteomics. Many proteomics workflows begin by destroying information about the interactions between different proteins, and the reduction of a complex protein mixture to constituent peptides also scrambles information about the combinatorial potential of post-translational modifications. To bring the focus of proteomics on to the domain of protein moonlighting will require novel analytical and quantitative approaches.

Large-scale label-free phosphoproteomics: from technology to data interpretation

Protein phosphorylation plays a central role in the dynamic intracellular signaling and the control of biochemical pathways in all living cells. Recent advances in high-performance MS/MS-based technology make the large-scale identification and quantification of phosphorylation sites possible. Here, we review the full data generation pipeline, starting from sample preparation methods and LC-MS detection procedures, through to data processing and analysis software tools that facilitate the systematic comparative profiling of thousands of phosphoproteins in different biological specimens in a single experiment. We emphasize current challenges and promising avenues for the mechanistic interpretation and visualization of global phosphorylation networks and their relevance to human health and disease.

Representation of selected-reaction monitoring data in the mzQuantML data standard

The mzQuantML data standard was designed to capture the output of quantitative software in proteomics, to support submissions to public repositories, development of visualization software and pipeline/modular approaches. The standard is designed around a common core that can be extended to support particular types of technique through the release of semantic rules that are checked by validation software. The first release of mzQuantML supported four quantitative proteomics techniques via four sets of semantic rules: (i) intensity-based (MS(1) ) label free, (ii) MS(1) label-based (such as SILAC or N(15) ), (iii) MS(2) tag-based (iTRAQ or tandem mass tags), and (iv) spectral counting. We present an update to mzQuantML for supporting SRM techniques. The update includes representing the quantitative measurements, and associated meta-data, for SRM transitions, the mechanism for inferring peptide-level or protein-level quantitative values, and support for both label-based or label-free SRM protocols, through the creation of semantic rules and controlled vocabulary terms. We have updated the specification document for mzQuantML (version 1.0.1) and the mzQuantML validator to ensure that consistent files are produced by different exporters. We also report the capabilities for production of mzQuantML files from popular SRM software packages, such as Skyline and Anubis.

A proteomic approach to obesity and type 2 diabetes

The incidence of obesity and type diabetes 2 has increased dramatically resulting in an increased interest in its biomedical relevance. However, the mechanisms that trigger the development of diabetes type 2 in obese patients remain largely unknown. Scientific, clinical and pharmaceutical communities are dedicating vast resources to unravel this issue by applying different omics tools. During the last decade, the advances in proteomic approaches and the Human Proteome Organization have opened and are opening a new door that may be helpful in the identification of patients at risk and to improve current therapies. Here, we briefly review some of the advances in our understanding of type 2 diabetes that have occurred through the application of proteomics. We also review, in detail, the current improvements in proteomic methodologies and new strategies that could be employed to further advance our understanding of this pathology. By applying these new proteomic advances, novel therapeutic and/or diagnostic protein targets will be discovered in the obesity/Type 2 diabetes area.

Quantification of extracellular matrix proteins from a rat lung scaffold to provide a molecular readout for tissue engineering

The use of extracellular matrix (ECM) scaffolds, derived from decellularized tissues for engineered organ generation, holds enormous potential in the field of regenerative medicine. To support organ engineering efforts, we developed a targeted proteomics method to extract and quantify extracellular matrix components from tissues. Our method provides more complete and accurate protein characterization than traditional approaches. This is accomplished through the analysis of both the chaotrope-soluble and -insoluble protein fractions and using recombinantly generated stable isotope labeled peptides for endogenous protein quantification. Using this approach, we have generated 74 peptides, representing 56 proteins to quantify protein in native (nondecellularized) and decellularized lung matrices. We have focused on proteins of the ECM and additional intracellular proteins that are challenging to remove during the decellularization procedure. Results indicate that the acellular lung scaffold is predominantly composed of structural collagens, with the majority of these proteins found in the insoluble ECM, a fraction that is often discarded using widely accepted proteomic methods. The decellularization procedure removes over 98% of intracellular proteins evaluated and retains, to varying degrees, proteoglycans and glycoproteins of the ECM. Accurate characterization of ECM proteins from tissue samples will help advance organ engineering efforts by generating a molecular readout that can be correlated with functional outcome to drive the next generation of engineered organs.

In-depth evaluation of software tools for data-independent acquisition based label-free quantification

Label-free quantification (LFQ) based on data-independent acquisition workflows currently experiences increasing popularity. Several software tools have been recently published or are commercially available. The present study focuses on the evaluation of three different software packages (Progenesis, synapter, and ISOQuant) supporting ion mobility enhanced data-independent acquisition data. In order to benchmark the LFQ performance of the different tools, we generated two hybrid proteome samples of defined quantitative composition containing tryptically digested proteomes of three different species (mouse, yeast, Escherichia coli). This model dataset simulates complex biological samples containing large numbers of both unregulated (background) proteins as well as up- and downregulated proteins with exactly known ratios between samples. We determined the number and dynamic range of quantifiable proteins and analyzed the influence of applied algorithms (retention time alignment, clustering, normalization, etc.) on quantification results. Analysis of technical reproducibility revealed median coefficients of variation of reported protein abundances below 5% for MS(E) data for Progenesis and ISOQuant. Regarding accuracy of LFQ, evaluation with synapter and ISOQuant yielded superior results compared to Progenesis. In addition, we discuss reporting formats and user friendliness of the software packages. The data generated in this study have been deposited to the ProteomeXchange Consortium with identifier PXD001240 (http://proteomecentral.proteomexchange.org/dataset/PXD001240).

Biocompatibility assessment of haemodialysis membrane materials by proteomic investigations

We examine and compare the protein adsorption capacity and coagulation profiles of different haemodialysis membrane biomaterials.

Quantitative dissection and modeling of the NF-κB p100-p105 module reveals interdependent precursor proteolysis

The mechanisms that govern proteolytic maturation or complete destruction of the precursor proteins p100 and p105 are fundamental to homeostasis and activation of NF-κB; however, they remain poorly understood. Using mass-spectrometry-based quantitative analysis of noncanonical LTβR-induced signaling, we demonstrate that stimulation induces simultaneous processing of both p100 and p105. The precursors not only form hetero-oligomers but also interact with the ATPase VCP/p97, and their induced proteolysis strictly depends on the signal response domain (SRD) of p100, suggesting that the SRD-targeting proteolytic machinery acts in cis and in trans. Separation of cellular pools by isotope labeling revealed synchronous dynamics of p105 and p100 proteolysis. The generation of p50 and p52 from their precursors depends on functional VCP/p97. We have developed quantitative mathematical models that describe the dynamics of the system and predict that p100-p105 complexes are signal responsive.

Analytical challenges translating mass spectrometry-based phosphoproteomics from discovery to clinical applications

Phosphoproteomics is the systematic study of one of the most common protein modifications in high throughput with the aim of providing detailed information of the control, response, and communication of biological systems in health and disease. Advances in analytical technologies and strategies, in particular the contributions of high-resolution mass spectrometers, efficient enrichments of phosphopeptides, and fast data acquisition and annotation, have catalyzed dramatic expansion of signaling landscapes in multiple systems during the past decade. While phosphoproteomics is an essential inquiry to map high-resolution signaling networks and to find relevant events among the apparently ubiquitous and widespread modifications of proteome, it presents tremendous challenges in separation sciences to translate it from discovery to clinical practice. In this mini-review, we summarize the analytical tools currently utilized for phosphoproteomic analysis (with focus on MS), progresses made on deciphering clinically relevant kinase-substrate networks, MS uses for biomarker discovery and validation, and the potential of phosphoproteomics for disease diagnostics and personalized medicine.