Identification and Quantitation of Coding Variants and Isoforms of Pulmonary Surfactant Protein A

Mass spectrometry-based targeted proteomics for analysis of protein mutations

Cancers are caused by accumulated DNA mutations. This recognition of the central role of mutations in cancer and recent advances in next-generation sequencing, has initiated the massive screening of clinical samples and the identification of 1000s of cancer-associated gene mutations. However, proteomic analysis of the expressed mutation products lags far behind genomic (transcriptomic) analysis. With comprehensive global proteomics analysis, only a small percentage of single nucleotide variants detected by DNA and RNA sequencing have been observed as single amino acid variants due to current technical limitations. Proteomic analysis of mutations is important with the potential to advance cancer biomarker development and the discovery of new therapeutic targets for more effective disease treatment. Targeted proteomics using selected reaction monitoring (also known as multiple reaction monitoring) and parallel reaction monitoring, has emerged as a powerful tool with significant advantages over global proteomics for analysis of protein mutations in terms of detection sensitivity, quantitation accuracy and overall practicality (e.g., reliable identification and the scale of quantification). Herein we review recent advances in the targeted proteomics technology for enhancing detection sensitivity and multiplexing capability and highlight its broad biomedical applications for analysis of protein mutations in human bodily fluids, tissues, and cell lines. Furthermore, we review recent applications of top-down proteomics for analysis of protein mutations. Unlike the commonly used bottom-up proteomics which requires digestion of proteins into peptides, top-down proteomics directly analyzes intact proteins for more precise characterization of mutation isoforms. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale targeted detection and quantification of important protein mutations are discussed.

Small Peptide Derivatives Within the Carbohydrate Recognition Domain of SP-A2 Modulate Asthma Outcomes in Mouse Models and Human Cells

Surfactant Protein-A (SP-A) is an innate immune modulator that regulates a variety of pulmonary host defense functions. We have shown that SP-A is dysfunctional in asthma, which could be partly due to genetic heterogeneity. In mouse models and primary bronchial epithelial cells from asthmatic participants, we evaluated the functional significance of a particular single nucleotide polymorphism of SP-A2, which results in an amino acid substitution at position 223 from glutamine (Q) to lysine (K) within the carbohydrate recognition domain (CRD). We found that SP-A 223Q humanized mice had greater protection from inflammation and mucin production after IL-13 exposure as compared to SP-A-2 223K mice. Likewise, asthmatic participants with two copies the major 223Q allele demonstrated better lung function and asthma control as compared to asthmatic participants with two copies of the minor SP-A 223K allele. In primary bronchial epithelial cells from asthmatic participants, full-length recombinant SP-A 223Q was more effective at reducing IL-13-induced MUC5AC gene expression compared to SP-A 223K. Given this activity, we developed 10 and 20 amino acid peptides of SP-A2 spanning position 223Q. We show that the SP-A 223Q peptides reduce eosinophilic inflammation, mucin production and airways hyperresponsiveness in a house dust mite model of asthma, protect from lung function decline during an IL-13 challenge model in mice, and decrease IL-13-induced MUC5AC gene expression in primary airway epithelial cells from asthmatic participants. These results suggest that position 223 within the CRD of SP-A2 may modulate several outcomes relevant to asthma, and that short peptides of SP-A2 retain anti-inflammatory properties similar to that of the endogenous protein.

ERK-dependent proteasome degradation of Txnip regulates thioredoxin oxidoreductase activity

Dynamic control of thioredoxin (Trx) oxidoreductase activity is essential for balancing the need of cells to rapidly respond to oxidative/nitrosative stress and to temporally regulate thiol-based redox signaling. We have previously shown that cytokine stimulation of the respiratory epithelium induces a precipitous decline in cell S-nitrosothiol, which depends upon enhanced Trx activity and proteasome-mediated degradation of Txnip (thioredoxin-interacting protein). We now show that tumor necrosis factor-α-induced Txnip degradation in A549 respiratory epithelial cells is regulated by the extracellular signal-regulated protein kinase (ERK) mitogen-activated protein kinase pathway and that ERK inhibition augments both intracellular reactive oxygen species and S-nitrosothiol. ERK-dependent Txnip ubiquitination and proteasome degradation depended upon phosphorylation of a PXTP motif threonine (Thr³⁴⁹) located within the C-terminal α-arrestin domain and proximal to a previously characterized E3 ubiquitin ligase-binding site. Collectively, these findings demonstrate the ERK mitogen-activated protein kinase pathway to be integrally involved in regulating Trx oxidoreductase activity and that the regulation of Txnip lifetime via ERK-dependent phosphorylation is an important mediator of this effect.

Using Stepwise Pharmacogenomics and Proteomics to Predict Hepatitis C Treatment Response in Difficult to Treat Patient Populations

PURPOSE

In the interferon era of hepatitis C virus (HCV) therapies, genotype/subtype, cirrhosis, prior treatment failure, sex, and race predicted relapse. Our objective is to validate a targeted proteomics platform of 17 peptides to predict sustained virologic response (SVR).

EXPERIMENTAL DESIGN

Stored plasma from three, open-label, trials of HIV/HCV-coinfected subjects receiving interferon-containing regimens is identified. LC-MS/MS is used to quantitate the peptides directly from plasma, and IL28B genotyping is completed using stored peripheral blood mononuclear cells (PBMC). A logistic regression model is built to analyze the probability of SVR using responders and nonresponders to interferon-based regimens.

RESULTS

The cohort (N = 35) is predominantly black (51.4%), male (86%), and with median age 48 years. Most patients achieve SVR (54%). Using multivariable models, it is verified that three human corticosteroid binding globulin (CBG) peptides are predictive of SVR in patients with the unfavorable IL28B genotypes (CT/TT). The model performs better than IL28B alone, with an area under the curve of 0.870.

CONCLUSIONS AND CLINICAL RELEVANCE

In HIV/HCV-coinfected patients, three human CBG peptides that accurately predict treatment response with interferon-based therapy are identified. This study suggests that a stepwise approach combining a genetic predictor followed by targeted proteomics can improve the accuracy of clinical decision-making.

Layers of regulation of cell-cycle gene expression in the budding yeast Saccharomyces cerevisiae

In the budding yeast Saccharomyces cerevisiae, transcription factors (TFs) regulate the periodic expression of many genes during the cell cycle, including gene products required for progression through cell-cycle events. Experimental evidence coupled with quantitative models suggests that a network of interconnected TFs is capable of regulating periodic genes over the cell cycle. Importantly, these dynamical models were built on transcriptomics data and assumed that TF protein levels and activity are directly correlated with mRNA abundance. To ask whether TF transcripts match protein expression levels as cells progress through the cell cycle, we applied a multiplexed targeted mass spectrometry approach (parallel reaction monitoring) to synchronized populations of cells. We found that protein expression of many TFs and cell-cycle regulators closely followed their respective mRNA transcript dynamics in cycling wild-type cells. Discordant mRNA/protein expression dynamics was also observed for a subset of cell-cycle TFs and for proteins targeted for degradation by E3 ubiquitin ligase complexes such as SCF (Skp1/Cul1/F-box) and APC/C (anaphase-promoting complex/cyclosome). We further profiled mutant cells lacking B-type cyclin/CDK activity ( clb1-6) where oscillations in ubiquitin ligase activity, cyclin/CDKs, and cell-cycle progression are halted. We found that a number of proteins were no longer periodically degraded in clb1-6 mutants compared with wild type, highlighting the importance of posttranscriptional regulation. Finally, the TF complexes responsible for activating G1/S transcription (SBF and MBF) were more constitutively expressed at the protein level than at periodic mRNA expression levels in both wild-type and mutant cells. This comprehensive investigation of cell-cycle regulators reveals that multiple layers of regulation (transcription, protein stability, and proteasome targeting) affect protein expression dynamics during the cell cycle.

Genetic Association of Pulmonary Surfactant Protein Genes, SFTPA1, SFTPA2, SFTPB, SFTPC, and SFTPD With Cystic Fibrosis

Surfactant proteins (SP) are involved in surfactant function and innate immunity in the human lung. Both lung function and innate immunity are altered in CF, and altered SP levels and genetic association are observed in Cystic Fibrosis (CF). We hypothesized that single nucleotide polymorphisms (SNPs) within the SP genes associate with CF or severity subgroups, either through single SNP or via SNP-SNP interactions between two SNPs of a given gene (intragenic) and/or between two genes (intergenic). We genotyped a total of 17 SP SNPs from 72 case-trio pedigree (SFTPA1 (5), SFTPA2 (4), SFTPB (4), SFTPC (2), and SFTPD (2)), and identified SP SNP associations by applying quantitative genetic principles. The results showed (a) Two SNPs, SFTPB rs7316 (p = 0.0083) and SFTPC rs1124 (p = 0.0154), each associated with CF. (b) Three intragenic SNP-SNP interactions, SFTPB (rs2077079, rs3024798), and SFTPA1 (rs1136451, rs1059057 and rs4253527), associated with CF. (c) A total of 34 intergenic SNP-SNP interactions among the 4 SP genes to be associated with CF. (d) No SNP-SNP interaction was observed between SFTPA1 or SFTPA2 and SFTPD. (e) Equal number of SNP-SNP interactions were observed between SFTPB and SFTPA1/SFTPA2 (n = 7) and SP-B and SFTPD (n = 7). (f) SFTPC exhibited significant SNP-SNP interactions with SFTPA1/SFTPA2 (n = 11), SFTPB (n = 4) and SFTPD (n = 3). (g) A single SFTPB SNP was associated with mild CF after Bonferroni correction, and several intergenic interactions that are associated (p < 0.01) with either mild or moderate/severe CF were observed. These collectively indicate that complex SNP-SNP interactions of the SP genes may contribute to the pulmonary disease in CF patients. We speculate that SPs may serve as modifiers for the varied progression of pulmonary disease in CF and/or its severity.

New Strategies and Challenges in Lung Proteomics and Metabolomics. An Official American Thoracic Society Workshop Report

This document presents the proceedings from the workshop entitled, "New Strategies and Challenges in Lung Proteomics and Metabolomics" held February 4th-5th, 2016, in Denver, Colorado. It was sponsored by the National Heart Lung Blood Institute, the American Thoracic Society, the Colorado Biological Mass Spectrometry Society, and National Jewish Health. The goal of this workshop was to convene, for the first time, relevant experts in lung proteomics and metabolomics to discuss and overcome specific challenges in these fields that are unique to the lung. The main objectives of this workshop were to identify, review, and/or understand: (1) emerging technologies in metabolomics and proteomics as applied to the study of the lung; (2) the unique composition and challenges of lung-specific biological specimens for metabolomic and proteomic analysis; (3) the diverse informatics approaches and databases unique to metabolomics and proteomics, with special emphasis on the lung; (4) integrative platforms across genetic and genomic databases that can be applied to lung-related metabolomic and proteomic studies; and (5) the clinical applications of proteomics and metabolomics. The major findings and conclusions of this workshop are summarized at the end of the report, and outline the progress and challenges that face these rapidly advancing fields.

Quantitative bottom up analysis of infliximab in serum using protein A purification and integrated μLC-electrospray chip IonKey MS/MS technology

Background: TNO Triskelion has applied its general workflow for the development of quantitative LC–MS methods for proteins in biological matrices to the quantification of infliximab in rat serum using bottom up μLC–MS/MS. Results/methodology: The general workflow consists of sample purification, analyte processing and LC–MS analysis. In the development of a quantitative μLC–MS/MS method for infliximab in rat serum the analyte processing part and the LC–MS part were optimized, in order to meet the different sample requirements of μLC–MS as compared with UPLC–MS. Using the optimized μLC–MS/MS method the LOQ was 75 ng/ml. Conclusion: The present study showed that it is possible to gain sensitivity when going to smaller scale LC–MS (UPLC–MS to μLC–MS). Due to the combination of a modified sample preparation approach and the application of μLC–MS a lower LOQ could be achieved for infliximab compared with a previously developed UPLC–MS method.

Targeted Proteomics of Human Metapneumovirus in Clinical Samples and Viral Cultures

The rapid, sensitive, and specific identification of infectious pathogens from clinical isolates is a critical need in the hospital setting. Mass spectrometry (MS) has been widely adopted for identification of bacterial pathogens, although polymerase chain reaction remains the mainstay for the identification of viral pathogens. Here, we explored the capability of MS for the detection of human metapneumovirus (HMPV), a common cause of respiratory tract infections in children. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) sequencing of a single HMPV reference strain (CAN97-83) was used to develop a multiple reaction monitoring (MRM) assay that employed stable isotope-labeled peptide internal standards for quantitation of HMPV. Using this assay, we confirmed the presence of HMPV in viral cultures from 10 infected patients and further assigned genetic lineage based on the presence/absence of variant peptides belonging to the viral matrix and nucleoproteins. Similar results were achieved for primary clinical samples (nasopharyngeal aspirates) from the same individuals. As validation, virus lineages, and variant coding sequences, were confirmed by next-generation sequencing of viral RNA obtained from the culture samples. Finally, separate dilution series of HMPV A and B lineages were used to further refine and assess the robustness of the assay and to determine limits of detection in nasopharyngeal aspirates. Our results demonstrate the applicability of MRM for identification of HMPV, and assignment of genetic lineage, from both viral cultures and clinical samples. More generally, this approach should prove tractable as an alternative to nucleic-acid based sequencing for the multiplexed identification of respiratory virus infections.

Mass spectrometrists should search only for peptides they care about

Analysis pipelines that assign peptides to shotgun proteomics mass spectra often discard identified spectra deemed irrelevant to the scientific hypothesis being tested. To improve statistical power, I propose that researchers remove irrelevant peptides from the database prior to searching rather than assigning these peptides to spectra and then discarding the matches.