Serum molecular biomarkers in neuromyelitis optica and multiple sclerosis.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is a rare and severe inflammatory demyelinating disorder of the central nervous system (CNS), which mainly affects the optic nerves and spinal cord. The aims of this study were to determine whether the expression levels of serological cytokines could distinguish 1) NMOSD from healthy controls (HCs); and 2) NMOSD patients with and without the aquaporin-4 (AQP4) antibody biomarker from each other; and 3) NMOSD patients without the antibody to AQP4 from MS patients. METHODS: The expression levels of 200 proteins in serum from 41 NMOSD (32 with antibodies to AQP4, 9 without antibodies to AQP4), 12 MS patients, and 34 HCs were measured using glass-based antibody arrays. None of the patients received any immunosuppressive treatment. In parallel, the correlation between protein expression in NMOSD/MS patients and clinical traits was determined with Weighted Gene Co-expression Network Analysis (WGCNA). RESULTS: Thirty-nine serological proteins were differentially expressed in NMOSD patients compared to HCs, with 29 of these proteins not observed in MS patients. In addition, the data reveal 15 differentially-expression proteins (DEPs) between AQP4-IgG seronegative and AQP4-IgG seropositive NMOSD patients, and 9 DEPs between NMOSD and MS patients who did not have AQP4-IgG. CONCLUSION: Serological IL-17B is significantly upregulated in both NMOSD and MS patients compared to HCs, and could be a key biomarker of NMOSD and MS. Serological VEGF, MPIF-1 and NrCAM were positively associated with AQP4-IgG titer. We also demonstrate that EGF may be involved in the breakdown of the BBB by downregulating Claudin-5.

A Case-Control Study of Follicular Fluid Cytokine Profiles in Women with Diminished Ovarian Reserve.

Ovarian reserve is an important determinant of a woman's reproductive potential, and women with diminished ovarian reserve (DOR) often seek in vitro fertilization (IVF). The underlying etiology of DOR is unknown, but follicular fluid cytokine concentrations likely play a role in follicular development and maturation. The present study seeks to investigate the expression of cytokines in follicular fluid (FF) of women with DOR undergoing IVF and explore correlated functional pathways. One hundred ninety-four women undergoing ovarian stimulation were recruited at the time of oocyte retrieval. Women were classified as having DOR if they met one or more of the following criteria: AMH < 1 ng/ml, FSH > 10 mIU/ml, and/or AFC < 10. Controls included women undergoing IVF for male factor, tubal factor due to tubal ligation, or planned oocyte cryopreservation (non-oncologic). The concentrations of 480 cytokines and related growth factors in follicular fluid were determined using a multiplex immunoassay. Fifty-nine cytokines had significantly different concentrations (53 higher and 6 lower) in the DOR relative to the control group after adjusting for age and body mass index (BMI) (false discovery rate; FDR < 0.1). Using the most informative 44 biomarkers as indicated by a random forest (RF) model, an area under the curve (AUC) of 0.78 was obtained. Thus, follicular microenvironment differs between women with DOR and normal ovarian reserve. The differentially expressed cytokines belong to diverse processes that are primarily involved in follicular maturation and ovulation. These changes may play an important role in treatment outcomes in women with DOR.

Data Analysis for Antibody Arrays.

When obtaining high-throughput data from antibody arrays, researchers have to face a couple of questions: How and by what means can they get reasonable results significant to their research from these data? Similar to a gene microarray, the classical statistical pipeline of an antibody array includes data preprocessing transformation, differential expression analysis, classification, and biological annotation analysis. In this chapter, we will provide a pipeline of statistical approaches suitable for antibody arrays to facilitate better understanding of the results gained from each of these steps.

Sandwich-Based Antibody Arrays for Protein Detection.

Sandwich-based antibody arrays enable the detection of multiple proteins simultaneously, thus offering a time- and cost-effective alternative to single-plex platforms. The protein of interest is "sandwiched" between an antibody that captures it to the array and a second antibody that is used for detection. Here we describe a 1-day procedure to process samples, such as serum or cell lysates, with a quantitative sandwich-based antibody array on a glass substrate using fluorescence.

Differences in serum proteins in traditional Chinese medicine constitutional population: Analysis and verification.

Traditional Chinese medicine assigns individuals into different categories called "constitutions" to help guide the clinical treatment according to subjective physiologic, psychologic analyses, large-scale clinical observations, and epidemiologic studies. To further explore more objective expressions of constitutions, antibody microarrays were used to analyze the serologic protein profiles of two different constitutions, a balanced (or healthy) constitution (BC) and the dampness constitution (DC) comprising phlegm-dampness and damp-heat constitutions. The profiles of changing constitutions across time were also analyzed. Nineteen differentially expressed proteins between the two groups were identified, with known biologic functions involved in immunity and inflammation. This proteomic study may provide a biologic explanation why the BC is different than the dampness constitution.

Developing a periodontal disease antibody array for the prediction of severe periodontal disease using machine learning classifiers.

BACKGROUND: The aim of this study was to simultaneously and quantitatively assess the expression levels of 20 periodontal disease-related proteins in gingival crevicular fluid (GCF) from normal controls (NOR) and severe periodontitis (SP) patients with an antibody array. METHODS: Antibodies against 20 periodontal disease-related proteins were spotted onto a glass slide to create a periodontal disease antibody array (PDD). The array was then incubated with GCF samples collected from 25 NOR and 25 SP patients. Differentially expressed proteins between NOR and SP patients were then used to build receiver operator characteristic (ROC) curves and compare five classification models, including support vector machine, random forest, k nearest neighbor, linear discriminant analysis, and Classification and Regression Trees. RESULTS: Seven proteins (C-reactive protein, interleukin [IL]-1α, interleukin-1ß, interleukin-8, matrix metalloproteinase-13, osteoprotegerin, and osteoactivin) were significantly upregulated in SP patients compared with NOR, while receptor activator of nuclear factor-kappa was significantly downregulated. The highest diagnostic accuracy using a ROC curve was observed for IL-1ß with an area under the curve of 0.984. Five of the proteins (IL-1ß, IL-8, MMP-13, osteoprotegerin, and osteoactivin) were identified as important features for classification. Linear discriminant analysis had the highest classification accuracy across the five classification models that were tested. CONCLUSION: This study highlights the potential of antibody arrays to diagnose periodontal disease.

Advances in cell-free protein array methods.

INTRODUCTION: Cell-free protein microarrays represent a special form of protein microarray which display proteins made fresh at the time of the experiment, avoiding storage and denaturation. They have been used increasingly in basic and translational research over the past decade to study protein-protein interactions, the pathogen-host relationship, post-translational modifications, and antibody biomarkers of different human diseases. Their role in the first blood-based diagnostic test for early stage breast cancer highlights their value in managing human health. Cell-free protein microarrays will continue to evolve to become widespread tools for research and clinical management. Areas covered: We review the advantages and disadvantages of different cell-free protein arrays, with an emphasis on the methods that have been studied in the last five years. We also discuss the applications of each microarray method. Expert commentary: Given the growing roles and impact of cell-free protein microarrays in research and medicine, we discuss: 1) the current technical and practical limitations of cell-free protein microarrays; 2) the biomarker discovery and verification pipeline using protein microarrays; and 3) how cell-free protein microarrays will advance over the next five years, both in their technology and applications.

Multiplexed Nucleic Acid Programmable Protein Arrays.

Rationale: Cell-free protein microarrays display naturally-folded proteins based on just-in-time in situ synthesis, and have made important contributions to basic and translational research. However, the risk of spot-to-spot cross-talk from protein diffusion during expression has limited the feature density of these arrays. Methods: In this work, we developed the Multiplexed Nucleic Acid Programmable Protein Array (M-NAPPA), which significantly increases the number of displayed proteins by multiplexing as many as five different gene plasmids within a printed spot. Results: Even when proteins of different sizes were displayed within the same feature, they were readily detected using protein-specific antibodies. Protein-protein interactions and serological antibody assays using human viral proteome microarrays demonstrated that comparable hits were detected by M-NAPPA and non-multiplexed NAPPA arrays. An ultra-high density proteome microarray displaying > 16k proteins on a single microscope slide was produced by combining M-NAPPA with a photolithography-based silicon nano-well platform. Finally, four new tuberculosis-related antigens in guinea pigs vaccinated with Bacillus Calmette-Guerin (BCG) were identified with M-NAPPA and validated with ELISA. Conclusion: All data demonstrate that multiplexing features on a protein microarray offer a cost-effective fabrication approach and have the potential to facilitate high throughput translational research.

Advancing translational research with next-generation protein microarrays.

Protein microarrays are a high-throughput technology used increasingly in translational research, seeking to apply basic science findings to enhance human health. In addition to assessing protein levels, posttranslational modifications, and signaling pathways in patient samples, protein microarrays have aided in the identification of potential protein biomarkers of disease and infection. In this perspective, the different types of full-length protein microarrays that are used in translational research are reviewed. Specific studies employing these microarrays are presented to highlight their potential in finding solutions to real clinical problems. Finally, the criteria that should be considered when developing next-generation protein microarrays are provided.

Development of a full-length human protein production pipeline.

There are many proteomic applications that require large collections of purified protein, but parallel production of large numbers of different proteins remains a very challenging task. To help meet the needs of the scientific community, we have developed a human protein production pipeline. Using high-throughput (HT) methods, we transferred the genes of 31 full-length proteins into three expression vectors, and expressed the collection as N-terminal HaloTag fusion proteins in Escherichia coli and two commercial cell-free (CF) systems, wheat germ extract (WGE) and HeLa cell extract (HCE). Expression was assessed by labeling the fusion proteins specifically and covalently with a fluorescent HaloTag ligand and detecting its fluorescence on a LabChip(®) GX microfluidic capillary gel electrophoresis instrument. This automated, HT assay provided both qualitative and quantitative assessment of recombinant protein. E. coli was only capable of expressing 20% of the test collection in the supernatant fraction with ≥20 µg yields, whereas CF systems had ≥83% success rates. We purified expressed proteins using an automated HaloTag purification method. We purified 20, 33, and 42% of the test collection from E. coli, WGE, and HCE, respectively, with yields ≥1 µg and ≥90% purity. Based on these observations, we have developed a triage strategy for producing full-length human proteins in these three expression systems.

Accurate LC peak boundary detection for ¹6O/¹8O labeled LC-MS data.

In liquid chromatography-mass spectrometry (LC-MS), parts of LC peaks are often corrupted by their co-eluting peptides, which results in increased quantification variance. In this paper, we propose to apply accurate LC peak boundary detection to remove the corrupted part of LC peaks. Accurate LC peak boundary detection is achieved by checking the consistency of intensity patterns within peptide elution time ranges. In addition, we remove peptides with erroneous mass assignment through model fitness check, which compares observed intensity patterns to theoretically constructed ones. The proposed algorithm can significantly improve the accuracy and precision of peptide ratio measurements.

Trauma-associated human neutrophil alterations revealed by comparative proteomics profiling.

PURPOSE: Polymorphonuclear neutrophils (PMNs) play an important role in mediating the innate immune response after severe traumatic injury; however, the cellular proteome response to traumatic condition is still largely unknown. EXPERIMENTAL DESIGN: We applied 2D-LC-MS/MS-based shotgun proteomics to perform comparative proteome profiling of human PMNs from severe trauma patients and healthy controls. RESULTS: A total of 197 out of ~2500 proteins (being identified with at least two peptides) were observed with significant abundance changes following the injury. The proteomics data were further compared with transcriptomics data for the same genes obtained from an independent patient cohort. The comparison showed that the protein abundance changes for the majority of proteins were consistent with the mRNA abundance changes in terms of directions of changes. Moreover, increased protein secretion was suggested as one of the mechanisms contributing to the observed discrepancy between protein and mRNA abundance changes. Functional analyses of the altered proteins showed that many of these proteins were involved in immune response, protein biosynthesis, protein transport, NRF2-mediated oxidative stress response, the ubiquitin-proteasome system, and apoptosis pathways. CONCLUSIONS AND CLINICAL RELEVANCE: Our data suggest increased neutrophil activation and inhibited neutrophil apoptosis in response to trauma. The study not only reveals an overall picture of functional neutrophil response to trauma at the proteome level, but also provides a rich proteomics data resource of trauma-associated changes in the neutrophil that will be valuable for further studies of the functions of individual proteins in PMNs.

Quantitative proteomics analysis of adsorbed plasma proteins classifies nanoparticles with different surface properties and size.

Nanoparticle biological activity, biocompatibility and fate can be directly affected by layers of readily adsorbed host proteins in biofluids. Here, we report a study on the interactions between human blood plasma proteins and nanoparticles with a controlled systematic variation of properties using (18)O-labeling and LC-MS-based quantitative proteomics. We developed a novel protocol to both simplify isolation of nanoparticle bound proteins and improve reproducibility. LC-MS analysis identified and quantified 88 human plasma proteins associated with polystyrene nanoparticles consisting of three different surface chemistries and two sizes, as well as, for four different exposure times (for a total of 24 different samples). Quantitative comparison of relative protein abundances was achieved by spiking an (18)O-labeled "universal" reference into each individually processed unlabeled sample as an internal standard, enabling simultaneous application of both label-free and isotopic labeling quantification across the entire sample set. Clustering analysis of the quantitative proteomics data resulted in distinctive patterns that classified the nanoparticles based on their surface properties and size. In addition, temporal data indicated that the formation of the stable protein corona was at equilibrium within 5 min. The comprehensive quantitative proteomics results obtained in this study provide rich data for computational modeling and have potential implications towards predicting nanoparticle biocompatibility.

Trypsin-catalyzed oxygen-18 labeling for quantitative proteomics.

Stable isotope labeling based on relative peptide/protein abundance measurements is commonly applied for quantitative proteomics. Recently, trypsin-catalyzed oxygen-18 labeling has grown in popularity due to its simplicity, cost-effectiveness, and its ability to universally label peptides with high sample recovery. In (18)O labeling, both C-terminal carboxyl group atoms of tryptic peptides can be enzymatically exchanged with (18)O, thus providing the labeled peptide with a 4 Da mass shift from the (16)O-labeled sample. Peptide (18)O labeling is ideally suited for generating a labeled "universal" reference sample used for obtaining accurate and reproducible quantitative measurements across large number of samples in quantitative discovery proteomics.

Blood peptidome-degradome profile of breast cancer.

BACKGROUND: Cancer invasion and metastasis are closely associated with activities within the degradome; however, little is known about whether these activities can be detected in the blood of cancer patients. METHODOLOGY AND PRINCIPAL FINDINGS: The peptidome-degradome profiles of pooled blood plasma sampled from 15 breast cancer patients (BCP) and age, race, and menopausal status matched control healthy persons (HP) were globally characterized using advanced comprehensive separations combined with tandem Fourier transform mass spectrometry and new data analysis approaches that facilitated top-down peptidomic analysis. The BCP pool displayed 71 degradome protein substrates that encompassed 839 distinct peptidome peptides. In contrast, the HP 50 degradome substrates found encompassed 425 peptides. We find that the ratios of the peptidome peptide relative abundances can vary as much as >4000 fold between BCP and HP. The experimental results also show differential degradation of substrates in the BCP sample in their functional domains, including the proteolytic and inhibitory sites of the plasmin-antiplasmin and thrombin-antithrombin systems, the main chains of the extracellular matrix protection proteins, the excessive degradation of innate immune system key convertases and membrane attack complex components, as well as several other cancer suppressor proteins. CONCLUSIONS: Degradomics-peptidomics profiling of blood plasma is highly sensitive to changes not evidenced by conventional bottom-up proteomics and potentially provides unique signatures of possible diagnostic utility.

Clinical microfluidics for neutrophil genomics and proteomics.

Neutrophils have key roles in modulating the immune response. We present a robust methodology for rapidly isolating neutrophils directly from whole blood with 'on-chip' processing for mRNA and protein isolation for genomics and proteomics. We validate this device with an ex vivo stimulation experiment and by comparison with standard bulk isolation methodologies. Last, we implement this tool as part of a near-patient blood processing system within a multi-center clinical study of the immune response to severe trauma and burn injury. The preliminary results from a small cohort of subjects in our study and healthy controls show a unique time-dependent gene expression pattern clearly demonstrating the ability of this tool to discriminate temporal transcriptional events of neutrophils within a clinical setting.

Plasma proteome response to severe burn injury revealed by 18O-labeled "universal" reference-based quantitative proteomics.

A burn injury represents one of the most severe forms of human trauma and is responsible for significant mortality worldwide. Here, we present the first quantitative proteomics investigation of the blood plasma proteome response to severe burn injury by comparing the plasma protein concentrations of 10 healthy control subjects with those of 15 severe burn patients at two time-points following the injury. The overall analytical strategy for this work integrated immunoaffinity depletion of the 12 most abundant plasma proteins with cysteinyl-peptide enrichment-based fractionation prior to LC-MS analyses of individual patient samples. Incorporation of an 18O-labeled "universal" reference among the sample sets enabled precise relative quantification across samples. In total, 313 plasma proteins confidently identified with two or more unique peptides were quantified. Following statistical analysis, 110 proteins exhibited significant abundance changes in response to the burn injury. The observed changes in protein concentrations suggest significant inflammatory and hypermetabolic response to the injury, which is supported by the fact that many of the identified proteins are associated with acute phase response signaling, the complement system, and coagulation system pathways. The regulation of approximately 35 proteins observed in this study is in agreement with previous results reported for inflammatory or burn response, but approximately 50 potentially novel proteins previously not known to be associated with burn response or inflammation are also found. Elucidating proteins involved in the response to severe burn injury may reveal novel targets for therapeutic interventions as well as potential predictive biomarkers for patient outcomes such as multiple organ failure.

Strategy for degradomic-peptidomic analysis of human blood plasma.

Herein we describe a strategy for degradomic-peptidomic analyses. The human blood peptidome was isolated through application of AC/SEC, which enriched its components by >300-fold. The isolated peptidome components were separated by long column HRLC providing a peak capacity of approximately 300 for species having MWs of up to 20 kDa. The separated species were identified by the FT MS/MS-UStags sequencing method. We identified >200 peptidome components that originated from 29 protein substrates from the blood plasma of a single healthy person. The peptidome peptides identified had MWs range of 0.5-14 kDa and identifications were achieved with extremely low (near zero) false discovery rates through searching the IPI human protein database (approximately 70,000 entries). Some of the peptidome peptides identified have mutations and modifications such as acetylation, acetylhexosamine, amidation, cysteinylation, didehydro, oxidation, and pyro-glu. The capabilities described enable the global analysis of the peptidome peptides to identify degradome targets such as degradome proteases, proteases inhibitors, and other relevant substrates, the cleavage specificities for the degradation of individual substrates, as well as a potential basis for using the various extents of substrate degradation for diagnostic purposes.

Endogenous 3,4-dihydroxyphenylalanine and dopaquinone modifications on protein tyrosine: links to mitochondrially derived oxidative stress via hydroxyl radical.

Oxidative modifications of protein tyrosines have been implicated in multiple human diseases. Among these modifications, elevations in levels of 3,4-dihydroxyphenylalanine (DOPA), a major product of hydroxyl radical addition to tyrosine, has been observed in a number of pathologies. Here we report the first proteome survey of endogenous site-specific modifications, i.e. DOPA and its further oxidation product dopaquinone in mouse brain and heart tissues. Results from LC-MS/MS analyses included 50 and 14 DOPA-modified tyrosine sites identified from brain and heart, respectively, whereas only a few nitrotyrosine-containing peptides, a more commonly studied marker of oxidative stress, were detectable, suggesting the much higher abundance for DOPA modification as compared with tyrosine nitration. Moreover, 20 and 12 dopaquinone-modified peptides were observed from brain and heart, respectively; nearly one-fourth of these peptides were also observed with DOPA modification on the same sites. For both tissues, these modifications are preferentially found in mitochondrial proteins with metal binding properties, consistent with metal-catalyzed hydroxyl radical formation from mitochondrial superoxide and hydrogen peroxide. These modifications also link to a number of mitochondrially associated and other signaling pathways. Furthermore, many of the modification sites were common sites of previously reported tyrosine phosphorylation, suggesting potential disruption of signaling pathways. Collectively, the results suggest that these modifications are linked with mitochondrially derived oxidative stress and may serve as sensitive markers for disease pathologies.

Region-specific protein abundance changes in the brain of MPTP-induced Parkinson's disease mouse model.

Parkinson's disease (PD) is characterized by dopaminergic neurodegeneration in the nigrostriatal region of the brain; however, the neurodegeneration extends well beyond dopaminergic neurons. To gain a better understanding of the molecular changes relevant to PD, we applied two-dimensional LC-MS/MS to comparatively analyze the proteome changes in four brain regions (striatum, cerebellum, cortex, and the rest of brain) using a MPTP-induced PD mouse model with the objective to identify potential nigrostriatal-specific and other region-specific protein abundance changes. The combined analyses resulted in the identification of 4,895 nonredundant proteins with at least two unique peptides per protein. The relative abundance changes in each analyzed brain region were estimated based on the spectral count information. A total of 518 proteins were observed with substantial MPTP-induced abundance changes across different brain regions. A total of 270 of these proteins were observed with specific changes occurring either only in the striatum and/or in the rest of the brain region that contains substantia nigra, suggesting that these proteins are associated with the underlying nigrostriatal pathways. Many of the proteins that exhibit changes were associated with dopamine signaling, mitochondrial dysfunction, the ubiquitin system, calcium signaling, the oxidative stress response, and apoptosis. A set of proteins with either consistent change across all brain regions or with changes specific to the cortex and cerebellum regions were also detected. Ubiquitin specific protease (USP9X), a deubiquination enzyme involved in the protection of proteins from degradation and promotion of the TGF-beta pathway, exhibited altered abundance in all brain regions. Western blot validation showed similar spatial changes, suggesting that USP9X is potentially associated with neurodegeneration. Together, this study for the first time presents an overall picture of proteome changes underlying both nigrostriatal pathways and other brain regions potentially involved in MPTP-induced neurodegeneration. The observed molecular changes provide a valuable reference resource for future hypothesis-driven functional studies of PD.