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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

A systems approach to prion disease.

Prions cause transmissible neurodegenerative diseases and replicate by conformational conversion of normal benign forms of prion protein (PrP(C)) to disease-causing PrP(Sc) isoforms. A systems approach to disease postulates that disease arises from perturbation of biological networks in the relevant organ. We tracked global gene expression in the brains of eight distinct mouse strain-prion strain combinations throughout the progression of the disease to capture the effects of prion strain, host genetics, and PrP concentration on disease incubation time. Subtractive analyses exploiting various aspects of prion biology and infection identified a core of 333 differentially expressed genes (DEGs) that appeared central to prion disease. DEGs were mapped into functional pathways and networks reflecting defined neuropathological events and PrP(Sc) replication and accumulation, enabling the identification of novel modules and modules that may be involved in genetic effects on incubation time and in prion strain specificity. Our systems analysis provides a comprehensive basis for developing models for prion replication and disease, and suggests some possible therapeutic approaches.

Enhanced detection of low abundance human plasma proteins using a tandem IgY12-SuperMix immunoaffinity separation strategy.

The enormous dynamic range of human bodily fluid proteomes poses a significant challenge for current MS-based proteomics technologies as it makes it especially difficult to detect low abundance proteins in human biofluids such as blood plasma, which is an essential aspect for successful biomarker discovery efforts. Here we present a novel tandem IgY12-SuperMix immunoaffinity separation system for enhanced detection of low abundance proteins in human plasma. The tandem IgY12-SuperMix system separates approximately 60 abundant proteins from the low abundance proteins in plasma, allowing for significant enrichment of low abundance plasma proteins in the SuperMix flow-through fraction. High reproducibility of the tandem separations was observed in terms of both sample processing recovery and LC-MS/MS identification results based on spectral count data. The ability to quantitatively measure differential protein abundances following application of the tandem separations was demonstrated by spiking six non-human standard proteins at three different levels into plasma. A side-by-side comparison between the SuperMix flow-through and IgY12 flow-through samples analyzed by both one- and two-dimensional LC-MS/MS revealed a 60-80% increase in proteome coverage as a result of the SuperMix separations, suggesting significantly enhanced detection of low abundance proteins. A total of 695 plasma proteins were confidently identified in a single analysis (with a minimum of two peptides per protein) by coupling the tandem separation strategy with two-dimensional LC-MS/MS, including 42 proteins with reported normal concentrations of approximately 100 pg/ml to 100 ng/ml. The concentrations of two selected proteins, macrophage colony-stimulating factor 1 and matrix metalloproteinase-8, were independently validated by ELISA as 202 pg/ml and 12.4 ng/ml, respectively. Evaluation of binding efficiency revealed that 45 medium abundance proteins were efficiently captured by the SuperMix column with >90% retention. Taken together, these results illustrate the potential broad utilities of this tandem IgY12-SuperMix strategy for proteomics applications involving human biofluids where effectively addressing the dynamic range challenge of the specimen is imperative.

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.

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.

Mouse-specific tandem IgY7-SuperMix immunoaffinity separations for improved LC-MS/MS coverage of the plasma proteome.

We report on a mouse specific SuperMix immunoaffinity separation system for separating low-abundance proteins from high and moderate abundance proteins in mouse plasma. When applied in tandem with a mouse IgY7 column that removes the seven most abundant proteins in plasma, the SuperMix column captures more than 100 additional moderate abundance proteins, thus allowing significant enrichment of low-abundance proteins in the flow-through fraction. A side-by-side comparison of results obtained from 2D-LC-MS/MS analyses of flow-through samples from IgY7 and SuperMix columns revealed a nearly 2-fold improvement in the overall proteome coverage. Detection of low-abundance proteins was also enhanced, as evidenced by a more than 2-fold increase in the coverage of cytokines, growth factors, and other low-abundance proteins. Moreover, the tandem separations are automated, reproducible, and allow effective identification of protein abundance differences from LC-MS/MS analyses. Considering the overall reproducibility and increased sensitivity using the IgY7-SuperMix separation system, we anticipate broad applications of this strategy for biomarker discovery using mouse models.

Dynamically multiplexed ion mobility time-of-flight mass spectrometry.

Ion mobility spectrometry-time-of-flight mass spectrometry (IMS-TOFMS) has been increasingly used in analysis of complex biological samples. A major challenge is to transform IMS-TOFMS to a high-sensitivity, high-throughput platform, for example, for proteomics applications. In this work, we have developed and integrated three advanced technologies, including efficient ion accumulation in an ion funnel trap prior to IMS separation, multiplexing (MP) of ion packet introduction into the IMS drift tube, and signal detection with an analog-to-digital converter, into the IMS-TOFMS system for the high-throughput analysis of highly complex proteolytic digests of, for example, blood plasma. To better address variable sample complexity, we have developed and rigorously evaluated a novel dynamic MP approach that ensures correlation of the analyzer performance with an ion source function and provides the improved dynamic range and sensitivity throughout the experiment. The MP IMS-TOFMS instrument has been shown to reliably detect peptides at a concentration of 1 nM in the presence of a highly complex matrix, as well as to provide a 3 orders of magnitude dynamic range and a mass measurement accuracy of better than 5 ppm. When matched against human blood plasma database, the detected IMS-TOF features were found to yield approximately 700 unique peptide identifications at a false discovery rate (FDR) of approximately 7.5%. Accounting for IMS information gave rise to a projected FDR of approximately 4%. Signal reproducibility was found to be greater than 80%, while the variations in the number of unique peptide identifications were <15%. A single sample analysis was completed in 15 min that constitutes almost 1 order of magnitude improvement compared to a more conventional LC-MS approach.

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.

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.