ProMAT calibrator: A tool for reducing experimental bias in antibody microarrays

Susceptibility to quantum dot induced lung inflammation differs widely among the Collaborative Cross founder mouse strains

Quantum dots (QDs) are engineered semiconductor nanoparticles with unique physicochemical properties that make them potentially useful in clinical, research and industrial settings. However, a growing body of evidence indicates that like other engineered nanomaterials, QDs have the potential to be respiratory hazards, especially in the context of the manufacture of QDs and products containing them, as well as exposures to consumers using these products. The overall goal of this study was to investigate the role of mouse strain in determining susceptibility to QD-induced pulmonary inflammation and toxicity. Male mice from 8 genetically diverse inbred strains (the Collaborative Cross founder strains) were exposed to CdSe-ZnS core-shell QDs stabilized with an amphiphilic polymer. QD treatment resulted in significant increases in the percentage of neutrophils and levels of cytokines present in bronchoalveolar lavage fluid (BALF) obtained from NOD/ShiLtJ and NZO/HlLtJ mice relative to their saline (Sal) treated controls. Cadmium measurements in lung tissue indicated strain-dependent differences in disposition of QDs in the lung. Total glutathione levels in lung tissue were significantly correlated with percent neutrophils in BALF as well as with lung tissue Cd levels. Our findings indicate that QD-induced acute lung inflammation is mouse strain dependent, that it is heritable, and that the choice of mouse strain is an important consideration in planning QD toxicity studies. These data also suggest that formal genetic analyses using additional strains or recombinant inbred strains from these mice could be useful for discovering potential QD-induced inflammation susceptibility loci.

Development of an ELISA microarray assay for the sensitive and simultaneous detection of ten biodefense toxins

Plant and microbial toxins are considered bioterrorism threat agents because of their extreme toxicity and/or ease of availability. Additionally, some of these toxins are increasingly responsible for accidental food poisonings. The current study utilized an ELISA-based protein antibody microarray for the multiplexed detection of ten biothreat toxins, botulinum neurotoxins (BoNT) A, B, C, D, E, F, ricin, shiga toxins 1 and 2 (Stx), and staphylococcus enterotoxin B (SEB), in buffer and complex biological matrices. The multiplexed assay displayed a sensitivity of 1.3 pg mL(-1) (BoNT/A, BoNT/B, SEB, Stx-1 and Stx-2), 3.3 pg mL(-1) (BoNT/C, BoNT/E, BoNT/F) and 8.2 pg mL(-1) (BoNT/D, ricin). All assays demonstrated high accuracy (75-120 percent recovery) and reproducibility (most coefficients of variation <20%). Quantification curves for the ten toxins were also evaluated in clinical samples (serum, plasma, nasal fluid, saliva, stool, and urine) and environmental samples (apple juice, milk and baby food) with overall minimal matrix effects. The multiplex assays were highly specific, with little cross-reactivity observed between the selected toxin antibodies. The results demonstrate a multiplex microarray that improves current immunoassay sensitivity for biological warfare agents in buffer, clinical, and environmental samples.

Oxidatively modified proteins as plasma biomarkers in breast cancer

BACKGROUND

Post-translational protein modifications (PTMs) are increased in breast tumors.

OBJECTIVE

We explored whether PTMs on proteins secreted by the breast could be detected in plasma and potentially used for the early detection of breast cancer.

METHODS

We used a custom ELISA microarray platform to measure 4-hydroxynonenal (HNE), glutathione (GSH), nitrotyrosine and halotyrosine adducts in 27 secreted proteins, for a total of 108 candidate biomarkers. Two independent sets of human plasma samples were measured, for a total of 160 samples. The results were analyzed for consistent cancer-associated changes across the two sample sets. Plasma samples for both cases and benign controls were collected at the time of tissue diagnosis after referral from a positive screen (such as mammography). The results from both studies were evaluated using ANOVA and t-tests or receiver operator curves (ROC).

RESULTS

Levels of GSH-modified ceruloplasmin and HNE-modified PDGF were significantly altered in plasma samples from cancer patients relative to benign controls. Healthy controls, which were only included in the first set of samples, were similar to the benign controls for both of these markers. A combination of three glutathionylated proteins produced the best area under the ROC curve, with a value of 76%.

CONCLUSIONS

Specific PTMs in individual proteins may be useful for distinguishing between women with breast cancer and those with benign breast disease. These oxidative changes in plasma proteins may reflect redox changes in breast cancer. Additional studies on oxidative modifications in individual proteins are warranted.

A halotyrosine antibody that detects increased protein modifications in asthma patients

Airway inflammation has a pathophysiological role in asthma. Eosinophils, which are commonly increased in asthmatic airways, express eosinophil peroxidase and thereby produce hypobromite and bromotyrosine. Bromotyrosine is believed to be a specific marker for eosinophil activity, but developing an antibody against monobromotyrosine, the predominant brominated tyrosine residue found in vivo has proven difficult. We evaluated whether a 3-bromobenozoic acid hapten antigen produced antibodies that recognized halogenated tyrosine residues. Studies with small-molecule inhibitors or brominated or chlorinated protein suggested that a mouse monoclonal antibody (BTK-94C) selectively bound free and protein mono- and dibromotyrosine and, to a lesser degree, chlorotyrosine, and thus was designated a general halotyrosine antibody. We evaluated if this antibody had potential for characterizing human asthma using an enzyme-linked immunosorbent assay (ELISA) microarray platform to examine the halogenation of 23 proteins in three independent sets of sputum samples (52 samples total). In 15 healthy control or asthmatic subjects, ICAM, PDGF and RANTES had greater proportional amounts of halogenation in asthmatic subjects and the halogenation signal was associated with the severity of exercise-induced airway hyperresponsiveness. In 17 severe asthma patients treated with placebo or mepolizumab to suppress eosinophils, drug-related decreases in halogenation were observed with p values ranging from 0.006 to 0.11 for these 3 proteins. Analysis of 20 subjects that either had neutrophilic asthma or were healthy controls demonstrated a broad increase in halotyrosine (possibly chlorotyrosine) in neutrophilic asthmatics. Overall, these results suggest that an ELISA utilizing BTK-94C could prove useful for assessing airway inflammation in asthma patients.

High-throughput, multiplexed analysis of 3-nitrotyrosine in individual proteins

Reactive nitrogen species (RNS) and reactive oxygen species (ROS) are derived as a result of inflammation and oxidative stress and can result in protein modifications. As such, these protein modifications are used as biomarkers for inflammation and oxidative stress. In addition, modifications in single-tissue-associated proteins released into blood can provide insight into the tissue localization of the inflammation or oxidative stress. We have developed an enzyme-linked immunosorbent assay antibody microarray platform to analyze the levels of 3-nitrotyrosine in specific proteins in a variety of biological samples, including human plasma and sputum. Selective-capture antibodies are used to immunoprecipitate individual proteins from samples onto isolated spots on the microarray chips. Then, a monoclonal antibody for 3-nitrotyrosine is used to detect the amount of 3-nitrotyrosine on each spot. Our studies suggest that this approach can be used to detect trace amounts of 3-nitrotyrosine in human plasma and sputum. In this paper, we describe our antibody microarray protocol for detecting 3-nitrotyrosine in specific proteins.

Photonic crystal enhanced fluorescence for early breast cancer biomarker detection

Photonic crystal surfaces offer a compelling platform for improving the sensitivity of surface-based fluorescent assays used in disease diagnostics. Through the complementary processes of photonic crystal enhanced excitation and enhanced extraction, a periodic dielectric-based nanostructured surface can simultaneously increase the electric field intensity experienced by surface-bound fluorophores and increase the collection efficiency of emitted fluorescent photons. Through the ability to inexpensively fabricate photonic crystal surfaces over substantial surface areas, they are amenable to single-use applications in biological sensing, such as disease biomarker detection in serum. In this review, we will describe the motivation for implementing high-sensitivity, multiplexed biomarker detection in the context of breast cancer diagnosis. We will summarize recent efforts to improve the detection limits of such assays though the use of photonic crystal surfaces. Reduction of detection limits is driven by low autofluorescent substrates for photonic crystal fabrication, and detection instruments that take advantage of their unique features.

Spatially selective photonic crystal enhanced fluorescence and application to background reduction for biomolecule detection assays

By combining photonic crystal label-free biosensor imaging with photonic crystal enhanced fluorescence, it is possible to selectively enhance the fluorescence emission from regions of the PC surface based upon the density of immobilized capture molecules. A label-free image of the capture molecules enables determination of optimal coupling conditions of the laser used for fluorescence imaging of the photonic crystal surface on a pixel-by-pixel basis, allowing maximization of fluorescence enhancement factor from regions incorporating a biomolecule capture spot and minimization of background autofluorescence from areas between capture spots. This capability significantly improves the contrast of enhanced fluorescent images, and when applied to an antibody protein microarray, provides a substantial advantage over conventional fluorescence microscopy. Using the new approach, we demonstrate detection limits as low as 0.97 pg/ml for a representative protein biomarker in buffer.

Smoking, COPD, and 3-nitrotyrosine levels of plasma proteins

BACKGROUND

Nitric oxide is a physiological regulator of endothelial function and hemodynamics. Oxidized products of nitric oxide can form nitrotyrosine, which is a marker of nitrative stress. Cigarette smoking decreases exhaled nitric oxide, and the underlying mechanism may be important in the cardiovascular toxicity of smoking. Even so, it is unclear if this effect results from decreased nitric oxide production or increased oxidative degradation of nitric oxide to reactive nitrating species. These two processes would be expected to have opposite effects on nitrotyrosine levels, a marker of nitrative stress.

OBJECTIVE

In this study, we evaluated associations of cigarette smoking and chronic obstructive pulmonary disease (COPD) with nitrotyrosine modifications of specific plasma proteins to gain insight into the processes regulating nitrotyrosine formation.

METHODS

A custom antibody microarray platform was developed to analyze the levels of 3-nitrotyrosine modifications on 24 proteins in plasma. In a cross-sectional study, plasma samples from 458 individuals were analyzed.

RESULTS

Average nitrotyrosine levels in plasma proteins were consistently lower in smokers and former smokers than in never smokers but increased in smokers with COPD compared with smokers who had normal lung-function tests.

CONCLUSIONS

Smoking is associated with a broad decrease in 3-nitrotyrosine levels of plasma proteins, consistent with an inhibitory effect of cigarette smoke on endothelial nitric oxide production. In contrast, we observed higher nitrotyrosine levels in smokers with COPD than in smokers without COPD. This finding is consistent with increased nitration associated with inflammatory processes. This study provides insight into a mechanism through which smoking could induce endothelial dysfunction and increase the risk of cardiovascular disease.

Plasma biomarker profiles differ depending on breast cancer subtype but RANTES is consistently increased

BACKGROUND

Current biomarkers for breast cancer have little potential for detection. We determined whether breast cancer subtypes influence circulating protein biomarkers.

METHODS

A sandwich ELISA microarray platform was used to evaluate 23 candidate biomarkers in plasma samples that were obtained from subjects with either benign breast disease or invasive breast cancer. All plasma samples were collected at the time of biopsy, after a referral due to a suspicious screen (e.g., mammography). Cancer samples were evaluated on the basis of breast cancer subtypes, as defined by the HER2 and estrogen receptor statuses.

RESULTS

Ten proteins were statistically altered in at least one breast cancer subtype, including four epidermal growth factor receptor ligands, two matrix metalloproteases, two cytokines, and two angiogenic factors. Only one cytokine, RANTES, was significantly increased (P < 0.01 for each analysis) in all four subtypes, with areas under the curve (AUC) for receiver operating characteristic values that ranged from 0.76 to 0.82, depending on cancer subtype. The best AUC values were observed for analyses that combined data from multiple biomarkers, with values ranging from 0.70 to 0.99, depending on the cancer subtype. Although the results for RANTES are consistent with previous publications, the multi-assay results need to be validated in independent sample sets.

CONCLUSIONS

Different breast cancer subtypes produce distinct biomarker profiles, and circulating protein biomarkers have potential to differentiate between true- and false-positive screens for breast cancer.

IMPACT

Subtype-specific biomarker panels may be useful for detecting breast cancer or as an adjunct assay to improve the accuracy of current screening methods.

Development of a fibrinogen-specific sandwich enzyme-linked immunosorbent assay microarray assay for distinguishing between blood plasma and serum samples

We have developed a fibrinogen-specific sandwich enzyme-linked immunosorbent assay (ELISA) microarray assay for use in qualitatively distinguishing between blood plasma and serum samples. Three capture antibodies (49D2, HPA001900, and F8512) were evaluated in conjunction with 1D6 as the detection antibody. The data show that 49D2 and (to a lesser extent) F8512 successfully identify previously unknown plasma and serum samples based on approximately a 28-fold difference in signal intensity between the sample types. This assay has utility in rapidly identifying previously archived clinical samples with incomplete annotation in a high-throughput manner prior to proteomic analyses.

Application of photonic crystal enhanced fluorescence to cancer biomarker microarrays

We report on the use of photonic crystal surfaces as a high-sensitivity platform for detection of a panel of cancer biomarkers in a protein microarray format. The photonic crystal surface is designed to provide an optical resonance at the excitation wavelength of cyanine-5 (Cy5), thus providing an increase in fluorescent intensity for Cy5-labeled analytes measured with a confocal microarray scanner, compared to a glass surface. The sandwich enzyme-linked immunosorbent assay (ELISA) is undertaken on a microarray platform to undertake a simultaneous, multiplex analysis of 24 antigens on a single chip. Our results show that the resonant excitation effect increases the signal-to-noise ratio by 3.8- to 6.6-fold, resulting in a decrease in detection limits of 6-89%, with the exact enhancement dependent upon the antibody-antigen interaction. Dose-response characterization of the photonic crystal antibody microarrays shows the capability to detect common cancer biomarkers in the <2 pg/mL concentration range within a mixed sample.

Protein secretion in human mammary epithelial cells following HER1 receptor activation: influence of HER2 and HER3 expression

Background

Protein secretion by mammary cells results in autocrine and paracrine signaling that defines cell growth, migration and the extracellular environment. Even so, we have a limited understanding of the cellular processes that regulate protein secretion.

Methods

In this study, we utilize human epithelial mammary cell (HMEC) lines that were engineered to express different levels of HER1, HER2 and HER3. Using an ELISA microarray platform, we evaluate the effects of epidermal growth factor family receptor (HER) expression on protein secretion in the HMEC lines upon initiation of HER1 receptor activation. The secreted proteins include three HER1 ligands, interleukins 1α and 18, RANTES, vascular-endothelial and platelet-derived growth factors, matrix metalloproteases 1, 2 and 9, and the extracellular portion of the HER1 and HER2 proteins. In addition, we investigate whether MAPK/Erk and PI3K/Akt signaling regulate protein secretion in these cell lines and if so, whether the involvement of HER2 or HER3 receptor alters their response to MAPK/Erk and PI3K/Akt signal pathway inhibition in terms of protein secretion.

Results

Differential expression of HER2 and HER3 receptors alters the secretion of a variety of growth factors, cytokines, and proteases. Some alterations in protein secretion are still observed when MAPK/Erk or PI3K/Akt signaling is inhibited.

Conclusion

This study suggests that HER overexpression orchestrates broad changes in the tumor microenvironment by altering the secretion of a diverse variety of biologically active proteins.

Analysis of high-throughput ELISA microarray data

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).