34 research outputs found

    Selective Affinity Enrichment of Nitrotyrosine-Containing Peptides for Quantitative Analysis in Complex Samples

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    Protein tyrosine nitration by oxidative and nitrate stress is important in the pathogenesis of many inflammatory or aging-related diseases. Mass spectrometry analysis of protein nitrotyrosine is very challenging because the non-nitrated peptides suppress the signals of the low-abundance nitrotyrosine (NT) peptides. No validated methods for enrichment of NT-peptides are currently available. Here we report an immunoaffinity enrichment of NT-peptides for proteomics analysis. The effectiveness of this approach was evaluated using nitrated protein standards and whole-cell lysates in vitro. A total of 1881 NT sites were identified from a nitrated whole-cell extract, indicating that this immunoaffinity-MS method is a valid approach for the enrichment of NT-peptides, and provides a significant advance for characterizing the nitrotyrosine proteome. We noted that this method had higher affinity to peptides with N-terminal nitrotyrosine relative to peptides with other nitrotyrosine locations, which raises the need for future study to develop a pan-specific nitrotyrosine antibody for unbiased, proteome-wide analysis of tyrosine nitration. We applied this method to quantify the changes in protein tyrosine nitration in mouse lungs after intranasal poly­(I:C) treatment and quantified 237 NT sites. This result indicates that the immunoaffinity-MS method can be used for quantitative analysis of protein nitrotyrosines in complex samples

    Observed and simulated dsRNA dose-dependence curves in hAECs.

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    <p>Experimental measurements, black circles with empirical 95% confidence intervals based on triplicate measurements; means of 100 simulated single-cell trajectories, blue lines; 95% confidence bands based on simulations, red lines. Two types of simulations presented (A) under extrinsic noise, (B) under extrinsic and intrinsic noise. Horizontal axis: dsRNA dose (µg); vertical axis: number of molecules.</p

    Model Estimation.

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    <p>Time series of mRNA levels of TNFAIP3, IκBα, RIG-I and IFNβ following stimulation by 4 µg dsRNA in hAECs cells for 0, 0.5, 1, 2, 4, and 6 hr. Gene expression estimated using Q-RT-PCR was as described previously <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0093396#pone.0093396-Liu1" target="_blank">[10]</a>. Experimental measurements, black circles with empirical 95% confidence intervals based on triplicate measurements; means of 100 simulated single-cell trajectories, blue lines; 95% confidence bands based on simulations, red lines. Two types of simulations presented (A) under extrinsic noise, (B) under extrinsic and intrinsic noise. Horizontal axis - time (hr); vertical axis - number of molecules. Absolute values of experimental measurements scaled to simulation data (see the text for details).</p

    Single cell nucleus/cytoplasm ratios under 50 µg of dsRNA stimulation (IRF3, red channel).

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    <p>Strawberry -IRF3 hAECs were electroporated with different dosages of synthetic dsRNA analog Poly IC and dynamic live cell imaging was performed. Time is in hr. Green trend lines are third-order polynomials, fitted using least-squares minimization. Upper row: Raw time series. Middle row: Detrended time series. Bottom row: Fourier periodograms. Columns 1–5: Observed single cells.</p

    Single cell nucleus/cytoplasm ratios under 5 µg of dsRNA stimulation (IRF3, red channel fluorescence).

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    <p>Strawberry -IRF3 hAECs were electroporated with different dosages of synthetic dsRNA analog Poly IC and dynamic live cell imaging was performed. Time presented in hr. Green trend lines are third-order polynomials, fitted using least-squares minimization. Upper row: Raw time series. Middle row: Detrended time series. Bottom row: Fourier periodograms. Columns 1–4: Observed single cells. Column 5: Two simulated cells.</p

    Model Validation.

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    <p>Gene knockdowns using siRNA specific to target genes in hAECs. The experiments were carried out using target gene-specific siRNA and the control nonspecific siRNA, which were reverse-transfected into hAECs at the concentration of 100 nM. The data presented are the corresponding mRNA levels at 6 hr after electroporation (fold change, in logarithmic scale). (A), knockdown of RelA, IRF3, RIG-I and IKKγ. (B), knockdown of TNFAIP3/A20, NFKBIA/IκBα, ISG56 and IFNβ. The mRNA levels of the indicated genes (at top) were determined by RT-PCR. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0093396#s3" target="_blank">Results</a> were represented as normalized fold change of expression compared to control non dsRNA-induced cells transfected with scrambled (non-target control) siRNA. Gray bars, experiment (dark, no dsRNA stimulation; light, 4 µg dsRNA); red lines, model simulation. 95% confidence intervals of experimental data (based on 3 replicates) are distorted by the logarithmic scale. In linear scale, the relative error rate is approximately 10%. Please notice that in IFNβ and ISG56 charts, the model values at time 0 are equal to 0, which is impossible to depict on the log scale. (C), Effect of RIG-I knockdown on NF-κB and IRF3 dependent gene expression. hAECs were transfected with siRNA to RIG-I or control siRNA (Con). Left panel, effect of RIG-I siRNA on RIG-I expression. Note that dsRNA induced RIG-I expression is largely inhibited in hAECs transfected with RIG-I siRNA. Middle panel, effect of RIG-I knockdown on NF-κB-dependent TNFAIP3/A20 gene expression. dsRNA induces TNFAIP3/A20 expression in RIG-I knockdown cells. Right panel, effect of RIG-I knockdown on IRF3-dependent gene expression. RIG-I knockdown significantly blunts IRF3-dependent ISG56 expression. We conclude from these data that RIG-I is primarily coupled to IRF3 signaling in hAECs. (D), Effect on RIG-I expression in murine MEF cells with both IRF3 and IRF7 genes knocked down. RIG-I is down-regulated, which suggests IRF7 may play a key role in RIG-I up-regulation. Compare with RIG-I results in Panel A where the IRF3 knock-down does not seem to down-regulate RIG-I expression.</p

    Model Couplings.

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    <p>Simplified schematic of the IRF3-NF-κB model. Only dsRNA, proteins (in the cytoplasm) and genes (in the nucleus) are shown. Solid green lines on the top denote direct chemical binding. Green dotted lines denote activation. Vertical thick colored arrows denote translocation of activated transcription factors into the nucleus. Red dotted lines denote inhibition. Horizontal solid black arrows in the nucleus denote gene transcription, with plus or minus signs denoting activation or repression, respectively. Transcripts and inactive forms of the proteins are omitted for simplicity.</p
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