Quiescin Sulfhydryl Oxidase from <i>Trypanosoma brucei</i>: Catalytic Activity and Mechanism of a QSOX Family Member with a Single Thioredoxin Domain

Quiescin sulfhydryl oxidase (QSOX) flavoenzymes catalyze the direct, facile, insertion of disulfide bonds into reduced unfolded proteins with the reduction of oxygen to hydrogen peroxide. To date, only QSOXs from vertebrates have been characterized enzymatically. These metazoan sulfhydryl oxidases have four recognizable domains: a redox-active thioredoxin (Trx) domain containing the first of three CxxC motifs (CI−CII), a second Trx domain with no obvious redox-active disulfide, a helix-rich domain, and then an Erv/ALR domain. This last domain contains the FAD moiety, a proximal CIII−CIV disulfide, and a third CxxC of unknown function (CV−CVI). Plant and protist QSOXs lack the second Trx domain but otherwise appear to contain the same complement of redox centers. This work presents the first characterization of a single-Trx QSOX. Trypanosoma brucei QSOX was expressed in Escherichia coli using a synthetic gene and found to be a stable, monomeric, FAD-containing protein. Although evidently lacking an entire domain, TbQSOX shows catalytic activity and substrate specificity similar to the vertebrate QSOXs examined previously. Unfolded reduced proteins are more than 200-fold more effective substrates on a per thiol basis than glutathione and some 10-fold better than the parasite bisglutathione analogue, trypanothione. These data are consistent with a role for the protist QSOX in oxidative protein folding. Site-directed mutagenesis of each of the six cysteine residues (to serines) shows that the CxxC motif in the single-Trx domain is crucial for efficient catalysis of the oxidation of both reduced RNase and the model substrate dithiothreitol. As expected, the proximal disulfide CIII−CIV, which interacts with the flavin, is catalytically crucial. However, as observed with human QSOX1, the third CxxC motif shows no obvious catalytic role during the in vitro oxidation of reduced RNase or dithiothreitol. Pre-steady-state kinetics demonstrates that turnover in TbQSOX is limited by an internal redox step leading to 2-electron reduction of the FAD cofactor. In sum, the single-Trx domain QSOX studied here shows a striking similarity in enzymatic behavior to its double-Trx metazoan counterparts

Grouping of carbonaceous nanomaterials based on association of patterns of inflammatory markers in BAL fluid with adverse outcomes in lungs

Carbonaceous nanomaterials (CNMs) are universally being used to make commodities, as they present unique opportunities for development and innovation in the fields of engineering, biotechnology, etc. As technology advances to incorporate CNMs in industry, the potential exposures associated with these particles also increase. CNMs have been found to be associated with substantial pulmonary toxicity, including inflammation, fibrosis, and/or granuloma formation in animal models. This study attempts to categorize the toxicity profiles of various carbon allotropes, in particular, carbon black, different multi-walled carbon nanotubes, graphene-based materials, and their derivatives. Statistical and machine learning-based approaches were used to identify groups of CNMs with similar pulmonary toxicity responses from a panel of proteins measured in bronchoalveolar lavage (BAL) fluid samples and with similar pathological outcomes in the lungs. Thus, grouped particles, based on their pulmonary toxicity profiles, were used to select a small set of proteins that could potentially identify and discriminate between the toxicity profiles associated within each group. Specifically, MDC/CCL22 and MIP-3β/CCL19 were identified as common protein markers associated with both toxicologically distinct groups of CNMs. In addition, the persistent expression of other selected protein markers in BAL fluid from each group suggested their ability to predict toxicity in the lungs, i.e. fibrosis and microgranuloma formation. The advantages of such approaches can have positive implications for further research in toxicity profiling.</p

Nonperturbative Chemical Modification of Graphene for Protein Micropatterning

Graphene’s extraordinary physical properties and its planar geometry make it an ideal candidate for a wide array of applications, many of which require controlled chemical modification and the spatial organization of molecules on its surface. In particular, the ability to functionalize and micropattern graphene with proteins is relevant to bioscience applications such as biomolecular sensors, single-cell sensors, and tissue engineering. We report a general strategy for the noncovalent chemical modification of epitaxial graphene for protein immobilization and micropatterning. We show that bifunctional molecule pyrenebutanoic acid-succinimidyl ester (PYR-NHS), composed of the hydrophobic pyrene and the reactive succinimide ester group, binds to graphene noncovalently but irreversibly. We investigate whether the chemical treatment perturbs the electronic band structure of graphene using X-ray photoemission (XPS) and Raman spectroscopy. Our results show that the sp2 hybridization remains intact and that the π band maintains its characteristic Lorentzian shape in the Raman spectra. The modified graphene surfaces, which bind specifically to amines in proteins, are micropatterned with arrays of fluorescently labeled proteins that are relevant to glucose sensors (glucose oxidase) and cell sensor and tissue engineering applications (laminin)

Fabricating Nanoscale Chemical Gradients with ThermoChemical NanoLithography

Production of chemical concentration gradients on the submicrometer scale remains a formidable challenge, despite the broad range of potential applications and their ubiquity throughout nature. We present a strategy to quantitatively prescribe spatial variations in functional group concentration using ThermoChemical NanoLithography (TCNL). The approach uses a heated cantilever to drive a localized nanoscale chemical reaction at an interface, where a reactant is transformed into a product. We show using friction force microscopy that localized gradients in the product concentration have a spatial resolution of ∼20 nm where the entire concentration profile is confined to sub-180 nm. To gain quantitative control over the concentration, we introduce a chemical kinetics model of the thermally driven nanoreaction that shows excellent agreement with experiments. The comparison provides a calibration of the nonlinear dependence of product concentration versus temperature, which we use to design two-dimensional temperature maps encoding the prescription for linear and nonlinear gradients. The resultant chemical nanopatterns show high fidelity to the user-defined patterns, including the ability to realize complex chemical patterns with arbitrary variations in peak concentration with a spatial resolution of 180 nm or better. While this work focuses on producing chemical gradients of amine groups, other functionalities are a straightforward modification. We envision that using the basic scheme introduced here, quantitative TCNL will be capable of patterning gradients of other exploitable physical or chemical properties such as fluorescence in conjugated polymers and conductivity in graphene. The access to submicrometer chemical concentration and gradient patterning provides a new dimension of control for nanolithography

Quantitative Profiling of Protein S‑Glutathionylation Reveals Redox-Dependent Regulation of Macrophage Function during Nanoparticle-Induced Oxidative Stress

Engineered nanoparticles (ENPs) are increasingly utilized for commercial and medical applications; thus, understanding their potential adverse effects is an important societal issue. Herein, we investigated protein S-glutathionylation (SSG) as an underlying regulatory mechanism by which ENPs may alter macrophage innate immune functions, using a quantitative redox proteomics approach for site-specific measurement of SSG modifications. Three high-volume production ENPs (SiO₂, Fe₃O₄, and CoO) were selected as representatives which induce low, moderate, and high propensity, respectively, to stimulate cellular reactive oxygen species (ROS) and disrupt macrophage function. The SSG modifications identified highlighted a broad set of redox sensitive proteins and specific Cys residues which correlated well with the overall level of cellular redox stress and impairment of macrophage phagocytic function (CoO > Fe₃O₄ ≫ SiO₂). Moreover, our data revealed pathway-specific differences in susceptibility to SSG between ENPs which induce moderate <i>versus</i> high levels of ROS. Pathways regulating protein translation and protein stability indicative of ER stress responses and proteins involved in phagocytosis were among the most sensitive to SSG in response to ENPs that induce subcytoxic levels of redox stress. At higher levels of redox stress, the pattern of SSG modifications displayed reduced specificity and a broader set pathways involving classical stress responses and mitochondrial energetics (<i>e.g.,</i> glycolysis) associated with apoptotic mechanisms. An important role for SSG in regulation of macrophage innate immune function was also confirmed by RNA silencing of glutaredoxin, a major enzyme which reverses SSG modifications. Our results provide unique insights into the protein signatures and pathways that serve as ROS sensors and may facilitate cellular adaption to ENPs, <i>versus</i> intracellular targets of ENP-induced oxidative stress that are linked to irreversible cell outcomes

The IRE1α/XBP1s Pathway Is Essential for the Glucose Response and Protection of β Cells

<div><p>Although glucose uniquely stimulates proinsulin biosynthesis in β cells, surprisingly little is known of the underlying mechanism(s). Here, we demonstrate that glucose activates the unfolded protein response transducer inositol-requiring enzyme 1 alpha (IRE1α) to initiate X-box-binding protein 1 (<i>Xbp1</i>) mRNA splicing in adult primary β cells. Using mRNA sequencing (mRNA-Seq), we show that unconventional <i>Xbp1</i> mRNA splicing is required to increase and decrease the expression of several hundred mRNAs encoding functions that expand the protein secretory capacity for increased insulin production and protect from oxidative damage, respectively. At 2 wk after tamoxifen-mediated <i>Ire1α</i> deletion, mice develop hyperglycemia and hypoinsulinemia, due to defective β cell function that was exacerbated upon feeding and glucose stimulation. Although previous reports suggest IRE1α degrades insulin mRNAs, <i>Ire1α</i> deletion did not alter insulin mRNA expression either in the presence or absence of glucose stimulation. Instead, β cell failure upon <i>Ire1α</i> deletion was primarily due to reduced proinsulin mRNA translation primarily because of defective glucose-stimulated induction of a dozen genes required for the signal recognition particle (SRP), SRP receptors, the translocon, the signal peptidase complex, and over 100 other genes with many other intracellular functions. In contrast, <i>Ire1α</i> deletion in β cells increased the expression of over 300 mRNAs encoding functions that cause inflammation and oxidative stress, yet only a few of these accumulated during high glucose. Antioxidant treatment significantly reduced glucose intolerance and markers of inflammation and oxidative stress in mice with β cell-specific <i>Ire1α</i> deletion. The results demonstrate that glucose activates IRE1α-mediated <i>Xbp1</i> splicing to expand the secretory capacity of the β cell for increased proinsulin synthesis and to limit oxidative stress that leads to β cell failure.</p></div

mRNA sequencing identifies IRE1α- and glucose-dependent mRNAs in islets.

<p>(A) mRNA-Seq data on β cell-specific mRNAs. The results show no significant change to INS1 or INS2 in the <i>KO</i>^{<i>Fe/-; Cre</i>} samples, while MAFA, GCG, and PC5 are increased by deletion ([<i>n</i> = 5], [18 mM <i>KO</i>^{<i>Fe/-; Cre</i>}, <i>p</i>-values ≤ 0.05]). mRNA-Seq expression fold changes were normalized relative to the 6 mM <i>WT</i>^<i>Fe/+</i> islet context. (B) Four-way Venn diagrams of <i>WT</i>^<i>Fe/+</i> versus <i>KO</i>^{<i>Fe/-; Cre</i>} islets during 6 mM versus 1 8mM glucose exposur<i>e</i> for 72 h. <i>Ire1α</i>-dependent mRNAs are in bold italics, while those also dependent on high glucose are in bold, italicized, and underlined font. At the center, bar graphs representing the <i>Ire1α</i>- and glucose-dependent trends of interest are labeled “Induction” and “Repression.” (C) Combined <b>DAVID</b> (the Database for Annotation, Visualization and Integrated Discovery) and “ConceptGen” GO analysis of <i>Ire1α-</i> and glucose-dependent mRNAs. Categories shown are specifically found in the genotype, while the shared categories have been omitted for simplicity, although no single mRNA was common between the groups. (D) Mass spectrometry of murine islets infected with <i>Ad-IREα-K907A (Ad-ΔR)</i> versus <i>Ad-β-Galactosidase</i> (<i>β-Gal</i>). Proteins with ≥5 unique peptides detected per protein increased or decreased upon infection in triplicate were analyzed for GO using ConceptGen and DAVID web resources (<i>n</i> = 3). The proteins shown (Fig 3D) exhibit the same expression dependence for IRE1α as measured by mRNA-Seq (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002277#pbio.1002277.s002" target="_blank">S2 Data</a>).</p

Tam-induced <i>Ire1α</i> deletion in adult β cells reduces proinsulin synthesis, insulin content, and insulin secretion, without altering insulin mRNA levels.

<p>(A) Blood glucose levels for 16-wk-old male mice following 4 h of fasting with increasing weeks post-Tam. Respectively for 4, 8, and 20 wk post-Tam ([<i>p</i> = 0.042, 0.009, 0.031], [<i>WT</i>^<i>Fe/+</i><i>n</i> = 8, <i>KO</i>^{<i>Fe/-; Cre</i>}<i>n</i> = 10]). (B) Glucose tolerance tests (GTTs) performed on 16-wk-old male mice at 6 wk post-Tam and the areas under the curves 6 wk post-Tam. The values for statistical significance in Fig 1A and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002277#pbio.1002277.s005" target="_blank">S1A Fig</a> were calculated from areas under the GTT curves. The data and statistics for the GTTs and all other data except when indicated are within <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002277#pbio.1002277.s001" target="_blank">S1 Data</a>. ([<i>WT</i>^<i>Fe/+</i>, <i>Het-I</i>^{<i>Fe/+; Cre</i>}, <i>Het-B</i>^<i>Fe/-</i> and <i>KO</i>^{<i>Fe/-; Cre</i>}<i>n</i> = 8], [<i>p</i> = 1.408 x 10⁻⁷, <i>WT</i>^<i>Fe/+</i> versus <i>KO</i>^{Fe/-; Cre}]). (C) Serum insulin levels in mice 6 wk post-Tam: fed, 4 h fasted, 30 and 90 min after refeeding ([<i>n</i> = 4, all groups], student’s <i>t</i> test for significance for <i>WT</i>^<i>Fe/+</i> versus <i>KO</i>^{<i>Fe/-; Cre</i>} [<i>p</i> = 0.044]). (D) Immunofluorescence microscopy of islets co-stained for insulin (red), proinsulin (green), and DAPI (blue); see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002277#pbio.1002277.s007" target="_blank">S3B Fig</a> for additional examples. Scale bar, 100 μm. (E) Percent islet areas were determined on 6-wk post-Tam pancreas by outlining 138, 153, 234, and 297 cross sections from 9, 9, 11, and 14 mice <i>WT</i>^<i>Fe/+</i>, <i>Het-I</i>^{<i>Fe/+; Cre</i>}, and <i>KO</i>^{<i>Fe/-; Cre</i>} groups, respectively. (F and G) Insulin and proinsulin ELISAs of acid ethanol extracts from 6 wk post-Tam mouse pancreas (<i>WT</i>^<i>Fe/+</i> versus <i>KO</i>^{<i>Fe/-; Cre</i>}; [insulin, <i>p</i> = 0.039, proinsulin, <i>p</i> = 0.031], [<i>n</i> = 5, all groups]). (H) Individual mouse proinsulin/insulin ratios were determined and averaged ([<i>p</i> = 0.009], [<i>n</i> = 5]). (I) Islets were shifted from 4 mM to 25 mM glucose for 30 min in [³⁵S]-Cys/Met in order to determine the synthesis rate during high glucose by antiproinsulin immunoprecipitation IP ([<i>n</i> = 3] for <i>WT</i>^<i>Fe/+</i>, <i>Het-I</i>^{<i>Fe/+; Cre</i>}, and <i>KO</i>^{<i>Fe/-; Cre</i>}), ([<i>n</i> = 6] for <i>+/+</i> infected with <i>Ad-Cre</i> versus <i>Ad-ΔR</i> (<i>p</i> = 0.019)]. Since limiting amounts of a homemade proinsulin antibody was used for the first five lanes, the Ad experiments used a commercial antibody that produced consistent results. (J) Real-time PCR (quantitative real-time PCR [qRT-PCR]) of total RNA isolated from islets at 6 wk post-Tam ([<i>n</i> = 5], [<i>p</i> = 0.022**, 0.039*, and 0.047*]) for <i>Ire1α</i> deletion-specific, <i>Xbp1</i> spliced-specific, and <i>Mafa</i> mRNAs, respectively.</p

<i>KO</i> islets exhibit ER stress.

<p>(A) qRT-PCR of UPR genes in islets isolated 6 wk post-Tam and incubated in 11 mM glucose 16 h ([<i>n</i> = 5], [<i>p</i> ≤ 0.05]). (B) Immunofluorescence microscopy of pancreas sections stained for KDEL (BIP and GRP94) (green), the plasma membrane protein GLUT2 (red), and nuclei DAPI (blue). Overlap of red/green channels represents defective compartmentalization that was found to be increased in the <i>KO</i>^{<i>Fe/-; Cre</i>} as shown in yellow. Scale bars, 400x = 50 μm, 1,000x = 10 μm, 5,180x = 2 μm and 10,500x = 1 μM. Additional examples are shown in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002277#pbio.1002277.s007" target="_blank">S3B Fig</a>. (C) EM of adult mouse (16 wk old) islets and their β cells from mice 2 wk post-Tam. Scale bars, both panels, 1 μm. Distended mitochondria are outlined with yellow dashes. (D) Conventional PCR flanking the 26 nt intron in <i>Xbp1</i> mRNA spliced by IRE1α from the islet complementary DNAs (cDNAs) used for mRNA-Seq analysis, 6 mM versus 18 mM glucose. Results representative of <i>n</i> = 5 per genotype. (E) Global heatmap for the ~22,000 mRNAs detected by mRNA-Seq for 18 mM <i>KO</i>^{<i>Fe/-; Cre</i>} & <i>WT</i>^<i>Fe/+</i> samples; green and red indicate increased and decreased expression. The blue box indicates genes with inverse expression dependent on IRE1α and high glucose.</p

<i>KO</i> islets accumulate oxidative stress, inflammation, and fibrosis.

<p>(A) mRNA-Seq expression values for 25/368 of the mRNAs identified by Venn analysis (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002277#pbio.1002277.g003" target="_blank">Fig 3C</a>; right panel, underlined) that are reduced by <i>Ire1α</i> because of glucose that accumulates in the <i>KO</i>^{<i>Fe/-; Cre</i>} ([<i>n</i> = 5], [<i>p</i>-values ≤ 0.05]). (B) Oxidized lipid (hydroxyl-octadecadienoic acids, HODEs) from islets of the indicated genotypes infected with <i>Ad-Cre Ad-GFP</i> or no virus control ([<i>n</i> = 2; controls versus <i>n</i> = 3; <i>Ad-Cre</i>], [<i>p</i> = 0.00434]). (C) Antinitrotyrosine immunohistochemistry (IHC) of islets from 8-mo-old <i>WT</i>^<i>Fe/Fe</i> and <i>KO</i>^{<i>Fe/Fe; Cre</i>} mice 15 wk post-Tam with or without BHA diet for 3 wk. (Scale bar, 50 μm) (<i>WT</i>^<i>Fe/Fe</i> [<i>n</i> = 4 with BHA], [<i>n</i> = 5 regular chow]), (<i>KO</i>^{<i>Fe/Fe; Cre</i>} [<i>n</i> = 5 with BHA], [<i>n</i> = 6 regular chow]). (<i>p</i> = 0.00698; <i>WT</i>^<i>Fe/Fe</i> versus <i>WT</i>^<i>Fe/Fe</i> with BHA), (<i>p</i> = 0.04018; <i>WT</i>^<i>Fe/Fe</i> versus <i>KO</i>^{<i>Fe/Fe; Cre</i>}) and (<i>p</i> = 0.04420; <i>KO</i>^{<i>Fe/Fe; Cre</i>} versus <i>KO</i>^{<i>Fe/Fe; Cre</i>} with BHA). (D) Masson’s trichrome stain (blue) for collagens. Results demonstrate increased staining surrounding <i>KO</i>^{<i>Fe/Fe; Cre</i>} islets with haemotoxylin (red) and eosin (black) co-stains. Quantification of percent strong collagen stain is shown below the images. Scale bar, 50 μm. (<i>WT</i>^<i>Fe/Fe</i> [<i>n</i> = 4 with BHA], [<i>n</i> = 5 regular chow]), (<i>KO</i>^{<i>Fe/Fe; Cre</i>} [<i>n</i> = 5 with BHA], [<i>n</i> = 6 without BHA]). Percent strong collagen stain significance for <i>WT</i>^<i>Fe/Fe</i> without BHA versus <i>KO</i>^{<i>Fe/Fe; Cre</i>} without BHA <i>p</i> = 0.01049). (E) 8-mo-old male mice carrying the doubly floxed allele (<i>Ire1α</i>^<i>Fe/Fe</i><i>)</i> with and without RIP-Cre 12 wk post-Tam had their pre-BHA GTTs taken, and then half were fed the antioxidant BHA supplemented chow diet for 3 wk or not before examining the mice by GTT again. (<i>WT</i>^<i>Fe/Fe</i> [<i>n</i> = 11 with BHA], [<i>n</i> = 12 regular chow], [<i>p</i> = 0.035]), (<i>KO</i>^{<i>Fe/Fe; Cre</i>} [<i>n</i> = 18 with BHA], [<i>n</i> = 16 without BHA], [<i>p</i> = 0.041]). <i>P</i>-values were calculated by one-tailed student’s <i>t</i> test comparison of the areas under the GTT curves for the biological replicates of control group <i>WT</i>^<i>Fe/Fe</i> versus the Tam-induced <i>KO</i>^{<i>Fe/Fe; Cre</i>} group.</p