In utero exposure to low doses of environmental pollutants disrupts fetal ovarian development in sheep

Epidemiological studies of the impact of environmental chemicals on reproductive health demonstrate consequences of exposure but establishing causative links requires animal models using ‘real life’ in utero exposures. We aimed to determine whether prolonged, low-dose, exposure of pregnant sheep to a mixture of environmental chemicals affects fetal ovarian development. Exposure of treated ewes (n = 7) to pollutants was maximized by surface application of processed sewage sludge to pasture. Control ewes (n = 10) were reared on pasture treated with inorganic fertilizer. Ovaries and blood were collected from fetuses (n = 15 control and n = 8 treated) on Day 110 of gestation for investigation of fetal endocrinology, ovarian follicle/oocyte numbers and ovarian proteome. Treated fetuses were 14% lighter than controls but fetal ovary weights were unchanged. Prolactin (48% lower) was the only measured hormone significantly affected by treatment. Treatment reduced numbers of growth differentiation factor (GDF9) and induced myeloid leukaemia cell differentiation protein (MCL1) positive oocytes by 25–26% and increased pro-apoptotic BAX by 65% and 42% of protein spots in the treated ovarian proteome were differently expressed compared with controls. Nineteen spots were identified and included proteins involved in gene expression/transcription, protein synthesis, phosphorylation and receptor activity. Fetal exposure to environmental chemicals, via the mother, significantly perturbs fetal ovarian development. If such effects are replicated in humans, premature menopause could be an outcome.
Introduction
Exposure to environmental compounds (ECs) may alter female reproductive tissues and thus affect the ability of human couples to conceive and maintain a healthy pregnancy (Hruska et al., 2000). ECs include endocrine disrupting compounds [EDCs, e.g. dioxins, polychlorinated biphenyls (PCB) and organochlorine pesticides] that have been/are used extensively in manufacturing and agriculture. ECs are found ubiquitously within the environment, together with heavy metal pollutants. Human exposure occurs through a variety of routes including the consumption of meat and dairy products, ingestion of water, absorption through the skin and inhalation. The concentrations of ECs within human tissues and the mechanisms through which they elicit effects on reproductive tissues are not well understood. Studies conducted in a variety of animal models demonstrate that the female fetus is particularly sensitive to small endocrine changes (Lovekamp-Swan and Davis, 2003; Henley and Korach, 2006) that have detrimental effects on reproductive function (Miller et al., 2004; Uzumcu and Zachow, 2007). There is uncertainty as to whether women’s fertility and reproductive health have deteriorated or whether the link between exposure to ECs and increased incidence of breast cancer, precocious puberty, premature menopause and decreased fertility is valid (Sharara et al., 1998; Hruska et al., 2000). Nevertheless, the importance of developmental disturbance in disease aetiology is increasingly evident (Heindel, 2006). Determining the incidence of reproductive problems in women (15–20% of couples have difficulty conceiving) is confounded by diagnostic, social (e.g. increasing age of women first trying to conceive) and obesity issues (Evers, 2002; Sharpe and Franks, 2002) which complicates linking changes in reproductive function with EC exposure (Akkina et al., 2004; Cesario and Hughes, 2007). Similarly, although the incidence of breast cancer is clearly rising and has a strong links with environmental factors and in utero exposures (Kortenkamp, 2006), there is no general increase in ovarian cancer (Bray et al., 2005). Two conclusions arise from the literature: first, that the development of the female fetus or embryo can be perturbed by exposure to ECs and, second, that the evidence for population trends in humans is mixed and often inconclusive.
Human tissues, including the maternal-fetal unit and maternal tissues during gestation, contain levels of ECs that are associated with many in utero effects (e.g. Ikezuki et al., 2002; Younglai et al., 2002; Tsutsumi, 2005; Barr et al., 2007; Chao et al., 2007; Huang et al., 2007; Thundiyil et al., 2007). However, the lack of robust human exposure-phenotype linkage data and multi-factorial effects on reproductive trends hampers our ability to test the hypothesis that in utero exposure to environmental chemicals damages female reproductive development (Foster, 2003). Many ECs have the potential to perturb development (Tabb and Blumberg, 2006; Watson et al., 2007) and epidemiological studies (Toft et al., 2004) suggest that there is a need to study the effects of EC exposure in relevant animal models at real-world rates of exposure, focusing on likely ‘sensitive’ components and mechanisms of relevant reproductive circuits. Most studies into effects of ECs have focused on rodent models, using single compounds, administered for short periods, often at pharmacological doses. Although essential to understanding of the mechanisms though which such compounds act, these studies are of limited value in the assessment of risks to human developmental health because the patterns of experimental exposure are not representative of normal human exposure. Thus an animal model using a prolonged, ‘real-life’ (defined as exposure through natural routes, not via specific application, such as injection), in-utero, pattern of EC exposure will be better able to indicate likely effects on humans.
An ovine model in which pregnant ewes are exposed to the complex mix of ECs and heavy metals contained in human sewage sludge, following its application to pasture as a fertilizer, is characterized by defects in fetal development (Paul et al., 2005). To determine which chemical classes might be involved in these effects, we measured levels of seven heavy metals, the di(2-ethylhexyl) phthalate (DEHP), nonyl phenol and seven polychlorinated biphenyl (PCB) congeners in tissues of exposed fetuses/offspring and found concentrations of Cu, Pb, Zn and DEHP to be significantly altered (Rhind et al., 2002, 2005a,b, 2007a,b). Sewage sludge is a relevant source of a chemical cocktail to which humans are exposed as it, in itself, broadly reflects human exposure (Rhind et al., 2002, 2005b; Abad et al., 2005; Oleszczuk, 2006; Martinez et al., 2007) to a complex mixtures of ECs (Groten et al., 2004; Jonker et al., 2004; Robinson and MacDonell, 2004; Koppe et al., 2006). In addition, sheep, like humans, are long-lived and have a relatively long gestation period (145 days), during which time ovine fetuses show a similar timing and sequence of ovarian development to that observed in the human (Pryse-Davies and Dewhurst, 1971; Juengel et al., 2002; Sawyer et al., 2002; De Felici et al., 2005). Unlike the rodent, the ruminant fetal ovary synthesizes estrogens which are important for germ cell development (Pannetier et al., 2006). Therefore, notwithstanding the metabolic and dietary differences between sheep and humans, the long-term, real-life, low-dose, exposure of pregnant sheep to a complex mix of relevant ECs is a good model for the human given that we know that many ECs are gaining access to the materno-fetal unit in pregnant women.
In this study, we aimed to determine whether prolonged, low-dose, exposure of the developing fetus, in utero, to maternal dietary EC load adversely affects the developing fetal ovary.
Materials and Methods
Animals, blood and tissue collection
The study was conducted at the Macaulay Institute research station (Hartwood, Lanarkshire, Scotland, UK) using Texel ewes. Animals were maintained on pasture at conventional stocking rates, adjusted according to pasture height, as described previously (Paul et al., 2005), so that animals from the respective treatments were maintained in comparable nutritional states. Neither group received supplementary feeding during their breeding lives. The animals were inspected by a qualified shepherd on a daily basis and routine animal care and vaccination procedures were conducted, as prescribed by best practice protocols.
Digested sewage sludge was applied twice annually, to each of three replicate 9 ha plots, at a rate of 2.25 metric tons of dry matter per hectare. For the first five applications, the sludge was applied in liquid form as described previously (Rhind et al., 2002). Thereafter, owing to changes in sludge production practices by the UK water authorities, thermally dried sludge pellets were used and applied at similar rates (about 2.25 tones dry matter/ha/year). The composition of the sludge, on a dry matter basis, did not differ between the two methods of application. The application of sludge to the surface of the pastures was not designed to conform to the UK recommendations for good practice (SEDE and Arthur Anderson, 2001). According to recognized codes of practice, sludge can only be applied to grazed grassland when it is deep injected into the soil or, if it is applied to the surface, there can be no grazing of that land within the season of application. However, this study was designed to maximize the rate of contamination of the pasture and topsoil and thus to maximize the risk of exposure of grazing animals to the chemical constituents of sewage sludge through their food’. Animals were not allowed to graze the pasture until a minimum of 3 weeks after sludge application, as prescribed by relevant legislation (Parliament, 1989). Control ewes were maintained on similar pasture to which 225 kg of nitrogen/ha/year was applied in the form of conventional inorganic fertilizers. The relatively harsh environmental conditions in central Scotland where the farm is located mean that there was no growth of clover or other estrogenic plant species in any of the pastures.
The treated and control groups from which the study animals were drawn each comprised 3 replicate subgroups of 5 breeding ewes in each of four age categories (total flock size = 120 ewes). For the present study, subgroups of ewes that were 6 years of age and had been maintained on the respective treatments throughout their breeding lives were drawn from all replicates of each treatment. Ewes from both groups underwent estrous cycle synchronization, using progestagen sponges (Chronolone, 30 mg; Intervet, Cambridge, UK), before being mated to rams of the same genotype and from the same source, to remove the effect of genotypic differences. Estimation of gestational age was based on the knowledge that conception should occur within 48 h of sponge removal when estrus cycle synchronization is used. Animals were euthanized at ∼110 days of gestation (GD110, equivalent to 27 weeks in the human) according to Schedule 1 protocols as defined by the UK Animals (Scientific Procedures) Act, 1986. Twenty-three female and 24 male fetuses were collected from both sets of ewes (control, n = 10, treatment, n = 7) and all of the resulting female fetal lambs (n = 15 in control, n = 8 in treated groups) were used for the ovary studies detailed below. Maternal and fetal body weight and fetal ovary weight were recorded at slaughter; fetal blood samples were also collected and the serum, isolated by centrifugation, stored at −20°C until required for assay. One ovary from each animal was fixed for 5.5 h in Bouin’s fixative and then transferred to 70% ethanol until analysis. The other ovary from each animal was snap-frozen in liquid N2 and stored at −80°C until analysis. GD110 was selected as a representative developmental stage since the primordial follicle pool has been established and expression of many developmentally important genes, such as growth differentiation factor 9 (GDF9) is maximal (Mandon-Pepin et al., 2003).
Immunohistochemistry
Sagittal 5 µm sections of each fetal ovary were cut, floated onto slides and dried at 50°C overnight. Slides were de-waxed in xylene, hydrated gradually through graded alcohols and washed in water. For all ovaries, slides were prepared containing two randomly selected, non-consecutive sections. At least one slide from each ovary was H&E stained for morphological assessment. Further slides were immunostained for induced myeloid leukaemia cell differentiation protein (MCL1) (pro-proliferative), GDF9 (development of primordial follicles) and phosphorylated histone H3 (pH3), to assess active proliferation and establish a mitotic index (Brenner et al., 2003). Following routine de-waxing, antigen retrieval procedures were used for the MCL1 and GDF9 epitopes [microwaving in 0.01 M citrate buffer (pH 6.0) on full power for 3 × 5 min]. Immunostaining for MCL1 and GDF9 was carried out using standard peroxidase-based immunostaining protocols (MCL1: chemMate, Dako and GDF9: vector). Slides for MCL1 were placed in a Dako autostainer and incubated with anti-MCL1 antibody (Serotec, 1/50), for 30 min. Antibody binding was visualized using the ChemMate peroxidase/DAB detection system (DakoCytomation Ltd., Ely, Cambridgeshire, UK). Slides for GDF9 were incubated overnight in a humid chamber with anti-GDF9 antibody (R & D Systems, 1/15) and antibody binding visualized using the Vector peroxidase/DAB detection system for 30 min (Vector Laboratories, Peterborough, UK). A rabbit anti-P-Histone H3 (#06–570; 1:500; Upstate Cell Signalling Solutions, Hampshire UK) was used after antigen retrieval and visualized using a goat biotinylated anti-rabbit antibody, followed by AB complex with horse-radish peroxidase (HRP) and DAB detection (all DAKO, Cambridge, UK). Ovarian sections were analysed for oocyte numbers and follicle size classes using an established follicle classification system (Lundy et al., 1999) by two independent observers (N.J.D. and H.M.) using six fields of view per section. Total numbers of pH3-positive granulosa, stromal, endothelial and surface epithelial cells were counted at ×40 and identified at ×400 by M.A. Because of the relatively low incidence of pH3-positive cells, cell numbers were expressed per mm2 of ×40 fields of view. In all analyses, sections from 15 control and 8 sewage sludge exposed fetuses were used. Only oocytes with the nucleus clearly visible were included in quantification of oocyte and follicle densities, which was performed in six separate slides containing a total of 12 sections for each fetus (H&E, MCL1 and GDF9).
Protein extraction
The frozen fetal ovaries were processed for one-dimensional and two-dimensional gel electrophoresis, as described in detail previously (Fowler et al., 2007a,b). Briefly, the frozen ovaries (15 control, 8 treated) were blotted on filter paper and combined with lysis buffer (1 mg wet tissue weight: 5 µl lysis buffer) containing 0.01 M Tris–HCl, pH 7.4, 1 mM EDTA, 8 M Urea, 0.05 M DTT, 10% (v/v) glycerol 5% (v/v) NP40, 6% (w/v) pH 3–10 Resolyte (Merk Eurolab Ltd, Poole, Dorset, UK) and protease inhibitor cocktail (Roche Diagnostics, Lewes, UK). The tissues were minced, sonicated in iced water for four 10 min bursts, with 2 min between each sonication, and centrifuged at 50 000g for 20 min at 4°C. Once the protein content of the final supernatant containing the soluble cellular proteins had been determined (RC-DC assay, Bio-Rad Laboratories Ltd, Hemel Hempstead, UK), the ovary extracts were stored at −80°C until required for further analysis.
One-dimensional gel electrophoresis and western blot
Individual ovary lysates (15 control and 8 treated) were electrophoresed (30 µg protein/lane) on 26-lane one-dimensional gel electrophoresis 4–12% Bis–Tris gels (Invitrogen Ltd, Paisley, UK) under reducing conditions and transferred to immobilon-FL membrane [Millipore (UK) Ltd, Watford, UK] as described previously (Lea et al., 2005). SeeBlue plus two molecular weight markers (Invitrogen) were electrophoresed in three lanes of every gel. The membranes were blocked (overnight, 4°C) with (Odyssey Blocking Buffer, 927–4000: LI-COR Biosciences UK Ltd, Cambridge, UK) and were incubated with primary antibodies (in blocking buffer) at 4°C overnight: (i) BAX (1:200: santa-Cruz Biotechnology Inc, CA, USA, sc-493), (ii) BCL2 (1:200: santa-Cruz, sc-783), (iii) SCF (1:200: santa-Cruz, sc-113126), (iv) CYP17A1 (1:2500: Fowler et al., 2007a), (v) SOD2 (1;2500: abnova Corp, Taipei, Taiwan, H00006648), all combined with an anti-β-actin load control of differing species (mouse 1:5000 AB6276; rabbit 1:10 000 AB8227, both AbCam Ltd, Cambridge, UK). The protein bands were visualized using an Odyssey infrared fluorescence imager (LI-COR) and the resulting electronic images were analysed using Phoretix-1D Advanced software (Nonlinear Dynamics Ltd, Newcastle upon Tyne, UK) in order to determine the band volumes and molecular weights. This software calculates band volumes, based on constant lane width and automatic band selection, from the raw data of pixel area and intensity that are independent of operator-altered contrast or brightness. The band volumes of β-actin were compared between groups to check the validity of this load control for ovaries from control and treated groups.
Proteomics
In the present study, we have selected proteomic methods as an exploratory tool to uncover novel effects on the ovary; we have previously demonstrated the utility of this approach for heterogeneous tissues (Fowler et al., 2007a,b) and others have used it to characterize responses to endocrine disruption (Alm et al., 2006).
Two-dimensional gel electrophoresis
Soluble proteins were analysed by two-dimensional gel electrophoresis using a small format gel system described previously (Cash and Kroll, 2003; Uwins et al., 2006), using pooled (control versus sewage sludge) lysates comprising equal quantities of protein from each ovary (15 ovaries in the control pool, 8 ovaries in the treated pool). Briefly, in order to ensure the clearest electrophoresis of the protein by two-dimensional gel electrophoresis, sample clean-up was performed using ReadyPrep 2-D Cleanup Kits (Bio-Rad Laboratories Ltd, Hemel Hempstead, Herts, UK) according to manufacturer’s instructions. Hundred microgram of total protein from the pooled lysates were separated in the first dimension on 7 cm pH 4–7 immobilized pH gradient gels (GE Healthcare, Uppsala, Sweden). For the second dimension, the proteins were resolved on 10–15% gradient polyacrylamide slab gels and proteins were detected using Colloidal Coomassie Blue G250. Four replicate gels were electrophoresed from each lysate pool. Stained gels were scanned using a Molecular Dynamics Personal Densitometer (GE Healthcare) at 50 µm resolution to generate 12-bit images, which were transferred to Phoretix 2D Analytical software, V 6.01 (Nonlinear Dynamics, Newcastle, UK). The semi-automated routines available in this software were used to detect and quantify protein spots as well as to match the profiles across a gel series. Individual spot volumes are expressed as normalized volumes relative to the total detected spot volume separately for each gel, minimizing potential analytical artefacts from variations in protein loading and migration.
Mass spectroscopic protein identification
Proteins in the gel pieces were digested with trypsin (sequencing grade, modified; Promega UK, Southampton, UK) using an Investigator ProGest robotic workstation (Genomic Solutions Ltd., Huntingdon, UK). Briefly, proteins were reduced with DTT (60°C, 20 min), S-alkylated with Iodoacetamide (25°C, 10 min) then digested with trypsin (37°C, 8 h). The resulting tryptic peptide extract was dried by rotary evaporation (SC110 Speedvac; Savant Instruments, Holbrook, NY, USA) and dissolved in 0.1% formic acid for LC-MS/MS analysis. Peptide solutions were analysed using an HCTultra PTM Discovery System (Bruker Daltonics Ltd., Coventry, UK) coupled to an UltiMate 3000 LC System [Dionex (UK) Ltd., Camberley, Surrey, UK]. Peptides were separated on a Monolithic Capillary Column (200 µm i.d. × 5 cm; Dionex part no. 161409). Eluent A was 3% acetonitrile in water containing 0.05% formic acid, Eluent B was 80% acetonitrile in water containing 0.04% formic acid with a gradient of 3–45% B in 12 min at a flow rate of 2.5 µl/min. Peptide fragment mass spectra were acquired in data-dependent AutoMS(2) mode with a scan range of 300–1500 m/z, three averages, and up to three precursor ions selected from the MS scan 100–2200 m/z. Precursors were actively excluded within a 1.0 min window, and all singly charged ions were excluded. Peptide peaks were detected and deconvoluted automatically using Data Analysis software (Bruker). Mass lists in the form of Mascot Generic Files were created automatically and used as the input for Mascot MS/MS Ions searches of the NCBInr database using the Matrix Science web server (www.matrixscience.com). The default search parameters used were: enzyme = Trypsin; Max. Missed cleavages = 1; Fixed modifications = Carbamidomethyl (C); Variable modifications = Oxidation (M); Peptide tolerance ± 1.5 Da; MS/MS tolerance ± 0.5 Da; Peptide charge = 2+ and 3+; Instrument = ESI-TRAP. Only proteins showing good agreement with mass and pI on the two-dimensional gels, statistically significant MOWSE scores and good sequence coverage were considered to be positive identifications.
Hormone assays
Fetal serum levels of follicle-stimulating hormone (FSH), estradiol and prolactin (PRL) were measured by radioimmunoassays that have been described and validated previously for sheep (McNeilly et al., 1986; Mann and Lamming, 1995; Lincoln et al., 2003; Crawford et al., 2004). The assay standards used, assay sensitivities and intra-assay coefficients of variation were: FSH; NIDDK-FSH-RP2 and NIH-LS18, 0.1 ng/ml, <10%, estradiol; MAIA estradiol kit (Serono Diagnostics, Fleet, Hants, UK), 0.2 pg/ml, <12%, PRL; NIDDK-PRL—RP3, 0.5 ng/ml, 10%). All fetal blood samples were measured in single assays.
Statistical analysis
Analyses were performed using JMP (5.1, Thomson Learning, London, UK). Normality of data distribution was tested with the Shapiro–Wilk test and non-normally distributed data were log-transformed prior to analysis. Morphological and endocrine data and the one-dimensional gel electrophoresis WB band volumes (normalized relative to β-actin expression separate for each lane) and normalized spot volumes (% of total spot volume for each gel separately) were compared as control versus sewage sludge-exposed using one-way ANOVA. For the proteomics, virtual ‘average’ gels were prepared so that only spots present in three out of four gels for each group were included and compared to determine differences in spot expression. Spots demonstrating statistically significant differences (ANOVA) in normalized volume were investigated further. Unless stated, otherwise data are presented as mean ± SEM.
Results
Maternal and fetal body weights and fetal ovary weights and endocrinology
There was no difference in the body weights, at the time of slaughter, of the ewes pastured on control and sewage sludge-treated fields (83 ± 2 versus 84 ± 1 kg, respectively). In contrast, the female fetuses from the ewes maintained on the sewage-treated pastures were significantly (P = 0.013) lighter (14%) (Table I) than the controls [and similar to the male fetuses (Paul et al., 2005)]. Despite difference in body weight, there was no significant (P > 0.05) treatment effect on the ovary weights. When ovary weights were normalized to body weight (mg/kg), the difference between treated and control animals remained non-significant (treated 22.7 ± 3.0 versus control 18.8 ± 1.1 mg/kg, P > 0.05). Of the three hormones measured, only PRL was significantly affected by exposure to sewage sludge (reduced 49% compared with controls, P = 0.011) although estradiol concentrations tended to be lower (22%) than the controls.
Table I.
Effects of sewage sludge on morphological and endocrine characteristics of Day 110 fetal ewes.
Characteristic
Control n = 15
Sludge-exposed n = 8
Fold-change following sludge-exposure
ANOVA
Body weight (g)
1593 ± 67
1365 ± 67
−1.17
P = 0.013
Ovary weight (mg)
29.4 ± 2.1
31.0 ± 4.2
+1.05
NS
FSH (ng/ml)
2.1 ± 0.3
1.4 ± 0.2
−1.50
NS
Estradiol (pmol/l)
128 ± 54
100 ± 27
−1.28
NS
PRL (ng/ml)
3.7 ± 0.7
1.9 ± 0.3
−1.95
P = 0.011
Lack of statistical significance (NS) is indicated where P > 0.05.
Effects of treatment on oocyte and follicle numbers and mitotic index
The densities of oocytes and follicles were similar, whether quantified by assessing H&E stained slides or MCL1 and GDF9 positive oocytes (Fig. 1a and b). Total oocyte densities were significantly reduced in the treated ovaries assessed by H&E staining (19% reduced: 18.8 ± 1.3 in treated versus 23.1 ± 1.6 in control, P = 0.042), MCL1 immunostaining (26% reduced: 14.6 ± 2.1 in treated versus 19.6 ± 1.5 in control, P = 0.039, Fig. 1) and GDF9 immunostaining (28% reduced: 13.9 ± 1.9 in treated versus 19.4 ± 1.4 in control, P = 0.034). The ratio of different follicle classes and isolated oocytes was also significantly skewed (P = 0.003 by two-way ANOVA combining treatment with follicle size class) by treatment (Fig. 1e) with a slightly, but significantly, greater proportion of the follicles being further developed following EC exposure: (combining classes 1a, 2 and 3: treated 16.1 ± 1.8 versus control 11.2 ± 0.9, P = 0.040). There were no statistically significant effects of sewage sludge exposure (P > 0.05) on the mitotic index of granulosa cells (0.6 ± 0.3 in treated versus 1.0 ± 0.2 in control), stromal cells (14.1 ± 1.3 in treated versus 13.3 ± 1.0 in control) or surface epithelial cells (0.3 ± 0.2 in treated versus 0.5 ± 0.1 in control), expressed as pH3-positive cells/mm2. In contrast, sewage sludge-exposed ovaries had significantly (P = 0.014) more pH3-positive endothelial cells/mm2 (1.2 ± 0.3 treated versus 0.3 ± 0.2 control).
Figure 1:
Effect of sewage sludge exposure on fetal ovarian morphology.
Immunolocalization of (a) MCL1, (b) GDF9 and (c) phosphorylated histone H3 expression in representative Day 110 fetal ovary sections. In (a) and (b), the arrow highlights immunopositive oocytes, whereas in (c), the arrow shows a histone pH3 positive granulosa cell. GDF9 and MCL1 immunopositive oocytes were present in all classes of follicles observed. Quantification (n = 15 control versus 8 treated ovaries) of the MCL1 immunohistochemistry is shown in (d) demonstrating the significant decrease in oocyte density in sewage sludge-exposed fetuses and (e) demonstrating the small but significant increase in the proportion of more advanced follicles in sewage sludge-exposed fetuses. Since the findings were similar between H&E staining and MCL1 and GDF9 positive oocytes, only the MCL1 data are shown to illustrate these results.
Effects of treatment of markers of apoptosis, developmental signalling, steroidogenesis and response to oxidative stress
There were no significant differences in β-actin band volumes between treated and control groups, demonstrating the validity of this load control. In utero exposure to sewage sludge pasture altered the balance between pro- and anti-apoptotic processes in the fetal ovaries. Whereas BAX was significantly higher in treated ovaries relative to the controls (65%, P = 0.002), BCL2 tended to be lower but this difference did not reach statistical significance (54%, P > 0.05, Fig. 2a and b). Expression of the key ovarian developmental signalling protein, SCF, was not different between controls and sludge-exposed ovaries (Fig. 2c). CYP17 expression tended to be lower (34%) in the treated compared with the control ovaries, but again this difference did not reach statistical significance (Fig. 2d). SOD2 was detected as both the mature 15 kDa form (weakly) and the 25 kDa precursor form (Fig. 2e and f). The precursor form tended to be lower (22%, P > 0.05), but the mature molecule was significantly lower (by 42%) in the treated compared with the control ovaries (P = 0.031).
Figure 2:
Quantification of levels of Day 110 fetal ovarian proteins (n = 15 control versus 8 treated ovaries) involved in (a) pro-apoptosis, BAX, (b) anti-apoptosis, BCL2, (c) developmental cell signalling, stem cell factor (SCF), (d) steroidogenesis, CYP17 and (e and f) oxidative stress response, manganese superoxide dismutase (SOD2).
P-values denote significant differences between control and sewage sludge-exposed fetuses and the load control was β-actin at 42 kDa.
Effects of treatment on the fetal ovarian proteome
There was little difference in the overall number of robust protein spots between the control (349 ± 9) and sewage sludge (354 ± 5) groups (P > 0.05); however, 147 protein spots showed significant (P < 0.05) differences in normalized volume and presence or absence in the sewage sludge compared with controls, based on a minimum change of ≥1.2-fold, P < 0.05, for inclusion. The differentially expressed protein spots covered a wide range of normalized spot volumes. In the sewage sludge ovarian proteome, a total of 52 spots were up-regulated (1.2–4.6-fold increased, P < 0.05), 46 were down-regulated (1.2–5.2-fold decreased, P < 0.05), 25 were absent (only present in the control group) and 24 were unique (only present in the sewage sludge group). Nineteen protein spots showing consistent detection, reproducible quantification between replicate gels and statistically significant differences, or very clear uniqueness to one experimental group, were identified by tandem mass spectroscopy (Table II and Fig. 3). Six of these proteins were blood protein which showed highly variable alterations in expression (−5.2-fold to +3.5-fold, absent to unique) between sewage sludge and control groups, preventing any simplistic links to potential differences in vascularization. The remaining 13 proteins fell into four broad functional categories: (i) cytoskeleton and its regulation, (ii) gene expression, transcription and processing, (iii) protein synthesis and (iv) protein phosphorylation and receptor activity. Pathway Architect software (Stratagene Europe, Amsterdam, The Netherlands) was used to inform on the functional links between the proteins that were seen to exhibit altered expression between the two groups. Six of these proteins were directly linked with translation (Fig. 4a), and SOD2 and BAX are directly associated with DNA fragmentation during apoptosis (Fig. 4b). Graphical representation of an interactions network demonstrates that CALM1 dominates the relationships between many of the differentially expressed proteins (Fig. 5).
Figure 3:
2-DE gel electrophoresis based proteomic analysis of Day 110 fetal ovaries (n = 15 control versus 8 treated ovaries) pooled into treated and control groups.
(a) Representative 2-DE 7 cm gel using a 4–7 pH gradient. The numbered arrows show the location of the 19 protein spots identified in Table II. Zoom boxes demonstrating representative protein spots showing (b) down-regulation and (c) up-regulation in fetuses exposed to sewage sludge. The histograms are based on averaged (n = 4 gels/group) spot volume (normalized relative to total spot volumes separately for each gel). Significant differences are based on ANOVA following log-transformation of spot volumes.
Figure 4:
Biological processes network of some of the differentially expressed proteins from the treated ovaries, demonstrating key interactions between CALM1 and HNRPH in regulating (a) translation and antagonism between SOD2 and BAX in (b) DNA fragmentation during apoptosis.
Output from Pathway Architect.
Figure 5:
Biological interactions network of some of the differentially expressed proteins from the treated ovaries.
CALM1 sits central within the network, interacting with most of the differentially regulated proteins via one or two steps. Ovals with a green background denote small molecules. Output from Pathway Architect software (Stratagene Europe, Amsterdam, the Netherlands).
Table II.
Positively identified proteins showing differential expression between ovaries at GD110 from 15 control fetuses with 8 fetuses exposed to sewage sludge in utero.
Spot #
Protein name GENE SYMBOL
Protein function and Tissue/cellular location
MW (kDa)
pI
MOWSE score
Accession number (NCBI)
Fold change (P, ANOVA)
Cytoskeleton and its regulation
1
Gelsolin [actin depolymerising factor (ADF), brevin] GSN
Promotes nucleation and severs formed filaments. Expression lost in ovarian carcinoma. Cytoplasm
80.9
5.58
429
2833344
−2.8 (P = 0.020)
2
Vinculin VCL
Involved in cell adhesion and focal complex assembly with role in actin microfilament attachment to plasma membranes. Cytoskeleton, cell–cell junctions.
117.2
5.83
1050
4507877
−3.4 (P = 0.043)
9
Tubulin α-chain (alpha-tubulin 1) TUBA1
Major constituent of microtubules, binds two GTP molecules. Cytoskeleton
50.6
4.97
383
3502919
+3.1 (P < 0.001)
Blood proteins
5
Serum albumin precursor ALB
Secreted protein, typically into plasma, binding molecule, regulates colloidal osmotic pressure
71.1
5.82
251
162648
−5.2 (P = 0.003)
10
97
+3.0 (P < 0.001)
12
189
Absent
8
Albumin precursor ALB
71.1
5.80
483
1387
+3.5 (P = 0.010)
16
646
Unique
14
Serotransferrin precursor (transferrin, siderophilin) TF
Iron-binding transport protein and stimulation of cell proliferation
79.9
6.75
243
29135265
−3.1 (P = 0.003)
Gene expression, transcription and processing
3
DNA-binding pur alpha PURA
Interacts with RNA and DNA and recruits regulatory proteins to specific nucleic acid sequences, stimulating transcription. Nucleus
34.8
5.88
61
9652255
−5.0 (P < 0.001)
7
Heterogeneous nuclear ribonucleoprotein K (HNRPK) HNRPK
Binds RNA, interacts with pur alpha to mediate repression of CD43 promoter. Ribonucleoprotein complex
51.3
5.14
598
74354615
+3.1 (P = 0.023)
11
Heterogeneous nuclear ribonucleoprotein H (HNRNPH) HNRPH1
Part of complex providing substrates for processing of pre-mRNA. Nucleus
49.5
5.89
475
10946928
Absent
Protein synthesis
4
Endoplasmic reticulum protein ERp29 (ERp31 or ERp28) ERP29
Molecular chaperone, participates in the folding of secretory proteins in endoplasmic reticulum. Endoplasmic reticulum
28.9
5.63
270
109658363
−3.2 (P = 0.002)
6
Calmodulin (CaM) CALM1
Mediates the control of enzymes and proteins (e.g. protein kinases and phosphatases) by Ca, role in calcium signalling. Cytoplasm, cell membrane
16.8
4.09
224
115509
−3.1 (P = 0.033)
17
Tu translation elongation factor (EF-Tu) TUFM
Role in protein synthesis, promoting GTP-dependent binding of tRNA to ribosomes. Mitochondria
49.7
6.72
235
111304949
Unique
18
Tumor rejection antigen 1 (GP96) (HSP90 family) TRA1 (GRP94, HSP90B1)
Molecular chaperone during processing, folding and transport of secreted proteins in the endoplasmic reticulum. Endoplasmic reticulum
92.7
4.76
727
27807263
Unique
Protein phosphorylation and receptor activity
13
Guanine nucleotide-binding protein G, beta 1 (transductin beta 1 chain) GNB1
Part of G-protein heterotrimer, transduces transmembrane signalling systems. Cell membrane, cytoplasm
38.2
5.60
384
6680045
Absent
15
Protein phosphatase 1D PPM1D (WIP1)
Required for relief of p53-dependent checkpoint mediated cell cycle, negatively regulates cell proliferation. Nucleus
38.0
5.84
351
227436
+4.6 (P = 0.010)
19
S100 calcium-binding protein A11 (similar to) S100A11
Proposed function is calcium-ion binding and signal transduction, negative regulation of cell proliferation. Cytoplasm
11.5
6.72
202
29135265
Unique
Discussion
The aim of this study was to establish whether long-term exposure of pregnant ewes to a cocktail of ECs disrupts female fetal ovarian development. Our results clearly show that long-term dietary exposure to such a cocktail, delivered via application of sewage sludge fertilizer to pasture, significantly disturbs both the fetal ovary and fetal endocrinology. These findings of alterations in the ovary were associated with a mild but significant growth restriction of the female fetuses.
In utero exposure of the female fetus to ECs results in a very wide range of morphological changes, varying according to species and nature of the chemicals (reviewed Miller et al., 2004). Although 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) does not produce the reduction in rodent oocyte and follicles numbers that we find (Flaws et al., 1997), PCBs and polycyclic aromatic hydrocarbons (PAHs) do (Flaws et al., 1997; Matikainen et al., 2002). The actions of other chemicals in the sewage sludge with effects on reproduction, such as cadmium (Henson and Chedrese, 2004), must also be taken into account. However, it is unlikely that our results were due to elevated phytoestrogens since studies of phytoestrogens (usually in rodents), such as genistein (e.g. Jefferson et al., 2006), show decreased germ cell apoptosis and reduced breakdown of oocyte nests, quite different from our findings of reduced oocyte density in fetuses exposed to sewage sludge chemicals in utero. This is extremely interesting given that ovarian BAX expression was significantly higher in sludge-exposed fetuses. In the mouse, BAX is a key regulator of follicle numbers and the BCL family is heavily implicated in the mechanisms underlying detrimental effects of selected environmental chemicals on the ovary (Borgeest et al., 2004; Miller et al., 2005; Greenfeld et al., 2007a,b). It is most probable that similar mechanisms act to determine the follicle pool in all mammals. That the anti-apoptotic BCL2 tended to be reduced, although not significantly so, in the sludge-exposed fetuses, suggests a redistribution of the pro- and anti-apoptotic balance more towards apoptosis. These findings agree with our observation that there were no differences in granulosa cell mitotic index and lead to the conclusion that the reduction in follicle numbers that we observed was due to an early loss of germ cells. Should these effects be reproduced in women exposed in utero to ECs as fetuses, it would be likely to result in reduced fertility and earlier onset of menopause. SCF was not affected by exposure to an EC cocktail in sewage sludge demonstrating the subtlety of the effects of a cocktail of chemicals. Clearly, while oocyte density is lower, the pre-granulosa or granulosa cells were producing the same amount of SCF, which is important in early follicle development (Parrott and Skinner, 2000; Jin et al., 2005). Sewage sludge exposure did not significantly affect the mitotic index (density of pH3-positive cells) of any ovarian cell type studied, other than endothelial cells. This suggests an effect on ovarian angiogenesis and supports our conclusion that chemicals in the sewage sludge are acting on the fetus since EDCs are know to have both stimulatory and inhibitory effects on angiogenesis (Tavolari et al., 2006).
Although neither was statistically significant, our findings of reduced levels of circulating estradiol and lowered ovarian expression of CYP17 in sludge-exposed fetuses were consistent with each other and suggest a mild impairment of steroidogenesis in these animals, possibly related to reduced germ cell proliferation (Pannetier et al., 2006) in sewage sludge-exposed fetuses. We quantified SOD2, because reactive oxygen species (ROS) induced by some ECs can damage developing organs (Ahmed et al., 2005). Further, methoxychlor and heavy metals decrease the expression of protective enzymes such as SOD1 and SOD2 in ovarian cells (Gupta et al., 2006; Nampoothiri et al., 2007), which would have developmental and steroidogenic consequences. Our animals exposed to a real-life complex cocktail of ECs revealed a similar trend since the levels of SOD2 were lower than that in the controls and thus their ovarian cells may be more susceptible to oxidative damage than controls. The reduction in SOD2 would also imply reduced inhibition of DNA fragmentation during apoptosis at a time when increased BAX will elevate apoptosis rates (Fig. 4b; Southgate et al., 2006). The fact that phytoestrogens, such as daidzein, reduce ROS-induced toxicity (Tang et al., 2006), contrasts sharply with the effects of exposure to sewage sludge chemicals emphasizing that the observed effects are not due to phytoestrogens.
Exposure to sewage sludge chemicals altered the expression patterns of 42% of the protein spots in the exposed compared with control ovaries. Although this by no means reflects the entire ovarian proteome, it indicates that chemicals in sewage sludge can cause widespread changes in the ovary. Some of these changes will reflect altered cell numbers, but some will reflect changes in pathways involved in ovarian function and development. In addition, proteins may be present in many spots and spots may contain several proteins and so changes in spot volumes reflect complex and sometimes very subtle alterations in the protein profile. Proteomics allows us to investigate global effects of exposure to environmental chemicals without preconceptions about pathways and mechanisms, complementing the targeted study of ovarian morphology and proteins of known importance in reproductive development. We targeted the most consistently, statistically significantly, altered proteins for identification. This addresses gel–gel variation and reduces potential methodological error. In addition, we limited ourselves to proteins showing a ≥2-fold change in expression. Liquid-chromatography-mass spectrometry enabled positive identification of all 19 selected protein spots that fit the selection criteria. Overall, the proteins showing disturbed expression would be consistent with altered transcription and translation, apoptosis/proliferation and protein production/actions within the developing ovary. The disturbed proteins could also result in dysregulated receptor and calcium-dependent functions.
The most obvious consequence of the altered proteins is the probable disturbance in translation since 6 of the 19 differentially expressed proteins, that we identified, have interactions and effects on translational processes (Fig. 4a). This would have consequences for the expression of gene products during development. The reduction of CALM1 protein in sludge-exposed fetal ovaries was unexpected because up-regulation of CALM1 is characteristic of genomic estrogenic activation (Wang et al., 2004). This, therefore, is evidence that exposure to sewage sludge was not necessarily activating conventional genomic estrogen pathways. Indeed, it is now well known that environmental chemicals operate through a wide range of mechanisms and pathways in addition to genomic estrogen action (Henley and Korach, 2006; Tabb and Blumberg, 2006). The 5-fold reduction of DNA-binding pur-alpha (PURA) in ovaries from fetuses exposed to sewage sludge chemicals is interesting on two counts. First, PURA, which recruits regulatory proteins to RNA and DNA sequences, is involved in oncogenic inhibitory pathways (Johnson et al., 2003), and, second, CALM1 stimulates PURA (Kuo et al., 1999), so a reduction in both proteins suggests a causative link. The location of CALM1 at the node of a biological interactions network that links most of the proteins we observed to be affected by exposure to sewage sludge chemicals (Fig. 5) demonstrates how changes in protein expression could propagate down numerous pathways involved from transcription along to post-translational modification and receptor activity. Relevantly, calmodulin-dependent kinases are implicated in maintaining ovarian steroidogenesis (Seals et al., 2004) and calmodulin binding protein is expressed in fetal germ cells during development (Luers et al., 2002), whereas defects in the caldesmon/calmodulin system impairs cell cycling and migration (Li et al., 2004). Gelsolin (GSN), 2.8-fold reduced in treated ovaries, was of interest since its expression is reduced in ovarian cancer (Noske et al., 2005). GSN, which modulates cellular motile activities, is widely expressed in the developing embryo (Arai and Kwiatkowski, 1999) and adult ovary (Teubner et al., 1994) where it is important in follicle growth. The role of vinculin (VCL) in a variety of processes, such as granulosa cell differentiation (Kranen et al., 1993), suggests that its down-regulation in our study may have consequences for ovarian development.
The HNRNP family of proteins is important in the formation of mRNA and both H and K forms are highly expressed in the primary oocyte (Kamma et al., 1995). HNRNPK, up-regulated in sludge-exposed ovaries, is important for cell spreading (Yoo et al., 2006) and transcriptional responses to DNA damage (Moumen et al., 2005). HNRNPK and PURA act together in transcriptional regulation of leukocytes (Da Silva et al., 2002) and, should both proteins act together on ovarian cells, disruption of transcription would be expected. Pertinently, the HNRNPH homologue, glorund, represses ovarian expression of Drosophila nanos (Kalifa et al., 2006), which is highly conserved and important for germ cell migration in mouse embryos (Tsuda et al., 2003). This contrasts with our study where HNRNPH was greatly reduced, which would suggest increased germ cell numbers. Disturbance of transcription would have multiple effects in many cell types, although redundancy of function could greatly reduce the severity of phenotypic effects.
The endoplasmic reticulum is important in protein secretion and many cellular activities, such as response to oxidative stress, so it is interesting that two endoplasmic reticulum chaperone proteins ERP29 and TRA1 (also called GRP94) were reduced and increased, respectively, by exposure to sewage sludge chemicals. Although not well understood, endoplasmic reticulum chaperone proteins are important in developmental and disease processes, including programmed cell death (Rao et al., 2006; Ni and Lee, 2007). TRA1 is abundant in the adult oolemma (Calvert et al., 2003) and regulates the secretion of a key player in ovarian function: insulin-like growth factor (Knight and Glister, 2006; Wanderling et al., 2007). TRA1 is increased in endoplasmic reticulum stress (Hagg et al., 2004) underlining the relevance of this finding. Although ERP29 is redox-inactive (Mkrtchian and Sandalova, 2006), it may be a target for reactive metabolites of toxic chemicals like bromobenzene (Koen and Hanzlik, 2002). The fact that pituitary levels of ERP29 are increased by exposure to estrogen (Blake et al., 2005), but decreased in our sewage sludge-exposed ovaries, may indicate either non-estrogenic effects or differential responses in the ovary. The increase in Tu translation elongation factor (TUFM), which has chaperone activities during protein synthesis (Suzuki et al., 2007), is interesting since mutations in elongation factors have developmental pathologies (Smeitink et al., 2006). Increased PPM1D and decreased GNB1 in the sludge-exposed ovaries imply effects on phosphorylation and receptor activity. PPM1D over-expression amplifies tumorigenesis by suppressing p53 activation (Bulavin et al., 2002) and enhances progesterone receptor activation (Proia et al., 2006). Importantly, progesterone receptor activation reduces primordial follicle assembly (Kezele and Skinner, 2003). This may be part of the mechanism by which sewage sludge-exposed ovaries exhibit reduced density of follicles at Day 110 of gestation.
The sludge-exposed female fetuses were 14% lighter than controls which raise the issue of what caused this difference and what effect this apparent very mild growth restriction might have on fetal ovarian development. There were no differences in maternal body weight in our study, which would contradict any conclusion that sludge-exposed fetuses were nutritionally challenged. The literature (reviewed Rhind et al., 2003) suggests that such a mild body weight difference is highly unlikely, in itself, to cause the ovarian developmental perturbation that we report here. For instance, a 50% maintenance diet during gestation resulted in a 32% decrease in lamb body weight and a 23% reduction in fetal ovary weight, but no loss of germ cells (Murdoch et al., 2003). More detailed studies of maternal undernutrition during pregnancy in sheep (e.g. Rae et al., 2001) found that cutting energy provision during pregnancy to 50% induced a trend towards smaller ovaries and significantly fewer more advanced follicles (types 2, 3 and 4) without changing germ cell numbers. This contrasts with our study in which the proportion of more advanced follicle increased, possibly contributing to our finding that ovary weight was not different between controls and sludge-exposed fetuses. Following growth-restricted fetuses into adulthood finds them recovering body mass with apparently normal hypothalamo-pituitary-ovary-axes, although ovulation rates were 20% reduced (Rae et al., 2002; Borwick et al., 2003). In the human, girls born small for gestational stage (i.e. growth-restricted) may have small ovaries and reduced ovulation rates at puberty (Ibanez et al., 2000, 2002), an effect that is at least partly related to insulin resistance (Ibanez and de Zegher, 2006), but probably not due to a reduction in the fetal follicle pool (de Bruin et al., 2001). The ovaries from our sludge-exposed fetuses are very different: no reduction in ovarian weight, but reduced germ cell and follicle densities and a small but significant increase in the proportion of more advanced follicles. Thus, we can conclude that growth restriction was not a major factor and, therefore, the effects of exposure to sewage sludge are much more likely to be due to chemicals in the sludge. That both the sewage sludge exposure in our study and the growth restriction of the sheep fetus (Phillips et al., 2001) have some similar reproductive consequences suggests some commonality in regulatory pathways between the two forms of fetal insult.
It is not clear which components of sewage sludge are reaching the maternal and fetal tissues and causing the disturbed fetal development we observed. It is currently impossible to accurately measure many chemicals in the fetal gonad because of the limited tissue quantity available. Therefore, we cannot be confident of actual fetal ovarian exposure to different chemicals in our study. Some tissue EC levels do differ significantly between control and sludge-exposed fetuses (see Introduction), but it is most likely that subtle and complex alterations in the balance between a very wide range of chemicals, probably affecting a variety of body systems and organs, is the key factor in causing the disruption of fetal ovarian development. This is supported by our finding that although maternal smoking during gestation does not lead to any major changes in fetal liver PAH concentrations, the fetuses were correctly allocated to smoking and non-smoking groups by discriminant analysis of liver PAH concentrations (Fowler et al., 2008).
The sheep in our study were pastured on fields treated with sewage sludge in a way that may have raised exposure above the levels to which sheep are normally exposed to under current UK/EC legislation and agricultural guidelines; the treatments were designed to maximize the risk of exposure. It is important to note that our studies are designed to elucidate the effects of prolonged exposure to a real-life cocktail of chemicals and are not designed to determine whether the use of processed human sewage sludge as a fertilizer poses human health risks (under the current best operating practices). With this proviso, we can strongly conclude from our study that long-term exposure to low doses of a complex ‘real-life’ cocktail of environmental chemicals affects the developing fetal ovary, probably starting very early in fetal life, in such a way as to suggest that similar human fetal exposures could reduce fertility of the resulting women and increase their chances of premature menopause. Future studies should address genetic and endocrine mechanisms involved in these effects and also establish the critical windows of exposure, as well as determining the fertility of resulting adults.
Funding
The Wellcome Trust (080388) to P.A.F.; NHS Research & Development (1664) to P.A.F.; the Scottish Executive Environment & Rural Affairs Department (302132) to S.M.R.

environmental chemicals
sewage sludge
oocyte
fetal development
granulosa cell


Perturbation of hyaluronan metabolism predisposes patients with type 1 diabetes mellitus to atherosclerosis

Aims/hypothesis Cardiovascular disease contributes to mortality in type 1 diabetes mellitus, but the specific pathophysiological mechanisms remain to be established. We recently showed that the endothelial glycocalyx, a protective layer of proteoglycans covering the endothelium, is severely perturbed in type 1 diabetes, with concomitantly increased plasma levels of hyaluronan and hyaluronidase. In the present study, we evaluated the relationship between hyaluronan and hyaluronidase with carotid intima-media thickness (cIMT), an established surrogate marker for cardiovascular disease.
Introduction
Macro- and microvascular complications are a major cause of morbidity and mortality in patients with diabetes mellitus. While the macrovascular complications in patients with type 2 diabetes mellitus can partly be attributed to the increased prevalence of classic cardiovascular risk factors such as dyslipidaemia, these risk factors cannot explain the increased prevalence of atherosclerosis in type 1 diabetes mellitus [1–3]. Recent data demonstrated that hyperglycaemia itself may play a causative role. Thus, improved metabolic control is associated with a decreased macrovascular event rate [1–3]. However, the pathophysiology of glucose-associated atherogenesis remains to be elucidated [4, 5]. In recent years, the glycocalyx has emerged as a potential orchestrator of vascular homeostasis, which closely determines anti-adhesive and barrier properties of the vessel wall [6]. In line, we found that the endothelial glycocalyx is adversely affected by both acute and chronic hyperglycaemia in volunteers and type 1 diabetes patients, respectively [7, 8].
Hyaluronan is a principal constituent of the glycocalyx and removal of the glycocalyx with hyaluronidase has been associated with increased vascular vulnerability towards atherogenic insults [9–11]. In animal models of type 1 diabetes, hyaluronidase activity has been shown to be increased and this correlated with increased carotid intima-media thickness (cIMT) [12–14]. In line with this, increased accumulation of hyaluronan within the arterial wall in type 1 diabetes patients correlated with vascular changes [15]. We recently found an acute increase in plasma hyaluronan coinciding with glycocalyx perturbation during a normo-insulinaemic–hyperglycaemic clamp in healthy volunteers [7]. Moreover, we observed an inverse correlation between plasma hyaluronan as well as plasma hyaluronidase and glycocalyx volume in patients with type 1 diabetes [8]. In this concept, hyperglycaemia-induced perturbation of hyaluronan metabolism, characterised by increased hyaluronidase activity with subsequent increased plasma hyaluronan levels, may indicate increased vascular vulnerability.
In the present study, we set out to evaluate the potential relationship between structural changes of the carotid artery and hyaluronan metabolism in patients with uncomplicated type 1 diabetes.
Subjects and methods
We enrolled non-smoking Europid patients with type 1 diabetes, all without clinical signs of micro- or macrovascular disease. The patients were recruited from the Internal Medicine outpatient clinics of the Academic Medical Center and Onze Lieve Vrouwe Gasthuis in Amsterdam, the Netherlands. The presence of macrovascular disease, defined as ECG abnormalities or a history of cardiac, cerebral or peripheral vascular events, was an exclusion criterion for the study. Moreover, subjects with retinopathy, neuropathy, (micro) albuminuria, or hypertension were excluded from participation. All patients were on multiple daily injections of insulin with no other concomitant medication use. Matched non-smoking controls (selected for this study specifically) were unrelated volunteers of similar age and sex. Investigations of both study groups were randomly performed during the study period. Approval for the study was obtained from the Internal Review Board of the Academic Medical Center Amsterdam and all subjects gave written informed consent. The study was carried out in accordance with the principles of the Declaration of Helsinki.
All measurements were performed after an overnight fast and in a quiet and air-conditioned room. Blood pressure was measured in triplicate and the last two measurements were averaged to obtain heart rate and systolic and diastolic blood pressure. The latter were averaged to calculate mean blood pressure. At baseline, blood samples were collected for determination of lipids, high sensitivity C-reactive protein (hsCRP), HbA1c, hyaluronan and hyaluronidase. The markers of hepatic function ASAT and ALAT (aspartate aminotransferase and alanine aminotransferase, respectively) were determined, since chronic liver disease is known to be associated with increased plasma hyaluronan levels [16]. After centrifugation (within 1 h after collection), aliquots were snap-frozen in liquid nitrogen and stored at −80°C.
Clinical chemistry Total cholesterol, HDL-cholesterol and triacylglycerol were measured by enzymatic methods (Roche Diagnostics, Basel, Switzerland). LDL-cholesterol was calculated using the Friedewald formula. ALAT and ASAT were measured by a pyridoxal-phosphate activation assay (Roche Diagnostics). HbA1c was measured using an HPLC (Reagens Bio-Rad Laboratories BV, the Netherlands) on a Variant II (Bio-Rad Laboratories). Total plasma hyaluronan and hsCRP levels were determined in duplicates by commercial ELISA (Echelon Biosciences, Salt Lake City, UT, USA and Roche, Bern, Switzerland, respectively). Plasma hyaluronidase levels were determined with a previously described assay [8, 17].
Ultrasound B-mode protocol for cIMT measurement B-mode ultrasound imaging was used to visualise three carotid arterial wall segments comprising common carotid, bulb and internal of the left and right carotid arteries according to a previously published protocol [18, 19]. Subjects were scanned in the reclined position following a predetermined, standardised protocol. An Acuson 128 XP/10 v (Siemens, Erlangen, Germany) equipped with an L7 linear array transducer and extended frequency software was used. B-mode images were stored as 4:1 compressed jpeg files on a digital still recorder (SONY DKR-700 P). All scans were performed by the same sonographer. To investigate intra-sonographer reproducibility, ten study subjects were scanned in duplicate. These investigations enabled us to provide robust arterial wall thickness measurements (SD of the means of the paired cIMT measurements 0.05 mm; CV = 9.0%). One image analyst performed the analyses off-line with semi-automated quantitative and qualitative video image analysis software. Both the sonographer and the image analyst were blinded to the clinical status of the subjects. These images provided the cIMT data. Mean cIMT was defined as the mean cIMT of the right and left common carotid, the carotid bulb and the internal carotid far wall segments. For a given segment, cIMT was defined as the average of the right and left cIMT measurements. The per-patient averaged means of the cIMT values of segments was used for the primary analysis.
Statistical analysis Mean values of continuous variables between type 1 diabetes patients and controls were compared using Student’s t test for independent samples. In the case of a skewed distribution the t test was performed on log-transformed values, while medians and interquartile ranges are presented. Chi-square tests were applied for comparison of distribution of dichotomous data. Correlation between hyaluronan and hyaluronidase was calculated by Spearman’s rank coefficient (two-tailed). In this study our main interest was to find predictors for type 1 diabetes-associated atherosclerosis and vascular dysfunction. The relationship between the dependent variable cIMT on the one hand and other parameters (e.g. plasma hyaluronan) on the other was first explored univariably using linear regression analysis. For clinical variables and variables which revealed statistically significant correlations in the univariate analysis, estimates of cIMT adjusted for confounding were calculated with SPSS version 11.5 (Chicago, IL, USA). In addition, several multivariate models were built to explore the effects of age, sex and the statistically significant variables on cIMT. Throughout, a two tailed p value <0.05 was considered statistically significant.
Results
Clinical characteristics of the 99 type 1 diabetes subjects and 99 matched controls are listed in Table 1. There was no significant difference between type 1 diabetes subjects and controls with regard to age, sex, BMI, systolic and diastolic blood pressure, liver function tests and cholesterol profile. However, we did observe increased values for HbA1c, heart rate, plasma hsCRP, hyaluronan and hyaluronidase in type 1 diabetes patients. A significant correlation was found between plasma hyaluronan and hyaluronidase activity in type 1 diabetes (r = 0.3, p < 0.05, see Fig. 1a). After exclusion of the highest hyaluronidase activity levels (levels >750 U/ml), the correlation between hyaluronan and hyaluronidase levels was still present. Liver function tests (ASAT and ALAT) were not significantly associated with plasma hyaluronan levels in type 1 diabetes.
Table 1Demographic and baseline parameters of the study cohort Type 1 diabetes patientsControlsNumber of participants9999Sex (male/female)44/5544/55Age (years)32.8 ± 14.834.9 ± 16.4Duration of diabetes (years)16.4 ± 11.9–Daily insulin dose (IU) 52.9 ± 20.3–Smoking (yes/no)0/990/99BMI (kg/m2)23.4 ± 3.523.3 ± 3.6Systolic blood pressure (mmHg)123 ± 17125 ± 20Diastolic blood pressure (mmHg)72 ± 973 ± 12Heart rate (beats/min)71 ± 11**60 ± 14 Total cholesterol (mmol/l)4.9 ± 0.94.9 ± 1.0LDL-cholesterol (mmol/l)2.8 ± 0.72.9 ± 0.8HDL-cholesterol (mmol/l)1.6 ± 0.51.5 ± 0.4Triacylglycerol (mmol/l)0.9 (0.5–1.1)1.0 (0.5–1.2)ASAT (U/l)24 (21–27)25 (21–29)ALAT (U/l)22 (15–28)20 (14–24)HbA1c (%)8.3 ± 1.6**5.1 ± 0.3Hyaluronan (ng/ml)78 ± 43*60 ± 18Hyaluronidase (U/ml)362 ± 23**242 ± 13hsCRP (mg/l)2.6 (0.4–2.9)*1.1 (0.2–2.0)cIMT (mm)0.61 ± 0.15**0.53 ± 0.12Data are means±SD, except for triacylglycerol, ASAT, ALAT and hsCRP, which are expressed as median (inter-quartile range).*p < 0.05, **p < 0.01 type 1 diabetes patients vs controlsFig. 1a Relationship between plasma hyaluronan levels and plasma hyaluronidase activity in type 1 diabetes patients. b Relationship between plasma hyaluronan levels and cIMT in type 1 diabetes patients
Mean cIMT was increased in the type 1 diabetes group compared with controls (0.61 ± 0.15 vs 0.53 ± 0.12 mm, p < 0.001). In type 1 diabetes subjects plasma hyaluronan levels (Fig. 1b), age, male sex, duration of diabetes and mean blood pressure were positively correlated with mean cIMT in univariate analysis. No dose-dependent relationship between insulin dose, HbA1c levels and mean cIMT was found in these patients. However, upon multivariate linear regression analysis only age and sex remained significantly associated with cIMT (Table 2).
Table 2Univariate and multivariate associations of cIMT with various risk factors in patients with type 1 diabetesParameterUnivariate β coefficientp valueMultivariate β coefficientp valueFemale sex −0.86*0.005−0.048*0.029Age0.007*0.0010.07*0.0001Duration of diabetes 0.008*0.001−0.1100.340Daily insulin dose−0.0010.109BMI0.0040.433Mean blood pressure0.004*0.004−0.0270.726Heart rate0.00010.994Total cholesterol0.0160.366LDL-cholesterol0.0210.321HDL-cholesterol0.0260.416Triacylglycerol−0.0540.076ASAT0.0370.615ALAT−0.0190.589HbA1c−0.0080.441Hyaluronan0.126*0.0010.1160.130Hyaluronidase0.0360.731hsCRP−0.0130.306*p < 0.05 type 1 diabetes patients vs controls
Discussion
In line with expectation, type 1 diabetes patients were characterised by structural changes of the arterial wall. In addition, we observed significant elevations of plasma hyaluronan and hyaluronidase activity levels in type 1 diabetes patients, whereas hyaluronan was correlated to cIMT. These present data imply that disturbances of hyaluronan metabolism may be associated with vascular damage in type 1 diabetes patients.
Intima-media thickness in type 1 diabetes We observed a significant increase in cIMT in type 1 diabetes patients without micro- or macro-vascular complications compared with controls and confirmed that male sex is associated with an increased cIMT [3]. Despite the cross-sectional design of our study, this finding is compatible with data from the longitudinal DCCT study [3]. LDL-cholesterol was not associated with cIMT progression in the DCCT cohort, underscoring a potential role for hyperglycaemia in diabetic atherogenesis [1, 20, 21]. In contrast to the DCCT findings, we did not find a correlation between cIMT and glycaemic status. This apparent discrepancy may have several explanations. First, a single determination of HbA1c in our study may not be a reliable reflection of glycaemic excursions over the last months to years. In the DCCT, HbA1c was evaluated repetitively in a prospective cohort of type 1 diabetes patients, all receiving an intensive treatment regimen [1, 3]. Under these circumstances, HbA1c was predictive of cIMT progression over the next 4 years. Second, the elderly patients in our cohort may have been exposed to longer periods of poorly controlled diabetes followed by more intensive treatment regimens only in the last few years. As a consequence, their present HbA1c levels may have underestimated long-term glycaemic exposure.
Hyaluronan metabolism and type 1 diabetes Hyaluronan is the principal constituent of endothelial glycocalyx as well as the extra-cellular matrix [7–10, 14, 15, 22]. Since the glycocalyx is a principal determinant of vascular permeability for macromolecules (e.g. lipoproteins), glycocalyx loss may contribute to the increased transvascular leakage of lipoproteins in patients with type 1 diabetes [20]. Indeed exposure of the carotid artery to atherogenic challenges in mice resulted in increased plasma hyaluronan shedding, concomitant loss of endothelial glycocalyx and increased cIMT [23, 24]. In line, we observed that patients with uncomplicated type 1 diabetes have a profound reduction of endothelial glycocalyx, which was associated with increased plasma hyaluronan and hyaluronidase levels [8]. In fact, in the present study we find a positive correlation between plasma hyaluronan and cIMT thickness. Upon multivariate analysis this correlation was lost, most likely due to the fact that age and sex are very closely associated with cIMT, thus attenuating the predictive value of hyaluronan [19]. We did not find a relationship between chronic inflammation as measured by hsCRP and plasma hyaluronan in type 1 diabetes. Therefore further studies are needed to evaluate the effect of other inflammatory markers (e.g. leucocyte count) on hyaluronan metabolism in these patients.Collectively, the present finding implies that hyperglycaemia may elicit alterations in hyaluronan metabolism, which are likely to reflect glycocalyx perturbation. The latter facilitates a wide array of pro-atherogenic effects, including vascular dysfunction and increased permeability of the vessel wall for, for example, lipoproteins. In line, aggregation of calcium with hyaluronan (and other subendothelial glycosaminoglycans) could enhance ectopic calcification of the cIMT, which is increased in type 1 diabetes patients [25, 26]. It would be interesting to investigate whether therapeutic intervention aimed at this disturbed hyaluronan metabolism in type 1 diabetes has the potential to reverse the pro-atherogenic state in these patients [27, 28].
Study limitations Several methodological aspects of our study merit caution. We did not determine fasting plasma glucose levels in our type 1 diabetes subjects, therefore we were only able to study markers of chronic hyperglycaemia (HbA1c) on vascular dysfunction. Moreover, the observational nature of our study combined with the use of surrogate markers of future vascular disease can be considered a weakness. However, solid evidence exists that changes in arterial wall function are predictive of cardiovascular outcome [29, 30]. In addition, reproducibility of the measurements was excellent, since a single ultrasound machine was used, one experienced sonographer performed all ultrasonography and images were analysed by a single reader. To reduce variability further, image analysis software automatically investigated each measurement.Finally endothelial glycocalyx also comprises other glycosaminoglycans such as syndecan, chondroitin sulphate and heparan sulphate, which all have their own function [6, 31]. Since hyaluronan and heparan sulphate are important in shear stress-mediated nitric oxide production, which is inextricably entangled with atherosclerosis, further research is needed to explore the role of these other endothelial glycocalyx compounds on diabetes mellitus associated vascular dysfunction.

hyaluronan
type 1 diabetes mellitus
hyaluronidase
intima-media thickness


Biochemical applications of surface-enhanced infrared absorption spectroscopy

An overview is presented on the application of surface-enhanced infrared absorption (SEIRA) spectroscopy to biochemical problems. Use of SEIRA results in high surface sensitivity by enhancing the signal of the adsorbed molecule by approximately two orders of magnitude and has the potential to enable new studies, from fundamental aspects to applied sciences. This report surveys studies of DNA and nucleic acid adsorption to gold surfaces, development of immunoassays, electron transfer between metal electrodes and proteins, and protein–protein interactions. Because signal enhancement in SEIRA uses surface properties of the nano-structured metal, the biomaterial must be tethered to the metal without hampering its functionality. Because many biochemical reactions proceed vectorially, their functionality depends on proper orientation of the biomaterial. Thus, surface-modification techniques are addressed that enable control of the proper orientation of proteins on the metal surface.
Introduction
The seminal discovery of surface-enhanced Raman scattering (SERS) in the early 70s opened the field of surface-enhanced spectroscopy [1, 2]. The phenomenon has subsequently also been observed at longer wavelengths and, ultimately, led to the realization of surface-enhanced infrared absorption spectroscopy (SEIRAS) [3]. Several reports appeared in the 90s on both practical and theoretical aspects of the phenomenon [4–6]. SERS and SEIRAS have lately received attention in the field of biochemistry and biophysics, because of growing interest in bio-nanotechnology [7]. Typical approaches of bio-nanotechnology are constructions of hybrid devices in which bio-molecules, e.g. DNA or proteins, are combined with a solid sensing and/or actuating substrate, for example as an electrode. With this architecture the whole bandwidth of biological functions can be addressed by exchange of signals with the sensor/actuator. The concept of the hybrid bio-device is key to the development of biosensors for DNA or proteins, or for immunoassays on a chip, etc. This concept is, moreover, valuable not only for technological progress but also for fundamental studies on proteins and other biologically active materials. Triggering the properties of the adsorbate on the substrate enables functional studies of biomolecules. A critical issue in the design of such a device is assessment of the interface between biomaterial and substrate in which the essential signal relay between the two different materials occurs. This signal relay comprises only small amounts of monolayer molecules at the interfaces which are difficult to detect by conventional Raman and IR techniques. Spectroscopic distinction from the strong background of the bulk is also difficult. This obstacle is overcome by exploiting the “optical near-field effect” of surface-enhanced spectroscopy in which the signal enhancement is restricted to the interface. Characteristic of vibrational techniques, SERS and SEIRA provide a wealth of molecular information on the level of a single chemical bond.
SERS and SEIRA are complementary techniques, and each has its own advantages and disadvantages. SERS takes advantage of its enormous enhancement factor (of the order of 106–1012). The strongest enhancement occurs as a result of the resonance condition if the biomolecule carries a chromophoric co-factor. The fluorescence which often accompanies this may render detection of the Raman spectrum difficult, however. Although the latter is not a problem with SEIRA, the surface-enhancement is only modest (∼101–103). SEIRAS probes almost all bands of the adsorbed species as long as the vibrational mode includes a dipole component perpendicular to the surface (surface-selection rule) [5]. Although the enhancement factor of SEIRAS is smaller than that of SERS, the cross-section for IR absorption is several orders of magnitude higher than the corresponding Raman cross-section. Thus, the modest enhancement of SEIRAS may be sufficient for many applications.
To study the functionality of proteins by IR spectroscopy, the difference technique has provided an unprecedented amount of molecular information [8–10]. The IR spectrum of a protein is recorded in one state—often the resting state—and subtracted from the IR spectrum of another state—an active state or reaction intermediate. The difference spectrum then contains only the vibrational bands associated with the transition from one state to the other. All of the other vibrational bands are cancelled which drastically simplifies interpretation of the vibrational changes. As a consequence, the amplitudes of the difference bands are much smaller than the absorption bands of the entire protein (difference bands may be smaller by a factor of 10−4, depending on the size of the protein). Resolving the small difference bands requires acute spectroscopic sensitivity, in particular when surface-enhanced infrared difference spectroscopy (SEIDAS) is performed on a protein monolayer.
In this report, we review applications of SEIRA in which biochemical processes were studied. Because SEIRAS was introduced to the field of biomolecules only recently, we consider it worthwhile to start with practical aspects of the method.
Experimental considerations
Preparation of thin metal-film substrates
Preparation of the thin metal film is the critical part of a successful SEIRA experiment. Enhancement by SEIRA is very dependent on the size, shape, and particle density of the selected metal-island film. These properties are easily affected by the experimental conditions during film fabrication, e.g. rate of film deposition, type of the substrate, the substrate temperature, etc. [11].
SEIRA-active metal islands are usually prepared by high-vacuum evaporation of the metal on to a supporting substrate. Metals such as Au, Ag, Cu, and Pt are vapor-deposited by Ar sputtering, electron-beam heating, or resistive thermal heating of a tungsten basket. The thickness and the rate of deposition are monitored by use of a quartz crystal microbalance (QCM). Controlling of the deposition rate is essential for optimum enhancement. Slow deposition (0.1 nm s−1 or less for deposition of Au or Ag on Si or CaF2) generally results in greater enhancement [11]. This condition also depends on the type of metal, the type of substrate, and the metal film thickness, however, and must therefore be optimized for the system being used. As the morphology of the metal film affects the extent of surface enhancement, templates such as a periodic particle-array film prepared by nanosphere lithography have been used [12, 13]. This approach not only increases the enhancement factor but the reproducibility of signal enhancement will enable quantitative SEIRAS.
Although vacuum evaporation is routinely used, the equipment is costly and not readily available. An alternative means of forming a metal thin film is by chemical (electroless) deposition. Stable SEIRA-active thin films of Au, Pt, Cu, and Ag have been reported on Si or Ge substrates [14–17]. The procedure for preparing a thin Au film on a silicon surface is described below:
The surface of the Si is covered with 40% w/v NH4F for a few minutes (typically 1–3 min) to remove the oxide layer and to terminate the surface with hydrogen.After rinsing with water, a freshly prepared 1:1:1 mixture of:
0.03 mol L−1 NaAuCl40.3 mol L−1 Na2SO3+0.1 mol L−1 Na2S2O3+0.1 mol L−1 NH4Cl, and2% w/v HFis put on the Si surface for 60–90 s.Although a shiny Au film is formed, the Au surface may still be contaminated with thio compounds from the plating chemicals. These are removed by electrochemical cycling of the potential between 0.1 and 1.4 V in 0.1 mol L−1 H2SO4 until the cyclic voltammogram of polycrystalline gold appears (broad oxidation peak above 1.1 V and a sharp reduction peak at 0.9 V relative to the SCE). One can, instead, apply a dc voltage of +1.5 V between the Au film and the counter electrode (e.g. a Pt wire) for ca. 1 min.
Atomic force microscope (AFM) images of the chemically deposited Au film reveals an island structure similar to that of the vacuum-evaporated Au films, albeit with somewhat larger average diameter of the metal islands [16, 17]. Another advantage of the chemical method is the stronger adhesion of the deposited metal layer to the substrate. This property helps significantly when long-term stability of the metal film is required, as is typical for preparation of biomimetic devices (vide infra).
An interesting option is the use of colloidal gold nano particles [18, 19]. Colloidal gold is prepared by reducing tetrachloroauric(III) acid with sodium citrate. It is also commercially available in different particle sizes. Typically, 10–50 nm colloidal gold is chosen. A major difference from the metal thin-film method is that the sample is attached to the colloidal gold suspension before measurement. The colloidal gold is then collected on an optical substrate by filtration or by centrifugation. The sample/colloid gold is measured either in the transmission configuration (with an IR card) or dried on an ATR prism.
Removal of the metal film from the supporting substrate
The metal film prepared by vacuum-evaporation is usually poorly adhesive. It is easily wiped off with ethanol or acetone. A metal film prepared by the chemical deposition method adheres much more strongly, and hence may not be removed by wiping or even by polishing with aluminium powder. Such metal films can be dissolved by immersion in a boiling solution of a 1:1:1 mixture of HCl (32%), H2O2 (30%), and H2O.
Geometry and optical configuration
The most widespread optical arrangement employs the so-called metal underlayer configuration (sample/metal film/supporting substrate; Fig. 1a). IR-transparent materials are usually used as supporting substrates. Highly refractive materials, for example Si, Ge, and ZnSe, are suitable for internal reflection optical geometry (Fig. 1a, (ii)) and CaF2 and BaF2 are more suitable for transmission geometry (Fig. 1a (i)). For the former, relatively thick metal films (in the range of ten to several hundred nanometers) can be used whereas for the latter geometry the thickness of metal film should be kept to less than 10 nm, because the island structure starts to merge at higher thickness. As a result, the metal film is no longer transmissive [11, 20].
Fig. 1Schematic diagram of the optical configuration of SEIRAS. (a) Metal underlayer configuration. (b) Metal overlayer configuration. The arrows denote the optical pathway of the IR beam in (i) transmission, (ii) attenuated total reflection, and (iii) external reflection geometry. (c) Spectro-electrochemical cell for SEIRA spectroscopy
For internal reflection geometry (Kretschmann attenuated total-reflection geometry), half-cylindrical, half-spherical, or trapezoidal prisms are commonly used. The former two types are advantageous for optical reasons, because the position of the focus on the metal film is not affected by changes in the angle of incidence of the IR beam. Si is commonly used as reflection element, because of its high chemical stability. One disadvantage is that the available spectral range is then limited to >1000 cm−1. Although use of Ge enables use of a wider spectral window (>700 cm−1), it is not suitable for electrochemical experiments at potentials above 0.0 V (relative to the SCE) in acidic solution (pH<4.0), in which it starts to dissolve. Although Ge matches well with Ag or Cu, combination with Au may cause a decrease in the enhancement factor, because of the formation of a Ge–Au alloy at the boundary which strongly affects the morphology of the island structure of the film.
Non-IR-transparent material, for example glass, polymers, carbon, and metal, can be used as a substrate only with external reflection which uses the metal overlayer configuration (metal particle/sample/supporting substrate, Fig. 1b). In this configuration the thin metal layer (ca. 4–7 nm) is directly evaporated on the sample/support surface. It should be noted that poorly reflective material is optically favorable, because of reduced distortion of band shape in the corresponding SEIRA spectrum [21, 22]. This configuration is advantageous for detection in trace analysis of a sample adsorbed on glass or a polymer [22]. It is pointed out, however, that external reflection IR spectroscopy is not very useful for functional studies of biomaterial, because of the required presence of bulk water that strongly absorbs the IR probe beam.
Chemical modification of the metal film surface
It is crucial to chemically modify the bare metal if direct contact with the metal surface hampers the structure and function of the biomaterial. Strong interaction forces may even induce denaturation of proteins, because their secondary structure is very dependent on weak hydrogen-bonds between amino acids. The use of a chemically modified electrode (CME) is an approach used to tackle these obstacles [23]. The surface of the metal electrode is modified by heterobifunctional crosslinkers that comprise:
a thiol group that is spontaneously adsorbed by the metal electrode;a spacer group with different lengths of alkyl chain; anda functional headgroup pointing toward the bulk solution.
The CME surface can be conveniently prepared by the so-called “SAM (self-assembled monolayer) method” in which the SEIRA-active metal substrate is immersed in a solution containing the crosslinker molecule (normally for between 10 min and 2 h, depending on size of the molecule). The SAM of the crosslinker is formed spontaneously by quasi-covalent bonding between the sulfur and the metal surface. The substrate is then thoroughly rinsed with the solvent so that a SAM of the crosslinker remains on the metal substrate.
Adsorption of the protein by the chemically modified electrode (CME) is a suitable model for protein–protein interaction. By varying the properties of the functional headgroup it is possible to mimic the specific conditions of the substrate during the protein–protein or protein–ligand interaction process. For example, use of a carboxyl headgroup mimics the side-chain terminus of Asp or Glu. The negatively charged carboxyl headgroup can specifically interact with positively charged amino acids, for example Lys, His, and Arg residues, on the protein surface. Another approach is to exploit the specific interaction of Ni2+-chelated nitrilotriacetic acid (NTA) with a sequence of histidine residues genetically introduced into the target protein (His-tag) [24, 25]. Details of this approach are given below.
Applications
Studies of nucleic acids and DNA
SEIRAS studies on nucleic acid bases have provided information about the adsorption and orientation of thymine on silver island film [26], and of cytosine [27] and uracil [28] on gold electrodes. These experiments have been expanded to studies of the hydrogen-bonding interaction between complementary bases (adenine (A)–thiamine (T) and guanine (G)–cytosine (C)) as model systems of DNA and RNA. Sato et al. used SEIRAS to study base-pairing between thymidine and 6-amino-8-purinethiol, a thio-derivatized adenine, immobilized on a gold electrode surface [29]. They observed a characteristic thymidine band at 1571 cm−1 adsorbed on the adenine-modified surface by hydrogen-bonding. This base-pairing occurs at potentials higher than 0.1 V (relative to the SCE), at which the N1 of adenine is deprotonated and orientated toward the solution. This result implies that hydrogen-bonding between the base pairs can be controlled by the applied electrode potential.
As an interesting extension of the method, SEIRAS has been used as a diagnostic criterion in cancer research [30, 31]. Although the reported enhancement factor of 3–5 only modest [31], the enhanced bands are impossible to observe with conventional IR spectroscopy but are crucial for determining the properties of nucleic acids of tumor tissues and their interaction with anticancer drugs.
Immunoassays based on SEIRAS
There is substantial interest in the development of biosensors in which the biological component is associated with a transducer to provide a means of detecting changes in the biological component. Most current biosensors consist of an enzyme or an antibody which interacts with the substrate or the respective antigen. The enzymes or antibodies are usually immobilized on a platform and the interaction between the enzyme and the substrate (or the antibody and the antigen) is monitored. Biosensors based on surface plasmon resonance (SPR) have received considerable attention in recent years. In this method, the biomaterial is immobilized on the surface of a metal-film-covered optical prism (ATR–Kretschmann configuration), i.e. the same optical principle is applied as with SEIRAS. The advantage of SEIRAS compared with SPR is that the chemical information derived from the vibrational spectrum identifies the nature of the adsorbed species yet the sensitivity of SEIRAS is comparable with that of SPR. The sensitivity of SPR is poor when the refractive index of the adsorbed species is close to that of the solvent, as it is for small organic molecules dissolved in an organic solvent. SEIRAS detects the individual vibrational modes of functional groups of the adsorbate, and the S/N ratio does not depend on the type of solvent if the vibrational bands of the solvent do not overlap with those of the adsorbate. SEIRAS can, moreover, be used to detect even minute structural changes that occur in the adsorbed layer during the adsorption process.
Brown et al. have applied SEIRAS to biosensor analysis for determination of antibody–antigen interactions [32]. In this experiment, antibodies for Salmonella (anti-SAL) were immobilized on a gold surface deposited on a silicon wafer. After taking the spectrum of anti-SAL, this “dipstick” sensor was immersed in a solution containing the antigen (SAL). The SEIRA spectra of anti-SAL without SAL has characteristic antibody peaks at 1085 and 990 cm−1. Addition of SAL results in an additional band at 1045 cm−1 which was assigned to the P–O stretching vibration of the phospholipid in the cell wall, which indicates the presence of SAL in the solution.
Initially, the analyte adsorbed by the “dipstick” sensor was probed by external reflection SEIRA spectroscopy. Later, the authors developed a new method for SEIRAS in which they used a colloidal gold surface as adsorption platform [19]. The colloidal gold–antibody–antigen complexes are left to assemble in solution, taking advantage of the tight binding of the antibodies to colloidal gold which stabilizes the colloid solution. When the sample has been assembled the complexes are collected, either by filtration on a porous polyethylene membrane [19] or by centrifugation on an ATR substrate [18], and are then readily mounted in the FTIR spectrometer. Both “dipstick” and “colloidal gold” furnish similar spectral quality, although the enhancement of the latter approach is not mentioned. The colloidal gold system is more convenient and less expensive means of preparation than coating by sputtering. Filtration of the colloidal particles on disposable IR cards is also a rapid, easy, and cost-effective means of producing a SEIRA substrate which operates in transmission mode and does not require complicated optical arrangements.
SEIRAS to probe protein functionality
The metal used for surface enhancement, can also be used as an electrode. The enzymatic reactions of many biological systems, especially those of membrane proteins, are driven by an electrochemical gradient across the cell membrane. Such a system can be artificially reproduced on an electrode surface to mimic the physiological properties of a biological membrane.
Electrochemically induced oxidation and reduction of a monolayer of cytochrome c (Cc), a protein that mediates single-electron transfer between the integral membrane protein complexes of the respiratory chain, is the model system for electron transfer within and between proteins [33]. Electrons are directly injected to and/or withdrawn from Cc after proper contact has been established with the electrode by means of a suitable surface modifier. Proteins can be attached to such a chemically modified electrode (CME) by electrostatic attraction or covalent interaction. Figure 2 depicts potential-induced difference spectra of Cc that has been electrostatically adsorbed by different types of CME. The positive and negative peaks are indicative of conformational changes associated with the transition from the fully oxidized to the fully reduced state. Details of band assignment have been published [14]. The difference spectra reveal subtle changes of the secondary structure induced by rearrangement of the hydrogen-bonded network among the internal amino acid side-chains surrounding the heme chromophore. Note that the peak positions of the observed Cc bands do not depend on the type of CME layer whereas the relative intensities are strongly dependent on the CME. The former suggests that the internal conformational changes of Cc are not affected by interaction with the modifiers. The latter observation is attributed to the different surface structure, i.e. the orientation or position of the Cc relative to the CME underlayer [14].
Fig. 2Potential-induced redox difference spectra of a cytochrome c monolayer adsorbed on a variety of chemically modified electrodes: (a) mercaptopropionic acid, (b) mercaptoethanol, (c) cysteine, (d) dithiodipyridine. Minor spectral contributions from the surface modifier have been subtracted to selectively reveal the vibrational spectra of the adsorbed cytochrome c [14]
Studies of molecular and protein recognition
The acute sensitivity of SEIRAS is particularly useful when the technique is applied to studies of membrane proteins. Handling of the membrane proteins usually requires great care, because of their sensitivity to degeneration as soon as they are separated from the native lipid bilayer. The large size of the proteins also makes it difficult to control their orientation.
A successful strategy for immobilization of membrane proteins is to attach the purified protein, by using the selective affinity of a genetically introduced histidine tag (His-tag), to a nickel-chelating nitrilotriacetic acid (Ni-NTA) monolayer (SAM) self-assembled on a chemically modified gold surface. The lipid environment of the surface-anchored membrane protein is subsequently restored by in-situ dialysis of the detergent around the amphiphilic membrane protein. This approach results in orientated immobilization and reconstitution of the native matrix, which enhances the stability of the membrane protein and restores full functionality.
The success of the method has been demonstrated by use of cytochrome c oxidase (CcO) [24, 25]. Recombinant CcO (solublized by detergent) from Rhodobacter sphaeroides was immobilized on the stepwise-formed Ni-NTA SAM bound to the gold surface. It is advantageous to follow each surface-modification step by in-situ SEIRAS, which ensures qualitative and quantitative control of each reaction step. The protein is subsequently embedded in the lipid layer by removing the detergent by addition of Bio-Beads. SEIRA spectra reveal the increase of several lipid bands during the reconstitution without any dissociation of protein from the surface. Atomic-force microscopy (AFM) provides direct evidence of the formation of the lipid bilayer. Spots of size ∼7 nm appear in the AFM image; this is in accordance with the diameter of a single CcO molecule [34]. It is remarked that the same approach can be used to bind CcO to a rough Ag surface. Integrity of the native structures of the heme cofactors (heme a and heme a3) was shown by surface-enhanced resonance Raman spectroscopy (SERRS) [35, 36].
Full functionality of the lipid-reconstituted CcO electrode is demonstrated by the fact that a catalytic current resulting from reduction of oxygen, the native property of CcO, is observed when an electron is donated by the adsorbed Cc. In such an experiment orientation of the CcO is controlled by the position of the His-tag on either side of the membrane surface CcO. With molecular genetic techniques, the His-tag is introduced either in the C-terminal tail of subunit I or in the C-terminus of subunit II. By binding CcO through the respective His-tag, the former orients CcO such that the binding site of Cc is exposed to the bulk solution. The latter orientation obstructs the binding site for Cc, because of the barrier imposed by the lipid bilayer. Indeed, SEIRAS, in combination with electrochemistry, reveals that Cc binds and initiates the catalytic reaction of CcO only when the Cc binding site faces the bulk aqueous phase and that Cc does not interact with the oppositely oriented CcO [24, 25].
Interestingly, the electrochemically induced redox difference surface-enhanced infrared difference absorption (SEIDA) spectrum of the Cc–CcO complex is remarkably similar to that of Cc adsorbed on a carboxy-terminated SAM (mercaptoundecanoic acid, MUA) (Fig. 3c and d). It is noted that SEIDA spectra of Cc are sensitive to the properties of the terminal headgroup of the SAM that it interacts with [14]. The similarity of the spectra of Cc–CcO and Cc–MUA suggests a preponderance of carboxylate residues at the physiological docking site of Cc, i.e., those of the side-chains of aspartate or glutamate units. Ferguson-Miller et al. have, indeed, identified residues Glu148, Glu157, Asp195, and Asp214 (all in subunit II of CcO from R. sphaeroides) as the major interaction partners of Cc [37].
Fig. 3Potential-induced IR difference spectra of: (a) cytochrome c bound to a monolayer of cytochrome c oxidase tethered to a gold surface via His-tag/Ni-NTA interaction; (b) tethered monolayer of cytochrome c oxidase alone; (c) difference between (a) and (b) which recovers the vibrational contribution from cytochrome c only; (d) cytochrome c adsorbed to a monolayer of mercaptoundecanoic acid
The same strategy has recently been applied to immobilization of photosystem 2 (PS2) on an Au surface with the purpose of developing a semi-artificial device for production of hydrogen by photosynthetic oxidation of water [38]. In this report, SEIRA was used to determine the adsorption kinetics of PS2 on the Ni-NTA-modified Au surface. On illumination of the surface-bound PS2 a photocurrent was generated. The action spectrum corresponds to the absorption spectrum of PS2, indicating that the observed photocurrent is caused by photoreaction of PS2.
This methodology is a general approach for immobilization of proteins, because the introduction of affinity tags is routine with modern genetic techniques. Other tags beyond the His-tag may also be an option. Thus, orientational control of protein adsorption on a solid surface can be conveniently achieved. An oriented sample is mandatory when the vectorial function of membrane proteins is addressed. Many membrane proteins are asymmetric in their functionality, because they translocate ions or solutes preferentially in one direction or because their stimulant, e.g. ligand, binding partner protein, membrane potential, etc., affects the protein from one side only.
Summary and outlook
Despite the accomplishments reported in this article, studies of biomaterials by SEIRA is still in its infancy. Potential-induced difference spectroscopy using SEIRA is a promising possibility for study of the functionality of proteins. The stimulus in such studies is not limited to the electric trigger, as reviewed here, but can also be light illumination, temperature jump, or chemical induction. Many protein functions can be addressed by these means and the mechanism of action of these molecular machines may be resolved down to the level of a single bond.
The sensitivity may not be sufficient for functional difference spectroscopy on any protein with SEIDAS, however. As the enhancement factor for SEIRA is modest compared with that for SERS, optimization of the enhancement by proper design of the metal surface is crucial. Although enhancement factors are usually in the range 10–100, factors as high as 1000 have sometimes been reported [16]. To obtain the latter enhancement reproducibly, however, development of homogeneous island metal film preparation under strict topological control will be mandatory.

electron transfer
protein
self-assembled monolayer
membrane
ftir