A new approach to the assessment of lumen visibility of coronary artery stent at various heart rates using 64-slice MDCT

Coronary artery stent lumen visibility was assessed as a function of cardiac movement and temporal resolution with an automated objective method using an anthropomorphic moving heart phantom. Nine different coronary stents filled with contrast fluid and surrounded by fat were scanned using 64-slice multi-detector computed tomography (MDCT) at 50–100 beats/min with the moving heart phantom. Image quality was assessed by measuring in-stent CT attenuation and by a dedicated tool in the longitudinal and axial plane. Images were scored by CT attenuation and lumen visibility and compared with theoretical scoring to analyse the effect of multi-segment reconstruction (MSR). An average increase in CT attenuation of 144 ± 59 HU and average diminished lumen visibility of 29 ± 12% was observed at higher heart rates in both planes. A negative correlation between image quality and heart rate was non-significant for the majority of measurements (P > 0.06). No improvement of image quality was observed in using MSR. In conclusion, in-stent CT attenuation increases and lumen visibility decreases at increasing heart rate. Results obtained with the automated tool show similar behaviour compared with attenuation measurements. Cardiac movement during data acquisition causes approximately twice as much blurring compared with the influence of temporal resolution on image quality.
Introduction
The introduction of multi-detector computed tomography (MDCT) has permitted the non-invasive visualisation of coronary arteries with sufficient temporal and spatial resolution. Moreover, MDCT has been used to research the assessment of coronary artery stent patency and discrimination between the presence of in-stent stenosis. Re-stenosis occurs in a substantial amount of patients which have been treated with stent implantation [1]. It has been shown that no direct visualisation of coronary in-stent re-stenosis is feasible using four-slice MDCT due to partial volume effects and beam hardening caused by metal artifacts of the stents [2–6]. Recently it has been shown that despite some limitations 16-slice MDCT is sufficiently useful for the assessment and detection of in-stent restenosis in patients with a high accuracy in comparison with conventional coronary angiography (CAG) [7]. With the emergence of 40 and 64-slice MDCT systems the assessment of lumen visibility and diagnostic accuracy of in-stent restenosis has been improved considerably with respect to the 16-slice MDCT systems [8, 9]. The artificial lumen narrowing shows a decrease of approximately 5% and the CT attenuation is reduced by approximately 35 HU [10].
Visualisation of the in-stent lumen with 16-slice MDCT allows for the assessment of coronary artery stent patency based on the measured enhancement of contrast [11]. It has been shown that the best diagnostic quality images are obtained with a sharp edge-enhancing reconstruction kernel, although the quality of the obtained images is hampered by increased noise levels compared with standard kernels [11–13]. The results originate from the comparison of the lumen visibility images pairs, which are reconstructed with different reconstruction kernels. The apparent lumen width is measured using a digital measuring tool included in the visualisation software. This method, however, is subjective to the observer and it is difficult to determine the exact boundary of the stents in the gradient part of the image. In addition, the image quality of the stents is very sensitive to the movement of the heart and image quality diminishes at heart rates higher than 75 beats per min (bpm) [14, 15].
In previous studies, a patient population was used to investigate image quality of coronary artery stents at high and low heart rates on four- and 16-slice MDCT [14, 15]. To our knowledge no systematic study has been published about the image quality of coronary artery stents on 64-slice MDCT. In this study, we therefore aimed at describing the correlation of image quality of coronary artery stents and heart rate using 64-slice MDCT in an ex-vivo setting by using an anthropomorphic moving heart phantom.
The purpose of our study was to assess the lumen visibility of coronary artery stents at various heart rates with an automated objective method using a moving heart phantom on a 64-MDCT system.
Theory
Coronary imaging is hampered by motion artefacts originating from the relative large velocity scale of the coronary arteries within the cardiac cycle compared with the temporal resolution of the MDCT acquisition technique [16]. This movement results in motion artefacts in the reconstructed images, expressed as blurring. The amount of blurring depends on (1) the amount of movement of the imaging target MS and (2) the acquisition time (AT). The amount of movement of the coronary artery is a function of the heart rate (HR) of the patient. The temporal resolution of a MDCT system is a function of the reconstruction method used and HR [17, 18]. This means that the resulting image quality (IS) can be expressed as
in which MS describes the amount of movement of the coronary artery as a function of heart rate, AT describes the acquisition time as a function of heart rate and g is a weight factor.
The heart rates can be ranked from low to high. With this ranking, a relative grading can be made for the function MS. In addition, the acquisition times can be ranked from high to low. With this ranking, a relative grading can be made for the function AT. The results of this grading are shown in Electronic supplementary material (ESM) Table 1, where a high score implies a high image quality. Since there is no cardiac movement at 0 bpm, this heart rate was graded with the highest score for both factors.
Materials and methods
Nine commercially available stents were used and stent dimensions were measured using a digital calliper. The stent properties are summarised in ESM Table 2.
The stents were inserted into plastic tubes and the tubes were filled with contrast fluid (Visipaque 320, Amersham Health, Little Chalfont, UK) diluted to an attenuation value of approximately 200 HU simulating contrast enhanced blood. The tubes were wrapped in horse fat with an attenuation value of −100 HU to simulate the in vivo situation of epicardial fat (Fig. 1left).
Fig. 1Left: schematic figure showing the experimental setup of the contrast fluid filled tube surrounded by horse fat in the axial plane. The numbers depict the HU values of the different relevant structures. Right: moving anthropomorphic heart phantom with artificial coronary arteries
Next, the stents were attached to a silicon, moving, anthropomorphic heart phantom (Limbs & Things, Bristol, UK) with artificial coronary arteries (Elastrat, Geneva, Switzerland) (Fig. 1right). The phantom is connected to a respirator, which was used to control the heart rate. The heart rate was set at values of 0, 50, 60, 70, 80, 90 and 100 bpm.
Measurements have been performed on a 64-detector CT-scanner (Somatom Sensation 64, Siemens, Forchheim, Germany). The scan parameters were 120 kV, 120 mAs, 370 ms rotation time and 64 × 0.6 mm collimation.
Image reconstruction was performed using a sharp convolution kernel (Siemens B46f) with a reconstruction slice width of 0.75 mm and a 0.5-mm increment. ECG-gating was used during scanning and the images were retrospectively reconstructed at 25% of the RR-interval corresponding to maximum expansion of the heart phantom.
Afterwards the stents were visualised on an Aquarius workstation version 3.3 (Terarecon, San Mateo, USA). We used two independent methods to asses the lumen visibility of the stents in the reconstructed images. In the first method, the average HU-value in the stent lumen was manually measured with a standard region of interest (ROI) technique. A window level/width of 300/800 was used for visualisation with an average ROI of 5.0 mm2 and 3.9 mm2 in the longitudinal and axial plane, respectively (Fig. 2). The lumen measurements were used to calculate the mean CT attenuation in the stent lumen. In the second automated method, screenshots were taken from every stent in the longitudinal and the axial plane with a window level/width of 512/2,048. The screenshots were used to perform the automated lumen visibility measurements using a dedicated tool.
Fig. 2Measuring the CT attenuation in the lumen. Left: measurements in the axial plane, Lekton Motion at 60 bpm. Right: measurements in the longitudinal plane, Lekton2 at 90 bpm. Calculated by the Aquarius workstation are mean HU-value, standard deviation and area of ROI
The automated lumen visibility measurements were performed with an Automatic Stent Visibility Calculation (ASVC), a custom-build Matlab tool (The Mathworks, Natick, USA). The tool constructs the average attenuation profile through the stent in the longitudinal and axial plane. The calculation of the average attenuation profile in the longitudinal plane is done as follows; attenuation profiles are calculated from position A to B for every image line perpendicular to the stent central axis, where the position A and B are determined by the user (Fig. 3left). The average longitudinal profile is calculated from the individual longitudinal profiles. The calculation of the average attenuation profile in the axial plane is doen as follows: after determination of the centre of the stent by the user, 180 attenuation profiles are calculated evenly distributed around the centre (Fig.3right). The average axial attenuation profile is calculated from the individual axial profiles.
Fig. 3Stent images (left: Jostent Stent Graft at 60 bpm; right: Taxus at 80 bpm) showing the positions of the individual profiles for calculation of the average stent profile in the longitudinal plane (left) and the axial plane (right)
The profile depth of the lumen (D), the full width at half maximum (FWHM) and the total width (TW) are calculated from both average profiles (ESM Fig. 4).
We define the percentual width (Wp) as a percentage of the FWHM and TW
The percentual width is used instead of the absolute width to compensate for different magnifications of the stent images.
From the profile depth (D) and Wp, the lumen visibility (LV) is defined by
If the left and right edge of the attenuation profile are at different heights, D is calculated from the average height.
The stent images at individual heart rates were ranked according to their CT attenuation (7=least attenuation, 1=most attenuation), FWHM (7=largest width, 1=smallest width) and D (7=largest depth, 1=smallest depth) in the axial and longitudinal plane.
The difference between the CT attenuation values in the axial and longitudinal plane were compared using the Wilcoxon test at a significance level of 5%. The correlation between heart rate and CT attenuation, and the correlation between heart rate and LV, were analysed by calculating the Spearman rank correlation coefficient at the significance level of 5%.
Results
CT attenuation in the stent lumen
The results for the HU-value measurements are summarised in ESM Tables 3 and 4 for the longitudinal and axial plane, respectively. The CT attenuation in the stent lumen was calculated for each heart rate and the results are shown for the longitudinal and axial plane in ESM Figs. 5 and 6, respectively. The error margins have been omitted to improve readability of both figures.
All stents showed increased attenuation with increasing heart rate in the longitudinal plane. The CT attenuation in the longitudinal plane showed an increase from 0 to 100 bpm between 75 and 221 HU for the Taxus and Bx Sonic stent, respectively. The average increase was 139 ± 49 HU. The average Spearman coefficient for all stents was 0.66.
All stents showed increased attenuation with increasing heart rates in the axial plane. The CT attenuation in the axial plane showed an increase from 0 to 100 bpm between 76 and 252 HU for the Bx Sonic, Multi-link Zeta and the Jostent, respectively. The average increase was 148 ± 69 HU from 0 to 100 bpm. The average Spearman coefficient in the axial plane was 0.58. The average increase of CT attenuation over both planes was 144 ± 59 HU.
Using the ASVC, the FWHM and depth of the stent profile were determined. The results for the FWHM are summarised in ESM Tables 5 and 6; the results for the profile depth are summarised in ESM Tables 7 and 8. The standard deviation for every measurement is given in parentheses.
The LV was calculated using equations 2 and 3 at each HR using the measured width FWHM and depth D. The data are plotted in ESM Figs. 7 and 8 for the longitudinal and axial plane, respectively, and have been fitted to a line. Error margins have been omitted to improve readability.
All stents showed decreasing LV with increasing heart rate in the longitudinal plane. The LV decreased from 0 to 100 bpm between 7.5% and 48.6% for the Taxus and Cypher stent respectively. The average decrease in LV was 26.8 ± 13.4%. The average Spearman coefficient was 0.47.
All stents showed decreasing LV with increasing heart rates in the axial plane. The LV decreased from 0 to 100 bpm between 19.8% and 48.8% for the Lekton and Multi-link Zeta stent respectively. The average decrease in LV was 30.9 ± 10.4%. The average Spearman coefficient was 0.58. The average decrease of LV over both planes was 29 ± 12%.
Image scoring
The measurements are shown in ESM Fig. 9 after grading and averaging as described in the methods section. From a least squares fit, we found an optimal value of g = 0.63 ± 0.06.
Discussion
Coronary artery stenting is a successful method to treat stenosis. However, re-stenosis in the stent may happen after the procedure. This makes check-ups a necessary procedure to perform [19, 20]. MDCT is one the candidates for visualisation of the lumen of coronary artery stents. Although the results look promising, the image quality is hampered by cardiac movement and metal artefacts [21, 22]. This may result in blurred images and an exaggerated thickness of the stent struts compromising the visibility of the lumen. The 64-MDCT scanner has increased spatial and temporal resolution compared with previous CT scanner generations [23, 24] and increased LV of coronary stents is expected with these new scanners. Although 64-MDCT imaging of coronary artery stents show an improved image quality with respect to previous CT scanners, the images still show blooming artefacts and blurring [9].
The apparent width is measured in a generally accepted method to assess the stent lumen, but this method is very subjective to the user [25]. In contrast, our method, developed in this study to analyse the stent lumen, is an automated method. It enables the possibility of a systemic evaluation of the stent lumen at various heart rates. The in vivo conditions were approached as much as possible using contrast fluid and fat.
Influence of increasing heart rate
To our knowledge there have been no previous studies systematically investigating the relation between heart rate and image quality of coronary stents using 64-MDCT. There are, however, some studies with 16-slice MDCT assessing coronary arteries, which concluded that for successful cardiac imaging a heart rate below 75 or 70 bpm is necessary [14, 15, 26–29]. In a study with 40-MDCT by Gaspar et al. [8], patients were given an oral beta-blocker if their heart rate was higher than 65 bpm, and in a study with 64-MDCT, patients were given beta-blockers if their heart rate was higher then 70 bpm [30]. Ferencik et al. [23, 30] concluded that a low heart rate is an important prerequisite for excellent image quality.
ASVC
Two different methods were used to assess the relationship between heart rate and image quality of coronary stents. The first method, the CT attenuation measurement, is a commonly used method. The second method, the ASVC technique, is a new approach. Both methods show a negative correlation between image quality and heart rate as expressed by the linear fits. The fits, however, show small significance. This small significance can be explained by the fact that the image quality does not depend entirely on heart rate, which shows a linear behaviour, but also on temporal resolution, which shows a non-linear behaviour, as can be seen from ESM Fig. 9. Despite the poor quality of the fit, the results obtained with this new ASVC method are in agreement with previous studies using generally accepted methods as stated before. Therefore, we conclude that our developed tool is a valid method for the analysis of coronary stent lumen.
Image scoring
The image scoring results (Fig. 9) show a varying resemblance between the theoretical scoring and the measured scoring. This resemblance depends on the proportion g and varies between 0 (IS completely depends on AT) and 1 (IS completely depends on MS). The best resemblance was found for g = 0.63. This implies that the cardiac movement causes almost twice as much blurring in the CT image compared with blurring caused by the limited temporal resolution of the acquisition method. Multi-segment reconstruction (MSR) has been developed to further increase the temporal resolution [6, 18, 32]. The data acquisition at a rotation time of 370 ms and a HR > 65 bpm has been performed during two consecutive heart cycles using a two-segment MSR. At heart rates of 70 and 90 bpm, the data acquisition is approximately evenly distributed over two consecutive heart cycles. At 80 and 100 bpm, however, the majority of data is acquired in the first heart cycle, and the remaining portion in the second heart cycle. From Fig. 9, we can deduce that for HR of 70 and 90 bpm the measured IS is smaller than the theoretical IS. For HR of 80 and 100 bpm, the measured IS is larger than the measured IS. From this we can conclude that it is beneficial to the image quality to acquire during one cycle and that the MSR technique is not beneficial to image quality. In contrast to this, Halliburton et al. [31] showed that MSR is beneficial for 16-slice MDCT. Two other studies concluded that MSR was not beneficial to the image quality for four-slice MDCT, in accordance with our results [31, 32]. This can be explained by the fact that the coronary artery has to be in exactly the same position in the two heart cycles for the MSR algorithm to work properly. However, in general the starting position of the arteries at the beginning of the heart cycle will not exactly be the same as in the previous heart cycle. This phenomenon will introduce additional motion artefacts which result in extra blurring to the image, as has been shown before by Greuter et al. [33].
Reducing blurring
Cardiac movement and limited temporal resolution will introduce blurring in CT images of coronary arteries. The result for image scoring showed that the influence of cardiac movement is almost twice as large as the influence of the temporal resolution. To reduce blurring, it is therefore more efficient to reduce the heart rate than to increase the temporal resolution.
Limitations
These results have been obtained using a moving heart phantom. It remains uncertain how well these results are applicable to patients. However, a previous study showed that the movement of the heart phantom is a good approximation to the in-vivo situation [18]. Furthermore, in order to approach the in-vivo situation as close as possible, contrast fluid and fat were used, with CT attenuation values equal to those in-vivo.
Screenshots captured with the visualisation software were used to perform LV measurements. A loss of information is expected due to image compression used in the .jpg format of the screenshots. However, a comparison between the screenshot method and direct analysis using dicom files showed no observable difference in results.
Conclusion
We have shown that at increasing heart rates the CT attenuation in the stent increases and the lumen visibility decreases. A new approach to asses the stent lumen has been described which shows similar results to CT attenuation measurements and previous studies. The cardiac movement during data acquisition causes approximately twice as much blurring compared with the influence of temporal resolution. We conclude that a lowering of the heart rate is more beneficial to image quality than using a multi-sector reconstruction technique. In addition, we conclude that it is beneficial to image quality to acquire data in one cardiac cycle.
Electronic Supplementary Material
Below is the link to the electronic supplentary material.
Fig. 4
Figure showinf the profile of the Bx Sonic at 80 bpm with the different variables which are determined by the ASVC; the dotted blue line depicts the error margins of the profile. TW total width; D depth; FWHM=full width half minimum (DOC 56 kb)
Fig. 5
CT attenuation measured in the stent lumen at various heart rates in the longitudinal plane (DOC 76 kb)
Fig. 6
CT attenuation measured in the stent lumen at various heart rates in the axial plane (DOC 77 kb)
Fig. 7
Lumen visibility plotted versus heart rate in the longitudinal plane (DOC 75 kb)
Fig. 8
Lumen visibility plotted versus heart rate in the axial plane (DOC 74 kb)
Fig. 9
The measured IS (green), the theoretical IS for g = 0.63 (blue), the theoretical IS for g = 0 (dotted red), the theoretical IS for g = 1 (dotted orange) (DOC 53 kb)
Table 1
Acquisition times for a 64-MDCT with 370 ms rotation time, number of cycles used and theoretical scores for every HR used in this study. AT acquisition time; MS the amount of movement of the imaging target (DOC 32 kb)
Table 2
Commercial name, manufacturer, material, length and diameter of the stents used in the study (DOC 33 kb)
Table 3
HU-value measurements in the longitudinal plane (DOC 34 kb)
Table 4
HU-value measurements in the axial plane (DOC 34 kb)
Table 5
Results of the measured FWHM in the longitudinal plane (DOC 34 kb)
Table 6
Results of the measured FWHM in the axial plane (DOC 34 kb)
Table 7
Results of the measured profile depth in the longitudinal plane (DOC 34 kb)
Table 8
Results of the measured profile depth the axial plane (DOC 34 kb)

64-slice mdct
heart phantom
coronary stent
image quality


Pathological or physiological erosion—is there a relationship to age?

This conventional literature review discusses whether pathological tooth wear is age dependant. It briefly reviews the components of tooth wear and the prevalence of tooth wear in children, adolescents and adults. The emphasis on terminology relating to tooth wear varies. In some countries, the role of erosion is considered the most important, whereas others consider the process to be a combination of erosion, attrition and abrasion often with one being more dominant. The importance of tooth wear or erosion indices in the assessment and the evidence for progression within subject and within lesions is described. The data from the few studies reporting pathological levels of wear reported in children and adults are discussed, in particular its relationship with age. There is little evidence to support the concept that pathological levels of erosion or wear are age dependant. There is, however, some evidence to suggest that normal levels of erosion or wear are age dependant.
Introduction
There has been considerable interest recently on the epidemiology and pathogenesis of dental erosion. Much of the epidemiology has been investigated in children and adolescents rather than adults and so the validity of any association between severity and age is based on clinical observations seen primarily in these young people [1, 3, 7, 17]. The aim of this paper is to consider and investigate the concept that pathological erosive tooth wear is age dependant.
There is some debate within the dental academic community on the appropriateness of terminology. Many academics recognise the term tooth wear as encompassing erosion, attrition and abrasion. However, other researchers focus upon acid erosion often using the term to describe what others would call tooth wear and use the term erosion in a context which others might not agree. Whilst the definitions of erosion, abrasion and attrition are accepted, the relative importance of these causes is not. Therefore, in this paper both terms are used where appropriate to convey meaning interpreted by many researchers working in this field.
Tooth wear and erosion
The causes of tooth wear are considered to be erosion, abrasion, attrition and possibly abfraction. Traditionally, erosion is associated with loss of enamel and dentine from acids either intrinsic [4] (gastric) or extrinsic (dietary) [29]. Abrasion is more commonly associated with wear from surfaces other than teeth, whereas attrition is wear from tooth to tooth contact [26]. Abfraction is a considered by some to be a component of tooth wear, but so far apart from some laboratory studies, there is little clinical evidence to provide support for its role [9].
However, different countries interpret the aetiologies in different ways [8]. Many European countries focus attention upon erosive tooth wear, whereas in North American countries, abrasion or attrition is more commonly recognised whilst the role of erosion is less understood. In the United Kingdom, although the importance of erosion is acknowledged, the impact of abrasion and attrition is also recognised, and the term tooth wear is more commonly used. When interpreting studies from different parts of the world, some consideration of these subtle differences should be understood. The major difference seems to be the impact of attrition. For many clinical situations, the impact of wear on the teeth is a combination of attrition and erosion particularly on the incisal or occlusal surfaces of teeth (Figs. 1 and 2) [10]. On the buccal or lingual surfaces, erosion is usually more dominant, but the impact of abrasion should not be forgotten. Since it is almost impossible to tell from the appearance of a lesion what is the underlying cause, it maybe more correct to use the term tooth wear. But there are circumstances in which one cause, more commonly erosion, is the dominant feature. Although the definitions of tooth wear and erosion are quite different, they can often be used to describe the same process.
Fig. 1The wear on the occlusal/incisal surfaces of the upper anterior teeth. The wear is caused by a combination of erosion and attrition. The “cupped out or ditched” areas result from the action of acids, whereas the flatter surfaces are caused by attritionFig. 2The wear on the palatal/lingual surfaces of the teeth has been caused by regurgitation erosion. It is unlikely that abrasion or attrition has contributed to the process
Prevalence
Tooth wear indices grade the severity of wear by recording the surface characteristics of teeth with a numerical score. These data can be used to compare wear rates between individuals and between different populations. However, there is currently no agreed consensus on a universally accepted tooth wear index. Some indices [20, 24] appear to be more widely used than others, but even these have undergone many modifications since they were first published [22]. For the most part, indices record wear on all tooth surfaces: cervical, buccal, occlusal/incisal and palatal/lingual [24]. The Smith and Knight index [24] records wear on all surfaces, but no attempt is made to relate the aetiology to the outcome of the wear on the teeth. Smith and Knight and later Robb and Smith estimated acceptable levels of wear in each age cohort [23, 25].
For the majority of the population, any wear on teeth is often limited to enamel, and dentine involvement only occurs in a relatively small proportion of the population [25]. A study by Dugmore and Rock [17] reported that 59.7% of 1,753 12-year-old children had evidence of tooth wear of which 2.7% had exposed dentine and this rose to 8.9% by the age of 14 years. Another study by Bardsley et al. [3] reported that 53% of 2,385 14-year-old adolescents had exposed dentine, but this included assessment of incisal surfaces. This latter study reported higher values in contrast to most other studies [1, 7]. From most of these studies, it is clear that in children and adolescents wear of enamel is common, almost normal, but wear of dentine exposing more than 1/3 of the tooth surface is less so.
Smith and Robb observed that tooth wear in adults was an almost universal experience with up to 97% of all ages experiencing some wear on their teeth with the older aged cohorts, dentine exposure became more common [25]. In their study, Smith and Robb [25] identified that between 5–7% of 1,007 adults had wear that could justify treatment, in all age cohorts. This is the only study published to date, with a large sample, which provides data on tooth wear in all age groups in adults. Other studies have reported the levels in specific age cohorts [20]; Donachie and Walls [14] reported the degree of tooth wear in a sample of 586 adults aged 45 and over in Newcastle, UK and reported no correlation between severity of wear and age. The data available to guide our knowledge on the levels of tooth wear in adults are therefore limited.
Progression of tooth wear
The term pathological tooth wear has been used to describe unacceptable levels of wear [18, 23, 25]. It is usually interpreted as meaning a level of wear that could justify operative treatment. However, finding a scientific way to interpret this concept is challenging. For pathological tooth wear to have meaning, the normal levels in different age groups are required to allow comparison, but the basic information on the pathogenesis of tooth wear is unknown. For instance, it is not known if tooth wear is episodic or continual throughout life. A few authors have reported data from longitudinal studies on adolescents and adults that indicate the development of new lesions [16, 19]. Lussi et al. [20] reported the results of a prevalence study on 26–30- and 46–50-year-old Swiss adults. In a later study, the same group of researchers reported the progression of wear in the same subjects over a 6-year period [19] and observed that wear progressed on the facial, occlusal and cervical surfaces and was more common in the older aged groups. However, the authors made no attempt to define what level of tooth wear was acceptable and what was not. Other studies have reported increase in the incidence of tooth wear in adolescents [16], but longitudinal data remain sparse.
There are no studies that report the progression of the same lesion within the same subject apart from one study which used a tooth wear index to record wear on study models taken from the subject's teeth [5]. They observed that only 7% of tooth surfaces showed any change over a median time of 26 months (IQR 14–50 months). The paucity of data on the severity of tooth wear in different age groups and its progression means it is difficult to be able to predict what is the pathophysiological behaviour of tooth wear.
A number of authors have published methods to measure tooth wear and erosion using profilometric scanners to accurately map teeth [2, 13, 21, 28]. But these methods have reported their findings on relatively small numbers, and the methods are as yet unsuitable for larger studies. Often the time needed to scan a single tooth can take up to one hour and therefore they remain research tools for small studies. However, data from these studies suggest that wear on teeth may progress between 3.7 μm at 6 months [6] and 5.56 μm/month [21] to 18.3 μm/month [28]. There are no data to indicate if particular teeth or tooth surfaces have a greater potential to wear or whether abrasion, attrition or erosion is more important in the progression. Furthermore, correlating this rather limited data to the general population is not possible, and therefore, most researchers rely upon epidemiological studies to record the severity of wear.
Pathological tooth wear
The concept that an unacceptable level of wear for a particular age group was first proposed by Eccles, Smith and others [18, 23, 25]. These and other authors argued that tooth wear continued throughout life as it was part of a normal physiological process. Berry and Poole [11, 12] hypothesised that in common with other mammals, humans have compensatory mechanisms that adapt to wear of teeth. They based their argument on comparative anatomy of mammals, in particular large herbivores, and suggested that tooth wear was beneficial to the efficiency of mastication. A gradual reduction in height and shape of cusps on molar teeth, they argued, led to improved masticatory efficiency. Their hypothesis remains unique and unproven but raises a number of interesting concepts.
Smith and coworkers [23, 27] introduced the term unacceptable levels of wear and later re-termed it as pathological tooth wear. The authors estimated unacceptable levels of wear based on their clinical judgement. Their so-called threshold levels were calculated for different age groups and used as an indicator for the necessity of operative intervention. However, these thresholds were judgements made by the authors, albeit based on clinical experience and previous research [25]. Smith and Robb [25] reported in their paper that the ultimate decision on the threshold values was the clinical experience of the first author. The data were analysed and re-analysed until the results matched the clinical judgement of the authors. Whilst this empirical assessment may have had some value at the time of publication, the ability to reproduce agreed thresholds in subsequent investigations would be challenging and have not been wholeheartedly supported by other researchers. Donachie and Walls [15] argued strongly that the threshold levels set for older age groups were inaccurate as they were based on a relatively small sample and so in their 1996 paper modified values were used [25].
We cannot rely upon the clinical judgement of one or two researchers to define what are pathological levels of tooth wear. Scientists need to have more defined and reproducible values. There are emerging data to suggest that tooth wear is common in all age groups [3, 17, 20, 25]. Smith and Robb [25] reported in their study of 1,007 subjects, aged 16 and over, that within each age cohort a proportion had higher grades of tooth wear [mean 5.1%] than the others. Virtually every other study on the prevalence of tooth wear also reports that a small proportion, generally between 2% and 10%, have higher levels of tooth wear than the majority. If these data are representative of the population at large, it is possible that a percentage of each age cohort has higher than normal levels of wear and this could be termed pathological.
The hypothesis that pathological tooth wear is age related depends on who is assessing the impact. State health care authorities, private insurance schemes, industry, dentists and patients all have different interpretations on what is pathological and what is not. For patients, loss of enamel could be considered pathological particularly if they are focussed upon the appearance of their teeth, whereas dentists may consider intervention is needed when dentine is involved, but their capacity to treat is affected by the limitations of restorative materials. On the other hand, state health care providers may take a much longer term view, with the assumption that a tooth remains functional, if not aesthetic, when operative care is not imperative.
Based on the current data, it is too challenging to suggest that tooth wear is an age-related phenomenon. There is some justification to this hypothesis based on the current data from children, adolescents and adults. Clinical experience suggests that as adults age they tend to develop more wear on the occlusal and incisal surfaces of teeth. It is likely, therefore, that some progression of wear on teeth is age related. However, this assumption needs investigating. Evidence partly from prevalence studies and partly from accurate measurement of tooth wear by profilometry tends to give support to this hypothesis. It must be remembered, however, that the prevalence studies at best report on just over 1,000 subjects. This is extremely small considering the populations involved. Tooth wear indices remain the most convenient and reproducible method to grade severity but are limited by incompatible criteria. It is imperative that a consensus is developed to build a simple and reproducible index, used by researchers so that data on the prevalence of tooth wear, particularly in adults, can be investigated.
Conclusion
The physiological wear of teeth is probably an age-related phenomenon. As the teeth continue to function and be challenged by erosive, attritive and abrasive factors, there will be change to the surfaces of teeth. This is most commonly seen on the incisal edges of the upper and lower incisors. As the challenges continue throughout life, it is not surprising therefore to see, as reported in Smith and Robb's study, that most people have some evidence of wear [25]. Therefore, small changes or evidence of gradual wear throughout life is probably a feature of the ageing of the dentition.
When pathological levels of wear are considered, the situation is less clear. There are insufficient data from epidemiological studies on adults to be definitive. But where data are present, it suggests similar proportions of severe levels of wear are observed in each age group, and it could be argued that this was independent of age [3, 17, 25]. It seems, therefore, that although tooth wear is an age-dependant phenomenon, severe tooth wear is not.

erosion
tooth wear
attrition
abrasion
tooth wear index


Investigation into mercury bound to biothiols: structural identification using ESI–ion-trap MS and introduction of a method for their HPLC separation with simultaneous detection by ICP-MS and ESI-MS

Mercury in plants or animal tissue is supposed to occur in the form of complexes formed with biologically relevant thiols (biothiols), rather than as free cation. We describe a technique for the separation and molecular identification of mercury and methylmercury complexes derived from their reactions with cysteine (Cys) and glutathione (GS): Hg(Cys)2, Hg(GS)2, MeHgCys, MeHgGS. Complexes were characterised by electrospray mass spectrometry (MS) equipped with an ion trap and the fragmentation pattern of MeHgCys was explained by using MP2 and B3LYP calculations, showing the importance of mercury–amine interactions in the gas phase. Chromatographic baseline separation was performed within 10 min with formic acid as the mobile phase on a reversed-phase column. Detection was done by online simultaneous coupling of ES-MS and inductively coupled plasma MS. When the mercury complexes were spiked in real samples (plant extracts), no perturbation of the separation and detection conditions was observed, suggesting that this method is capable of detecting mercury biothiol complexes in plants.
Introduction
Mercury is one of the most important elements to consider when environmental pollution is concerned, and ever since the Minamata disaster in 1959, the organic compound methylmercury has been in focus owing to its enhanced toxicity and its biomagnification properties in the food chain [1].
Following the Minamata disaster, the differentiation of inorganic mercury in the form of Hg2+ from organic mercury, namely in the form of methylmercury, has become a major task. Mercury speciation in complex matrices is not easy to achieve [2], and more and more sophisticated analytical methods have been developed in the past few years in order to obtain reliable quantitative results. In particular, species-specific isotope dilution mass spectrometry (SSIDMS) employing stable mercury isotopes has been a major breakthrough [3, 4]. Otherwise, experiments with stable isotope tracers introduced into the environment have given invaluable information on the distribution and transformation behavior of mercury in the environment [5–7]. Mercury has also been identified as a global pollutant, and the importance of new analytical methods towards a more complete understanding of species distribution, pathways and global impact has been highlighted recently [8].
As of today, the most common application of mercury speciation in biota is focused on the determination and distinction between methylmercury and inorganic mercury in the forms of MeHg+ and Hg2+. To separate the mercury species from their matrix, usually extraction or soft digestion methods are applied, which conserve the C–Hg bond, keeping the methylmercury moiety intact. However, it is more than unlikely that mercury and methylmercury occur as free cations, be it in biota or in the environment, and rather they are likely bound to sulfur-containing biomolecules, e.g. in fish [9], or present as chloride complexes, e.g. in seawater [10]. But, with the usual practice of mercury speciation, the counterion bound to the mercury species is lost and, even worse, completely disregarded. Thus, the information on the molecular entity of the mercury species is wasted—strictly speaking, this is not really speciation, but rather a fractionation method.
Now, in spite of the enormous progress made in mercury speciation, many questions relating to mercury and its behavior in biota remain unsolved mysteries: Why is methylmercury highly bioaccumulated, while Hg2+ is not? Why are different organs targeted by methylmercury as opposed to Hg2+, and how can the enormous latency period (up to several months!) for methylmercury intoxication be explained [1, 11]?
Little is known today about the mechanisms that enable mercury uptake into cells, and its subsequent distribution and bioaccumulation in biota. But, mercury and methylmercury are well known to bind to biothiols abundant in biota and form stable complexes via Hg–S bonds. Especially, in a model system, mercury complexes with cysteine (Cys) as a ligand have been found to be able to cross cell membranes, and the Hg(Cys)2 complex has been defined as a likely form in which Hg2+ is present. Zalups [12] and Bridges and Zalups [13] proposed that Hg(Cys)2 mimics the cystine molecule, and thus may use the active cell transport systems usually used for cystine transport into the cell. Although the theory of molecular mimicry has recently been questioned using structural comparison obtained from X-ray absorption studies of the complexes concerned [14], it is still commonly agreed that mercury and methylmercury are most likely bound to and transported as complexes formed with biothiols abundant in biota. Other studies employing direct speciation methods in biota, like extended X-ray absorption fine structure and X-ray absorption near-edge structure, underpin the assumption that methylmercury and mercury are bound to sulfur in a complex matrix [9].
Although mercury biothiol complexes have not been identified in vivo so far, mercury biothiols certainly play a key role in cell uptake, distribution and subsequently toxicity of mercury in biota [1, 11–13]. But, even state-of-the-art analytical methods for mercury speciation fail to provide us with all the necessary information, i.e. the complete molecular structure of the mercury compounds present in vivo.
Therefore, our interest lies in the development of an analytical method that allows the direct detection of mercury and methylmercury biothiol complexes in biota.
In this paper, we describe an analytical method allowing the species identification of mercury and methylmercury biothiols as intact molecules. As example species, Cys and glutathione (GS) complexes with mercury and methylmercury were synthesised and analysed. Cys is a small sulfur-containing amino acid, while GS is a small peptide comprising only three amino acids: γ-glutamyl (γ-Glu), Cys and glycine (Gly). Like Cys, this compound is usually abundant in living cells in millimolar concentrations, and it is a key compound for the cell’s redox state control: GS is the smallest building block for the synthesis of phytochelatins, which are produced in plants as a response to metal stress, and are believed to play a paramount role in metal detoxification in plants [15]. Plants are well known to accumulate mercury when grown on polluted soil [16, 17], and a future object of study for mercury exposure will be rice (Oryza sativa); therefore, we tested the method and the species stability in the matrix of a real plant extract derived from rice plants.
Experimental
Instrumentation
The instrumentation used for this work consisted of an Agilent Technologies (USA) suite comprising an 1100 series high-performance liquid chromatography (HPLC) system, an electrospray mass spectrometer (ES-MS) (XCT ion-trap mass spectrometer) and an inductively coupled plasma mass spectrometer (ICP-MS) (7500 c series). The HPLC system was equipped with an automatic degasser, a gradient pump, a thermostated autosampler tray and a thermostated column device.
For the chromatographic separation of the mercury biothiols, an HPLC method was adapted from that of Raab et al. [18]. Species separation was carried out using an Agilent Zorbax Eclipse XDB C-18 (4.6 mm × 150 mm, 5–μm) reversed-phase (RP) HPLC column using a gradient elution with eluent A being 0.1% formic acid in water and eluent B being 0.25% formic acid in methanol. The gradient programme went from 100% eluent A to 50% eluent B in 20 min with a flow rate of 1 mL/min, and a volume of 50 μL was injected via the autosampler. The autosampler tray was cooled to 4 °C for all experiments.
Coupling of the HPLC instrument to the ES-MS and ICP-MS system was performed either individually using PEEK capillary tubing (1.6-mm outer diameter, 0.3-mm inner diameter), or simultaneously via a micro flow splitter (Upchurch, UK). In split mode for simultaneous coupling, 80% of the HPLC eluent was directed into the ES-MS system, while 20% went into the ICP-MS system.
Hg(Cys)2, HgMeCys, Hg(GS)2 and HgMeGS solutions were prepared as described above in concentrations of 10 mg/L (as Hg), each in 0.1% formic acid. From these solutions, a mixture containing all four compounds was prepared at equal concentrations, resulting in a solution with a concentration of 2.5 mg/L (as Hg) of each compound.
A continuous internal standard (Rh, 20 μg/L) was mixed with the HPLC effluent prior to the ICP-MS nebuliser via a Teflon T-piece. This internal standard enables the monitoring of overall instrument sensitivity and plasma conditions, and may potentially be used to correct the mercury signal for changes in intensity due to matrix effects stemming from the introduction of methanol during gradient elution [19].
The ES-MS system was also used in direct injection mode for the species’ fragmentation experiments. Here, the sample was introduced into the ES source via a syringe pump using a 1-mL glass syringe. The ES-MS and ICP-MS instrumentation parameters can be found in Table 1.
Table 1ICP-MS and ES-MS parametersInstrumentSettingsICP-MSInstrumentAgilent Technologies 7500 cTorchStandard Ar gas flows  Cooling gas16 L/min Auxiliary gas1 L/min  Nebuliser gas0.95 L/min  Optional gas: (O2)5%  Spray chamberScott, cooled (2 °C)  NebuliserPFA, microconcentric   Internal standardContinuous aspiration, 20 μg/L Rh in 1% HNO3  ConesPlatinum  Isotopes monitored200Hg, 202Hg, 103Rh, 34S, 32S16OES-MSInstrumentAgilent Technologies XCT ion-trap mass spectrometerIon sourceElectrospray ionisationCapillary voltage4,500 VNebuliser pressureHPLC 50 psi (0.345 MPa); direct injection 20 psi (0.138 MPa)Drying gasHPLC 12 L/min; direct injection 5 L/min Gas temperature350 °CScan windowm/z 100–900MS2 fragmentation window m/z 4PFA perfluoroalkoxy, HPLC high-performance liquid chromatography, MS2 Ion trap
Reagents
All reagents used were of analytical grade and were purchased from Sigma-Aldrich, UK, unless mentioned otherwise. The water used for all the preparations was of suprapure quality (18 MΩ, ELGA water system, UK). HPLC eluents were prepared from formic acid at 0.1% in H2O and 0.25% in methanol.
An inorganic mercury (Hg2+) standard stock solution at approximately 1,000 mg/kg (as Hg) was prepared by dissolving solid HgCl2 in water. A methylmercury (MeHg+) standard stock solution at approximately 1,000 mg/kg (as Hg) was prepared from solid MeHgCl in methanol. For the preparation of mercury and methylmercury biothiols, these stock solutions were further diluted in 0.1% formic acid. The water for the preparation of standards was degassed using ultrasonication (10 min) followed by purging with N2 (10 min at 200 mL/min). Stock solutions were kept in a freezer at −20 °C; further dilutions were kept for a maximum of 1 week at 4 °C in the dark.
Reduced l-cysteine and reduced GS were dissolved in water at a concentration of 1 mg/mL and were prepared fresh daily.
Synthesis of HgMeCys, HgMeGS, Hg(Cys)2 and Hg(GS)2
From solutions prepared as described above, mercury and methylmercury biothiols were synthesised by stoichiometrically adding the respective amounts of dissolved biothiol (GS or Cys) to a defined volume of mercury or methylmercury solution. All steps were carried out in a glove bag under a N2 atmosphere in order to avoid oxidation of the thiols. Usually, mercury–thiol compounds were prepared fresh daily.
Modelling the MeHgCys conformation: ab initio and density functional theory calculations
The conformation of MeHgCys might involve bonding via either an oxygen atom in the carboxylic group or a nitrogen atom from the amino group, and either an uncharged or zwitterionic form could be possible. In an attempt to predict which, if any, of these conformations/configurations might be favoured in the gas phase, a series of ab initio and density functional theory (DFT) calculations were performed on a variety of possible structures. Geometry optimisations were performed using the electronic structure software GAMESS-US [20] at both the DFT B3LYP and the ab initio MP2 levels of theory. The 7 September 2006 release of GAMESS-US was used for the DFT calculations and the 24 March 2007 release was used for the MP2 calculations. In both sets of calculations the 6-31G(d,p) basis set [21] was employed for all atoms with the exception of mercury, which was described by the SBKJC effective core potential basis [22]. A subsequent vibrational analysis at the optimised geometries showed them to be true minima and also provided zero-point energies (ZPEs) for use in correcting the energies obtained from the minimisations. The ZPEs were scaled by 0.961 (B3LYP) and 0.9646 (MP2) as suggested by the collected data available online from the CCCBDB database at http://srdata.nist.gov/cccbdb/. The relative populations of the conformers with the lowest ZPE-corrected energies were estimated by calculating the ratios of the Boltzmann factors [23] at 350 °C, which is the gas temperature inside the ES ion source.
Plant preparation
Rice (Oryza sativa) was grown from seeds in vermiculite medium and fed with regular Hoagland solution [24] three times a week. After 2 months of growth, the rice plants were harvested. The vermiculite was washed off the roots, and the plants were sectioned into roots and shoots, cut into pieces of approximately 5 mm length. Extracts were prepared according to the method of Raab et al. [25]. Briefly, 1 g of plant material was ground in a mortar under addition of liquid N2, the sample was transferred into a 15-mL Greiner tube, 3 mL of 1% formic acid was added and the mixture was left standing in ice at 0 °C for 1 h.
Results and discussion
The objective of this work was to develop an analytical method for the separation and identification of mercury and methylmercury bound to Cys and GS. Structural MS carried out here using an ES mass spectrometer equipped with an ion trap was used as a tool for the identification and structural characterisation on a molecular level. The information gained via the fragmentation pattern obtained from the ion-trap measurements proves invaluable for the identification of unknown molecules, along with some information on the molecules’ conformation, while the simultaneous element-selective detection of mercury via ICP-MS is the key to identifying mercury-containing biomolecules in a complex matrix amidst a variety of other organic molecules.
More detailed information on the conformation of the HgMeCys molecule was obtained by a modelling approach, which underpins the findings of ion-trap ES-MS.
In this paper, we focus on the structural identification of the selected mercury and methylmercury biomolecules via ion-trap ES-MS after their separation using RP HPLC. Here, all mercury compounds were measured under the same detection conditions, and all ES-MS parameters were kept constant for all four species during direct injection as well as in HPLC injection mode. Simultaneous detection with ICP-MS was applied with HPLC separation for mercury-selective determination.
Ion-trap ES-MS measurements of HgMeCys, HgMeGS, Hg(Cys)2 and Hg(GS)2 using direct sample injection
In a first approach of identification, mercury and methylmercury complexes with Cys and GS, synthesised as described earlier in 0.1% formic acid at a concentration of 50 mg/kg (as Hg) each, were injected as single standards into the ES source of the ion-trap MS instrument. The ES-MS parameters can be found in Table 1.
The species identification was performed by using information obtained from the ES-MS and ion-trap MS data:
The MH+ molecule clusterThe characteristic isotope pattern dominated by the mercury isotope distributionIn-source fragmentation of the mercury biomolecule Cys and GS moietiesIon trap MS (MS2) of the MH+ molecular ion peak
In Fig. 1, the ES-MS spectra measured for the molecular ions (MH+) of the four compounds are shown. The vertical black lines represent the theoretical isotope ratio pattern of the molecules according to their molecular structure.
Fig. 1Electrospray (ES) mass spectrometry (MS) spectra of the MH+ peak cluster for four mercury biothiol compounds (direct injection of single standards). The theoretical isotope pattern is shown as vertical black lines. Molecular structures as ball-and-stick models are shown on the left (Hg violet, S yellow, O red, N green, C grey, H not shown). Theoretical isotope abundance is matched to the highest-abundance peak, set at 100%. The exact mass (theoretical) is given for the 100% peak. a MeHgCys. b MeHgGS. c Hg(Cys)2. d Hg(GS)2. Cys cysteine, GS glutathione
The mercury isotope pattern is very prominent, it dominates the overall isotope pattern of the molecules, and can therefore be used as a characteristic fingerprint: In small mercury biomolecules, the mercury isotope pattern is greatly preserved, even when the organic molecular structure, like in HgGS2, accounts for 75% of the molecular mass. The mass spectra show that under the ionisation conditions applied, the mercury compounds are protonated and detected by the ES-MS instrument as a molecule cluster. The experimentally obtained isotope cluster for MH+ match well with the theoretical isotopic molecule patterns calculated for each compound. The major isotope in the clusters is here referred to as the 100% abundance isotope, reflecting the usual practice in isotope abundance visualisation by defining the major mass as 100% and the less abundant isotopes as fractions of this.
In-source fragmentation of HgMeCys, HgMeGS, Hg(Cys)2 and Hg(GS)2
Molecule fragmentation is usually observed during the ionisation step in the ES ion source. The fragmentation pattern obtained in this process gives information about the molecular structure of a compound, using the different fragments for reconstruction of the complete molecule. However, for our experiments, we are interested in keeping the in-source fragmentation as low as possible in order to get the main peak from the molecular ion MH+. One reason for this is that we try to obtain optimum detection limits for mercury biomolecules in real samples, and in-source fragmentation leads to a diminished MH+ intensity. Moreover, the MH+ peak gives information on the molecular mass and enables identification via the characteristic isotope pattern. Finally, where more information on the molecular structure is needed, e.g. to elucidate isomeric forms, further fragmentation is performed on selected masses within the ion-trap MS instrument, using collision-induced fragmentation.
All mercury compounds were synthesised in solution in stoichiometric amounts (i.e. two molecules of thiol for Hg2+, one molecule of thiol for MeHg+). In order to determine whether the mercury compounds had reacted quantitatively with the organic thiols, we monitored the protonated molecular ions (MH+) of Cys (m/z 122) and GS (m/z 308). As only the reduced thiols are able to bind to mercury, we also checked for the oxidised dimers of Cys and GS with m/z 224 and m/z 613. The ratio between the molecular ions of the mercury complexes and those of the free reduced or oxidised thiols gives an indication for the reaction yield in solution, as well as the stability of the complexes.
In Fig. 2, the mass spectra (MS+) of the four mercury compounds investigated are shown, highlighting the in-source fragments observed. In-source fragmentation can be influenced by ionisation parameters, such as capillary voltage. Here, the parameters used were as detailed in Table 1 for the direct-injection mode.
Fig. 2ES-MS spectra (MS+) showing the in-source fragmentation for four mercury biothiol compounds (direct injection of single standards). a MeHgCys. b MeHgGS. c Hg(Cys)2. d Hg(GS)2
From Fig. 1 it is evident that from the four mercury compounds investigated only MeHgCys (Fig. 1a) shows extensive in-source fragmentation, resulting in two clusters of approximately the same peak height: the MH+ cluster with m/z 338 as the 100% abundance isotope and a second cluster with m/z 321 as the 100% abundance isotope, showing a mass loss of 17 from the MH+ molecular ion cluster. This mass loss can be attributed to the loss of either OH or NH3. Apart from the two most prominent in-source fragments, only one fragment exhibiting a mercury-like isotope pattern can be found at m/z 234. This may be attributed to a  or a MeHgOH moiety, and accounts for just 3% of the combined peak areas of the two main peaks. Similar fragmentation has been described by D’Agostini et al. [26], who suggested the loss of NH3 from the MH+ ion, and hypothesised that two isomeric species of MeHgCys are present in solution, either exhibiting a Hg–N or a Hg–O interaction. Here, we show that the Hg–N interaction is the most likely form present in the ion source, and that the in-source fragment at m/z 321 is indeed most likely formed through loss of NH3. This was achieved through the ion-trap MS2 fragmentation pattern and a modelling approach, in which the most stable conformation for MeHgCys was calculated in the gas phase. These experiments are highlighted further below.
A fragment with mass 119.5 may be attributed to free Cys or cystine (doubly charged), but occurs at less than 1% abundance compared with the two main clusters. The absence of free Cys also suggests that the complex is formed quantitatively in the solution.
Figure 2b shows the in-source fragmentation of MeHgGS during direct injection, clearly showing the MH+ molecular peak cluster as the dominant component. Two more fragment peaks can be identified. One fragment at m/z 395, exhibiting a cluster with the typical mercury isotope pattern, can be attributed to a loss of the γ-Glu moiety from GS. A second peak appears at m/z 308, which can be clearly attributed to protonated GS. The spectrum shows the MeHgGS molecule peak prevailing with more than 95% abundance, while the two other fragments observed correspond to approximately 1% MH+ abundance only.
For Hg(Cys)2 (Fig. 2c), MH+ is the most prominent peak in the spectrum. An in-source fragment obtained from a mass loss of 17 is also observed, but accounts for less than 6% of the MH+ peak only. Another fragment with the typical mercury isotope pattern and m/z 339 the 100% abundance peak may be attributed to a  moiety, similar to the fragment observed for MeHgCys: a Cys group can obviously be cleaved from the molecule, leaving a Hg–N bond behind. Two more peaks can be distinguished at m/z 241 and m/z 122, corresponding to protonated cystine (Cys–Cys) and Cys. Cystine at m/z 241 seems quite abundant, but accounts for only 10% of the MH+ cluster of Hg(Cys)2. Only traces of free Cys at m/z 122 (less than 1% of the mercury molecular cluster) were found.
The spectrum of Hg(GS)2 (Fig. 2d) shows two mercury-containing fragments at m/z 544 and m/z 508 besides the most prominent peak for MH+ at m/z 815. While m/z 508 can clearly be attributed to a protonated HgGS fragment after loss of one GS group, the cluster at m/z 544 cannot be clearly identified, but might be a Hg–GS cluster with two water molecules associated. A peak at m/z 407 corresponds to the doubly charged molecule peak MH2+. Two more peaks can be distinguished: m/z 613, corresponding to protonated oxidised GS, and m/z 308, corresponding to free reduced GS.
The two mercury-containing fragments correspond to 10% (m/z 544) and 15% (m/z 508), respectively, of the overall abundance, while the protonated oxidised and reduced GS only account for approximately 1% each, and MH2+ accounts for less than 2%. MH+ is found to occur at more than 70%.
The ionisation efficiencies differ substantially between the four different compounds: While MeHgCys exhibits the lowest intensities, with 2 × 105 counts, the MeHgGS signal is tenfold higher. Hg(Cys)2 and Hg(GS)2, each with around 5 × 105 counts, show intensities between these two. Taking into account that MeHgCys forms an abundant in-source fragment with the same intensity as the MH+ ion, these three molecules appear to have similar ionisation behaviour, leading to comparable ratios of protonation in the ES source under the conditions applied.
Conformation of HgMeCys: ion-trap MS2 fragmentation and conformation modelling
Collision-induced fragmentation was performed using the ion-trap device of the ES-MS instrument. The in-source fragmentation of MeHgCys showed an important fragment with a mass loss of 17 amu with abundance as high as the MH+ molecular ion. This mass loss can be explained by either loss of OH or NH3 from MH+, and both possibilities have been postulated before [26]. Here, we use the ion-trap MS2 information on the two prevailing peaks obtained combined with a modelling approach to find the most probable conformation of MeHgCys, which may explain the fragmentation behaviour observed.
As shown in Fig. 3, the MS2 spectrum of the MeHgCys molecular ion (m/z 336, 200Hg) shows a predominant fragment at m/z 318 due to loss of H2O. A second fragment at m/z 231 can be attributed to either  or MeHg–O+, formed through rearrangement of the molecule under loss of the residual Cys moiety, and corresponds to the fragmentation pattern obtained in source. This finding is an indication that the Hg–S bond is not the only interaction between Cys and HgMe, but that either Hg–O or Hg–N bonding is involved, i.e. either the carboxylic or the ammonia group forms a bond to the central metal.
Fig. 3Ion trap MS (MS2) spectra as obtained from collision-induced fragmentation in the ion-trap device from the two main in-source fragments obtained from the direct injection of a single standard of MeHgCys. a MS2 of MH+ at m/z 336 (Me200HgCys). b MS2 of MH+ at m/z 319 (Me200HgCys–OH or Me200HgCys–NH3)
A different picture is seen when MS2 is performed on the in-source fragment ion with m/z 319 (formed through loss of OH or NH3 from 200HgMH+ at m/z 336) . Here, we can distinguish several fragments: m/z 301 (loss of H2O), m/z 288 and m/z 261, formed through the successive loss of parts of the Cys moiety, and m/z 215, corresponding to MeHg+. In contrast to the MS2 of MH+ (m/z 336), the fragment at m/z 231 is not formed. This is an indication that the group forming this fragment has been lost during in-source fragmentation.
Modelling the MeHgCys conformation using ab initio and DFT calculations
The conformation of MeHgCys can involve either bonding via an oxygen atom in the carboxylic group or a nitrogen atom from the ammonia group, and can carry the proton at either group. A modelling approach was used to determine the total energies for the different possible conformations of HgMeCys, including correction for the ZPE.
The final conformations obtained from the geometry optimisations at the MP2 level are shown in Fig. 4 (conformers 1–6). Those obtained from the B3LYP calculations differed only by small deviations in bond lengths and angles and are therefore not shown. Two of the geometry optimisations were started in zwitterionic configurations with either a carboxylic oxygen (conformer 1) or the amino nitrogen (conformer 2) positioned close to the mercury atom. The zwitterionic form of MeHgCys was found to be unstable and optimisations led to the neutral form regardless of the initial protonation state. Of the remaining calculations, conformer 3 and 4 were started with the amino nitrogen close to the mercury, whereas conformers 5 and 6 were started with a carboxylic oxygen in this position. In all of these optimisations the initial Hg–X (X is O or N) interaction was retained throughout, suggesting that this is generally favoured in the conformational behaviour of MeHgCys.
Fig. 4Modelling the MeHgCys conformation: final conformations of MeHgCys obtained from geometry optimisation at the MP2 level. Model numbers (1–6) as used in Table 2
The pattern of relative conformational energies (Table 2) is basically the same at both levels of theory, with the most energetically favoured conformations displaying the Hg–N interaction. Those conformations displaying Hg–O interaction make up the second-most thermodynamically stable grouping, whereas the extended conformer where the mercury atom is free from nonbonded interaction is considerably higher in energy than all the others. The energy differences are more pronounced at the MP2 level than at the B3LYP level and this is probably due to the fact that the perturbation theory treatment is capable of describing dispersion effects, whereas DFT is not. Dispersion effects are responsible for mediating nonbonded interactions such as hydrogen bonds and van der Waals “bonds” and therefore it would be expected that these would be important in this particular case. For this reason, the MP2 results are expected to be more reliable than those obtained with DFT since the former provide a more complete physical picture of the MeHgCys system.
Table 2Conformational energies obtained for the two different models usedConformerB3LYP/6-31G(d,p) ΔE (kJ/mol)aMP2/6-31G(d,p) ΔE (kJ/mol)b17.418.0212.730.330.00.047.66.9525.821.0613.721.4Scale factors obtained from the CCCBDB database at http://srdata.nist.gov/cccbdb/aZero-point energies scaled by 0.9610bZero-point energies scaled by 0.9646
The results of the Boltzmann factor calculations based on the corrected MP2 energies indicate that at the experimental temperature approximately 98% of the MeHgCys would be present as the form displaying the Hg–N interaction, with the remaining 2% consisting almost exclusively of the Hg–O forms. Using the B3LYP energies, these calculations suggest that the slightly lower figure of 87.5% for the Hg–N forms, with one of the Hg–O conformers making up most of the remaining population. As the MP2 energies are thought to be more accurate on the basis of physical considerations, it is reasonable to assume that the figure of 98% for the Hg–N population is similarly more accurate; however, even at the B3LYP level the figures clearly point to this being the form of the molecule expected to be dominant in the gas phase at 350 °C. The use of larger and/or more flexible basis sets might lead to alterations in these results owing to improved description of the Hg–X interactions but it is felt that this would be unlikely to significantly alter the distribution of energies in this case.
Assuming that the Hg–N form is dominant in the ion source, it is reasonable to assume that the in-source fragment obtained at m/z 234 (202Hg) corresponds to a (protonated)  ion. This is confirmed by the occurrence of the same fragment in MS2 at m/z 231 (). The in-source fragment at m/z 319 (200Hg) does not exhibit the m/z 231 fragment during MS2, but loses the Cys completely, with MeHg+ remaining as the smallest mercury-incorporating fragment. This is suggestive of the possibility that the in-source fragment with m/z 319 has lost NH3 rather than OH – a MeHg–N fragment cannot be formed from this mother ion. However, it should be noted that besides the Hg–N interaction, a small contribution of Hg–O is possible.
Ion-trap MS2 of the MH+ cluster of Hg(Cys)2, HgMeGS and Hg(GS)2
Figure 5 depicts the ion-trap fragmentation patterns obtained for the three remaining mercury-containing biomolecules. The m/z values of the MS2 spectra shown here in Fig. 5 are each defined for the 200Hg isotope. However, the chosen trap window ion width of 4 amu ensures that a major part of the ion cluster is trapped and undergoes collision-induced fragmentation. Thus, easier identification of mercury-containing fragments is possible, as the mercury pattern is greatly conserved. However, the fragment incorporating 200Hg will be trapped with the highest abundance.
Fig. 5MS2 spectra as obtained from collision-induced fragmentation of the MH+ molecular cluster in the ion-trap device from three mercury biothiols. a MeHgGS. b Hg(Cys)2. c Hg(GS)2
Hg(Cys)2
The ion-trap collision-induced fragmentation of Hg(Cys)2 exhibits a most abundant fragment at m/z 434, corresponding to the loss of H2O, and a second important fragment at m/z 337, which corresponds to the loss of one Cys molecule leaving a nitrogen atom bound to mercury (CysHg–N+). This behaviour is similar to what was found for the fragmentation of MeHgCys, and seems to be typical for mercury bound to a Cys moiety. No other fragments containing mercury can be observed, and no unbound Cys molecules were detected.
MeHgGS
The MS2 of MeHgGS shows one high-abundance fragment at m/z 375, corresponding to the loss of a Glu moiety and OH, plus two low-abundance fragments at m/z 509 (loss of H2O) and m/z 393 (loss of Glu). GS is not lost during this fragmentation, but rather the Glu moiety is chopped off the GS. Interestingly, a MeHg+ ion fragment that it is formed during MS2 of HgMeCys cannot be detected either; hence, mercury is probably stabilised by the Gly/Cys moiety.
Hg(GS)2
The MS2 of Hg(GS)2 shows two main fragments with m/z 686 (loss of Glu) and m/z 508 (loss of GS), plus four less abundant fragments: m/z 795 (loss of H2O), and m/z 666, m/z 557 and m/z 547 formed by successive loss of GS amino acids.
HPLC separation of HgMeCys, HgMeGS, HgCys2 and HgGS2 with simultaneous ES-MS and ICP-MS detection
For the chromatographic separation of the mercury biomolecules, HPLC and the simultaneously coupled ES-MS and ICP-MS system was used as described in “Instrumentation”. Hg(Cys)2, HgMeCys, Hg(GS)2 and HgMeGS solutions were prepared accordingly, as well as a mixture of four compounds with a concentration of 2.5 mg/L (as Hg) each.
Single injections of each standard revealed the retention times for each compound, and these injections were followed by injection of the mixture of the compounds. The elution order obtained was Hg(Cys)2, HgMeCys, Hg(GS)2 and HgMeGS, with HgMeGS being eluted at approximately 9.5 min. All compounds were eluted at a gradient composition of less than 15% eluent B, showing that relatively soft elution conditions can be applied. Figure 6 shows the combined ICP-MS (202Hg, 103Rh) and ES-MS traces for the extracted ion chromatograms of m/z for MH+ for the four mercury species.
Fig. 6Simultaneous ICP-MS and ES-MS spectra from high-performance liquid chromatography injection of MeHgCys, MeHgGS, Hg(Cys)2 and Hg(GS)2
The ES-MS traces of the extracted ion chromatograms show distinct peaks of the protonated molecular ion masses. For each compound, the same isotope cluster was found as was obtained in the flow-injection experiments with the single species. Moreover, the MS+ spectra (in-source fragmentation) are identical to those obtained in the direct-injection experiment, as are the MS2 spectra of the MH+ molecular ions (data not shown).
All ion traces in ES-MS are on the same y-scale, and it is evident that the intensities measured in ES-MS are species-dependent, like in the direct-injection experiments. MeHgGS shows the highest intensity, approximately 10 times higher than MeHgCys. Although a methanol gradient was used in the HPLC experiment (12.5% methanol at 10 min retention time), the relative peak intensities are comparable with those obtained with the direct injections.
A different picture is seen for the ICP-MS signal for mercury. In ICP-MS, all compounds should be completely destroyed by the hard ionisation conditions in the plasma. Therefore, the signal intensities for the different compounds should only be governed by the absolute mercury concentration. As all the compounds were made up in the same concentration (as Hg), the ICP-MS response should be very similar for all compounds. Figure 6 shows that for the four compounds the intensities obtained are much more similar than those obtained by ES-MS, but are not ideally equal: the peaks corresponding to the first and the last species eluted (HgCys2 and MeHgGS) are approximately twice the peaks obtained for MeHgCys and HgGS2. Several reasons can be responsible for this finding:
Overall intensity changes due to the input of methanol into the plasma. As shown in Fig. 6, the signal for the internal standard is constant up to approximately 4 min of runtime; afterwards it decreases to about 50 % of the initial value at 10-min runtime, when the last mercury compound is eluted. If the mercury intensities are influenced by this process only, the signals for the first compounds eluted (both less than 4 min retention time) should be equal, whereas the signals for the GS complexes should be only about half. This is not the case; in fact the last compound eluted, MeHgGS, exhibits a signal equal to the first compound eluted. However, the behaviour of mercury with its high ionisation potential (10.4 eV) is greatly influenced by organic matter in the plasma, and the mercury signal intensity may change in a different way from the intensity of rhodium. The dependence of the mercury intensity on the methanol content of the eluent must be determined, but this was not performed during the experiments reported here.The volatilities of the compounds may be different, so different amounts of each compound may be introduced into the plasma during pneumatic nebulisation: this effect is well known for volatile species like HgMe2, and has to be investigated further for the compounds used in this experiment.MeHgCys and HgGS2 may partly decompose on the column, so not all of the compound injected may reach the plasma: in this case, we would expect broad, tailing peaks and substantial amounts of free Cys and reduced GS. However, these have not been observed.MeHgCys and HgGS2 are not present to 100% in the standard, and thus the concentrations of the mercury reaching the plasma are diminished: in this case, signals for unbound Cys and GS should show also significant intensity. In fact, some oxidised Cys and oxidised GS can be distinguished in the ES-MS, but is not clear whether the amounts may sum up to explain the intensity loss in MeHgCys and HgGS2. However, the corresponding mercury part of the molecules (Hg2+ and MeHg) should show up in the ICP-MS trace, and this is not the case. As shown further later for the spiking experiments (Fig. 7), Hg2+ and HgMe+ are eluted from the column with distinct retention times differing from the retention times of the other complexes.Fig. 7Overlaid chromatograms for injections of free and biothiol-complexed mercury species in a plant extract spiked with different Hg and HgMe biothiol complexes. Peak assignment: 1 Hg(Cys)2, 2 Hg2+, 3 MeHgCys, 4 MeHg+, 5 MeHgGS, 6 Hg(GS)2
Thus, a final explanation for the difference in intensity of the four compounds cannot be given at this point.
Compound stability during spiking experiments of plant extracts
The mercury biomolecules synthesised and characterised here shall be detected and identified in real-world samples. One future application is the determination of such compounds in plants exposed to mercury contamination. Mercury can readily be taken up by plants, can accumulate in the roots and can be translocated into shoots and fruits [16, 17, 27, 28].
For the determination of such complexes in plant material, the latter has to be extracted using a minimally invasive method which does not destroy or transform the compounds we are looking for. Here, we tested the stability of the four example compounds in extracts from roots and shoots of rice plants.
The plant extracts, prepared as described earlier, were spiked with the four compounds and the signals obtained were compared with the corresponding signals when the compounds were prepared in 0.1% formic acid. Simultaneous ES-MS and ICP-MS detection was applied using the same setup as described earlier. Additionally, plant extracts were spiked with “free” Hg2+ and HgMe+ in order to determine their retention behaviour on the column, and to see whether any complexes would form in situ with any biothiols possibly present in the plant extracts.
In Fig. 7, the 202Hg traces monitored by ICP-MS are shown for MeHgCys, Hg2+, Hg(Cys)2, MeHg+, Hg(GS)2 and MeHgGS spiked into the shoot extract of a rice plant at a concentration of 10 mg/kg (as Hg) each. It is evident that the elution order of the four mercury biothiol complexes matches very well the one obtained in a standard mixture (Fig. 6). Surprisingly, Hg2+ is eluted later than HgCys2, whereas MeHg+ is eluted with a broad peak with a retention time of approximately 5 min between the Cys and GS complexes. The elution order and the retention times are practically the same for the standard, root and shoot extracts, and this also remains over time: a second injection of all samples, done 7 h after the first run, showed no significant change in retention times. A similar picture is seen for the peak areas. Except for Hg2+ and MeHgCys, the peak areas measured after 7 h are more than 80% of the initial value (peak areas corrected for instrumental drift using the internal standard signal). Surprisingly, MeHgCys turns out to be more stable in the extracts than in the standard solution. This might be due to the presence of some unidentified chelating agents. The peak area for Hg2+ varies considerably, showing a 50% rise for the standard in 0.1% formic acid, whereas a 30% decrease is observed in the plant extract. While no explanation can be given here for the intensity rise of the Hg2+ peak in the standard, in the shoot extract the formation of other, unidentified mercury complexes may be proposed.
The results for retention time and peak intensity reproducibility are summarised in Tables 3 and 4.
Table 3Retention times for consecutive injection of six mercury compounds with 7 h differenceSampleHgCys2Hg2+MeHgCysMeHg+HgGS2MeHgGSStandard 1120.7152213.5302458.4529.1Standard 2120.7152218.5303454.1527.7Roots extract 1125.7NA213.5286457.8529.8Roots extract 2126NA212.8284.9452.7526.9Shoots extract 1125.7150.6213.5295.6457.7529.1Shoots extract 2125151.4214.2292.8455.5526.2Average123.9151.5214.3294.1456.0528.1σ2.50.662.17.72.31.4RSD (%)2.00.40.92.60.50.3NA not available, RSD relative standard deviationTable 4Peak area (as percentage of first measurement) recoveries for consecutive injection of six mercury compounds with 7 h differenceSampleHgCys2Hg2+MeHgCysMeHg+HgGS2MeHgGSStandard 9115910989283Roots extract93NA67898786Shoots extract967749958686
The addition of MeHg+ to the extracts did not result in any additional peaks in the ICP-MS trace, while for the addition of Hg2+ a small, very broad peak can be distinguished around the retention time of HgMeGS. An elevated mercury background is seen after the introduction of Hg2+ to the standard and the extract, pointing to some kind of exchange on the HPLC column, possibly through formation of unidentified, labile complexes. However, the mercury counts are at the normal background level again prior to injection of the next sample. Regarding the ES-MS measurements (data not shown), the same MH+ ion cluster patterns are found for the four spiked mercury complexes as in the standards. As already seen from the ICP-MS traces, addition of Hg2+ or MeHg+ did not result in the formation of any other distinguishable mercury biothiol compounds. In the unspiked extracts, only trace amounts of free Cys or GS were found, but there was some oxidised and thus inactive GS.
Conclusion and outlook
In this work, we could successfully show the synthesis, structural identification and HPLC separation of mercury and methylmercury complexes with Cys and GS. An ES-MS system equipped with an ion trap for MS2 measurements revealed characteristic MH+ and MS2 fragmentation patterns for these compounds, enabling the identification of these or similar complexes in biota samples. The simultaneous coupling of HPLC with ES-MS and ICP-MS with its invaluable combined information on molecular structure and quantitative mercury detection proved to be suited for this kind of compounds. The method described seems to be acceptably robust and reproducible, and also suited for real samples. This was shown through spiking experiments of plant extracts.
However, the quantification approach via the ICP-MS trace needs further investigation, especially in terms of mercury intensity changes due to the gradient introduction of methanol into the plasma, and also in terms of decomposition on column as has been described for As(GS)3 [18].
The work presented here is the first step in the determination of mercury species in biota on the molecular level.
Ongoing experiments are aimed at plant exposure to mercury and methylmercury. Here, we can also expect mercury complexes with larger biothiols, especially phytochelatins: phytochelatins are small peptides of the general structure (γ-Glu–Cys)n –Gly (n = 2–11), which can bind to metal ions and play an important role in metal detoxification and translocation processes in plants. Other biota samples, e.g. fish, will be targeted as well.
Finally, this study presents the first identification of mercury and methylmercury biothiols in spiked plant extracts; hence, this method is a novel tool to investigate whether mercury and methylmercury indeed form complexes with biothiols such as Cys and GS, or if they rather bind to larger entities such as phytochelatins in plants or proteins in fish and other biota.

inductively coupled plasma mass spectrometry


A low perfusion rate microreactor for continuous monitoring of enzyme characteristics: application to glucose oxidase

This report describes a versatile and robust microreactor for bioactive proteins physically immobilized on a polyether sulfone filter. The potential of the reactor is illustrated with glucose oxidase immobilized on a filter with a cut-off value of 30 kDa. A flow-injection system was used to deliver the reactants and the device was linked on-line to an electrochemical detector. The microreactor was used for on-line preparation of apoglucose oxidase in strong acid and its subsequent reactivation with flavin adenine dinucleotide. In addition we describe a miniaturized version of the microreactor used to assess several characteristics of femtomole to attomole amounts of glucose oxidase. A low negative potential over the electrodes was used when ferrocene was the mediator in combination with horseradish peroxidase, ensuring the absence of oxidation of electro-active compounds in biological fluids. A low backpressure at very low flow rates is an advantage, which increases the sensitivity. A variety of further applications of the microreactor are suggested.
Introduction
Conventionally, characterizing enzyme properties in terms of kinetics, conversion rate, and substrate specificity requires substantial amounts of pure enzyme. We aim to develop a versatile and robust microreactor to monitor on-line the activity of small amounts of enzymes, and that can be used under harsh conditions if required, for instance, to prepare modified forms of glucose oxidase (GOx) in which the flavin adenine dinucleotide (FAD) cofactor has been replaced by artificial flavins. GOx uses β-d-(+)-glucose with high specificity as substrate, converting it to gluconolactone and H2O2. Preparation of apoGOx with low residual activity requires partial unfolding of the protein under strongly acidic conditions followed by removal of the flavin by size-exclusion chromatography [1]. The activity of the enzyme can be restored by applying a solution of FAD or FAD analogues [1–4].
Enzyme reactors can be created by covalent immobilization [5, 6]. Another option is to co-polymerise the enzyme in a flow system, trapping the enzyme in a polymer matrix [7, 8]. With these approaches assessment of enzyme properties, inhibitor screening [7], or conversion rates of stereoselective or enantiomeric substrates [9, 10] have been reported. Although convenient, covalent attachment and co-polymerisation require substantial amounts of protein to obtain a good response [11]. Upon immobilization, enzyme characteristics are often altered and enzyme activity may be lost. Especially when rare or expensive enzymes have to be used, it would be beneficial to have a system that uses far less enzyme, does not use chemical immobilization, and is easy to handle.
We propose a device where the enzyme is confined in a small space on top of one filter or between two filters and continuously perfused. The device, based on our previously described biosensor technique [12], is robust, easy to handle, and loss of activity and consumption of enzyme are kept to a minimum. With this device we were able to prepare apoGOx on-line by retaining GOx on a single polyether sulfone (PES) filter using acid treatment. Restoration of the enzyme activity was achieved in the same system using a solution of FAD. Furthermore, we were able to miniaturize the microreactor, using less enzyme, and increase the sensitivity of the system using a combination of ferrocene and horseradish peroxidase (HRP) as a mediator for electrochemical detection.
Experimental
Materials
GOx from Aspergillus niger (EC 1.1.3.4, grade 1) and horseradish peroxidase (HRP; EC 1.11.1.7, grade 1) were obtained from Roche (Almere, The Netherlands). Ferrocene carbolic acid was from Lancaster Chemicals (Lancaster Synthetics UK, Morecambe, Lancs, UK). Other chemicals were of pro analysis quality and purchased from Merck (Amsterdam, The Netherlands). Double quartz-distilled water was used for all aqueous solutions. Before and after acid treatment, the running buffer (a) of the microreactor was 0.15 mol L−1 sodium phosphate, pH 7.0, containing 1 mmol L−1 NaCl and 0.1% Kathon GC (Rohm and Haas, Croydon, Surrey, UK). Glucose solution (50 mmol L−1) prepared in running buffer was left to stand for several hours to reach mutarotational equilibrium. For electrochemical detection of GOx in combination with HRP, the running buffer (b) also contained 0.5 mmol L−1 ferrocene carbolic acid.
Design of the microreactors
The overall design of the microreactors is shown in Fig. 1. They were micro machined from Delrin by the instrumental workshop of Groningen University. For preparation of apoGOx and reconstitution of GOx activity, a microreactor as described in Ref. [12] was used. In contrast to the original device, only one PES filter with a cut-off value of 30 kDa (Sartorius, Göttingen, Germany) and punched to a diameter of 13 mm, was used. Performance studies were done with our miniaturized design. The dimensions of the miniaturized microreactor were: outer length 3 cm, outer diameter 1.5 cm. A PES membrane filter was punched to a diameter of 4 mm and placed in the microreactor (effective diameter 3 mm, effective volume 1 μL) and connected between the injection valve and the detector with fused-silica tubing (FST) (150 μm OD, 50 μm ID) (Polymicro Technologies, Phoenix, AZ, USA) pinched off in Teflon tubing 1/16 inch OD and 170 μm ID (Aurora Borealis Control, Schoonebeek, The Netherlands) with use of finger-tight fittings, to avoid high dead volumes.
Fig. 1Schematic design of the reaction compartment of the microreactor. (a) sketch; (b) schematic diagram. Shown here is the microreactor with one PES ultrafilter which is then connected to the flow system using FST and finger-tight fittings. The mesh screen is used to support the ultrafilter
Set-up of the system
The perfusates of the microreactor were introduced into a flow-injection system and monitored electrochemically (VT-03 electrochemical flow cell and Decade Digital Electrochemical Amperometric Detector; Antec Leyden, Zoeterwoude, The Netherlands), essentially as previously described [13–15]. For the preparation of apoGOx and subsequent reconstitution of the holoenzyme a voltage of +0.5 V was applied between the working and reference electrodes.
GOx/HRP activity monitoring
For flows >1 μL min−1, a LC10ADvp solvent-delivery pump (Shimadzu Corporation, Kyoto, Japan) was used; for flows <1 μL min−1 a Harvard 22-syringe pump (Harvard Apparatus, Holliston, MA, USA) was used. A voltage of −150 mV was applied between the working (glassy carbon) and reference (Ag/AgCl) electrodes. The injection valve (Vici Cheminert C4, Valco Instruments, Houston, TX, USA) was equipped with a 20 nL internal loop; injection cycles were designed using software incorporated in the Decade system, which also thermostatically controlled the reaction temperature at 37°C. The current was registered using a flatbed recorder type BD41 (Kipp & Zonen, Delft, The Netherlands) and/or the signal was integrated using Chromeleon Software (Dionex Corporation, Sunnyvale, CA, USA) on a PC using an RS232 interface. After the filter was installed in the system, it was left to equilibrate to a flow of 50 nL min−1. Glucose solution injection was sequenced to load/inject 2/3 min (cycle time 5 min) and repeated until a stable baseline was obtained.
Preparation of apoGOx and restoration of the enzyme activity
Preparation of apoGOx was essentially the same as described in Ref. [16], with a solution of 0.1 mol L−1 glycine, 0.1 mol L−1 NaCl, and 0.1 mol L−1 HCl, pH 1.5 mixed with glycerol to a final concentration of glycerol of 30% (v/v), cooled in ice. This solution was applied to the GOx containing reactor. In detail, a 10 μL solution of 100 mg mL−1 GOx (625 μmol L−1) was pipetted on to the microreactor’s PES filter, which was thus loaded with 6.25 nmol. After stabilisation of the signal, the initial enzyme activity was determined (=100%). The reactor was detached from the detector. The detached reactor was cooled in ice, and perfused with the cooled acidic glycerol solution at a rate of 25 μL min−1 for 15 min. After application of running buffer (a) until the effluent was pH 7, the reactor was taken out of the flow system, re-attached to the detector cell, and the residual activity of the apoGOx was measured in buffer system (a) with a flow of 25 μL min−1.
After the reactor was released from the flow system, ca 150 μL of an FAD solution (3.4 mmol L−1) in 0.15 mol L−1 sodium phosphate, pH 7.0, at room temperature, was applied manually during ca 15 min, except for time-dependent tests. Afterwards, the reactor was re-attached to the detector cell and the restored activity of the holoenzyme was measured as described above.
Determination of several characteristics of the miniaturized enzyme reactor
Increasing amounts of GOx in running buffer (b) (range 625 amol to 625 pmol) were injected into the system, providing the amount of GOx retained on the membrane. After equilibration, a sequence of load/inject of the glucose solution was applied. Subsequently, a solution of HRP in running buffer (b) was injected into the system providing 0.68 pmol (30 ng) of HRP. After equilibration the sequence of load/inject of glucose was repeated. The efficiency of conversion at the electrode was calculated according to Eq. (1):
where h = peak height (pA), σ = peak width at 60.7% (s), I = injection volume (μL), c = concentration (μmol L−1), n = number of electrons, F = 96485 (Faraday’s constant, C mol−1) and √(2π)hσ is peak area (C)
In Eq. (1) the charge that is transferred to the electrode (area under the curve) is related to the real charge that is available in the reaction, e.g. the concentration of the substrate, the number of electrons involved, and Faraday’s constant.
Results
Preparation of apoGOx and restoration of the enzyme activity
We followed the response to glucose, the residual enzyme activity of apoGOx after acid treatment, and restoration of the enzyme activity after application of a solution of FAD. After acid treatment, negligible activity of apoGOx was observed. Application of the FAD solution restored the enzyme activity. The time dependency of enzyme activity restoration is shown in Fig. 2, composed of individual data from five apoGOx preparations. This time dependency of the reactivation is in accordance with Eq. (2).
where k = 0.035 min−1 and t is the reaction time (min).
Fig. 2Restoration of apoGOx activity: circles, observed relative reactivation with FAD; solid line, fitting according to the equation f(t) = 1 − exp(−0.035t)
Approximately 80% of the enzyme activity was restored within 60 min, which is above average compared to other procedures [1, 2].
Performance
Several properties of the system were investigated. These included backpressure of the reactor at various protein loads, its stability and reproducibility, the efficiency at the electrode, system sensitivity, and ease of handling. The relationship of backpressure to the flow and the amount of protein retained on the filter are depicted in Figs. 3a and 3b. The level of the backpressure is acceptable with these flows and these amounts of protein. The stability and reproducibility of the system, as tested with 625 fmol GOx on a series of glucose injections, showed an intra-assay standard deviation of less than 3%. The efficiency of the reaction is inversely proportional to the amount of protein on the filter. The sensitivity of the set-up was determined by retaining various amounts of GOx, ranging from 62.5 amol to 625 pmol on the ultrafilter, and testing the response. A measurable and reproducible response was obtained, even with the lowest amounts of enzyme tested (Table 1). One load of enzyme in the microreactor can be used at least 10 times and the system can be regenerated simply by replacing the filter and injection of a fresh aliquot of protein solution.
Fig. 3System backpressure. (a) Backpressure in relation to the flow at various protein loadings: diamonds, 0 μg; squares, 13 μg; triangles, 24 μg; circles, 39 μg; stars, 61 μg GOx. (b) Backpressure in relation to the amount of protein retained on the filter at various flow rates: circles 1 μL min−1; squares, 5 μL min−1; triangles, 10 μL min−1; diamonds, 25 μL min−1Table 1Measured detector signal and relative conversion of glucose in relation to the amount of enzyme retained on the filter in the miniaturized microreactor. Indicated are the amounts of GOx (in fmol) on the PES filter and the signals of the detector (in nA) indicating the amount of converted glucose, calculated as described in the method sectionProtein (GOx) on the filter (fmol)Signal (nA)Conversion (%)0.06250.0160.040.6250.0280.0066.250.0510.0016250.530.00016250002.40.0000006
Conclusions
The low perfusion rate microreactor is suitable for the new application described here—preparation of minute amounts of apoGOx and reconstitution of enzyme activity with a solution of FAD. In comparison to the conventional preparation of apoGOx using size-exclusion chromatography [1, 2, 16], this device requires neither complicated handling nor expensive materials and equipment. The enzyme is simply retained on the PES ultrafilter.
A scale-up of the microreactor can easily be performed, allowing the preparation of larger amounts of apoGOx to be used, for example, in studies with modified FAD [2–4] or as the basis of a biosensor with which a wide variety of analytes can be detected [1]. The combination with immunological principles allows the analysis of small molecules when no specific enzyme is available, combining molecular recognition with enzyme enhancement of the signal. The sensitivity is improved even more by using electrochemical detection.
Low perfusion rate microreactors may facilitate the study of enzymatic properties and modifications, including substrate inhibition, competitive and non-competitive inhibition, and allosteric activation. Because of the mild fixation conditions, they may enable investigation of receptor activity also. An advantage of the microreactor presented here is the small amount of protein required, thus allowing the use of expensive and rare enzymes. Applications using related devices, e.g. Refs. [7, 10, 17] usually require micrograms to milligrams of protein. Glucose sensors using glucose oxidase or glucose dehydrogenase have also been developed for clinical use. One example of such an application uses a volume of 300 nL blood for glucose measurements in diabetics [18]. Such reactors still use larger volumes as compared to the 20 nL we used here. Although we used electrochemical detection, other modes of detection including capillary electrophoresis, fluorescence, or chemiluminescence, are possible. In addition, with the current interest in proteomics, applications can be found where minute amounts of protein can be digested reproducibly and analysed directly by LC–MS–MS [19–21].

glucose oxidase
apoglucose oxidase
flavin adenine dinucleotide
enzyme reactor
deflavination