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Unformatted text preview: IOP PUBLISHING BIOMEDICAL MATERIALS doi:10.1088/1748-6041/5/1/015002 Biomed. Mater. 5 (2010) 015002 (7pp) An in vitro multi-parametric approach to measuring the effect of implant surface characteristics on cell behaviour J T Davies1 , J Lam2 , P E Tomlins2 and D Marshall1 1 2 LGC, Queens Road, Teddington, Middlesex, TW11 0LY, UK National Physical Laboratory, Hampton Road, Teddington, Middlesex, TW11 0LW, UK Received 6 August 2009 Accepted for publication 3 December 2009 Published 7 January 2010 Online at Abstract Orthopaedic implants are designed to promote biocompatibility and hence their integration with surrounding tissue. This involves influencing cell–implant interactions through changes in both surface topography and surface roughness. However, the large range of machining techniques used in implant manufacture and inconsistencies in the measurement techniques used for surface characterization make it difficult to measure the impact of surface characteristics on cell–implant interactions. Here, we describe a new in vitro multi-parametric approach that uses commercially available arrays of engineered surfaces that linearly increase in roughness, as measured by Ra, and that can be used to obtain quantitative measurements of cell attachment, differentiation and bone formation. Using this model, we demonstrate that cell attachment above 50% confluency occurs over a narrow range of roughness (Ra from 0.0125 μm to 6.3 μm) and that promotion of cell differentiation and bone development, while significantly influenced by surface topography, does not correlate directly with initial levels of cell attachment. These results compare well with published in vivo implant biocompatibility data indicating that this approach has the potential to offer a rapid, reliable and reproducible in vitro prediction of in vivo implant biocompatibility. or finish and hence justifies changes to the manufacturing procedure. Osseointegratable devices are one of the largest groups of surgical implants and have applications ranging from dental implants through to the repair of fractured or broken bone and joint replacement. The majority of these implants are coated with titanium and its alloys [4] which have been shown in both clinical and in vivo models to have good biocompatibility [5–9]. Nonetheless, it still remains challenging to determine the potential biointeractions of titanium-coated implants with the in vivo cellular environment [10, 11], and the mechanisms underlying these events remain largely unknown [12]. In general terms, the attachment of a cell to a material surface is mediated, at least initially, by the surface chemistry and the properties of the adsorbed layer of proteins that rapidly coat a surface in vivo [13]. Protein adsorption is followed by cell adhesion. This involves a number of molecules including extracellular matrix, cell membrane and cytoskeleton proteins that interact and contribute to the induction of cellular 1. Introduction Fewer than 20 materials are routinely used in the body to restore or repair damaged or diseased tissues due to issues of biocompatibility which varies with material type and between individual patients [1]. The challenge remains to manage the degree of interaction between the metal implant and the surrounding tissue controlling the level of cell attachment (increasing or decreasing) to maximize the performance of the implant. Many attempts have been made to realize this goal using coatings that range from porous materials which facilitate integration with the surrounding tissue [2] to polymer films that contain cytotoxic agents that inhibit cell attachment [3]. The efficacy of these different approaches is difficult to quantify, due to low patient numbers, differences in patient activity, age, sex and disease state, as well as a significant contribution from the surgical procedure itself. This lack of quantification makes it difficult to optimize a particular coating 1748-6041/10/015002+07$30.00 1 © 2010 IOP Publishing Ltd Printed in the UK Biomed. Mater. 5 (2010) 015002 J T Davies et al Table 1. Assessment of cell attachment to different comparator samples was analysed using light microscopy and was ranked for each sample as either one star (<10% cell coverage), two star (∼30% cell coverage), three star (∼50% cell coverage), four star (∼70% cell coverage) or five star (>80% cell coverage). The samples selected for the differentiation study are shown in the shaded boxes. Plate no. 315 329 329 331 Sample 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Machine finish Ra (µm) Cell attachment Plate no. 0.025 0.05 0.1 0.2 Surface grinding 0.4 0.8 1.6 3.2 0.025 0.05 Shot Blasting 0.1 0.2 0.025 0.05 Grit Blasting 0.1 0.2 Spark Erosion 0.4 0.8 331 334 336 processes [14–19] and in turn, influence the cell signalling cascades [20]. The surface texture of commonly used orthopaedic implants varies substantially according to the manufacturing method which can lead to significant heterogeneities in the surface texture and roughness of an implant. Previous studies using a range of in vivo models have shown that surface roughness can significantly affect bone integration into an implant [21–23]. However, the influence of surface roughness and/or surface chemistry in the wide range of different machined surfaces used in implant manufacture has yet to be evaluated. This study uses a novel in vitro system composed of commercially engineered surfaces generated using a range of machining techniques that are representative of those found on commercially available implants. These surfaces, which can be titanium coated to replicate orthopaedic implants, form a linear array of increasing surface roughness derived using a single measurement technique (Ra) allowing the effect of multiple surface characteristics to be examined in parallel. Using this system we demonstrate how machining technique and Ra impact on cell attachment, differentiation and bone formation. Sample 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 Machine finish Spark Erosion Casting Polishing Ra (µm) Cell attachment 1.6 3.2 6.3 12.5 25 50 1.6 3.2 6.3 12.5 25 50 0.0125 0.025 0.05 0.1 0.2 0.4 99.5% titanium (Grade 2) to a depth of approximately 100 nm (Teer Coatings, UK). For differentiation studies, the textured areas were cut into 1 cm diameter discs prior to coating. 2.3. Imaging of textured surfaces Surface images of the comparator plate and 3D image reconstruction were performed using an Alicona Infinite Focus microscope (Alicona Imaging GmbH Germany). Surface imaging of commercial orthopaedic implants was performed using an XL30 scanning electron microscope (Phillips Ltd) at an operating voltage of 15 kV. Imaging of cells attached to the plates was performed using a Nikon TE2000S fluorescent inverted microscope. 2.4. Cell adhesion study Prior to use all comparator plates were sterilized by washing for 15 min in EDTA followed by 15 min in 100% acetone, rinsed in 100% ethanol, air dried, wrapped in aluminium foil and autoclaved for 20 min at 121 ◦ C. Sterile comparator plates were incubated at 37 ◦ C, 5% CO2 for 10 days with MC3T3-E1 cells at a seeding density of 5000 cells cm−2 in α -MEM proliferation medium containing 10% foetal calf serum, 100 units ml−1 penicillin (Sigma, UK), 100 μg ml−1 streptomycin (Sigma, UK) and 1% amphotericin B (Sigma, UK). The medium was changed every 48–72 h. After 10 days incubation, the cells attached to the surfaces were fixed with 70% ice cold ethanol for 15 min and washed twice with phosphate buffered saline (PBS) (Invitrogen, UK). Fixed cells were stained with 1% toluidine blue in PBS for 2 min followed by washing three times in PBS. Cells were imaged as described above. 2. Material and methods 2.1. Cell culture Murine MC3T3-E1 (subclone 14) calvarial cells were obtained from the American Type Tissue Collection (ATCC) (LGC Standards, UK) at passage 15 and were used between passages 17 and 20. Cells were maintained at 37 ◦ C, 5% CO2 in Minimum Essential Medium alpha modification (α -MEM, Sigma, UK) containing 10% foetal calf serum (ATCC, LGC Standards, UK). The medium was changed every 48–72 h. 2.5. Fluorescent live cell labelling 2.2. Preparation of comparator plate surfaces MC3T3-E1 cells were seeded onto comparator plates as described above and incubated in proliferation medium at 37 ◦ C, 5% CO2 for 7 days with media changed every 48– 72 h. The cells were then incubated for 4 h at 37 ◦ C in α -MEM media containing 1 μg ml−1 calcein-AM (Invitrogen, Nickel comparator plates consisting of an array of surface textures produced by different machining techniques or finishing processes were obtained from Rubert and Company, UK (table 1). The plates were magnetron sputter-coated with 2 Biomed. Mater. 5 (2010) 015002 J T Davies et al UK) to fluorescently label the live cells, followed by three 5 min washes in PBS. The fluorescent emission from labelled cells was measured at 16 predefined points on each comparator plate using an M200 Infinite Plate Reader (Tecan Ltd, UK) at 485 nm excitation and 530 nm emission. Control plates that had not been seeded with cells were incubated in calcein-AM and measured on the Tecan plate reader as described above. Following measurement of fluorescence, the cells attached to the comparator plates were fixed for 15 min at room temperature in 3.7% formaldehyde and washed twice for 5 min in dH2 O. Cell nuclei were stained by incubating the plates for 5 min at room temperature in 2 μg ml−1 Hoechst solution (Sigma, UK) followed by two times 5 min washes in dH2 O. Cells were fluorescently imaged as described above. (a) (c) (f ) (g) Comparator plate samples were cut into 1 cm diameter discs prior to coating with 99.5% titanium and sterilized as described above. MC3T3-E1 cells were seeded onto the discs in a 24 well plate at a density of 5000 cells/well and maintained for 7 days in proliferation media. Differentiation along an osteogenic lineage was induced by incubating the cells for a further 21 days in α -MEM supplemented with 10 mM β glycerophosphate, 50 μg ml−1 ascorbic acid and 100 nM dexamethasone. The differentiated cells were fixed for 10 min in 3.7% formaldehyde and washed three times in PBS. To examine the extent of differentiation in the cells, the comparator discs were incubated for 30 min in PBS containing 2% bovine serum albumin (BSA) and 1% sodium azide at room temperature. The cells were then incubated for 1 h at room temperature in PBS containing primary antibodies against either alkaline phosphatase (rabbit-anti-mouse 1:100 dilution, Abcam, UK) or osteocalcin (goat-anti-mouse 1:500 dilution, Abcam, UK) followed by three times 5 min washes in PBS. Negative controls contained no primary antibodies. Secondary antibodies, FITC-conjugated donkey-anti-rabbit (1:200 dilution) or Texas-Red-conjugated donkey-anti-goat (1:100 dilution), were applied to the discs for 1 h at room temperature. The discs were then washed three times for 5 min in PBS and the nuclei stained with Hoechst solution and imaged as described above. (d ) (e) 2.6. Cell differentiation study (b) ( h) Figure 1. Variations in surface structure created by machining techniques. (a) ×25 magnification SEM image of the titanium beads used to promote cell growth of bone into the exterior surface of an acetabular cup. (b) ×150 magnification SEM image of a single titanium bead showing the heterogeneous surface topography. (c)–(d) ×1000 magnification SEM images of a titanium bead showing the ‘pits and grooves’ structure on the surface. (e)–(h) 3D images of Ti-coated comparator blocks that have the same Ra value (3.2 μm). The samples were prepared by surface grinding (e), spark erosion (f ), shot blasting (g) and grit blasting (h). Bar = 600 μm in (a), 100 μm in (b), and 20 μm in (c)–(d). with the same surface roughness (Ra = 3.2 μm), generated using different machining techniques, i.e. surface grinding (figure 1(e)), shot blasting (figure 1(f )), spark erosion (figure 1(g)) and casting (figure 1(h)). From these images it is clear that the surface texture details can be significantly different in terms of periodicity and characteristic features for the same Ra value. The adhesion of cells to the different titanium-coated surfaces was assessed using MC3T3-E1 cells. Figure 2 shows the attachment of the cells to textured surfaces manufactured by surface grinding (figures 2(a)–(c)) and spark erosion (figures 2(d)–(f )). These surfaces, which differ significantly in their surface topography, promote cell attachment to different levels, with increased attachment of cells to surfaces with low Ra values (figures 2(a), (d)) and decreasing cell attachment as the corresponding surface roughness increases. 3. Results 3.1. In vitro model development Examples of commercially available orthopaedic implants were examined using SEM to assess surface homogeneity. Figure 1(a) shows SEM images of a double layer of sintered medical grade titanium alloy beads applied to the exterior of an acetabular cup to facilitate bone in-growth. Closer examination of the surface of these beads shows that the texture varies significantly (figure 1(b)) and is composed of a roughened texture made up of ‘pits and grooves’ (figures 1(c)– (d)). These surface characteristics can be replicated using a range of surface machining techniques (table 1) and the surface chemistry replicated by sputter coating with titanium. Figures 1(e)–(h) show the range of surface characteristics 3.2. Assessment of cell attachment A scoring system was devised to rank the level of cell attachment to 36 surfaces created using six different machining 3 Biomed. Mater. 5 (2010) 015002 (a) (d ) J T Davies et al (c) (b) (f) (e) Figure 2. Cell attachment to defined surface roughness comparator plates. (a)–(c) Toluidine blue stained cells attached to comparator plate surfaces created using surface grinding with increasing Ra values. (d)–(f ) Toluidine blue stained cells attached to comparator plate surfaces created using spark erosion with increasing Ra values. Bar = 100 μm. techniques over a wide range of surface roughness (table 1). The scoring system ranked cell attachment over the same 10 day time frame from one star (cell attachment below 10% confluency) to five stars (cell attachment above 80% confluency). This scoring system shows clear correlations in the attachment of cells to surfaces with low Ra values regardless of the machining method used. For example, samples 1–8 (surface grinding), 25–30 (casting) and 31– 36 (polishing) all show cell attachment above 80% confluency on their respective smoothest surfaces (lowest Ra values, samples 1, 25 and 31) with decreasing cell attachment as Ra values increase, until less than 10% confluency is observed on the roughest surfaces for each machining method (samples 8, 30 and 36). This scoring method also shows the impact of surface topography on the preferential attachment of cells. For example, sample 1, which has a Ra of 0.025 produced by surface grinding, promotes better cell attachment (greater than 80%) than samples with the same Ra but manufactured by shot blasting (sample 9), grit blasting (sample 13) or polishing (sample 32). The scoring system is intended as a label free minimally invasive technique to assess cell attachment during the cell culture process. To confirm the accuracy of the scoring system, cells that were incubated with the different comparator plates were labelled with calcein-AM, a fluorescent live cell stain, and the fluorescent emission was measured at 16 points on each plate. Figures 3(a)–(d) show the live cell staining for samples 31, 33, 34 and 36 which showed decreasing cell attachment as the surface roughness increases using the scoring system. The fluorescent emission from these samples (figure 3(e)) shows significant differences in the levels of cell attachment between samples 31, 34 and 36, between samples 33 and 36 and between samples 34 and 36. By comparison, control samples, using the same surfaces that were not exposed to cells during incubation, had very low levels of background fluorescence. The differences in fluorescent emission confirm (a) (b) (c) (d ) (e) Figure 3. Fluorescent live cell measurements on the surface of comparator plates. (a)–(d) Cells on the surface of four comparator plates labelled with the live cell fluorescent markers calcein-AM (1 μg ml−1 ) (green) and Hoechst (blue). (e) Graph showing the fluorescent emission read from 16 points on each of four control plates (C1–C4) and the four comparator plates in images (a) to (d), analysis of variance was used to determine differences between comparator plates ∗ = P < 0.05. Bar = 100 μm. the correlation between surface roughness and cell attachment shown using the scoring method. 4 Biomed. Mater. 5 (2010) 015002 J T Davies et al (a) (b) (c) (d ) (e) (f) (g) (h) (i) ( j) (k) (l) (m) (n) (o) (p) Figure 4. Immunocytochemistry for markers of early and late osteogenic differentiation. (a), (c), (e), (g), (i), (k), (m), (o) Light micrographs of sample 1 (a), sample 4 (c), sample 8 (e), sample 17 (g), sample 22 (i), sample 31 (k), sample 32 (m) and sample 35 (o). (b), (d), (f ), (h), (j ), (l), (n), (p) Fluorescent immunocytochemistry images showing cell differentiation (green) and bone nodule formation (red) on sample 1 (b), sample 4 (d), sample 8 (f ), sample 17 (h), sample 22 (j ), sample 31 (l), sample 32 (n) and sample 35 (p). Bar = 100 μm. example, samples 1, 4 and 8 (surface grinding) and samples 31, 32 and 35 (polishing). 3.3. Differentiation of cells along an osteogenic lineage To examine the correlation between cell attachment and bone formation, eight surfaces which promoted cell adhesion to different levels (highlighted in table 1) were selected for a cell differentiation study. MC3T3-E1 cells at 5000 cells/well were incubated with three replicates of each sample and differentiated along an osteogenic lineage. Figure 4 shows immunocytochemistry for alkaline phosphatase (green) as a marker for early differentiation and osteocalcin (red) showing formation of bone nodules by the differentiated cells (late differentiation marker). Machined surfaces which promoted high levels of cell attachment also supported cell differentiation, including the expression of late stage differentiation markers. The development of bone nodules evident through the expression of osteocalcin was observed in samples 1 (figures 4(a) and arrows in (b)), 4 (figures 4(b), (c)), 8 (figures 4(d), (e)), 31 (figures 4(k), (l)), 32 (figures 4(m), (n)) and 35 (figures 4(o), (p)). By comparison, no expression of the late differentiation marker was observed in samples 17 (figures 4(g), (h)) or 22 (figures 4(i), (j )) with the cells expressing comparatively higher levels of the early differentiation marker alkaline phosphatase (figure 4(h), arrow). Interestingly, comparator surfaces supporting cell attachment to similar levels such as samples 4 and 17 (cell attachment of approximately 50%) were not comparable in their expression of osteocalcin. It can also be seen that samples with grooved surfaces had enhanced cell differentiation, for 4. Discussion The well-established role that surface roughness and chemical composition play in determining the interaction of surgical implants with their surrounding tissues and promoting clinical integration has led to the development of a diverse range of implants. However, it remains difficult to predict the exact effect that surface characteristics have on cell–implant interactions [24]. This makes valid cross-study comparisons difficult. Indeed most studies to date tend to examine one particular machining technique and alter either the surface chemistry or the surface roughness to determine cell–surface interactions using a single end point measurement. Whilst this approach can give an excellent in-depth evaluation of the impact of a particular characteristic, it is difficult to generate a bigger picture of how combinations of factors affect cell behaviour. In this study, we have addressed these issues by using surface roughness arrays created from commercial comparator plates that are widely used in engineering. This system allows cell behaviour to be measured and quantified on a variety of surface textures and chemistries. A simple scoring technique was developed to measure the level of cell attachment on a large number of different surfaces. This 5 Biomed. Mater. 5 (2010) 015002 J T Davies et al type of non-contact, label-free method allows an evaluation of both cell adhesion/proliferation (after 10 days in culture) and an end point cell differentiation measurement (after 28 days in culture) with direct comparison of the two events. The development of a quantitative fluorescent assay demonstrated the relative accuracy of the scoring system allowing a link between observations of cell attachment to the different surfaces with subsequent cell differentiation. From these combined analyses, we have been able to show the increased attachment of cells to surfaces with distinctly different topographies produced by, for example, surface grinding, casting and polishing and a clear negative correlation between increasing surface roughness, as defined by Ra and cell attachment. The machining techniques which promoted the highest cell attachment did so over a relatively narrow range of Ra values (0.0125–6.3 μm) when using 50% cell confluency as a measure of satisfactory cell–surface compatibility. This is consistent with a number of other reports which have used in vivo methods to examine implant biocompatibility that have shown increased cell implant responses over an Ra range of 0.5–8.5 μm [15]. This comparability demonstrates the potential for this system to be used as an in vitro predictor of in vivo implant biocompatibility. It has been reported that surface topographical features can positively influence factors such as cell attachment [25], osteogenic gene expression [26] and the level of immune response [27] but directly linking different machined surfaces and surface roughness with cell attachment and bone formation has yet to be evaluated. In this study, we have shown how surface features created using machining techniques, such as surface grinding and polishing, positively influence bone mineralization, as indicated by the expression of osteocalcin in cells that have been differentiated along a bone lineage. This positive promotion of bone development is, to a certain extent, independent of initial levels of cell attachment as evidenced by samples that had an initial cell attachment value below 30% but still had cells that expressed late differentiation markers. By contrast, sample surfaces that had a ‘pitted’ topography did not promote bone mineralization even in samples with high initial cell adhesion (50% attachment) and had only a few cells expressing early differentiation markers. These results demonstrate the powerful effect that certain machined surfaces have on influencing and sustaining long complex cellular processes, such as differentiation, and fits well with other reports that have used osteoblastic cells to show bone mineralization over shorter periods in response to specific engineered features such as ‘tapered pits’ [28] or ‘discontinuous-edges’ [12]. There is a real need for the development of standardized methods for measuring surface roughness and generating defined surface topographies to allow data comparison between laboratories. This study goes some way towards this by using an engineered reproducible platform that has surface roughness (Ra) characterized using a single method. 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