Abstract. Introduction. RBMOnline - Vol 8. No Reproductive BioMedicine Online; on web 3 February 2004

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1 RBMOnline - Vol 8. No Reproductive BioMedicine Online; on web 3 February 2004 Article Flow cytometry and microscopic acridine orange test: relationship with standard semen analysis Anwyn Apedaile obtained BSc (Hons) and MSc degrees from the University of Melbourne, Australia, graduating in Her Master s project involved a large-scale analysis of the potential applications of flow cytometry for the assessment of male subfertility. She is currently studying for a PhD at Imperial Collage, University of London, UK. She is investigating the dynamics of DNA methylation during X-chromosome inactivation in mammals, a topic that is in keeping with her interests in reproductive and developmental biology. Anwyn E Apedaile Anwyn E Apedaile 1, Claire Garrett 2,5, De Yi Liu 2,3, Gary N Clarke 4, Stephanie A Johnston 2, HW Gordon Baker 2,3 1 Clinical Sciences Centre, Medical Research Council, Imperial College School of Medicine, Hammersmith Hospital, Du Cane Road, London W12 0NN, UK; 2 The University of Melbourne Department of Obstetrics and Gynaecology, Royal Women s Hospital, 132 Grattan Street, Carlton, 3053, Australia; 3 Reproductive Services, Royal Women s Hospital, 132 Grattan Street, Carlton, 3053, Australia; 4 Department of Andrology, Royal Women s Hospital, 132 Grattan Street, Carlton, 3053, Australia 5 Correspondence: Tel: ; Fax: ; garrettc@unimelb.edu.au Abstract Improved prediction of male fertility requires advances in semen analysis. This study examined the reproducibility and independence of the flow cytometry acridine orange test (FCM-AOT) of sperm chromatin integrity as an assessment of semen quality. The study found that FCM-AOT results are not significantly affected by up to 6 h delay in semen preparation (n = 9) or contamination of semen with moderate concentrations of bacteria (<10 8 /ml E. coli or Staph. epidermidis, n = 14). The variation of replicate measurements within samples was low (%Abnormal α t : SD = 1.4, 95%CI = 4.6, n = 25) and different samples from the same men were mostly within the range of measurement error (n = 35). FCM-AOT variables, in particular %Abnormal α t, displayed significant correlations with motility (r = 0.557), vitality (r = 0.469) and morphology (r = 0.464, n = 201), which are similar in magnitude to those existing between the standard semen variables. Surprisingly, no correlation was found between %Abnormal α t and the microscopic acridine orange test (M-AOT) (n = 185), suggesting the FCM results are sensitive to a different aspect of sperm quality. In summary, this study confirms that although not totally independent of standard semen analysis or the M-AOT, it is found to be a robust, sensitive and reproducible measure of semen quality, representative of the individual. Keywords: acridine orange, chromatin structure, flow cytometry, SCSA, semen quality 398 Introduction Male infertility is a common but poorly understood problem (Oehninger, 2003). Most patients are subfertile rather than sterile, but the degree of subfertility is difficult to predict (Baker, 2001). Of the standard semen variables, sperm morphology and motility have the greatest correlation with IVF rates (Mahadevan and Trounson, 1984; Liu et al., 1988; Liu and Baker, 1992a,b), while concentration has the greatest correlation with natural pregnancies (Baker et al., 1985; Kruger et al., 1988; Bonde et al., 1998). However, routine semen analysis involves laborious manual microscopic assessment that, despite the development of guidelines by the World Health Organization (WHO, 1999), remains inconsistent, poorly standardized and highly subjective (Giwercman et al., 1999; Auger et al., 2000). Emphasis has therefore been placed on developing more robust or independent complementary measures of semen quality (Oehninger, 2003). Many alternative assessments, including sperm function tests for the acrosome reaction and zona pellucida binding, produce results that are strongly related to standard semen parameters, particularly morphology (Liu and Baker, 1992b, 1994a,b). Assessment of sperm chromatin integrity using the metachromatic dye acridine orange (AO) has also been examined using both manual and automated techniques, and is claimed to be an independent measure of semen quality (Evenson et al., 1991; Liu and Baker, 1992a; Hoshi et al., 1996).

2 DNA-intercalating dyes such as AO have proved useful for examining alterations in chromatin packaging. The composition of normal double stranded DNA results in the spatial separation of AO molecules, causing them to act like the monomeric form of the dye and emit green fluorescence when excited by a 488 nm light source. In the presence of denatured (single-stranded) DNA, the dye molecules bind electrostatically to the strands and each other to form aggregates, whereby dye dye interactions cause a concentration dependent loss of absorbed energy and a subsequent metachromatic shift to red fluorescence (Darzynkiewicz, 1979). The microscopic assessment of sperm chromatin integrity classifies AO stained spermatozoa as normal if fluorescing green and abnormal if red. However, this visual classification introduces some subjectivity to the assessment, since the emission spectrum from individual spermatozoa is often a mix of wavelengths, with stained spermatozoa appearing yellow to brown and not clearly identifiable with either category. Nevertheless, the microscopic AO test (M-AOT) has demonstrated significant relationships with male infertility and with fertilization and pregnancy rates in IVF, independent of other sperm characteristics including sperm zona binding and morphology (Tejada et al., 1984; Liu and Baker, 1992a; Hoshi et al., 1996). Automation of the detection and analysis of AO fluorescence is provided by flow cytometry (FCM) and employed in the sperm chromatin structure assay (SCSA), which was first developed by Evenson et al. in 1980 as a potential measure of livestock fertility. FCM provides a powerful statistical advantage over manual microscopic methods through objective and rapid multi-parametric analysis of large numbers of cells. The SCSA assay assesses the integrity of sperm chromatin structure, using AO as a probe to measure the susceptibility of sperm DNA to in-situ induced denaturation. The original assay measured heat-induced denaturation, but this has subsequently been replaced with an acid detergent treatment (ph 1.2) (Evenson et al., 1986). Spermatozoa with a normal chromatin structure appear impervious to treatment, while spermatozoa with an abnormal chromatin structure undergo partial denaturation (Darzynkiewicz, 1979). The detergent Triton X-100 allows greater AO access to the DNA by permeabilizing the cell membranes, similar to the cell fixation procedure in the M-AOT. In addition to the acid detergent treatment step, SCSA also differs from the M- AOT in that both red and green fluorescence intensities are measured for individual cells, thus enabling a reproducible definition for the classification of spermatozoa with abnormal red intensity and quantitative measures that reflect the degree of denaturation averaged over the entire population. The percentage of sperm cells with abnormally high red fluorescence is given by the SCSA variable COMPα t, and in more recent terminology, the detectable DNA fragmentation index (Evenson et al., 2002). SCSA results are reported to be closely related to fertility in both animals and humans (Evenson et al., 1980; Ballachey et al., 1987; Dobrinski et al., 1994; Sailer et al., 1996). In particular, a threshold value of COMPα t >30% is reported to identify subfertile men and poor results with IVF (Evenson et al., 1999; Larson et al., 2000; Spano et al., 2000; Larson-Cook et al., 2003). Also, in both microscopic and automated methods of the AO test, the above studies have revealed some men with abnormal sperm chromatin but otherwise normal semen analysis results, suggesting that AO can detect sperm defects not apparent in standard semen analysis This study examines the assessment of sperm chromatin integrity using FCM measurement of AO fluorescence, including the impact of potential influences on the analysis such as delay in semen preparation and contamination of semen with bacteria. The relationship between the results from the microscopic and FCM assessments of AO fluorescence is also examined. The methodology of the sperm chromatin structure assay (SCSA) was originally published by Evenson et al. in Since that date, there have been modifications to protocol and terminology associated with the assay. SCSA is a federally registered trademark of SCSA Diagnostics, Inc., Brookings, South Dakota, USA. So far as is known, there are no patents or patents pending in respect of the protocol or analysis for the assay, nor does the trademark SCSA give any rights to, or financial involvement in the work undertaken at the Department of Obstetrics and Gynaecology, University of Melbourne in the subject of this article. Materials and methods Semen analysis Semen samples from 201 men being investigated for infertility were collected by masturbation after 2 5 days abstinence. Measurements of sperm concentration, progressive motility and straight-line velocity (VSL) were performed using a Hamilton-Thorne Motility Analyser (IVOS 10.8) (Hamilton Thorne Research, Beverly, MA, USA) with an Ident module. The Ident stain was dissolved in Tyrode s solution (5% BSA; CSL, Melbourne, Australia) at a final concentration of 16 µg/ml. Semen samples were diluted with an equal volume of the Ident stain. Those with high concentrations (> /ml) were diluted 1:4 in seminal plasma, prior to staining. Sperm vitality was determined using eosin nigrosin staining (6.7 mg/ml eosin and 100 mg/ml nigrosin in H 2 O) and 200 spermatozoa per sample were analysed at 400 magnification. Semen smears were fixed in 90% ethanol (30 min at room temperature), air-dried and stained with haematoxylin (with acetic acid) and eosin (0.5%). The morphology of 200 spermatozoa was assessed under an oil immersion lens at 1000 magnification using World Health Organization criteria (WHO, 1999). Flow cytometry-acridine orange test (FCM-AOT) FCM-AOT was conducted following the protocol for SCSA described by (Evenson and Jost, 1994). Samples were diluted 1:4 in TNE buffer (0.15 mol/l NaCl, 0.1 mol/l Tris, 1 mmol/l EDTA, ph 7.4) and stored at 70 C in 500 µl aliquots ready for batch analysis. Immediately prior to analysis, the samples were thawed at 37 C and diluted to a concentration of spermatozoa/ml in TNE. Aliquots of 200 µl of the diluted sample were treated with 400 µl acid detergent solution (0.1% Triton X-100, 0.15 mol/l NaCl, 0.08 N HCl, ph 1.2) and after 30 s stained with 1200 µl of AO staining solution (6 µg AO/ml, 37 mmol/l citric acid, 126 mmol/l Na 2 HPO 4, 1 mmol/l EDTA, 0.15 mol/l NaCl, ph 7.4). Three minutes after commencing the 399

3 400 acid detergent treatment the green and red fluorescence intensities of 10,000 events were measured using a Becton Dickinson (BD) FACScan orthogonal flow cytometer (BD Biosciences, North Ryde, NSW, Australia) with a closed-quartz flow cell and a 488 nm, 100 mw argon ion laser. Green and red fluorescence intensities for each cell were measured using a 530 ± 15 nm bandpass and 650 nm longpass filter respectively, with detector pulse heights recorded over 1024 channels using the online BD CellQuest software. A reference sample pooled from equal volumes of semen from seven fertile men was cryopreserved and used to calibrate the flow cytometer detectors at the beginning of every run and after every fifth sample. Red and green detector voltages for the reference sample were adjusted to match the Evenson guidelines of the mean green intensity (X green ) at channel 445 ± 5 and mean red intensity (X red ) at channel 145 ± 5. Duplicate measurements were made for each sample and all data were stored as list files for eventby-event analysis offline using software developed within this laboratory. From a preliminary examination of the event-by-event data from all control and patient samples, gates at low green (channel 325) and low red (channel 115) fluorescence intensities were chosen to define background events to be excluded from the summary analysis for each sample (Figure 1a). Events falling into the limiting channel 1024 for either detector were also excluded. The variable α t, the proportion of red fluorescence expressed as a percentage of the total of red plus green fluorescence, was calculated for each gated event (Darzynkiewicz, 1979) and displayed as a histogram for each sample (Figure 1b). From the preliminary examination of the α t histograms, a fixed cut-off value of α t = 26% was found to differentiate between events in the main peak (representing the normal sperm population) and those with abnormally high proportions of red fluorescence, in all samples. The associated summary variable for a sample, %Abnormal α t, was therefore defined as the percentage of gated events with α t 26%. It is the equivalent of COMPα t, and more recently the detectable DFI variables of SCSA (Evenson and Jost, 1994; Evenson et al., 2002) (Figure 1a,b). Samples with a high proportion of spermatozoa with abnormal chromatin structure undergo greater denaturation following the acid detergent treatment and their α t histograms demonstrate a broader distribution of α t, with a greater proportion of events with α t 26% and correspondingly higher mean (Xα t ) and standard deviation (SDα t ) (Figure 1c). The summary variable %HighGreen was also defined by a fixed cut-off (channel 750 of 1024 for green fluorescence), and represents the percentage of sperm with abnormally high absolute values of green fluorescence intensity, compared with those of the main population. %HighGreen is thought to represent immature sperm or spermatids that have not undergone chromatin condensation during epididymal transit (Evenson et al., 1986). Factors influencing FCM-AOT analysis The effect of delay in the preparation of semen on FCT-AOT results was examined by leaving nine semen samples in specimen jars at room temperature (~20 C) for up to 6 h. At 1, 2, 4 and 6 h post-ejaculation, aliquots of each of the samples were diluted 1:4 in TNE buffer and stored at 70 C for subsequent analysis. To examine the effect of bacteria in the semen on FCM-AOT results, two species of bacteria, Escherichia coli and Staphylococcus epidermidis were added to 14 different semen samples. The samples were diluted to spermatozoa/ml in TNE buffer and bacteria added at concentrations of approximately /ml, /ml and /ml approximately 1 h prior to storage at 70 C. Unspiked aliquots of the same samples were used as controls. Reproducibility of FCM-AOT results Within sample variation reflects measurement error and was estimated from 10 replicate assays on the same semen samples. Samples from 25 men were used in this study, selected to represent a wide range of results from the FCM- AOT (%Abnormal α t = 4 54%). The between-samples, within-subject variation reflects both biological day-to-day changes and measurement error, and was estimated from comparison of two semen samples (provided 1 3 months apart) from 35 men. The microscopic-acridine orange test (M-AOT) The microscopic AO test was performed following the protocol previously described (Tejada et al., 1984; Liu and Baker, 1992a) for the assessment of DNA normality. Smears of 185 semen samples were fixed in Carnoy s solution (3:1, methanol:glacial acetic acid) for a minimum of 3 h, washed and air-dried. The slides were then immersed in AO working solution (2.5 ml of 1% AO stock solution, 10 ml 0.1 mol/l citric acid and 400 µl of 0.3 mol/l Na 2 HPO 4.H 2 O, prepared daily) for 5 min, rinsed with H 2 O and wet-mounted immediately for reading in a darkened environment. The percentage of spermatozoa with normal DNA (green fluorescence) was determined by rapid counting of 200 spermatozoa under a fluorescence microscope (Dialux 20, Leitz Wetzlar) with 400 magnification (oil immersion lens) and excitation wavelength of nm. Avoiding unnecessary delays and applying the above procedures was systematically found to overcome the reported problems of dye fading and non-uniform staining in the M-AOT assessments. Two observers independently assessed each slide and the mean value was used for analysis. Experiments were devised to examine the possibility that differences between the FCM and microscopic assessments of AO fluorescence may be generated by the unshared acid detergent and fixation steps used respectively in these techniques. Ten semen samples were subjected to three different treatments prior to staining with AO and microscopic assessment: 1) smear fixed in Carnoy s solution, washed in 10 ml 0.9% NaCl and air-dried; 2) treated with acid detergent solution (as for FCM-AOT), smeared on slides and air-dried; or 3) treated with acid detergent solution, smeared on slides and fixed in Carnoy s solution. Statistical analysis Statistical analysis was preformed using MINITAB 13.1 (MINITAB statistical software, MINITAB Inc., State College, PA, USA). ANOVA was used to assess the significance of differences within and between sample groups, and the

4 Figure 1. (a) A typical red green fluorescence cytogram for the FCM-AOT. The boxed region in the lower left hand corner represents low intensity background events excluded from the analysis. The labelled population of normal spermatozoa emit a predominance of green fluorescence, defined by α t = 100 red/(red + green) <26. The %HighGreen variable represents the percentage of spermatozoa with a higher green fluorescence intensity than the main population. (b) An α t frequency plot for a sample with normal chromatin structure. (c) An α t frequency plot for a sample with a high proportion of spermatozoa with abnormal chromatin structure. 401

5 components of variance. Spearman s ranked correlation and multiple regression analysis were used to examine the relationship between FCM-AOT results and the standard semen analysis variables of volume, concentration, vitality, progressive motility, straight line velocity (VSL) and morphology. Ethics approval The Royal Women s Hospital Research and Ethics Committee approved the project. Results Factors influencing FCM-AOT analysis No FCM-AOT variables were significantly affected by delaying the preparation of semen samples for analysis by up to 6 h (two-way ANOVA, P > 0.05). The results for %Abnormal α t are illustrated in Figure 2. The qualitative effect on the assay of the added presence of E. coli in a normal semen sample is shown in the cytograms of Figure 3 for the control sample and three concentrations of bacterial contamination. As the concentration of added bacteria increases, there is an initial increase in the density of events in the background region not included in the α t analysis, but at the extreme concentration of 10 8 bacteria/ml (Figure 3d) a distinct population of events is introduced at low but above gated levels of fluorescence, corresponding to α t values higher than those of the normal sperm population. By paired t- test, the only significant difference in FCM-AOT results between control and spiked samples was at this extreme level of contamination, with a mean %Abnormal α t of 11.5 for the control and 16.8 for the spiked sample (P < 0.001, n = 14). Although the cytograms of samples spiked with Staph. epidermidis had a similar appearance, none of the results was significantly affected (control: mean %Abnormal α t = 11.5; : mean = 12.4, P = 0.22). Reproducibility of FCM-AOT measurements Relationship of FCM-AOT with standard semen analysis Standard semen analysis and FCT-AOT results are summarized for 201 semen samples in Table 1. The samples represent a wide range of semen quality, with about 15% oligozoospermic, 30% asthenozoospermic and 46% with poor sperm morphology. The correlations between FCM-AOT and standard semen analysis variables are listed in Table 2. FCM- AOT results exhibited no significant correlation with volume, and only low correlations with sperm concentration. All FCM- AOT derived variables, particularly %HighGreen, exhibited significant correlations with sperm morphology. The variables based on α t (%Abnormal α t, Xα t and SDα t ) were significantly related to motility and to a lesser degree to vitality, morphology and VSL. The correlations between FCM-AOT and standard semen analysis variables were similar in magnitude to the correlations observed between many of the standard semen variables. For example, sperm morphology and %Abnormal α t were significantly (P < 0.001) related to motility (ρ = and respectively), VSL (ρ = and 0.406) and concentration (ρ = and 0.222). Multiple regression analysis indicates that 46.4% of sample variation in %Abnormal α t could be explained by variation in standard semen parameters, with the major contributions from motility (r = 0.298), vitality (r = 0.285) and morphology (r = 0.282). Correlation of FCM-AOT with the microscopic acridine orange test (M- AOT) The M-AOT was performed on 185 semen samples. The percentage of sperm with normal DNA (scored green) ranged from 13 to 98% per sample, with an overall mean of 68.6% (SD 19.6%). The only FCM-AOT variable significantly related to the microscopic test was X red (P < 0.001), with Xα t, X green and %HighGreen showing a weak correlation (P < 0.05) and %Abnormal α t and SDα t notably, not significantly related (Table 3). Of the standard semen analysis variables, only sperm vitality and morphology were significantly related to the M-AOT results. 402 Figure 4 illustrates the variation of %Abnormal α t results within and between semen samples from the same individuals. Results for the other FCM-AOT variables were similar or less variable. The variation of replicate measurements within a sample was low (%Abnormal α t : SD = 1.4, CV = 13%), with the outlier indicated in Figure 4a excluded from analysis. While samples with a mean %Abnormal α t >10 appeared to have higher standard deviations than those <10 (1.549 and respectively), the difference was not statistically significant (F 9/14 = 1.853, P > 0.05). The overall 95% confidence interval for %Abnormal α t was 4.6. Figure 4b illustrates the difference in %Abnormal α t between two semen samples collected from 35 individuals. The components of variance in ANOVA showed the percentage of variation between individuals was 61% and within individuals 39%. Although the majority of sample pairs lay within the measurement error of 4.6 determined from the replicate measurements, the degree of variation was significantly greater than this error (F-test: F 34/24 = 4.82, P < 0.05). Figure 2. Effect of delaying semen storage on FCM-AOT analysis, illustrated for the main FCM-AOT variable, %Abnormal α t. Analysis was determined in duplicate at 1, 2, 4 and 6 h after ejaculation in nine samples. No significant changes in %Abnormal α t were observed (two-way ANOVA, P = 0.429).

6 Figure 3. The effect on the red green cytogram with the addition of E. coli to a normal semen sample. As the concentration increases there is an initial increase in the density of events in the background region which at the extremely high contaminant concentration (10 8 bacteria/ml) falls within the gated region and the contaminant population significantly affects the analysis (arrow). For this sample, %Abnormal α t : control = 15.7, spiked ( ) = 18.5 and spiked ( ) = Figure 4. Reproducibility of %Abnormal α t results within and between semen samples. (a) Standard deviation of %Abnormal α t plotted against mean of %Abnormal α t for 10 replicates in 25 samples. One sample (hollow diamond) lay >3 SD from the pooled mean and was excluded from analysis. (b) The difference between two measurements of %Abnormal α t in pairs of different semen samples from 35 individuals. The dashed lines are the mean and 95% confidence limits. 403

7 Table 1. Summary statistics of standard semen analysis and FCM-AOT variables for 201 men. Method of Variable Mean (SD) Range Normal % outside analysis limit normal range Standard Volume (ml) 3.5 (1.6) >2 a 11 Concentration 83.2 (79.0) 3 601>20 a 15 ( 10 6 /ml) Vitality (%) 86.2 (9.6) >75 a 8 Progressive 46.1 (16.9) 0 85 >40 a 30 motility (%) VSL (µm/s) 34.2 (8.2) 0 49 >30 24 Morphology 14.0 (15.1) 0 70 >15 a 46 (%) FCM-AOT %Abnormal α t 11.2 (8.4) 2 50 <30 b 4 Xα t (34.2) SDα t (36.6) X green (36.1) X red (22.8) %HighGreen 7.1 (4.6) 1 30 a World Health Organization (1999). b Evenson et al. (1999). Table 2. Correlations between FCM-AOT and standard semen analysis variables (Spearman s ranked test, n = 201). Semen variable %Abnormal α t Correlation coefficient %Abnormal α t Xα t Xα t SDα t SDα t X green a a X green X red X red %HighGreen %High Green Volume a a a a a a Volume (ml) Concentration b b a Concentration (10 6/ ml) Vitality b a a a Vitality (%) Motility a b Motility (%) VSL a a VSL (µm/s) Morphology b b The variable α t, is the proportion of red fluorescence expressed as a percentage of the total of red plus green fluorescence. a P 0.05, b P < 0.05, otherwise P <

8 Table 3. Correlation between microscopic AO test (M-AOT), %normal green fluorescence with the FCM-AOT and standard semen analysis variables (Spearman s ranked test, n = 185). Semen variable %Abnormal α t Xα t b SDα t X green b X red a %HighGreen b Volume Concentration Vitality a Motility VSL Morphology b a P < 0.001, b P < Ten samples were prepared with and without fixation and with and without acid detergent treatment and assessed by two observers. There were no significant differences between the mean percentages of normal DNA fluorescence following the different treatments: fixation (P = 0.7) and acid detergent treatment (P = 0.8). Discussion M-AOT (%normal) Both the automated FCM-AOT and the manual M-AOT have previously been applied to the assessment of human semen quality; however, no study has explicitly examined the relationship between these two similar techniques. This study investigated the reproducibility, robustness and independence of the FCM-AOT results compared with standard semen analysis, and also examined the relationship with M-AOT results for sperm chromatin integrity. A delay in the preparation and storage of semen by up to 6 h after ejaculation was found to cause no significant changes in FCM-AOT results, thus allowing preparation of semen to be delayed if necessary, without adversely affecting results. Evenson et al. (1991) had suggested that a strong fine line of fluorescence to the left of the main population observed in some cytograms may indicate the presence of bacteria in a semen sample. However, observations have found this occasional phenomenon in samples that had no obvious signs of infection (discolouration or the presence of bacteria or leukocytes under the microscope). However, many semen samples were visibly contaminated with bacteria, and therefore the effect of adding bacteria on the results of FCM- AOT analysis was examined. Using 14 different control samples spiked with either of two types of bacteria commonly present in semen (E. coli and Staph. epididymis), no concentration dependent change in the cytograms was seen to the left of the main normal population of events. For the E. coli spiked samples, there was a concentration dependent shift of a visible contaminant from the background region of the cytogram into the gated region, with relatively low green fluorescence intensity and abnormal α t value. This could be explained by the aggregation of bacteria at higher concentrations, with high α t values from the RNA in the bacteria. However, only at an extreme concentration rarely encountered in nature did the added E. coli significantly influence the calculated results for %Abnormal α t. Internal quality control studies suggest that the intralaboratory variation for standard semen analysis variables can be as high as 30% (Cooper et al., 1992; Clements et al., 1995; Auger et al., 2000). The results obtained for replicate measurements of FCM-AOT variables in this study indicate a much higher precision (%Abnormal α t : CV = 13%). The variation of FCM-AOT results between samples within a subject was also low. In most cases, the differences between two samples within an individual could be accounted for by measurement error. This consistency between samples from an individual demonstrates a higher stability of FCM-AOT results compared with standard semen analysis variables for an individual, in agreement with previous studies that have demonstrated that SCSA results for different samples within an individual are highly reproducible (Ballachey et al., 1987; Evenson et al., 1999). However, in a small proportion of subjects (three in 35), there were large differences outside experimental error. These differences most likely reflect transient, genuine changes in semen quality caused by febrile illness, infection or other factors (Evenson et al., 1991, 2000). Significant relationships were observed in this study between FCM-AOT and standard semen analysis variables. The α t based variables were significantly related to motility, vitality, morphology and VSL. Several publications have also demonstrated a relationship between SCSA and the semen analysis variables: significant negative correlations between COMPα t (Spearman tests on groups ranging in size from 45 to 277) and sperm morphology (ρ = 0.21 to 0.38), motility (ρ = 0.30 to 0.41) and vitality (ρ = 0.23 to 0.26) (Evenson et al., 1991, 1999; Spano et al., 1998, 1999). Although the correlation coefficients observed in the present study were slightly higher, this could be accounted for by differences in the patient populations and semen analysis techniques. The correlations observed in this and other studies are also similar in magnitude to those frequently observed between the various standard semen analysis variables (Table 2). The established correlations are consistent with the concept that defects of sperm production commonly affect all components of semen analysis. Moreover, due to large measurement errors in standard semen analysis techniques, even closely related semen variables can exhibit low correlations. Thus, for example, the Spearman s ρ for the correlation between such physically closely related variables as sperm motility and VSL is 0.611, equivalent in magnitude to the correlation between motility and %Abnormal α t or %HighGreen and %Normal morphology. Similarly, other measures of chromatin integrity related to those of AO, such as chromamycin A 3 and TUNEL analysis of DNA stand-breaks (Roux and Dadoune, 1989; Nasr-Esfahani et al., 2001; Zini et al., 2001) are related to the standard semen analysis variables (Tejada et al., 1984; Francavilla et al., 1996; Moilanen et al., 1999; Gandini et al., 2000; Irvine et al., 2000; Nasr-Esfahani et al., 2001). This study has revealed a surprising lack of correlation between the results of the automated FCM-AOT and the visual 405

9 406 M-AOT in their respective assessments of sperm DNA integrity. Since both tests ostensibly measure the susceptibility of spermatozoa to induced DNA denaturation using AO as the marker, the percentage of red spermatozoa assessed by eye under the microscope in M-AOT was expected to equate with the percentage of cells with an abnormally high proportion of red fluorescence (%Abnormal α t ) by FCM-AOT. Even given the subjectivity of bimodal classification of red and green fluorescence by visual assessment, this negative result is unexpected, particularly since the methodology of the M-AOT has been shown by several groups to be sufficiently reproducible to identify correlations between abnormal DNA integrity with sperm morphology, sperm zona pellucida binding and also fertilization rates in vitro (Claassens, 1992; Liu and Baker, 1992a,b; Hoshi et al., 1996). The only FCM-AOT variable significantly related (P < 0.001) to the M-AOT results was X red (ρ = 0.246), indicating the expected relationship between FCM mean red fluorescence with an increase in the percentage of cells with a visual predominance of red fluorescence. However, the weaker negative correlation with X green ( 0.153, P < 0.05) is contradictory. The lack of expected correlation between the FCM and microscopic methods is not explained by the different acid/detergent/fixation steps in these procedures. This was tested by subjecting spermatozoa to a range of treatments prior to microscopic assessment. No significant difference in the percentage of normal spermatozoa classified by M-AOT was detected when samples were either fixed, fixed following acid detergent treatment, left unfixed or left unfixed following acid detergent treatment. This result probably reflects that both the fixation (used in M-AOT) and detergent treatment (used in FCM-AOT) cause significant permeablization of cell membranes (Darzynkiewicz, 1979), and that the exposure of spermatozoa to low ph (~2.4) during the staining and fixation processes in M-AOT is not dissimilar to the acid treatment for FCM-AOT. The latter observation is supported by Evenson and Jost (1994), who report that increasing the harshness of the physical conditions applied to spermatozoa in the SCSA, such as lowering the ph in the acid detergent treatment, generates a proportionate increase in the percentage of spermatozoa with abnormally high α t in all samples, and does not alter the comparative assessment of chromatin integrity between samples. However, it should be noted that the high sensitivity of the fluorescence cytogram and associated α t results to changing acid concentration in the treatment step indicates a potential source of problems with reproducibility, as the acid denaturation medium is not appropriately buffered. In conclusion, the results of this study confirm that although FCM-AOT is not totally independent of standard semen analysis or the M-AOT, it is found to be a robust, sensitive and reproducible measure of semen quality, representative of the individual. Acknowledgements The authors would like to thank Ms Ming Li Liu and staff in the Reproductive Services and Andrology Laboratories for their assistance in obtaining and preparing samples for analysis. They would also like to thank Dr Donald Evenson for his technical assistance in establishing the FCM-AOT in this laboratory. This research was supported by the Royal Women s Hospital Research Advisory Committee. References Auger J, Eustache F, Ducot B et al Intra- and inter-individual variability in human sperm concentration, motility and vitality assessment during a workshop involving ten laboratories. Human Reproduction 15, Baker HWG 2001 Male infertility. In: De Groot LH, Jameson JL (eds) Endocrinology. Saunders, Philadelphia, pp Baker HWG, Burger HG, de Kretser DM et al Testicular vein ligation and fertility in men with varicoceles. Br Med J (Clin Res Ed) 291, Ballachey BE, Hohenboken WD, Evenson DP 1987 Heterogeneity of sperm nuclear chromatin structure and its relationship to bull fertility. Biology of Reproduction 36, Bonde JP, Ernst E, Jensen TK et al Relation between semen quality and fertility: a population-based study of 430 firstpregnancy planners. Lancet 352, Claassens OE, Menkveld R, Franken DR et al The acridine orange test: determining the relationship between sperm morphology and fertilization in vitro. Human Reproduction 7, Clements S, Cooke ID, Barratt CL 1995 Implementing comprehensive quality control in the andrology laboratory. Human Reproduction 10, Cooper TG, Neuwinger J, Bahrs S et al Internal quality control of semen analysis. Fertility and Sterility 58, Darzynkiewicz Z 1979 Acridine orange as a molecular probe in studies of nucleic acids in-situ. In: Melamed MR, Mullaney PF, Mendelson ML (eds) Flow Cytometry and Sorting. Wiley, New York, pp Dobrinski I, Hughes HP, Barth AD 1994 Flow cytometric and microscopic evaluation and effect on fertility of abnormal chromatin condensation in bovine sperm nuclei. Journal of Reproduction and Fertility 101, Evenson D, Jost L 1994 Sperm chromatin structure assay: DNA denaturability. Methods in Cell Biology 42, Evenson DP, Darzynkiewicz Z, Melamed MR 1980 Relation of mammalian sperm chromatin heterogeneity to fertility. Science 210, Evenson D, Darzynkiewicz Z, Jost L et al Changes in accessibility of DNA to various fluorochromes during spermatogenesis. Cytometry 7, Evenson DP, Jost LK, Baer RK et al Individuality of DNA denaturation patterns in human sperm as measured by the sperm chromatin structure assay. Reproductive Toxicology 5, Evenson DP, Jost LK, Marshall D et al Utility of the sperm chromatin structure assay as a diagnostic and prognostic tool in the human fertility clinic. Human Reproduction 14, Evenson DP, Jost LK, Corzett M et al Characteristics of human sperm chromatin structure following an episode of influenza and high fever: a case study. Journal of Andrology 21, Evenson DP, Larson KL, Jost LK 2002 Sperm chromatin structure assay: its clinical use for detecting sperm DNA fragmentation in male infertility and comparisons with other techniques. Journal of Andrology 23, Francavilla S, Cordeschi G, Gabriele A et al Chromatin defects in normal and malformed human ejaculated and epididymal spermatozoa: a cytochemical ultrastructural study. Journal of Reproduction and Fertility 106, Gandini L, Lombardo F, Paoli D et al Study of apoptotic DNA fragmentation in human spermatozoa. Human Reproduction 15, Giwercman A, Spano M, Lahdetie J et al Quality assurance of semen analysis in multicenter studies. ASCLEPIOS. Scandinavian Journal of Work Environment and Health 25, 23 25; discussion Hoshi K, Katayose H, Yanagida K et al The relationship between acridine orange fluorescence of sperm nuclei and the fertilizing ability of human sperm. Fertility and Sterility 66,

10 Irvine DS, Twigg JP, Gordon EL et al DNA integrity in human spermatozoa: relationships with semen quality. Journal of Andrology 21, Kruger TF, Acosta AA, Simmons KF et al Predictive value of abnormal sperm morphology in in vitro fertilization. Fertility and Sterility 49, Larson KL, DeJonge CJ, Barnes AM et al Sperm chromatin structure assay parameters as predictors of failed pregnancy following assisted reproductive techniques. Human Reproduction 15, Larson-Cook KL, Brannian JD, Hansen KA et al Relationship between the outcomes of assisted reproductive techniques and sperm DNA fragmentation as measured by the sperm chromatin structure assay. Fertility and Sterility 80, Liu DY, Baker HWG 1992a Sperm nuclear chromatin normality: Relationship with sperm morphology, sperm zona pellucida binding, and fertilization rates in vitro. Fertility and Sterility 58, Liu DY, Baker HWG 1992b Tests of human sperm function and fertilization in vitro. Fertility and Sterility 58, Liu DY, Baker HWG 1994a Disordered acrosome reaction of spermatozoa bound to the zona pellucida: a newly discovered sperm defect causing infertility with reduced sperm zona pellucida penetration and reduced fertilization in vitro. Human Reproduction 9, Liu DY, Baker HWG 1994b A new test for the assessment of sperm zona pellucida penetration: relationship with results of other sperm tests and fertilization in vitro. Human Reproduction 9, Liu DY, Du Plessis YP, Nayudu PL et al The use of in vitro fertilization to evaluate putative tests of human sperm function. Fertility and Sterility 49, Mahadevan MM, Trounson AO 1984 The influence of seminal characteristics on the success rate of human in vitro fertilization. Fertility and Sterility 42, Moilanen JM, Carpen O, Hovatta O 1999 Flow cytometric analysis of semen preparation, and assessment of acrosome reaction, reactive oxygen species production and leucocyte contamination in subfertile men. Andrologia 31, Nasr-Esfahani MH, Razavi S, Mardani M 2001 Relation between different human sperm nuclear maturity tests and in vitro fertilization. Journal of Assisted Reproduction and Genetics 18, Oehninger S 2003 Pathophysiology of oligoasthenoteratozoospermia: are we improving in the diagnosis? Reproductive BioMedicine Online 7, Roux C, Dadoune JP 1989 Use of the acridine orange staining on smears of human spermatozoa after heat-treatment: evaluation of the chromatin condensation. Andrologia 21, Sailer BL, Jost LK, Evenson DP 1996 Bull sperm head morphometry related to abnormal chromatin structure and fertility. Cytometry 24, Spano M, Kolstad AH, Larsen SB et al The applicability of the flow cytometric sperm chromatin structure assay in epidemiological studies. ASCLEPIOS. Human Reproduction 13, Spano M, Cordelli E, Leter G et al Nuclear chromatin variations in human spermatozoa undergoing swim-up and cryopreservation evaluated by the flow cytometric sperm chromatin structure assay. Molecular Human Reproduction 5, Spano M, Bonde JP, Hjollund HI et al Sperm chromatin damage impairs human fertility. The Danish first pregnancy planner study team. Fertility and Sterility 73, Tejada RI, Mitchell JC, Norman A et al A test for the practical evaluation of male fertility by acridine orange (AO) fluorescence. Fertility and Sterility 42, World Health Organization 1999 WHO Laboratory Manual for the Examination of Human Semen and Sperm Cervical Mucus Interaction. Cambridge University Press, Cambridge, UK. Zini A, Bielecki R, Phang D et al Correlations between two markers of sperm DNA integrity, DNA denaturation and DNA fragmentation, in fertile and infertile men. Fertility and Sterility 75, Received 10 December 2003; refereed 23 December 2003; accepted 13 January