DNA flow cytometry of human semen

U.B. Hacker-Klom1,5, W. Göhde2, E. Nieschlag3 and H.M. Behre3,4

1 Clinic and Policlinic of Radiotherapy–Radiooncology, 2 Institute of Radiobiology, 3 Institute of Reproductive Medicine and 4 Department of Obstetrics and Gynaecology, University of Münster, Germany


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
The aim of this study was the evaluation of DNA flow cytometry for the analysis of male infertility. 171 ejaculates from 155 patients with fertility problems were analysed by flow cytometry and by conventional microscopical procedures. Using flow cytometry, it was possible to determine the relative proportions of the various cell populations: mature haploid and abnormal diploid mature spermatozoa, cellular fragments, immature germ cells (haploid round spermatids, diploid cells, S phase and 4C cells), and of leukocytes as indicators of infection. A linear association was observed between sperm concentration in semen as quantified by light microscopy and by flow cytometry, even with fewer than 20x106 spermatozoa/ml. Eight classes of histograms, each with differing fractions of spermatozoa and other particles, were obtained and correlated with the results of the spermiograms. During the 10 year follow-up, the two patient groups with a low sperm concentration or a high concentration of cellular debris exhibited significantly impaired fertility. The two patient groups with >=5% diploid spermatozoa and with malcondensed sperm chromatin were also subfertile. No ovulatory disorders were revealed in the 155 female partners. DNA flow cytometry thus provides an additional dimension to semen analysis not easily gained by other methods and has the advantage of being rapidly performed and interpreted. We therefore recommend application of this technique in the diagnosis of male infertility.

Key words: DNA flow cytometry/light microscopy/male infertility/semen


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Public concern has been generated recently following claims of a reduction of human semen quality during the past 50 years: in a meta-analysis of 61 studies carried out at various centres worldwide (Carlsen et al., 1992Go), a significant decrease in mean sperm concentration occurred between 1940 and 1990 from 11.3x106/ml to 6.6x106/ml (P < 0.0001). Other subsequent studies (Auger et al., 1995Go; Irvine et al., 1996Go) reported similar results. It has been proposed that lifestyle, environmental toxins or prenatal exposure to oestrogens might contribute to this phenomenon (Sharpe and Skakkebæk, 1993Go). However, the lowering of reference values for `normal' sperm concentration from 60x106/ml in the 1940s (MacLeod and Heim, 1945Go) to the present value of 20x106/ml (WHO, 1987Go) alone could be responsible for the observation (Bromwich et al., 1994Go). The standard determination of sperm concentration is by use of a haemocytometer. It has been shown, however, that there is a high variability in results obtained by this method (Neuwinger et al., 1990Go). Therefore the application of other methods might be useful.

Since the possibility of a long-term decline in human sperm concentration is highly controversial (Lerchl and Nieschlag, 1996Go), prospective studies on large population groups will be necessary to test the hypothesis. These could be facilitated by application of an automated method for sperm counting such as flow cytometry (FCM). Since this allows the analysis of thousands of spermatozoa, statistical errors are minimized.

Among the numerous studies on sperm populations in mammals (e.g. Harrison, 1997), only some of those reporting FCM analysis of semen samples relevant to the present study need be mentioned here. Measurement problems resulting from the asymmetric shape and the highly condensed chromatin (CC) of the spermatozoa were finally overcome: Zante introduced papain for the decondensation of sperm chromatin and used a flow cytometer less susceptible to optical-geometric artefacts (Zante et al., 1977Go), while Dean improved the measuring accuracy by hydrodynamic orientation of spermatozoa (Dean et al., 1978Go). Further studies followed (Otto et al., 1979aGo; Johnson et al., 1993Go; Ashwood-Smith, 1994Go; Fugger et al., 1995).

The reduced fluorescence intensity of stained sperm DNA when using epi-illumination systems allows reliable differentiation between haploid spermatozoa and haploid round spermatids and between diploid spermatozoa and other diploid cells (early germ cells or somatic cells such as leukocytes or epithelial cells) (Van Dilla et al., 1977Go; Otto et al., 1979bGo; Hartmann et al., 1982Go). Cell sorting of testicular cells and subsequent DNA FCM using experimental animals has been used to confirm the identity of the cells in each DNA histogram peak (Hacker-Klom et al., 1989Go). Since the histograms obtained from both testicular and ejaculated cells are qualitatively similar in various different mammals including the human, the conclusions drawn from the sorting data may also be applicable to man. Clinical application of FCM as a suitable method for supplementing the information obtained from the spermiogram of patients with infertility was proposed by Otto et al. (1979b).

In the present study, we demonstrate that FCM provides information about the condensation state of chromatin and the ploidy status of spermatozoa additional to the data obtained by conventional light microscopy. Sperm counts are obtained by FCM. A sample of 155 patients with infertility was analysed and classified into eight groups with differing sperm DNA histograms. To the best of our knowledge this is the first 10 year follow-up study revealing subfertile patient groups by DNA content of spermatozoa.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Patients and sample collection
A total of 171 ejaculates of 155 consecutive patients attending the Institute of Reproductive Medicine for suspected infertility was analysed. The patients were Caucasian and 20–53 years old (median: 32 years). The samples were obtained by masturbation after 2–7 days of abstinence. If two or three ejaculates per patient were available, they were all analysed to assess the reproducibility of the results obtained.

All female partners were seen for infertility work-up in the Department of Obstetrics and Gynaecology of the University. No ovulatory disorders were revealed in the 155 women. In two women bilateral occlusion was detected by laparoscopy. In-vitro fertilization was therefore performed.

FCM
Aliquots of the 171 ejaculates were fixed with 10% acetic acid for 24 h to 2 months at 5°C. The semen samples were prepared slightly modified from the previous protocol (Otto et al., 1979aGo). Thus 0.2 ml of fixed cells were diluted in 3 ml DAPI solution (5 µg 4',6-diamidino-2-phenylindole 2·HCl/ml 0.1 mol/l Tris-HCl buffer, pH 8.0, with 40 mmol/l MgCl2). In special cases, the fixed cells were centrifuged for 10 min at 200 g, resuspended in 1 ml 0.1 N sodium citrate-sodium hydroxide buffer, pH 6.4, containing 300 Anson units papain/ml (Anson unit: 1 unit will produce a {Delta}a280 of 0.001 per min at pH 2.0 at 37°C, measured as TCA-soluble products using haemoglobin as substrate), 20 mM dithioerythritol (DTE), 1 mmol/l ethylenediaminetetraacetic acid (EDTA) disodium salt and 1% dimethylsulphoxide (DMSO) and incubated for 15 min at 20°C. The samples were centrifuged again, resuspended and stained with DAPI as above.

A PAS II flow cytometer (Partec GmbH, Münster, Germany) equipped with a mercury arc lamp (HBO 100; Osram, Munich, Germany), a UG1 excitation filter, KG1 and BG38 heat filters, a TK420 beam splitter, and a GG435 barrier filter (Schott Glas, Mainz, Germany) in front of the photomultiplier was used. Each sample was measured at least twice.

Analysis of frequency histograms
Approximately 2x104 cells were measured for each frequency histogram. DNA frequency histograms were evaluated using cumulative frequency distributions (Figure 1Go). We discriminated one category more than Fosså's group (Fosså et al., 1989Go), i.e. five categories: (i) cells with sub-haploid DNA content <1CC (debris that may be of apoptotic origin, Darzynkiewicz et al., 1992). The term `CC' means `condensed chromatin' and is used to indicate haploid spermatozoa which have a normal DNA content of IC but which is too condensed to be stained accordingly (Zante et al., 1977Go); (ii) mature haploid spermatozoa in the 1CC peak; (iii) haploid round spermatids in the 1C peak; (iv) diploid spermatozoa in the 2CC peak; and (v) cells registered to the right of the 2CC level including 2C cells (leukocytes, G1-spermatogonia, primary spermatocytes at preleptotene etc.), cells in the DNA synthesis phase (S) and 4C cells (primary spermatocytes etc.; cf. Zante et al., 1977, Fosså et al., 1989).



View larger version (27K):
[in this window]
[in a new window]
 
Figure 1. DNA histograms of normal human semen and corresponding cumulative frequency distribution. The relative DNA content is indicated on the x axis, which is divided into 256 channels, and the number of cells per channel on the y axis. The frequencies of the five different cell populations are: (i) sub-haploid region <1CC (debris): 21%; (ii) 1CC peak (mature haploid spermatozoa): 71%; (iii) 1C peak (round spermatids): 1.2%; (iv) 2CC peak (diploid spermatozoa): 4.7%; and (v) >2CC level including cells at 2C (leukocytes; G1-spermatogonia, primary spermatocytes etc.), in the DNA synthesis phase and at 4C: 2.3%.

 
Diploid spermatozoa of mammals are represented by a peak of twice the modal channel number of haploid spermatozoa as confirmed by cell sorting (Hacker-Klom et al., 1989Go). Reproducibility was examined by six consecutive measurements of one sample and yielded a coefficient of variation (CV) of 0.067 for the percentage of 1CC cells (mature haploid spermatozoa). The coefficient of variation indicating measuring accuracy was determined by calculating the ratio of the standard deviation to the mean. Sperm counts were measured in a volume of 0.2 ml by means of a special electronic device within the FCM (Partec GmbH).

Spermiograms
Ejaculates were analysed by light microscopy according to WHO (1987).

Statistics
Correlation coefficients between different features of spermatozoa as determined by FCM and light microscopy were determined for identical samples with the method of least square deviations, using a programmable calculator assuming a linear regression. Since neither the correlation coefficient nor regression analysis was considered appropriate in the analysis of measurement method comparison, a graphical technique was applied (Bland and Altman, 1986Go). The {chi}2 test with Yates' correction for continuity for contingency tables and the unpaired t-test were applied wherever appropriate. In general, data are given as mean ± SD.


    Results
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
There was a strong linear association between sperm concentration of 63 semen samples as determined by LM and FCM (Figures 2 and 3GoGo). All 171 semen samples can be classified into eight classes as suggested by the FCM data (Table IGo).



View larger version (15K):
[in this window]
[in a new window]
 
Figure 2. Sperm concentration (106/ml) of semen samples as measured by flow cytometry (FCM) and conventionally by light microscopy (LM): (a) all 63 concentrations; (b) 31 samples with sperm concentration <20 x106/ml.

 


View larger version (20K):
[in this window]
[in a new window]
 
Figure 3. Difference of sperm concentration (106/ml) (log) measured by light microscopy (LM) and flow cytometry (FCM) against sperm concentration (106/ml) measured by FCM as a double log plot (cf. Bland and Altmann, 1986).

 

View this table:
[in this window]
[in a new window]
 
Table I. Summary of the data from 171 semen samples within the eight classes as determined by DNA flow cytometry (FCM).
 
The peak of 1CC mature haploid spermatozoa in the DNA histograms appeared at 66% (range: 60–71%) of the fluorescence intensity of haploid round spermatids at 1C (Figure 4Go). The samples of the first three classes are normozoospermic or oligozoospermic, showing a normally distributed 1CC peak with decreasing proportion of 1CC, and were considered normal or quasi-normal. Typical after increasing the high voltage was the splitting of the peak at 1CC, indicating discrimination of the two populations of X and Y chromosome-bearing spermatozoa with the Y spermatozoa on the left as demonstrated here by one sample from class 1 (Figure 4aGo). The material to the left of the 1CC peak represents cellular debris. In contrast to this histogram, the other histograms in Figure 4Go were measured at a lower input of only 314 V to the photomultiplier. This decrease in high voltage led to a shift of the main peak at 1CC to the left of the histogram, enabling us to visualize the range up to 4C. Class 1 is considered normal with >=90% 1CC: a representative histogram (Figure 4bGo) shows only one major peak representing normal haploid spermatozoa at 1CC comprising 91% of the measured particles. The rest is cellular debris to the left of the main peak (<1CC), haploid round spermatids at 1C and diploid spermatozoa at 2CC. No signals were registered in the region to the right of 2CC (2C, S and 4C). This ejaculate is normozoospermic (72x106 spermatozoa/ml).



View larger version (28K):
[in this window]
[in a new window]
 
Figure 4. Ten DNA histograms of human semen: (a) the peak representing haploid spermatozoa at 1CC is split into two peaks representing Y and X chromosome bearing spermatozoa; (b–j) after decreasing the high voltage to the photomultiplier, the spectrum up to 4C is visible. (b) Class 1: DNA distribution of a normozoospermic man representing >=90% mature haploid spermatozoa at 1CC. (c) Class 2: nearly normal DNA histogram with 71% mature haploid spermatozoa. (d) Class 3: more severe disturbance of spermatogenesis representing only 67% at 1CC. (e) Class 4: DNA histogram reflecting >=5% of diploid spermatozoa at 2CC. (f) Class 5: the chromatin condensation of 55% of the haploid spermatozoa is disturbed as reflected by the skewing of the DNA histogram to the left. (g) and (h) Class 6: the presence of >10% of different immature spermatogenic cell types at 1C, 2C, S and 4C levels besides mature haploid spermatozoa is reflected in these histograms with the more extreme case in (h). (h) The 1C peak (round spermatids) appears in the place of 1CC (haploid spermatozoa) in this histogram because 1CC was shifted to the left by lowering the high voltage applied to the photomultiplier in order to make the whole spectrum up to 4C visible in this particular case. (i) Class 7: the DNA histogram reflects a total count of only 3.5 x106 spermatozoa in the ejaculate. (j) Class 8: only cellular debris is present in the ejaculate, as shown by the DNA histogram. This patient is azoospermic.

 
Class 2 was characterized by a 1CC peak that contained 70–90% of the particles counted. In one representative sample (Figure 4cGo), there were 71% mature haploid spermatozoa and a great deal of cellular debris (26%). The other particles were haploid round spermatids and diploid spermatozoa, and only 0.52% were >2CC. The ejaculate had a volume of 2.4 ml with a pH of 7.8 and 34x106 spermatozoa/ml. According to the spermiogram, only 29% of the spermatozoa were normal. The 42 samples that fell into this class had a mean of 46 ± 14% normal spermatozoa (Table IGo).

Class 3 contained 10 histograms with <70% mature haploid spermatozoa at 1CC. The typical DNA histogram (Figure 4dGo) shows a peak representing haploid mature spermatozoa comprising 67% of the particles counted, a high amount of debris (31%), a few haploid round spermatids, diploid spermatozoa and no cells with a DNA content higher than 2CC. The ejaculate is oligozoospermic (3.3x106 spermatozoa/ml) and teratozoospermic with only 17% normal spermatozoa. A semen analysis of the same patient ~4 months earlier yielded a similar spermiogram. FCM analysis assigned this earlier sample to class 5.

Histograms of classes 4–8 characterized different types of spermatogeneic perturbations. Class 4 has diploid mature spermatozoa at 2CC at a high level of at least 5% and >70% 1CC. The typical histogram showed 6.3% diploid spermatozoa (Figure 4eGo). This ejaculate was normozoospermic with 72x106 spermatozoa/ml. In all, 47 samples fell into this class (Table IGo). Within class 4, there were 8.6 ± 3.5% diploid spermatozoa compared with only 2.5 ± 0.72% within group 1, and 2.1 ± 0.54% double-headed spermatozoa were identified by LM in group 4 in contrast with only 0.6 ± 0.35 within group 1. The difference is significant at the P < 0.05 level by t-test.

Class 5 was characterized by a reproducible skewing of the 1CC peak to the left (Figure 4fGo). Although the skewing could not be changed by treating the samples with papain for 15–60 min (thus inducing sperm chromatin decondensation), no explanation other than a disturbance of chromatin condensation of the haploid spermatozoa that could make the spermatozoa resistant to papain could be found. In this ejaculate (Figure 4fGo) 55% of the haploid spermatozoa were not properly condensed. The patient had a parvisaemia (pathologically small ejaculate volume <2 ml), with an ejaculate volume of only 1.2 ml, was normozoospermic with 40x106/ml, and had 39% normal spermatozoa. Sixteen histograms fell into this class (Table IGo). Only 45% of the samples within group 5 were normozoospermic.

Typical of class 6 is that >10% cells were >1CC, indicating the presence of immature germ cells and/or inflammatory cells. The representative histogram of class 6 (Figure 4gGo) shows 68% haploid spermatozoa, 8% debris and other cell types: spermatogenic cells, including haploid round spermatids (9%), diploid spermatozoa (5%), and cells with a regular 2C DNA content (4%), e.g. leukocytes and macrophages indicating infection. The spermiogram revealed that the ejaculate is oligoteratozoospermic (7.6x106 spermatozoa/ml with only 12% normal spermatozoa). In one extreme case, the histogram resembles a typical DNA frequency distribution of mammalian testicular tissue (including that of man) with four peaks (Figure 4hGo). In the ejaculate, there were only 0.4x106 spermatozoa/ml and 23% round cells as revealed by LM. Sixteen samples fell into this category (Table IGo). Within this group, there were only 29% normozoospermic samples and, on average, more amorphous spermatozoa than normal forms. The frequency of round cells was highest in this group: 9.4 ± 1.0x106/ml in contrast with only 3.9 ± 0.8x106/ml in group 1.

Class 7 contained no or only a few spermatozoa/ml. No complete histogram could be obtained even if the whole sample was measured (Figure 4iGo). As revealed by light microscopy, the sample came from a cryptozoospermic teratozoospermic ejaculate (0.7x106 spermatozoa/ml, total volume 5 ml containing 2x106/ml round forms, and 37% normal spermatozoa in the sediment). Sixteen samples fell into this category. The spermiograms revealed a mean of only 2.2x106 spermatozoa/ml among samples within this group (Table IGo).

Class 8 was characterized by a skewing of the particle distribution from channel 0 onwards, indicating a preponderance of cellular debris in the representative DNA histogram (Figure 4jGo). This ejaculate, with a volume of 7.0 ml, pH 7.5, was totally azoospermic. Ten samples fell into this category (Table IGo). None of these samples was normozoospermic. The spermiograms revealed that any spermatozoa present were amorphous rather than normal, and some defect tails were found.

Table IGo summarizes the results of the 171 ejaculates assigned to classes 1–8: only 7% of the patients with fertility problems are in the class with the highest sperm quality (class 1). Overall, the patients presented with a mean of 68 ± 23% haploid spermatozoa, a mean sperm density of 33 ± 44x106/ml and a mean of 41 ± 18% normal spermatozoa. In all, 13% of the patients naturally fathered a child during the 10 years of observation. Only 4% of the men with >=5% diploid spermatozoa (class 4), 17% of class 6 and none of the class 5 patients with malcondensed spermatozoa or class 7 and 8 patients with low sperm concentrations or high amounts of cellular debris in the semen respectively fathered children. The two cycles of in-vitro fertilization resulted in a pregnancy in one woman whose husband belonged to class 3. The husband of the woman not achieving a pregnancy by in-vitro fertilization belonged to class 4. The {chi}2 test reveals a statistically significant difference in paternity rates between the classes (P = 0.02). When classes 1–3 and 4–8 are compared, the difference is highly significant (P < 0.001).

Assuming a linear correlation, the percentage of 1CC cells in the DNA histogram was correlated best with the percentage of normal spermatozoa in the spermiogram (r = 0.67) (Table IIGo). Debris in the histograms were correlated most favourably with spermatozoa with defective tails (r = 0.74), diploid spermatozoa with double-headed spermatozoa (r = 0.96), 2C cells with leukocytes (r = 0.97), and skewing of peak I with amorphous sperm heads (r = 0.76).


View this table:
[in this window]
[in a new window]
 
Table II. Correlation coefficients (r) obtained between flow cytometry (FCM) data and characteristics observed by light microscopy (LM) for identical samples: % haploid spermatozoa (FCM) is most strongly correlated with % normal spermatozoa (LM), % debris <1CC with % defect sperm tails, % diploid spermatozoa with % duplicate sperm heads, % 2C cells with % leukocytes, and a skewing to the left of the 1CC peak with % amorphous sperm heads
 
The percentage of haploid spermatozoa as measured by FCM within the group of three azoospermic patients was zero (Table IIIGo). Within this group, there were only debris and >2CC cells indicating inflammation. Within the group of 117 oligozoospermic patients, there were 65 ± 40% haploid and 3.8 ± 3.0% diploid spermatozoa (Table IIIGo). Within the 51 normozoospermic patients, 80 ± 20% haploid and 4.3 ± 3.8% diploid spermatozoa were found.


View this table:
[in this window]
[in a new window]
 
Table III. DNA flow cytometry (FCM) data and sperm concentration as arithmetic means ± standard deviation: the 171 ejaculates are assigned to three groups (azoospermic, oligozoospermic and normozoospermic samples)
 
Of 155 patients, 141 gave one ejaculate, 12 gave two and two patients gave three samples. 16/24 (67%) of the samples from the 12 patients providing two sperm samples for analysis at an interval of several weeks were assigned twice to the same classes; the remaining 8/24 (33%) were not. Of the six ejaculates provided by two patients, two samples from each patient were assigned to one class, and the other sample to another class. Differences in classification occurred over time for quantitative rather than qualitative reasons, for example, a finding of 4.0% diploid sperm in the first sample and 5.1% diploid sperm in the second.


    Discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
To overcome the influence of subjective factors in semen analysis by conventional methods, intensive efforts are being made to establish objective laboratory methods, e.g. by computer-aided sperm analysis (CASA). However, `CASA is highly dependent on the system settings used' (Knuth et al., 1987) which is especially critical in cases of oligozoospermia (Chan et al., 1989Go).

As has been shown in the present paper, FCM allows precise determination of sperm concentration. Linear associations between the sperm concentration obtained by conventional LM and by FCM for normozoospermic men and for oligozoospermic patients with counts down to 0.1x106 spermatozoa/ml respectively indicate that counting by FCM may be performed reliably, rapidly and objectively.

The 155 patients enrolled in our study had a mean sperm concentration of 32.6 ± 43.7x106/ml. The average sperm concentration ±SD of 68 ± 23% within the group of 155 patients as analysed by FCM was lower than that indicated by Fosså et al. (1989) for patients with testicular cancer (91%) and the corresponding control group (97%), reflecting decreased semen quality in patients with impaired fertility.

However, sperm counts are not the only parameter determining fertility (cf. Bostofte et al., 1982). Since the evaluation of motility and morphology by LM tends to be subjective (WHO, 1987Go), other parameters of fertility need to be found.

In the present paper, eight classes with different semen quality were determined by FCM and correlated with the results of the spermiograms. About one-third of the 155 patients were normozoospermic, with other factors having apparently affected the fertility. Increasing fractions of up to 35% of cellular debris of possibly apoptotic origin did not affect fertility in normo- and oligozoospermic men (classes 1–3). One unexpected feature, however, was that only two of the 47 men with >5% diploid spermatozoa fathered children within 10 years (class 4). Although these patients had high mean sperm concentrations and high percentages of normal haploid spermatozoa, the occurrence of a high frequency of diploid spermatozoa probably reflects not only faulty meiotic segregation involving the synaptonemal complex, but also major disturbances of spermatogenesis (Weissenberg et al., 1998Go). In certain patients, an abnormally high frequency of diploid spermatozoa seems to be correlated with repeated miscarriages (de Geyter et al., 1997Go), possibly caused by sperm polyploidy. Polyploidy, mainly triploidy, is found in 20% of human spontaneous abortions (Tolksdorf, 1979Go). In cases with repeated abortions, sorting of diploid spermatozoa may therefore be useful.

It was also striking that there were no paternities among the 18 class 5 patients with malcondensed sperm during the 10 year follow-up: malcondensation of sperm chromatin is considered to be correlated with infertility not necessarily reflected by poor sperm morphology (Evenson and Melamed, 1983Go; Evenson et al., 1991Go; Hofmann and Hilscher, 1991Go; Golan et al., 1997Go; Spanò et al, 1998Go). The detection of disturbances in murine sperm chromatin condensation after very low-dose X-rays (Sailer et al., 1995Go) suggests that screening for genetic damage could be useful in the diagnosis and characterization of infertility. Another reason for the skewing of the sperm histogram, besides malcondensation of sperm chromatin, might be apoptosis (as suggested by Dr Z.Darzynkiewicz, personal communication).

Within class 6, the presence of immature germ cells or inflammatory cells did not affect fertility within the 10 year observation period. It was no surprise that the 16 patients with very low sperm concentration of zero or close to zero (class 7) and the 10 men with cellular fragments prevailing in the ejaculates (class 8) were infertile.

As suggested by these data, DNA FCM might be helpful in future studies of human infertility, allowing the clinician to assess rapidly and objectively the sperm count, the state of chromatin condensation and the presence of immature germ cells, of inflammatory cells and of diploid spermatozoa or of aneuploid tumour cells in the ejaculate (cf. Otto et al., 1979b; Clausen and Åabyholm, 1980; Evenson et al., 1980; Åabyholm and Clausen, 1981; Steen and Hanson, 1981; Evenson and Melamed, 1983; Fosså et al., 1989; Evenson et al., 1991; Seligmann et al., 1994; Golan et al., 1997; Weissenberg et al., 1998). Changes induced intentionally (e.g. male contraception) or accidentally during treatments (e.g. therapies employing radiation, hormones or cytostatic agents and affecting spermatogenesis) can be readily monitored and documented. Environmental or occupational toxin exposure might be suggested by identifying suspected decreases in the quality of semen in epidemiological analyses (cf. Spanò et al., 1983, 1998).


    Acknowledgments
 
The authors cordially thank Ms G.Bellmann, Institute of Radiation Biology, University of Münster, for excellent technical help, Dr D.Neugebauer, Working Group Cellular Excitation Physiology, University of Bochum, for helpful suggestions, and Dr D.S.Joshi, Molecular Biology and Agriculture Division, Bhabda Research Center, Bombay, India, and Dr M.H.Brinkworth, Institute of Reproductive Medicine, University of Münster, for language editing.


    Notes
 
5 To whom correspondence should be addressed at: Klinik und Poliklinik für Strahlentherapie-Radioonkologie, Albert-Schweitzer-Str. 33, D-48149 Münster, Germany Back


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Åabyholm, T. and Clausen, O.P.F. (1981) Clinical evaluation of DNA flow cytometry of fine needle aspirates from the testes of infertile men. Int. J. Androl., 4, 505–514.[ISI][Medline]

Ashwood-Smith, M.J. (1994) Human sperm sex selection. Safety of human sperm selection by flow cytometry. Hum. Reprod., 9, 757.[ISI][Medline]

Auger, J., Kunstmann, J.M., Czyglik, F. et al. (1995) Decline in semen quality among fertile men in Paris during the past 20 years. N. Engl. J. Med., 332, 281–285.[Abstract/Free Full Text]

Behre, H.M., Yeung, C.H. and Nieschlag, E. (1997) Diagnosis of male infertility and hypogonadism. In Nieschlag, E. and Behre, H.M. (eds), Andrology: Male Reproductive Health and Dysfunction. Springer, Berlin, p. 104.

Bland, J.M. and Altman, D.G. (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet, i, 307–310.

Bostofte, E., Serup, J. and Rebbe, H. (1982) Relation between sperm count and semen volume, and pregnancies obtained during a twenty-year follow-up period. Int. J. Androl., 5, 267–275.[ISI][Medline]

Bromwich, P., Cohen, J., Stewart, I. et al. (1994) Decline in sperm counts: an artefact of changed reference range of `normal'? Br. Med. J., 309, 19–22.[Abstract/Free Full Text]

Carlsen, E., Gilwercman, A., Keiding, N. et al. (1992) Evidence for decreasing quality of semen during past 50 years. Br. Med. J., 305, 609–613.[ISI][Medline]

Chan, S.Y.W. Wang, C., Song, B.L. et al. (1989) Computer-assisted image analysis of semen concentration in human semen before and after swim-up separation: comparison with assessment by haemocytometer. Int. J. Androl., 12, 339–345.[ISI][Medline]

Clausen, O.P.F. and Åabyholm, T. (1980) Deoxyribonucleic acid flow cytometry of germ cells in the investigation of male infertility. Fertil. Steril., 34, 369–374.[ISI][Medline]

Darzynkiewicz, Z., Bruno, S., Del Bino, G. et al. (1992) Features of apoptotic cells measured by flow cytometry. Cytometry, 13, 795–808.[ISI][Medline]

Dean, P.N., Pinkel, D. and Mendelsohn, M.L. (1978) Hydrodynamic orientation of sperm heads for flow cytometry. Biophys J., 23, 7–13.[Abstract]

de Geyter, Ch., De Geyter, M., Castel, A.M. et al. (1997) Assisted fertility. In Nieschlag, E. and Behre, H. M. (eds), Andrology – Male Reproductive Health and Dysfunction. Springer, Berlin, pp. 323–346.

Evenson, D.P. and Melamed, M.R. (1983) Rapid analysis of normal and abnormal cell types in human semen and testis biopsies by flow cytometry. J. Histochem. Cytochem., 31, 248–253.[ISI][Medline]

Evenson, D.P., Darzynkiewicz, Z. and Melamed, M.R. (1980) Relation of mammalian sperm chromatin heterogeneity to fertility. Science, 210, 1131–1133.[ISI][Medline]

Evenson, D.P., Jost, L.K., Baer et al. (1991) Individuality of DNA denaturation patterns in human sperm as measured by the sperm chromatin structure assay. Reprod. Toxicol., 5, 115–125.[ISI][Medline]

Fosså, S.D., Melvik, J.E., Juul, N.O. et al. (1989) DNA flow cytometry in sperm cells from unilaterally orchiectomized patients with testicular cancer before further treatment. Cytometry, 10, 345–350.[ISI][Medline]

Golan, R., Shochat, L., Weissenberg, R. et al. (1997) Evaluation of chromatin condensation in human spermatozoa: a flow cytometric assay using acridine orange staining. Mol. Hum. Reprod., 3, 47–54.[Abstract]

Hacker-Klom, U., Heiden, T., Otto, F.J. et al. (1989) Radiation-induced diploid spermatids in mice. Int. J. Radiat. Biol., 55, 797–806.[ISI][Medline]

Harrison, R.A. (1997) Sperm plasma membrane characteristics and boar semen fertility. J. Reprod. Fertil., 52, 195–211.

Hartmann, W., Hettwer, H., Hofmann, N. et al. (1982) Die Pepsinvorbehandlung menschlichen Spermas als Standardmethode in der impulscytophotometrischen Analyse. Andrologia, 14, 135–142.[ISI][Medline]

Hofmann, N. and Hilscher, B. (1991) Use of aniline blue to assess chromatin condensation in morphologically normal spermatozoa in normal and infertile men. Hum. Reprod., 6, 979–982.[Abstract]

Irvine, S., Cawood, E., Richardson, D. et al. (1996) Evidence of deteriorating semen quality in the United Kingdom: birth cohort study in 577 men in Scotland over 11 years. Br. Med. J., 312, 467–471.[Abstract/Free Full Text]

Johnson, L.A., Welch, G.R., Keyvanfar, K. et al. (1993) Gender preselection in humans? Flow cytometric separation for the prevention of X-linked diseases. Hum. Reprod., 8, 1333–1339.

Knuth, U.A., Yeung, C.H. and Nieschlag, E. (1997) Computerized semen analysis: objective measurement of semen characteristics is biased by subjective parameter setting. Fertil. Steril., 48, 118–124.

Lerchl, A. and Nieschlag, E. (1996) Decreasing sperm counts? A critical review. Exp. Clin. Endocrinol. Diab., 104, 301–307.[ISI][Medline]

Levinson, G., Keyvanfar, K., Wu, J.C. et al. (1995) DNA-based X-enriched sperm separation as an adjunct to preimplantation genetic testing for the prevention of X-linked disease. Hum. Reprod., 54, 474–482.

MacLeod, J. and Heim, L.M. (1945) Characteristics and variations in semen specimens in 100 normal men. J. Urol., 54, 474–482.[ISI]

Neuwinger, J., Behre, H.M. and Nieschlag, E. (1990) External quality control in the andrology laboratory: an experimental multicenter trial. Fertil. Steril., 54, 308–314.[ISI][Medline]

Otto, F.J., Hacker, U., Zante, J. et al. (1979a) Flow cytometry of human spermatozoa. Histochemistry, 61, 249–254.[ISI][Medline]

Otto, F.J., Hofmann, N., Hettwer, H. et al. (1979b) Die Analyse von Spermaproben mit Hilfe impulszytophotometrischer DNS-Bestimmungen. Andrologia, 11, 279–286.[ISI][Medline]

Sailer, B. L., Jost, L. K., Erickson, M. et al. (1995) Effects of X-irradiation on mouse testicular cells and sperm chromatin structure. Environ. Mol. Mutagen, 25, 23–30.[ISI][Medline]

Seligman, J., Kopsower, N.S., Weissenberg, R. et al. (1994) Thiol-disulfide status of human sperm proteins. J. Reprod. Fertil., 101, 435–443.[Abstract]

Sharpe, R.M. and Skakkebæk, N.E. (1993) Are oestrogens involved in falling sperm counts and disorders of the male reproductive tract? Lancet, 341, 1392–1395.[ISI][Medline]

Spanò, M., Calugi, A., Capuano, V. et al. (1983) Flow cytometry and sizing for routine andrological analysis. Andrologia, 16, 367–375.[ISI]

Spanò, M., Kolstad, A.H., Larsen, S.B. et al. (1998) The applicability of the flow cytometric sperm chromatin structure assay in epidemiological studies. Hum. Reprod., 9, 2495–2505.

Steen, H.B. and Hanson, U. (1981) Sperm maturation determination by flow cytometry. Cytometry, 2, 129.

Tolksdorf, M. (1979) Chromosomale Ursachen des Spontanabortes. In Schirren, C., Mettler, L. and Semm, K. (eds), Fortschritte der Fertilitätsforschung FDF 8. Grosse-Verlag, Berlin, pp. 41–46.

Van Dilla, M.A., Gledhill, B.L., Lake, S. et al. (1977) Measurement of mammalian sperm deoxyribonucleic acid by flow cytometry. Problems and approaches. J. Histochem. Cytochem., 25, 763–773.[Abstract]

Weissenberg, R., Aviram, A., Lewin, L.M. et al. (1998) Concurrent use of flow cytometry and fluorescence in-situ hybridization techniques for detecting faulty meiosis in a human sperm sample. Mol. Hum. Reprod., 4, 61–66.[Abstract]

WHO (1987) Laboratory Manual for the Examination of Human Semen and Semen–Cervical Mucus Interaction, 2nd edn. Cambridge University Press, Cambridge.

Zante, J., Schumann, J., Göhde, W. et al. (1977) DNA-fluorometry of mammalian sperm. Histochemistry, 54, 1–7.[ISI][Medline]

Submitted on January 13, 1999; accepted on June 9, 1999.