Morphometric Subpopulations Research Articles

Label-Free High Dimensional Single Cell Morphological Profiling of Different Hematological Malignancies By Ghost Cytometry

Characterizing the heterogeneity in human leukemias is critical for understanding mechanisms of disease onset, uncovering biomarkers for disease diagnosis, and guiding research into novel treatment approaches. While extensive research focus has been placed on characterizing the molecular heterogeneity in leukemia by modern 'omics technologies, comparatively less emphasis has been placed on studying the diversity in holistic morphological changes that occur in single cells in the context of disease. Here, we report on a novel approach to understanding and characterizing different hematological malignancies using ghost cytometry, a recently developed high-content flow cytometric method that leverages high-speed, artificial intelligence (AI) driven morphological characterization and analysis of single cells. We performed morphometric profiling on human bone marrow samples from patients with T and B-cell acute lymphoblastic leukemia (ALL, n=5), acute myeloid leukemia (AML, n=5), multiple myeloma (MM, n=5) and healthy bone marrow mononuclear cell (BM-MNC) controls (n=6) (Figure 1). Morphological profiles from individual cells were analyzed by unsupervised machine learning (universal manifold approximation and projection, UMAP) and compared within disease subsets and against controls. We identified disease-specific cell populations from a mixture of healthy control and disease samples without any labeling, based on completely label-free information (Figure 2). For validation of the specific cell subsets, we overlaid known cell surface markers (e.g. CD45 for blast cells, CD10/CD19 for B-ALL, CD33/CD34 for AML, CD38/CD138 for MM). The intensity of CD45 was dimmer and disease-specific markers were highly expressed in the disease-specific cell population. We also identified unique cell populations across blood cell populations that were distinct from the healthy BM-MNC controls. We also analyzed three human myeloma cell lines (AMO1, KMS, and L363) for comparison to the primary MM samples. In the UMAP analysis using LF-GC data, in all three types of cell lines, Bortezomib-resistant cell lines exhibited different distributions from the control parental cell lines. In addition, we observed distinct morphological profiles between primary myeloma samples and myeloma cell lines. Here we present a novel cell characterization approach for human hematological diseases that leverages AI-based, label-free, high-speed morphological characterization of single cells. We demonstrate that the approach can be used to identify subtle morphological differences in blast cells from a range of blood cancer subtypes. Application of morphological profiling and AI can be used to identify measurable, disease-related changes in these diseases that have diagnostic, drug screening, and therapeutic monitoring potential. Keywords: flow cytometry, acute leukemia, multiple myeloma, label-free cell analysis, biomarker, liquid biopsy, ghost cytometry, artificial intelligence, machine learning Figure 1. Research design overview. Bone marrow samples from patients and non-diseased controls will be analyzed by Ghost Cytometry to assess disease by conventional markers and identify novel morphometric subpopulations. Morphological information is acquired as label-free GMI signals without any labeling. The label-free GMI information is transformed into two-dimensional space by UMAP dimensionality reduction method to identify subpopulations of interest. Both samples are stained with known cell surface markers for validation of unsupervised classification. Figure 2. Identification of disease-specific cell subpopulations by unsupervised approach. Using an unsupervised machine learning technique called UMAP, label-free morphologically distinct cellular subpopulations can be identified in B-ALL, AML, MM when compared to healthy donor controls (left panels, inside the dotted circles). For validation of the subpopulations, known cell surface markers (CD45 for blast cells, CD10/CD19 for B-ALL, CD33/CD34 for AML, CD38/CD138 for MM) and cell trace marker (CellTracker) were overlaid. The intensity increases monotonically through the colormaps. The intensity of CD45 was dimmer and disease-specific markers were highly expressed in the disease-specific cell population.

Feline sperm head morphometry in relation to male pedigree and fertility

Computer-assisted sperm morphometry analysis is an advanced tool which allows to precise measure sperm head parameters like length, width, area, and perimeter. On the basis of these and calculated parameters, morphometric subpopulations of spermatozoa can be distinguished. In many species, the distribution of subpopulation within the ejaculate is related to male fertility. There is no information about such a relation for domestic cats; therefore, the aim of this study was to evaluate whether spermatozoa from non-pedigree and purebred domestic cats differ in morphometric parameters. The second aim was to check if there is a relationship between sperm morphometry and fertility. Urethral semen was collected from 27 tomcats, divided into three study groups: non-pedigree cats of unknown fertility, purebred infertile cats and purebred fertile cats. The morphometric assessment was performed by CASMA, followed by principal component analysis and clustering. The results revealed huge intra- and inter-individual variation in sperm head morphometric parameters and three sperm-head morphometric subpopulations were identified in feline semen. Neither mean values of morphometric parameters nor the distribution of spermatozoa between morphometric subpopulations differ between non-pedigree cats of unknown fertility and purebred infertile and fertile cats. We hypothesize that other factors, especially abnormalities of the midpiece and tail, and overall worse quality of the semen of infertile males could have masked the effect of subtle changes in the sperm head morphometry.

Predictive Capacity of Boar Sperm Morphometry and Morphometric Sub-Populations on Reproductive Success after Artificial Insemination.

Simple SummaryThe efficiency of swine production measured as litter size influences the profitability of the pig industry. Furthermore, sow fertility potential depends in part on the boar semen quality and reproductive efficiency. The objective of this study is to compare boar sperm head size and morphometric features of shape to evaluate their relationships with reproductive success after artificial insemination (AI). A morphometric analysis of boar ejaculate reveals morphometrically separate sub-populations. The differences between sub-populations are displayed for sperm head size. In addition, sperm clustering into sub-populations did not have a predictive capacity on litter size variables. Nevertheless, the morphometric variables of the sperm may have a predictive, albeit reduced, capacity regarding litter size variables. The results of this study therefore open up possibilities for future assessments of fertility. The aim of the study was to compare the morphometric features of sperm head size and shape from the Pietrain line and the Duroc × Pietrain boar crossbred terminal lines, and to evaluate their relationship with reproductive success after artificial insemination of sows produced from crossbreeding the York, Landrace and Pietrain breeds. Semen samples were collected from 11 sexually mature boars. Only ejaculates with greater than 70% motility rate and <15% of abnormal sperm were used for artificial inseminations (AI) and included in the study. Samples were analyzed using an ISAS®v1 computer-assisted sperm analysis system for eight morphometric parameters of head shape and size (CASA-Morph). Sub-populations of morphometric ejaculates were characterized using multivariate procedures, such as principal component (PC) analysis and clustering methods (k-means model). Four different ejaculate sub-populations were identified from two PCs that involved the head shape and size of the spermatozoa. The discriminant ability of the different morphometric sperm variables to predict sow litter size was analyzed using a receiver operating characteristics (ROC) curve analysis. Sperm head length, ellipticity, elongation, and regularity showed significant predictive capacity on litter size (0.59, 0.59, 0.60, and 0.56 area under curve (AUC), respectively). The morphometric sperm sub-populations were not related to sow litter size.

Sperm kinematics and morphometric subpopulations analysis with CASA systems: a review

Sperm kinematics and morphometric subpopulations analysis with CASA systems: a review. The subjective evaluation of seminal quality has given way to the use of objective assessment techniques by CASA technology (computer-assisted semen analysis). The application of principal components (PC) and clustering methods to reveal subpopulations of spermatozoa is a powerful tool to evaluate raw semen and processed cell suspensions, but not many researchers are aware of the technique. PC analysis is a multivariate statistical method that reduces the number of variables used in subsequent calculations used to describe the data. By integrating the original variables according to their coherence in a database into a new complex mathematical variable, clearly defined homogenous subpopulations of spermatozoa can be defined. Kinematic, morphometric, morphological or DNA integrity tests may apply to characterize it and understand the reproductive biology of the spermatozoon. In recent years there has been a substantive change in the conceptual paradigm regarding what an ejaculate is. It should be said that until recently it was considered that the representative population (billions) of sperm was made up of "equivalent" cells with a common goal: to be the one that could finally fertilize the oocyte. The verification that the set of spermatozoa is grouped in distinct subpopulations, according to their kinematic and morphometric characteristics, opens the way towards a more cooperative vision. Besides, we have seen that the subpopulation distribution is different among males, which seems to indicate different strategies that can be understood within another paradigm, that of sperm competition between different ejaculates. The existence of heterogeneous subpopulations of spermatozoa in the ejaculate that show kinematics and morphometric patterns is widely known but the biological meaning of these different sperm subpopulations is still not clear. Although the role of the different subpopulations remains unknown, the work should continue in that direction.

Sistemas de análisis computadorizado de semen en la reproducción animal

Computer-assisted semen analysis (CASA) is used in animal reproduction with the objective of evaluating spermquality, quickly and reliably. Currently, artificial insemination centers must have reliable and objective systems thatensure the reliability of reproductive data. The aim of this paper was to review computer-assisted semen analysisin livestock species. The use of CASA systems replace routine quality analyzes that introduce biases and leads to different inaccuracy degrees. In addition, if intrinsic limitations of microscopy or sperm with different motilitypatterns are considered, it is most likely that considerable variability will be introduced which will have an impact on the objectivity of the estimation. At first, this type of technology was inaccessible, but they are currently used routinelyin most research laboratories for the evaluation of sperm samples of different species of zootechnical interest..Computerized techniques are able to issue reports with a high number of characteristics, to minimize the subjectivefactor of routine semen analysis, and to ensure a better correlation with the fertilizing capacity of spermatozoa by the relationship between sperm motility and functional competence. The use of CASA systems together with multivariatestatistical analysis have demonstrated the existence of kinetic and morphometric subpopulations in ejaculates ofdifferent species, eliminating the idea that ejaculates are homogeneous, formed by a single sperm population with normal distribution.

Identification of sperm morphometric subpopulations in cooled-stored canine sperm and its relation with sperm DNA integrity.

The aims of this study were to (i) identify different morphometric subpopulations in cooled-stored canine sperm and their patterns of distribution during cool-storage for up to 240hr and (ii) determine whether or not morphometric sperm subpopulations (sP) are related to sperm DNA integrity. For that purpose, morphometric parameters were analysed by computer-assisted sperm analysis (CASA) and sperm DNA fragmentation (sDFi) using the sperm Halomax test. Four morphometric sperm heads subpopulations were identified: sP1 (large and rounded), sP2 (large and elongated), sP3 (small and rounded) and sP4 (small and elongated). sP1 was the most predominant subpopulation for up to 72hr and thereafter sP3 increased progressively. sDFi increased after 48hr of cool-storage. Although sP3 showed a positive correlation with sDFi, and both increased over time, it could not be ensured that only the sperm with fragmented DNA are accumulated in sP3. In conclusion, sP3 and DNA fragmentation increased progressively during cool-storage, becoming possible indicators of sperm damage. However, it cannot be concluded that sP3 only contains sperm with fragmented DNA.

Sperm kinematic, head morphometric and kinetic-morphometric subpopulations in the blue fox (Alopex lagopus).

This work provides information on the blue fox ejaculated sperm quality needed for seminal dose calculations. Twenty semen samples, obtained by masturbation, were analyzed for kinematic and morphometric parameters by using CASA-Mot and CASA-Morph system and principal component (PC) analysis. For motility, eight kinematic parameters were evaluated, which were reduced to PC1, related to linear variables, and PC2, related to oscillatory movement. The whole population was divided into three independent subpopulations: SP1, fast cells with linear movement; SP2, slow cells and nonoscillatory motility; and SP3, medium speed cells and oscillatory movement. In almost all cases, the subpopulation distribution by animal was significantly different. Head morphology analysis generated four size and four shape parameters, which were reduced to PC1, related to size, and PC2, related to shape of the cells. Three morphometric subpopulations existed: SP1: large oval cells; SP2: medium size elongated cells; and SP3: small and short cells. The subpopulation distribution differed between animals. Combining the kinematic and morphometric datasets produced PC1, related to morphometric parameters, and PC2, related to kinematics, which generated four sperm subpopulations – SP1: high oscillatory motility, large and short heads; SP2: medium velocity with small and short heads; SP3: slow motion small and elongated cells; and SP4: high linear speed and large elongated cells. Subpopulation distribution was different in all animals. The establishment of sperm subpopulations from kinematic, morphometric, and combined variables not only improves the well-defined fox semen characteristics and offers a good conceptual basis for fertility and sperm preservation techniques in this species, but also opens the door to use this approach in other species, included humans.

Morphometric and kinematic sperm subpopulations in split ejaculates of normozoospermic men.

This study was designed to analyze the sperm kinematic and morphometric subpopulations in the different fractions of the ejaculate in normozoospermic men. Ejaculates from eight normozoospermic men were collected by masturbation in three fractions after 3–5 days of sexual abstinence. Analyses of sperm motility by computer-assisted sperm analysis (CASA-Mot), and of sperm morphometry by computer-assisted sperm morphometry analysis (CASA-Morph) using fluorescence were performed. Clustering and discriminant procedures were performed to identify sperm subpopulations in the kinematic and morphometric data obtained. Clustering procedures resulted in the classification of spermatozoa into three kinematic subpopulations (slow with low ALH [35.6% of all motile spermatozoa], with circular trajectories [32.0%], and rapid with high ALH [32.4%]), and three morphometric subpopulations (large-round [33.9% of all spermatozoa], elongated [32.0%], and small [34.10%]). The distribution of kinematic sperm subpopulations was different among ejaculate fractions (P < 0.001), with higher percentages of spermatozoa exhibiting slow movements with low ALH in the second and third portions, and with a more homogeneous distribution of kinematic sperm subpopulations in the first portion. The distribution of morphometric sperm subpopulations was also different among ejaculate fractions (P < 0.001), with more elongated spermatozoa in the first, and of small spermatozoa in the third, portion. It is concluded that important variations in the distribution of kinematic and morphometric sperm subpopulations exist between ejaculate fractions, with possible functional implications.

Spermiogram and sperm head morphometry assessed by multivariate cluster analysis results during adolescence (12-18 years) and the effect of varicocele.

This work evaluates sperm head morphometric characteristics in adolescents from 12 to 18 years of age, and the effect of varicocele. Volunteers between 150 and 224 months of age (mean 191, n = 87), who had reached oigarche by 12 years old, were recruited in the area of Barranquilla, Colombia. Morphometric analysis of sperm heads was performed with principal component (PC) and discriminant analysis. Combining seminal fluid and sperm parameters provided five PCs: two related to sperm morphometry, one to sperm motility, and two to seminal fluid components. Discriminant analysis on the morphometric results of varicocele and nonvaricocele groups did not provide a useful classification matrix. Of the semen-related PCs, the most explanatory (40%) was related to sperm motility. Two PCs, including sperm head elongation and size, were sufficient to evaluate sperm morphometric characteristics. Most of the morphometric variables were correlated with age, with an increase in size and decrease in the elongation of the sperm head. For head size, the entire sperm population could be divided into two morphometric subpopulations, SP1 and SP2, which did not change during adolescence. In general, for varicocele individuals, SP1 had larger and more elongated sperm heads than SP2, which had smaller and more elongated heads than in nonvaricocele men. In summary, sperm head morphometry assessed by CASA-Morph and multivariate cluster analysis provides a better comprehension of the ejaculate structure and possibly sperm function. Morphometric analysis provides much more information than data obtained from conventional semen analysis.

Differential distribution of sperm subpopulations and incidence of pleiomorphisms in ejaculates of captive howling monkeys (Alouatta caraya)

The aim of this study was to develop an objective method to determine the incidence of pleiomorphisms and its influence on the distribution of sperm morphometric subpopulations in ejaculates of howling monkeys (Alouatta caraya) by using a combination of computerized analysis system (ASMA) and principal component analysis (PCA) methods. Ejaculates were collected by electroejaculation methods on a regular basis from five individuals maintained under identical captive environmental, nutritional, and management conditions. Each sperm head was measured for dimensional parameters (Area [A, (square micrometers)], Perimeter [P, (micrometers)], Length [L, (micrometers)], and Width [W, (micrometers)]) and shape-derived parameters (Ellipticity [(L/W)], Elongation [(L - W)/(L + W)], and Rugosity [(4лA/P (2))]). PCA revealed two principal components explaining more than the 96 % of the variance. Clustering methods and discriminant analyzes were performed and seven separate subpopulations were identified. There were differences (P < 0.001) in the distribution of the seven subpopulations as well as in the incidence of abnormal pleiomorphisms (58.6 %, 49.8 %, 35.1 %, 66.4 %, and 55.1 %, P < 0.05) among the five donors tested. Our results indicated that differences among individuals related to the incidence of pleiomorphisms, and sperm subpopulational structure was not related to the captivity conditions or the sperm collection method, since all individuals were studied under identical conditions. In conclusion, the combination of ASMA and PCA is a useful clinical diagnostic resource for detecting deficiencies in sperm morphology and sperm subpopulations in A. caraya ejaculates that could be used in ex situ conservation programs of threatened species in Alouatta genus or even other endangered neotropical primate species.

A comparative study of sperm morphometric subpopulations in cattle, goat, sheep and pigs using a computer-assisted fluorescence method (CASMA-F)

This study was designed to compare the sperm nuclear morphometric subpopulations of four species of domestic artiodactyls (cattle, sheep, goat and pigs). Samples from 20 males of each species were collected. After semen collection, sperm concentration and motility were measured and samples prepared for morphometric determinations. Smears were fixed with 2% glutaraldehyde, stained with Hoechst 33342 and photographed. At least 200 spermatozoa per sample were processed using the Image J analysis open software. Clustering procedures were performed to identify sperm subpopulations using the morphometric data obtained from each species. Results of the present study show that, applying the computer-assisted sperm morphometry analyisis-fluorescence (CASMA-F) technology and multivariate cluster analyses, it was possible to determine the subpopulations of spermatozoa with different morphometric characteristics in the four species studied. Bulls and boars had two clearly differentiated size categories: large and small. However, the final sperm subpopulations were four in the bull (large-round, large-elongated, small-round, and small-elongated) and only three in the boar (large, small-elongated and small-round). In small ruminant species, three sperm nuclei size categories were established: large, average sized and small. Two of these subpopulations were also elongated in goat bucks, with three subpopulations (large-round, small-elongated and average size-elongated). In the ram three morphometric subpopulations were also obtained (large, small and average size-round), but none was elongated. When comparing among species, sperm subpopulations were smaller in the buck and less elliptical and elongated in the ram than those in the other species studied. Male variability was identified in the distribution of sperm subpopulations described in the four species studied. It was concluded that the combination of CASMA-F technology with multivariate cluster analyses allow the study of morphometric sperm subpopulations and that there are important variations in the subpopulations among the four species studied.

Identification of sperm head subpopulations with defined pleiomorphic characteristics in ejaculates of captive Goeldi's monkeys (Callimico goeldii)

The aim of this study was to evaluate the incidence of pleiomorphisms and its influence on the distribution of sperm morphometric subpopulations in ejaculates from the vulnerable Goeldi's monkey (Callimico goeldii) by using a combination of computerized analysis system and Principal Component Analysis (PCA) methods. Each sperm head was measured for four primary spermatozoal head dimensional parameters (area [A (μm2)], perimeter [P (μm)], length [L (μm)] and width [W (μm)]) and three head shape derived parameters (ellipticity [(L/W)], elongation [(L−W)/(L+W)] and rugosity [(4πA/P2)]). Six separate subpopulations (SPs) were identified: SP1, constituted by very large, narrow and very elliptical spermatozoa (A=16.85±1.56μm2, W=2.75±0.42μm and ellipticity=2.16±0.24); SP2, characterized by average sized, short, wide and round spermatozoa (A=15.00±1.92μm2, L=5.06±0.49μm, W=3.51±0.31μm and ellipticity=1.44±0.15); SP3, represented by small, wide and slightly round spermatozoa (A=14.95±1.75μm2, W=3.47±0.29μm and ellipticity=1.48±0.14); SP4 included very small, short and very round spermatozoa (A=14.15±2.38μm2, L=4.90±0.57μm and elongation=0.18±0.05); SP5 consisted of average sized and slightly elliptical spermatozoa (A=15.14±1.72μm2 and ellipticity=1.49±0.14); and SP6 included large and round spermatozoa (A=16.30±1.62μm2 and elongation=0.19±0.04). There were differences in the sperm subpopulation distribution (P<0.001) among the five donors analyzed. In conclusion, the results of the current study confirmed that the use of computer sperm analysis methods combined with PCA cluster analyses are useful methods to identify, classify, and characterize different sperm head morphometric subpopulations in neotropical primates. Broadening our knowledge of C. goeldii sperm morphometric abnormalities as well as developing reliable techniques for sperm evaluation may be essential for ex situ conservation of this threatened species.

Sperm head morphometry in ejaculates of adult marmosets (Callithrix jacchus): A model for studying sperm subpopulations and among-donor variations

In humans and other mammals, sperm morphology has been considered one of the most important predictive parameters of fertility. The objective was to determine the presence and distribution of sperm head morphometric subpopulations in a nonhuman primate model (Callithrix jacchus), using an objective computer analysis system and principal component analysis (PCA) methods to establish the relationship between the subpopulation distribution observed and among-donor variation. The PCA method revealed a stable number of principal components in all donors studied, that represented more than 85% of the cumulative variance in all cases. After cluster analysis, a variable number (from three to seven) sperm morphometric subpopulations were identified with defined sperm dimensions and shapes. There were differences in the distribution of the sperm morphometric subpopulations (P < 0.001) in all ejaculates among the four donors analyzed. In conclusion, in this study, computerized sperm analysis methods combined with PCA cluster analyses were useful to identify, classify, and characterize various head sperm morphometric subpopulations in nonhuman primates, yielding considerable biological information. In addition, because all individuals were kept in the same conditions, differences in the distribution of these subpopulations were not attributed to external or management factors. Finally, the substantial information derived from subpopulation analyses provided new and relevant biological knowledge which may have a practical use for future studies in human and nonhuman primate ejaculates, including identifying individuals more suitable for assisted reproductive technologies.

Seasonal dynamics of sperm morphometric subpopulations and its association with sperm quality parameters in ram ejaculates

Sperm morphologic assessment is considered an irreplaceable part of standard laboratory routine analyses in the diagnosis of male fertility. Thus, in an attempt to quantify the effects of season on sperm morphology and its functional significance in relation to sperm quality parameters, sperm head morphometric traits were analyzed by using an objective computerized analysis combined with principal components analysis (PCA) cluster analysis to establish the relationship between the distribution of the subpopulations found and sperm quality in each season. There were slight variations on sperm motility and sperm membrane integrity indexes (P > 0.05). However, the mean values for sperm concentration substantially changed among seasons in all individuals studied (P < 0.01). There were significant differences in sperm morphometric parameters (P < 0.01) as well as in the distribution of morphometric subpopulations between seasons (P < 0.001). In conclusion, this study confirmed that there was an important seasonal effect on sperm morphometric traits. In addition, the distribution of these subpopulations seems to be related to the season studied and the ejaculate quality which would be a very important indicator of sperm function. The substantial information derived from these morphometric subpopulations has provided new knowledge which can be used in future studies using sperm morphometry as a seasonal indicator in ram ejaculates.

Morphometrically-distinct sperm subpopulations defined by a multistep statistical procedure in Ram ejaculates: intra- and interindividual variation

The existence of sperm subpopulations within the mammalian ejaculate has now been widely recognized. However, to the best of our knowledge, no data exist regarding the existence of sperm morphometric subpopulations within the ovine ejaculate. Computer assisted sperm morphometry analysis (ASMA) data and clustering methods were used in this study to identify sperm-head subpopulations in ram semen. Two experiments were carried out. In Experiment 1, ejaculates from 226 mature rams of the Manchega breed belonging to 36 different herds were used. A minimum of 100 sperm heads were analyzed from each male and eight morphometric characteristics for each individual sperm were recorded. Subpopulation analysis was performed in sequential steps: variable group analysis and correlation analysis to select which morphometric characteristics to use in cluster analyses; nonhierarchical clustering analysis using sperm head length and p2a (also known as roundness) shape factor as initial classificatory variables; and hierarchical clustering analysis to obtain the final number of clusters. The clustering analyses, based on 26 306 individual cells, revealed the existence of four sperm subpopulations (SP1, SP2, SP3 and SP4) with different morphometric characteristics. Significant differences in the proportion of spermatozoa in the SP1 and SP3 were found between rams belonging to different herds. In Experiment 2, the intra- and intermale variability on the distribution of sperm subpopulations was assessed. Three ejaculates from each of 21 rams were collected and the same multistep clustering analysis was performed. For all subpopulations defined, the intermale variability resulted in high values, being the intramale variability much lower. This fact would allow the use of sperm head morphometry to characterize a male and might provide valuable information to asses its fertility. In conclusion, our results show that using computer assisted sperm morphometry analysis and multivariate cluster analyses, four sperm subpopulations with different head phenotype were identified in ram ejaculates.

Sperm morphometric subpopulations are differentially distributed in rams with different maturity age in cryopreserved ejaculates

It is widely accepted that sperm morphology is a good indicator of fertility and it has been proposed that sperm quality may be related to subtle changes in sperm head morphology. However, a precise estimation of the morphology of ram sperm would be very useful to improve reproductive success in ovine. Computer-assisted morphometric analysis and clustering analysis have been important tools to study sperm subpopulations in domestic animals. However, to the best of our knowledge, no data exist studing morphometric differences regarding to sperm subpopulations within the ovine ejaculate. The aim of this study was to test the presence and distribution of sperm morphometric subpopulations in cryopreserved ejaculates from yearling and mature rams using an objective method by computer analysis system and to establish the relationship between the distribution of the subpopulations found and sperm quality in each individual ram. Principal component analysis revealed that three principal components for yearlings and four components for mature rams that represented more than 84% of the cumulative variance in both cases. After cluster analysis, three sperm morphometric subpopulations for yearlings (CLY) and four for mature (CLM) rams were identified with defined sperm dimensions and shapes. CLY1 included big, round and short sperm (37%), CLY2 included average size and slightly elliptical and elongated sperm (48%), CLY3 included small, long, elliptical and elongated sperm cells (15%). CLM1 consisted of average size and moderate elliptical and elongated (26%), CLM2 consisted of small, long, elliptical and elongated (31%), CLM3 consisted of small and round (32%) and CLM4 included big, short and round (8%) spermatozoa respectively. There were significant differences in the distribution of the three subpopulations (P < 0.001) as well as in the sperm concentration, total motility (%), sperm viability (%) and the overall (P < 0.05) in the ejaculates among the four yearling rams tested. Same results were found for the four subpopulations and the different sperm quality parameters in the ejaculates among the four mature rams tested. In conclusion, cryopreserved ram semen showed a specific structure with regard to sperm morphometric subpopulations. In addition, the distribution of these subpopulations seems to be related to stud maturity age and the ejaculate quality which would be a very important indicator of sperm function. Thus, analysis of sperm morphometric subpopulation structure together with functional tests could provide valuable information to assess the cryoresistence of ram spermatozoa.

Identification of Sperm‐Head Morphometric Subpopulations in Iberian Red Deer Epididymal Sperm Samples

Computer-assisted sperm morphometry analysis (CASMA) was used in this study to identify sperm morphometric subpopulations in Iberian red deer epididymal sperm samples. Epididymal sperm samples were collected from 37 mature stags and were divided. One portion was diluted in a Tris-citrate-egg yolk medium. A microscope slide was prepared from single extended sperm samples prior to freezing. The remainder of each sample was frozen in nitrogen vapours using a conventional protocol. After thawing, sperm smears were prepared as described for extended samples. All slides were air-dried and stained with Hemacolor. The sperm-head dimensions for a minimum of 145 sperm-heads were analyzed from each sample by means of the Sperm-Class Analyser, and the mean measurements recorded. Each sperm-head was measured for four primary sperm-head parameters, and five parameters of head shape. All sperm morphometric parameters evaluated were placed in a statistical database and a multivariate cluster analysis was performed. The clustering analyses, based on 10 867 individual spermatozoa, revealed the existence of three subpopulations (SP(1), SP(2), SP(3)) of spermatozoa with different morphometric characteristics (p < 0.001). The proportion of spermatozoa present in any of the three subpopulations remained constant (p > 0.05) through the cryopreservation process. Pre-freeze and post-thaw sperm quality was in vitro evaluated by microscopic assessments of individual sperm motility and of plasma membrane and acrosome integrities. In conclusion, our results show that applying the CASMA techniques and multivariate cluster analyses, it was possible to determine that three subtle subpopulations of spermatozoa with different morphometric characteristics coexist in red deer semen.

Identification of sperm morphometric subpopulations in the canine ejaculate: do they reflect different subpopulations in sperm chromatin integrity?

A statistical approach using sequentially principal component analysis (PCA) clustering and discriminant analysis was developed to disclose morphometric sperm subpopulations. In addition, we used a similar approach to disclose subpopulations of spermatozoa with different degrees of DNA fragmentation. It is widely accepted that sperm morphology is a strong indicator of semen quality and since the sperm head mainly comprises the sperm DNA, it has been proposed that subtle changes in sperm head morphology may be related to abnormal DNA content. Semen from four mongrel dogs (five replicates per dog) were used to investigate DNA quality by means of the sperm chromatin structure assay (SCSA), and for computerized sperm morphometry (ASMA). Each sperm head was measured for nine primary parameters: head area (A), head perimeter (P), head length (L), head width (W), acrosome area (%), midpiece width (w), midpiece area (a), distance (d) between the major axes of the head and midpiece, angle (theta) of divergence of the midpiece from the head axis; and four parameters of head shape: FUN1 (L/W), FUN2 (4pi A/P2), FUN3 ((L - W)/(L + W)) and FUN 4 (pi LW/4A). The data matrix consisted of 2361 observations, (morphometric analysis on individual spermatozoa) and 63,815 observations for the DNA integrity. The PCA analysis revealed five variables with Eigen values over 1, representing more than 79% of the cumulative variance. The morphometric data revealed five sperm subpopulations, while the DNA data gave six subpopulations of spermatozoa with different DNA integrity. Significant differences were found in the percentage of spermatozoa falling in each cluster among dogs (p < 0.05). Linear regression models including sperm head shape factors 2, 3 and 4 predicted the amount of denatured DNA within each individual spermatozoon (p < 0.001). We conclude that the ASMA analysis can be considered a powerful tool to improve the spermiogram.

OC3 Morphometry Characterisation of Catalan Donkey Spermatozoa and Identification of Sperm Morphometric Subpopulations

This study determined morphometric patterns of Catalan donkey spermatozoa. For this purpose, 32 ejaculates were collected from seven Catalan donkeys. Semen smears were stained with Harris’ Hematoxilin stain and analyzed with an ASMA system. VARCLUS and FASTCLUS procedures were applied to determine the most significant morphology parameters and the morphologic subpopulations respectively. Mean values of head morphometry were: length (LH) 5.45 ± 0.53 μm, width (WH) 2.68 ± 0.21 μm, area (AH) 11.56 ± 1.32 μm2, percentage of reacted acrosomes 45.2 ± 6.95%, FUN1 (LH/AH) 2.0 ± 0.21, FUN3 (4piS/PH2) 0.3 ± 0.04. Mean values of midpiece were: width (WMP) 1.2 ± 1.08 μm, area (AMP) 3.2 ± 0.99 μm2, angle between head and midpiece (AHMP) 8.8 ± 17.46 degrees. Four different sperm morphometric subpopulations were identified. Subpopulation 1 (2.18% of spermatozoa) showed a WMP of 2.66 μm, an AMP of 39.96 μm2. Subpopulation 2 (72.78% of spermatozoa) showed a WMP of 1.00 μm, an AMP of 4.01 μm2. Subpopulation 3 (24.24% of spermatozoa) showed a WMP of 1.36 μm, an AMP of 14.11 μm2. Finally, subpopulation 4 (0.94% of spermatozoa) showed a WMP of 7.70 μm, an AMP of 171.53 μm2. It is noteworthy that four morphologic subpopulations were identified suggesting a possible relationship between these and the four motility subpopulations previously described (Miró et al. 2005, Theriogenology 63: 706–1716).

Identification of Sperm Morphometric Subpopulations in Two Different Portions of the Boar Ejaculate and Its Relation to Postthaw Quality

A statistical approach using sequentially principal component analysis (PCA), clustering, and discriminant analyses was developed to identify sperm morphometric subpopulations in well-defined portions of the fresh boar ejaculate. Semen was obtained as 2 portions (the first 10 mL of the sperm-rich fraction and the rest of the ejaculate, respectively) and frozen using a conventional protocol. Before freezing, an aliquot was used for computer-assisted sperm morphometry analysis (ASMA). Postthaw quality was evaluated using computer-assisted sperm analysis (CASA), and an annexin-V/PI assay evaluated sperm membranes. The PCA revealed that 3 variables represented more than 78% of the cumulative variance in sperm subpopulations. The clustering and discriminant analyses, based on 5780 individual spermatozoa, revealed the existence of 4 sperm subpopulations. The relative percentage of these subpopulations varied between boar and ejaculate portions. Linear regression models based on measured morphometric characteristics could account for up to 36% of the percentage of intact sperm membranes postthaw. The ASMA protocol used in our study was useful to detect subtle morphometric differences between spermatozoa, and the combination of this analysis with a multivariate statistical procedure gave new information on the biological characteristics of boar ejaculates that is not given by conventional sperm analysis.