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Fish sperm subpopulations: Changes after cryopreservation process and relationship with fertilization success in tambaqui (Colossoma macropomum)
Accepted Manuscript Fish sperm subpopulations: changes after cryopreservation process and relationship with fertilization success in tambaqui (Colossoma macropomum) V. Gallego, S.S. Cavalcante, R.Y. Fujimoto, P.C.F. Carneiro, H.C. Azevedo, A.N. Maria PII:
S0093-691X(16)30353-3
DOI:
10.1016/j.theriogenology.2016.08.001
Reference:
THE 13769
To appear in:
Theriogenology
Received Date: 19 April 2016 Revised Date:
1 August 2016
Accepted Date: 2 August 2016
Please cite this article as: Gallego V, Cavalcante SS, Fujimoto RY, Carneiro PCF, Azevedo HC, Maria AN, Fish sperm subpopulations: changes after cryopreservation process and relationship with fertilization success in tambaqui (Colossoma macropomum), Theriogenology (2016), doi: 10.1016/ j.theriogenology.2016.08.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
CLEAN COPY ACCEPTED MANUSCRIPT 1
Fish sperm subpopulations: changes after cryopreservation process
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and relationship with fertilization success in tambaqui (Colossoma
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macropomum)
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V. Gallegoa,b
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S. S. Cavalcantec
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R.Y.Fujimotob
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P.C.F Carneirob
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H. C. Azevedob A.N. Mariab,*
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a
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Universitat Politècnica de València. Camino de Vera s/n. 46022, Valencia, Spain.
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b
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Av. Beira Mar, nº 3250, bairro Jardins, 49025-040, Aracaju-SE, Brazil
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c
Programa de Pós-graduação em Zootecnia, Universidade Federal de Sergipe
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*
Corresponding author:
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Alexandre Nizio Maria
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Laboratório de Biotecnologia da Reprodução Animal (LABRA)
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Embrapa Tabuleiros Costeiros
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Av. Beira Mar, Aracaju-SE, Brasil.
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Tel: 55-79-4009-1360.
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e-mail: [email protected]
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Grupo de Acuicultura y Biodiversidad. Instituto de Ciencia y Tecnología Animal.
Animal Reproduction and Biotechnology Laboratory - Embrapa Tabuleiros Costeiros.
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Abstract
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Fish tambaqui (Colossoma macropomum) is the native Brazilian fish with the highest
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agricultural production under intensive aquaculture in South America. However, the
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decreased in the genetic variability in fish farms has become necessary the improvement
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of cryopreservation process through new statistical studies of spermatozoa (like
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subpopulation studies).
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The evaluation of the kinetic data obtained with a CASA system, applying a Two-Step
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Cluster analysis, yielded in tambaqui 3 different subpopulations in fresh sperm: SP1,
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considered as a slow non-linear subpopulation; SP2, considered as a fast non-linear
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subpopulation and finally; SP3, considered as a fast linear subpopulation. For
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cryopreserved sperm, the cluster analysis yielded only 2 sperm subpopulations: SP1’,
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considered as a slow non-linear subpopulation and SP2’, which seemed to be an
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intermediate subpopulation (showing medium motility and velocity values) merged
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from SP2 and SP3 obtained from fresh sperm.
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Coefficients of correlation (r) and determination (r-squared) between the sperm
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subpopulations from fresh sperm and the fertilization rates were calculated, and SP2 and
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SP3 (the fast-spermatozoa subpopulations) showed a high positive correlation with the
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fertilization rates (r = 0.93 and 0.79, respectively). In addition, the positive significant
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correlations found in curvilinear velocity (r = 0.78), straight line velocity (r = 0.57) and
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average velocity (r = 0.75) indicates that sperm kinetic features seem to be a key factor
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in the fertilization process in tambaqui, as occur in other fish species.
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Keywords
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CASA; Motility; Velocity; Kinetic parameters; Sperm quality
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1. Introduction
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The presence of various sperm types within a species is a widespread phenomenon both
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in invertebrates and vertebrates, implying that spermatozoa with different physiological
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and/or morphological characteristics coexist in the same ejaculate [1]. These
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spermatozoa can be grouped by clusters based on different biological features and
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classified in different sperm subpopulations. Although this topic was initially reported
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in many species of mammals [2–4], recently it has received considerable attention in
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fish studies [5–7].
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The first step for the sperm subpopulations study is the choice of a classification
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criterion (head or flagella morphology, swimming pattern, etc…), and it is reasonable to
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assume that criterion chosen should be related with the sperm quality. In this respect,
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the kinetic features of spermatozoa represent a suitable approach for making
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subpopulations, and the gradual appearance of CASA (Computer Assisted Sperm
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Analysis) systems represents a useful tool for working on this topic. Nevertheless,
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although most of these CASA´s parameters have been independently correlated with the
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fertilization ability in some species [8,9], there are scarce reports linking sperm
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subpopulations and the fertilization success both in mammals and fish.
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Analysis of sperm subpopulations have been successfully applied in several scientific
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matters, among them we can emphasize the assessment and improvement of
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cryopreservation protocols [5]. In this respect, sperm cryopreservation has led to
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transcendental changes in the reproductive biotechnology in fish, and this technique has
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provided important advantages such as (i) the simplification of broodstock management,
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(ii) the synchronization of gamete availability of both sexes, (iii) the transport of
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gametes from different fish farms, and (iv) the germplasm storage for conservation of
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species [10]. However, cryopreservation protocols also generate damage to cell
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structure and physiology, altering sperm motion patterns of spermatozoa [11]. In this
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respect, the task of assessing the influence of the freezing process in the ability of
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spermatozoa
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cryopreservation field.
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The choice of working with the Amazonian fish tambaqui (Colossoma macropomum) is
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related to the great economic and ecological importance of this species in South
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America, being the native Brazilian fish with the highest agricultural production under
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intensive aquaculture [12]. However, a decrease in the genetic variability of broodstocks
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to
fertilize
the
oocyte
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essential
for
improving
the
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traits of the produced fingerlings. Therefore, both the analysis of sperm subpopulations
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based on motility characteristics and the improvement of cryopreservation process could
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minimize these obstacles, helping to assess the status of the sperm sample and its
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fertility potential.
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In summary, the main goals of this study were (i) to identify and characterize sperm
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subpopulations through kinetic parameters in fresh sperm of tambaqui, assessing the
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changes caused by the cryopreservation process; and (ii) evaluate the correlation of
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these subpopulations with the fertilization rates, trying to find sperm quality biomarkers
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(subpopulations) for its application in the aquaculture sector.
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2. Materials and methods
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2.1 Fish handling and gamete collection
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All the trials were carried out in accordance with the animal guidelines of the Principles
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of Laboratory Animal Science and performed at the Santa Clara Aquaculture Farm
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(Propriá, Sergipe, Brazil) and the Animal Reproduction and Biotechnology Laboratory
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of Embrapa Coastal Tablelands (Aracaju, Sergipe, Brazil).
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Males and females of sexually mature tambaqui were transfer from earthen pond to 5-
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m3 running freshwater tanks at 27 - 29°C. Males were induced to maturation by a single
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dose of carp pituitary extract (CPE) of 2.0 mg kg-1 and females by an initial dose of 0.5
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and a final dose, 12 h later, of 5 mg kg-1 of CPE. Approximately 10 h after the last CPE
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injection, the genital area of both males and females was cleaned and thoroughly dried
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to avoid the contamination (faeces, urine or freshwater), and gentle abdomen pressure
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was applied to obtain the gametes. Sperm from each male was collected into a glass test
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tube and maintained at 4ºC until motility analysis. Oocytes were collected just before
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the fertilization assay.
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The number of fish used for each trial was different: i) for the characterization of fish
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sperm subpopulation of fresh and cryopreserved sperm, 61 males were used; for the
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characterization of sperm kinetics parameters of fresh and cryopreserved sperm, 8 males
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were used; and finally, for the fertilization trail, 15 males and one female were used.
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2.2 Assessment of sperm motility parameters
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ACCEPTED MANUSCRIPT Sperm samples were evaluated mixing an aliquot of 2 or 20 µl of fresh or cryopreserved
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sperm, respectively, with 500 µl of NaHCO3 (230 mOsm, pH adjusted to 8.2). A 3-µL
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drop of activated sperm was placed and observed on the microscope (Nikon® H550S,
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ECLIPSE 50i, Japan) using a Makler® chamber (10 µm deep; Sefi Medical Instruments,
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Haifa, Israel). Video sequences were recorded at 100 fps using a high-sensitivity video
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camera (Basler Vision Technologies® A-602fc-2, Germany). Ten one-second videos
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were automatically captured every 3 s for each sample starting at 10 s after sperm
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activation. All the motility analyses were performed in triplicate using the motility
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module of Sperm Class Analyzer (SCA®, Microptics S.L., Barcelona, Spain).
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The parameters assessed in this study were total motility (TM, %), defined as the
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percentage of motile cells; progressive motility (PM, %), defined as the percentage of
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spermatozoa which swim in an essentially straight line; curvilinear velocity (VCL,
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µm/s), defined as time-averaged velocity of a sperm head along its actual curvilinear
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path, as perceived in two dimensions in the microscope; straight line velocity (VSL,
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µm/s), defined as the time-averaged velocity of a sperm head along the straight line
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between its first detected position and its last; average path velocity (VAP, µm/s),
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defined as time-averaged velocity of a sperm head along its average path; straightness
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(STR, %), defined as the linearity of the average path (VSL/VAP); linearity (LIN, %),
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defined as the linearity of a curvilinear path (VSL/VCL); wobble (WOB, %), defined as
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a measure of oscillation of the actual path about the average path (VAP/VCL); the
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amplitude of lateral head displacement (ALH, µm), defined as magnitude of lateral
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displacement of a sperm head about its average path. It can be expressed as a maximum
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or an average of such displacements; and beat cross frequency (BCF, beats/s), defined
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average rate at which the curvilinear path crosses the average path. Spermatozoa were
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considered immotile if their VCL was lower than 20 µm/s.
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2.3 Sperm cryopreservation
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Sperm samples were cryopreserved according to the protocol proposed by Carneiro et
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al. (2012) [13]. Sperm was diluted in a medium composed of 5% glucose (277 mM) +
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10% methyl glycol + 5% egg yolk at a 1:9 ratio (sperm:freezing medium) and stored in
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0.5 mL straws, identified and sealed with polyvinyl alcohol. After 20 minutes
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(equilibration time), the straws were cryopreserved in liquid nitrogen into a dry shipper
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model (MVE 4/2v) at -175°C, where they remained stored (a minimum of 24 h) until
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the moment of thawing 5
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For thawing process, the straws were removed from the liquid nitrogen canister and
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immediately placed in a bain-marie water bath at 60 °C for eight seconds. Then, their
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contents were poured into 1.5 mL plastic tubes for immediate evaluation of sperm
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quality. The samples with sperm motility greater than 50% were considered suitable for
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use in the fertilization trials.
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Gametes from 15 males and 1 female were used for fertilizations assays. Eggs from the
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female were equally divided into 15 batches of ~600 eggs and placed into 50 mL plastic
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cups. A known aliquot of sperm from each male, adjusting the volume according to the
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2.5 x105 sperm/egg ratio, was added to the corresponding batch of eggs and finally,
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sperm activation was triggered tacking on 5 ml of NaHCO3 solution (230 mOsm, pH
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adjusted to 8.2). After an incubation period of 2 min, the eggs were transferred into
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incubators of PVC pipe (100 mm diameter x 150 mm height, working volume of
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approximately one liter) with a screened bottom (500 µm) and then incubated at a
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controlled temperature of 27 - 29°C. Fertilization rates were evaluated between 6-8 h
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after insemination by counting the percentage of embryos, which reached the blastula
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stage in relation to the total number of used eggs.
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2.5 Statistical analysis
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All the statistical analyses were performed using the statistical package SPSS version
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19.0 for Windows software (SPSS Inc., Chicago, IL, USA). The mean and standard
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error were calculated for all the sperm quality parameters. Shapiro-Wilk and Levene
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tests were used to check the normality of data distribution and variance homogeneity,
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respectively. Pearson´s correlation, coefficient of determination and linear regression
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analysis were used to find the relationship between the different sperm quality
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parameters and fertilization rates.
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For the study of sperm subpopulations, a total of 59,767 and 50,680 motile spermatozoa
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were analysed both in fresh and cryopreserved samples (n=61), respectively. For the
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fertilization trials, 5,375 motile spermatozoa were analysed (n=15).
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All the analysis were carried out based on a Two-Step Cluster analysis using the
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spermatozoa kinetic parameters rendered by SCA® software and following the
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methodology reported by Beirão el al (2011) [5]. Clustering was carried out using the
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log-likelihood distances and the Schwarz’s Bayesian criterion (BIC).
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3. Results
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3.1 Sperm motility parameters of fresh and cryopreserved sperm
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In this trial, the sperm motility parameters of fresh and cryopreserved sperm were
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analysed during the first 40 s after activation (Figure 1). Cryopreservation process
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affected significantly TM values, and cryopreserved sperm showed significantly lower
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values than fresh sperm at the beginning of sperm activation (10, 13 and 16 s; Fig. 1A).
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However, TM of fresh sperm displayed a sharp decline over time, with significant
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differences from 25 s post-activation. At the end of the swimming period (34 and 37 s),
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cryopreserved sperm showed higher TM values than fresh sperm. Regarding PM, fresh
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sperm displayed a dramatically decline at the beginning of the swimming period (10-16
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s), and only showed higher values than cryopreserved sperm at 10 s after activation
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(Fig. 1B). For its part, cryopreserved sperm displayed a slight decline in PM values;
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therefore, it showed significantly higher values than fresh sperm from 22 s after
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activation until the end of the swimming period.
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With regards to spermatozoa velocities, a common pattern was found in either VCL,
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VSL or VAP (Fig. 1C, D and E). Fresh and cryopreserved sperm displayed similar
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velocity values at the beginning of sperm activation, and significant differences respect
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to the initial values were found at 16 and 25 s, respectively. Fresh sperm displayed a
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steeper drop in spermatozoa velocity values, therefore cryopreserved sperm showed
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significantly higher values than fresh sperm from 19 s after activation.
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Other sperm quality parameters linked to the spermatozoa trajectories are shown in
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Table 1. LIN, STR, WOB and BCF from both fresh and cryopreserved sperm showed a
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gradual decline over time, even though it was much more pronounced in fresh
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spermatozoa. Therefore, cryopreserved sperm showed higher values than fresh sperm in
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all these parameters as the activation time progressed. Regarding ALH, cryopreserved
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sperm showed similar values over time while fresh spermatozoa displayed newly a
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sharp decline.
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3.2 Sperm subpopulations of fresh and cryopreserved sperm
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The application of Two-Step Cluster analysis to the values obtained by SCA® software
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for fresh sperm yielded 3 sperm subpopulations (SP1, SP2 and SP3), which were
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characterized by the mean values of motility parameters (Table 2). 7
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analysed spermatozoa. SP1 showed the lowest velocity (VCL, VSL and VAP) and
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linearity (LIN and STR) values, so it was considered a slow non-linear subpopulation
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(Fig. 2A). On the other hand, SP2 accounted for 31.61% of the total analysed
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spermatozoa, with moderately high velocity (VCL, VSL and VAP) values but showing
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circular and regular trajectories. Therefore, SP2 was considered as a fast non-linear
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subpopulation (Fig. 2B). Finally, SP3 was the most abundant subpopulation, accounting
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for 39.58% of the total analysed spermatozoa. SP3 showed the highest velocity (VCL,
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VSL and VAP) and linearity (LIN and STR) values, hence it was considered a fast
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linear subpopulation (Fig. 2C). It is important to note that males showed a high
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variability in the frequency subpopulation´s distribution (Fig. 3). In this respect, SP1
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ranged from 8 to 82% between selected males, and SP2 and SP3 from 11 to 43% and 5
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to 63%, respectively. In addition, a significant negative correlation (p<0,01) was found
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between SP1 and the subpopulations SP2 and SP3.
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For cryopreserved sperm, the subpopulation analysis yielded 2 sperm subpopulations
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(SP1’ and SP2’), as summarized in Table 2. SP1’ and SP2’ accounted for 33.24% and
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66.76% of total analysed spermatozoa, respectively. Spermatozoa of SP1’ showed low
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velocity (VCL, VSL and VAP) and linearity (LIN and STR) values, therefore SP1’ was
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considered a slow non-linear subpopulation (Fig. 2D). For its part, spermatozoa of SP2’
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showed high velocity (VCL, VSL and VAP) and linearity (LIN and STR) values, hence
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this population was considered a fast linear subpopulation (Fig. 2E). It is important to
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highlight that cryopreserved sperm showed only 2 subpopulations, where SP2’ seems to
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be an intermediate subpopulation (showing medium motility and velocity values)
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merged from SP2 and SP3 obtained from fresh sperm.
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3.3 Linking sperm motility parameters and subpopulations to fertilization ability
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Coefficients of correlation (r) and determination (r-squared) between the sperm motility
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parameters and fertilization rates are shown in Table 3. Positive correlations between
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fertilization rates and all parameters provided by SCA system were found, and motilities
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(TM and PM; r = 0.67 and 0.60, respectively) and velocities (VCL and VAP; r = 0.78
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and 0.75, respectively) showed the highest correlations. Regarding coefficient of
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determination (r-squared), which shows the goodness of fit of a model and represents
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the proportion of variability in a data set that is accounted by the statistical mode,
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spermatozoa velocities (VCL and VAP) showed the highest values. 8
ACCEPTED MANUSCRIPT 249 Coefficients of correlation (r) and determination (r-squared) between the sperm
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subpopulations (SP1, SP2 and SP3) yielded from fresh sperm and the fertilization rates
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are shown in Figure 4. Linear regression equation was calculated for each subpopulation
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and SP2 and SP3 showed a high positive correlation with the fertilization rates (r = 0.93
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and 0.79, respectively). However, SP1 did not show a significant correlation with the
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fertilization rates (r = 0.28).
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4. Discussion
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Sperm motility parameters of fresh and cryopreserved sperm
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The motility of the tambaqui spermatozoa has been studied during the recent years [13–
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15]; however, there are no studies with detail on the kinematic patterns over time
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neither in fresh nor in cryopreserved sperm. In this respect, and seeking a way to
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improve the handling of fish sperm used in aquaculture, ecological or scientific
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purposes, a thorough characterization of kinetic characteristics of tambaqui spermatozoa
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over a swimming period has been reported in this study.
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Our results showed cryopreservation process affects significantly total and progressive
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motility values, and cryopreserved sperm shows significantly lower values than fresh
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sperm in these parameters at the beginning of sperm activation. However, it is important
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to note that although initial values of most of sperm motion parameters from fresh
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sperm showed higher values than cryopreserved sperm, cryopreserved spermatozoa
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displayed a slight decline until the end of the motion period, showing higher values than
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fresh sperm for much of motility period. In this respect, it is a hard task to found a
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biological reason about this sperm motion pattern after cryopreservation process, and
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metabolic pathways related to expense of ATP should be involved on it [18].
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On the other hand, the results obtained in this study improve previous cryopreservation
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experiments carried out in tambaqui, which reported post-thawing motility values from
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51% [16] to 56% [17] (around 72% were newly recorded during this experiment). In
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this sense, although has been recently published that frozen sperm of tambaqui is as
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good as fresh sperm in leading to a successful pregnancy through IVF trials [19], new
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approaches from the rational use of cryopreserved sperm should improve several
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aquaculture procedures in fertilization trials. In this respect, cryopreservation process
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must be implemented with the aim i) to improve existing hatchery operations by
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providing sperm on demand and simplifying the timing of induced spawning; ii) to
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enhance efficient use of facilities and create new opportunities in the hatchery by
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eliminating the need to maintain live males; ant iii) to maintain valuable genetic
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lineages such as endangered species or research models.
286 Sperm subpopulations of fresh and cryopreserved sperm
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Although several studies have used CASA systems to track tambaqui spermatozoa
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[16,17,20], no reports have focused on classifying the spermatozoa according to their
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kinematic patterns, so this is the first study which has yielded sperm subpopulations in
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tambaqui sperm. Data generated in this trial supported the interpretation that there are
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three sperm subpopulations (SP1, SP2 and SP3) in tambaqui sperm, and this finding is
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closed and consistent with other studies reported in fish. Beirão et al. (2011) [5]
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detected 3 sperm subpopulations in gilthead sea bream (Sparus aurata); Kanuga et al.
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(2011) [6] detected 3 sperm subpopulations in rainbow trout (Oncorhynchus mykiss);
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Martínez-Pastor et al. (2008) [21] reported 4 sperm subpopulations in Senegalese sole
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(Solea senegalensis); and finally, Gallego et al. (2014) [7] detected 3 subpopulations in
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European eel (Anguilla Anguilla). Regarding the motion pattern of each subpopulation,
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our results are also consistent with these studies, where SP1 is represented by ‘slow and
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linear’ spermatozoa, SP2 by ‘fast and non-linear’ spermatozoa and finally, SP3 by ‘fast
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and linear’ spermatozoa. This pattern resembles the subpopulations found in sea bream
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[5] and sole fish [21,22], with some differences regarding the ‘slow and non-linear’’
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subpopulation in European eel [7]. Nevertheless, all the studies had a ‘fast and linear’
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subpopulation and a ‘fast and non-linear’ subpopulation in common. It is possible that
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this ‘fast linear’ subpopulation (SP3 in the present study) includes the best-quality
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spermatozoa, as has been suggested previously [5]. Meanwhile, SP1 could correspond
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to immature spermatozoa, forced out during the stripping process, and SP2 could be
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represented by an intermediate state between the SP3 and SP1 patterns, or it could just
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be a transient stage of SP3 spermatozoa.
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On the other hand, an interesting result was obtained regarding the number and
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distribution of sperm subpopulations after cryopreservation process. In this respect, only
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two sperm subpopulations (SP1’ and SP2’) were obtained from frozen sperm, where
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SP1’ was considered the slow non-linear subpopulation (like SP1) and SP2’ the fast
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linear subpopulation. However, it is important to highlight that SP2’ seems to be an
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intermediate subpopulation merged from SP2 and SP3 (obtained from fresh sperm),
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showing medium motility and velocity values. In this respect, cryopreservation
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protocols generates damage to cell structure and physiology, altering sperm motion
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patterns of spermatozoa, and favouring the apparition of “new motion tracks” of
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spermatozoa [23].
320 Linking sperm motility parameters and subpopulations to fertilization ability
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The use of high quality gametes from both males and females is an essential factor to
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reach suitable fertilization and hatching rates [24]; and the current appearance of CASA
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systems has made it possible to estimate a higher number of sperm parameters by an
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objective, rapid and accurate technique [25]. In this study we have estimated, for the
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first time, the relationship between all the parameters provided by a CASA system and
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the fertilization rates (FR) in amazon tambaqui. High correlations were found between
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total and progressive motility and FR (r > 0.6), the same as seen in some freshwater
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species such as rainbow trout (Oncorhynchus mykis) [26]; African catfish (Clarias
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gariepinus) [27]; tench (Tinca tinca) [28]; or common carp (Cyprinus carpio) [29]. In
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addition to the percentage of motile spermatozoa as a good tool to predict fertilization
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ability, spermatozoa velocities may also serve as prognostic indicators of the
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fertilization potential of sperm [30]. In fact, in our study the highest coefficients of
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correlation and determination were found for VCL and VAP (r > 0.7), which showed
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better correlations with FR than the parameters traditionally used to define sperm
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quality (TM and PM). This result can be explained through logical hypothesis: at the
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gamete level, the egg-sperm contact could be influenced by several factors such as the
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amount of spermatozoa, the number of motile spermatozoa, sperm velocity and sperm
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longevity. When in IVF trials the number of spermatozoa becomes a limiting factor
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(tight sperm/egg ratio), increases in spermatozoa velocities will enable spermatozoa to
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look for the egg and penetrate the micropyle at a faster rate per time unit, increasing in
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this way fertilization success [30,31].
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On the other hand, this is the first study relating fertilization ability with sperm
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subpopulations in fresh water species. Data generated in this experiment showed that
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SP2 was the subpopulation best correlated with the fertilization rate (r > 0.9), while SP1
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presented a lower correlation with the fertilization rate, which could indicate that they
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are represented by spermatozoa with a lower possibility of attaining fertilization when
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competing with spermatozoa present in SP2 and SP3. In this respect, SP2 represent the
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ACCEPTED MANUSCRIPT fast and non-linear spermatozoa, so linearity of spermatozoa is not presented as an
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indispensable requirement to achieve high FR in amazon tambaqui.
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In this respect, new approaches in relation to male´s broodstock selection through sperm
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kinetics features, like sperm subpopulations, can be used from this perspective.
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Improvements in the aquaculture sector could optimize the reproductive efficiency in
354
the fish farms, making possible the rational use of gametes, limiting the number of
355
breeding fish and, thus, reducing production costs. However, it is important to highlight
356
that breeding fish programs involves a lot of factors and, reducing the number of
357
breeders we could also be decreasing the genetic diversity/basis of broodstock.
358
Therefore, the proper application of several factors among these programs will define
359
the further improvements in aquaculture sector.
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Acknowledgements
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This work was supported by grants-in-aid for scientific research from National Council
363
for Scientific and Technological Development of Brazil (CNPq) and Foundation for
364
Research Support and Technological Innovation of Sergipe State (FAPITEC).
365
The authors would like to thank Mr. José Bonifácio V. de Carvalho, the owner of Santa
366
Clara Fish Farm, for providing the facilities and specimens used in the experiments. The
367
authors also would like to thank CNPq and FAPITEC for financial support.
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[28] Rodina M, Gela D, Kocour M, Alavi SMH, Hulak M, Linhart O.
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[29] Linhart O, Rodina M, Cosson J. Cryopreservation of sperm in common carp
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[30] Gallego V, Pérez L, Asturiano JF, Yoshida M. Relationship between
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[31] Gage MJG, Macfarlane CP, Yeates S, Ward RG, Searle JB, Parker GA.
460
Spermatozoal traits and sperm competition in Atlantic salmon. Curr Biol
462 463 464
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2004;14:44–7.
Table legends
465 466
Table 1. Motion parameters of tambaqui sperm at different post-activation times: 10,
467
13, 16, 19, 22, 25, 28, 31, 34 and 37 s. Data are expressed as mean ± SEM (n = 8).
15
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Asterisks mean significant differences between fresh and cryopreserved sperm at the
469
same post-activation time.
470
Abbreviations: LIN, linearity; STR, straightness; WOB, wobble; ALH, amplitude of
471
lateral head displacement; BCF, beat cross frequency.
472 Table 2. Mean values ± SD obtained from the clustering analysis for the motile
474
subpopulations of fresh (SP1, SP2 and SP3) and cryopreserved (SP1’ and SP2’) sperm
475
based on the kinetic parameters given by SCA® system (61 males; n= 59.767 and
476
50.680 spermatozoa analysed from fresh and cryopreserved sperm, respectively).
477
Abbreviations: VCL, curvilinear velocity; VSL, straight line velocity; VAP, average
478
path velocity; LIN, linearity; STR, straightness; WOB, wobble; ALH, amplitude of
479
lateral head displacement; BCF, beat cross frequency.
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Table 3. Coefficients of correlation (r) and determination (r-squared) between the sperm
482
motility parameters and fertilization rates (n=15). Asterisks indicates significant
483
correlations between parameters (*, p-value < 0.05; **, p-value < 0.01).
484
Abbreviations: TM, total motility; PM, progressive motility; FA, fast spermatozoa; ME,
485
medium spermatozoa; SL, slow spermatozoa; VCL, curvilinear velocity; VSL, straight
486
line velocity; VAP, average path velocity; LIN, linearity; STR, straightness; WOB,
487
wobble; ALH, amplitude of lateral head displacement; BCF, beat cross frequency.
488
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Table 4. Mean values ± SD obtained from the clustering analysis for the 3 motile
490
subpopulations (SP1, SP2 and SP3) of fresh sperm used for fertilization trial on the
491
kinetic parameters given by SCA® system (n= 5.375 spermatozoa from 15 males).
492
Abbreviations: VCL, curvilinear velocity; VSL, straight line velocity; VAP, average
493
path velocity; LIN, linearity; STR, straightness; WOB, wobble; ALH, amplitude of
494
lateral head displacement; BCF, beat cross frequency.
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Figure legends
496 Figure 1. Motility and velocity parameters of tambaqui sperm at different post-
498
activation times: 10, 13, 16, 19, 22, 25, 28, 31, 34 and 37 s. Data are expressed as mean
499
± SEM (n = 8). Asterisks mean significant differences between fresh and cryopreserved
500
sperm at the same time and arrows indicate significant differences respect to the initial
501
values (black and grey arrow: fresh and cryopreserved sperm, respectively).
502
Abbreviations: TM, total motility; PM, progressive motility; VCL, curvilinear velocity;
503
VSL, straight line velocity; VAP, average path velocity.
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Figure 2. Schematic diagram of spermatozoa motion pattern from the different
506
subpopulations of fresh (A: SP1, B: SP2, C: SP3) and cryopreserved sperm (D: SP1’ ,
507
E: SP2’).
508
Black line represents the real trajectory covered by spermatozoa; grey line represents
509
the straight trajectory covered by spermatozoa (from the initial to the final point); and
510
grey spotted line represents the average trajectory covered by spermatozoa.
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Figure 3. Distribution of tambaqui sperm subpopulations from fresh sperm in each male
513
(SP1, SP2, SP3) in fresh sperm (n = 61).
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Figure 4. Relationship between the sperm subpopulations (A, SP1; B, SP2; C, SP3) and
516
fertilization rates in tambaqui (n = 15). Linear regression equation was calculated for
517
each subpopulation.
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Table 1 LIN (%)
ALH (µm)
Cryo
Fresh
Cryo
Fresh
Cryo
Fresh
Cryo
Fresh
Cryo
10
62.13 ± 1.84
62.72 ± 3.04
69.65 ± 1.79
71.70 ± 2.22
85.00 ± 1.01
82.16 ± 2.25
1.33 ± 0.04*
1.16 ± 0.03
20.03 ± 1.09
20.38 ± 1.39
13
57.60 ± 1.86
61.65 ± 2.77
66.81 ± 1.83
71.68 ± 1.56
80.85 ± 1.47
80.40 ± 2.56
1.29 ± 0.04*
1.16 ± 0.03
17.65 ± 1.01
19.87 ± 1.25
16
50.30 ± 2.17
56.60 ± 2.48
61.73 ± 1.60
67.90 ± 1.64*
74.57 ± 1.87
76.55 ± 2.55
1.26 ± 0.04*
1.16 ± 0.03
14.59 ± 1.00
17.79 ± 1.11
19
40.68 ± 2.28
55.35 ± 3.16*
54.80 ± 1.50
68.49 ± 1.87*
67.65 ± 2.23
74.53 ± 2.86
1.20 ± 0.04
1.17 ± 0.03
11.71 ± 0.86
17.85 ± 1.35*
22
33.90 ± 1.95
50.37 ± 4.06*
48.86 ± 1.62
66.08 ± 2.42*
62.10 ± 1.83
70.42 ± 3.58
1.18 ± 0.03
1.18 ± 0.03
9.15 ± 0.61
15.78 ± 1.77*
25
25.57 ± 2.51
45.22 ± 4.99*
42.45 ± 2.32
61.71 ± 3.84*
55.63 ± 2.01
66.74 ± 3.76*
1.13 ± 0.02
1.18 ± 0.03
6.70 ± 0.79
14.38 ± 2.05*
28
18.79 ± 1.81
40.53 ± 5.08*
37.24 ± 1.44
58.75 ± 4.06*
49.65 ± 2.30
63.43 ± 3.65*
1.10 ± 0.03
1.17 ± 0.03
5.28 ± 0.65
12.63 ± 2.12*
31
13.76 ± 0.95
36.75 ± 4.63*
30.88 ± 0.89
56.97 ± 3.62*
46.25 ± 2.31
60.40 ± 3.23*
1.04 ± 0.03
1.17 ± 0.04*
3.80 ± 0.36
10.74 ± 1.93*
34
11.07 ±1.71
31.93 ± 4.74*
27.61 ± 2.58
52.27 ± 4.36*
42.22 ± 3.40
57.70 ± 2.69*
0.94 ± 0.04
1.14 ± 0.03*
2.61 ± 0.41
9.16 ± 1.81*
37
9.82 ± 1.37
26.03 ± 3.68*
26.70 ± 1.97
47.95 ± 4.12*
38.17 ± 4.53
52.73 ± 1.89*
0.88 ± 0.05
1.11 ± 0.04*
2.01 ± 0.43
6.98 ± 1.46*
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BCF (Hz)
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WOB (%)
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STR (%)
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Table 2
Fresh sperm SP2
SP3
SP1´
58.92
±
22.19
114.1
±
34.52
134.11
±
26.24
52.96
±
23.23
121.57
±
33.74
VSL (µm/s)
12.96
±
9.07
50.71
±
20.24
108.94
±
24.05
11.40
±
10.49
85.62
±
37.95
VAP (µm/s)
32.62
±
13.44
89.93
±
29.89
125.81
±
24.71
25.99
±
14.90
109.00
±
35.17
LIN (%)
23.15
±
16.13
46.77
±
17.70
81.41
±
9.21
20.70
±
14.74
69.02
±
21.68
STR (%)
40.01
±
22.79
59.17
±
20.67
86.57
±
7.59
41.70
±
24.20
77.09
±
20.15
WOB (%)
57.73
±
18.92
79.40
±
13.33
93.87
±
5.14
49.44
±
19.50
87.96
±
14.44
ALH (µm)
1.16
±
0.34
1.56
±
0.37
1.32
±
0.23
1.03
±
0.35
1.33
±
0.29
BCF (Hz)
6.79
±
4.34
21.49
±
8.33
±
8.86
5.61
±
4.42
26.00
±
10.54
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VCL (µm/s)
SP2´
EP
26.73
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Cryopreserved sperm
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Table 3 Fertilization rate 0.45
*
0.36
VCL
0.78
**
0.61
VSL
0.57*
0.32
VAP
0.75**
0.56
LIN
0.20
0.04
STR
0.21
0.04
WOB
0.65*
0.42
ALH
0.71**
0.50
BFC
*
0.27
TM
0.60
0.52
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PM
0.67
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r-squared **
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r
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ACCEPTED MANUSCRIPT Table 4 SP1
SP2
SP3
VCL (µm/s)
52.65
±
22.38
109.72
±
42.16
147.27
±
27.48
VSL (µm/s)
10.16
±
7.83
54.59
±
20.89
124.86
±
25.68
VAP (µm/s)
29.78
±
16.23
93.85
±
37.64
140.36
±
25.69
LIN (%)
19.53
±
13.20
53.78
±
18.67
84.93
±
8.56
STR (%)
35.64
±
21.22
62.90
±
20.42
88.88
±
6.97
WOB (%)
56.13
±
18.46
85.55
±
10.30
95.38
±
4.28
ALH (µm)
1.06
±
0.36
1.45
±
0.36
1.33
±
0.24
BCF (Hz)
5.74
±
4.16
19.03
±
8.35
26.15
±
8.94
SC
RI PT
528 529
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A
*
80 *
80
Fresh Cryo
B
*
60 40
*
*
20
90
*
60 30
*
*
*
*
C
*
*
*
*
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*
*
*
*
*
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VSL (µm)
*
60 40
PM (%)
*
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TM (%)
100
SC
531
0
E
VAP (µm)
120
90
*
*
60
*
*
*
*
*
30 0 10
532 533
15
20
25
30
35
40
Time (s)
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ACCEPTED MANUSCRIPT Figure 2 B
D
E
SP2´
C
SP3
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RI PT
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SC
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Figure 3
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SP1 SP2 SP3
Males
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r = 0.28 y = 0.81x + 39.95
r = 0.93 y = 1.51x + 27.89
r = 0.79 y = 0.89x + 30.31
80
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60
20 A
0 20
30
0
10
20
SP2 (%)
40
C
0
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60
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S0093-691X(16)30353-3
DOI:
10.1016/j.theriogenology.2016.08.001
Reference:
THE 13769
To appear in:
Theriogenology
Received Date: 19 April 2016 Revised Date:
1 August 2016
Accepted Date: 2 August 2016
Please cite this article as: Gallego V, Cavalcante SS, Fujimoto RY, Carneiro PCF, Azevedo HC, Maria AN, Fish sperm subpopulations: changes after cryopreservation process and relationship with fertilization success in tambaqui (Colossoma macropomum), Theriogenology (2016), doi: 10.1016/ j.theriogenology.2016.08.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
CLEAN COPY ACCEPTED MANUSCRIPT 1
Fish sperm subpopulations: changes after cryopreservation process
2
and relationship with fertilization success in tambaqui (Colossoma
3
macropomum)
5
V. Gallegoa,b
6
S. S. Cavalcantec
7
R.Y.Fujimotob
8
P.C.F Carneirob
9
H. C. Azevedob A.N. Mariab,*
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11 12
a
13
Universitat Politècnica de València. Camino de Vera s/n. 46022, Valencia, Spain.
14
b
15
Av. Beira Mar, nº 3250, bairro Jardins, 49025-040, Aracaju-SE, Brazil
16
c
Programa de Pós-graduação em Zootecnia, Universidade Federal de Sergipe
18
*
Corresponding author:
19
Alexandre Nizio Maria
20
Laboratório de Biotecnologia da Reprodução Animal (LABRA)
21
Embrapa Tabuleiros Costeiros
22
Av. Beira Mar, Aracaju-SE, Brasil.
23
Tel: 55-79-4009-1360.
24
e-mail: [email protected]
M AN U
Grupo de Acuicultura y Biodiversidad. Instituto de Ciencia y Tecnología Animal.
Animal Reproduction and Biotechnology Laboratory - Embrapa Tabuleiros Costeiros.
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Abstract
26
Fish tambaqui (Colossoma macropomum) is the native Brazilian fish with the highest
27
agricultural production under intensive aquaculture in South America. However, the
28
decreased in the genetic variability in fish farms has become necessary the improvement
29
of cryopreservation process through new statistical studies of spermatozoa (like
30
subpopulation studies).
31
The evaluation of the kinetic data obtained with a CASA system, applying a Two-Step
32
Cluster analysis, yielded in tambaqui 3 different subpopulations in fresh sperm: SP1,
33
considered as a slow non-linear subpopulation; SP2, considered as a fast non-linear
34
subpopulation and finally; SP3, considered as a fast linear subpopulation. For
35
cryopreserved sperm, the cluster analysis yielded only 2 sperm subpopulations: SP1’,
36
considered as a slow non-linear subpopulation and SP2’, which seemed to be an
37
intermediate subpopulation (showing medium motility and velocity values) merged
38
from SP2 and SP3 obtained from fresh sperm.
39
Coefficients of correlation (r) and determination (r-squared) between the sperm
40
subpopulations from fresh sperm and the fertilization rates were calculated, and SP2 and
41
SP3 (the fast-spermatozoa subpopulations) showed a high positive correlation with the
42
fertilization rates (r = 0.93 and 0.79, respectively). In addition, the positive significant
43
correlations found in curvilinear velocity (r = 0.78), straight line velocity (r = 0.57) and
44
average velocity (r = 0.75) indicates that sperm kinetic features seem to be a key factor
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in the fertilization process in tambaqui, as occur in other fish species.
46
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Keywords
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CASA; Motility; Velocity; Kinetic parameters; Sperm quality
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1. Introduction
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The presence of various sperm types within a species is a widespread phenomenon both
51
in invertebrates and vertebrates, implying that spermatozoa with different physiological
52
and/or morphological characteristics coexist in the same ejaculate [1]. These
53
spermatozoa can be grouped by clusters based on different biological features and
54
classified in different sperm subpopulations. Although this topic was initially reported
55
in many species of mammals [2–4], recently it has received considerable attention in
56
fish studies [5–7].
57
The first step for the sperm subpopulations study is the choice of a classification
58
criterion (head or flagella morphology, swimming pattern, etc…), and it is reasonable to
59
assume that criterion chosen should be related with the sperm quality. In this respect,
60
the kinetic features of spermatozoa represent a suitable approach for making
61
subpopulations, and the gradual appearance of CASA (Computer Assisted Sperm
62
Analysis) systems represents a useful tool for working on this topic. Nevertheless,
63
although most of these CASA´s parameters have been independently correlated with the
64
fertilization ability in some species [8,9], there are scarce reports linking sperm
65
subpopulations and the fertilization success both in mammals and fish.
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Analysis of sperm subpopulations have been successfully applied in several scientific
67
matters, among them we can emphasize the assessment and improvement of
68
cryopreservation protocols [5]. In this respect, sperm cryopreservation has led to
69
transcendental changes in the reproductive biotechnology in fish, and this technique has
70
provided important advantages such as (i) the simplification of broodstock management,
71
(ii) the synchronization of gamete availability of both sexes, (iii) the transport of
72
gametes from different fish farms, and (iv) the germplasm storage for conservation of
73
species [10]. However, cryopreservation protocols also generate damage to cell
74
structure and physiology, altering sperm motion patterns of spermatozoa [11]. In this
75
respect, the task of assessing the influence of the freezing process in the ability of
76
spermatozoa
77
cryopreservation field.
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The choice of working with the Amazonian fish tambaqui (Colossoma macropomum) is
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related to the great economic and ecological importance of this species in South
80
America, being the native Brazilian fish with the highest agricultural production under
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intensive aquaculture [12]. However, a decrease in the genetic variability of broodstocks
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to
fertilize
the
oocyte
becomes
essential
for
improving
the
3
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traits of the produced fingerlings. Therefore, both the analysis of sperm subpopulations
84
based on motility characteristics and the improvement of cryopreservation process could
85
minimize these obstacles, helping to assess the status of the sperm sample and its
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fertility potential.
87
In summary, the main goals of this study were (i) to identify and characterize sperm
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subpopulations through kinetic parameters in fresh sperm of tambaqui, assessing the
89
changes caused by the cryopreservation process; and (ii) evaluate the correlation of
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these subpopulations with the fertilization rates, trying to find sperm quality biomarkers
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(subpopulations) for its application in the aquaculture sector.
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2. Materials and methods
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2.1 Fish handling and gamete collection
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All the trials were carried out in accordance with the animal guidelines of the Principles
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of Laboratory Animal Science and performed at the Santa Clara Aquaculture Farm
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(Propriá, Sergipe, Brazil) and the Animal Reproduction and Biotechnology Laboratory
98
of Embrapa Coastal Tablelands (Aracaju, Sergipe, Brazil).
99
Males and females of sexually mature tambaqui were transfer from earthen pond to 5-
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m3 running freshwater tanks at 27 - 29°C. Males were induced to maturation by a single
101
dose of carp pituitary extract (CPE) of 2.0 mg kg-1 and females by an initial dose of 0.5
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and a final dose, 12 h later, of 5 mg kg-1 of CPE. Approximately 10 h after the last CPE
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injection, the genital area of both males and females was cleaned and thoroughly dried
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to avoid the contamination (faeces, urine or freshwater), and gentle abdomen pressure
105
was applied to obtain the gametes. Sperm from each male was collected into a glass test
106
tube and maintained at 4ºC until motility analysis. Oocytes were collected just before
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the fertilization assay.
108
The number of fish used for each trial was different: i) for the characterization of fish
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sperm subpopulation of fresh and cryopreserved sperm, 61 males were used; for the
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characterization of sperm kinetics parameters of fresh and cryopreserved sperm, 8 males
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were used; and finally, for the fertilization trail, 15 males and one female were used.
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2.2 Assessment of sperm motility parameters
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ACCEPTED MANUSCRIPT Sperm samples were evaluated mixing an aliquot of 2 or 20 µl of fresh or cryopreserved
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sperm, respectively, with 500 µl of NaHCO3 (230 mOsm, pH adjusted to 8.2). A 3-µL
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drop of activated sperm was placed and observed on the microscope (Nikon® H550S,
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ECLIPSE 50i, Japan) using a Makler® chamber (10 µm deep; Sefi Medical Instruments,
118
Haifa, Israel). Video sequences were recorded at 100 fps using a high-sensitivity video
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camera (Basler Vision Technologies® A-602fc-2, Germany). Ten one-second videos
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were automatically captured every 3 s for each sample starting at 10 s after sperm
121
activation. All the motility analyses were performed in triplicate using the motility
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module of Sperm Class Analyzer (SCA®, Microptics S.L., Barcelona, Spain).
123
The parameters assessed in this study were total motility (TM, %), defined as the
124
percentage of motile cells; progressive motility (PM, %), defined as the percentage of
125
spermatozoa which swim in an essentially straight line; curvilinear velocity (VCL,
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µm/s), defined as time-averaged velocity of a sperm head along its actual curvilinear
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path, as perceived in two dimensions in the microscope; straight line velocity (VSL,
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µm/s), defined as the time-averaged velocity of a sperm head along the straight line
129
between its first detected position and its last; average path velocity (VAP, µm/s),
130
defined as time-averaged velocity of a sperm head along its average path; straightness
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(STR, %), defined as the linearity of the average path (VSL/VAP); linearity (LIN, %),
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defined as the linearity of a curvilinear path (VSL/VCL); wobble (WOB, %), defined as
133
a measure of oscillation of the actual path about the average path (VAP/VCL); the
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amplitude of lateral head displacement (ALH, µm), defined as magnitude of lateral
135
displacement of a sperm head about its average path. It can be expressed as a maximum
136
or an average of such displacements; and beat cross frequency (BCF, beats/s), defined
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average rate at which the curvilinear path crosses the average path. Spermatozoa were
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considered immotile if their VCL was lower than 20 µm/s.
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2.3 Sperm cryopreservation
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Sperm samples were cryopreserved according to the protocol proposed by Carneiro et
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al. (2012) [13]. Sperm was diluted in a medium composed of 5% glucose (277 mM) +
143
10% methyl glycol + 5% egg yolk at a 1:9 ratio (sperm:freezing medium) and stored in
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0.5 mL straws, identified and sealed with polyvinyl alcohol. After 20 minutes
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(equilibration time), the straws were cryopreserved in liquid nitrogen into a dry shipper
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model (MVE 4/2v) at -175°C, where they remained stored (a minimum of 24 h) until
147
the moment of thawing 5
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For thawing process, the straws were removed from the liquid nitrogen canister and
149
immediately placed in a bain-marie water bath at 60 °C for eight seconds. Then, their
150
contents were poured into 1.5 mL plastic tubes for immediate evaluation of sperm
151
quality. The samples with sperm motility greater than 50% were considered suitable for
152
use in the fertilization trials.
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Gametes from 15 males and 1 female were used for fertilizations assays. Eggs from the
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female were equally divided into 15 batches of ~600 eggs and placed into 50 mL plastic
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cups. A known aliquot of sperm from each male, adjusting the volume according to the
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2.5 x105 sperm/egg ratio, was added to the corresponding batch of eggs and finally,
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sperm activation was triggered tacking on 5 ml of NaHCO3 solution (230 mOsm, pH
160
adjusted to 8.2). After an incubation period of 2 min, the eggs were transferred into
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incubators of PVC pipe (100 mm diameter x 150 mm height, working volume of
162
approximately one liter) with a screened bottom (500 µm) and then incubated at a
163
controlled temperature of 27 - 29°C. Fertilization rates were evaluated between 6-8 h
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after insemination by counting the percentage of embryos, which reached the blastula
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stage in relation to the total number of used eggs.
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2.5 Statistical analysis
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All the statistical analyses were performed using the statistical package SPSS version
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19.0 for Windows software (SPSS Inc., Chicago, IL, USA). The mean and standard
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error were calculated for all the sperm quality parameters. Shapiro-Wilk and Levene
171
tests were used to check the normality of data distribution and variance homogeneity,
172
respectively. Pearson´s correlation, coefficient of determination and linear regression
173
analysis were used to find the relationship between the different sperm quality
174
parameters and fertilization rates.
175
For the study of sperm subpopulations, a total of 59,767 and 50,680 motile spermatozoa
176
were analysed both in fresh and cryopreserved samples (n=61), respectively. For the
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fertilization trials, 5,375 motile spermatozoa were analysed (n=15).
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All the analysis were carried out based on a Two-Step Cluster analysis using the
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spermatozoa kinetic parameters rendered by SCA® software and following the
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methodology reported by Beirão el al (2011) [5]. Clustering was carried out using the
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log-likelihood distances and the Schwarz’s Bayesian criterion (BIC).
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3. Results
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3.1 Sperm motility parameters of fresh and cryopreserved sperm
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In this trial, the sperm motility parameters of fresh and cryopreserved sperm were
186
analysed during the first 40 s after activation (Figure 1). Cryopreservation process
187
affected significantly TM values, and cryopreserved sperm showed significantly lower
188
values than fresh sperm at the beginning of sperm activation (10, 13 and 16 s; Fig. 1A).
189
However, TM of fresh sperm displayed a sharp decline over time, with significant
190
differences from 25 s post-activation. At the end of the swimming period (34 and 37 s),
191
cryopreserved sperm showed higher TM values than fresh sperm. Regarding PM, fresh
192
sperm displayed a dramatically decline at the beginning of the swimming period (10-16
193
s), and only showed higher values than cryopreserved sperm at 10 s after activation
194
(Fig. 1B). For its part, cryopreserved sperm displayed a slight decline in PM values;
195
therefore, it showed significantly higher values than fresh sperm from 22 s after
196
activation until the end of the swimming period.
197
With regards to spermatozoa velocities, a common pattern was found in either VCL,
198
VSL or VAP (Fig. 1C, D and E). Fresh and cryopreserved sperm displayed similar
199
velocity values at the beginning of sperm activation, and significant differences respect
200
to the initial values were found at 16 and 25 s, respectively. Fresh sperm displayed a
201
steeper drop in spermatozoa velocity values, therefore cryopreserved sperm showed
202
significantly higher values than fresh sperm from 19 s after activation.
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Other sperm quality parameters linked to the spermatozoa trajectories are shown in
204
Table 1. LIN, STR, WOB and BCF from both fresh and cryopreserved sperm showed a
205
gradual decline over time, even though it was much more pronounced in fresh
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spermatozoa. Therefore, cryopreserved sperm showed higher values than fresh sperm in
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all these parameters as the activation time progressed. Regarding ALH, cryopreserved
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sperm showed similar values over time while fresh spermatozoa displayed newly a
209
sharp decline.
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3.2 Sperm subpopulations of fresh and cryopreserved sperm
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The application of Two-Step Cluster analysis to the values obtained by SCA® software
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for fresh sperm yielded 3 sperm subpopulations (SP1, SP2 and SP3), which were
214
characterized by the mean values of motility parameters (Table 2). 7
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analysed spermatozoa. SP1 showed the lowest velocity (VCL, VSL and VAP) and
217
linearity (LIN and STR) values, so it was considered a slow non-linear subpopulation
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(Fig. 2A). On the other hand, SP2 accounted for 31.61% of the total analysed
219
spermatozoa, with moderately high velocity (VCL, VSL and VAP) values but showing
220
circular and regular trajectories. Therefore, SP2 was considered as a fast non-linear
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subpopulation (Fig. 2B). Finally, SP3 was the most abundant subpopulation, accounting
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for 39.58% of the total analysed spermatozoa. SP3 showed the highest velocity (VCL,
223
VSL and VAP) and linearity (LIN and STR) values, hence it was considered a fast
224
linear subpopulation (Fig. 2C). It is important to note that males showed a high
225
variability in the frequency subpopulation´s distribution (Fig. 3). In this respect, SP1
226
ranged from 8 to 82% between selected males, and SP2 and SP3 from 11 to 43% and 5
227
to 63%, respectively. In addition, a significant negative correlation (p<0,01) was found
228
between SP1 and the subpopulations SP2 and SP3.
229
For cryopreserved sperm, the subpopulation analysis yielded 2 sperm subpopulations
230
(SP1’ and SP2’), as summarized in Table 2. SP1’ and SP2’ accounted for 33.24% and
231
66.76% of total analysed spermatozoa, respectively. Spermatozoa of SP1’ showed low
232
velocity (VCL, VSL and VAP) and linearity (LIN and STR) values, therefore SP1’ was
233
considered a slow non-linear subpopulation (Fig. 2D). For its part, spermatozoa of SP2’
234
showed high velocity (VCL, VSL and VAP) and linearity (LIN and STR) values, hence
235
this population was considered a fast linear subpopulation (Fig. 2E). It is important to
236
highlight that cryopreserved sperm showed only 2 subpopulations, where SP2’ seems to
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be an intermediate subpopulation (showing medium motility and velocity values)
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merged from SP2 and SP3 obtained from fresh sperm.
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3.3 Linking sperm motility parameters and subpopulations to fertilization ability
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Coefficients of correlation (r) and determination (r-squared) between the sperm motility
242
parameters and fertilization rates are shown in Table 3. Positive correlations between
243
fertilization rates and all parameters provided by SCA system were found, and motilities
244
(TM and PM; r = 0.67 and 0.60, respectively) and velocities (VCL and VAP; r = 0.78
245
and 0.75, respectively) showed the highest correlations. Regarding coefficient of
246
determination (r-squared), which shows the goodness of fit of a model and represents
247
the proportion of variability in a data set that is accounted by the statistical mode,
248
spermatozoa velocities (VCL and VAP) showed the highest values. 8
ACCEPTED MANUSCRIPT 249 Coefficients of correlation (r) and determination (r-squared) between the sperm
251
subpopulations (SP1, SP2 and SP3) yielded from fresh sperm and the fertilization rates
252
are shown in Figure 4. Linear regression equation was calculated for each subpopulation
253
and SP2 and SP3 showed a high positive correlation with the fertilization rates (r = 0.93
254
and 0.79, respectively). However, SP1 did not show a significant correlation with the
255
fertilization rates (r = 0.28).
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4. Discussion
258
Sperm motility parameters of fresh and cryopreserved sperm
259
The motility of the tambaqui spermatozoa has been studied during the recent years [13–
260
15]; however, there are no studies with detail on the kinematic patterns over time
261
neither in fresh nor in cryopreserved sperm. In this respect, and seeking a way to
262
improve the handling of fish sperm used in aquaculture, ecological or scientific
263
purposes, a thorough characterization of kinetic characteristics of tambaqui spermatozoa
264
over a swimming period has been reported in this study.
265
Our results showed cryopreservation process affects significantly total and progressive
266
motility values, and cryopreserved sperm shows significantly lower values than fresh
267
sperm in these parameters at the beginning of sperm activation. However, it is important
268
to note that although initial values of most of sperm motion parameters from fresh
269
sperm showed higher values than cryopreserved sperm, cryopreserved spermatozoa
270
displayed a slight decline until the end of the motion period, showing higher values than
271
fresh sperm for much of motility period. In this respect, it is a hard task to found a
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biological reason about this sperm motion pattern after cryopreservation process, and
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metabolic pathways related to expense of ATP should be involved on it [18].
274
On the other hand, the results obtained in this study improve previous cryopreservation
275
experiments carried out in tambaqui, which reported post-thawing motility values from
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51% [16] to 56% [17] (around 72% were newly recorded during this experiment). In
277
this sense, although has been recently published that frozen sperm of tambaqui is as
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good as fresh sperm in leading to a successful pregnancy through IVF trials [19], new
279
approaches from the rational use of cryopreserved sperm should improve several
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aquaculture procedures in fertilization trials. In this respect, cryopreservation process
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must be implemented with the aim i) to improve existing hatchery operations by
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providing sperm on demand and simplifying the timing of induced spawning; ii) to
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enhance efficient use of facilities and create new opportunities in the hatchery by
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eliminating the need to maintain live males; ant iii) to maintain valuable genetic
285
lineages such as endangered species or research models.
286 Sperm subpopulations of fresh and cryopreserved sperm
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Although several studies have used CASA systems to track tambaqui spermatozoa
289
[16,17,20], no reports have focused on classifying the spermatozoa according to their
290
kinematic patterns, so this is the first study which has yielded sperm subpopulations in
291
tambaqui sperm. Data generated in this trial supported the interpretation that there are
292
three sperm subpopulations (SP1, SP2 and SP3) in tambaqui sperm, and this finding is
293
closed and consistent with other studies reported in fish. Beirão et al. (2011) [5]
294
detected 3 sperm subpopulations in gilthead sea bream (Sparus aurata); Kanuga et al.
295
(2011) [6] detected 3 sperm subpopulations in rainbow trout (Oncorhynchus mykiss);
296
Martínez-Pastor et al. (2008) [21] reported 4 sperm subpopulations in Senegalese sole
297
(Solea senegalensis); and finally, Gallego et al. (2014) [7] detected 3 subpopulations in
298
European eel (Anguilla Anguilla). Regarding the motion pattern of each subpopulation,
299
our results are also consistent with these studies, where SP1 is represented by ‘slow and
300
linear’ spermatozoa, SP2 by ‘fast and non-linear’ spermatozoa and finally, SP3 by ‘fast
301
and linear’ spermatozoa. This pattern resembles the subpopulations found in sea bream
302
[5] and sole fish [21,22], with some differences regarding the ‘slow and non-linear’’
303
subpopulation in European eel [7]. Nevertheless, all the studies had a ‘fast and linear’
304
subpopulation and a ‘fast and non-linear’ subpopulation in common. It is possible that
305
this ‘fast linear’ subpopulation (SP3 in the present study) includes the best-quality
306
spermatozoa, as has been suggested previously [5]. Meanwhile, SP1 could correspond
307
to immature spermatozoa, forced out during the stripping process, and SP2 could be
308
represented by an intermediate state between the SP3 and SP1 patterns, or it could just
309
be a transient stage of SP3 spermatozoa.
310
On the other hand, an interesting result was obtained regarding the number and
311
distribution of sperm subpopulations after cryopreservation process. In this respect, only
312
two sperm subpopulations (SP1’ and SP2’) were obtained from frozen sperm, where
313
SP1’ was considered the slow non-linear subpopulation (like SP1) and SP2’ the fast
314
linear subpopulation. However, it is important to highlight that SP2’ seems to be an
315
intermediate subpopulation merged from SP2 and SP3 (obtained from fresh sperm),
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showing medium motility and velocity values. In this respect, cryopreservation
317
protocols generates damage to cell structure and physiology, altering sperm motion
318
patterns of spermatozoa, and favouring the apparition of “new motion tracks” of
319
spermatozoa [23].
320 Linking sperm motility parameters and subpopulations to fertilization ability
322
The use of high quality gametes from both males and females is an essential factor to
323
reach suitable fertilization and hatching rates [24]; and the current appearance of CASA
324
systems has made it possible to estimate a higher number of sperm parameters by an
325
objective, rapid and accurate technique [25]. In this study we have estimated, for the
326
first time, the relationship between all the parameters provided by a CASA system and
327
the fertilization rates (FR) in amazon tambaqui. High correlations were found between
328
total and progressive motility and FR (r > 0.6), the same as seen in some freshwater
329
species such as rainbow trout (Oncorhynchus mykis) [26]; African catfish (Clarias
330
gariepinus) [27]; tench (Tinca tinca) [28]; or common carp (Cyprinus carpio) [29]. In
331
addition to the percentage of motile spermatozoa as a good tool to predict fertilization
332
ability, spermatozoa velocities may also serve as prognostic indicators of the
333
fertilization potential of sperm [30]. In fact, in our study the highest coefficients of
334
correlation and determination were found for VCL and VAP (r > 0.7), which showed
335
better correlations with FR than the parameters traditionally used to define sperm
336
quality (TM and PM). This result can be explained through logical hypothesis: at the
337
gamete level, the egg-sperm contact could be influenced by several factors such as the
338
amount of spermatozoa, the number of motile spermatozoa, sperm velocity and sperm
339
longevity. When in IVF trials the number of spermatozoa becomes a limiting factor
340
(tight sperm/egg ratio), increases in spermatozoa velocities will enable spermatozoa to
341
look for the egg and penetrate the micropyle at a faster rate per time unit, increasing in
342
this way fertilization success [30,31].
343
On the other hand, this is the first study relating fertilization ability with sperm
344
subpopulations in fresh water species. Data generated in this experiment showed that
345
SP2 was the subpopulation best correlated with the fertilization rate (r > 0.9), while SP1
346
presented a lower correlation with the fertilization rate, which could indicate that they
347
are represented by spermatozoa with a lower possibility of attaining fertilization when
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competing with spermatozoa present in SP2 and SP3. In this respect, SP2 represent the
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350
indispensable requirement to achieve high FR in amazon tambaqui.
351
In this respect, new approaches in relation to male´s broodstock selection through sperm
352
kinetics features, like sperm subpopulations, can be used from this perspective.
353
Improvements in the aquaculture sector could optimize the reproductive efficiency in
354
the fish farms, making possible the rational use of gametes, limiting the number of
355
breeding fish and, thus, reducing production costs. However, it is important to highlight
356
that breeding fish programs involves a lot of factors and, reducing the number of
357
breeders we could also be decreasing the genetic diversity/basis of broodstock.
358
Therefore, the proper application of several factors among these programs will define
359
the further improvements in aquaculture sector.
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Acknowledgements
362
This work was supported by grants-in-aid for scientific research from National Council
363
for Scientific and Technological Development of Brazil (CNPq) and Foundation for
364
Research Support and Technological Innovation of Sergipe State (FAPITEC).
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The authors would like to thank Mr. José Bonifácio V. de Carvalho, the owner of Santa
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Clara Fish Farm, for providing the facilities and specimens used in the experiments. The
367
authors also would like to thank CNPq and FAPITEC for financial support.
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semen characteristics of tambaqui Colossoma macropomum. Zygote 2012;20:39–
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[14] Maria AN, Azevedo HC, Santos JP, Silva CA, Carneiro PCF. Semen
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characterization and sperm structure of the Amazon tambaqui Colossoma
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macropomum. J Appl Ichthyol 2010;26:779–83.
[15] Vieira MJAF, Carvalho MAM, Salmito-Vanderley CSB, Salgueiro CCM,
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Viveiros ATM, Moura AAAN, et al. Características do sêmen de tambaqui
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(Colossoma macropomum) em latitude equatorial. Arch Zoot n.d.;60:1263–70.
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[16] Varela Junior AS, Goularte KL, Alves JP, Pereira FA, Silva EF, Cardoso TF, et
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al. Methods of cryopreservation of Tambaqui semen, Colossoma macropomum.
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Anim Reprod Sci 2015;157:71–7.
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[17] Carneiro PCF, Azevedo HC, Santos JP, Maria AN. Cryopreservation of tambaqui
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(Colossoma macropomum) semen: Extenders, cryoprotectants, dilution ratios and
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freezing methods. Cryo-Letters 2012;33:385–93.
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[18] Figueroa E, Valdebenito I, Zepeda AB, Figueroa CA, Dumorné K, Castillo RL,
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et al. Effects of cryopreservation on mitochondria of fish spermatozoa. Rev
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Aquac 2015.
[19] Varela Junior AS, Corcini CD, Gheller SMM, Jardim RD, Lucia T, Streit DP, et
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al. Use of amides as cryoprotectants in extenders for frozen sperm of tambaqui,
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Colossoma macropomum. Theriogenology 2012;78:244–51.
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[20] Maria AN, Carvalho ACM, Araújo RV, Santos JP, Carneiro PCF, Azevedo HC.
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Use of cryotubes for the cryopreservation of tambaqui fish semen (Colossoma
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macropomum). Cryobiology 2015;70:109–14.
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[21] Martínez-Pastor F, Cabrita E, Soares F, Anel L, Dinis MT. Multivariate cluster
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analysis to study motility activation of Solea senegalensis spermatozoa: a model
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for marine teleosts. Reproduction 2008;135:449–59.
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[22] Beirão J, Soares F, Herráez MP, Dinis MT, Cabrita E. Sperm quality evaluation
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in Solea senegalensis during the reproductive season at cellular level.
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Theriogenology 2009;72:1251–61.
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[23] Cabrita E, Sarasquete C, Martínez-Páramo S, Robles V, Beirão J, Pérez14
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Cerezales S, et al. Cryopreservation of fish sperm: Applications and perspectives.
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J Appl Ichthyol 2010;26:623–35.
438 439
[24] Bobe J, Labbé C. Egg and sperm quality in fish. Gen Comp Endocrinol 2010;165:535–48. [25] Gallego V, Carneiro PCF, Mazzeo I, Vílchez MC, Peñaranda DS, Soler C, et al.
441
Standardization of European eel (Anguilla anguilla) sperm motility evaluation by
442
CASA software. Theriogenology 2013;79:1034–40.
RI PT
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[26] Tuset VM, Dietrich GJ, Wojtczak M, Słowińska M, de Monserrat J, Ciereszko A.
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Relationships between morphology, motility and fertilization capacity in rainbow
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trout (Oncorhynchus mykiss) spermatozoa. J Appl Ichthyol 2008;24:393–7.
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[27] Rurangwa E, Volckaert FAM, Huyskens G, Kime DE, Ollevier F. Quality control
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of refrigerated and cryopreserved semen using computer-assisted sperm analysis
448
(CASA), viable staining and standardized fertilization in African catfish.
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Theriogenology 2001;55:751–69.
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[28] Rodina M, Gela D, Kocour M, Alavi SMH, Hulak M, Linhart O.
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Cryopreservation of tench, Tinca tinca, sperm: Sperm motility and hatching
452
success of embryos. Theriogenology 2007;67:931–40.
[29] Linhart O, Rodina M, Cosson J. Cryopreservation of sperm in common carp
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Cyprinus carpio: sperm motility and hatching success of embryos. Cryobiology
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2000;41:241–50.
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[30] Gallego V, Pérez L, Asturiano JF, Yoshida M. Relationship between
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spermatozoa motility parameters, sperm/egg ratio, and fertilization and hatching
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rates in pufferfish (Takifugu niphobles). Aquaculture 2013;416-417:238–43.
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[31] Gage MJG, Macfarlane CP, Yeates S, Ward RG, Searle JB, Parker GA.
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Spermatozoal traits and sperm competition in Atlantic salmon. Curr Biol
462 463 464
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2004;14:44–7.
Table legends
465 466
Table 1. Motion parameters of tambaqui sperm at different post-activation times: 10,
467
13, 16, 19, 22, 25, 28, 31, 34 and 37 s. Data are expressed as mean ± SEM (n = 8).
15
ACCEPTED MANUSCRIPT 468
Asterisks mean significant differences between fresh and cryopreserved sperm at the
469
same post-activation time.
470
Abbreviations: LIN, linearity; STR, straightness; WOB, wobble; ALH, amplitude of
471
lateral head displacement; BCF, beat cross frequency.
472 Table 2. Mean values ± SD obtained from the clustering analysis for the motile
474
subpopulations of fresh (SP1, SP2 and SP3) and cryopreserved (SP1’ and SP2’) sperm
475
based on the kinetic parameters given by SCA® system (61 males; n= 59.767 and
476
50.680 spermatozoa analysed from fresh and cryopreserved sperm, respectively).
477
Abbreviations: VCL, curvilinear velocity; VSL, straight line velocity; VAP, average
478
path velocity; LIN, linearity; STR, straightness; WOB, wobble; ALH, amplitude of
479
lateral head displacement; BCF, beat cross frequency.
M AN U
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SC
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473
Table 3. Coefficients of correlation (r) and determination (r-squared) between the sperm
482
motility parameters and fertilization rates (n=15). Asterisks indicates significant
483
correlations between parameters (*, p-value < 0.05; **, p-value < 0.01).
484
Abbreviations: TM, total motility; PM, progressive motility; FA, fast spermatozoa; ME,
485
medium spermatozoa; SL, slow spermatozoa; VCL, curvilinear velocity; VSL, straight
486
line velocity; VAP, average path velocity; LIN, linearity; STR, straightness; WOB,
487
wobble; ALH, amplitude of lateral head displacement; BCF, beat cross frequency.
488
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481
Table 4. Mean values ± SD obtained from the clustering analysis for the 3 motile
490
subpopulations (SP1, SP2 and SP3) of fresh sperm used for fertilization trial on the
491
kinetic parameters given by SCA® system (n= 5.375 spermatozoa from 15 males).
492
Abbreviations: VCL, curvilinear velocity; VSL, straight line velocity; VAP, average
493
path velocity; LIN, linearity; STR, straightness; WOB, wobble; ALH, amplitude of
494
lateral head displacement; BCF, beat cross frequency.
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Figure legends
496 Figure 1. Motility and velocity parameters of tambaqui sperm at different post-
498
activation times: 10, 13, 16, 19, 22, 25, 28, 31, 34 and 37 s. Data are expressed as mean
499
± SEM (n = 8). Asterisks mean significant differences between fresh and cryopreserved
500
sperm at the same time and arrows indicate significant differences respect to the initial
501
values (black and grey arrow: fresh and cryopreserved sperm, respectively).
502
Abbreviations: TM, total motility; PM, progressive motility; VCL, curvilinear velocity;
503
VSL, straight line velocity; VAP, average path velocity.
SC
504
RI PT
497
Figure 2. Schematic diagram of spermatozoa motion pattern from the different
506
subpopulations of fresh (A: SP1, B: SP2, C: SP3) and cryopreserved sperm (D: SP1’ ,
507
E: SP2’).
508
Black line represents the real trajectory covered by spermatozoa; grey line represents
509
the straight trajectory covered by spermatozoa (from the initial to the final point); and
510
grey spotted line represents the average trajectory covered by spermatozoa.
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511
Figure 3. Distribution of tambaqui sperm subpopulations from fresh sperm in each male
513
(SP1, SP2, SP3) in fresh sperm (n = 61).
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514
Figure 4. Relationship between the sperm subpopulations (A, SP1; B, SP2; C, SP3) and
516
fertilization rates in tambaqui (n = 15). Linear regression equation was calculated for
517
each subpopulation.
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Table 1 LIN (%)
ALH (µm)
Cryo
Fresh
Cryo
Fresh
Cryo
Fresh
Cryo
Fresh
Cryo
10
62.13 ± 1.84
62.72 ± 3.04
69.65 ± 1.79
71.70 ± 2.22
85.00 ± 1.01
82.16 ± 2.25
1.33 ± 0.04*
1.16 ± 0.03
20.03 ± 1.09
20.38 ± 1.39
13
57.60 ± 1.86
61.65 ± 2.77
66.81 ± 1.83
71.68 ± 1.56
80.85 ± 1.47
80.40 ± 2.56
1.29 ± 0.04*
1.16 ± 0.03
17.65 ± 1.01
19.87 ± 1.25
16
50.30 ± 2.17
56.60 ± 2.48
61.73 ± 1.60
67.90 ± 1.64*
74.57 ± 1.87
76.55 ± 2.55
1.26 ± 0.04*
1.16 ± 0.03
14.59 ± 1.00
17.79 ± 1.11
19
40.68 ± 2.28
55.35 ± 3.16*
54.80 ± 1.50
68.49 ± 1.87*
67.65 ± 2.23
74.53 ± 2.86
1.20 ± 0.04
1.17 ± 0.03
11.71 ± 0.86
17.85 ± 1.35*
22
33.90 ± 1.95
50.37 ± 4.06*
48.86 ± 1.62
66.08 ± 2.42*
62.10 ± 1.83
70.42 ± 3.58
1.18 ± 0.03
1.18 ± 0.03
9.15 ± 0.61
15.78 ± 1.77*
25
25.57 ± 2.51
45.22 ± 4.99*
42.45 ± 2.32
61.71 ± 3.84*
55.63 ± 2.01
66.74 ± 3.76*
1.13 ± 0.02
1.18 ± 0.03
6.70 ± 0.79
14.38 ± 2.05*
28
18.79 ± 1.81
40.53 ± 5.08*
37.24 ± 1.44
58.75 ± 4.06*
49.65 ± 2.30
63.43 ± 3.65*
1.10 ± 0.03
1.17 ± 0.03
5.28 ± 0.65
12.63 ± 2.12*
31
13.76 ± 0.95
36.75 ± 4.63*
30.88 ± 0.89
56.97 ± 3.62*
46.25 ± 2.31
60.40 ± 3.23*
1.04 ± 0.03
1.17 ± 0.04*
3.80 ± 0.36
10.74 ± 1.93*
34
11.07 ±1.71
31.93 ± 4.74*
27.61 ± 2.58
52.27 ± 4.36*
42.22 ± 3.40
57.70 ± 2.69*
0.94 ± 0.04
1.14 ± 0.03*
2.61 ± 0.41
9.16 ± 1.81*
37
9.82 ± 1.37
26.03 ± 3.68*
26.70 ± 1.97
47.95 ± 4.12*
38.17 ± 4.53
52.73 ± 1.89*
0.88 ± 0.05
1.11 ± 0.04*
2.01 ± 0.43
6.98 ± 1.46*
TE D
M AN U
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Fresh
BCF (Hz)
EP
520
WOB (%)
AC C
Time (s)
STR (%)
RI PT
519
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Table 2
Fresh sperm SP2
SP3
SP1´
58.92
±
22.19
114.1
±
34.52
134.11
±
26.24
52.96
±
23.23
121.57
±
33.74
VSL (µm/s)
12.96
±
9.07
50.71
±
20.24
108.94
±
24.05
11.40
±
10.49
85.62
±
37.95
VAP (µm/s)
32.62
±
13.44
89.93
±
29.89
125.81
±
24.71
25.99
±
14.90
109.00
±
35.17
LIN (%)
23.15
±
16.13
46.77
±
17.70
81.41
±
9.21
20.70
±
14.74
69.02
±
21.68
STR (%)
40.01
±
22.79
59.17
±
20.67
86.57
±
7.59
41.70
±
24.20
77.09
±
20.15
WOB (%)
57.73
±
18.92
79.40
±
13.33
93.87
±
5.14
49.44
±
19.50
87.96
±
14.44
ALH (µm)
1.16
±
0.34
1.56
±
0.37
1.32
±
0.23
1.03
±
0.35
1.33
±
0.29
BCF (Hz)
6.79
±
4.34
21.49
±
8.33
±
8.86
5.61
±
4.42
26.00
±
10.54
M AN U
SC
VCL (µm/s)
SP2´
EP
26.73
AC C
523
Cryopreserved sperm
TE D
SP1
RI PT
522
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Table 3 Fertilization rate 0.45
*
0.36
VCL
0.78
**
0.61
VSL
0.57*
0.32
VAP
0.75**
0.56
LIN
0.20
0.04
STR
0.21
0.04
WOB
0.65*
0.42
ALH
0.71**
0.50
BFC
*
0.27
TM
0.60
0.52
M AN U
PM
0.67
RI PT
r-squared **
SC
r
AC C
EP
TE D
526 527
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ACCEPTED MANUSCRIPT Table 4 SP1
SP2
SP3
VCL (µm/s)
52.65
±
22.38
109.72
±
42.16
147.27
±
27.48
VSL (µm/s)
10.16
±
7.83
54.59
±
20.89
124.86
±
25.68
VAP (µm/s)
29.78
±
16.23
93.85
±
37.64
140.36
±
25.69
LIN (%)
19.53
±
13.20
53.78
±
18.67
84.93
±
8.56
STR (%)
35.64
±
21.22
62.90
±
20.42
88.88
±
6.97
WOB (%)
56.13
±
18.46
85.55
±
10.30
95.38
±
4.28
ALH (µm)
1.06
±
0.36
1.45
±
0.36
1.33
±
0.24
BCF (Hz)
5.74
±
4.16
19.03
±
8.35
26.15
±
8.94
SC
RI PT
528 529
AC C
EP
TE D
M AN U
530
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ACCEPTED MANUSCRIPT Figure 1 *
A
*
80 *
80
Fresh Cryo
B
*
60 40
*
*
20
90
*
60 30
*
*
*
*
C
*
*
*
*
D *
*
*
*
*
*
AC C
EP
90
30
*
M AN U
120
60
*
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VCL (µm)
0
VSL (µm)
*
60 40
PM (%)
*
RI PT
TM (%)
100
SC
531
0
E
VAP (µm)
120
90
*
*
60
*
*
*
*
*
30 0 10
532 533
15
20
25
30
35
40
Time (s)
22
ACCEPTED MANUSCRIPT Figure 2 B
D
E
SP2´
C
SP3
M AN U
SP1´
SP2
RI PT
A
SC
534 535
AC C
EP
TE D
536 537
23
ACCEPTED MANUSCRIPT
Figure 3
RI PT
538
SC M AN U
60
20
TE D
40
EP
539 540
80
SP1 SP2 SP3
Males
AC C
Percentage of subpopulation (%)
100
24
ACCEPTED MANUSCRIPT
100
r = 0.28 y = 0.81x + 39.95
r = 0.93 y = 1.51x + 27.89
r = 0.79 y = 0.89x + 30.31
80
SC
60
20 A
0 20
30
0
10
20
SP2 (%)
40
C
0
20
40
60
SP3 (%)
EP
TE D
SP1 (%)
30
B
AC C
10
M AN U
40
0
542
RI PT
Figure 4
Fertilization rate (%)
541
25