Relação das subpopulações espermáticas em touros Senepol com a produção in vitro de embriões
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Data
2019-11-08
Autores
Campanholi, Suzane Peres [UNESP]
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Universidade Estadual Paulista (Unesp)
Resumo
Em bovinos, a produção in vitro de embriões (PIVE) configura-se como uma das biotecnologias reprodutivas de maior importância no Brasil, sendo responsável pela rápida expansão da raça Senepol em nosso país. Estimar a PIVE em animais Senepol com base na análise seminal dos reprodutores seria valioso para a indústria de criopreservação de sêmen, institutos de pesquisa e criadores da raça. Espermatozoides que diferem quanto ao seu padrão de motilidade coexistem em um ejaculado e podem ser agrupados em diferentes subpopulações espermáticas após análise da cinética com o sistema CASA (Computer-assisted sperm analysis). Aliar essa avaliação com outras análises de qualidade espermática e analisar os resultados com estatísticas multivariadas e inteligência artificial pode ajudar a melhorar a estimativa de fertilidade de um reprodutor. Diante disso, os objetivos no presente estudo foram: 1) identificar e caracterizar as subpopulações espermáticas no sêmen criopreservado de touros Senepol após processo de lavagem para fertilização in vitro (FIV); 2) gerar um modelo estatístico para estimar a PIVE com base nas subpopulações espermáticas e demais atributos espermáticos analisados, utilizando análises estatísticas multivariadas e 3) aplicar a inteligência artificial, por meio do uso das redes neurais artificiais (RNAs) com o intuito de melhorar a estimativa da PIVE. Dados retrospectivos de 386 rotinas de PIVE foram obtidos a partir dos registros pertencentes à empresa In Vitro Brasil e a produção embrionária foi categorizada em alta, média e baixa. Após, 38 amostras de sêmen criopreservado de touros Senepol, utilizadas nas rotinas de PIVE, foram adquiridas da empresa Senepol 3G para avaliação. Pós-descongelação todas as amostras passaram por avaliação da morfologia espermática e em seguida foram submetidas a um processo de lavagem que é realizado antes da FIV. Pós-lavagem todas as amostras foram avaliadas pelo sistema CASA para obter a cinética geral das amostras e a cinética individual dos espermatozoides. Ademais, foi realizada avaliação, por citometria de fluxo, da integridade das membranas plasmática e acrossomal, potencial mitocondrial, status oxidativo e resistência da cromatina. Após análises multivariadas de componentes principais e agrupamento foram identificadas três subpopulações espermáticas: SBP1 (movimento rápido e progressivo), SBP2 (movimento hiperativado) e SBP3 (movimento lento e não progressivo). Com a análise de regressão logística foi constatado que a PIVE sofre efeito da SBP1 e SBP2 e um modelo com essas variáveis foi gerado para estimar as categorias de produção embrionária. Com a análise de RNAs foram gerados modelos para estimar a PIVE com 18, oito e seis variáveis preditoras, sendo que o modelo mais simples incluiu as três subpopulações espermáticas e as variáveis de integridade das membranas plasmática e acrossomal, alto potencial mitocondrial e defeitos totais como preditores.
In cattle, in vitro embryo production (IVEP) is one of the most important reproductive biotechnologies in Brazil, being responsible for the rapid expansion of the Senepol breed in our country. Estimating IVEP in Senepol animals based on seminal analysis of breeders would be valuable for the semen cryopreservation industry, research institutes and Senepol cattle breeders. Spermatozoa that differ in their motility pattern coexist in an ejaculate and can be grouped into different sperm subpopulations after kinetic analysis with the CASA system (Computer-assisted sperm analysis). Combining this assessment with other analyzes of sperm quality and analyzing the results with multivariate statistics and artificial intelligence can help to improve a breeder's fertility estimate. Therefore, the objectives in the present study were: 1) identify and characterize sperm subpopulations in cryopreserved semen of Senepol bulls after washing process for in vitro fertilization (IVF); 2) generate a statistical model to estimate IVEP based on the sperm subpopulations and other sperm attributes analyzed, using multivariate statistical analysis and 3) apply artificial intelligence, through the use of artificial neural networks (ANNs) in order to improve the estimate of IVEP. Retrospective data from 386 IVEP routines were obtained from the records belonging to the enterprise In Vitro Brasil and embryonic production was categorized as high, medium and low. After, 38 samples of cryopreserved semen from Senepol bulls, used in IVEP routines, were acquired from the enterprise Senepol 3G for evaluation. After thawed, all samples were evaluated for sperm morphology and then subjected to a washing process that is performed before IVF. After washing, all samples were evaluated by the CASA system to obtain the general kinetics of the samples and the individual kinetics of the sperm. In addition, flow cytometry was evaluated for the integrity of the plasma and acrosomal membranes, mitochondrial potential, oxidative status and chromatin resistance. After multivariate analyzes of principal components and grouping, three sperm subpopulations were identified: SBP1 (fast and progressive motility), SBP2 (hyperactived motility) and SBP3 (slow and non-progressive motility). With the logistic regression analysis, it was found that IVEP suffers the effect of SBP1 and SBP2 and a model with these variables was generated to estimate the categories of embryonic production. With the analysis of ANNs, models were generated to estimate IVEP with 18, eight and six predictor variables, and the simplest model included the three sperm subpopulations and the variables plasma and acrosomal membranes integrity, high mitochondrial potential and total defects such as predictors.
In cattle, in vitro embryo production (IVEP) is one of the most important reproductive biotechnologies in Brazil, being responsible for the rapid expansion of the Senepol breed in our country. Estimating IVEP in Senepol animals based on seminal analysis of breeders would be valuable for the semen cryopreservation industry, research institutes and Senepol cattle breeders. Spermatozoa that differ in their motility pattern coexist in an ejaculate and can be grouped into different sperm subpopulations after kinetic analysis with the CASA system (Computer-assisted sperm analysis). Combining this assessment with other analyzes of sperm quality and analyzing the results with multivariate statistics and artificial intelligence can help to improve a breeder's fertility estimate. Therefore, the objectives in the present study were: 1) identify and characterize sperm subpopulations in cryopreserved semen of Senepol bulls after washing process for in vitro fertilization (IVF); 2) generate a statistical model to estimate IVEP based on the sperm subpopulations and other sperm attributes analyzed, using multivariate statistical analysis and 3) apply artificial intelligence, through the use of artificial neural networks (ANNs) in order to improve the estimate of IVEP. Retrospective data from 386 IVEP routines were obtained from the records belonging to the enterprise In Vitro Brasil and embryonic production was categorized as high, medium and low. After, 38 samples of cryopreserved semen from Senepol bulls, used in IVEP routines, were acquired from the enterprise Senepol 3G for evaluation. After thawed, all samples were evaluated for sperm morphology and then subjected to a washing process that is performed before IVF. After washing, all samples were evaluated by the CASA system to obtain the general kinetics of the samples and the individual kinetics of the sperm. In addition, flow cytometry was evaluated for the integrity of the plasma and acrosomal membranes, mitochondrial potential, oxidative status and chromatin resistance. After multivariate analyzes of principal components and grouping, three sperm subpopulations were identified: SBP1 (fast and progressive motility), SBP2 (hyperactived motility) and SBP3 (slow and non-progressive motility). With the logistic regression analysis, it was found that IVEP suffers the effect of SBP1 and SBP2 and a model with these variables was generated to estimate the categories of embryonic production. With the analysis of ANNs, models were generated to estimate IVEP with 18, eight and six predictor variables, and the simplest model included the three sperm subpopulations and the variables plasma and acrosomal membranes integrity, high mitochondrial potential and total defects such as predictors.
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Palavras-chave
Bovino, Espermatozoides, Fertilização, Movimento, Inteligência Artificial