PSII-12 Comparison of fine needle aspiration and tissue sections to determine Sertoli and germ cell counts in prepubertal beef bulls

Abstract

Abstract Daily sperm production in bulls is determined by the size of the testicular Sertoli cell (SC) population established before puberty. Fine needle aspiration (FNA) is currently used as a diagnostic tool, but its value to determine SC and germ cell (GC) counts remains unexplored. The objectives were to compare three sampling techniques [(smears produced via 22G fine needle aspiration (SMR) vs. tissue sections collected via 14G aspiration (FNS) vs. conventional tissue sections (HIS)] and two stains [immunohistochemistry with GATA4 (IHC) and HE] to determine SC density in prepubertal bulls. Fourteen age-matched Angus bulls were surgically castrated. Testicular parenchyma samples and smears were stained using anti-GATA4 as a specific SC marker and HE. For stain comparison, mirrored tissue cuts were produced allowing cell counts of complementary seminiferous tubule (ST) cross sections. All data were analyzed using Pearson’s product moment correlations and linear regression. Testicular weights were correlated with IHC SC density (P = 0.018). High correlations existed for SC and GC counts done on ST cross sections using IHC (P < .0001) and HE (P < .0001). Within HIS and FNS, high correlations (r = 0.955; P ≤ 0.0001) existed between SC and automated GATA4+ cell densities. However, when comparing IHC SC density across techniques, no significant correlations (P ≤ 0.587) existed. The high correlation observed between SC counts done on mirrored ST cross sections for HE and IHC underlines the value of GATA4 as a specific SC marker in prepubertal bulls. Furthermore, the high correlation established between SC and GATA4+ cell densities within IHC HIS and FNS collection methods infers SC density determination can be automated. However, lack of correlation for SC density among techniques indicates that aspiration and conventional methods lead to different results. Research supported by North Dakota EPSCoR Doctoral Dissertation Assistantship (DDA) program.