Optimization of a Filter-Lysis Protocol to Purify Rat Testicular Homogenates for Automated Spermatid Counting

Department of Pathology and Laboratory Medicine, Brown University, Box G-E5, Providence, RI 02912. .
Journal of Andrology (Impact Factor: 2.47). 01/2012; 33(5):811-6. DOI: 10.2164/jandrol.111.015131
Source: PubMed


Quantifying testicular homogenization-resistant spermatid heads (HRSH) is a powerful indicator of spermatogenesis. These counts have traditionally been performed manually using a hemocytometer, but this method can be time consuming and biased. We aimed to develop a protocol to reduce debris for the application of automated counting, which would allow for efficient and unbiased quantification of rat HRSH. We developed a filter-lysis protocol that effectively removes debris from rat testicular homogenates. After filtering and lysing the homogenates, we found no statistical differences between manual (classic and filter-lysis) and automated (filter-lysis) counts using 1-way analysis of variance with Bonferroni's multiple comparison test. In addition, Pearson's correlation coefficients were calculated to compare the counting methods, and there was a strong correlation between the classic manual counts and the filter-lysis manual (r = 0.85, P = .002) and the filter-lysis automated (r = 0.89, P = .0005) counts. We also tested the utility of the automated method in a low-dose exposure model known to decrease HRSH. Adult Fischer 344 rats exposed to 0.33% 2,5-hexanedione in the drinking water for 12 weeks demonstrated decreased body (P = .02) and testes (P = .002) weights. In addition, there was a significant reduction in the number of HRSH per testis (P = .002) when compared to controls. A filterlysis protocol was optimized to purify rat testicular homogenates for automated HRSH counts. Automated counting systems yield unbiased data and can be applied to detect changes in the testis after low-dose toxicant exposure.


Available from: Linnea M Anderson, Sep 16, 2014
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    ABSTRACT: Current human reproductive risk assessment methods rely on semen and serum hormone analyses, which are not easily comparable to the histopathological endpoints and mating studies used in animal testing. Because of these limitations, there is a need to develop universal evaluations that reliably reflect male reproductive function. We hypothesized that toxicant-induced testicular injury can be detected in sperm using mRNA transcripts as indicators of insult. To test this, we exposed adult male Fischer 344 rats to low doses of model testicular toxicants and classically characterized the testicular injury while simultaneously evaluating sperm mRNA transcripts from the same animals. Overall, this study aimed to: 1) identify sperm transcripts altered after exposure to the model testicular toxicant, 2,5-hexanedione (HD) using microarrays; 2) expand on the HD-induced transcript changes in a comprehensive time course experiment using qRT-PCR arrays; and 3) test these injury indicators after exposure to another model testicular toxicant, carbendazim (CBZ). Microarray analysis of HD-treated adult Fischer 344 rats identified 128 altered sperm mRNA transcripts when compared to control using linear models of microarray analysis (q<0.05). All transcript alterations disappeared after 3 months of post-exposure recovery. In the time course experiment, time-dependent alterations were observed for 12 candidate transcripts selected from the microarray data based upon fold change and biological relevance, and 8 of these transcripts remained significantly altered after the 3-month recovery period (p<0.05). In the last experiment, 8 candidate transcripts changed after exposure to CBZ (p<0.05). The two testicular toxicants produced distinct molecular signatures with only 4 overlapping transcripts between them, each occurring in opposite directions. Overall, these results suggest that sperm mRNA transcripts are indicators of low dose toxicant-induced testicular injury in the rat.
    PLoS ONE 08/2012; 7(8):e44280. DOI:10.1371/journal.pone.0044280 · 3.23 Impact Factor