Porcine sperm binding to oviduct cells and glycans as supplements to traditional laboratory semen analysis.
Porcine sperm binding to oviduct cells and glycans as supplements to traditional laboratory semen analysis.
复制标题
猪精子与输卵管细胞和聚糖结合，作为传统实验室精液分析的补充。
DOI：
10.1093/jas/sky372
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发表时间：
2018
影响因子：
3.3
通讯作者：
Miller,DavidJ
中科院分区：
文献类型：
--
作者：
Winters,RebeccaA;Hamilton,DanielN;Bhatnagar,AdrienneS;Fitzgerald,Robert;Bovin,Nicolai;Miller,DavidJ
准确的精液评估对于保持高繁殖效率是必要的，但很难实现。目的是确定结合输卵管细胞或输卵管聚糖的能力是否是传统精液分析的有用补充。测量与特定可溶性聚糖的结合比评估与输卵管细胞聚集体的结合更省力，并且更适合常规使用。先前的研究表明，精子与输卵管细胞结合可以改善生育能力预测，这可能是通过估计精子形成输卵管储库的能力来实现的。测试了以高亲和力和特异性结合公猪精子的两个输卵管聚糖基序，即双触角 6-唾液酸化 N-乙酰基乳糖胺 (bi-SiaLN) 和 LewisX三糖 (LeX)。 30 头公猪的精液连夜运送用于实验室分析和授精以确定生育力（n = 3 个重复）。输卵管细胞结合和传统精子分析（包括运动性和形态学）已完成。此外，还测量了与可溶性荧光素聚糖 bi-SiaLN、硫酸化 LeX(suLeX) 和对照乳糖胺二糖 (LacNAc) 的结合。授精在中西部的 15 个农场（每头公猪超过 50 次交配）进行，并使用了所有交配的产仔数据。使用 SAS 9.4 中的 MIXED 程序，对妊娠率 (PR) 和产仔数 (LS) 进行调整，以考虑不同的农场、服务数量、授精剂量数量和母猪胎次。生成由 PR × LS 组成的生育力指数 (FI)，以估计公猪的总体生育力。最后，使用 GLMSELECT 过程来选择对 PR、LS 和 FI 有显着影响的变量。使用 REG 程序进一步分析构建的预测模型，并解释 PR、LS 和 FI 变异的 58% 或更多 [PR (P< 0.001，r2= 0.60)、LS (P< 0.001，r2= 0.58) 和 FI (P< 0.001，r2= 0.63)]。 PR 的最终模型包括输卵管细胞结合以及公猪年龄、远端液滴百分比、头部形态、尾部形态、跳动/交叉频率和曲线速度。 LS 的最终模型包括公猪年龄、远端液滴百分比、尾部形态和整体形态。最后，FI 模型包括公猪年龄、远端液滴百分比、头部形态、尾部形态、曲线速度和每次射精的精液量。尽管与完整输卵管细胞的结合作为预测 PR 的手段具有影响力，但与特定可溶性输卵管聚糖的结合并不是对传统精液分析的有用补充。
Accurate semen evaluation is necessary to maintain high reproductive efficiency but difficult to accomplish. The objective was to determine if the ability to bind oviduct cells or oviduct glycans are useful supplements to traditional semen analyses. Measuring binding to specific soluble glycans is less laborious than assessing binding to oviduct cell aggregates and more suitable for routine use. Previous work has shown that sperm binding to oviduct cells improves fertility prediction, possibly by estimating the ability of sperm to form an oviduct reservoir. The two oviduct glycan motifs, biantennary 6-sialylatedN-acetyllactosamine (bi-SiaLN) and LewisXtrisaccharide (LeX), that bind boar spermatozoa with high affinity and specificity were tested. Semen from 30 boars was shipped overnight for laboratory analysis and for inseminations to determine fertility (n= 3 replicates). Oviduct cell binding and traditional sperm analyses including motility and morphology were completed. Additionally, binding to soluble fluoresceinated glycans bi-SiaLN, sulfated LeX(suLeX), and the control lactosamine disaccharide (LacNAc) was measured. Inseminations were at 15 farms (>50 matings per boar) in the Midwest and farrowing data from all matings were used. Pregnancy rate (PR) and litter size (LS) were adjusted to account for different farms, number of services, number of doses inseminated, and sow parity, using the MIXED procedure in SAS 9.4. A fertility index (FI) was generated, consisting of PR × LS, to estimate boar overall fertility. Finally, the GLMSELECT procedure was used to select variables having a significant impact on PR, LS, and FI. The predictive models constructed were further analyzed using the REG procedure and accounted for 58% or more of the variation in PR, LS, and FI [PR (P< 0.001,r2= 0.60), LS (P< 0.001,r2= 0.58), and FI (P< 0.001,r2= 0.63)]. The final model for PR includes oviduct cell binding as well as boar age, % distal droplets, head morphology, tail morphology, beat/cross frequency, and curvilinear velocity. The final model for LS includes boar age, % distal droplets, tail morphology, and overall morphology. Finally, the FI model included boar age, % distal droplets, head morphology, tail morphology, curvilinear velocity, and semen volume per ejaculate. Although binding to intact oviduct cells was impactful as a means to predict PR, binding to specific soluble oviduct glycans was not a useful supplement to traditional semen analysis.