Morphometric analysis of sperm used for IVP by three different separation methods with spatial light interference microscopy

Rubessa, M.; Kandel, Mikhail E.; Schreiber, Sierra; Meyers, Sasha; Beck, D.; Popescu, Gabriel; Wheeler, Matthew B.

doi:10.1080/19396368.2019.1701139

Cited by 12 publications

(12 citation statements)

References 29 publications

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“…It is conceivable that our approach would be especially useful when selecting among seemingly healthy sperm, with no obvious defects. We note that the assay of these relatively small ratios is made possible by the high sensitivity of SLIM (57,58). Importantly, in this work, we presented a template for automating the annotation of a large number of cells.…”

Section: Discussionmentioning

confidence: 99%

Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure

Kandel

Rubessa

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

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The ability to evaluate sperm at the microscopic level, at high-throughput, would be useful for assisted reproductive technologies (ARTs), as it can allow specific selection of sperm cells for in vitro fertilization (IVF). The tradeoff between intrinsic imaging and external contrast agents is particularly acute in reproductive medicine. The use of fluorescence labels has enabled new cell-sorting strategies and given new insights into developmental biology. Nevertheless, using extrinsic contrast agents is often too invasive for routine clinical operation. Raising questions about cell viability, especially for single-cell selection, clinicians prefer intrinsic contrast in the form of phase-contrast, differential-interference contrast, or Hoffman modulation contrast. While such instruments are nondestructive, the resulting image suffers from a lack of specificity. In this work, we provide a template to circumvent the tradeoff between cell viability and specificity by combining high-sensitivity phase imaging with deep learning. In order to introduce specificity to label-free images, we trained a deep-convolutional neural network to perform semantic segmentation on quantitative phase maps. This approach, a form of phase imaging with computational specificity (PICS), allowed us to efficiently analyze thousands of sperm cells and identify correlations between dry-mass content and artificial-reproduction outcomes. Specifically, we found that the dry-mass content ratios between the head, midpiece, and tail of the cells can predict the percentages of success for zygote cleavage and embryo blastocyst formation.

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Section: Discussionmentioning

confidence: 99%

Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure

Kandel

Rubessa

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

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“…PCA statistics have been used to determine the seminal traits affecting bull fertility [48], the differentiating factors of bull fertility [49], the role of seminal plasma proteins in sperm motility of buffalo [50], morphometric analysis of sperm by different separation methods [51], changes in bull semen metabolome concerning cryopreservation and fertility [52], the cellular and functional parameters on the freezability of sperm [53], proteomic and lipidomic tolerance of stored boar spermatozoa to autologous seminal plasma [54], and spermatozoa quantitative proteomics of human normozoospermia and asthenozoospermia [55]. To the best of our knowledge, using PCA to determine the fertility of post-thawed extended semen has never been studied.…”

Section: )mentioning

confidence: 99%

Effect of insulin-like growth factor-1 complex of Simmental bull seminal plasma on post-thawed Kacang buck semen fertility

et al. 2021

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Background and Aim: Kacang buck sperm is cryosensitive due to the seminal plasma of semen itself. Meanwhile, bull seminal plasma contains the insulin-like growth factor-1 (IGF-1) complex, which is cryoprotective. The addition of the crude protein of Simmental bull seminal plasma increased the quality of post-thawed semen of Kacang buck. The study was conducted to determine the effects of Simmental bull seminal plasma with IGF-1 on the fertility of post-thawed Kacang buck semen. Materials and Methods: Buck semen was diluted in the following skim milk-egg yolk extender preparations: Without the addition of Simmental bull seminal plasma IGF-1 complex protein (T0); with the addition of 12-μg Simmental bull seminal plasma IGF-1 complex protein (T1); and with the addition of 24-μg Simmental bull seminal plasma IGF-1 complex protein (T2). The extended semen was packed in 0.25-mL straws and frozen. Post-thawed semen fertility was evaluated based on the following variables: Sperm motility, viability, intact plasma membrane (IPM), malondialdehyde (MDA) levels, capacitation status, and acrosome reaction. The difference in each variable among the groups was evaluated using analysis of variance, followed by Tukey's honestly significant difference test, at a 95% level of significance. Meanwhile, principal component analysis (PCA) was used to identify the principal component of semen fertility among the seven parameters. Results: The T1 group showed the highest sperm motility, viability, IPM, and percentage of incapacitated sperm and the lowest MDA levels, percentage of capacitated sperm, and acrosome reaction. PCA revealed that sperm motility had a moderate to very robust correlation with other variables and is the most crucial parameter, accounting for 80.79% of all variables. Conclusion: The IGF-1 complex in Simmental bull seminal plasma was useful for increasing the fertility of post-thawed Kacang buck semen, and sperm motility was the principal component of semen fertility.

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“…Even more when variations in sperm morphometry have been widely associated with fertility (reviewed by Maroto‐Morales et al (2016) and differentiation processes among breeds (Soler et al, 2017) and species (Martinez & Garcia, 2020; Vicente‐Fiel et al, 2013). Although the mechanism underlying such relationship is still unveiled, it has been shown that sperm head shape could affect sperm motility in several livestock species (Love, 2011; Malo et al, 2006; Rubessa et al, 2020), thereby affecting their ability to reach and penetrate the egg (García‐Vázquez et al, 2016). On the contrary, several comparative and experimental studies have failed to address the link between sperm morphology and motility, providing contradictory results even within the same taxa (reviewed by Simmons and Fitzpatrick (2012).…”

Section: Introductionmentioning

confidence: 99%

Sperm morphometry is affected by increased inbreeding in the Retinta cattle breed: A molecular approach

Teran

Azcona

Ramón

et al. 2021

Molecular Reproduction Devel

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The effect of inbreeding depression on sperm motility is well documented, but its influence on sperm morphometry has been scarcely examined to date. Here, we combined the use of computer‐assisted sperm morphometry analysis (CASMA) with a SNP‐based genomic approach to determine and characterize the effect of inbreeding on the sperm shape of a highly inbred cattle population. We determined seven morphometric parameters on frozen‐thawed sperm samples of 57 Retinta bulls: length (L, µm), width (W, µm), area (A, µm2), perimeter (P, µm), ellipticity (ELI; L/W), elongation (L−W)/(L + W) and perimeter‐to‐area shape factor (p2a; P2/4 × π × A). The comparison of highly inbred (HI) and lowly inbreed (LI) individuals based on runs of homozygosity (ROH) inbreeding values (F ROH) showed no differences between groups. An additional two‐step unsupervised sperm subpopulation analysis based on morphometric parameters showed significant differences in the abundance of different sperm subpopulations between groups (p < 0.05). This analysis revealed that HI bulls harbored a higher percentage of narrow‐head sperm as opposed to the higher percentage of large‐ and round‐headed sperm detected in LI. A further genomic characterization revealed 23 regions differentially affected by inbreeding in both groups, detecting six genes (SPAG6, ARMC3, PARK7, VAMP3, DYNLRB2, and PHF7) previously related to different spermatogenesis‐associated processes.

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Morphometric analysis of sperm used for IVP by three different separation methods with spatial light interference microscopy

Cited by 12 publications

References 29 publications

Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure

Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure

Effect of insulin-like growth factor-1 complex of Simmental bull seminal plasma on post-thawed Kacang buck semen fertility

Sperm morphometry is affected by increased inbreeding in the Retinta cattle breed: A molecular approach

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