Extracellular vesicles (EVs) are gaining recognition for their essential role in enhancing gamete quality and improving outcomes in assisted reproductive technologies. These nanosized particles, released by cells, carry proteins, lipids, and RNAs, facilitating critical cell communication and offering the potential to enhance gamete maturation and improve fertilization rates. Most research on males has concentrated on seminal plasma, a complex fluid produced by the testes and accessory glands vital in modulating sperm fertility potential. The components of seminal plasma significantly affect sperm functionality, embryo survival, and placental development, making this a prominent area of interest in reproductive biology. The EVs within seminal plasma contribute to maintaining sperm membrane stability, enhancing motility, and promoting capacitation, which may influence the female reproductive tract following mating. In females, EVs have been identified in both the follicular and uterine environments, where effective embryo–maternal communication is crucial. The oviduct epithelium supports gamete transport and early embryonic development, with EVs found in oviductal fluid playing a key role in reproductive processes. These EVs support the embryo’s growth in the nutrient-rich uterine environment. These important studies underscore the significant role of EVs in transporting essential molecular compounds to gametes and embryos, leading to an enhanced understanding and potential manipulation of reproductive processes. This review aims to summarize the current research on the benefits of EVs in gamete manipulation and embryo development, highlighting their promising implications for reproductive health.

Sperm quality is essential to guarantee the success of assisted reproduction. However, selecting high-quality sperm and maintaining it during (cryo)preservation for high efficiency remains challenging in livestock reproduction. A comprehensive understanding of sperm biology allows for better assessment of sperm quality, which could replace conventional sperm analyses used today to predict fertility with low accuracy. Omics approaches have revealed numerous biomarkers associated with various sperm phenotypic traits such as quality, survival during storage, freezability, and fertility. At the same time, nanotechnology is emerging as a new biotechnology with high potential for use in preparing sperm intended to improve reproduction in livestock. The unique physicochemical properties of nanoparticles make them exciting tools for targeting (e.g., sperm damage and sexing) and non-targeting bioapplications. Recent advances in sperm biology have led to the discovery of numerous biomarkers, making it possible to target specific subpopulations of spermatozoa within the ejaculate. In this review, we explore potential biomarkers associated with sperm phenotypes and highlight the benefits of combining these biomarkers with nanoparticles to further improve sperm preparation and technology.

Artificial insemination (AI) plays a critical role in livestock reproduction, with semen quality being essential. In swine, AI primarily uses cool-stored semen adhering to industry standards assessed through routine analysis, yet fertility inconsistencies highlight the need for enhanced semen evaluation. Over 10-day storage at 17 °C, boar semen samples were analyzed for motility, morphology, sperm membrane integrity, apoptosis, and oxidative stress indicators. Additionally, machine learning tools were employed to explore the potential of Raman and near-infrared (NIR) spectroscopy in enhancing semen sample evaluation. Sperm motility and morphology gradually decreased during storage, with distinct groups categorized as “Good” or “Poor” survival semen according to motility on Day 7 of storage. Initially similar on Day 0 of semen collection, “Poor” samples revealed significantly lower total motility (21.69 ± 4.64% vs. 80.19 ± 1.42%), progressive motility (4.74 ± 1.71% vs. 39.73 ± 2.57%), and normal morphology (66.43 ± 2.60% vs. 87.91 ± 1.92%) than their “Good” counterparts by Day 7, using a computer-assisted sperm analyzer. Furthermore, “Poor” samples had higher levels of apoptotic cells, membrane damage, and intracellular reactive oxygen species on Day 0. Conversely, “Good” samples maintained higher total antioxidant capacity. Raman spectroscopy outperformed NIR, providing distinctive spectral profiles aligned with semen biochemical changes and enabling the prediction of semen survival during storage. Overall, the spectral profiles coupled with machine learning tools might assist in enhancing semen evaluation and prognosis.

In the swine industry, artificial insemination (AI) primarily uses chill-stored semen, making sperm preservation crucial for reproductive success. However, sperm quality declines at varying rates during chilled storage at 17 °C, distinguishing high-survival semen from low-survival semen. This study investigates the metabolomic profiles of boar sperm with different abilities to survive liquid storage. We analyzed sperm motility, kinematics, and morphology in freshly extended (Day 0) and 7-day stored AI semen doses. The AI semen doses were classified as high-motile (HM) or low-motile (LM) based on sperm motility after 7 days of storage (Day 7). Metabolomic data were collected in positive (ESI+) and negative (ESI−) ion modes using a Vanquish Flex UPLC coupled with a Q Extractive Plus. We consistently detected 442 metabolites (251 in ESI+, 167 in ESI−, and 24 in both) across samples and storage durations. In freshly extended and 7-day stored AI doses, we identified 42 and 56 differentially expressed metabolites (DEMs), respectively. A clustering analysis showed significant changes in DEMs between the HM and LM samples. These DEMs were mainly enriched in amino acid metabolism, the pentose phosphate pathway, glycerolipid metabolism, glyoxylate and dicarboxylate metabolism, terpenoid backbone biosynthesis, etc. In summary, this study highlights the metabolomic differences between semen doses with varying abilities to survive liquid storage. Glyceric acid and lysoPC(20:3) emerged as potential markers for sperm preservation.

High semen quality is vital for reproductive success in the swine industry; however, seasonal fluctuations often compromise this quality. The molecular mechanism underlying these seasonal effects on semen quality remains largely unclear. This study employed untargeted metabolomic profiling of boar seminal plasma (SP) to identify metabolites and metabolic pathways associated with semen quality during the summer and winter months. Semen samples were collected from mature Duroc boars at a commercial boar stud and classified as Passed or Failed based on motility and morphology. SP from five samples per group was analyzed using ultra-high-performance liquid chromatography–mass spectrometry (UHPLC-MS). In total, 373 metabolites were detected in positive ion mode and 478 in negative ion mode. Several differentially expressed metabolites (DEMs) were identified, including ergothioneine, indole-3-methyl acetate, and avocadyne in the summer, as well as LysoPC, dopamine, and betaine in the winter. These metabolites are associated with key sperm functions, including energy metabolism, antioxidant defense, and capacitation. KEGG pathway analysis indicated enrichment in starch and sucrose metabolism, pyrimidine metabolism, and amino acid metabolism across the seasons. Overall, the results reveal that SP metabolomic profiles vary with the season, thereby influencing semen quality. The identified metabolites may serve as potential biomarkers for assessing semen quality and enhancing reproductive efficiency in swine production.

Semen quality is a key determinant of reproductive performance in breeding boars, and emerging evidence suggests the seminal microbiome may influence sperm function. However, the composition of the seminal plasma microbiome and its relationship to sperm quality remain poorly characterized. This study aimed to investigate the microbial composition of boar seminal plasma and its association with sperm quality. Semen ejaculates collected from Duroc boars were analyzed and classified as Passed (≥70% normal morphology) or Failed (<70% normal morphology). Seminal plasma was isolated by centrifugation and analyzed using 16S/ITS rRNA gene sequencing. The dominant bacterial phyla were Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. The most abundant genera included Porphyromonas, Bacteroides, and Cladosporium. Only the Shannon diversity index was significantly higher in Failed samples for the bacterial microbiome (p = 0.038). Furthermore, correlation analysis showed a negative association between Tenericutes and sperm concentration (r = −0.90; p = 0.014). Linear discriminant analysis identified microbial biomarkers associated with sperm quality, including Rhodococcus, Sphingomonas, Lactobacillus, Streptococcus, and Empedobacter. The increased abundance of these genera in Failed samples suggests disruption of the normal seminal microbial community. In conclusion, boar seminal plasma harbors a distinct bacterial and fungal microbiome that is associated with sperm morphology.