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32 pages, 5051 KiB  
Article
Alterations in Abundance and Compartmentalization of miRNAs in Blood Plasma Extracellular Vesicles and Extracellular Condensates during HIV/SIV Infection and Its Modulation by Antiretroviral Therapy (ART) and Delta-9-Tetrahydrocannabinol (Δ9-THC)
by Steven Kopcho, Marina McDew-White, Wasifa Naushad, Mahesh Mohan and Chioma M. Okeoma
Viruses 2023, 15(3), 623; https://doi.org/10.3390/v15030623 - 24 Feb 2023
Cited by 3 | Viewed by 3591
Abstract
In this follow-up study, we investigated the abundance and compartmentalization of blood plasma extracellular miRNA (exmiRNA) into lipid-based carriers—blood plasma extracellular vesicles (EVs) and non-lipid-based carriers—extracellular condensates (ECs) during SIV infection. We also assessed how combination antiretroviral therapy (cART), administered in conjunction with [...] Read more.
In this follow-up study, we investigated the abundance and compartmentalization of blood plasma extracellular miRNA (exmiRNA) into lipid-based carriers—blood plasma extracellular vesicles (EVs) and non-lipid-based carriers—extracellular condensates (ECs) during SIV infection. We also assessed how combination antiretroviral therapy (cART), administered in conjunction with phytocannabinoid delta-9-tetrahydrocannabinol (THC), altered the abundance and compartmentalization of exmiRNAs in the EVs and ECs of SIV-infected rhesus macaques (RMs). Unlike cellular miRNAs, exmiRNAs in blood plasma may serve as minimally invasive disease indicators because they are readily detected in stable forms. The stability of exmiRNAs in cell culture fluids and body fluids (urine, saliva, tears, cerebrospinal fluid (CSF), semen, blood) is based on their association with different carriers (lipoproteins, EVs, and ECs) that protect them from the activities of endogenous RNases. Here, we showed that in the blood plasma of uninfected control RMs, significantly less exmiRNAs were associated with EVs compared to the level (30% higher) associated with ECs, and that SIV infection altered the profile of EVs and ECs miRNAome (Manuscript 1). In people living with HIV (PLWH), host-encoded miRNAs regulate both host and viral gene expression, which may serve as indicators of disease or treatment biomarkers. The profile of miRNAs in blood plasma of PLWH (elite controllers versus viremic patients) are different, indicating that HIV may alter host miRNAome. However, there are no studies assessing the effect of cART or other substances used by PLWH, such as THC, on the abundance of exmiRNA and their association with EVs and ECs. Moreover, longitudinal exmiRNA profiles following SIV infection, treatment with THC, cART, or THC+cART remains unclear. Here, we serially analyzed miRNAs associated with blood plasma derived EVs and ECs. Methods: Paired EVs and ECs were separated from EDTA blood plasma of male Indian rhesus macaques (RMs) in five treatment groups, including VEH/SIV, VEH/SIV/cART, THC/SIV, THC/SIV/cART, or THC alone. Separation of EVs and ECs was achieved with the unparalleled nano-particle purification tool ─PPLC, a state-of-the-art, innovative technology equipped with gradient agarose bead sizes and a fast fraction collector that allows high resolution separation and retrieval of preparative quantities of sub-populations of extracellular structures. Global miRNA profiles of the paired EVs and ECs were determined with RealSeq Biosciences (Santa Cruz, CA) custom sequencing platform by conducting small RNA (sRNA)-seq. The sRNA-seq data were analyzed using various bioinformatic tools. Validation of key exmiRNA was performed using specific TaqMan microRNA stem-loop RT-qPCR assays. Results: We investigated the effect of cART, THC, or both cART and THC together on the abundance and compartmentalization of blood plasma exmiRNA in EVs and ECs in SIV-infected RMs. As shown in Manuscript 1 of this series, were in uninfected RMs, ~30% of exmiRNAs were associated with ECs, we confirmed in this follow up manuscript that exmiRNAs were present in both lipid-based carriers—EVs and non-lipid-based carriers—ECs, with 29.5 to 35.6% and 64.2 to 70.5 % being associated with EVs and ECs, respectively. Remarkably, the different treatments (cART, THC) have distinct effects on the enrichment and compartmentalization pattern of exmiRNAs. In the VEH/SIV/cART group, 12 EV-associated and 15 EC-associated miRNAs were significantly downregulated. EV-associated miR-206, a muscle-specific miRNA that is present in blood, was higher in the VEH/SIV/ART compared to the VEH/SIV group. ExmiR-139-5p that was implicated in endocrine resistance, focal adhesion, lipid and atherosclerosis, apoptosis, and breast cancer by miRNA-target enrichment analysis was significantly lower in VEH/SIV/cART compared to VEH/SIV, irrespective of the compartment. With respect to THC treatment, 5 EV-associated and 21 EC-associated miRNAs were significantly lower in the VEH/THC/SIV. EV-associated miR-99a-5p was higher in VEH/THC/SIV compared to VEH/SIV, while miR-335-5p counts were significantly lower in both EVs and ECs of THC/SIV compared to VEH/SIV. EVs from SIV/cART/THC combined treatment group have significant increases in the count of eight (miR-186-5p, miR-382-5p, miR-139-5p and miR-652, miR-10a-5p, miR-657, miR-140-5p, miR-29c-3p) miRNAs, all of which were lower in VEH/SIV/cART group. Analysis of miRNA-target enrichment showed that this set of eight miRNAs were implicated in endocrine resistance, focal adhesions, lipid and atherosclerosis, apoptosis, and breast cancer as well as cocaine and amphetamine addiction. In ECs and EVs, combined THC and cART treatment significantly increased miR-139-5p counts compared to VEH/SIV group. Significant alterations in these host miRNAs in both EVs and ECs in the untreated and treated (cART, THC, or both) RMs indicate the persistence of host responses to infection or treatments, and this is despite cART suppression of viral load and THC suppression of inflammation. To gain further insight into the pattern of miRNA alterations in EVs and ECs and to assess potential cause-and-effect relationships, we performed longitudinal miRNA profile analysis, measured in terms of months (1 and 5) post-infection (MPI). We uncovered miRNA signatures associated with THC or cART treatment of SIV-infected macaques in both EVs and ECs. While the number of miRNAs was significantly higher in ECs relative to EVs for all groups (VEH/SIV, SIV/cART, THC/SIV, THC/SIV/cART, and THC) longitudinally from 1 MPI to 5 MPI, treatment with cART and THC have longitudinal effects on the abundance and compartmentalization pattern of exmiRNAs in the two carriers. As shown in Manuscript 1 where SIV infection led to longitudinal suppression of EV-associated miRNA-128-3p, administration of cART to SIV-infected RMs did not increase miR-128-3p but resulted in longitudinal increases in six EV-associated miRNAs (miR-484, miR-107, miR-206, miR-184, miR-1260b, miR-6132). Furthermore, administration of cART to THC treated SIV-infected RMs resulted in a longitudinal decrease in three EV-associated miRNAs (miR-342-3p, miR-100-5p, miR181b-5p) and a longitudinal increase in three EC-associated miRNAs (miR-676-3p, miR-574-3p, miR-505-5p). The longitudinally altered miRNAs in SIV-infected RMs may indicate disease progression, while in the cART Group and the THC Group, the longitudinally altered miRNAs may serve as biomarkers of response to treatment. Conclusions: This paired EVs and ECs miRNAome analyses provided a comprehensive cross-sectional and longitudinal summary of the host exmiRNA responses to SIV infection and the impact of THC, cART, or THC and cART together on the miRNAome during SIV infection. Overall, our data point to previously unrecognized alterations in the exmiRNA profile in blood plasma following SIV infection. Our data also indicate that cART and THC treatment independently and in combination may alter both the abundance and the compartmentalization of several exmiRNA related to various disease and biological processes. Full article
(This article belongs to the Special Issue Viruses and Extracellular Vesicles 2023)
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Figure 1

Figure 1
<p>Study workflow for isolation and characterization of blood plasma derived EVs and ECs. (<b>A</b>) Description of experimental model. (<b>B</b>) Methodological workflow for isolation, and characterization of EVs and ECs. (<b>C</b>) Pie chart showing percent detectable miRNAs in the EVs and ECs for each treatment group. (<b>D</b>) The number of detectable miRNAs for the EVs and ECs at the Pre, 1 MPI and 5 MPI time points for VEH/SIV, VEH/SIV/ART, THC/SIV, THC/SIV/ART, and THC/no SIV treatment groups. (<b>E</b>) The number of detectable miRNAs for the EVs and ECs at 1 MPI (left) and 5 MPI (right) for VEH/SIV, VEH/SIV/ART, THC/SIV, THC/SIV/ART, and THC/no SIV treatment groups. To be included, miRNA count needed to be ≥1 for n = 3 RMs. Binary students’ t tests (Welch’s correction) were used to determine significant differences between EVs and ECs for each of the time points in each group. *** <span class="html-italic">p</span> &lt; 0.005, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05, and ns = non-significant.</p>
Full article ">Figure 2
<p>Repertoires of EV− and EC − associated miRNA following SIV infection and treatment with cART and THC. (<b>A</b>) Venn diagram comparing total detectable miRNAs for EVs and ECs at 1 MPI for VEH/SIV, VEH/SIV/ART, THC /SIV, THC/SIV /ART, and THC/no SIV treatment Groups. (<b>B</b>) PCA analysis of the common EVs and ECs miRNAs from the Venn diagrams (indicated by black square) at 1 MPI for the VEH/SIV, VEH/SIV/ART, THC/SIV, THC/SIV/ART, and THC/no SIV treatment groups. Unit variance scaling is applied to rows; SVD with imputation is used to calculate principal components. X and Y axis show principal component 1 and principal component 2. n = 3 RMs per treatment group. (<b>C</b>) Hierarchical clustering heatmap of the common EVs and ECs miRNAs from the Venn diagrams (indicated by black square) at 1 MPI for the VEH/SIV, VEH/SIV/ART, THC/SIV, THC/SIV/ART, and THC/no SIV treatment groups. Rows are centered; unit variance scaling is applied to rows. Both rows and columns are clustered using correlation distance and average linkage. N = 3 RMs per treatment group. (<b>D</b>) Venn diagram comparing total detectable miRNAs for EVs and ECs at 5 MPI for VEH/SIV, VEH/SIV/ART, THC/SIV, THC/SIV/ART, and THC/no SIV treatment groups. (<b>E</b>) PCA analysis of the common EV and associated miRNAs from the Venn diagrams (indicated by black square) at 5 MPI for the VEH/SIV, VEH/SIV/ART, THC/SIV, THC/SIV/ART, and THC/no SIV treatment groups. Unit variance scaling is applied to rows; SVD with imputation is used to calculate principal components. X and Y axis show principal component 1 and principal component 2. n = 3 RMs per treatment group. (<b>F</b>) Hierarchical clustering heatmap of the common EV and EC miRNAs from the Venn diagrams (indicated by black square) at 5 MPI for the VEH/SIV, VEH/SIV/ART, THC/SIV, THC/SIV/ART, and THC/no SIV treatment groups. Rows are centered; unit variance scaling is applied to rows. Both rows and columns are clustered using correlation distance and average linkage. n = 3 RMs per treatment group.</p>
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<p>Varying miRNA abundance in EVs and ECs in response to SIV infection and cART. (<b>A</b>) Volcano plot showing down-(blue) regulated and up-(red) regulated miRNAs in VEH/SIV/ART EVs relative to VEH/SIV EVs at 1 MPI (left) and 5 MPI (right) as shown by black arrows. Red circle indicates miRNAs (miR-378d, miR-206) suppressed by SIV infection in Figs. 5C, 5E of Manuscript 1. (<b>B</b>) Volcano plot showing down-(blue) regulated miRNAs in SIV/ART ECs relative to SIV ECs at 1 MPI (left) and 5 MPI (right). Black arrows indicate miRNAs shown to be significantly downregulated at 1 MPI and 5 MPI. (<b>C</b>) miRNA-target enrichment analysis showing top target genes by # of interactions for miR-206 and miR-378d. (<b>D</b>) Visualization of miRNA-target interaction network for miR-206 and miR-378d. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>E</b>) Dot plot of functional enrichment analysis for target genes of miR-206 and miR-378d. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated to that category. (<b>F</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for the 5 EC-associated miRNAs significantly downregulated at 1 MPI and 5 MPI; miR-299-3p, miR-324-5p, miR-4446-3p, miR-299-3p, and miR-671-5p. (<b>G</b>) Visualization of miRNA-target interaction network for miR-299-3p, miR-324-5p, miR-4446-3p, miR-299-3p, and miR-671-5p. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>H</b>) Dot plot of functional enrichment analysis for target genes of miR-299-3p, miR-324-5p, miR-4446-3p, miR-299-3p, and miR-671-5p. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated with that category). (<b>I</b>) Venn diagram comparing significantly modulated miRNAs in EVs and ECs at 1 MPI and 5 MPI. Red circle indicates miRNA (miR-139-5p) that was found to be significantly downregulated at 5 MPI in both EVs and ECs. (<b>J</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for miR-139-5p. (<b>K</b>) Visualization of miRNA-target interaction network for miR-139-5p. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>L</b>) Dot plot of functional enrichment analysis for miR-139-5p. Color of dots represent adjusted p-values (FDR) and size of dots represent gene ratio (number of miRNA targets found enriched in each category/number of total genes associated to that category).</p>
Full article ">Figure 4
<p>Alterations in miRNA profile of THC-treated SIV-infected cART-naive RMs. (<b>A</b>) Volcano plot showing down-(blue) regulated and up-(red) regulated miRNAs in THC/SV EVs relative to VEH/SIV EVs at 1 MPI (left) and 5 MPI (right). Red circle indicates miRNAs suppressed by SIV infection miR-99a-5p. (<b>B</b>) Volcano plot showing down-(blue) regulated and miRNAs in THC/SIV ECs relative to SIV ECs at 1 MPI left) and 5 MPI (right). Black arrows indicate miRNAs shown to be significantly downregulated at both MPI and 5 MPI. (<b>C</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for miR-99a-5p. (<b>D</b>) Visualization of miRNA-target interaction network for miR-9a-5p. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>E</b>) Dot plot of functional enrichment analysis for target genes of miR-99a-5p. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated to that category. (<b>F</b>) miRNAtarget enrichment analysis showing top target genes by number of interactions for the EC-associated miRNA (miR-5-3p) significantly downregulated at 1 MPI and 5 MPI. (<b>G</b>) Visualization of miRNA-target interaction network for miR-95-3p. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>H</b>) Dot plot of functional enrichment analysis for target genes of miR-95-3p. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category number of total genes associated with that category. (<b>I</b>) Venn diagram comparing significantly modulated miRNAs in the EVs and ECs at MPI and 5 MPI. Red circle indicates miRNA (miR-335-5p) that was found to be significantly downregulated at 5 MPI in both EVs and ECs. (<b>J</b>) Visualization of miRNAtarget interaction network for miR-335-5p. (<b>K</b>) Dot plot of functional enrichment analysis for miR-335-5p Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category number of total genes associated to that category.</p>
Full article ">Figure 5
<p>Alterations in miRNA profile of THC-treated SIV-infected cART-treated RMs. (<b>A</b>) Volcano plot showing down-(blue) regulated and up-(red) regulated miRNAs in THC/SIV/ART EVs relative to VEH/SIV/ART EVs at 1 MPI (left) and 5 MPI (right). Red circle indicates miRNAs (miR-186-5p, miR-382-5p, miR-139-5p, and miR-652) suppressed by ART treatment of SIV-infected macaques. (<b>B</b>) Volcano plot showing down-(blue) regulated and miRNAs in THC/SIV/ART ECs relative to VEH/SIV/ART ECs at 1 MPI (left) and 5 MPI (right). (<b>C</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for miR-186-5p, miR-382-5p, miR-139-5p. (<b>D</b>) Visualization of miRNA-target interaction network for miR-574, miR-374b-5p and miRA-139-5p. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>E</b>) Dot plot of functional enrichment analysis for target genes of miR-186-5p, miR-382-5p, miR-139-5p. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated to that category. (<b>F</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for miR-139-5p and miR-374b-5p. (<b>G</b>) Visualization of miRNA-target interaction network for miR-139-5p and miR-374b-5p. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>H</b>) Dot plot of functional enrichment analysis for target genes of miR-139-5p and miR-374b-5p. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated to that category. (<b>I</b>) Venn diagram comparing significantly modulated miRNAs in EVs and ECs at 1 MPI and 5 MPI. Red circle indicates miR-139-5p that was significantly downregulated at 5 MPI in both EVs and ECs.</p>
Full article ">Figure 6
<p>Alterations in miRNA profile of THC-treated, SIV-infected, cART-treated RMs. (<b>A</b>) Volcano plot showing down-(blue) regulated and up-(red) regulated miRNAs in THC/SIV/ART EVs relative to THC/SIV EVs at 1 MPI (left) and 5 MPI (right). (<b>B</b>) Volcano plot showing down-(blue) regulated and miRNAs in THC/SIV/ART ECs relative to THC/SIV ECs at 1 MPI (left) and 5 MPI (right). (<b>C</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for the 13 significantly modulated EV-associated miRNAs (miR-130b-3p, miR-654-3p, miR-28-5p, miR-95-3p, miR-144, miR-1260b, miR-24-3p, miR-206, miR-31-5p, miR-657, miR-139-5p, miR-638, miR-652) at 1 MPI and 5 MPI. (<b>D</b>) Visualization of miRNA-target interaction network for the 13 significantly modulated EV-associated miRNAs. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>E</b>) Dot plot of functional enrichment analysis for the 13 significantly modulated EV miRNAs. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated to that category. (<b>F</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for the 7 EC-associated miRNA significantly modulated at 1 MPI and 5 MPI. (<b>G</b>) Visualization of miRNA-target interaction network for the 7 EC-associated miRNA significantly modulated at 1 MPI and 5 MPI. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>H</b>) Dot plot of functional enrichment analysis for target genes of the 7 EC-associated miRNA significantly modulated at 1 MPI and 5 MPI. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated to that category.</p>
Full article ">Figure 7
<p>Identification of differentially and longitudinally altered EV − and EC − associated miRNAs of SIV-infected cART and/or THC treated RMs: (<b>A</b>) Volcano plot showing down-(blue) regulated and up-(red) regulated miRNAs in SIV/ART EVs at 1 MPI (left) and at 5 MPI (right). Black arrows indicate longitudinally upregulated miRNAs. (<b>B</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for the longitudinally upregulated EV-associated miRNAs in panel A. (<b>C</b>) Visualization of miRNA-target interaction network for the longitudinally upregulated EV-associated miRNAs in panel A. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>D</b>) Dot plot of functional enrichment analysis for the longitudinally upregulated EV-associated miRNAs in panel A. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated to that category). (<b>E</b>) Volcano plot showing down-(blue) regulated and up-(red) regulated miRNAs in THC/SIV/ART EVs at 1 MPI (left) and at 5 MPI (right). Black arrows indicate longitudinally THC/ART-downregulated miRNAs. (<b>F</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for the longitudinally downregulated EV-associated miRNAs in panel E. (<b>G</b>) Visualization of miRNA-target interaction network for the longitudinally downregulated EV-associated miRNAs in panel E. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>H</b>) Dot plot of functional enrichment analysis for the longitudinally downregulated EV-associated miRNAs in panel E. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated to that category. (<b>I</b>) Volcano plot showing down-(blue) regulated and up-(red) regulated miRNAs in THC/SIV/ART ECs at 1 MPI (left) and at 5 MPI (right). Black arrows indicate longitudinally THC/ART-downregulated miRNAs. (<b>J</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for the longitudinally downregulated EC-associated miRNAs in panel I. (<b>K</b>) Visualization of miRNA-target interaction network for the longitudinally downregulated EC-associated miRNAs in panel I. The blue circles represent the miRNAs, while the target genes are represented by the yellow circles. Pathways are represented by blue lines. (<b>L</b>) Dot plot of functional enrichment analysis for the longitudinally downregulated EC-associated miRNAs in panel I. Color of dots represent adjusted p-values (FDR) and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated to that category.</p>
Full article ">Figure 8
<p>Circulating blood plasma miRNAs and their association with EVs and ECs in SIV-infected rhesus macaques under various treatments—THC, ART, THC, and ART. Parts of this illustration was created with BioRender.com.</p>
Full article ">
28 pages, 4094 KiB  
Article
SIV Infection Regulates Compartmentalization of Circulating Blood Plasma miRNAs within Extracellular Vesicles (EVs) and Extracellular Condensates (ECs) and Decreases EV-Associated miRNA-128
by Steven Kopcho, Marina McDew-White, Wasifa Naushad, Mahesh Mohan and Chioma M. Okeoma
Viruses 2023, 15(3), 622; https://doi.org/10.3390/v15030622 - 24 Feb 2023
Cited by 2 | Viewed by 4141
Abstract
Background: This is Manuscript 1 of a two-part Manuscript of the same series. Here, we present findings from our first set of studies on the abundance and compartmentalization of blood plasma extracellular microRNAs (exmiRNAs) into extracellular particles, including blood plasma extracellular vesicles [...] Read more.
Background: This is Manuscript 1 of a two-part Manuscript of the same series. Here, we present findings from our first set of studies on the abundance and compartmentalization of blood plasma extracellular microRNAs (exmiRNAs) into extracellular particles, including blood plasma extracellular vesicles (EVs) and extracellular condensates (ECs) in the setting of untreated HIV/SIV infection. The goals of the study presented in this Manuscript 1 are to (i) assess the abundance and compartmentalization of exmiRNAs in EVs versus ECs in the healthy uninfected state, and (ii) evaluate how SIV infection may affect exmiRNA abundance and compartmentalization in these particles. Considerable effort has been devoted to studying the epigenetic control of viral infection, particularly in understanding the role of exmiRNAs as key regulators of viral pathogenesis. MicroRNA (miRNAs) are small (~20–22 nts) non-coding RNAs that regulate cellular processes through targeted mRNA degradation and/or repression of protein translation. Originally associated with the cellular microenvironment, circulating miRNAs are now known to be present in various extracellular environments, including blood serum and plasma. While in circulation, miRNAs are protected from degradation by ribonucleases through their association with lipid and protein carriers, such as lipoproteins and other extracellular particles—EVs and ECs. Functionally, miRNAs play important roles in diverse biological processes and diseases (cell proliferation, differentiation, apoptosis, stress responses, inflammation, cardiovascular diseases, cancer, aging, neurological diseases, and HIV/SIV pathogenesis). While lipoproteins and EV-associated exmiRNAs have been characterized and linked to various disease processes, the association of exmiRNAs with ECs is yet to be made. Likewise, the effect of SIV infection on the abundance and compartmentalization of exmiRNAs within extracellular particles is unclear. Literature in the EV field has suggested that most circulating miRNAs may not be associated with EVs. However, a systematic analysis of the carriers of exmiRNAs has not been conducted due to the inefficient separation of EVs from other extracellular particles, including ECs. Methods: Paired EVs and ECs were separated from EDTA blood plasma of SIV-uninfected male Indian rhesus macaques (RMs, n = 15). Additionally, paired EVs and ECs were isolated from EDTA blood plasma of combination anti-retroviral therapy (cART) naïve SIV-infected (SIV+, n = 3) RMs at two time points (1- and 5-months post infection, 1 MPI and 5 MPI). Separation of EVs and ECs was achieved with PPLC, a state-of-the-art, innovative technology equipped with gradient agarose bead sizes and a fast fraction collector that allows high-resolution separation and retrieval of preparative quantities of sub-populations of extracellular particles. Global miRNA profiles of the paired EVs and ECs were determined with RealSeq Biosciences (Santa Cruz, CA) custom sequencing platform by conducting small RNA (sRNA)-seq. The sRNA-seq data were analyzed using various bioinformatic tools. Validation of key exmiRNAs was performed using specific TaqMan microRNA stem-loop RT-qPCR assays. Results: We showed that exmiRNAs in blood plasma are not restricted to any type of extracellular particles but are associated with lipid-based carriers—EVs and non-lipid-based carriers—ECs, with a significant (~30%) proportion of the exmiRNAs being associated with ECs. In the blood plasma of uninfected RMs, a total of 315 miRNAs were associated with EVs, while 410 miRNAs were associated with ECs. A comparison of detectable miRNAs within paired EVs and ECs revealed 19 and 114 common miRNAs, respectively, detected in all 15 RMs. Let-7a-5p, Let-7c-5p, miR-26a-5p, miR-191-5p, and let-7f-5p were among the top 5 detectable miRNAs associated with EVs in that order. In ECs, miR-16-5p, miR-451, miR-191-5p, miR-27a-3p, and miR-27b-3p, in that order, were the top detectable miRNAs in ECs. miRNA-target enrichment analysis of the top 10 detected common EV and EC miRNAs identified MYC and TNPO1 as top target genes, respectively. Functional enrichment analysis of top EV- and EC-associated miRNAs identified common and distinct gene-network signatures associated with various biological and disease processes. Top EV-associated miRNAs were implicated in cytokine–cytokine receptor interactions, Th17 cell differentiation, IL-17 signaling, inflammatory bowel disease, and glioma. On the other hand, top EC-associated miRNAs were implicated in lipid and atherosclerosis, Th1 and Th2 cell differentiation, Th17 cell differentiation, and glioma. Interestingly, infection of RMs with SIV revealed that the brain-enriched miR-128-3p was longitudinally and significantly downregulated in EVs, but not ECs. This SIV-mediated decrease in miR-128-3p counts was validated by specific TaqMan microRNA stem-loop RT-qPCR assay. Remarkably, the observed SIV-mediated decrease in miR-128-3p levels in EVs from RMs agrees with publicly available EV miRNAome data by Kaddour et al., 2021, which showed that miR-128-3p levels were significantly lower in semen-derived EVs from HIV-infected men who used or did not use cocaine compared to HIV-uninfected individuals. These findings confirmed our previously reported finding and suggested that miR-128 may be a target of HIV/SIV. Conclusions: In the present study, we used sRNA sequencing to provide a holistic understanding of the repertoire of circulating exmiRNAs and their association with extracellular particles, such as EVs and ECs. Our data also showed that SIV infection altered the profile of the miRNAome of EVs and revealed that miR-128-3p may be a potential target of HIV/SIV. The significant decrease in miR-128-3p in HIV-infected humans and in SIV-infected RMs may indicate disease progression. Our study has important implications for the development of biomarker approaches for various types of cancer, cardiovascular diseases, organ injury, and HIV based on the capture and analysis of circulating exmiRNAs. Full article
(This article belongs to the Special Issue Viruses and Extracellular Vesicles 2023)
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Graphical abstract

Graphical abstract
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<p>Study workflow, EV and EC isolation and characterization. (<b>A</b>) Description of experimental model; 15 male Indian Rhesus Macaques were randomly assigned to 5 groups of 3. Pre-infection and pre-treatment blood plasma samples were collected and processed. (<b>B</b>) Methodological workflow for isolation of EVs and ECs and their characterization. (<b>C</b>) Representative PPLC spectra of EVs and ECs. Blue box: indicates EV-containing fraction. Green box: indicates EC-containing fraction. (<b>D</b>) Representative negative-stain TEM images of purified EVs and ECs from pooled (<span class="html-italic">n</span> = 15) RMs. Blue arrows indicate gold-labeled CD9 on the surface of EVs. Green arrows indicate ECs. Scale bars: 200 nm for EVs and ECs (Top), 50 nm EVs (bottom), and 100 nm ECs (bottom). (<b>E</b>–<b>G</b>) Nanoparticle tracking analysis (NTA) measurements of different BEV properties, including (<b>E</b>) mean EV size, (<b>F</b>) mean EV concentration, (<b>G</b>) mean EV zeta-potential.</p>
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<p>Identification of common BEV and BEC miRNAs. (<b>A</b>) Number of miRNAs detected (miRNA distribution count ≥1) for each RM (<span class="html-italic">n</span> = 15), for both EVs and ECs. (<b>B</b>) Venn diagram comparing total detectable miRNAs for EVs and ECs (<span class="html-italic">n</span> = 15). To be included in the list, miRNA count needed to be ≥1 at least 1 RM. (<b>C</b>,<b>D</b>) Venn diagram showing common and unique miRNAs among the 5 groups for (<b>C</b>) EVs and (<b>D</b>) ECs. Dotted red circle indicates miRNAs detected in monkeys (<span class="html-italic">n</span> = 15) for EVs (19) and ECs (114). (<b>E</b>,<b>F</b>) Top 10 detected commonly expressed miRNAs as measured by miRNA distribution counts for (<b>E</b>) EVs and (<b>F</b>) ECs. Unpaired T-test with Welch’s correction was used to assess statistical differences between EVs and ECs in panel (<b>A</b>). Error bars represent S.E.M. ****, <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>The top 10 miRNAs identified in EVs and ECs regulate distinctive pathways. (<b>A</b>,<b>B</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for A) EV-associated miRNAs and (<b>B</b>) EC-associated miRNAs. The color of the bars represents adjusted <span class="html-italic">p</span>-values (FDR). (<b>C</b>,<b>D</b>) Visualization of miRNA-target interaction network for (<b>C</b>) EV-associated miRNAs and (<b>D</b>) EC-associated miRNAs. Blue circles indicate miRNAs, yellow circles indicate their target genes. (<b>E</b>,<b>F</b>) Dot plot of functional enrichment analysis for target genes of top 10 miRNAs resulting from miRNA-target enrichment analysis for (<b>E</b>) EV-associated miRNAs and (<b>F</b>) EC-associated miRNAs. Color of dots represents adjusted <span class="html-italic">p</span>-values (FDR), and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated with that category). (<b>G</b>) Venn diagram comparing differences and similarities in KEGG pathways of EV- and EC-associated miRNAs.</p>
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<p>Identification and pathway analysis of common and unique miRNAs associated with EVs and ECs. (<b>A</b>) Venn diagram showing common and unique miRNAs among the common EV and EC miRNAs (<span class="html-italic">n</span> = 15). (<b>B</b>) miRNA distribution counts of EV-associated unique miRNAs (1) for <span class="html-italic">n</span> = 15 RMs. (<b>C</b>) miRNA distribution counts of top 10 EC-associated miRNAs. (<b>D</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for the 1 unique EV-associated miRNA. (<b>E</b>) Visualization of miRNA-target interaction network for the 1 unique EV-associated miRNA. (<b>F</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for the top 10 unique EC-associated miRNAs. (<b>G</b>) Visualization of miRNA-target interaction network for the top 10 unique EC-associated miRNAs. (<b>H</b>) Dot plot of functional enrichment analysis for the top 10 unique EC-associated miRNAs. Color of dots represents adjusted <span class="html-italic">p</span>-values (FDR), and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated with that category). (<b>I</b>) PCA plot of the 18 (arrow from panel (<b>A</b>)) common EV and EC miRNAs. Unit variance scaling is applied to rows; SVD with imputation is used to calculate principal components. X and Y axis show principal component 1 and principal component 2, which explain 74.4% and 19.1% of the total variance, respectively. Predication ellipses are such that with a probability of 0.95, a new observation from the same group will fall inside the ellipse. <span class="html-italic">N</span> = 15 data points. (<b>J</b>) Hierarchical clustering heatmap of the 18 common EV and EC miRNAs. Rows are centered; unit variance scaling is applied to rows. Both rows and columns are clustered using correlation distance and average linkage. (<b>K</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for the 18 common EV- and EC-associated miRNAs. (<b>L</b>) Visualization of miRNA-target interaction network for 18 common EV- and EC-associated miRNAs. (<b>M</b>) Dot plot of functional enrichment analysis for target genes of 18 common EV- and EC-associated miRNAs. Color of dots represents adjusted <span class="html-italic">p</span>-values (FDR), and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated with that category.</p>
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<p>SIV infection of RMs longitudinally downregulates EV-associated miR-128-3p. (<b>A</b>) Schematic of SIV infection of RMs; 12 male Indian RMs were infected with SIV. One month post-infection (1 MPI), blood plasma was collected from <span class="html-italic">n</span> = 12 RMS. Five months post-infection (5 MPI), blood plasma was collected from <span class="html-italic">n</span> = 3 RMS. (<b>B</b>) Number of miRNAs detected (miRNA distribution count ≥ 1) for each RM, for both EVs and ECs. Pre (<span class="html-italic">n</span> = 15), SIV 1 MPI (<span class="html-italic">n</span> = 12), SIV 5 MPI (<span class="html-italic">n</span> = 3). (<b>C</b>–<b>F</b>) Volcano plots showing down-regulated (blue) and up-regulated (red) miRNAs in (<b>C</b>) EVs 1 MPI, (<b>D</b>) ECs 1 MPI, (<b>E</b>) EVs 5 MPI, and (<b>F</b>) BCs 5 MPI compared to healthy uninfected RMs (Pre). (<b>G</b>–<b>I</b>) miRNA-target enrichment analysis (<b>G</b>), visualization of miRNA-target interaction network (<b>H</b>), and dot plot of functional enrichment analysis (<b>I</b>) for the longitudinally downregulated EV-associated miRNAs (miR-206, miR-99a-5p, miR-128-3p). Color of dots in panel (<b>I</b>) represents adjusted <span class="html-italic">p</span>-values (FDR), and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated with that category. (<b>J</b>) TaqMan PCR validation using 128a-3p specific assays. Statistical differences were assessed by ordinary one-way ANOVA test with Tukey’s correction (<span class="html-italic">n</span> = 3). *, <span class="html-italic">p</span> &lt; 0.05. (<b>K</b>) miRNA-target enrichment analysis showing top target genes by number of interactions for miR-128-3p. (<b>L</b>) Visualization of miRNA-target interaction network for miR-128-3p. (<b>M</b>,<b>N</b>) Dot plots of functional enrichment analysis (<b>M</b>) KEGG and (<b>N</b>) disease Ontology for target genes of miR-128-3p. Color of dots represents adjusted <span class="html-italic">p</span>-values (FDR), and size of dots represents gene ratio (number of miRNA targets found enriched in each category/number of total genes associated with that category). Unpaired T-test with Welch’s correction was used to assess statistical differences between EVs and ECs in panels (<b>B</b>) and (<b>J</b>) (left). Error bars represent S.E.M. *, <span class="html-italic">p</span> &lt; 0.05; ****, <span class="html-italic">p</span> &lt; 0.0001; ns, not significant. In Panel J, Ordinary One-way ANOVA multiple comparison test (Tukey’s test) was used to assess statistical differences, with ns denoting non-significant.</p>
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<p>Circulating blood plasma miRNAs and their association with EVs and ECs in uninfected and SIV-infected rhesus macaques. Part of this illustration was created with BioRender.com.</p>
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9 pages, 501 KiB  
Review
MicroRNAs as Candidate Biomarkers for Alzheimer’s Disease
by Colin Kanach, Jan K. Blusztajn, Andre Fischer and Ivana Delalle
Non-Coding RNA 2021, 7(1), 8; https://doi.org/10.3390/ncrna7010008 - 1 Feb 2021
Cited by 17 | Viewed by 5367
Abstract
The neurological damage of Alzheimer’s disease (AD) is thought to be irreversible upon onset of dementia-like symptoms, as it takes years to decades for occult pathologic changes to become symptomatic. It is thus necessary to identify individuals at risk for the development of [...] Read more.
The neurological damage of Alzheimer’s disease (AD) is thought to be irreversible upon onset of dementia-like symptoms, as it takes years to decades for occult pathologic changes to become symptomatic. It is thus necessary to identify individuals at risk for the development of the disease before symptoms manifest in order to provide early intervention. Surrogate markers are critical for early disease detection, stratification of patients in clinical trials, prediction of disease progression, evaluation of response to treatment, and also insight into pathomechanisms. Here, we review the evidence for a number of microRNAs that may serve as biomarkers with possible mechanistic insights into the AD pathophysiologic processes, years before the clinical manifestation of the disease. Full article
(This article belongs to the Collection Feature Papers in Non-Coding RNA)
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<p>Proposed approach toward discovering and evaluating circulating miRNA biomarker candidates for prognosing and diagnosing AD-associated cognitive decline.</p>
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18 pages, 16345 KiB  
Article
Testosterone-Dependent miR-26a-5p and let-7g-5p Act as Signaling Mediators to Regulate Sperm Apoptosis via Targeting PTEN and PMAIP1
by Jideng Ma, Yu Fan, Jinwei Zhang, Siyuan Feng, Zihui Hu, Wanling Qiu, Keren Long, Long Jin, Qianzi Tang, Xun Wang, Qi Zhou, Yiren Gu, Weihang Xiao, Lingyan Liu, Xuewei Li and Mingzhou Li
Int. J. Mol. Sci. 2018, 19(4), 1233; https://doi.org/10.3390/ijms19041233 - 18 Apr 2018
Cited by 44 | Viewed by 6138
Abstract
Recent evidence suggests that testosterone deficiency can dramatically decrease the quality of sperm. MicroRNAs (miRNAs) are conserved mediators of post-transcriptional gene regulation in eukaryotes. However, the systemic regulation and function of miRNAs in sperm quality decline induced by testosterone deficiency has not been [...] Read more.
Recent evidence suggests that testosterone deficiency can dramatically decrease the quality of sperm. MicroRNAs (miRNAs) are conserved mediators of post-transcriptional gene regulation in eukaryotes. However, the systemic regulation and function of miRNAs in sperm quality decline induced by testosterone deficiency has not been investigated. Here, we found that the sperm apoptosis was significantly enhanced and the sperm motility was dramatically decreased in hemicastrated pigs. We then used small RNA sequencing to detect miRNA profiles of sperm from pigs with prepubertal hemicastration (HC) and compared them with control libraries. We identified 16 differentially expressed (DE) miRNAs between the sperm of prepubertal HC and control (CT) pigs. Functional enrichment analysis indicated that the target genes of these DE miRNAs were mainly enriched in apoptosis-related pathways including the p53, mitogen-activated protein kinase (MAPK), and mammalian target of rapamycin (mTOR) pathways. Furthermore, gain- and loss-of-function analyses demonstrated potential anti-apoptotic effects of the DE miRNAs miR-26a-5p and let-7g-5p on sperm cells. The luciferase reporter assay confirmed that PTEN and PMAIP1 are targets of miR-26a-5p and let-7g-5p, respectively. Spearman’s correlation analysis revealed significantly positive correlations between the sperm and its corresponding seminal plasma exosomes regarding the miRNA expression levels. In conclusion, testosterone deficiency-induced changes in the miRNA components of seminal plasma exosomes secreted by the genital tract may partially elucidate sperm miRNAome alterations, which are further responsible for the decline of sperm motility. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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Graphical abstract
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<p>Altered profile of biological parameters between prepubertal hemicastration and control pigs. The influences of prepubertal hemicastration on porcine (<b>A</b>) body weight, (<b>B</b>) body size, and (<b>C</b>) main organ indexes. Prepubertal hemicastration significantly affected the (<b>D</b>) serum testosterone level, (<b>E</b>) testis index, and (<b>F</b>) testis size. (<b>G</b>) Histological analysis of the testis of control and hemicastrated pigs. Bars = 200 μm; 100× magnification; hematoxylin-eosin staining. (<b>H</b>) Sperm density of experimental pigs. (<b>I</b>) Sperm motility rate (%) represents the percentage of sperm showing motility. (<b>J</b>) Three motility parameters, including the curvilinear velocity (VCL, μm/s), average path velocity (VAP, μm/s) and straight line velocity (VSL, μm/s), were assessed for both experimental pig groups. (<b>K</b>) Amplitude of lateral head displacement (ALH, μm) for both experimental pig groups. (<b>L</b>) The wobble (WOB, %) measures the oscillation of the actual trajectory of sperm cells. (<b>M</b>,<b>N</b>) Sperm apoptosis rates of control and hemicastrated pigs were evaluated by flow cytometry analysis. (<b>O</b>) Apoptotic bodies in testicular tissues of control and hemicastrated pigs, detected as strongly green fluorescent cells. Bars = 100 μm; 200× magnification. CT and HC represent the prepubertally hemicastrated Yorkshire boars and normal controls, respectively. All data are expressed as means ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Altered profile of biological parameters between prepubertal hemicastration and control pigs. The influences of prepubertal hemicastration on porcine (<b>A</b>) body weight, (<b>B</b>) body size, and (<b>C</b>) main organ indexes. Prepubertal hemicastration significantly affected the (<b>D</b>) serum testosterone level, (<b>E</b>) testis index, and (<b>F</b>) testis size. (<b>G</b>) Histological analysis of the testis of control and hemicastrated pigs. Bars = 200 μm; 100× magnification; hematoxylin-eosin staining. (<b>H</b>) Sperm density of experimental pigs. (<b>I</b>) Sperm motility rate (%) represents the percentage of sperm showing motility. (<b>J</b>) Three motility parameters, including the curvilinear velocity (VCL, μm/s), average path velocity (VAP, μm/s) and straight line velocity (VSL, μm/s), were assessed for both experimental pig groups. (<b>K</b>) Amplitude of lateral head displacement (ALH, μm) for both experimental pig groups. (<b>L</b>) The wobble (WOB, %) measures the oscillation of the actual trajectory of sperm cells. (<b>M</b>,<b>N</b>) Sperm apoptosis rates of control and hemicastrated pigs were evaluated by flow cytometry analysis. (<b>O</b>) Apoptotic bodies in testicular tissues of control and hemicastrated pigs, detected as strongly green fluorescent cells. Bars = 100 μm; 200× magnification. CT and HC represent the prepubertally hemicastrated Yorkshire boars and normal controls, respectively. All data are expressed as means ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>miRNA expression profiles of sperm cells in control and hemicastrated pigs. (<b>A</b>) The length distribution of identified miRNAs in all small RNA libraries. (<b>B</b>) Hierarchical clustering analysis for the expression of 206 known sperm miRNAs between control and hemicastrated pigs based on the Euclidean distance. Complete linkage hierarchic clustering was performed with the Euclidian distance measure. (<b>C</b>) Ranking analysis of the top 10 sperm miRNAs with the highest expression levels in control and hemicastrated pigs. The labels upper the bar represent the ranking of the top 10 miRNAs by expression, while the labels below the bar represent the accumulative % of the top 10 miRNAs in total read per million (RPM) of all expressed miRNAs. Seven miRNAs that are present in the top 10 position in both experimental groups are connected by lines. (<b>D</b>) Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of potential targets of the DE miRNAs. <span class="html-italic">p</span>-Values indicating the significance of enrichment were calculated by the Benjamini-corrected modified Fisher’s exact test. (<b>E</b>) Heat maps of the expression pattern of the DE sperm miRNA families and a cluster in control and hemicastrated groups. CT and HC represent prepubertally hemicastrated Yorkshire boars and controls, respectively.</p>
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<p>miRNA expression profiles of sperm cells in control and hemicastrated pigs. (<b>A</b>) The length distribution of identified miRNAs in all small RNA libraries. (<b>B</b>) Hierarchical clustering analysis for the expression of 206 known sperm miRNAs between control and hemicastrated pigs based on the Euclidean distance. Complete linkage hierarchic clustering was performed with the Euclidian distance measure. (<b>C</b>) Ranking analysis of the top 10 sperm miRNAs with the highest expression levels in control and hemicastrated pigs. The labels upper the bar represent the ranking of the top 10 miRNAs by expression, while the labels below the bar represent the accumulative % of the top 10 miRNAs in total read per million (RPM) of all expressed miRNAs. Seven miRNAs that are present in the top 10 position in both experimental groups are connected by lines. (<b>D</b>) Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of potential targets of the DE miRNAs. <span class="html-italic">p</span>-Values indicating the significance of enrichment were calculated by the Benjamini-corrected modified Fisher’s exact test. (<b>E</b>) Heat maps of the expression pattern of the DE sperm miRNA families and a cluster in control and hemicastrated groups. CT and HC represent prepubertally hemicastrated Yorkshire boars and controls, respectively.</p>
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<p>The miR-26a-5p-mediated regulation of sperm quality. (<b>A</b>) Relative expression levels of miR-26a-5p in control, mimic- and inhibitor-transfected sperm. (<b>B</b>) Effect of miR-26a-5p mimic and inhibitor on three velocity parameters of sperm cells, including curvilinear velocity (VCL, μm/s), average path velocity (VAP, μm/s) and straight line velocity (VSL, μm/s). (<b>C</b>) Effect of miR-26a-5p mimics and inhibitor on sperm motility rate (%). No significant changes were observed in (<b>D</b>) amplitude of lateral head displacement (ALH, μm), (<b>E</b>) sperm density (million/mL), (<b>F</b>) motility parameter wobble (WOB, %), or (<b>G</b>) linearity (LIN, %) and STR (%). (<b>H</b>) Effect of miR-26a-5p mimics and inhibitor on the expression levels of apoptosis-related genes. Con, control; Mimi, mimics; MC, mimic control; Inhi, inhibitor; IC, inhibitor control. CT and HC represent prepubertally hemicastrated Yorkshire boars and normal controls, respectively. Three independent experiments were performed in triplicate and all data are expressed as means ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Testosterone-dependent miRNAs exert a pro-viability function by inhibiting pro-apoptotic factors. (<b>A</b>) Potential binding sites predicted by TargetScan [<a href="#B40-ijms-19-01233" class="html-bibr">40</a>] and RNAhybrid [<a href="#B41-ijms-19-01233" class="html-bibr">41</a>] for miR-26a-5p and let-7g-5p in the 3′-UTR of <span class="html-italic">PTEN</span> and the 5′-UTR of <span class="html-italic">PMAIP1</span>, respectively, and the mutant <span class="html-italic">PTEN</span> 3′-UTR and <span class="html-italic">PMAIP1</span> 5′-UTR used in our study. A luciferase reporter assay was performed by co-transfecting luciferase reporter containing the 3′-UTR of <span class="html-italic">PTEN</span> and 5′-UTR of <span class="html-italic">PMAIP1</span> (wild-type (Wt) or mutant (Mut)) with the mimic or control of miR-26a-5p and let-7g-5p into PK15 cells. The red underlined bases highlighted the miRNA seed sequences and their corresponding target sites in the mRNA UTR sequences. Luciferase activity was determined 48 h after transfection for (<b>B</b>) miR-26a-5p and (<b>C</b>) let-7g-5p. MC, mimics control. Three independent experiments were performed in triplicate and all data are expressed as means ± SD. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>The comparison of miRNA data of sperm and seminal plasma exosomes. (<b>A</b>) Particle size distribution of CT-1 seminal plasma exosomes detected using atomic force microscopy. (<b>B</b>) Western blot analysis showing the enrichment of CD63 and CD81 and the absence of tubulin in CT-1 seminal plasma exosomes compared with sperm cell lysates. (<b>C</b>) The expression pattern of a sperm-specific marker, <span class="html-italic">PRM-1/2</span>, in sperm and seminal plasma exosomes. (<b>D</b>) Hierarchical clustering analysis for the expression of known exosomal miRNAs between control and hemicastrated pigs based on the Euclidean distance. (<b>E</b>) Spearman’s correlation of miRNA expression profiles between sperm and corresponding seminal plasma exosomes. (<b>F</b>) Venn diagram of DE miRNAs between sperm and seminal plasma exosomes in the HC versus CT group. (<b>G</b>) qRT-PCR validation of expression changes of five overlapping DE miRNAs between HC and CT groups. Three independent qRT-PCR experiments were performed in triplicate. All data are expressed as means ± SD. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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