Animals

Male C57BL/6J and female 129S1/SvImJ mice obtained from Jackson Laboratories were used to produce C57BL/6:129 F1 hybrids. F1 hybrids were used for all germline transmission studies. 6–8-week-old C57BL/6:129 F1 hybrid females (Jackson Laboratories, B6129SF1/J) were used for oocyte donation for ICSI studies. ICR female mice (Charles River, CD-1 IGS) were used as surrogates for embryo transfers for ICSI studies. All mice were housed in a 12:12 light:dark cycle with temperature 22 °C and relative humidity 42%. Food (Purina Rodent Chow; 28.1% protein, 59.8% carbohydrate, 12.1% fat) and water were provided ad libitum. All studies were performed according to experimental protocols approved by the University of Pennsylvania Institutional Animal Care and Use Committee, and all procedures were conducted in accordance with the NIH Guide for the Care and Use of Laboratory Animals.

Chronic stress

Having solidified the sufficient duration of chronic stress required for intergenerational stress to occur (4 weeks vs. previous 6 weeks), we developed a model whereby we could investigate dynamic vs. long-lasting changes in tissues contributing to intergenerational transmission, using a time point post-stress that does not transmit a phenotype to offspring and a time point that did. At postnatal day 28 (PN28), males were weaned, pair-housed with a same-sex littermate, and randomly assigned to a control or stress group. Psychological stress occurred over 28 days (PN28-56). One stressor was administered each day and the order of stressors was randomized each week. Stressors include the following: 36 h constant light, 1 h exposure to predator odor (1:5000 2,4,5-trimethylthiazole (Acros Organics) or 1:2000 phenethylamine (Sigma)), 15 min restraint, novel object (marbles or glass vials) overnight, multiple cage changes, 100 dB white noise overnight, and saturated bedding overnight, as previously described10,59.

Breeding scheme

Following completion of stress exposure (PN56), males were all left undisturbed for at least 1 week to remove the acute effects of stress. Males were then housed with virgin, stress-naive F1 hybrid females at either 9 or 20 weeks. To minimize male–female interactions that may impact maternal investment or care60, observation of a copulation plug within 1 h after lights on signaled the immediate removal of the female to her own cage containing a nestlet.

Tissue collection

Males were rapidly decapitated under isoflurane anesthesia 24 h following copulation. The testes, caput and cauda epididymis were removed and flash frozen in liquid nitrogen. For E12.5 embryo collections, pregnant ICR surrogate dams were deeply anesthesized with isoflurane on E12.5, and each uterine horn was removed where conceptuses were harvested. Fetal brains, placentas and tails were flash frozen in liquid nitrogen and stored at −80 °C until processing. All dissections were completed between 11:00 and 15:00.

Caudal sperm collection

Approximately 5 × 106 sperm were collected from the caudal epididymis via a double swim-up assay. Briefly, the caudal epididymis was minced in 1% bovine serum albumin in 3 mL warmed PBS and allowed to sit at room temperature for 30 min. The 1% BSA including sperm and epididymal tissue were transferred to a conical tube and incubated in a water bath at 37 °C for 30 min. The top 2 mL of supernatant was transferred to a new conical tube and incubated at 37 °C for 10 min. The top 1.5 mL of this supernatant was transferred to a new tube and centrifuged for 5 min at 4000 rpm at 4 °C. The supernatant was removed and the pellet containing mature sperm was flash frozen and stored at −80 °C until processing. Sperm samples were not pooled for any experiments in these studies.

HPA axis assessment

Plasma corticosterone was measured in response to an acute 15 min restraint stress in a 50 mL conical tube. Testing occurred 2–5 h after lights on. Tail blood was collected at onset and completion of restraint (0 and 15 min) and 15 and 115 min after the end of restraint (30 and 120 min). Samples were immediately mixed with 50 mM EDTA and centrifuged 10 min at 5000 rpm. Three microliters of plasma was collected and stored at −80 °C until analysis. Corticosterone levels were determined by 125I-corticosterone radioimmunoassay (MP Biomedical) according to manufacturer’s protocol. The N for each HPA axis assessment is as follows: Fig. 1b: 8 Control offspring and 8 Stress offspring (1 outlier); 1c: 8 Control offspring and 8 Stress offspring; 1d: 9 Control offspring and 7 Severe Stress offspring (1 outlier); 1e: 7 Control offspring (1 outlier) and 6 Severe Stress offspring; 3e: 5 EVVeh offspring and 4 EVCort offspring.

Cell culture and corticosterone treatment

Immortalized mouse distal caput epididymal epithelial (DC2) cells were purchased from Applied Biological Materials and cultured as previously described61. Briefly, cells were seeded in 75 cm2 Nunc EasYFlasks (Thermo Fisher) coated in collagen type 1, rat tail (Millipore). Cells were grown in Iscove’s modified Dulbecco’s medium (IMDM) supplemented with 10% exosome-free fetal bovine serum (Gibco) and 1% penicillin-streptomycin (Gibco). Fetal bovine serum was not charcoal-stripped and therefore contained base levels of steroids, including testosterone. At monolayer confluency, the media was replaced, and cells were either treated with 1:1000 vehicle (ethanol; resulting in 0.1% ethanol) or 1:1000 corticosterone in ethanol (Sigma; baseline concentration 144 nM, stress concentration 1.4 μM—resulting in 50 or 500 ng/mL of corticosterone in the culture media, respectively). Cells were treated every 24 h for 3 days for a total of three treatments. The media was replaced 24 and 96 h following the last treatment. Media and cells were collected at 24, 96, or 192 h following the last treatment and were not pooled. For cell collection, cells were trypsinized in 0.25% trypsin-EDTA (Gibco), centrifuged at 1500 rpm for 3 min, and frozen at −80 °C until further analysis.

Extracellular vesicle (EV) isolation

EVs were isolated from conditioned media using differential ultracentrifugation62. Briefly, cellular debris was removed from the media by centrifugation at 200 × g for 10 min, 2000 × g for 10 min, and 10,000 × g for 30 min. EVs were pelleted by ultracentrifugation at 100,000 × g for 1 h using the Optima L-90K Ultracentrifuge and SW 32 Ti swinging bucket rotor (Beckman Coulter). The EV pellet was resuspended in PBS or TriZol reagent and frozen at −80 °C until further analysis. EVs were not pooled for any experiments in these studies.

Protein extraction and western immunoblotting

EVs were processed for immunoblotting using established protocols. Samples were homogenized and resuspended in radioimmunoprecipitation assay (RIPA) buffer with protease inhibitor cocktail (Sigma), rotated for 2 h at 4 °C, and pelleted at 5000 × g for 10 min. Protein quantification was done using Bradford assay (BioRad). For immunoblotting, 20 μg of protein was loaded per lane for gel electrophoresis onto a NuPAGE 4–12% Bis-Tris gel (Life Technologies). After running, gels were cut and the same molecular weight sections for all samples were transferred together to enable multiple probing and to control for transfer conditions. After transfer of proteins to a nitrocellulose membrane (Life Technologies), membranes were blocked with Odyssey blocking buffer (Li-Cor) and probed with rabbit anti-CD63 (1:1000; Systems Biosciences EXOAB-CD63A-1), rabbit anti-Calnexin (1:1000; Abcam ab22595), and/or rabbit anti-Lamp1 (1:1000; Abcam ab24170), followed by incubation in IRDye800-conjugated donkey anti-rabbit secondary (1:20,000; Li-Cor).

Nanoparticle tracking analysis

All samples were run on a NanoSight NS500 to determine the size distribution of EV particles at the Center for Nanotechnology in Drug Delivery at the University of North Carolina. All samples were diluted to a concentration between 1 × 108 and 5 × 108 particles/mL in filtered PBS. Five 40 s videos were taken of each sample to capture particles moving by way of Brownian motion. The nanosight software tracked the particles individually and, using the Stokes–Einstein equation, calculated the hydrodynamic diameters. The N for Fig. 2f, g: 4 Vehicle EV samples and 4 Stress Cort EV samples and samples were not pooled.

IVIS spectrum imaging of labeled EVs

EVs isolated from cultured DC2 cells at day 11 (8 days post treatment) were labeled with XenoLight DiR Fluorescent Dye (PerkinElmer) per manufacturer’s instruction. Briefly, EV pellets were resuspended in 600 μL of cold PBS and incubated with 20 μL of 10 mM DiR dye for 5 min at RT. As a non-EV control, 600 μL of PBS alone was processed in parallel. The total volume was brought up to 38 mL with PBS and ultracentrifuged at 100,000 × g for 1 h. The dyed EV pellet was resuspended in PBS and 5 × 107 particles were injected intravenously via the tail vein into naive adult F1 hybrid male mice. Twenty-four hours following injection, the mice were sacrificed and their tissues were collected for imaging using an IVIS Spectrum (PerkinElmer). The excitation filter was set at 745 nm and the emission filter was set at 800 nm. For quantification, total radiant efficiency was calculated using Living Image software, with the minimum set at 1 × 107 and the maximum set at 1.45 × 107. The N for IVIS experiments in Supplementary Fig. 5 is as follows: 6 injected Vehicle EVs, 6 injected Stress Cort EVs, where EVs were not pooled for any injection.

Proteomics mass spectrometry

Individual EV samples were solubilized in 5% sodium deoxycholate after washing in phosphate-buffered saline. Proteins were washed, reduced, alkylated and trypsinolyzed on filter as previously described63,64. Tryptic peptides were separated on a nano-ACQUITY UPLC analytical column (BEH130 C18, 1.7 μm, 75 μm × 200 mm, Waters) over a 165-min linear acetonitrile gradient (3–40%) with 0.1% formic acid on a Waters nano-ACQUITY UPLC system and analyzed on a coupled Thermo Scientific Orbitrap Fusion Lumos Tribrid mass spectrometer as described65. Full scans were acquired at a resolution of 120,000, and precursors were selected for fragmentation by higher-energy collisional dissociation (normalized collision energy at 30%) for a maximum 3-s cycle. Tandem mass spectra were searched against a UniProt mouse reference proteome using Sequest HT algorithm66 and MS Amanda algorithm67 with a maximum precursor mass error tolerance of 10 ppm. Carbamidomethylation of cysteine and deamidation of asparagine and glutamine were treated as static and dynamic modifications, respectively. Resulting hits were validated at a maximum false discovery rate of 0.01 using a semi-supervised machine learning algorithm Percolator68. Label-free quantifications were performed using Minora, an aligned AMRT (Accurate Mass and Retention Time) cluster quantification algorithm (Thermo Scientific, 2017). Protein abundances were measured by comparing the MS1 peak volumes of peptide ions, whose identities were confirmed by MS2 sequencing as described above. The N for proteomics experiments is as follows: Fig. 2d left and Supplementary Figure 4: 5 Vehicle 4d EVs, 5 Stress Cort 4d EVs; Fig. 2d right, 2e: 6 Vehicle 11d EVs, 6 Stress Cort 11d EVs, where EVs were not pooled.

Histone extraction, bottom-up nanoLC MS/MS

Samples were processed as previously described69. Briefly, whole caput epididymides were homogenized in nuclei isolation buffer (15 mM Tris-HCl pH 7.5, 60 mM KCl, 15 mM NaCl, 5 mM MgCl 2 , 1 mM CaCl 2 , 250 mM sucrose) with 1 mM DTT, 1% phosphatase inhibitor (Sigma), 1 pellet protease inhibitor (Roche), 10 mM sodium butyrate (Sigma), and 10% NP-40. Histones were acid extracted from nuclei by rotating overnight in 0.4 N H 2 SO 4 at 4 °C and precipitated with 100% trichloroacetic acid overnight at 4 °C. Extracted histones were washed with acetone and quantified by Bradford reagent according to manufacturer’s protocol (Sigma). Approximately 20 μg histones were derivatized using propionic anhydride (Sigma) and digested with 1:10 trypsin (Promega). Samples were subsequently desalted by binding to C18 material from a solid phase extraction disk (Empore), washed with 0.5% acetic acid, and eluted in 75% acetonitrile and 5% acetic acid. Peptides were separated in EASY-nLC nanoHPLC (Thermo Scientific, Odense, Denmark) through a 75 μm ID × 17 cm Reprosil-Pur C 18 -AQ column (3 μm; Dr. Maisch GmbH, Germany) using a gradient of 0–35% solvent B (A = 0.1% formic acid; B = 95% acetonitrile, 0.1% formic acid) over 40 min and from 34 to 100% solvent B in 7 min at a flow-rate of 250 nL/min. LC was coupled with an Orbitrap Fusion mass spectrometer (Thermo Fisher Scientific, San Jose, CA, USA) with a spray voltage of 2.3 kV and capillary temperature of 275 °C. Full scan MS spectrum (m/z 300 − 1200) was acquired in the Orbitrap with a resolution of 60,000 (at 200 m/z) with an AGC target of 5 × 10e5. At Top Speed MS/MS option of 2 s, the most intense ions above a threshold of 2000 counts were selected for fragmentation with higher-energy collisional dissociation (HCD) with normalized collision energy of 29, an AGC target of 1 × 10e4 and a maximum injection time of 200 ms. MS/MS data were collected in centroid mode in the ion trap mass analyzer (normal scan rate). Only charge states 2–4 were included. The dynamic exclusion was set at 30 s. Where data-dependent acquisition70 was used to analyze the peptides, full scan MS (m/z 300–1100) was performed also in the Orbitrap with a higher resolution of 120,000 (at 200 m/z), AGC target set at the same 5 × 10e5. The difference in the MS/MS though also performed in the ion trap, was with sequential isolation windows of 50 m/z with an AGC target of 3 × 10e4, a CID collision energy of 35, and a maximum injection time of 50 ms. MS/MS data were collected in centroid mode. For both acquisition methods, peak area was extracted from raw files by using our in-house software EpiProfile71. The relative abundance of a given PTM was calculated by dividing its intensity by the sum of all modified and unmodified peptides sharing the same sequence. For isobaric peptides, the relative ratio of two isobaric forms was estimated by averaging the ratio for each fragment ion with different mass between the two species. Samples were not pooled.

RNA isolation

Total RNA extraction from epididymal sperm and EV pellets were performed using the TRIzol reagent (Thermo Fisher) according to manufacturer’s protocol. Samples for all experiments represent individual samples and were not pooled.

Incubation of caput epididymal sperm with DC2 EVs

Caput epididymal sperm were obtained by making incisions at both ends of the caput and through the tissue with a needle in modified Biggers, Whitten, and Whittingham media (BWW, composed of 91.5 mM NaCl, 4.6 mM KCl, 1.7 mM CaCl 2 .2H 2 O, 1.2 mM KH 2 PO 4 , 1.2 mM MgSO 4 .7H 2 O, 25 mM NaHCO 3 , 5.6 mM NaHCO 3 , 5.6 mM d-glucose, 0.27 mM sodium pyruvate, 55 mM sodium lactate, 5 U/ml penicillin/streptomycin, 20 mM HEPES buffer, 3 mg/ml BSA at pH 7.4) and left to ooze for 90 min at 37 °C, as previously described48. The whole volume (1 mL) was placed over a 3 mL 27% Percoll/BWW density gradient and spun at 400 × g for 15 min at RT. Spermatozoa in the pellet were washed again with BWW buffer and pelleted at 400 × g for 2 min. Using DC2 EVs extracted on the same day, individual caput epididymal sperm samples were split into two (not pooled) and co-incubated with 100 μL of either vehicle or corticosterone-treated DC2 EVs (~4 × 109 total EVs) in a 96-well plate for 3 h at 37 °C with 5% CO 2 with slight rotation, as previously described72. Following incubation, sperm were pelleted at 400 × g for 3 min and washed three times with warmed PBS. Clean sperm samples were then resuspended in the cryoprotective medium gCPA, containing 100 mM l-glutamine, and flash frozen in liquid nitrogen until intracytoplasmic sperm injection.

Superovulation and oocyte collection

All the oocytes used for this experiment were collected from 6- to 8-week-old Bl6 x129 females (Jackson Laboratories). The donor females were super-ovulated using 5 IU of pregnant mare’s serum gonadotropin (PMSG) followed 48 h later by 5 IU of human chorionic gonadotropin (hCG). All the hormones were administrated via intraperitoneal injection IP. The oocytes were dissected from the ampulla of the oviduct 13–16 h post hCG and were placed in CZB-HEPES media supplemented with 3 mg/ml hyaluranidase to remove the cumulus cells. After 2–3 min incubation at room temperature, the oocytes were separated from the cumulus cells and immediately washed 3–4 times and cultured in KSOM media (Millipore) in a 37 °C, 5% CO 2 incubator. The KSOM culture drops were covered with mineral oil (Millipore) to prevent evaporation.

Intracytoplasmic sperm injection (ICSI) and embryo transfer

All the microinjections were performed at RT using a Narishige micromanipulator attached to a Nikon inverted microscope. To reduce the oocyte lysing rate, the CZB-HEPES media supplemented with 1% PVP was used for sperm injection and the 500–800 μL injection drop was covered with mineral oil to prevent evaporation; moreover, a glass-bottom dish was used to increase the resolution and contrast. The frozen sperm was washed once in CZB-HEPES media before it was placed in the injection drop on the microscope where the oocytes were added in groups of 10 to perform the microinjection. The sperm head was detached from tails by pining down the sperm to the bottom of the dish and applying some pressure right at the head/neck junction. The detached sperm heads were injected into the oocytes using an Eppendorf PiezoXper Microinjector. After injection the oocytes were placed back in the KSOM media in the 37 °C, 5% CO 2 incubator where after 2–3 washes they were cultured 24–30 h until they were transferred into recipient females. Twenty-four to thirty hours post ICSI, all the embryos which successfully cleaved to the 2-cell stage were transferred into recipient females via oviduct transfer. Both, the left and the right oviduct were used for embryo transfers and the ICR recipient females were synchronized by using vasectomized males. CZB-HEPES media was used for embryo transfer.

mRNA sequencing and analysis

Total RNA from E12.5 brains and placentas were quantified on a NanoDrop 2000 spectrophotometer (Thermo Scientific). Libraries for RNA sequencing were made using a TruSeq Stranded mRNA Sample Preparation Kit (Illumina) with 250 ng RNA according to manufacturer’s protocol. All library sizes and concentrations were confirmed on a TapeStation 4200 (Agilent) and Qubit 3.0 Fluorometer (Thermo Fisher). Individually barcoded libraries were pooled and and libraries for this study were sequenced on the same Illumina NextSeq 500 (75-bp single-end) flow cell, to control for batch effects. Fastq files containing an average of 50 million reads were processed for pseudoalignment and abundance quantification using Kallisto (version 0.43.1)73. The transcriptome was aligned to the EnsemblDB Mus musculus package (version 79). For mRNA sequencing, the N is as follows for each experiment: Fig. 3b–d and Supplementary Fig. 6: 6 ICSI EVVeh E12.5 brains; 6 ICSI EVCort E12.5 brains; Supplementary Fig. 7: 6 ICSI EVVeh E12.5 placentas; 6 ICSI EVCort E12.5 placentas where samples were not pooled.

Gene set enrichment analysis (GSEA)

Gene set enrichment analysis74 (version 3.0, Broad Institute) was used to assess patterns of gene expression to determine greater-than-chance enrichment in biological pathways in a threshold-free manner (i.e., differential expression of genes was not considered). Total genes were run against the c5_BP gene set from the Molecular Signature Database (MsigDB v5.0, Broad Institiute) using 1000 gene_set permutations on E12.5 transcriptomic data and clustered to reduce redundancy using the ClusterMaker2 function in Cytoscape.

Small RNA sequencing and analysis

Small RNA libraries were constructed using the NEBNext Small RNA Library Prep Set for Illumina (NEB) with 200 ng total RNA according to manufacturer’s protocol. All library sizes and concentrations were confirmed on a TapeStation 4200 (Agilent) and Qubit 3.0 Fluorometer (Thermo Fisher). Individually barcoded libraries were pooled and sequenced on an Illumina NextSeq 500 (75-bp single-end). Fastq files containing an average of 10 million reads per sample were aligned and quantified using miRDeep2 (version 2.0.0.8)75. For small RNA sequencing of sperm, the N is as follows: Fig. 1f: 7 Control 9-week samples, 6 Stress 9-week samples, 8 Control 20-week, 8 Stress 20-week (1 outlier). For sequencing of DC2 EVs, the N is as follows: Fig. 2b, c, Supplementary Fig. 3: 4 days—3 Vehicle EVs, 4 Baseline Cort EVs, and 4 Stress Cort EVs; 7 days—4 Vehicle EVs, 4 Baseline Cort EVs, and 4 Stress Cort EVs; 11 days—4 Vehicle EVs, 4 Baseline Cort EVs, and 3 Stress Cort EVs. Samples were not pooled. For each study, samples from all treatment groups were represented in each of two flow cells so that each treatment group was equally represented per sequencing run to control for batch effects.

Taqman miRNA assay

To confirm observed changes in the sperm and DC2 EV RNA-sequencing data, miRNA displaying effects of age (miR-741-3p and miR-881-3p), stress (miR-34c-5p and miR-9-3p), or corticosterone (miR-22-3p and miR-34c-5p) treatment were assayed by reverse-transcription quantitative real-time PCR (RT-qPCR) in conjunction with TaqMan miRNA Assays (Applied Biosystems) according to the manufacturer’s protocol. Selected miRNA had high expression levels (ranging from 70 to 40,000 normalized reads) and displayed robust effects by age or treatment (log 2 fold change > |0.40|) by RNA sequencing. Briefly, 350 ng of total RNA was reverse transcribed to cDNA using the Taqman MicroRNA Reverse Transcription Kit (Applied Biosystems) and a pool of assay-specific reverse transcriptase primers. Prior to the real-time PCR reaction, the RT product was amplified using the Taqman PreAmp Master Mix (Applied Biosystems). PCR reactions, including two endogenous controls (U6 snRNA and snoRNA-202), were run using TaqMan Universal Master Mix II, no UNG (Applied Biosystems) on a QuantStudio 5 Real-Time PCR System. All Taqman reactions were run in triplicate in 384-well plates, where samples were distributed across two plates so that each treatment group was equally represented per run to control for batch effects. Ct values were calculated using the instrument’s onboard software. The mean Ct values for the two endogenous controls were subtracted from corresponding Ct values of the miRNA of interest. Resulting ΔCt values were used to calculate expression (relative to Control 9-week) using the ΔΔCt method. To correlate Taqman qPCR with RNA-sequencing results, the log 2 values of the qRT-PCR fold change (relative to 9-week control or vehicle EVs) were plotted against the log 2 RNA-sequencing read counts for selected miRNA and examined using linear regression analysis. For the Taqman miRNA assays in sperm, the N was as follows: Supplementary Fig. 2b: 7 Control 9-week samples, 8 Control 20-week samples, 6 Stress 9-week samples, and 7 Stress 20-week samples, where sperm samples were not pooled; and 4 Vehicle EV samples and 3–4 Corticosterone EV samples, where EV samples were not pooled.

Bioinformatics analyses

All analyses were performed using R version 3.3.3 and Bioconductor version 3.4.

Rank–rank hypergeometric overlap (RRHO)

The R package RRHO2 was used to evaluate the degree and significance of overlap in threshold-free differential expression data (nominal p-values for all miRNA from Control vs Stress comparisons using DEseq analysis) between in vivo sperm and in vitro EV miRNA datasets46,47. This updated RRHO pipeline improves the visualization of overlap heatmaps, where pixels are plotted in one of four quadrants in order to determine the concordance and directional overlap between datasets, compared with prior uses of the original RRHO analysis where pixels were continuously plotted without distinctive areas for each categorization (hence, one heatmap with no separation). Heatmaps generated using RRHO2 have top right (both increasing) and bottom-left (both decreasing) quadrants, representing the concordant miRNA changes, while the top left and bottom right represent discordant overlap (opposite directional overlap between datasets). For each comparison, one-sided enrichment tests were used on −log 10 (nominal p-values) with the default step size for each quadrant, and corrected Benjamini–Yekutieli p-values were calculated. To ensure RRHO-identified significant overlap between sperm and DC2 EV miRNA were detected above chance, EV miRNA samples were randomly assigned to groups and the same analysis was rerun on nominal p-values of all detected miRNA, where randomization was used on Vehicle and Stress Cort EV miRNA samples within time at 8 days post treatment, on Vehicle, Baseline Cort, and Stress Cort EV miRNA samples within time at 8 days post treatment, and on Vehicle and Stress Cort EV miRNA samples across time such that 1 Vehicle and 1 Stress Cort sample were randomly selected from 1, 4, and 8 days post treatment. The number of concordant EV miRNA for each analysis was quantified and used to calculate the percentage of concordant miRNA over total identified miRNA

Differential expression analysis

The R package DESeq was used to perform pairwise differential expression analyses on RNA-sequencing datasets using the negative binomial distribution76. For E12.5 brain mRNA sequencing, count data were filtered for at least 10 counts per gene across all groups, normalized, and dispersions were estimated per condition with a maximum sharing mode. Small RNA-sequencing data from mouse sperm and DC2 cell EVs were filtered for >2 counts in at least three samples across all groups, normalized, and dispersions were estimated per condition using empirical values. Significance for all differential expression was set at a corrected p-value < 0.05. Heatmaps were generated using the R package gplots heatmap.2 function. All heatmaps are plotted as average Z scores per treatment group.

Random forests

The R package randomForest45 was used to analyze histone mass spectrometry ratio data with the parameters ntree = 1000 and mtry = √p for classification analysis, based on calculation of p where p = total number of histone modifications identified. Importance values were calculated and scaled by standard deviation for permutation-based measures. This approach ranks each histone modification by the percent decrease (MDA) to the model’s accuracy that occurs if the histone mark is removed, allowing for the identification of a histone code that discriminates between treatment groups. To estimate the minimal number of histone modifications required for prediction, ten-fold cross-validation using the ‘rfcv’ command was implemented through the randomForest package.

Statistics

Investigators blinded to animal treatment groups conducted all experiments and analyses. Samples for all experiments represent individual samples and were not pooled. For the following, statistical comparison was conducted using Prism 7.0 (Graphpad). Corticosterone levels were analyzed by two-way ANOVA with time as a repeated measure. Corticosterone AUC, litter characteristics, and gene expression data were analyzed by two-way ANOVAs. Outliers for HPA axis assessment were excluded at all time points and determined by data greater than two standard deviations away from the group mean or corticosterone levels >150 ng/mL at the 120 min time point, indicating no stress recovery and/or within littermate fighting that were noted at time of experiment (for 9-week HPA, 1 Stress offspring and 1 Severe Stress offspring, for 20-week HPA, 1 Control offspring). Taqman miRNA qRT-PCR data were analyzed using two-way ANOVA for sperm and unpaired two-tailed Student’s t-test for EVs. Immunoblotting data, nanosight, and IVIS radiant efficiency were analyzed using unpaired two-tailed Student’s t-tests. When appropriate, Bonferroni’s post hoc test was used to explore main effects followed by multiple comparisons adjustment (denoted adjusted p). Significance was set at p < 0.05.

Recruitment of human subjects

A cohort of 18 healthy males had been recruited from the University of Pennsylvania student body to establish normative sperm molecular signatures as a benchmark for comparison to later clinical populations. The study was approved by the Perelman School of Medicine at the University of Pennsylvania Institutional Review Board, and all participants provided written informed consent. Subjects between the ages of 18 and 25 were screened for history of major medical illnesses, mental health diagnoses, and substance abuse. The participants were English-speaking and gave written informed consent for participation in this study, which was approved by the Perelman School of Medicine at the University of Pennsylvania Institutional Review Board. Key exclusion criteria included (1) history of major medical illnesses, including liver diseases, suspected or known malignancy, pulmonary disorders, clotting or bleeding disorders, heart disease, diabetes, history of stroke or other medical conditions that the physician investigator deemed as contraindicated for the patient to be in the study, as determined by participant self-report; (2) regular or recreational use of psychotropic medication (antidepressants, antipsychotics, or anxiolytics), as per self-report, and recent (within previous year) psychiatric diagnosis and treatment for Axis I disorders including major depression, bipolar disorder, generalized anxiety disorder, post-traumatic stress disorder, and panic disorder, as determined by MINI International Neuropsychiatric Interview77; (3) lifetime history of schizophrenia or other psychotic disorder, as per MINI International Neuropsychiatric Interview; (4) lifetime substance addiction disorder, excepting nicotine, as per MINI International Neuropsychiatric Interview; (5) substance abuse disorders within the previous 2 years, excepting nicotine, as per MINI International Neuropsychiatric Interview; (6) use of any tobacco products, determined by urine cotinine level; (7) positive drug screen for any substance, determined by urine drug screen at screening.

Study procedures for human subjects

The study involved a total of seven visits. The first visit was a screening visit to determine participant eligibility. The following six visits were sperm collection visits. During the screening visit, subjects underwent an in-office assessment including a urine toxicology screen, urine cotinine screen, and clinical assessments, including the Adverse Childhood Experiences (ACE) questionnaire43 and the MINI International Neuropsychiatric Interview. Subsequent visits (2–7) took place once a month for 6 months. At these visits, subjects submitted a semen sample, collected at home within the previous hour, to experienced andrologists at Penn Fertility Care clinic for processing and sample cryopreservation. Participants were asked to abstain from ejaculation for 48 h prior to semen collection. Within the same day, participants also completed a series of questionnaires to assess stress and anxiety experienced over the previous month, including the Perceived Stress Scale (PSS)41 and the Spielberger State-Trait Anxiety Inventory42 (STAI). One participant did not return for their final donation, therefore only timepoints 1–5 were available for subject 11.

Assessing the impact of stress dynamic on human sperm miRNA

Procedures for the isolation of small RNA from mature sperm were adapted from a previous study78. Briefly, cryopreserved sperm samples were thawed, suspended in PureSperm Buffer (Nidacon), then mature sperm were enriched by centrifugation (300 × g, 15 min) through a 50% PureSperm density gradient (Nidacon). Sperm were then lysed in TRIzol-LS (Thermo Fisher) reagent, supplemented with 0.2 M β-mercaptoethanol and 100 mg of nuclease-free stainless-steel beads, by homogenization on a Disruptor Genie (Scientific Industries) at 3000 rpm for 5 min. RNA, enriched for small RNA, was isolated using Qiagen’s miRNeasy Mini kit according to manufacturer’s instructions. RNA concentration and quality were assessed using Agilent’s small RNA chipsrun on a Bioanalyzer 2100 (Agilent Technologies). Three subjects (4, 6, and 15) were excluded from further analysis due to consistently low RNA yield and quality across donated samples. PSS scores reported by the remaining subjects over the 6-month study period were assessed to identify subjects with a stress experience dynamic that best mimicked our mouse model. Four subjects (1, 7, 12, and 18) that experienced elevated perceived stress early in the study, followed by a period of recovery (recovering-stress dynamic) (defined as a change in PSS score >10 between the max PSS score early in the study (month 1 or 2) and minimum PSS score late in the study (month 5 or 6)). Four individuals (2, 5, 11, and 14) with minimal variation in reported PSS scores over the study (standard deviation from the mean PSS score <2) were selected to make up a comparison stable-stress dynamic group. The small RNA content of samples from these two groups of subjects was analyzed by small RNA sequencing. Libraries were constructed using the TruSeq small RNA Library Prep Kit (Illumina) with 10 ng of small RNA according to the manufacturer’s protocol. Post-PCR cleanup and size selection for products >100 bp was performed using AMPure XP bead purification. Library size distribution and quantification was performed using on a TapeStation 4200 (Agilent) using their High Sensitivity D1000 screentape. Individually barcoded libraries were pooled to achieve ~10 million reads per sample and sequenced on an Illumina NextSeq 550 (36-bp single-end).

Bioinformatic analysis of human sperm miRNA

Because sequence reads were 36 bp, which is greater than the average size of miRNA (22 bp), reads were trimmed at the 3′ end to remove any trailing adaptor sequence using the Trimmomatic tool79. After read trimming, reads shorter than 15 bp were discarded before downstream analyses. One sample was excluded at this stage for quality concerns (sample from subject 5 at collection 4 had <1 million remaining reads). Trimmed reads were then aligned to the human reference genome build GRCh38 using the Bowtie short read aligner80. Reads were aligned allowing for 2 mismatches and a seed length of 15. The expression of each known miRNA from miRbase v2281 were computed using HTSeq python framework82. Normalized expression counts for miRNA detected in >50% of samples (341 miRNA) were further analyzed by implementing a linear mixed effects model using the R package ‘lme4’, accounting for the repeated measures structure of the data by treating subject as a ‘random’ effect83. Using this modeling strategy, we tested the association between stress-experience dynamic group assignment and principal components identified in an unbiased dimensional reduction analysis (PCA analysis) of the expression of total miRNA across samples.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.