ABSTRACT
There has been a rapid increase in neonates born with a history of prenatal opioid exposure. How prenatal opioid exposure affects pain sensitivity in offspring is of interest, as this may perpetuate the opioid epidemic. While few studies have reported hypersensitivity to thermal pain, potential mechanisms have not been described. This study posits that alterations in the gut microbiome may underly hypersensitivity to pain in prenatally methadone-exposed 3-week-old male offspring, which were generated using a mouse model of prenatal methadone exposure. Fecal samples collected from dams and their offspring were subjected to 16s rRNA sequencing. Thermal and mechanical pain were assessed using the tail flick and Von Frey assays. Transcriptomic changes in whole brain samples of opioid or saline-exposed offspring were investigated using RNA-sequencing, and midbrain sections from these animals were subjected to qPCR profiling of genes related to neuropathic and inflammatory pain pathways. Prenatal methadone exposure increased sensitivity to thermal and mechanical pain and elevated serum levels of IL-17a. Taxonomical analysis revealed that prenatal methadone exposure resulted in significant alterations in fecal gut microbiota composition, including depletion of Lactobacillus, Bifidobacterium, and Lachnospiracea sp and increased relative abundance of Akkermansia, Clostridium sensu stricto 1, and Lachnoclostridium. Supplementation of the probiotic VSL#3 in dams rescued hypersensitivity to thermal and mechanical pain in prenatally methadone-exposed offspring. Similarly, cross-fostering prenatally methadone-exposed offspring to control dams also attenuated hypersensitivity to thermal pain in opioid-exposed offspring. Modulation of the maternal and neonatal gut microbiome with probiotics resulted in transcriptional changes in genes related to neuropathic and immune-related signaling in whole brain and midbrain samples of prenatally methadone-exposed offspring. Together, our work provides compelling evidence of the gut-brain-axis in mediating pain sensitivity in prenatally opioid-exposed offspring.
Introduction
Opioid use in pregnant women continues to reach epidemic proportions as a result of the opioid epidemic. From 2010 to 2017, the number of women with opioid-related diagnoses documented at delivery increased from 3.5 to 8.2 per 1000 delivery hospitalizations, representing a relative increase of 131%.Citation1 Additionally, self-reported data from both the Pregnancy Risk Assessment Monitoring System (PRAMS) survey and maternal and infant health surveys revealed 6.6% of women used prescription opioids during pregnancy.Citation2 Among these women, 21.2% reported misuse and 27.1% reported wanting or needing to cut down or stop using opioidsCitation2. Current recommendations for opioid dependent women during pregnancy are to transition to medication for opioid use disorder (MOUD) during pregnancy, among which methadone or buprenorphine are first-line therapy optionsCitation3. Though still opioids, opioid agonist pharmacotherapy during pregnancy is reported to prevent opioid withdrawal symptoms in the fetus and complications of nonmedical opioid use by reducing relapse risk in the motherCitation3. However, as opioids cross the placenta, collectively this substantial increase in opioid use among pregnant woman has further deepened the pool of infants born with a history of prenatal opioid exposure. This is evidenced by an 82% increase in the rate of neonatal opioid withdrawal syndrome (NOWS) in prenatally opioid-exposed offspring from 2017 to 2019Citation1, though there is some evidence of lessened severity of NOWS and obstetrical complications with the use of MOUDs compared to non-MOUDs maternal opioid use.Citation3–5
Prenatal opioid exposure has been associated with significant neurodevelopmental health consequences, among which vulnerability to future addiction and alterations in pain sensitivity are major endpoints of interest, as these may perpetuate the opioid epidemic.Citation6–11 Pain and substance use are highly prevalent and co-occurring conditions, which interact in a positive feedback loop resulting in the exacerbation and maintenance of both conditions over time.Citation12 Abnormal pain perception contributes to the development and maintainance of addiction.Citation13–16 Furthermore, preexisting pain is a common finding in opioid addicts, especially amongst those who used prescription opioids only or initially.Citation17 Indeed, pain is a potent motivator of substance self-administration, and may contribute to escalating use, and poorer substance-related treatment outcomes.Citation12 How prenatal opioid exposure affects pain sensitivity in offspring has been relatively unexplored in humans. In one study, prenatal opioid exposure was associated with heightened sympathetic arousal and higher facial expressions of pain/distress in babies at baseline.Citation18 Others have corroborated these findings, showing increased skin conductance in newborns with NOWS, which reflects heightened responses to painful stimuli compared with control newborns.Citation19 Preclinical models have further described thermal hyperalgesia in prenatally-opioid exposed rodents during childhood (postnatal day 29–39) per hot plate assay,Citation20 which in other studies have continued to adolescence/early adulthood (postnatal day 60) per tail flick assay,Citation21 suggesting that opioid-exposed offspring may have dysregulated pain responses.
While both clinical and preclinical studies have reported increased pain with POE, there is a major gap in our understanding of processes that play a key role in the development of hyperalgesia. This is especially relevant as uncovering mechanisms that play a role in aberrant pain responses may help mitigate future adverse effects of prenatal opioid exposure and provide insights into therapeutic strategies for early intervention. Here, we hypothesize that dysbiosis of the gut microbiota may mediate hypersensitivity to pain in opioid-exposed offspring. Recent advances in research have described the importance of gut microbiota in neurodevelopment and behavior through the gut-brain-axis. Sometimes referred to as the “second brain,” the gut is known to release cytokines, neurotransmitters, neuropeptides, chemokines, endocrine messengers, and microbial metabolites, which affect brain development and function, regulate brain chemistry, and influence neuro-endocrine systems.Citation22 Importantly, dysregulation of the gut-brain axis has been associated with adverse health outcomes, including visceral, mechanical, or thermal hypersensitivity, stress-induced hyperalgesia, allodynia, inflammatory pain, and functional disordersCitation22. This dysregulation may start from alterations in the composition of the gut microbiota due to diet, drugs, or disease, termed dysbiosis. Indeed, consistent with the widely accepted developmental origins of health and disease theory, dysbiosis of the maternal and neonatal gut microbiome has emerged as a leading mechanism underlying adverse neurodevelopmental outcomes in offspring.Citation23–28 Previous studies have shown that opioid use during pregnancy is associated with profound changes in the maternal and neonatal gut microbiome; prenatally opioid-exposed offspring exhibit lasting alterations in their gut microbiome composition which often reflects loss of commensal bacteria and expansion of pathogenic flora.Citation29–32 However, whether alterations to the gut microbiome may modulate the hypersensitivity to thermal pain reported in prenatally opioid-exposed offspring has not yet been examined. Furthermore, whether opioid exposed offspring display altered pain sensitivities in other tests of pain-like-behavior such as the von Frey test of mechanical pain, which tests cutaneous sensitivities such as neuropathic and inflammatory related pain, is also unknown.Citation33–35 Accordingly, we test the hypothesis that the gut microbiome may mediate altered sensitivity to thermal as well as mechanical pain in a murine model of prenatal methadone exposure. We further examine the effects of opioids on the developing brain using RNA sequencing or qPCR profiling to uncover unique transcriptional signatures induced by prenatal methadone exposure and how these are influenced with modulation of the maternal and neonatal gut microbiome using probiotics and fecal microbial transplantation strategies.
Methods
Animals
All animal experiments were approved by the Institutional Animal Care and Use Committee policies at the University of Miami and adhered to all ethical guidelines related to the care of laboratory animals. Twelve-week-old female C57BL/6 (WT) mice (20–24 g) were purchased from Jackson Laboratories (Bar Harbor, ME, USA) (https://www.jax.org/strain/003752), with age-matched littermate wild type (WT) mice used as controls. Mice were housed five per cage under a controlled temperature (22 ± 2C), humidity (30%–70%), and 12 h light/dark cycle (light at 0700), with food pellets and water ad libitum. Mice were maintained in sterile microisolator cages under pathogen-free conditions. All efforts were made to minimize animal suffering and to reduce the number of animals used. Animals were humanely sacrificed using CO2 asphyxiation followed by cervical dislocation, as recommended by the Panel of Euthanasia of the American Veterinary Medical Association (AVMA). Specifically, dams were either sacrificed on estrous day 15 for placenta studies or when their offspring were 3 weeks of age. Offspring were sacrificed at either 3-weeks of age or in longitudinal studies, 12 weeks of age. All animal experiments comply with the ARRIVE guidelines and were carried out in accordance with the U.K. Animals (Scientific Procedures) Act, 1986 and the National Research Council’s Guide for the Care and Use of Laboratory Animals.
Generation of animals
Prenatal opioid-exposed (MET) or control (CTRL) offspring were generated by randomly assigning 12-week-old female C57 BL/6 mice to receive subcutaneous injections of either saline or hydromorphone (0.5 mg/kg, s.c., b.i.d., pre-gestation day (PG) 1–3, 1.25 mg/kg, s.c., b.i.d. PG 4–6, 2 mg/kg, s.c., b.i.d. PG 7–9, 2.75 mg/kg, s.c., b.i.d. PG 10–12, 3.5 mg/kg, s.c., b.i.d. PG 13–14) 2 weeks prior to mating to induce hydromorphone dependence. Two female mice were housed per cage, and co-housed females were all given the same treatment, given coprophagic behavior. Females remained co-housed throughout treatments and birth and weaning of pups.
After two weeks of treatment, hydromorphone-dependent mice were transitioned to methadone (10 mg/kg, s.c., b.i.d), while saline-treated animals continued to receive saline injections. Additionally, at this time hydromorphone-dependent females were mated with drug-naïve 14-week-old male C57 BL/6 mice, breeding ratio 2 co-housed females to 1 male mouse per cage. After five days, males were removed from the cage. Animals were checked daily for copulation plugs to adequately date pregnancy and create timelines for future treatments. Animals that did not get pregnant during this 5-day window were eliminated from the experiment.
Maternal methadone or saline treatment continued throughout pregnancy and postnatally, until weaning of pups at 3 weeks of age. This experimental strategy models standard recommendations to initiate and maintain medication for opioid use disorder (e.g., methadone or buprenorphine) during pregnancy in a previously opioid dependent (e.g., hydromorphone) female to reduce fetal and neonatal mortality.Citation3,Citation36 At weaning, offspring were sexed; only male offspring were used for experiments. In longitudinal studies, after 3 weeks of age, mice were weaned from mothers and housed 5 male offspring of the same treatment group per cage, until experimentation at 12 weeks of age. Otherwise, both offspring and mothers were sacrificed at 3-weeks of age or weaning of pups for experiments. In dams, at sacrifice (postnatal day (P) 21), large intestinal contents were collected, In offspring, at sacrifice at either P21 or P84 (longitudinal studies), blood, large intestinal contents, large intestinal tissue, or whole brain samples were collected.
Probiotic treatments
For probiotic treatment, from E19 to P21, pregnant dams were gavaged once daily with 3E9 CFU/mL of the VSL#3 probiotic (Sigma-Tau Pharmaceuticals, Inc., Gaithersburg, MD) containing the following strains: L. acidophilus, L. bulgaricus, L. paracasei, L. plantarum, B. breve, B. infantis, B. longum, and S. thermophilus, or an equal volume of vehicle (sterile water). VSL#3 arrives prepackaged at concentration of 450 billion colony forming units/packet. VSL#3 suspension was prepared daily by diluting 4 × 10Citation11 colony forming units of freeze-dried VSL#3 in sterile water to desired concentration. 0.2 mL of resuspended solution was gavaged to each animal. Concentrations were confirmed by cultural analyses of the suspension via retrospective plate counts on blood agar plates.
Cross fostering
For cross-fostering experiments, on P3, control or methadone pups were randomized to be fostered to nursing saline treated mothers (FCM) or nursing methadone treated mothers (FMM) until P21. No pups remained with their birth mothers. Individual pups from control or methadone-exposed litters were randomly selected to be cross fostered to FCM or FMM such that each fostered litter contained a maximum of three male pups, coming from three different litters of the same treatment group. At least five foster mothers per group and their new litters were used for experimentation. Thus, the following four groups are described in cross fostering experiments: 1) MET FMM-methadone pups cross fostered to methadone mothers 2) MET FCM-methadone pups cross fostered to saline treated mothers 3) CTRL FCM- control pups cross fostered to saline treated mothers 4) CTRL FMM-control pups cross fostered to methadone treated mothers. Pups were monitored for acceptance from their foster mothers by monitoring pup retrieval time. Pups stayed with fostering mothers until weaning at P21, after which they were used for experiments.
Tail flick
The thermal nociceptive thresholds were assessed by tail flick assays as described previously.Citation37 A light beam was focused on the dorsal surface of an animal’s tail to measure the latency of the tail-flick response (Columbus Instrument, Columbus, OH, USA). The recorded time to tail flick was utilized as a measure of pain threshold. The cutoff time for the heat stimulus was set at 10 sec to avoid tissue damage.
Manual Von Frey
Mechanical hypersensitivity (allodynia) was tested with von Frey filaments consisting of calibrated filaments (Dynamic Plantar Anesthesiometer, UGO BASILE, Varese, Italy; 0.4 g–7.5 g). Thirty minutes before the test, mice (n = 12 per group) were placed in elevated plastic boxes with a wire mesh floor. Beginning with the filament of 0.4 g, filaments were applied perpendicularly to the medial plantar surface of the hind paw from below the mesh floor in an ascending order until buckling of the filament occurred and maintained for approximately 2 s. Mechanical thresholds (expressed in g) corresponded to the lowest force that elicits a behavioral response (withdrawal of the hind paw) with at least two out of three applications.
Fecal Microbial Transfer (FMT)
Fecal contents from either MET (or CTRL) mice were collected and pooled after sacrifice. The fecal content was processed, as previously described.Citation38 Briefly, 200 mg of fecal extracts were suspended in 1 mL sterile PBS, filtered through 70 µM cell strainer, and centrifuged at 6000Xg for 20 min. Naïve C57 BL/6 3-week male recipient mouse were pretreated with ABX (Bacitracin 10 mg/ml, Metronidazole 10 mg/ml, Neomycin 40 mg/ml, Vancomycin 4 mg/ml and Pimaricin 24 μg/mL) for one day, after which tail flick assay was performed to obtain baseline readings. Mice were randomized into 2 treatment groups (CTRL FMT or MET FMT) based on baseline readings to ensure no statistical difference between groups, or removed from experiment if considered an outlier. Antibiotic pre-treatment was followed by oral gavage with 200 µL of freshly prepared fecal suspension for five consecutive days before tail flick analysis on day 7. Mice were transferred to clean cages after FMT given mice coprophagic behavior.
Luminex cytokine bead array
Blood was collected by cardiac venipuncture, and serum was isolated and stored at −80°C after centrifugation at 6,000 rpm for 10 min. Serum concentrations of a panel of cytokines and chemokines were measured using the ProcartaPlex Mouse Cytokine and Chemokine Panel 1 (26-plex) (Thermo Fisher Scientific, Vienna, Austria) according to the manufacturer’s instructions. The panel included the following proteins: IFN-γ, IL-12p70, IL-13, IL-1β, IL-2, IL-4, IL-5, IL-6, TNF-α, IL-18, IL-10, IL-17A, IL-22, IL-23, IL-27, IL-9, GRO-α, IP-10, MCP-1, MCP-3, MIP-1α, MIP-1β, MIP-2, RANTES, eotaxin, and GM-CSF.
RT2 profiler
The Mouse Pain: Neuropathic & Inflammatory RTCitation2 Profiler PCR Array (Gene Globe ID: PAMM-162Z) was used to profile the expression of 84 key genes related to the transduction, maintenance, and modulation of pain responses according to the manufacturer’s instructions. Briefly, total RNA from midbrains of offspring was extracted using TRIzol (Invitrogen). cDNA was synthesized using the RT2 First Strand Kit (Qiagen) following manufacturer’s protocol. Quantitative real-time polymerase chain reaction was performed using RT2 Profiler PCR Arrays containing pre-designed primer sets in combination with LightCycler® 480 SYBR Green I Master (Roche). PCR reaction was performed on Roche LightCycler 96 (Roche, CA, USA) using a 3-step cycling program: 95°C for 10 min, 40 cycles at 95°C for 15 s, 55°C for 30 s, and 72°C for 30 s, followed by a melting temperature to check the amplification curve. The fold change and relative expression levels to reference were calculated according to the previously described ΔΔCt method, using an online data analysis RT2 Profiler™ PCR Array Data Analysis software: https://geneglobe.qiagen.com/us/analyze). The expression levels of target genes were normalized relative to the values automatically selected from the entire catalog array that yielded Geometric means with minimal variation between samples (Actb, P2rx7, Kcnq2, Comt, Ednra) and quantified against controls. A heat map was constructed to provide a graphical representation of the gene expression profile of experimental groups. Control offspring (generated from dams receiving saline injections) were used as a reference. A two-fold change (FC) was set as a cutoff for upregulation and 0.5 for downregulation. To represent fold-change results in a biologically meaningful way, fold regulation values were calculated for FC below 1, as − 1/fold change.
Histological evaluation
Paraffin-embedded colon tissues were cut into 5-μm sections, dewaxed in xylene for 10 min, and dehydrated in gradient alcohol. Hematoxylin and eosin (H&E) staining was performed by The Division of Comparative Pathology according to standard protocols. Each colonic section was blindly examined and scored using a modified histological scoring system, previously describedCitation39 ranging from 0 to 9 points based on 3 criteria: epithelial damage, inflammation, and epithelial expulsion to lumen, each scored from 0 to 3.
FITC Dextran
To access in vivo intestinal permeability, 500 mg/kg of FITC-dextran (wt 4000; Sigma-Aldrich) was orally gavaged into mice 4 h prior to blood collection. After sacrifice, serum FITC dextran fluorescence intensity was measured by SpectraMax® i3×. (excitation wavelength 488 nm; emission 520 nm).
Opioid withdrawal scoring
Mice were filmed for spontaneous withdrawal signs for 15 min while placed in a plexiglass chamber. Total withdrawal score was calculated after manually scoring the total number of grooming, wet dog shakes, and jumping events by an investigator blinded to treatment conditions.
Pup retrieval time
Pup retrieval time was assessed at postnatal day 1. Pups were placed into one corner of the cage opposite to the dam’s nest site. Pup retrieval was defined as latency to pick up a pup by mouth and was evaluated by manual scoring by two reviewers blinded to experimental group. Each data point represents the average latency to retrieval for 3–5 pups by their birth mother, and each experiment includes pup retrieval data from at least five independent dams. Cutoff time for latency for pup retrieval was set at 120 s.
16S rRNA gene sequencing
DNA was extracted from fecal contents under aseptic conditions using DNeasy 96 PowerSoil Pro QIAcube Kit with QIAcube HT liquid-handling machine (Qiagen, Maryland, USA). Two extraction controls were included to remove potential contamination from samples. Sequencing was performed by the University of Minnesota Genomics Center. The hypervariable V4 region of the 16S rRNA gene was PCR amplified using the forward primer 515F (GTGCCAFCMGCCGCGGTAA), reverse primer 806 R (GGACTACHVGGGTWTCTAAT), Illumina adaptors, and molecular barcodes to produce 427 base pair (bp) amplicons. Amplicons were sequenced with the Illumina MiSeq v.3 platform, generating 300-bp paired-end reads. The extraction controls could not be PCR amplified and were therefore excluded from the sequencing process.
RNA quantification
Whole brain was isolated from 3-week-old offspring, and immediately flash frozen in liquid nitrogen and stored at −80°C. Total RNA was isolated using the TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s recommendations. Sample quality check was achieved using 1% agarose gel electrophoresis to assess for RNA degradation and contamination, NanoPhotometer® spectrophotometer (IMPLEN, Westlake Village, CA, USA) reading to assess RNA concentration and purity, and the Qubit® RNA Assay Kit (Life Technologies, CA, USA) to measure the RNA concentration. RNA integrity was evaluated with the RNA Nano 6000 Assay Kit of the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA). Samples passing quality control proceeded to polyA enrichment library preparation using the NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA), following manufacturers’ protocol and 2 × 150 bp paired-end sequencing was performed using the Illumina HiSeq 4000 platform by Novogene Bioinformatics Technology Co., Ltd., in Beijing, China. Reads were aligned to Genome Browser assembly ID: GRCm39.
Differential expressed genes (DEG) screening, and pathway enrichment analysis
The feature table for transcriptome was used to calculate differentially expressed genes (DEGs) between pairwise groups using the DESeq2 package (ver. 1.38.2) with R version 4.2.2 (2022-10-31). Resulting p values were adjusted using the Benjamini and Hochberg approach to control false discovery rates (FDRs). Genes with adjusted P <.05, and log2 fold change ≥ 0.5 were considered differentially expressed. and the differential expression of transcripts between different groups was calculated and analyzed using the DESeq2. Heatmaps were generated using the ComplexHeatmap v 2.14.0 package for R. Differentially expressed genes subsequently analyzed using QIAGEN Ingenuity Pathway Analysis (IPA) to predict functional annotations, canonical pathways. The threshold of DEG was set to |log2FoldChange| ≥ 0.5 & p-value <0.05. Fisher’s exact test was utilized in all those analyses to identify the overrepresented proteins or genes with a p-value of less than 0.05. In addition to identifying the canonical pathways associated with different neurotransmitter systems including the opioid, serotonergic, and dopaminergic systems, other functions associated with DEG including behavior, nervous system development and function, cell–cell signaling, and cellular assembly and organization were also identified.
Microbiome analysis
Demultiplexed sequence reads were clustered into amplicon sequence variants (ASVs) with the DADA2 package (version 1.26.0)Citation40 implemented in R (version 4.1.0). The steps of the DADA2 pipeline include error filtering, trimming, learning of error rates, denoising, merging of paired reads, and removal of chimeras. Filtering function filterAndTrim was used with filtering parameters: maxN = 0, truncQ = 2, rm.phix=TRUE and maxEE = 2. For paired end reads truncLen 200, 190 was used to overlap after truncation to merge for forward and reverse reads, respectively. Parametric error model (err) was used to learn error rate. These error rates were used to infer unique reads from the samples. Merging was performed by aligning the denoised forward reads with the reverse-complement of the corresponding denoised reverse reads, and then constructing the merged “contig” sequences. Merged data frames were used to construct an amplicon sequence variant (ASV) table, and a higher-resolution version of the OTU table was produced by traditional methods. Identification and removal of chimeric ASVs was further performed. Taxonomy assignment was done using function assign. Taxonomy to the SILVA v138 reference database including species with 99% similarity and for species exact match was executed to improve accuracy. ASV and taxonomy tables were imported in MicrobiomeAnalystCitation41 for generating alpha and beta diversity plots, taxonomy bar plots and linear discriminant analysis effect size (LEfSe)Citation42 plot. A minimum count of 4 and prevalence filter 20% was set for low count filter. ASVs with less than 10% variation measured by inter-quantile range were also filtered. Total sum scaling was used for normalization. The threshold on the logarithmic LDA score for discriminative features was set to 2. BugBaseCitation43 is a microbiome analysis algorithm that predicts high-level phenotypes present in microbiome samples using 16S amplicon data. The BugBase phenotype predictions were implemented using the online web app (https://bugbase.cs.umn.edu/).
Transcriptome and microbiome correlation network
Correlation analysis between microbiome and transcriptome was done using R package Hmisc (v 4.7–2). Significant differentially expressed genes with p-value <0.05; LFC ≥ 0.5 and genus, species with p-value <0.05 were used. The co-occurrence among taxa and genes was calculated on the basis of the relative abundances by Spearman’s rank correlation coefficient (P <.05), as previously doneCitation44. The network layout was calculated and visualized using a organics circular layout by the Cytoscape software. Only edges with correlations greater than 0.5 were shown for bacteria/fecal metabolites, and unconnected nodes were omitted. Correlation coefficients with a magnitude of 0.5 or above were selected for visualization in Cytoscape (version 3.9.1). The size of the nodes represents the abundance of these variables. Red and green dots indicate the increased and decreased relative abundances of variables relative to controls, respectively. Bacterial species annotated to the genus or species level are marked. Edges between nodes indicate Spearman’s negative (light blue) or positive (light red) correlation; edge thickness indicates range of P value (P < 0.05).
Statistical analysis
Statistical analysis was performed using R software (version 4.1.0) with Phyloseq package 1.38.0. Relative abundance was calculated for ASVs. For normally distributed data t test were used; otherwise, the Mann–Whitney test was used. The distribution of diversity indices was plotted as box plots. Beta diversity analysis was performed with the Bray-Curtis metric to analyze the dissimilarly between the groups. Significance testing was performed using permutation testing (1234 interactions) with the vegan package. All diversity metrics were calculated using the R vegan package. Plots were generated using the ggplot2 package. GraphPad 9.3.1 software (GraphPad Software Inc., San Diego, CA, USA) was used to plot additional data. Data are presented as means ± SD, with data points from individual animals (n). All experiments were randomized to use animals from at least 3 different litters per experimental group. All experiments utilized a sample size of at least 5 animals. For other datasets, student t test or 2-way ANOVA was used (GraphPad Prism). Analysis of variance for repeated measures with Tukey’s post hoc test was used for temporal comparisons in any given group. Post-hoc tests were only run if F achieved the necessary level of statistical significance. P <.05 was considered to be statistically significant.
Materials
Hydromorphone and methadone were obtained from National Institutes of Health [NIH]/National Institute on Drug Abuse [NIDA] (Bethesda, MD).
Results
Gestational opioid exposure alters maternal fertility and behavior
Prenatal methadone- or saline-exposed offspring were generated by subcutaneously injecting 12-week-old female C57 BL/6 mice with an escalating dose ramp of hydromorphone (or saline) for two weeks prior to pregnancy, after which females were mated with drug-naïve males; pregnant dams were maintained on methadone (or saline) until weaning of pups at 3 weeks of age and are referred to as methadone-exposed or control mothers (). Hydromorphone dependency was established by discontinuing hydromorphone after 2 weeks of treatment and assessing for withdrawal symptoms; total withdrawal score was significantly higher in hydromorphone withdrawn animals than in saline withdrawn (Sup Fig S1A). Methadone dosage was chosen based on past studies to minimize maternal and fetal withdrawal.Citation45,Citation46 To confirm, 11-h post a.m. methadone dose (aka 1 h before the p.m. methadone dose) animals were evaluated for withdrawal behavior. No significant difference in withdrawal score was detected between methadone-maintained dams and saline (control) maintained dams (Sup Fig S1B).
Figure 1. Maternal opioid exposure during gestation alters maternal gut microbiota.
Previous studies have reported changes in fertility and fecundity with gestational opioid useCitation47. To evaluate how maternal opioid exposure during pregnancy affects fertility, on estrous day 15, dams were sacrificed to evaluate number of placentas. Maternal opioid exposure significantly decreased the number of placentas between methadone-exposed or control dams (Sup Fig S1C). The number of live births (evaluated at postnatal day 1) was also significantly lower in methadone-exposed dams relative to controls (Sup Fig S1D and S1E). No sex differences were noted between control or methadone-exposed dams, though there was a trend toward increased females in methadone-exposed dams. To evaluate how gestational opioid exposure affects maternal behavior, pup retrieval time was assessed (Sup Fig S1F) 30 min or (Sup Fig S1G) 6-h post methadone (or saline) injection. Thirty minutes post-methadone injection, pup retrieval time was significantly higher in methadone dams, with methadone dams averaging 109.29 s to attend to pups while control dams averaged about 7.495 s (Sup Fig S1F). Six hours post methadone injection, pup retrieval time still remained significantly higher in methadone-exposed dams, though average pup retrieval time averaged 30.00 seconds in methadone dams and 7.17 seconds in control dams (Sup Fig S1G), indicating that maternal opioid exposure significantly affects maternal behavior. Weight of pups was not significantly different as measured on postnatal day 2, 7, 14, or 21 (Sup Fig S1H). Collectively, these data show gestational opioid exposure results in significant alterations to maternal fertility and behavior.
Maternal opioid exposure during gestation disrupts maternal and neonatal gut microbial composition
Opioids have been demonstrated to cause gut-dysbiosis in a number of studies (reviewed inCitation48. To evaluate changes in gut microbiome diversity and composition in methadone-exposed or control dams, Illumina sequencing of microbial 16S-rRNA genes was performed to identify differentially enriched taxa and unique microbial signatures. Maternal opioid exposure did not significantly change α diversity per Shannon index in fecal samples of control or methadone-treated dams collected at weaning (). Notably, significant differences in β diversity were observed at this time point () per Bray-Curtis dissimilarity index, with distinct clustering observed between fecal samples from methadone-treated and control dams (PERMANOVA: F = 4.8039 R2 = 0.243, p =.002). In particular, enrichment of Akkermansia and Bacteroides were observed in methadone-treated mothers, whereas Turicibacter was significantly enriched in control mothers (). Using BugBase, high-level potential phenotypes were predicted among methadone-exposed and controlled dams. Methadone-exposed dams showed significantly enriched aerobic, biofilm forming bacteria, and gram-negative bacteria relative to control, and decreased relative abundance of gram-positive bacteria (). There were no predicted significant differences in the relative abundance of anaerobic bacteria, bacteria containing mobile elements, facultative bacteria, potentially pathogenic bacteria, or stress tolerant bacteria between groups (Sup Fig S2). The microbial metagenome was predicted with the PICRUSt algorithm, and functions were categorized with KEGG pathways to further elucidate the specific changes in microbial pathways (). In total, 7 KEGG level 2 pathways were predicted among all intestinal samples (). Pathways related to the nervous system, cellular processes and signaling, infectious diseases, lipid metabolism, genetic information processing, and the excretory system were positively correlated with samples from methadone-exposed dams (). On the other hand, pathways related to enzyme families were positively correlated with samples from control dams (). Cumulatively, these data show significant disturbances to the gut microbiota in dams with gestational opioid use.
Dysbiosis of the maternal gut microbiota during pregnancy has increasingly been associated with dysbiosis in neonates.Citation29,Citation31,Citation32 To determine the impact of gestational opioid exposure on neonatal gut microbiota, fecal samples from the offspring of methadone-exposed or control dams were collected. After quality control of raw sequencing, 445,631 unique ASVs were identified among all samples (Supplemental Table S1). Prenatal methadone exposure did not change α diversity (measured by Shannon, Observed, Simpson, or Chao1 indices) relative to control offspring (). However, significant differences in β diversity were observed using the Bray-Curtis dissimilarity index (). As demonstrated in the principle-coordinate analysis (PCoA) plot, the fecal samples of the prenatally methadone-exposed (MET) and control (CTRL) offspring clustered distinctly (PERMANOVA: F = 4.06544, R2 = 0.202, p =.001) (). At the phylum level, prenatal methadone exposure significantly increased the abundance of Bacteroidota (p =.027) and Verrucomicrobiota (p = 4.6E–5) and decreased the abundance of Firmicutes (p =.027) relative to control offspring (Sup Fig. S3). At the genus level, 15 differentially abundant taxa between prenatal methadone and control samples were identified. Significant decreases in the relative abundance of genera Lachnospiraceae A2, Anaeroplasma, Clostridium sp. ASF356, Bifidobacterium, Enterorhabdus, Erysipelatoclostridium, Family XIII UCG-001, Lachnospiraceae UCG-001, and Lactobacillus were found in fecal samples from prenatal methadone-exposed offspring relative to controls (). In contrast, the relative abundance of genera Akkermansia, Alistipes, Bacteroides, Butyricicoccus, Clostridium sensu stricto 1, and Lachnoclostridium was significantly enriched in prenatal methadone-exposed samples relative to controls (). To predict high-level phenotypes between MET and CTRL samples, BugBase analysis was used which predicted that the relative abundance of potentially pathogenic, gram negative, aerobic and biofilm-forming bacteria was significantly higher in MET offspring relative to controls (). Conversely, the relative abundance of bacteria containing mobile elements, facultative bacteria and gram-positive bacteria were significantly higher in CTRL offspring relative to MET offspring (). MET offspring followed the same predicted trend for the relative abundance of gram negative, aerobic, biofilm-forming, and gram-positive bacteria as MET dams. Surprisingly, the relative abundance of potentially pathogenic bacteria was predicted to be enriched in MET offspring though there were no significant differences predicted in dams, suggesting that dysbiotic alterations to the gut microbiome during pregnancy may promote more aberrant microbial seeding in neonates.
Figure 2. Maternal opioid exposure during gestation alters neonatal gut microbiota.
Prenatal methadone exposure increases sensitivity to thermal and mechanical pain in male offspring, which is mediated by the microbiome
Recent advances in research have described the importance of the gut microbiota in neurodevelopment and behavior through the gut-brain-axis, representing bidirectional communication between the central and enteric nervous system.Citation49 Dysregulation of this axis has been associated with adverse health outcomes, including visceral, mechanical, or thermal hypersensitivity, stress-induced hyperalgesia, allodynia, inflammatory pain and functional disorders.Citation22 To determine the effect of prenatal methadone exposure on thermal pain sensitivity, tail flick latency time was assessed in MET or CTRL 3-week-old male offspring (). Tail flick latency time was significantly reduced in MET offspring compared to CTRL (). Mechanical threshold was also assessed in MET or CTRL 3-week-old male offspring and consistently revealed decreased mechanical threshold in MET offspring (). Interestingly, this hypersensitivity to thermal pain in MET offspring persisted until adulthood when animals were tested at 12 weeks of age, though no differences in mechanical threshold was noted at this timepoint between groups (Sup Fig S4). To test the hypothesis that alterations in the microbiome may mediate pain sensitivity in MET offspring, fecal microbiota transplantation (FMT) with feces from prenatally opioid-exposed or CTRL offspring was gavaged into 3-week-old naïve male offspring, after pretreatment with antibiotics (). As expected, no significant differences were observed between CTRL-assigned and opioid-assigned mice. However, opioid FMT to naïve 3-week-old offspring resulted in significantly reduced latency time to flick relative to CTRL FMT (). The mean percent change in tail flick latency in the CTRL-FMT was + 5.39%, whereas it was −16.26% in the Opioid-FMT group. The significant reduction of tail flick latency time in naïve controls with the addition of feces from MET offspring suggests that an opioid-induced dysbiotic gut microbiome is sufficient to modulate pain sensitivity.
Figure 3. Prenatal opioid exposure increases sensitivity to thermal and mechanical pain in 3-week-old male offspring.
To further validate the role of the microbiome in mediating pain sensitivity in MET offspring, we next attempted to modulate the microbiome in MET or CTRL offspring with probiotic administration in dams. Based on the decreased abundance of Lactobacillus and Bifidobacterium in MET offspring (), the VSL#3 probiotic containing four strains of Lactobacillus (Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus casei, and Lactobacillus delbrueckii subspecies bulgaricus), three strains of Bifidobacterium (Bifidobacterium breve, Bifidobacterium longum, and Bifidobacterium infantis), and one strain of Streptococcus (Streptococcus salivarius subspecies thermophilus) was administered to dams (). There were no significant differences in number of placentas or offspring sex distribution with probiotic administrations in dams, relative to vehicle (Sup Fig S1C and E). However, probiotic administration in dams showed limited improvement in number of live births with significant differences in live births still remaining even with probiotic administration in dams (Sup Fig S1D and E). Additionally, probiotic administration did not significantly change maternal behavior relative to vehicle – pup retrieval time still remained significantly higher 30 min or 6-h post-methadone exposure (Sup Fig S1F and G).
Figure 4. Supplementation with VSL#3 cocktail in dams alters maternal gut microbiome at weaning.
To determine whether probiotic administration in dams would lead to alterations in the maternal gut microbiome, 16S sequencing on fecal samples was performed in methadone and control dams receiving probiotics or vehicle. Probiotic administration in dams did not significantly change α diversity per Shannon index in fecal samples of either control (ControlMom vs ControlMomPro) or methadone-treated dams (MethaMom vs MethaMomPro) collected at weaning (). Interestingly, significant differences in β diversity were observed at this time point () per Bray-Curtis dissimilarity index, with distinct clustering observed between fecal samples from probiotic-treated relative to untreated control (ControlMom vs ControlMomPro, PERMANOVA: F = 11.337 R2 = 0.55745, p =.005) or methadone-exposed dams (MethaMom vs MethaMomPro, PERMANOVA: F = 16.939 R2 = 0.53036, p =.002). Notably, in both control and methadone-exposed dams, probiotics administration relative to vehicle was predicted to decrease potentially pathogenic, aerobic, biofilm forming bacteria, gram-negative, and stress-tolerant bacteria and to increase facultative bacteria, gram-positive bacteria and bacteria containing mobile elements per BugBase analysis (). Additionally, probiotic administration relative to administration of vehicle differentially enriched Lactobacillus and Streptococcus (amongst other beneficial bacteria) in both control and methadone-exposed dams (). These were associated with alterations in several KEGG pathways, amongst which pathways related to carbohydrate metabolism and enzyme families were positively correlated with samples from probiotic treated dams. However, pathways related to lipid metabolism, biosynthesis of other secondary metabolites, glycan biosynthesis and metabolism, endocrine system, transport and catabolism, metabolism of cofactors and vitamins, amino acid metabolism, and the excretory system were negatively correlated to probiotic treated dams (). Interestingly, probiotic treatment in methadone dams was negatively correlated to neurodegenerative diseases and pathways related to the nervous system relative to methadone dams gavaged with vehicle (), though this was not observed with probiotic treatment in control dams relative to control mothers gavaged with vehicle ().
Next, we aimed to determine whether probiotic administration in dams could in fact alter the neonatal gut microbiome. Interestingly, maternal VSL#3 supplementation significantly increased the abundance of Lactobacillus and Bifidobacterium in prenatally methadone-exposed (MET+PRO) and control (CTRL+PRO) offspring relative to offspring whose mothers had not received probiotics (). Interestingly, for offspring whose mothers had received probiotics, the abundance of Bifidobacterium was significantly higher in MET+PRO offspring than in CTRL+PRO (). Probiotic treatment in dams significantly altered neonatal alpha and beta diversity in neonatal fecal samples to promote more commensal and less pathogenic bacteria, with profound changes in several KEGG pathways in the offspring of dams treated with probiotics relative to vehicle (, Sup Fig S5, and Sup Fig S6). Still between MET+PRO relative to CTRL+PRO offspring, significantly increased abundance of Turicibacter, Dorea, and Butyricicoccus, as well as decreased abundance of Streptococcus and Staphylococcus, was still noted (Fig. S5D and S5E), which was positively correlated in MET+PRO offspring to 1 KEGG pathway, Xenobiotics Biodegradation and Metabolism (). Still, no significant differences in aerobic, anaerobic, mobile element-containing, facultative, biofilm-forming, gram negative, gram positive, or potentially pathogenic bacteria were noted between CTRL+PRO vs MET+PRO 3-week-old male offspring (). This demonstrates the beneficial effects of maternal probiotics during pregnancy and weaning to the neonatal gut microbiome postnatally.
Figure 5. Supplementation with VSL#3 cocktail in dams alters neonatal gut microbiome and rescues hypersensitivity to thermal and mechanical pain in 3-week-old methadone-exposed offspring.
To evaluate whether the gut microbiome may mediate sensitivity to thermal pain in methadone-exposed offspring, thermal pain withdrawal threshold in 3-week-old CTRL+PRO and MET+PRO offspring was subsequently assessed. VSL#3 administration in dams significantly increased latency to tail flick in MET+PRO compared to MET offspring (p <.05) (). Surprisingly, no significant increase in tail flick latency was observed in CTRL offspring compared to CTRL+PRO (). Notably, maternal probiotic administration eliminated differences in tail flick latency in CTRL and MET offspring, with no differences in tail flick latency observed between CTRL+PRO and MET+PRO (). Similarly, probiotic administration in dams was able to rescue differences in mechanical threshold between CTRL and MET offspring, with no differences in mechanical threshold observed between CTRL+PRO and MET+PRO (). This provides further evidence of the role of the gut microbiome in mediating thermal and mechanical pain hypersensitivity in MET offspring.
While probiotic engraftment in adults has had mixed results, several studies have posited the neonatal gastrointestinal tract may be more permissive to colonization with supplemented bacteria due to greater niche availability and the lack of an established adult microbiomeCitation50–53. However, whether probiotic strains can establish long-term colonization in prenatally opioid-exposed offspring, and if so, what the impact of this colonization is on thermal pain sensitivity, has not been elucidated. To determine whether long-term engraftment of Lactobacillus and Bifidobacterium could be achieved in offspring following maternal VSL#3 supplementation, the relative abundance of these microbes were assessed in 12-week-old offspring (Sup Fig S7). While the abundance of Lactobacillus and Bifidobacterium in offspring was less than that observed during maternal supplementation in 3-week-old offspring, still no significant difference in the alpha diversity or the abundance of these two bacteria was noted in 12-week-old CTRL+PRO and MET+PRO offspring (Sup Fig S7A-C). Still, the beta diversity per Bray-Curtis dissimilarity index was significantly different between 12-week-old MET+PRO and CTRL+PRO offspring (PERMANOVA: F = 6.8929, R2 = 0.2769, p = 0.001), with enrichment of Allobaculum and Roseburia, and depletion of Dehalobacterium, Sutterella, and Adlercreutzia in 12-week-old MET+PRO offspring relative to CTRL+PRO per LEfse (Sup Fig S7D and E). The relative abundance of facultative bacteria was predicted to be significantly higher in 12-week-old MET+PRO offspring (Sup Fig S7G). KEGG pathways related to translation, replication and repair, nucleotide metabolism, genetic information and processing, and metabolic diseases were positively correlated with MET+PRO offspring during this time (Sup Fig S7F). Notably, latency to tail flick in 12-week-old offspring was not significantly different between MET+PRO vs CTRL+PRO. Still, while maternal probiotic supplementation increased latency to tail flick in 3-week-old MET+PRO vs MET offspring, no increase in tail flick latency was observed at 12 weeks between CTRL+PRO vs CTRL or MET+PRO vs MET (Sup Fig S7H), suggesting a waning effect of probiotics.
Together, these data utilizing FMT and maternal probiotic administration show that increased thermal and mechanical pain in MET offspring is mediated by the microbiome.
Prenatal methadone exposure elevates IL-17a in systemic circulation, which is ameliorated with maternal probiotic administration
Though clarifying mechanisms have not been fully elucidated, it has been posited that gut microbiota-derived metabolites including short chain fatty acids (SCFAs), neurotransmitters, bile acids, and inflammatory mediators are directly involved in pain transmission and modulation through neural (i.e., vagus, enteric nervous system and spinal nerves), endocrine (cortisol) and immune (cytokines) pathwaysCitation49,Citation54. Previous studies have reported increased levels of inflammatory cytokines, including IL-1β, IL-6, and TNF-α, in the serum of prenatal opioid-exposed rats at postnatal day 10Citation55, though only IL-1β remained elevated at postnatal day 21. We hypothesized that microbial-derived inflammatory products may contribute to the observed pain response and used multiplex electrochemiluminescence to determine concentrations of 26 cytokines and chemokines in 3-week-old CTRL, MET, CTRL+PRO, or MET+PRO serum samples. An increased concentration of IL-17a was detected in the serum of MET offspring compared to CTRL at 3 weeks of age (), though no other changes in chemokines or cytokines were detected at this age (Sup Fig S8). Notably, no differences in the concentration of IL-17a were observed in CTRL+PRO and MET+PRO offspring ().
Figure 6. Prenatal opioid exposure increases IL-17 in systemic circulation, which is attenuated by maternal probiotic administration.
Previous reports have informed that the intestinal barrier of 3-week-old neonatal mice is significantly more permeable than that of adults even to macromolecules as large as 70kDa due to altered tight junction localization and protein expression (e.g., decreased ZO-1, ZO-3, occludin, and JAM-A) in infant tissueCitation56. To confirm these findings in our neonatal mice and to determine whether MET offspring have increased permeability relative to CTRL, FITC-Dextran was gavaged to 3-week-old CTRL or MET mice to assess for intestinal permeability. As expected, both CTRL and MET offspring displayed significantly elevated levels of FITC-Dextran in serum (), indicating enhanced neonatal intestinal permeability. However, no significant differences in the serum concentration of FITC-Dextran were found between CTRL and MET animals ().
Commensal gut microbiota play key roles in maintaining gut homeostasisCitation57,Citation58. Additionally, preclinical studies in adults have shown that opioid-induced gut dysbiosis has adverse consequences on gut histology, including epithelial cell injury as well as apical villous expulsion and inflammatory cell influx into the lumen.Citation38,Citation39,Citation59,Citation60 As MET mice had significantly altered fecal microbiota, we next investigated whether alterations to the gut microbiota conferred changes to colonic histology, using established histological criteria based on epithelial damage, inflammation, and epithelial expulsion to lumen, previously describedCitation39 (). Modest changes were observed in H&E-stained colonic sections from MET and CTRL offspring (). Quantitative analysis of histological scores showed increased inflammatory infiltration in colonic samples from MET offspring compared to CTRL. Notably, there was no significant difference in histological score between MET+PRO vs CTRL+ PRO offspring, which both were representative of normal colonic architecture.
Together these data show increased gut permeability in both CTRL and MET mice, with increased histological damage and elevated levels of IL-17a in the serum of MET offspring, both of which were attenuated in offspring by maternal probiotic administration.
Prenatal opioid exposure alters neuropathic and inflammatory pain-related genes in the brain
It has been established that chemokines and cytokines released during inflammatory processes activate intracellular downstream signal pathways (i.e., cyclic adenosine monophosphatase, protein kinase A (PKA), protein kinase C (PKC)) leading to phosphorylation of receptors and ion channels in primary sensory neurons which results in neuronal hyperexcitability and peripheral sensitization.Citation22,Citation54 To determine how prenatal opioid exposure globally affects transcriptional signatures in the brain, the transcriptome expression of whole brain samples in MET or CTRL 3-week-old male offspring was assessed by RNA-sequencing. The transcriptome profile of brain samples from MET or CTRL offspring were distinct, according to the results of principal component analysis (). A total of 3516 differentially expressed genes (DEG) were identified, of which 1671 were upregulated and 1845 were downregulated, between the MET and CTRL groups (). To determine the biological relevance of DEG (FDR adjusted) associated with prenatal methadone exposure, canonical pathways, molecular and cellular functions, and physiological functions associated with differentially expressed genes were analyzed by Ingenuity Pathway Analysis (IPA). A total of 96 canonical pathways were significantly altered (p <.05) by prenatal methadone exposure (Supplemental Table S2), of which 23 canonical pathways were selected for their key roles in neurological and immune function as well as behavior (). IPA analysis showed inhibition of the 11 following pathways: G-protein coupled receptor (GPCR) signaling, CREB signaling in neurons, phagosome formation, S100 family signaling pathway, synaptogenesis signaling pathway, antioxidant action of Vitamin C, oxytocin signaling pathway, GPCR-mediated nutrient sensing in enteroendocrine cells, Gαi signaling, dopamine-DARPP32 feedback in cAMP signaling, and opioid signaling pathway. The 12 activated pathways were glutamate receptor signaling, GP6 signaling, neuropathic pain signaling in dorsal horn neurons, synaptic long-term potentiation, synaptic long-term depression, endocannabinoid neuronal synapse, protein kinase A signaling, wound healing signaling, corticotropin releasing hormone signaling, neuroinflammation signaling, neutrophil extracellular trap signaling, and signaling by Rho family GTPases (). These correlated to significant increases in nociception, sensation, and sensory system development, as well as significant decreases in neurotransmission, learning, memory, and cognition in MET offspring compared to CTRL per Disease and Function pathway analysis from the IPA Knowledgebase Database (Supplemental Table S3). Notably, these data show increases in intracellular downstream signal pathways involved in pain sensitization, which are consistently reflected by activation of neuroinflammation and neuropathic pain pathways.
Figure 7. Maternal opioid exposure alters gene expression profile in whole brain of 3-week-old offspring.
To identify significant associations between gut microbiota and the brain transcriptome, correlation analysis was next performed to create a co-occurrence network from identified DEG and the relative abundance of different bacterial genera in MET vs CTRL offspring (Sup Fig. S9). Co-occurrence analysis revealed that several bacterial genera formed strong and broad co-occurring relationships with brain transcripts (Sup Fig. S9); in particular, Lactobacillus, which was significantly depleted in MET offspring relative to CTRL, was found to be the microbe most significantly correlated with the most DEG between opioid-exposed offspring and controls (Sup Fig S9). Notably, alterations in gut microbial composition observed with prenatal methadone exposure were correlated with alterations in the expression of genes related to the opioid signaling pathway, neuropathic pain signaling pathway in dorsal horn neurons, and neuroinflammation signaling pathway ().
To further clarify the role of the gut microbiota in mediating gene expression, RNA-sequencing was performed on brains from 3-week-old MET+PRO or CTRL+PRO and compared to MET and CTRL brains. Per principal component and DEG analysis, the transcriptome profile of brain samples from offspring whose mothers were administered probiotics were distinct from those administered vehicle (Fig S8A and S8B). Based on the DEG observed in CTRL vs MET offspring, probiotic administration in methadone-exposed dams was able to attenuate differences in hundreds of genes (), by altering the expression of genes related to neuroinflammation, serotonin receptor signaling, and second messenger signaling pathways (). Specifically, the transcriptome profile of brain samples from CTRL+PRO offspring were distinct relative to CTRL offspring (Sup Fig. S10A). A total of 1810 genes were identified, of which 1001 were upregulated and 809 were downregulated in CTRL+PRO vs CTRL (Sup Fig. S10B and S10C). Similarly, the transcriptome profile of brain samples from MET+PRO offspring were distinct relative to MET offspring (Sup Fig S11A). A total of 2247 genes were identified, of which 1168 were upregulated and 1079 were downregulated in MET+PRO vs MET (Sup Fig S11B and S11C). Notably, IPA analysis revealed 77 canonical pathways that were significantly altered (p <.05) by maternal probiotic supplementation in MET+PRO vs MET offspring (Supplemental Table S4). Of these, 12 were found to reverse previously noted trends in MET vs CTRL offspring. Specifically, probiotic supplementation in opioid-exposed dams was able to activate GPCR signaling, CREB signaling in neurons, phagosome formation, S100 family signaling pathway, synaptogenesis signaling pathway, antioxidant action of Vitamin C, oxytocin signaling pathway, and opioid signaling pathway in their offspring, which were inhibited in MET offspring relative to CTRL (Sup Fig S11D). Furthermore, probiotic supplementation also led to inhibition of the following previously activated pathways in MET offspring relative to CTRL: neuropathic pain signaling in dorsal horn neurons, endocannabinoid neuronal synapse, protein kinase A signaling, and neutrophil extracellular trap signaling (Sup Fig S11D). These correlated to significant increases in neurotransmission, learning, memory, and cognition as well as significant decreases in anxiety and sensation in MET+PRO offspring compared to MET per Disease and Function pathway analysis from the IPA Knowledgebase Database (Supplemental Table S5). Probiotic supplementation in CTRL+PRO offspring relative to CTRL also altered the transcriptomic profile, including activation of GPCR signaling, synaptogenesis signaling pathway, endocannabinoid neuronal synapse, protein kinase A signaling, and GPCR-mediated nutrient sensing in enteroendocrine cells, and inhibition of neutrophil extracellular trap signaling (Sup Fig. S10D, Supplemental Table S6 and S7). This highlights the benefits of the commensal microbiota through maternal administration of VSL#3 probiotic on host physiology and brain function in offspring.
Figure 8. Neonatal brain transcription networks altered by maternal probiotic administration.
As an additional validation of the importance of the gut in mediating pain responses, we next evaluated for markers of neuropathic and inflammatory pain in the midbrain of CTRL, MET, CTRL+PRO, and MET+PRO offspring using a RT2 Profiler for Mouse Pain: Neuropathic and Inflammatory to profile the expression of 84 genes involved in the transduction, maintenance, and modulation of pain responses (Sup Fig. S12A). The periaqueductal gray matter of the midbrain, in particular, plays a key role in the propagation and modulation of painCitation61–64, and was thus used to evaluate differences in gene expression levels of genes related to neuropathic and inflammatory pain pathways. Nerve growth factor (Ngf) was significantly upregulated in the midbrains of MET mice (Sup Fig. S12B). However, the fold regulation of brain derived neurotrophic factor (Bdnf), endothelin 1 (Edn1), opioid receptor mu 1 (Oprm1), sodium channel, voltage-gated, type X, alpha (Scn10a), and solute carrier family 6 (neurotransmitter transporter, noradrenaline), member 2 (Slc6a2) was significantly decreased in the midbrains of MET mice compared to CTRL (Sup Fig. S12B). Interestingly, while no significant differences were observed in the midbrains of CTRL+PRO vs CTRL offspring (Sup Fig. S12D), probiotic administration in opioid-exposed dams led to increased fold regulation of Oprm1 and 5-hydoxytryptamine (serotonin) receptor 2A (Hir2a) in their offspring (MET+PRO) relative to MET offspring (Sup Fig. S12C).
Together, these data demonstrate the importance of microbiota in regulating multiple brain developmental processes including opioid receptor signaling, neuropathic pain signaling in dorsal horns, synaptogenesis and related second messenger pathways; this further suggests that neurobiological deficits associated with prenatal methadone exposure may in part be mediated by the gut microbiome.
Cross-fostering prenatally methadone-exposed offspring to control dams attenuates hypersensitivity to thermal pain
To further confirm the role of the gut microbiome in mediating thermal pain sensitivity, a cross-fostering strategy was utilized in which MET or CTRL offspring were cross-fostered on postnatal day 3 to methadone (FMM) dams or to saline-treated (FCM) dams (). Cross-fostering allows for the determination of postnatal versus prenatal environmental contributions by examining how the microbiome of offspring cross fostered to dams of the same treatment group compares to offspring cross fostered to dams of differing treatment groups. This is particularly relevant as our data indicated alterations in maternal behavior with gestational opioid exposure (Sup Fig S1F and G), which could also influence neonatal microbial seeding. To determine whether cross-fostering could induce microbial shifts in offspring, the community structure of the gut microbiota was analyzed based on α-diversity and β-diversity indices. Changes in microbial composition were compared against the 15 differentially enriched or depleted genera between CTRL and MET offspring raised by biological mothers () to determine how fostering to surrogate dams changed this significant subset of bacteria.
Figure 9. Cross-fostering opioid-exposed offspring to control dams also rescues hypersensitivity to thermal pain in methadone-exposed offspring.
Cross-fostering did not significantly impact α diversity (measured by Shannon, Observed, Simpson, or Chao1 indices) (), except for a significant increase in CTRL FMM vs CTRL FCM () by Simpson index alone (p <.05). The relationships between microbial communities in control or methadone-exposed offspring that had been nursed by surrogate dams were visualized by PCoA plots using the Bray Curtis dissimilarity index; significant differences (p < 0.05) in β diversity were observed using the Bray-Curtis dissimilarity index for all pairwise comparisons (), indicating that cross fostering offspring to dams of different treatment groups resulted in significant changes in the microbiome of cross-fostered pups.
To parse out prenatal contributions, changes in microbial composition were examined in MET FCM vs MET FMM and in CTRL FCM vs CTRL FMM offspring. A total of 9 differentially enriched genera were identified in methadone-exposed pups fostered by saline-treated mothers (MET FCM) compared to methadone-exposed pups fostered by methadone mothers (MET FMM) (Sup Fig. S13). Cross-fostering was able to rescue significant increases in Butyricicoccus and Lachnoclostridium, and significant decreases in Family XIII UCG-001 in MET FCM relative to MET FMM (Sup Fig. S13). A total of 16 differentially enriched genera were identified in control pups fostered by methadone mothers (CTRL FMM) compared to control offspring fostered by saline-treated (CTRL FCM) mothers (Sup Fig. S14). The relative abundance of a majority of the genera in CTRL FMM pups followed the same trend as methadone-exposed offspring fostered by biological mothers (MET) when compared to controls fostered by biological mothers (CTRL) (Sup Fig. S14). Specifically, significant decreases in the relative abundance of genera Lachnospiraceae A2, Bifidobacterium, Erysipelatoclostridium and Lactobacillus, and significant increases in the relative abundance of genera Akkermansia, Alistipes, and Clostridium sensu stricto 1 were still noted in fecal samples from CTRL FMM relative to CTRL FCM (Sup Fig. S14). Surprisingly, CTRL FMM pups still retained a decreased relative abundance of Lachnoclostridium relative to CTRL FCM offspring (Sup Fig. S14), whereas it was increased in MET relative to CTRL offspring ().
Cross-fostering immediately after birth has been reported to induce a permanent microbial shift that is shaped by the nursing motherCitation65. To parse out postnatal contributions, including those from the nursing mother, microbial composition was examined in animals nursed by the same group of mothers: MET FCM vs CTRL FCM offspring, or CTRL FMM vs MET FMM offspring. A total of 21 differentially enriched genera were identified in MET FCM compared to CTRL FCM (Sup Fig. S15). MET FCM offspring resembled the microbiome of methadone-exposed offspring raised by biological mothers when compared to control offspring. Notably, among the genera found significant in MET offspring relative to CTRL (), significant decreases in the relative abundance of genera Lachnospiraceae A2, Bifidobacterium, Erysipelatoclostridium, and Lactobacillus and significant increases in the genera Akkermansia, Bacteroides, Clostridium sensu stricto 1 were observed in MET FCM samples relative to CTRL FCM offspring (Sup Fig. S15). Interestingly, Lachnoclostridium was significantly decreased in MET FCM offspring, while it was increased in MET offspring compared to CTRL (Sup Fig. S15). A total of 12 differentially enriched genera were identified in CTRL FMM pups compared to MET FMM pups (Sup Fig. S16). The majority of the genera in CTRL FMM pups followed the same trend as CTRL when compared to MET offspring. Specifically, the relative abundance of genera Akkermansia, Bacteroides, Butyricicoccus, and Lachnoclostridium were significantly decreased, while the relative abundance of genera Lachnospiraceae A2, Anaeroplasma, and Lactobacillus were significantly increased in fecal samples from CTRL FMM relative to MET FMM (Sup Fig. S16). However, the relative abundance of Clostridium sensu stricto 1 in CTRL FMM offspring followed a different trend from CTRL relative to MET offspring and was observed to be significantly enriched in CTRL FMM offspring compared to MET FMM offspring. Taken together, these data suggest that the neonatal gut microbiome can be perturbed postnatally by cross fostering to surrogate dams. However, these cross-fostering experiments also demonstrate that the relative abundance of certain microbial genera remain rather resistant to change even when offspring are nursed by dams of differing treatment groups. This was particularly evident in CTRL, but also in MET cross-fostered offspring, suggesting that both prenatal and postnatal environments, perhaps through genetic or epigenetic mechanisms, may shape the seeding and development of the neonatal gut ecosystem.
To determine the impact of cross fostering methadone or control pups to surrogate dams on thermal pain sensitivity in offspring, thermal pain withdrawal threshold in 3-week-old CTRL or MET offspring fostered to surrogate dams was subsequently assessed (). MET FMM offspring still displayed significantly decreased latency time to flick relative to CTRL FCM offspring. Interestingly, fostering methadone pups to control mothers significantly increased tail flick latency time relative to methadone pups raised by methadone mothers (MET FCM vs MET FMM) (). However, fostering control pups to methadone mothers did not significantly affect latency to flick (CTRL FMM vs CTRL FCM) (). Surprisingly, control pups fostered by methadone mothers still had increased tail flick latency relative to methadone pups raised by methadone mothers (CTRL FMM vs MET FMM) (). However, no significant differences were observed between CTRL FCM and MET FCM offspring (), which demonstrates a rescue of hypersensitivity to pain in MET offspring.
Discussion
While previous studies have shown that prenatal opioid exposure alters sensitivity to thermal painCitation20,Citation21, this study is the first to show that hypersensitivity to thermal and mechanical pain may be mediated by the gut microbiome, with modulation of the microbiome using FMT, probiotics, and cross fostering able to increase tail flick latency and mechanical threshold in methadone-exposed offspring. Importantly, our cross-fostering strategy uniquely allowed us to alter the neonatal gut microbiome postnatally and provides key insight as to how postnatal maternal factors influence microbial seeding in offspring. Additionally, for the first time, here we show how administration of probiotics to saline- or opioid-treated dams affects the neonatal gut microbiome, as well as offspring thermal and mechanical pain sensitivity. Using RNA-sequencing, we further illustrate how modulation of the gut microbiome alters the brain transcriptome, with specific changes in the expression of neuropathic and inflammatory related genes detected in midbrains of prenatally methadone-exposed animals.
We first developed a clinically relevant model of prenatal opioid exposure, in which opioid use was initiated prior to pregnancy and opioid maintenance therapy continued throughout pregnancy and weaning. As opioids have been shown to cause maternal and neonatal dysbiosis, we next analyzed microbiome diversity and composition in dams and in CTRL or MET offspring. Regarding the offspring, we found no difference in alpha diversity but observed significant differences in beta diversity with distinct clustering between CTRL and MET pups. These results are consistent with several studies, which have reported alterations in the gut microbiome with prenatal and early neonatal opioid exposure.Citation29–31,Citation66 Both briefCitation29 and chronic opioid exposureCitation30,Citation31,Citation66 have previously been reported to induce maternal and neonatal microbial dysbiosis. While these studies differed on their reports of alpha diversity, with some reporting increased alpha diversity per Chao 1 indexCitation30,Citation66 and others reporting no difference in this metric,Citation29,Citation31 all studies documented profound changes in microbial composition apparent at weaning,Citation29,Citation66 adolescence,Citation30 and adulthood.Citation30,Citation31 Collectively, this suggests that opioid exposure during critical developmental windows of pregnancy influences microbial seeding in neonates. Specifically, in our studies, we identified 15 differentially enriched bacteria between CTRL and MET offspring. Notably, decreases in Lactobacillus and Bifidobacterium in MET offspring were consistent with that found in opioid-exposed offspring in previous studies.Citation30 However, the relative abundance of Clostridium sensu stricto 1,Citation31 Butyricicoccus,Citation31 and members of the Lachnospiracea familyCitation66 differed in our study compared to others, which may be due to differences in treatment regimens, methods of sample collection, and age of tested animals.
Here, we showed that the relative abundance of Bacteroides, Butyricicoccus, Clostridium sensu stricto 1, and Lachnoclostridium was enriched in MET offspring relative to CTRL, which has been associated with increased pain from intraepidermal electrical stimulation,Citation67 anti-inflammatory effectsCitation68, visceral hypersensitivity/necrotizing enteritis,Citation69–71 and spinal cord injury/colorectal adenoma,Citation72,Citation73 respectively. We also uncovered significant decreases in the relative abundance of genera Anaeroplasma,Citation74 Enterorhabdus,Citation75 Erysipelatoclostridium,Citation75 and Family XIII UCG-001Citation75 in MET offspring relative to CTRL, which has been associated with decreased mucosal IgACitation74 and anhedonia susceptibility.Citation75 Of note, chronic pain susceptibility has been associated with anhedonic behaviorCitation76 and IgA activates T regulatory cells to promote an anti-inflammatory response.Citation22 Members of the family Lachnospiraceae and genera Clostridium, Lactobacillus, and Bifidobacterium, which were also depleted with prenatal methadone exposure, have been demonstrated to be important SCFA producers, known for their regulatory roles in synaptic transmission, neurotransmitter synthesis, immune modulation, antimicrobial resistance, and mediation of inflammatory signaling in the gut, and have been related to several pain conditions.Citation22,Citation54,Citation77 Still, it is important to note that the pathogenic or beneficial function of several gut microbes may be strain and context specific.Citation78 For instance, while Akkermanisa has been linked to improvements in inflammation and metabolic diseases, recent studies have found that an increased abundance of Akkermansia in the gut microbiome has been associated with Parkinson’s Disease, Multiple Sclerosis, and Alzheimer’s.Citation78–83 Similarly, while elevations in Alistipes have been demonstrated to have protective characteristics in diseases like colitis, it has also been shown to have pathogenic roles in other diseases like depression and anxiety.Citation84 Utilizing whole genome sequencing to identify strain-specific compositional gut-microbiota shifts and examining the activity level of differentially enriched/depleted bacteria (for example, Butyricicoccus) could further our understanding of functional changes in offspring. Additionally, while this study focused on the gut microbiome, the contributions of other microbiomes including the breastmilk, vaginal, urinary, skin, and oral will need to be clarified in mediating pain sensitivity.
Accumulating studies have shown maternal dysbiosis during critical windows in gestation can affect neonatal neurodevelopment and behavior through the gut-brain-axis.Citation49 We next validated that our animals displayed hypersensitivity to thermal and mechanical pain. Wallin et al., 2019 had previously shown increased sensitivity to pain assessed by the hot plate assay in male and female Sprague Dawley (SD) rats at postnatal day 29–39, following prenatal buprenorphine exposure.Citation20 Similarly, Chiang et al., 2015 previously reported increased pain sensitivity in the tail flick assay in male SD rats with prenatal methadone exposure at postnatal day 30 and 60.Citation21 In agreement with this, MET offspring displayed hypersensitivity to thermal and mechanical pain, with hypersensitivity to thermal pain persisting when animals were tested at 12 weeks of age. Based on our hypothesis that the gut microbiome may mediate hypersensitivity to thermal pain, FMT using feces from prenatally methadone-exposed or control animals was performed. Interestingly, FMT of feces from prenatally methadone-exposed animals into naïve 3-week-old control male mice decreased tail flick latency, showing that altering the microbiome on its own is sufficient to affect pain sensitivity. Other studies have reported beneficial effects of FMT on pain sensitivity in adults. Prior to morphine treatment, at baseline, Enterococcus faecalis administration in morphine-assigned mice was shown to significantly decrease latency time to flick, as compared to controls.Citation60 In this paradigm, the pathogenic E. faecalis was used as a biomarker of morphine-induced alterations of the gut microbiome, and this was sufficient to increase pain sensitivity in adult wild type mice.Citation60 Additionally, Lee et al., 2018 transplanted antibiotic-treated mice with saline or morphine microbiota to determine whether a morphine-associated microbiota was sufficient to produce an opioid-dependent phenotype in drug-naive animals.Citation85 Their studies showed that antibiotic-treated mice transplanted with saline control microbiota, but not morphine-associated microbiota, exhibited increased baseline thermal withdrawal threshold, further confirming that modulation of the gut microbiome can alter thermal pain sensitivity.Citation85
In our studies we additionally modulated the gut microbiome through probiotic administration in dams. Given significant reductions in Lactobacillus and Bifidobacteria in MET offspring compared to CTRL, we aimed to restore these bacteria through the VSL#3 cocktail, containing both Lactobacillus and Bifidobacteria species. Notably, VSL#3 has been shown to reduce pain in animal models of visceral hypersensitivity associated with treatment-induced changes in the expression of genes encoding for proteins involved in nociception and inflammation.Citation86,Citation87 Additionally, this probiotic has been demonstrated to have anti-inflammatory effects as well as attenuate morphine tolerance in models of chronic opioid exposure.Citation88,Citation89 As there is not yet consensus on the presence or absence of a prenatal gut microbiome.Citation90–93 we initiated probiotics in dams three days prior to parturition until weaning of pups to minimize this potential confounder. With maternal administration of VSL#3, we found a significant increase in the commensal Lactobacillus and Bifidobacteria in 3-week-old offspring, suggesting sufficient engraftment. Interestingly, our results further showed that maternal probiotic administration in CTRL+PRO pups did not significantly affect latency to tail flick (CTRL+PRO vs CTRL), though maternal administration in MET+PRO pups did (MET+PRO vs MET), leading to a rescue in hypersensitivity to pain. The absence of an increased latency to flick in CTRL+PRO vs CTRL offspring may be due to the presence of an already balanced gut ecosystem, which cannot be further improved by maternal probiotics, though this remains to be tested. Notably, we also showed that engraftment of VSL#3 probiotics may not be long lasting, as the increase latency to tail flick in MET+PRO compared to MET was lost at 12 weeks. While there were no significant changes between the relative abundance of Lactobacillus or Bifidobacteria at 12 weeks between MET+PRO and CTRL+PRO, the relative abundance of Lactobacillus was significantly reduced as compared to 3-week-old offspring. As 16S rRNA gene surveys are unable to distinguish between probiotic and endogenous strains of bacteria, future studies utilizing tagged Lactobacillus or Bifidobacteria will be needed to better elucidate the process of neonatal microbial seeding and engraftment.
Our cross-fostering studies clarified biological and environmental contributions to seeding of the neonatal microbiome. Still, offspring in our studies were cross fostered to surrogate dams at postnatal day 3 to maximize survival; as such, we cannot fully rule out early contributions from biological mothers on postnatal day 1 and 2 to microbial seeding. Future studies in which offspring may be cross fostered to nursing mothers following cesarean section delivery of offspring may better eliminate this confound. Additionally, while our studies show that modulation of the maternal microbiome may be a promising modality to alter neonatal gut microbiota toward a more balanced ecosystem, this remains to be tested in humans; while the microbiome in mouse and humans share many features, utilizing randomized control trials in which opioid-dependent mothers supplement with probiotics and examining microbial composition and diversity in offspring will be needed. Future studies should also evaluate sex differences in pain sensitivity in prenatally opioid-exposed offspring, which have been described in other models,Citation20,Citation94,Citation95 and if this is also mediated by the gut microbiome. This study examined gut microbial mediated effects on pain sensitivity in opioid-exposed males. Data from clinical and preclinical studies suggests opioid-exposed males may earlier demonstrate poorer outcomes, particularly in terms of cognitive processing and emotional regulation.Citation96 For instance, prenatally exposed males are reported to have poorer cognitive and language development, with boys scoring significantly lower than girls on the Bayley-II mental development index at 1 and 2 years of age.Citation97 In some studies, while differences in cognitive abilities between opioid-exposed males and non-exposed children were substantially larger for boys than for girls, group differences increased over time for girls, while they remained relatively stable for boys.Citation98 Others have similarly reported that male offspring may show earlier deficits in development that may be attenuated during puberty,Citation99,Citation100 though continuous risk of increased anxiety-like and depressive-like behaviors later in life has also been reported.Citation101,Citation102 Studies utilizing other prenatal exposures have further recapitulated that males may particularly susceptible to in utero exposure to cocaine,Citation103–106 methamphetamine,Citation107 alcohol,Citation108 tobacco,Citation109–111 heroin,Citation98 and maternal stress.Citation112–114 Thus, this investigation primarily focused on parsing out the gut microbial mediated effects in MET male offspring, though the effects in females still remain to be studied. This is especially relevant as emerging evidence suggest that the maternal gut microbiome may orchestrate nutrient and metabolite availability in a temporal specific manner, and that sex differences in the transport, uptake, and downstream effects of maternal microbe-derived substrates may impact neurodevelopment.Citation112 For instance, in one study maternal depletion of Lactobacillus corresponded with a sex-specific increase of obligate anaerobes, Bacteroides and Clostridium, in early prenatally stress-exposed males, but not in exposed female offspring.Citation113 These changes in bacterial composition were associated with sex-specific changes in the availability of nutrients known to influence neurodevelopment, such as histidine and glutamate.Citation113
Manipulation of the neonatal microbiome with FMT, maternal probiotics, or cross fostering to surrogate dams yielded some important observations. First, the use of FMT allowed us to conclude that pain sensitivity is mediated by the microbiome, though assuredly other factors may interact with the gut microbiome. These FMT experiments were particularly clarifying as the possibility remained that treatments administered to dams including methadone or VSL#3 might be absorbed in the gastrointestinal tract and cross physiological barriers to be distributed in body fluids, altering by themselves the neurodevelopment of offspring. Next, our studies showed that the microbiome of neonates can be modulated by their mothers, as microbiome composition in offspring and dams was significantly altered by maternal probiotic administration or in offspring by cross fostering to different mothers. Additionally, our probiotic studies highlight the fact that maternal supplementation with probiotics can rescue hypersensitivity in MET offspring. This expands the current literature on the beneficial effects of probiotics in mitigating pain in adultsCitation54 to pregnant women and their offspring. Tail-flick withdrawal data at 12 weeks combined with quantification of Lactobacillus and Bifidobacteria suggest that repeat probiotic administration in offspring post-weaning may be necessary to maintain long-term engraftment for more significant rescue of hypersensitivity. Furthermore, while we selected the VSL#3 probiotic containing species of Lactobacillus and Bifidobacteria, as these microbiota were significantly decreased in methadone-exposed offspring, it still remains to be tested whether enrichment of other commensal bacteria or depletion of other pathogenic bacteria may lead to a rescue of hypersensitivity to pain and how these probiotics exert their beneficial effects. Alongside showing that probiotics themselves were able to increase the growth of commensal gut microbiota, our studies demonstrated that probiotics also changed the relative abundance of other genera. This highlights the fact that aside from marking successful engraftment by the presence/absence of certain species, the proportion of bacterial populations relative to others is indeed vital for the growth of a healthy gut ecosystem. Last, the effect of early-life stress is especially important to consider in our model. Notably, corticotropin releasing hormone signaling was significantly upregulated in the brains of 3-week-old MET offspring relative to CTRL. Early-life stress is well known to influence microbial composition,Citation115 and can postnatally alter pain pathways. This has been described to occur via reduction of gut tight junction expression leading to increased gut permeability and translocation of bacterial products that can induce pro-inflammatory factor release from immune cells to reduce nociceptive threshold,Citation115 or via direct modulation of vagal afferent activity.Citation116 Modulation of gut microbiota by probiotics or via FMT has been documented to have a strong impact on stress related disorders such as pain and anxiety.Citation117,Citation118 In our studies, though maternal probiotic administration rescued hypersensitivity to pain in 3-week-old MET+PRO offspring compared to MET, corticotropin releasing hormone signaling was still upregulated in these animals. This suggests that either experimental treatments including maternal opioid or probiotic administration or maternal behavior in dams caused considerable stress to offspring. This gives rise to the possibility that more dramatic effects in altering neonatal microbial composition and pain sensitivity might be observed by dampening neonatal and/or maternal stress signaling. While our studies favored therapeutic interventions to modulate the microbiome in opioid-dependent mothers and hence used probiotics, evaluating pain sensitivity in prenatally methadone-exposed offspring generated from germ free animals should also be utilized to further clarify the role of the microbiome.
Lastly, we assessed transcriptomic changes in the midbrains and whole brains of MET, CTRL, MET+PRO, and CTRL+PRO offspring. Prenatal methadone exposure resulted in a large number of differentially regulated features. In agreement with our findings, others have found the following canonical pathways to be significantly dysregulated in the placenta of neonatal opioid withdrawal syndrome-affected pregnancies: endocannabinoid neuronal synapse pathway, calcium signaling, CREB signaling in neurons, synaptogenesis signaling pathway, and the opioid signaling pathway.Citation119 Disease and Function pathway analysis correlated DEG with increased nociception, sensation and sensory system development and decreased learning, memory, and cognition in prenatally methadone-exposed offspring. In line with our findings, experimental animal models have found that prenatal opioid exposure is associated with decreased levels of neurotransmitters,Citation120–122 decreased neurogenesis,Citation123,Citation124 impairments in somatosensory circuit function/compromised sensory adaptation to repeat tactile stimuli,Citation125 and altered myelination,Citation126,Citation127 brain connectivity, and brain network topology.Citation128 Additionally, impairments in learning and memory have also been noted in opioid-exposed offspring.Citation129–133 Recent meta-analyses have validated these animal findings, showing cognitive, behavioral, and sensory deficits in opioid-exposed infants.Citation134–139 For instance, a systematic review and meta-analysis of 26 studies including 1455 children exposed to prenatal opioids compared with unexposed children showed that prenatal opioid exposure was associated with lower cognitive scores in children, most notably between 6 months and 6 years of age.Citation135 Together, our data is in agreement with previous literature defining neurobiological deficits in opioid-exposed offspring. Our studies, which show that administration of maternal probiotics can modulate gene expression in offspring, supports mounting evidence of the microbiota as a potential target to improve brain plasticity and function.
The mechanisms by which the gut-microbiome may mediate central and peripheral (spinal-mediated) pain-related networks still remain to be examined. While this work has established a critical role for the gut microbiome, there exists a range of other host factors that may act in combination with or independent of the gut microbiome that may also play a role in pain sensitivity. Highly recognized is gut-microbial regulation of immune responses which in turn, can modulate behavior and neuroinflammation.Citation49,Citation54 For instance, gut microbiota derived mediators (including cytokines, chemokines, toll like receptor agonists, and SCFAs) can indirectly increase dorsal root ganglion (DRG) neuron excitability by inducing pro-inflammatory factor release which can enhance pain responses; alternatively, gut microbial derived bile acids have been shown to decrease DRG neuronal excitability by stimulating the release of endogenous opioids which inhibit pain response.Citation54 In this study, using multiplex electrochemiluminescence, our studies uncovered elevations in IL-17a in the serum of MET compared to CTRL at 3 weeks of age, with no changes in IL-17 concentration observed between MET+PRO and CTRL+PRO offspring. Accumulating studies have demonstrated the involvement of peripheral IL-17 in pain.Citation140 For instance, elevations in IL-17 in injured nerves have been reported in neuropathic pain models,Citation141,Citation142 and intra-hind pawCitation143,Citation144 and intra-kneeCitation145 injections of recombinant IL-17 in mice induced hyperalgesia. IL-17 knockout mice have also been shown to have significantly decreased mechanical hypersensitivity compared to controls.Citation143 In line with our findings, others have further contributed that spinal IL-17 can promote thermal hyperalgesia and NMDA NRI phosphorylation in an inflammatory pain rat model.Citation140 Notably, gut microbiota can regulate the development and function of a variety of immune cells, including regulatory T cells as well as Th17 cells, which produce IL-17α.Citation146 Surprisingly, our studies did not uncover differences in the expression of any other serum cytokines, despite BugBase predictions of increased gram-negative bacteria and potential pathogens in MET offspring and our findings of decreased pain thresholds in these offspring. Other studies have previously reported increased expression of IL-1β, IL-6, and TNF-α, in the serum of prenatal opioid-exposed rats at postnatal day 10, though only IL-1β remained elevated at postnatal day 21.Citation55 Notably, levels of IL-1β at that time were reduced by about 50% compared to postnatal day 10.Citation55 This merits replication of our studies at earlier timepoints to determine if peripheral- or neuro-inflammation can be detected. Additionally, though no differences in cytokine expression levels were noted at baseline, differences in counts and functionality of immune populations in MET offspring remain to be tested at baseline and in response to environmental or chemical challenges. This may yield important insight into how early life exposures may have critical influences on offspring immune programming and neurodevelopment and complement studies detailed here.
Conclusion
In summary, the present study provides compelling evidence of the gut-brain-axis in mediating pain sensitivity in prenatally opioid-exposed offspring. Our preclinical models suggest the importance of maintaining a balanced gut microbiome during pregnancy as one arm of a comprehensive treatment strategy to help mitigate downstream effects of prenatal opioid exposure.
List of abbreviations
| POE | = | prenatal opioid exposure |
| FMM | = | fostered to methadone mothers |
| FCM | = | fostered to saline-treated (control) mothers |
| CTRL | = | prenatally saline-exposed (control) offspring |
| MET | = | prenatally methadone-exposed offspring |
| MET + PRO | = | MET whose mothers were administered VSL#3 probiotics |
| CTRL+ PRO | = | CTRL whose mothers were administered VSL#3 probiotics |
Authors’ contributions
YA conceptualized this project, and coordinated the experimental design, conduct, and data acquisition and analysis of this project. YA generated mouse lines and wrote and revised the majority of the manuscript. YA, SS, IC, and JM performed experiments, analyzed data and/or contributed to the writing of this manuscript. PS and JT performed data analyses. This research was supported by grants from SR. All authors reviewed the results, commented on the manuscript, and approved the final version of the manuscript.
Availability of data and materials
All data generated or analyzed during this study are included in this published article and its supplementary information files. Accompanying metadata is available using accession number S-BSST1226 at the online data repository: https://www.ebi.ac.uk/biostudies/studies/S-BSST122
Ethics approval and consent to participate
This study was approved by the Institutional Animal Care and Use Committee policies at the University of Miami and adhered to all ethical guidelines related to the care of laboratory animals. (Protocol: 20–100).
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We thank Valerie Gramling from the University of Miami Writing Center for help with the editing of this manuscript.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/19490976.2023.2292224
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Funding
References
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