ORIGINAL INVESTIGATION

Revision to psychopharmacology mRNA and microRNA profilesare associated with stress susceptibility and resilience inducedby psychological stress in the prefrontal cortex

Jiuyong Yang1& Jinyan Sun1

& Yanjun Lu1& Tingting An1

& Wei Lu1& Jin-Hui Wang1,2,3

Received: 27 February 2020 /Accepted: 12 June 2020# Springer-Verlag GmbH Germany, part of Springer Nature 2020

AbstractObjectives The prefrontal cortex is associated with many mental neurological diseases. The mRNA and microRNA profiles ofstress susceptibility and resilience induced by psychological stress in the prefrontal cortex remain to be elucidated.Methods The C57 observer was placed in the cage next to the CD1 mouse and suffered psychological stress by watching theCD1 attacking another C57 mouse. After 5 days of psychological stress, the degree of fear memory and anxiety of mice weremeasured by social interaction test and elevated plus maze (EPM). The prefrontal cortex was extracted and mRNA andmicroRNA profiles were analyzed by high-throughput sequencing.Results In susceptible mice versus resilient mice, the downregulation of genes involved in serotonergic synapse may be related tothe susceptibility to psychological stress. The imbalanced regulation of genes involved in VEGF, p53, chemokine, Ras,sphingolipid, GnRH, MAPK, and NOD-like receptor signaling pathways may be related to the susceptibility to psychologicalstress. Compared with control mice, susceptible mice and resilient mice have changed genes involved in serotonergic synapse,neuroactive ligand-receptor interaction, axon guidance, calcium, cAMP, GnRH, estrogen, PI3K-Akt, MAPK, Rap1, and Rassignaling pathways, these changes may be related to psychological stress processing. The sequencing results of mRNAs andmicroRNAs were verified by qRT-PCR and dual-luciferase reporter assay.Conclusions The downregulation of genes involved in serotonergic synapse and imbalance of signaling pathways in the pre-frontal cortex may be related to susceptibility to psychological stress.

Keywords Psychological stress . Susceptibility . Resilience . Anxiety and prefrontal cortex

Introduction

There are many types of stress, including acute severe stressand chronic mild stress, psychological stress, and physical

stress, and excessive stress can induce phobia, anxiety, de-pression, and post-traumatic stress disorder (PTSD)(Coutellier and Usdin 2011; Desmedt et al. 2015; Orsini andMaren 2012; Si et al. 2018). People’s responses to stress andtrauma vary widely. Some people develop related mental ill-nesses, such as post-traumatic stress disorder (PTSD) or de-pression, while most people who experience stressful eventsdo not show signs of mental illness (Charney 2004; Krishnanet al. 2007; Southwick and Charney 2012). These tolerantindividuals exhibit characteristics such as cognitive flexibility(Yehuda et al. 2006) and optimism (Charney 2004). But themolecular mechanisms that mediate these resistances to stressare unclear.

The prefrontal cortex is associated with key symptomsthat regulate depression and anxiety (Vialou et al. 2014).Animal models involving long-term exposure to physicalstress can impair the structure and function of medial pre-frontal cortex (mPFC) neurons (Radley et al. 2006).

Electronic supplementary material The online version of this article(https://doi.org/10.1007/s00213-020-05593-x) contains supplementarymaterial, which is available to authorized users.

* Wei Luluwei@qdu.edu.cn

* Jin-Hui Wangjhw@ibp.ac.cn

1 School of Pharmacy, Qingdao University, 38 Dengzhou,Qingdao 266021, Shandong, China

2 University of Chinese Academy of Sciences, Beijing 100049, China3 Institute of Biophysics, University of Chinese Academy of Sciences,

15 Datun Road, Chaoyang District, Beijing 100101, China

Psychopharmacologyhttps://doi.org/10.1007/s00213-020-05593-x

Reduced mPFC neuron activity is associated with depres-sion and anxiety-like behaviors in mice caused by socialfailure (Vialou et al. 2014). Rodent mPFC controls emo-tional behavior by projecting lateral basal amygdala(BLA) and nucleus accumbens (NAc) (Barbas and Blatt1995; Stern et al. 2013). Previous studies have shown thatmolecules in the prefrontal cortex are involved in stresssusceptibility and resilience. For example, dopamine D1receptor in the medial prefrontal cortex can suppressstress susceptibility (Shinohara et al. 2018). Besides, inBagot’s research, an integrated network biology approachwas used to identify transcriptional networks that regulatesusceptibility to depression-like symptoms (Bagot et al.2016). By sequencing RNA of the prefrontal cortex, themolecular mechanism of susceptibility to depression-likesymptoms was studied. Bagot studied social defeat causedby physical and psychological stress and only sequencedmRNA. We plan to simultaneously sequence mRNA andmiRNA in the prefrontal cortex to study the molecularmechanism of susceptibility induced by psychologicalstress.

miRNA plays an important role in various physiologicalphenomena such as stress response, synaptic remodeling,and neurogenesis (Lopez et al. 2014; Meerson et al. 2010;Uchida et al. 2008). miRNA has been shown to be related tosusceptibility to stress. For example, the downregulation ofmiR-218 in mPFC can increase the susceptibility to a singlesession social defeat (Torres-Berrío et al. 2020). It is worthnoting that miRNA interacts with mRNA and can regulate theexpression and translation of the corresponding target mRNAand may also directly lead to the degradation of target mRNA(Ambros 2004). Therefore, the combined sequencing ofmRNA and miRNA and analysis of their interactions will bemore convincing. How social stress causes epigenetic chang-es, such as how miRNAs interact and regulate mRNA andprotein expression, needs further study (Ma et al. 2016a; Maet al. 2016b).

Physical and psychological stress can induce fear memory,anxiety, and depression-like behavior (Coutellier and Usdin2011). Fear can be acquired indirectly by observing the emo-tional expressions of others. In the observational fear condi-tioning protocol, the participant (observer) watches a demon-strator being presented with a conditioned stimulus (CS)paired with an aversive unconditioned stimulus (US)(Haaker et al. 2017). In previous studies, the social interactiontest was used to assess the level of fear memory in mice (Duet al. 2019; Sun et al. 2019). At present, most of the currentstress models directly inflict physical and psychological stresson the experimental animals (Krishnan et al. 2007; Vialouet al. 2014), and there are few simple psychological stressmodels. In our study, to simulate psychological stress, C57observer mice were placed into the cage next to CD1 miceto watch the CD1 attack another C57 mouse. After 5 days of

psychological stress, the fear memory in mice was detected bythe social interaction test, and the anxiety of the mice wasdetected by elevated plus maze. The observer mice were di-vided into resilient and susceptible mice according to the ratioin the social interaction test. The mRNA and miRNA profilesof control, resilient, and susceptible mice were analyzed byhigh-throughput sequencing. Through the combined analysisof mRNA and miRNA, we hope to find molecular expressionprofiles related to stress susceptibility and resilience inducedby psychological stress.

Materials and methods

All experiments are following the guideline and regulationsby Administration Office of Laboratory Animals in BeijingChina. Protocols were approved by Institutional Animal Careand Use Committee in this office (B10831). The mice werehoused in the cages (32 × 16 × 16 cm) with free access waterand food pellets under. The ambient temperature was 22 ±2 °C. Relative humidity was 55 ± 5%. The circadian rhythmwas 12 h in the dark (07:00–19:00) and 12 h in the light(19:00–07:00).

Stress susceptibility and resilience induced by psychologicalstress in mice Fear memory and anxiety in mice were in-duced by a witness paradigm adjusted by the social defeatmodel (Berton et al. 2006; Bjorkqvist 2001; Golden et al.2011; Krishnan et al. 2007; Staron et al. 2018; Tsankovaet al. 2006). The reason for choosing this pattern is thatpsychological stress is more common in social life. MaleCD1 mice were used as residents in this paradigm. In thisexperiment, male C57 mice were selected after 6 weeks ofbirth. During the adaptation period of 7 days, male CD1mice were placed in a room that took up half of a normalcage (29 × 17.5 × 12.5 cm). A neighboring room (29 ×17.5 × 12.5 cm) was separated by a transparent partition.During this period, C57 mice were housed in normalcages, touched five times a day to adapt to the environ-ment. After 7 days of adaptation, the C57 mice with aratio of over 0.5 in the social interaction test and over2% staying in open arms of elevated plus maze were con-sidered with normal social activities and anxiety levels.The criteria for determining that mice had normal socialactivities and anxiety levels were based on the previouslypublished literature (Du et al. 2019; Sun et al. 2019).These mice were divided into the observer group andthe control group.

The observers experienced psychological stress for 5 days.When the psychological stress was given, an observer mousewas placed into the room next to the CD1 mouse room, andanother C57 mouse was placed into the CD1 mouse room. Asthe CD1 mice were aggressive, the C57 mice placed into their

Psychopharmacology

territory would be attacked. The C57 mice (observers) re-ceived psychological stress by watching CD1 mice attackingother C57 mice. Psychological stress stimulations were per-formed twice in the morning and afternoon for 5 days. Thetime of witness was based on the latency of aggressive behav-iors five times, and the time was about 5–10 min. This timewas determined based on previous research, and Du proposedthat the duration of time was based on the attack times whenCD1 male resident mouse had bitten the C57 intruder mousefive times on his back (Du et al. 2019). In addition, Goldenet al. (2011) proposed a standardized protocol for repeatedsocial defeat in mice. In the protocol, the intruder C57 wasplaced in the cage of the CD1 mouse, and the attack time wasquantified as 5–10 min.

After 5 days of psychological stress, the observer andcontrol groups were tested via the social interaction testagain. The social interaction test was performed in a 50 ×50-cm open field with a 10 × 10-cm transparent cage. The5-cm area next to the transparent cage was defined as theinteraction zone (Fig. 1c). The ratios of the time C57stayed in the interaction zone with a CD1 mouse in thetransparent cage to the time C57 stayed in the interactionzone without a CD1 mouse were collected. The C57 mice’sfear memory behaviors were identified by avoiding thecontainer near the CD1 male and spending less time inthe interaction zone.

The observer mice were divided into susceptible mice andresilient mice according to the ratio (Golden et al. 2011). InGolden et al.’s study, the mice whose ratios were less than 1were defined as susceptible mice, and the mice whose ratioswere greater than 1 were defined as the resilient mice. In ourstudy, we also considered the change of ratio before and aftertraining. After psychological stress, the observers whose ratioswere decreased by more than 20% and less than 1 were definedas the susceptible mice. The observers whose ratios were de-creased by less than 20% or whose ratios were increased andgreater than 1 were defined as the resilient mice. Those that didnot meet the above two criteria were defined as atypical mice.

Testing of anxiety state The elevated plus maze (EPM) wasused to assess the anxiety-like behaviors of mice and isconsidered an effective and classic method for assessinganxiety levels in the rodents (Pellow et al., 1985). TheEPM consists of two open arms (30 × 5 cm), two closedarms (30 × 5 × 15.25 cm), and the central platform (5 ×5 cm). The EPM was located 40 cm above the ground.Because of the rodents’ penchant for darkness, they tendto move in closed arms when placed in the elevated plusmaze and to explore open arms out of curiosity. Anxietylevels of mice were assessed by the ratios of explorationtime they spent in the open arms to the total explorationtime. The highly anxiety-like behaviors were described as

Fig. 1 The social defeat and social interaction in mice induced bypsychological stress. a After 7 days of acclimatization, the C57 micewere screened by elevated plus maze (EPM) test and social interactiontest before psychological stress. The observer was subjected to psycho-logical stress in the morning and afternoon for 5 days. The EPM test andsocial interaction test were used to test the anxiety and fear memory of theC57 mice. The prefrontal cortex was then removed for transcriptomesequencing. b The paradigm of psychological stress stimulation. The

C57 mouse (observer) was placed into the room next to the CD1 room,and another C57 mouse was placed into the room of the CD1 mouse. TheC57 mouse (observer) was able to watch the CD1 mouse attack anotherC57 mouse by the transparent partition. c The social interaction test wasperformed in an open field (50 × 50 cm) with a transparent perforatedcage (10 × 10 cm). The area of 5 cm around the cage is defined as theinteraction zone

Psychopharmacology

the mice spending more time in the closed arms and lesstime in the open arms (Du et al. 2019; Sun et al. 2019).

RNA purification from prefrontal cortex tissue Twenty-fourhours after these behavior tests, we collected the prefrontalcortex tissue. This time was based on previous research (Maet al. 2016a; Sun et al. 2019). The mice in the control group,resilient group, and susceptible group were anesthetized by4% chloral hydrate, then perfused with 4 °C physiologicalsaline and decapitated. The prefrontal cortex was quickly sep-arated at − 20 °C and placed in an EP tube containingRNAwait. After overnight in the refrigerator at 4 °C, the tissueblock was removed from RNAwait and transferred to the −80 °C refrigerator for that storage. The total RNAs of theprefrontal cortex were isolated by TRIzol reagent (LifeTechnologies, Carlsbad, CA, USA). RNA samples were sentto the Beijing Genomics Institute (BGI) for high-throughputsequencing. The 2100 bioanalyzer (Agilent Technology,USA) with RNA 6000 nano Reagents Port 1 was used tocontrol the quality of the RNA samples. The value of RNAintegrity number (RIN), the concentration of total RNAs, andthe ratios of 28S to 18S ribosomal RNAs were measured.Samples with the total RNAs larger than 10 μg, the concen-tration larger than 200 ng/μl and the RIN larger than 8, and theratio of 28S/18S ratio larger than 1.5 were selected for theconstruction of transcriptome and small RNA libraries. Theprefrontal cortex tissues that met these qualifications wereused for high-throughput sequencing, and the correlation co-efficient was greater than 0.8.

RNA sequencingmRNAs were extracted from total RNA, andeukaryotic mRNAs were enriched with magnetic beads witholigo (dT). The eukaryotic mRNA has a poly-A, and there aremany T oligonucleotides on the surface of the oligo (dT) mag-netic beads. The mRNA will be adsorbed on the magneticbeads. The mRNA was randomly cut into 200 bp fragmentsby ultrasonic disruption, chemical treatment, or heat treat-ment. Fragments were reversely transcribed to cDNA by ran-dom oligonucleotides. These cDNAs were purified by theQiaQuick PCR extraction kit and ligated by sequencing adap-tors after the sticky ends were repaired. To select and purifycDNAs by agarose gel electrophoresis, the amplificationswere done with Illumina PCR Primer Cocktail in 15 PCR-reaction cycles. cDNAs between 200 and 300 bp were usedfor library construction.

18–30 nt RNAs were isolated from total RNA and used toconstruct a microRNA sequencing library. RNAs ligated to 5′-RNA adapter by T4 RNA ligase were size-fractionated and36–50 nucleotide fractions were excised. The precipitatedRNAs were ligated to 3′-RNA adapter by T4 RNA ligaseand size-fractionated, and then 62–75 nucleotide fraction(small RNA + adaptors) was excised. To produce templatesenough for the sequencing, small RNAs ligated with adaptors

were subjected to RT-PCR. Products were purified and col-lected for high-throughput sequencing.

Qualities of mRNA and miRNA libraries were evaluatedby 2100 Bioanalyzer. Their quantities were verified by ABIStepOnePlus Real-Time PCR System. Their sequencingswere done by Illumina HiseqTM 2500 platform (IlluminaInc., San Diego, CA, USA). The average length of themRNA library was 100 bp and double-ended sequencingwas performed. The average length of miRNA libraries was49 bp and single-ended sequencing was performed.

Bioinformatics for mRNAOriginal image data was transformedinto raw data or raw reads by base calling. Dynamic Trim Perlscript implemented in the SolexaQA package was done tocontrol the quality of raw sequencing data. The reads withadapters, unknown bases more than 10% as well as 50% baseswith the low-quality score (PHRED score 5) were removed.The remained “clean reads” were mapped to the mouse ge-nome reference sequence (UCSC mm10) by TopHat v1.0.12incorporated Bowtie v0.11.3 software to perform alignments.The maximum allowable mismatch was set to three for eachread in the alignment and mapping. To calculate the geneexpression level, the sole reads uniquely aligned to genes wereused. Fragments per kilobase per million (FPKM) were usedfor gene expression. Genes in low expression levels (FPKM<0.5) were removed for further analysis.

The DESeq2 package was used to screen differentiallyexpressed genes (DEGs) between two groups with biolog-ical replicates, e.g., susceptible versus control, resilientversus control, and susceptible versus resilient. A thresh-old to identify DEGs was fold change above 2; the pvalue was less than 0.05. Pathway enrichment analysisin DEG association with physiological or biochemicalprocesses was conducted. Canonical pathways from theKyoto Encyclopedia of Genes and Genomes (KEGG) da-tabase were used in these enrichment analyses. Comparedto the whole genome background, the enriched metabolicpathways or signal transduction pathways in DEGs wouldbe identified in the analyses. Pathways with p values lessthan 0.05 were thought to be significantly enriched.

Bioinformatics for microRNA (miRNA) Adaptor sequences,low-quality reads, and contaminant in 49 nt-tags from Hiseqsequencing were removed. The remained credible clean readswere aligned to GeneBank database and Rfam database withblast or bowtie software to further remove reads of noncodingRNA, such as ribosomal RNAs, transfer RNAs, small nuclearRNAs, small nucleolar RNAs, and repeat RNA. To obtainmiRNA count, high-quality clean reads ranging in 18–25 ntwere matched to the known miRNA precursor of correspond-ing species in miRBase. miRNAs that could be consistentwith miRNA precursor in miRBase without mismatchedmarkers and mature miRNA in miRBase with at least 16 nt

Psychopharmacology

overlap allowing offset could be counted. For unannotatedremaining reads, Miredp was used to predict new miRNAswith potential stem-loop structure (Friedlander et al. 2012).To correct biased results for low expression, miRNAs withreading counts less than 5 were removed in differential ex-pression analysis.

In the susceptible group versus control group, resilientgroup versus control group, susceptible group versus resilientgroup, DESeq2 package was used to compare known or newmiRNA expression. The criterion to identify differential ex-pression of miRNA was that the fold change was more thantwo times, and the Q value was less than 0.001. RNAhybrid,Targetscan, and miRanda were used to predict the target genesof differentially expressed miRNAs.

Integrated miRNA/mRNA network analysis Through bioinfor-matics analysis, the correlation between differentiallyexpressed miRNAs and their target mRNAs was found.Except for a few, miRNAs were theoretically inversely relatedto their targeted mRNAs. Integrating differentially expressedmiRNAs and mRNAs was to identify potential target genesregulated by miRNAs. In our analysis, miRNAs and mRNAsshould be reversed simultaneously, and the miRNAs shouldpredict mRNAs by RNAhybrid, Targetscan, and miRanda.The Cytoscape software was used to make the interactivenetworks between miRNAs and their target mRNAs (SanDiego, CA USA).

Quantitative RT-PCR was used for the validations of miRNAand mRNA Differentially expressions of 26 mRNAs and 15miRNAs were validated by quantitative real-time PCR (qRT-

PCR). Supplementary Table 1 lists the used primers. Briefly,real-t ime PCR was performed using the Bio-RadCFX96Touch. Total RNA was extracted from the prefrontalcortex using the TRIzol kit. For mRNAs, cDNAs were syn-thesized by HiScript III RT SuperMix for qPCR kit (Vazyme,R323-01, Nanjing, China). The cDNAs were amplified by theChamQ Universal SYBR qPCRMaster Mix (Vazyme, Q711-02, Nanjing, China) and performed in a 20-μl system, includ-ing 1 μl cDNA sample, 4 μl upstream primer (0.2 μmol/l),4 μl downstream primer (0.2 μmol/l), 10 μl 2× ChamQUniversal SYBR qPCR Master Mix, and 1 μl ddH2O. FormiRNAs, cDNAs were synthesized using the Mir-X miRNAFirst-Strand Synthesis Kit (Clontech, 638315, CA, USA). FormiRNAs, qRT-PCR was performed in a 20-μl system, includ-ing 2 μl sample cDNA, 0.5 μl mRQ 3′ Primer, 0.5 μl miRNA-specific Primer (10 μM), 12.5 μl 2× SYBR advantage Premix(2×), and 9.5 μl ddH2O. The relative expression levels ofmRNAs in tissues were normalized to a reference gene,GAPDH. The relative expression levels of miRNAs in tissueswere normalized to U6 small nucleolar RNA. qRT-PCR wasrepeated three times. The results were calculated using the2−ΔΔCt methods (Livak and Schmittgen 2001).

Dual-luciferase reporter assay The sequence containing thetarget site of the targeted gene was amplified by 2× PhantaMax Master Mix (Vazyme, P515-01, Nanjing, China) andperformed in a 50-μl system, including 25 μl 2× PhantaMax Master Mix, 2 μl upstream primer (0.4 μmol/l), and2 μl downstream primer (0.4 μmol/l), 2 μl cDNA, and 19 μlddH2O. The sequence containing the targeted site of thetargeted gene was digested by XhoI/NotI. The sequence was

Fig. 2 The ratios of control, resilient, and susceptible groups in the socialinteraction test at day 0 and day 6. Control group n = 13, resilient groupn = 20, susceptible group n = 15. Three asterisks show p < 0.001; twoasterisks show p < 0.01. Two-way repeated measures ANOVA was usedfor the comparisons among control, resilient, and susceptible groups be-fore and after psychological stress

Fig. 3 Time ratios in open arms of control, resilient, and susceptiblegroups at day 0 and day 6. Control group n = 13, resilient group n = 20,susceptible group n = 15. Two asterisks show p < 0.01; one asteriskshows p < 0.05. Two-way repeated measures ANOVA was used for thecomparisons among control, resilient, and susceptible groups before andafter psychological stress

Psychopharmacology

Table 1 Pathways identified by KEGG based on DEGs data of mPFC in susceptible mice versus control mice

KEGG entry Term Involved gene count Genes

mmu05012 Parkinson’s disease 4 Cox8b (cytochrome c oxidase subunit VIIIb)↓, Cox6a2(cytochrome coxidase subunit VIa polypeptide 2)↓, Sncaip(synuclein, alpha interacting protein (synphilin))↓, Th(tyrosine hydroxylase)↑

mmu04340 Hedgehog signaling pathway 2 Hhip (Hedgehog-interacting protein)↓

Gli1 (GLI-Kruppel family member GLI1)↓

mmu04151 PI3K-Akt signaling pathway 6 Ngfr (nerve growth factor receptor (TNFR superfamily, member16))↓, Thbs4 (thrombospondin 4)↓

Col3a1 (collagen, type III, alpha 1)↓, Col27a1 (collagen, typeXXVII, alpha 1)↓, Fgfr4 (fibroblast growth factor receptor4)↓, Spp1 (secreted phosphoprotein 1)↓

mmu05010 Alzheimer’s disease 4 Cacna1s (calcium channel, voltage-dependent, L type,alpha 1S subunit)↓

Atp2a1 (ATPase, Ca++ transporting, cardiac muscle, fasttwitch 1)↓, Cox8b (cytochrome c oxidase subunit VIIIb)↓,Cox6a2 (cytochrome c oxidase subunit VIa polypeptide 2)↓

mmu04020 Calcium signaling pathway 4 Atp2a1 (ATPase, Ca++ transporting, cardiac muscle, fasttwitch 1)↓, Cacna1s (calcium channel, voltage-dependent, Ltype, alpha 1S subunit)↓, Hrh1 (histamine receptor H1)↑,Ptafr (platelet-activating factor receptor)↑

mmu04024 cAMP signaling pathway 4 Htr1a (5-hydroxytryptamine (serotonin) receptor 1A)↓,Cacna1s (calcium channel, voltage-dependent, L type, alpha1S subunit)↓

Gli1 (GLI-Kruppel family member GLI1)↓, Hhip(Hedgehog-interacting protein)↓

mmu04310 Wnt signaling pathway 3 Fzd4 (frizzled class receptor 4)↓

Wif1 (Wnt inhibitory factor 1)↓, Sfrp2 (secretedfrizzled-related protein 2)↓

mmu04080 Neuroactive ligand-receptor interaction 4 Htr1a (5-hydroxytryptamine (serotonin) receptor 1A)↓, Chrna1(cholinergic receptor, nicotinic, alpha polypeptide 1(muscle))↓, Hrh1 (histamine receptor H1)↑, Ptafr (platelet--activating factor receptor)↑

mmu04912 GnRH signaling pathway 2 Cacna1s (calcium channel, voltage-dependent, L type, alpha 1Ssubunit)↓, Mmp2 (matrix metallopeptidase 2)↓

mmu04010 MAPK signaling pathway 3 Cacna1s (calcium channel, voltage-dependent, L type, alpha 1Ssubunit)↓, Fgfr4 (fibroblast growth factor receptor 4)↓

Flnc (filamin C, gamma)↓

mmu04726 Serotonergic synapse 2 Htr1a (5-hydroxytryptamine (serotonin) receptor 1A)↓,Cacna1s (calcium channel, voltage-dependent, L type,alpha 1S subunit)↓

mmu04910 Insulin signaling pathway 2 Ppp1r3a (protein phosphatase 1, regulatory (inhibitor)subunit 3A)↓

mmu04022 cGMP-PKG signaling pathway 2 Cacna1s (calcium channel, voltage-dependent, L type,alpha 1S subunit)↓

Atp2a1 (ATPase, Ca++ transporting, cardiac muscle,fast twitch 1)↓

mmu05016 Huntington’s disease 2 Cox8b (cytochrome c oxidase subunit VIIIb)↓, Cox6a2(cytochrome c oxidase subunit VIa polypeptide 2)↓

mmu04015 Rap1 signaling pathway 2 Fgfr4 (fibroblast growth factor receptor 4)↓, Ngfr (nerve growthfactor receptor (TNFR superfamily, member 16))↓

mmu04014 Ras signaling pathway 2 Fgfr4 (fibroblast growth factor receptor 4)↓, Ngfr (nerve growthfactor receptor (TNFR superfamily, member 16))↓

mmu04390 Hippo signaling pathway 1 Fzd4 (frizzled class receptor 4)↓

mmu04727 GABAergic synapse 1 Cacna1s (calcium channel, voltage-dependent, L type,alpha 1S subunit)↓

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ligated with the double luciferase vector psiCHECKTM-2 viaT4DNA ligase (Vazyme, C301-01, Nanjing, China). The site-directed mutation of the miRNA targeting site was performedwith the Mut Express II Fast Mutagenesis Kit V2 (Vazyme,C214-02, Nanjing, China). HEK293T cells were planted in24-well plates with 5 × 104 cells per well and maintained inDMEM containing 10% FBS. After 24 h, 50 ngpsiCHECKTM-2 wild-type or mutant plasmids 50 nMmiRNA mimic or miRNA-NC were co-transfected into293 T cells with Lipofectamine 2000 transfection reagent(Invitrogen, Carlsbad, CA, USA). After 48 h, the activitiesof firefly luciferase and Renilla luciferase were detected byDual-Glo® Luciferase Assay System (Promega, Cat. E2920,USA). Each treatment was performed in three independentexperiments.

Different expression levels and biological indicationCompared with the control group, in the susceptible groupand the resilient group, if mRNAs were differentiallyexpressed in both groups and change in the same direction,these mRNAs may be related to psychological stress. Thedifferentially expressed mRNAs between the susceptiblegroup and the resilient group may be related to the suscepti-bility of psychological stress.

Statistical analysis The initial data of mRNA and miRNAexpression profiles were processed by the DESeq2 softwarealgorithm. In the behavior test, luciferase activity and geneanalysis, the data were expressed as mean ± SEM. Pearson’scorrelation coefficients were used to evaluate the relationshipsbetweenmiRNAs and the target gene. In the data of molecularbiology, an unpaired Student t test was used to compare thedata between susceptible and control mice, resilient and con-trol mice, and susceptible and resilient mice. Two-way repeat-ed measures ANOVA with post hoc comparison byBonferroni’s multiple comparisons test was used to comparethe data from behavioral tests among groups. P < 0.05 wasconsidered statistically significant.

Results

Fear memory and anxiety-like behaviors induced bypsychological stress

According to the criteria that mice have normal social activ-ities and anxiety levels, 20% of the mice were excluded,leaving about 80% of the mice. In the 5 days of psycholog-ical stress, the observer mice in the next room separated by a

Table 1 (continued)

KEGG entry Term Involved gene count Genes

mmu04725 Cholinergic synapse 1 Cacna1s (calcium channel, voltage-dependent, L type,alpha 1S subunit)↓

mmu04920 Adipocytokine signaling pathway 1 Slc2a4 (solute carrier family 2 (facilitated glucose transporter),member 4)↓

mmu04620 Toll-like receptor signaling pathway 1 Spp1 (secreted phosphoprotein 1)↓

mmu04360 Axon guidance 1 Sema3b (sema domain, immunoglobulin domain (Ig), shortbasic domain, secreted, (semaphorin) 3B)↓

mmu04728 Dopaminergic synapse 1 Th (tyrosine hydroxylase)↑

mmu04068 FoxO signaling pathway 1 Slc2a4 (solute carrier family 2 (facilitated glucose transporter),member 4)↓

mmu04917 Prolactin signaling pathway 1 Th (tyrosine hydroxylase)↑

mmu04915 Estrogen signaling pathway 1

Mmp2 (matrix metallopeptidase 2)↓

mmu04062 Chemokine signaling pathway 1 Hck (hemopoietic cell kinase)↓

mmu04630 Jak-STAT signaling pathway 1 Csf2rb2 (colony stimulating factor 2 receptor, beta 2,low-affinity (granulocyte-macrophage))↓

mmu04722 Neurotrophin signaling pathway 1 Ngfr (nerve growth factor receptor (TNFR superfamily, member16))↓

mmu04152 AMPK signaling pathway 1 Slc2a4 (solute carrier family 2 (facilitated glucose transporter),member 4)↓

mmu04921 Oxytocin signaling pathway 1 Cacna1s (calcium channel, voltage-dependent, L type, alpha 1Ssubunit)↓

mmu04350 TGF-beta signaling pathway 1 Fst (follistatin)↓

mmu04066 HIF-1 signaling pathway 1 Timp1 (tissue inhibitor of metalloproteinase 1)↓

Upward arrow indicates upregulation in the tissue of mPFC from susceptible versus control mice, whereas downward arrow represents downregulation

Psychopharmacology

Table 2 Pathways identified by KEGG based on DEGs data of mPFC in resilient mice versus control mice

KEGG entry Term Involved gene count Genes

mmu04151 PI3K-Akt signaling pathway 11 Vwf (Von Willebrand factor)↓, Col3a1 (collagen, type III, alpha1)↓, Col6a3 (collagen, type VI, alpha 3)↓, Col6a4 (collagen,type VI, alpha 4)↑, Col27a1 (collagen, type XXVII, alpha 1)↓

Cdk2 (cyclin-dependent kinase 2)↓, Fgfr4 (fibroblast growthfactor receptor 4)↓, Itga11 (integrin alpha 11)↓, Itga10(integrin, alpha 10)↑, Lamc2 (laminin, gamma 2)↑, Tnc(tenascin C)↓

mmu04020 Calcium signaling pathway 6 Adora2b (adenosine A2b receptor)↓, Ptafr (platelet-activatingfactor receptor)↑, Trhr (thyrotropin releasing hormonereceptor)↑

Atp2a1 (ATPase, Ca++ transporting, cardiac muscle, fasttwitch 1)↓, Mylk4 (myosin light chain kinase family, member4)↓, Tnnc2 (troponin C2, fast)↓

mmu04080 Neuroactive ligand-receptor interaction 8 Htr1a (5-hydroxytryptamine (serotonin) receptor 1A)↓,Adora2b (adenosine A2b receptor)↓, Chrna1 (cholinergicreceptor, nicotinic, alpha polypeptide 1 (muscle))↓, Chrng(cholinergic receptor, nicotinic, gamma polypeptide)↓, Glp2r(glucagon-like peptide 2 receptor)↑, Ptafr (platelet-activatingfactor receptor)↑, Gm10334 (predicted gene 10,334)↑, Trhr(thyrotropin releasing hormone receptor)↑

mmu05016 Huntington’s disease 5 Cox8b (cytochrome c oxidase subunit VIIIb)↓, Cox7a2l(cytochrome c oxidase subunit VIIa polypeptide 2-like)↑,Dnah6 (dynein, axonemal, heavy chain 6)↓, Dnah7a (dynein,axonemal, heavy chain 7A)↓, Dnah8 (dynein, axonemal,heavy chain 8)↓

mmu04620 Toll-like receptor signaling pathway 3 Tlr1 (toll-like receptor 1)↓, Tlr6 (toll-like receptor 6)↓

Ctsk (cathepsin K)↓

mmu05010 Alzheimer’s disease 4 Lpl (lipoprotein lipase)↓

Atp2a1 (ATPase, Ca++ transporting, cardiac muscle, fasttwitch 1)↓,Cox8b (cytochrome c oxidase subunitVIIIb)↓,Cox7a2l (cytochrome c oxidase subunit VIIapolypeptide 2-like)↑

mmu04010 MAPK signaling pathway 5 Fgfr4 (fibroblast growth factor receptor 4)↓, Il1r1 (interleukin 1receptor, type I)↓

Flnc (filamin C, gamma)↓, Hspa8 (heat shock protein 8)↑, Il1r1(interleukin 1 receptor, type I)↓, Pla2g4e (phospholipase A2,group IVE)↓

mmu04910 Insulin signaling pathway 3 Ppp1r3a (protein phosphatase 1, regulatory (inhibitor) subunit3A)↓, Ppp1r3e (protein phosphatase 1, regulatory (inhibitor)subunit 3E)↑, Slc2a4 (solute carrier family 2 (facilitated glu-cose transporter), member 4)↓

mmu03320 PPAR signaling pathway 2 Angptl4 (angiopoietin-like 4)↓, Lpl (lipoprotein lipase)↓

mmu05012 Parkinson’s disease 3 Park2 (Parkinson disease (autosomal recessive, juvenile) 2,parkin)↑, Cox8b (cytochrome c oxidase subunit VIIIb)↓,Cox7a2l (cytochrome c oxidase subunit VIIa polypeptide2-like)↑

mmu04921 Oxytocin signaling pathway 3 Mylk4 (myosin light chain kinase family, member 4)↓, Nfatc4(nuclear factor of activated T cells, cytoplasmic, calcineurindependent 4)↓, Pla2g4e (phospholipase A2, group IVE)↓

mmu04350 TGF-beta signaling pathway 2 Dcn (decorin)↓, Fst (follistatin)↓

mmu04912 GnRH signaling pathway 2 Mmp2 (matrix metallopeptidase 2)↓

Pla2g4e (phospholipase A2, group IVE)↓

mmu04022 cGMP-PKG signaling pathway 3 Atp2a1 (ATPase, Ca++ transporting, cardiac muscle, fasttwitch 1)↓, Mylk4 (myosin light chain kinase family, member4)↓, Nfatc4 (nuclear factor of activated T cells, cytoplasmic,calcineurin dependent 4)↓

Psychopharmacology

transparent and perforated partition watched the CD1 miceattacking other C57 mice (Fig. 1b). Mice in the controlgroup did not undergo psychological stress training. Afterpsychological stress for 5 days, the observer mice and thecontrol mice were examined by behavioral tests (Fig. 1a).The basis for judging the formation of fear memory was thaton the sixth day, they escaped from a container containingthe CD1 mouse, and the time to enter the interaction zonewas significantly reduced (Fig. S1) and after psychological

stress, the susceptible group n = 15, the resilient group n =20, and the atypical group n = 4, excluding about 9.5% ofatypical mice.

Figure S1 shows the trajectories for control, resilient, andsusceptible mice without CD1 mice in a cage and with CD1mice in the cage at day 0 and day 6. The fewer trajectories ofC57 mice around the cage, the more the C57 mice were afraidof CD1 mice. Figure 2 shows the ratios of stay time in theinteraction zone of the control, resilient, and susceptible mice

Table 2 (continued)

KEGG entry Term Involved gene count Genes

mmu04915 Estrogen signaling pathway 2

Mmp2(matrix metallopeptidase 2)↓, Hspa8(heat shock protein 8)↑

mmu04066 HIF-1 signaling pathway 2 Eno1 (enolase 1, alpha non-neuron)↑, Eno1b (enolase 1B,retrotransposed)↓

mmu04668 TNF signaling pathway 2 Mmp3 (matrix metallopeptidase 3)↓, Gm5431(predicted gene 5431)↓

mmu04062 Chemokine signaling pathway 3 LOC100861978 (c-C motif chemokine 27-like)↓, Ccr6(chemokine (C-C motif) receptor 6)↓, Gm13308 (predictedgene 13,308)↓

mmu04360 Axon guidance 2 Nfatc4 (nuclear factor of activated T cells, cytoplasmic,calcineurin dependent 4)↓, Sema3b (sema domain,immunoglobulin domain (Ig), short basic domain, secreted,(semaphorin) 3B)↓

mmu04726 Serotonergic synapse 2 Pla2g4e (phospholipase A2, group IVE)↓, Htr1a(5-hydroxytryptamine (serotonin) receptor 1A)↓

mmu04068 FoxO signaling pathway 2 Cdk2 (cyclin-dependent kinase 2)↓, Slc2a4 (solute carrier family2 (facilitated glucose transporter), member 4)↓

mmu04310 Wnt signaling pathway 2 Wif1 (Wnt inhibitory factor 1)↓, Nfatc4 (nuclear factor ofactivated T cells, cytoplasmic, calcineurin dependent 4)↓

mmu04024 cAMP signaling pathway 2 Htr1a (5-hydroxytryptamine (serotonin) receptor 1A)↓

Gli1 (GLI-Kruppel family member GLI1)↓

mmu04015 Rap1 signaling pathway 2 Adora2b (adenosine A2b receptor)↓, Fgfr4 (fibroblast growthfactor receptor 4)↓

mmu04014 Ras signaling pathway 2 Fgfr4 (fibroblast growth factor receptor 4)↓

Pla2g4e (phospholipase A2, group IVE)↓

mmu04664 Fc epsilon RI signaling pathway 1 Pla2g4e (phospholipase A2, group IVE)↓

mmu04115 p53 signaling pathway 1 Cdk2 (cyclin-dependent kinase 2)↓

mmu04340 Hedgehog signaling pathway 1 Gli1 (GLI-Kruppel family member GLI1)↓

mmu04064 NF-kappa B signaling pathway 1 Il1r1 (interleukin 1 receptor, type I)↓

mmu04920 Adipocytokine signaling pathway 1 Slc2a4(solute carrier family 2 (facilitated glucose transporter),member 4)↓

mmu04152 AMPK signaling pathway 1 Slc2a4(solute carrier family 2 (facilitated glucose transporter),member 4)↓

mmu04540 Gap junction 1 Tuba1c (tubulin, alpha 1C)↓

mmu04919 Thyroid hormone signaling pathway 1 Dio3 (deiodinase, iodothyronine type III)↑

mmu04071 Sphingolipid signaling pathway 1 Acer2 (alkaline ceramidase 2)↓

mmu04370 VEGF signaling pathway 1 Pla2g4e (phospholipase A2, group IVE)↓

mmu04724 Glutamatergic synapse 1 Pla2g4e (phospholipase A2, group IVE)↓

Upward arrow indicates upregulation in the tissue of mPFC from resilient versus control mice, whereas downward arrow represents downregulation

Psychopharmacology

at day 0 and day 6. The results of the statistical analysis areshown in Table S2. At day 0, the control mice (n = 13), resil-ient mice (n = 20), and susceptible mice (n = 15) have a ratioof 1.11 ± 0.07, 1.1 ± 0.04, and 1.22 ± 0.04. There is no statis-tical difference in the comparison of the ratios among thecontrol, resilient, and susceptible mice at day 0 (control vsresilient, p > 0.99; control vs susceptible, p = 0.57; resilientvs susceptible, p = 0.39, two-way repeated measuresANOVA). At day 6, the ratios are 1.06 ± 0.07, 1.3 ± 0.06,and 0.74 ± 0.03 for the control, resilient, and susceptible mice.There is a significant difference in the comparison of the ratiosamong the control, resilient, and susceptible mice at day 6(control vs resilient, p = 0.003; control vs susceptible,p < 0.001; resilient vs susceptible, p < 0.001, two-way repeat-ed measures ANOVA). The ratios in the control group are

1.11 ± 0.07 at day 0 and 1.06 ± 0.07 at day 6 (p > 0.99, n =13). The ratios in the resilient group are 1.1 ± 0.04 at day 0 and1.3 ± 0.06 at day 6 (p = 0.005, n = 20). The ratios in the sus-ceptible group are 1.22 ± 0.04 at day 0 and 0.74 ± 0.03 at day6 (p < 0.001, n = 15). These behavioral results indicate thatafter psychological stress for 5 days, the susceptible mice de-veloped fear memory for CD1 mice, and the resilient micedeveloped resilience for CD1 mice.

Figure S2 shows the movement trajectories for control,resilient, and susceptible mice in the elevated plus maze atday 0 and day 6. Figure 3 shows the time ratios in openarms of control, resilient, and susceptible groups at day 0and day 6. The results of the statistical analysis are shown inTable S3. At day 0, the time ratios of staying in open armsfor control, resilient, and susceptible mice are 11.94 ±

Table 3 Pathways identified by KEGG based on DEGs data of mPFC in susceptible mice versus resilient mice

KEGG entry Term Involvedgene count

Genes

mmu04151 PI3K-Akt signaling pathway 6 Vwf (Von Willebrand factor)↑, Col5a1(collagen, type V,alpha 1)↓, Col6a3 (collagen, type VI, alpha 3)↑, Col27a1(collagen, type XXVII, alpha 1)↓, Kdr (kinase insertdomain protein receptor)↓

Thbs4 (thrombospondin 4)↓

mmu04066 HIF-1 signaling pathway 3 Eno1b (enolase 1B, retrotransposed)↑, Serpine1 (serine (orcysteine) peptidase inhibitor, clade E, member 1), Trf(transferrin)↓

mmu04370 VEGF signaling pathway 2 Kdr (kinase insert domain protein receptor)↓

Pla2g4e (phospholipase A2, group IVE)↓

mmu04115 p53 signaling pathway 2 Cd82 (CD82 antigen)↓, Serpine1 (serine (or cysteine)peptidase inhibitor, clade E, member 1)↓

mmu04062 Chemokine signaling pathway 2 Ccr6(chemokine (C-C motif) receptor 6)↓

Gm2506 (predicted gene 2506)↓

mmu04014 Ras signaling pathway 2 Kdr (kinase insert domain protein receptor)↓

Pla2g4e (phospholipase A2, group IVE)↓

mmu04071 Sphingolipid signaling pathway 1 Acer2 (alkaline ceramidase 2)↓

mmu05016 Huntington’s disease 1 Dnah6 (dynein, axonemal, heavy chain 6)↓

mmu04540 Gap junction 1 Tuba1c (tubulin, alpha 1C)↓

mmu04912 GnRH signaling pathway 1 Pla2g4e (phospholipase A2, group IVE)↓

mmu04390 Hippo signaling pathway 1 Serpine1(serine (or cysteine) peptidase inhibitor, clade E,member 1)↓

mmu04015 Rap1 signaling pathway 1 Kdr (kinase insert domain protein receptor)↓

mmu04010 MAPK signaling pathway 1 Pla2g4e(phospholipase A2, group IVE)↓

mmu04621 NOD-like receptor signaling pathway 1 Naip5 (NLR family, apoptosis inhibitory protein 5)↓

mmu04726 Serotonergic synapse 1 Pla2g4e (phospholipase A2, group IVE)↓

mmu04530 Tight junction 1 Myh8 (myosin, heavy polypeptide 8, skeletal muscle,perinatal)↓

mmu04620 Toll-like receptor signaling pathway 1 Tlr1 (toll-like receptor 1)↓

mmu04664 Fc epsilon RI signaling pathway 1 Pla2g4e (phospholipase A2, group IVE)↓

mmu04921 Oxytocin signaling pathway 1 Pla2g4e (phospholipase A2, group IVE)↓

Upward arrow indicates upregulation in the tissue of mPFC from susceptible versus resilient mice, whereas downward arrow represents downregulation

Psychopharmacology

1.15%, 11.30 ± 1.15%, and 11.39 ± 1.21%, respectively.There is no statistical difference between the three groups(control vs resilient, p > 0.99; control vs susceptible,p > 0.99; resilient vs susceptible, p > 0.99, two-way repeatedmeasures ANOVA). At day 6, the time ratios of staying inopen arms for control, resilient, and susceptible mice are12.71 ± 1.91%, 10.35 ± 1.37%, and 5.80 ± 0.9%, respective-ly. There is a significant difference between the three groups(control vs resilient, p = 0.63; control vs susceptible, p =0.002; resilient vs susceptible, p = 0.04, two-way repeatedmeasures ANOVA). After 5 days of psychological stress,compared with the control and resilient groups, the timeratio of the susceptible group in the open arms is significant-ly reduced. The time ratios in the control group are 11.94 ±1.15% at day 0 and 12.71 ± 1.91% at day 6 (p > 0.99, n =13). The time ratios in the resilient group are 11.30 ± 1.15%

at day 0 and 10.35 ± 1.37% at day 6 (p > 0.99, n = 20). Thetime ratios in the susceptible group are 11.39 ± 1.21% at day0 and 5.80 ± 0.9% at day 6 (p = 0.02, n = 15). The abovedata indicate that anxiety-like behavior occurred in suscepti-ble mice and resilience occurred in resilient mice.

Subsequently, high-throughput sequencing was used toquantitatively study mRNA and miRNA expression levels inthe control, resilient, and susceptible groups. The molecularmechanisms of psychological stress-induced stress suscepti-bility and resilience were studied.

Overall qualities of RNA-sequencing dataset

High-throughput sequencing was used to sequencemRNA and miRNA from the prefrontal cortex of the con-trol (n = 2), resilient (n = 3), and susceptible (n = 3)

Fig. 4 The validation of differentially expressed mRNAs in the prefrontal cortex from susceptible mice versus control mice. Three asterisks showp < 0.001; two asterisks show p < 0.01, in which a two-sample t test was used for the comparisons between susceptible mice versus control mice

Psychopharmacology

groups. 55.53–58.95 Mb raw sequence reads (100 bp)were obtained from the mRNA library Illumina sequenc-ing. The reads with low quality and adaptor were filteredout to get and map 44.09–45.19 Mb clean reads from eachlibrary, 88.49–93.06% of total reads from the mouse ge-nome (UCSC mm10) equivalently for samples (Table S4).A total of about 29,377,864–31,152,188 raw tag countswere generated in small RNA library, and 27,620,806–28,893,939 clean tag counts were obtained after filteringout low-quality reads and adaptor (Table S5). The lengthsof clean small RNA reads in each library were between 10and 44 nucleotides, in which the most abundant lengthswere 22 nucleotides (Fig. S3). High-quality clean readsgreater than 18 nucleotides were matched into the mousegenome, and the reads that matched the mouse genomewere classified into different categories of small RNAsbased on their biogenesis and annotation (Fig. S4). Themost abundant RNA category in each library was miRNA.High-quality mRNA and small RNA data were used forfurther analysis.

mRNA expression in the prefrontal cortex of control,resilient, and susceptible mice

High-throughput sequencing was performed on the mRNAsin the prefrontal cortex, and the FPKM value was calculated.The genes with low expression were removed (FPKM < 0.5),while other genes with high expression were analyzed by theDESeq2 package for differential expression.When comparingsusceptible and control, resilient and control, and susceptibleand resilient groups, 13,354 (13,334; 13,326) mRNAs fromclean-read sequences with high-quality were screened, includ-ing 6801 (6616;6523) mRNAs with upregulated expressionand 6544 (6709; 6771) mRNAs with downregulated expres-sion. The criterion for determining the differential expressionof genes was that the fold change of the FPKM value wasmore than two times and p value < 0.05.

Between susceptible mice and control mice, 183 differentlyexpressed mRNAs were screened out, in which 30 mRNAswere upregulated and 153 mRNAs were downregulated(Table S6). The volcano map of mRNAs was made (Fig.

Fig. 5 The validation of differentially expressedmRNAs in the prefrontalcortex from resilient mice versus control mice. Three asterisks showp < 0.001, two asterisks show p < 0.01, and one asterisk shows p < 0.05,

in which a two-sample t test was used for the comparisons betweenresilient mice versus control mice

Psychopharmacology

S5a). Table 1 shows the pathways identified by KEGG basedon DEGs between susceptible mice and control mice. Amongthe genes associated with synapses, the top half of the tableshows genes encoding synaptic elements, and the bottom halfshows genes encoding signal pathways that regulate synapses.Among the genes related to signaling pathways, the top half ofthe table shows genes encoding molecules that constitute thesignaling pathway, and the bottom half shows genes encodingmolecules that regulate the signaling pathway. In the prefron-tal cortex, the upregulated genes related to synaptic elementsin susceptible mice include Hrh1, Ptafr, and Th. Based on theKEGG database, these upregulated genes encode structuralproteins involved in neuroactive ligand-receptor interactionand dopaminergic synapse. The downregulated genes relatedto synaptic elements in the susceptible mice include Htr1a,Chrna1, and Cacna1s. Based on the KEGG database, thesedownregulated genes encode structural proteins involved inserotonergic, neuroactive ligand-receptor interaction,

GABAergic, and cholinergic synapses. Regarding the signal-ing pathways that regulate synaptic function, the upregulatedgenes are Hrh1, Ptafr, and Th. These upregulated genes areinvolved in calcium and prolactin signaling pathways.Downregulated genes related to the signaling pathways in-clude Sema3b, Hhip, Ngfr, Thbs4, Atp2a1, Htr1a, Fzd4,Mmp2, Fgfr4, and Ppp1r3a. These downregulated genes areinvolved in axon guidance, Hedgehog, PI3K-Akt, cAMP, cal-cium, Wnt, GnRH, cGMP-PKG, and Ras signaling pathways.

Between resilient mice and control mice, 461 differentiallyexpressed mRNAswere screened, in which 179 mRNAswereupregulated and 282 mRNAs were downregulated (Table S8).The volcano map of mRNAs was made (Fig. S5b). Table 2shows the pathways identified by KEGG based on DEGsbetween resilient mice and control mice. The upregulatedgenes related to synaptic elements include Glp2r, Ptafr,Gm10334, and Trhr, which encode structural proteins for neu-roactive ligand-receptor interaction. The downregulated genes

Fig. 6 The validation of differentially expressedmRNAs in the prefrontalcortex from susceptible mice versus resilient mice. Three asterisks showp < 0.001, two asterisks show p < 0.01, and one asterisk show p < 0.05, in

which a two-sample t test was used for the comparisons between suscep-tible mice versus resilient mice

Psychopharmacology

related to synaptic elements includeHtr1a, Adora2b, Chrna1,Chrng, and Pla2g4e, which encode structural proteins forneuroactive ligand-receptor interaction, serotonergic, and glu-tamatergic synapses. In terms of signal pathways that regulatesynaptic function, the upregulated genes include Col6a4,Itga10, Lamc2, Ptafr, Trhr, Hspa8, Ppp1r3e, and Eno1 areinvolved in PI3K-Akt, calcium, MAPK, insulin, and HIF-1signaling pathways. The downregulated genes related to sig-naling pathways include Vwf, Col3a1, Adora2b, Tlr1, Tlr6,Fgfr4, Il1r1, Ppp1r3a, Slc2a4, Atp2a1, Mylk4, Nfatc4,Sema3b, Mmp3, Gm5431, TNF, Htr1a, and Mmp2, whichare involved in PI3K-Akt, calcium, Toll-like receptor,MAPK, insulin, cGMP-PKG, cAMP, axon guidance, andGnRH signaling pathways.

Between susceptible mice and resilient mice, 169 different-ly expressed mRNAs were screened out, in which 68 mRNAswere upregulated and 101 mRNAs were downregulated(Table S10). The volcano map of mRNAs was made (Fig.S5c). Table 3 shows the pathways identified by KEGG basedon DEGs between susceptible and resilient mice. The

downregulated gene related to the synaptic element isPla2g4e, which is related to the serotonergic synapse. In termsof signal pathways that regulate synaptic function, the upreg-ulated genes are Vwf, Col6a3, and Eno1b, which are related toPI3K-Akt and HIF-1 signaling pathways. In terms of signal-ing pathways, the downregulated genes are Col5a1, Kdr, Trf,Cd82, Serpine1, Ccr6, Pla2g4e, Acer2, and Naip5, which arerelated to PI3K-Akt, HIF-1, VEGF, p53, chemokine, Ras,sphingolipid, GnRH, MAPK, and NOD-like receptor signal-ing pathways.

To further validate the mRNA sequencing results, we se-lected 28 mRNAs from the DEGs and performed qRT-PCR.The expressions ofHtr1a, Sema3b, A2m, Plin4, Six1, Pcdh17,and Myh8 were downregulated, and the expressions of Th,Apln, and Apold1were upregulated in susceptible mice versuscontrol mice (Fig. 4). The expressions of Adora2b, Htr1a,Chrna1, and Des were downregulated, and the expressionsof Gm10334, Glp2r, Zfp867, Vill, and Pxdn were upregulatedin resilient mice versus control mice (Fig. 5). The expressionof Padi6 was downregulated, and the expressions of Tuba1c,

Table 4 The changed miRNAs predict target mRNAs in susceptible mice versus control mice

miRNAs The predicted target mRNAs thatmatch DEGs in transcriptome

miRNAs The predicted target mRNAs that match DEGs in transcriptome

let-7a-1-3p↓ Rpl29↑, Myoc↑, Pcdhga11↑,Rpl35a↑

miR-486b-5p↓ Hrh1↑, Myoc↑

miR-107-5p↓ Rnps1↑, Aoc2↑ miR-491-5p↓ Rps2↑

miR-10b-5p↓ Hjurp↑ miR-499-5p↓ Apold1↑

miR-124-5p↓ Amy2a5↑ miR-671-5p↓ Apold1↑, Pcsk9↑

miR-1249-3p↓ Amy2a5↑ miR-92b-3p↓ Apln↑, Rpl35a↑

miR-129-1-3p↓ Myoc↑, Pcsk9↑, Rpl35a↑ let-7i-3p↑ Ldb3↓, Flnc↓, Timp1↓, Six1↓

miR-133a-3p↓ Hrh1↑, Th↑ miR-124-3p↑ Sh3tc2↓, Ldb3↓, Tbx1↓, Nexn↓, Gfap↓, Sall1↓

miR-142a-3p↓ 2610507I01Rik↑ miR-141-3p↑ Egr4↓, Spp1↓, Ldb3↓, Neb↓, Gfap↓, Synpo2l↓, Ehd4↓

miR-187-3p↓ Hrh1↑, Rnps1↑, Rpl29↑ miR-183-5p↑ Slc25a13↓, Sfrp2↓, A2m↓, Ldb3↓, Tbx15↓, Cabp7↓, Serpina3n↓, Plin4↓, Myh8↓,Dlk1↓, Sall1↓, Rsc1a1↓

miR-199a-5p↓ Samd3↑, Pcdhga11↑ miR-199a-3p↑ Sncaip↓, Galnt15↓, Egr4↓, A2m↓, Ldb3↓, Flnc↓, Abca8a↓, Neb↓, Htr1a↓, Mmp2↓,Sema3b↓, Casq1↓

miR-199b-3p↓ Hjurp↑, Pcdhga11↑ miR-211-5p↑ Fam160a1↓, A2m↓, Bfsp1↓, Gdnf↓, Ldb3↓, Trdn↓, Slfn8↓, Stab2↓, Synpo2l↓,Dlk1↓, Ptchd4↓, Lrrcc1↓

miR-1a-3p↓ Pcsk9↑ miR-212-5p↑ Gsn↓, Sncaip↓, Fitm1↓, Sema3b↓, Dlk1↓, Gli1↓, Fgfr4↓

miR-1b-5p↓ Upp2↑, Pcdhga11↑ miR-214-3p↑ Sspo↓, Ngfr↓, Cacna1s↓, Tbx1↓, Tnnt1↓, Draxin↓, Hspb6↓, Cdh23↓, Fam46b↓,Col3a1↓

miR-20a-5p↓ Ptafr↑ miR-429-3p↑ Fam160a1↓, Cldn23↓, Ufl1↓, Ldb3↓, Arhgap28↓, Mb↓, Klhl41↓, Lrrcc1↓

miR-219a-5p↓ Hrh1↑, Samd3↑ miR-451a↑ Podn↓, Cldn23↓, A2m↓, Ldb3↓, Tbx1↓, Col15a1↓, Wif1↓, Sostdc1↓, Casq1↓,Lrrcc1↓

miR-3072-3p↓ Pcdhga11↑ miR-490-5p↑ Podn↓, Igfbp5↓, Sspo↓, Best3↓, Col15a1↓, Cdh23↓, Chrna1↓, Dlk1↓, Fgfr4↓,Myom2↓

miR-329-5p↓ Omp↑ miR-673-5p↑ Sspo↓, Cacna1s↓, Alpk3↓, Cdh23↓, Lmod3↓, Pcdh17↓, Plin4↓, Col27a1↓,Ptchd4↓

miR-449a-5p↓ Hrh1↑, Hjurp↑, Ptafr↑,D830030K20Rik↑

miR-96-5p↑ Gsn↓, Pirb↓, Syce1l↓, Ankrd2↓, Col15a1↓, Ppp1r3a↓, Tpm2↓

miR-486a-3p↓ Pcsk9↑

Upward arrow indicates upregulation in the tissue of mPFC from susceptible versus control mice, whereas downward arrow represents downregulation

Psychopharmacology

Tagap, Frzb, Kdr, Pla2g4e, Dnah6, H2-T10, and Pcdha8were upregulated in susceptible mice versus resilient mice(Fig. 6). The qRT-PCR results were consistent with themRNA sequencing results, which confirmed the reliabilityof the sequencing results.

Based on the interaction between mRNAs and miRNAs,the expression levels of mRNAs could be affected bymiRNAs. The bindings of miRNAs with their dicers can de-grade mRNAs and weaken the translation of mRNAs(Afonso-Grunz and Muller 2015; Dwivedi 2014). If the

Table 5 The changed mRNAs predict target miRNAs in susceptible mice versus control mice

Gene symbol The predicted target miRNAsthat match DEGs in transcriptome

GeneSymbol

The predicted target miRNAs that matchDEGs in transcriptome

2610507I01Rik↑ miR-142a-3p↓ Gfap↓ miR-124-3p↑, miR-141-3p↑Amy2a5↑ miR-124-5p↓, miR-1249-3p↓ Gli1↓ miR-212-5p↑Aoc2↑ miR-107-5p↓ Gsn↓ miR-212-5p↑, miR-96-5p↑Apln↑ miR-92b-3p↓ Hspb6↓ miR-214-3p↑Apold1↑ miR-499-5p↓, miR-671-5p↓ Htr1a↓ miR-199a-3p↑D830030K20Rik↑ miR-449a-5p↓ Igfbp5↓ miR-490-5p↑Hjurp↑ miR-10b-5p↓, miR-199b-3p↓, miR-449a-5p↓ Klhl41↓ miR-429-3p↑Hrh1↑ miR-133a-3p↓, miR-187-3p↓, miR-219a-5p↓,

miR-449a-5p↓, miR-486b-5p↓Ldb3↓ let-7i-3p↑, miR-124-3p↑, miR-141-3p↑, miR-183-5p↑, miR-199a-3p↑,

miR-211-5p↑, miR-429-3p↑, miR-451a↑Myoc↑ let-7a-1-3p↓, miR-129-1-3p↓, miR-486b-5p↓ Lmod3↓ miR-673-5p↑Omp↑ miR-329-5p↓ Lrrcc1↓ miR-211-5p↑, miR-429-3p↑, miR-451a↑Pcdhga11↑ let-7a-1-3p↓, miR-199a-5p↓, miR-199b-3p↓,

miR-1b-5p↓, miR-3072-3p↓Mb↓ miR-429-3p↑

Pcsk9↑ miR-129-2-3p↓, miR-1a-3p↓, miR-486a-3p↓,miR-671-5p↓

Mmp2↓ miR-199a-3p↑

Ptafr↑ miR-20a-5p↓, miR-449a-5p↓ Myh8↓ miR-183-5p↑Rnps1↑ miR-107-5p↓, miR-187-3p↓ Myom2↓ miR-490-5p↑Rpl29↑ let-7a-1-3p↓, miR-187-3p↓ Neb↓ miR-141-3p↑, miR-199a-3p↑Rpl35a↑ let-7a-1-3p↓, miR-129-2-3p↓, miR-92b-3p↓ Nexn↓ miR-124-3p↑Rps2↑ miR-491-5p↓ Ngfr↓ miR-214-3p↑Samd3↑ miR-199a-5p↓, miR-219a-5p↓ Pcdh17↓ miR-673-5p↑Th↑ miR-133a-3p↓ Pirb↓ miR-96-5p↑Upp2↑ miR-1b-5p↓ Plin4↓ miR-183-5p↑, miR-673-5p↑A2m↓ miR-183-5p↑, miR-199a-3p↑, miR-211-5p↑,

miR-451a↑Podn↓ miR-451a↑, miR-490-5p↑

Abca8a↓ miR-199a-3p↑ Ppp1r3a↓ miR-96-5p↑Alpk3↓ miR-673-5p↑ Ptchd4↓ miR-211-5p↑, miR-673-5p↑Ankrd2↓ miR-96-5p↑ Rsc1a1↓ miR-183-5p↑Arhgap28↓ miR-429-3p↑ Sall1↓ miR-124-3p↑, miR-183-5p↑Best3↓ miR-490-5p↑ Sema3b↓ miR-199a-3p↑, miR-212-5p↑Bfsp1↓ miR-211-5p↑ Serpina3n↓ miR-183-5p↑Cabp7↓ miR-183-5p↑ Sfrp2↓ miR-183-5p↑Cacna1s↓ miR-214-3p↑, miR-673-5p↑ Sh3tc2↓ miR-124-3p↑Casq1↓ miR-199a-3p↑, miR-451a↑ Six1↓ let-7i-3p↑Cdh23↓ miR-214-3p↑, miR-490-5p↑,

miR-673-5p↑Slc25a13↓ miR-183-5p↑

Chrna1↓ miR-490-5p↑ Slfn8↓ miR-211-5p↑Cldn23↓ miR-429-3p↑, miR-451a↑ Sncaip↓ miR-199a-3p↑, miR-212-5p↑Col15a1↓ miR-451a↑, miR-490-5p↑, miR-96-5p↑ Sostdc1↓ miR-451a↑Col27a1↓ miR-673-5p↑ Spp1↓ miR-141-3p↑Col3a1↓ miR-214-3p↑ Sspo↓ miR-214-3p↑, miR-490-5p↑, miR-673-5p↑Dlk1↓ miR-183-5p↑, miR-211-5p↑, miR-212-5p↑,

miR-490-5p↑Stab2↓ miR-211-5p↑

Draxin↓ miR-214-3p↑ Syce1l↓ miR-96-5p↑Egr4↓ miR-141-3p↑, miR-199a-3p↑ Synpo2l↓ miR-141-3p↑, miR-211-5p↑Ehd4↓ miR-141-3p↑ Tbx1↓ miR-124-3p↑, miR-214-3p↑, miR-451a↑Fam160a1↓ miR-211-5p↑, miR-429-3p↑ Tbx15↓ miR-183-5p↑Fam46b↓ miR-214-3p↑ Timp1↓ let-7i-3p↑Fgfr4↓ miR-212-5p↑, miR-490-5p↑ Tnnt1↓ miR-214-3p↑Fitm1↓ miR-212-5p↑ Tpm2↓ miR-96-5p↑Flnc↓ let-7i-3p↑, miR-199a-3p↑ Trdn↓ miR-211-5p↑Galnt15↓ miR-199a-3p↑ Ufl1↓ miR-429-3p↑Gdnf↓ miR-211-5p↑ Wif1↓ miR-451a↑

Upward arrow indicates upregulation in the tissue of mPFC from susceptible versus control mice, whereas downward arrow represents downregulation

Psychopharmacology

expressions of mRNAs decrease, the corresponding expres-sions of miRNAs will be upregulated, or vice versa. We ana-lyzed the miRNA expression profiles in the prefrontal cortexof the control, resilient, and susceptible groups.

Analysis of differentially expressed miRNAs in theprefrontal cortex of control, resilient, and susceptiblemice

In susceptible mice versus control mice, 47 differentiallyexpressed miRNAs were detected based on the fold changeof FPKM more than two times, Q value < 0.001, of which 13miRNAs were upregulated and 34 miRNAs were downregu-lated (Table S12). According to the three databases(RNAhybrid, TargetScan, and miRanda), miRNA targetgenes were predicted and matched with the mRNA measuredby mRNA sequencing. Table 4 shows that the changedmiRNAs predict target mRNAs between susceptible and con-trol mice. Table 5 shows the changed mRNAs and their cor-responding miRNAs between susceptible and control mice.The interactive networks of miRNAs and correspondingmRNAs between susceptible and control mice were construct-ed (Fig. 7). From Tables 4 and 5, we could find that theregulations of miRNAs and target mRNAs were matched.

In resilient versus control mice, 34 differentially expressedmiRNAs were screened out, of which 9 miRNAs were upreg-ulated and 25 miRNAs were downregulated (Table S13).Three databases (RNAhybrid, TargetScan, and miRanda)about interactions between miRNAs and mRNAs were usedto predict miRNA target genes. Table 6 shows that thechanged miRNAs predict target mRNAs between resilientand control mice. Table 7 shows the changed mRNAs andtheir corresponding miRNAs between resilient and controlmice. The interactive networks of miRNAs and correspondingmRNAs between resilient mice and control mice were con-structed (Fig. 8). From Tables 6 and 7, we could find that theregulations of miRNAs and target mRNAs were matched.

In susceptible versus resilient mice, 20 differentiallyexpressed miRNAs were selected, of which 10 miRNAs wereupregulated and 10 miRNAs were downregulated(Table S14). According to the three databases (RNAhybrid,TargetScan, and miRanda) about interactions betweenmiRNAs and mRNAs, miRNA target genes were predicted.Table 8 shows that the changed miRNAs predict targetmRNAs between susceptible and resilient mice. Table 9shows the changed mRNAs and their correspondingmiRNAs between susceptible and resilient mice. The interac-tive networks of miRNAs and corresponding mRNAs

Fig. 7 MicroRNA/mRNA network in susceptible mice versus controlmice. MicroRNA/mRNA networks were constructed between the 36miRNAs and 94 overlapped mRNAs using transcriptome expression dataand predicted target genes from RNAhybrid, Targetscan, and miRanda

databases. Red symbols present the upregulated miRNAs or mRNAs andthe deeper the red, the more upregulated. Blue symbols present the down-regulated miRNAs or mRNAs and the deeper the blue, the moredownregulated

Psychopharmacology

between susceptible and resilient mice were constructed (Fig.9). From Tables 8 and 9, we could find that the regulations ofmiRNAs and target mRNAs were matched.

To further validate the miRNA sequencing results, we se-lected a portion of miRNAs to perform qRT-PCR. ThemiRNAs selected in susceptible mice versus control mice in-cluded miR-211-5p, miR-183-5p, miR-673-5p, miR-92b-3p,and miR-671-5p (Fig. 10a). The miRNAs selected in resilientmice versus control mice included miR-378d, miR-92b-3p,miR-3072-3p, miR-532-3p, and miR-744-5p (Fig. 10b). ThemiRNAs selected in susceptible mice versus resilient miceincluded miR-219a-2-3p, miR-338-3p, miR-199a-3p, miR-212-5p, and let-7a-1-3p (Fig. 10c). The qRT-PCR results were

consistent with the miRNA sequencing results, which furthervalidated our study. It should also be noted that somemiRNAswere reversely expressed in susceptible mice versus resilientmice. In other words, these miRNAs might affect the suscep-tibility to psychological stress (Table S14).

Pcdh17 and Plin4 are the targets of miR-673-5p

To verify the relationship between miRNAs and their pre-dicted target mRNAs in Tables 4, 5, 6, 7, 8, and 9, qRT-PCR and dual-luciferase reporter assay were used to verifywhether miR-673-5p targeted Pcdh17 and Plin4. First,qRT-PCR results showed that miR-673-5p was negatively

Table 6 The changed miRNAs predict target mRNAs in resilient mice versus control mice

miRNAs The predicted target mRNAs thatmatch DEGs in transcriptome

miRNAs The predicted target mRNAs that match DEGs in transcriptome

miR-10a-5p↓ Bub1b↑, C030037D09Rik↑, Fut10↑, Gp1bb↑,Hjurp↑, Mettl7a3↑, Rnps1↑, Slc37a2↑,Spint1↑

miR-378d↓ Cdk15↑, Fam163a↑, Glp2r↑, Itga10↑, Mirt1↑, Vill↑

miR-10b-5p↓ Abhd14a↑, Cdk15↑, Cfap69↑, Glp2r↑,Gp1bb↑, Hjurp↑, Hyal1↑, Ppp1r3e↑,Spint1↑, Zfp85os↑

miR-449a-5p↓ Bbs12↑, D830030K20Rik↑, Hectd2os↑, Hjurp↑, Ptafr↑, Tekt2↑

miR-1249-3p↓ Amy2a5↑, Capn11↑, Fam163a↑, Gm10516↑,Hmga1↑, Pxdn↑, Slc37a2↑, Tnfrsf25↑

miR-486a-3p↓ Fut10↑, Ly6a↑, Park2↑, Pcsk9↑,Upk1b↑, Zfp85os↑

miR-133a-3p↓ Elane↑, Itga10↑, Tmed5↑, Tmem45a↑,Zfp874a↑

miR-486a-5p↓ Cox7a2l↑, Mirt1↑, Park2↑, Slc39a2↑

miR-142a-3p↓ 2610507I01Rik↑ miR-486b-5p↓ Best1↑, E230016M11Rik↑, Myoc↑, Slc30a2↑, Slc39a2↑, Zfp354b↑

miR-199a-5p↓ Adgrf4↑, Bbs12↑, Btla↑, Gm10037↑,Hist1h2be↑, Pcdhga11↑, Rpl21↑, Zfp867↑

miR-499-5p↓ Chd9↑, Fam26e↑, Rpl34↑, Slc30a2↑

miR-199b-3p↓ Elane↑, Hjurp↑, Kiss1↑, Ly6a↑, Pcdhga11↑,Vill↑

miR-744-5p↓ Hspa8↑, Kiss1↑, Wfdc18↑

miR-1a-3p↓ Fv1↑, Gm10635↑, Pcsk9↑, Ppp1r3e↑,Srd5a1↑

miR-92b-3p↓ Apln↑, Fv1↑, Lax1↑, Rpl35a↑, Vill↑

miR-1b-5p↓ Impg2↑, Pcdhga11↑, Scoc↑, Upp2↑,Zfp729b↑

miR-183-5p↑ A2m↓, Dlk1↓, H2-DMb1↓, Klhl31↓, Lrat↓, Morf4l1b↓, Myh8↓,Mylk4↓, Pax7↓, Plin4↓, Sall1↓, Serpina3n↓, Tlr6↓, Ttn↓

miR-206-3p↓ Abca17↑, Ang↑, Mettl7a3↑, Slc37a2↑, Stk26↑ miR-199a-3p↑ A2m↓, Abca8a↓, Atp10d↓, B3gnt9↓, Casq1↓, Ccr6↓, Flnc↓,Galnt15↓, Htr1a↓, Ifit3b↓, Igfbp7↓, Lrat↓, Mmp2↓, Neb↓,Sema3b↓, Slc16a12↓, Ttn↓, Vash2↓

miR-223-3p↓ Dmkn↑, Nlrp5-ps↑ miR-211-5p↑ 4930555G01Rik↓, A2m↓, Abhd1↓, Atp10d↓, D17H6S56E5↓, Dlk1↓,Fam160a1↓, Gdnf↓, Klc3↓, Lrrcc1↓, Pcdhga4↓, Ptchd4↓, Rsph1↓,Shox2↓, Synpo2l↓, Trdn↓, Ttn↓, Xlr4b↓

miR-296-5p↓ 1700047I17Rik2↑, Aoc2↑, Hmga1↑,Pcdhga11↑, Zfp933↑

miR-338-5p↑ Adm↓, Dcn↓, Fmo2↓, Klhl41↓, Lmod3↓, Lpp↓, Lrrcc1↓, Pcdhb3↓,Pla2g4e↓, Plac8↓, Shmt1↓, Ttn↓, Xdh↓, Zbtb25↓

miR-3072-3p↓ Pcdhga11↑, Tnfrsf25↑ miR-384-5p↑ Fst↓, Gdnf↓, Iigp1↓, Musk↓, Serping1↓,Slc16a12↓, Zbtb25↓

miR-351-5p↓ Chd9↑, Lamc2↑, Pxdn↑ miR-451a↑ A2m↓, Actn2↓, BC021767↓, Casq1↓, Col15a1↓, Dnah7a↓, Il1r1↓,Lpp↓, Lrrcc1↓, Pcdhb2↓, Postn↓, Sostdc1↓, Wif1↓

miR-375-3p↓ Cox7a2l↑, Cyp4f15↑, Etnk2↑, Hjurp↑,Hmga1↑, Lax1↑, Nek11↑, Sftpc↑, Sla2↑,Slc39a2↑, Stk26↑

miR-532-3p↑ Des↓, Ehd4↓, Ifit2↓, Itga11↓, Kif24↓, Ky↓, Lmod3↓, Mxra8↓,Myh7b↓, Myl1↓, Pcdhga4↓, Sall1↓, Sostdc1↓, Ttn↓

miR-378a-5p↓ Apln↑, Cd164l2↑, Dmkn↑, Etnppl↑, Hjurp↑,Hmga1↑, Insl5↑, Nlrp5-ps↑

miR-673-5p↑ Angptl7↓, Col27a1↓, Col6a3↓, Gbp10↓, Hspg2↓, Igfbp7↓, Klhl31↓,Lmod3↓, Pcdh17↓, Plin4↓, Ptchd4↓, Ttn↓, Vwf↓

miR-378b↓ Ankub1↑, Bbs12↑, Cox7a2l↑, Golt1a↑,Rnf17↑, Spint1↑

miR-96-5p↑ Ankrd2↓, Col15a1↓, Dnah6↓, Fut4↓, Hspg2↓, Myh7b↓, Ppp1r3a↓,Tmod4↓, Tpm2↓, Ttn↓, Vash2↓

Upward arrow indicates upregulation in the tissue of mPFC from resilient versus control mice, whereas downward arrow represents downregulation

Psychopharmacology

Table 7 The changed mRNAs predict target miRNAs in resilient mice versus control mice

mRNA The predicted target miRNAs that match DEGs intranscriptome

mRNA The predicted target miRNAs that match DEGs intranscriptome

1700047I17Rik2↑ miR-296-5p↓ 4930555G01Rik↓ miR-211-5p↑

2610507I01Rik↑ miR-142a-3p↓ A2m↓ miR-183-5p↑, miR-199a-3p↑, miR-211-5p↑, miR-451a↑

Abca17↑ miR-206-3p↓ Abca8a↓ miR-199a-3p↑

Abhd14a↑ miR-10b-5p↓ Abhd1↓ miR-211-5p↑

Adgrf4↑ miR-199a-5p↓ Actn2↓ miR-451a↑

Amy2a5↑ miR-1249-3p↓ Adm↓ miR-338-5p↑

Ang↑ miR-206-3p↓ Angptl7↓ miR-673-5p↑

Ankub1↑ miR-378b↓ Ankrd2↓ miR-96-5p↑

Aoc2↑ miR-296-5p↓ Atp10d↓ miR-199a-3p↑, miR-211-5p↑

Apln↑ miR-378a-5p↓, miR-92b-3p↓ B3gnt9↓ miR-199a-3p↑

Bbs12↑ miR-199a-5p↓, miR-378b↓, miR-449a-5p↓ BC021767↓ miR-451a↑

Best1↑ miR-486b-5p↓ Casq1↓ miR-199a-3p↑, miR-451a↑

Btla↑ miR-199a-5p↓ Ccr6↓ miR-199a-3p↑

Bub1b↑ miR-10a-5p↓ Col15a1↓ miR-451a↑, miR-96-5p↑

C030037D09Rik↑ miR-10a-5p↓ Col27a1↓ miR-673-5p↑

Capn11↑ miR-1249-3p↓ Col6a3↓ miR-673-5p↑

Cd164l2↑ miR-378a-5p↓ D17H6S56E-5↓ miR-211-5p↑

Cdk15↑ miR-10b-5p↓, miR-378d↓ Dcn↓ miR-338-5p↑

Cfap69↑ miR-10b-5p↓ Des↓ miR-532-3p↑

Chd9↑ miR-351-5p↓, miR-499-5p↓ Dlk1↓ miR-183-5p↑, miR-211-5p↑

Cox7a2l↑ miR-375-3p↓, miR-378b↓,miR-486a-5p↓

Dnah6↓ miR-96-5p↑

Cyp4f15↑ miR-375-3p↓ Dnah7a↓ miR-451a↑

D830030K20Rik↑ miR-449a-5p↓ Ehd4↓ miR-532-3p↑

Dmkn↑ miR-223-3p↓, miR-378a-5p↓ Fam160a1↓ miR-211-5p↑

E230016M11Rik↑ miR-486b-5p↓ Flnc↓ miR-199a-3p↑

Elane↑ miR-133a-3p↓, miR-199b-3p↓ Fmo2↓ miR-338-5p↑

Etnk2↑ miR-375-3p↓ Fst↓ miR-384-5p↑

Etnppl↑ miR-378a-5p↓ Fut4↓ miR-96-5p↑

Fam163a↑ miR-1249-3p↓, miR-378d↓ Galnt15↓ miR-199a-3p↑

Fam26e↑ miR-499-5p↓ Gbp10↓ miR-673-5p↑

Fut10↑ miR-10a-5p↓, miR-486a-3p↓ Gdnf↓ miR-211-5p↑, miR-384-5p↑

Fv1↑ miR-1a-3p↓, miR-92b-3p↓ H2-DMb1↓ miR-183-5p↑

Glp2r↑ miR-10b-5p↓, miR-378d↓ Hspg2↓ miR-673-5p↑, miR-96-5p↑

Gm10037↑ miR-199a-5p↓ Htr1a↓ miR-199a-3p↑

Gm10516↑ miR-1249-3p↓ Ifit2↓ miR-532-3p↑

Gm10635↑ miR-1a-3p↓ Ifit3b↓ miR-199a-3p↑

Golt1a↑ miR-378b↓ Igfbp7↓ miR-199a-3p↑, miR-673-5p↑

Gp1bb↑ miR-10a-5p↓, miR-10b-5p↓ Iigp1↓ miR-384-5p↑

Hectd2os↑ miR-449a-5p↓ Il1r1↓ miR-451a↑

Hist1h2be↑ miR-199a-5p↓ Itga11↓ miR-532-3p↑

Hjurp↑ miR-10a-5p↓, miR-10b-5p↓, miR-199b-3p↓,miR-375-3p↓, miR-378a-5p↓, miR-449a-5p↓

Kif24↓ miR-532-3p↑

Hmga1↑ miR-1249-3p↓, miR-296-5p↓, miR-375-3p↓,miR-378a-5p↓

Klc3↓ miR-211-5p↑

Hspa8↑ miR-744-5p↓ Klhl31↓ miR-183-5p↑, miR-673-5p↑

Hyal1↑ miR-10b-5p↓ Klhl41↓ miR-338-5p↑

Impg2↑ miR-1b-5p↓ Ky↓ miR-532-3p↑

Insl5↑ miR-378a-5p↓ Lmod3↓ miR-338-5p↑, miR-532-3p↑, miR-673-5p↑

Psychopharmacology

Table 7 (continued)

mRNA The predicted target miRNAs that match DEGs intranscriptome

mRNA The predicted target miRNAs that match DEGs intranscriptome

Itga10↑ miR-133a-3p↓, miR-378d↓ Lpp↓ miR-338-5p↑, miR-451a↑

Kiss1↑ miR-199b-3p↓, miR-744-5p↓ Lrat↓ miR-183-5p↑, miR-199a-3p↑

Lamc2↑ miR-351-5p↓ Lrrcc1↓ miR-211-5p↑, miR-338-5p↑, miR-451a↑

Lax1↑ miR-375-3p↓, miR-92b-3p↓ Mmp2↓ miR-199a-3p↑

Ly6a↑ miR-199b-3p↓, miR-486a-3p↓ Morf4l1b↓ miR-183-5p↑

Mettl7a3↑ miR-10a-5p↓, miR-206-3p↓ Musk↓ miR-384-5p↑

Mirt1↑ miR-378d↓, miR-486a-5p↓ Mxra8↓ miR-532-3p↑

Myoc↑ miR-486b-5p↓ Myh7b↓ miR-532-3p↑, miR-96-5p↑

Nek11↑ miR-375-3p↓ Myh8↓ miR-183-5p↑

Nlrp5-ps↑ miR-223-3p↓, miR-378a-5p↓ Myl1↓ miR-532-3p↑

Park2↑ miR-486a-3p↓, miR-486a-5p↓ Mylk4↓ miR-183-5p↑

Pcdhga11↑ miR-199a-5p↓, miR-199b-3p↓, miR-1b-5p↓,miR-296-5p↓, miR-3072-3p↓

Neb↓ miR-199a-3p↑

Pcsk9↑ miR-1a-3p↓, miR-486a-3p↓ Pax7↓ miR-183-5p↑

Ppp1r3e↑ miR-10b-5p↓, miR-1a-3p↓ Pcdh17↓ miR-673-5p↑

Ptafr↑ miR-449a-5p↓ Pcdhb2↓ miR-451a↑

Pxdn↑ miR-1249-3p↓, miR-351-5p↓ Pcdhb3↓ miR-338-5p↑

Rnf17↑ miR-378b↓ Pcdhga4↓ miR-211-5p↑, miR-532-3p↑

Rnps1↑ miR-10a-5p↓ Pla2g4e↓ miR-338-5p↑

Rpl21↑ miR-199a-5p↓ Plac8↓ miR-338-5p↑

Rpl34↑ miR-499-5p↓ Plin4↓ miR-183-5p↑, miR-673-5p↑

Rpl35a↑ miR-92b-3p↓ Postn↓ miR-451a↑

Scoc↑ miR-1b-5p↓ Ppp1r3a↓ miR-96-5p↑

Sftpc↑ miR-375-3p↓ Ptchd4↓ miR-211-5p↑, miR-673-5p↑

Sla2↑ miR-375-3p↓ Rsph1↓ miR-211-5p↑

Slc30a2↑ miR-486b-5p↓, miR-499-5p↓ Sall1↓ miR-183-5p↑, miR-532-3p↑

Slc37a2↑ miR-10a-5p↓, miR-1249-3p↓ Sema3b↓ miR-199a-3p↑

Slc39a2↑ miR-375-3p↓, miR-486a-5p↓, miR-486b-5p↓ Serpina3n↓ miR-183-5p↑

Spint1↑ miR-10a-5p↓, miR-10b-5p↓, miR-378b↓ Serping1↓ miR-384-5p↑

Srd5a1↑ miR-1a-3p↓ Shmt1↓ miR-338-5p↑

Stk26↑ miR-206-3p↓, miR-375-3p↓ Shox2↓ miR-211-5p↑

Tekt2↑ miR-449a-5p↓ Slc16a12↓ miR-199a-3p↑, miR-384-5p↑

Tmed5↑ miR-133a-3p↓ Sostdc1↓ miR-451a↑, miR-532-3p↑

Tmem45a↑ miR-133a-3p↓ Synpo2l↓ miR-211-5p↑

Tnfrsf25↑ miR-1249-3p↓, miR-3072-3p↓ Tlr6↓ miR-183-5p↑

Upk1b↑ miR-486a-3p↓ Tmod4↓ miR-96-5p↑

Upp2↑ miR-1b-5p↓ Tpm2↓ miR-96-5p↑

Vill↑ miR-199b-3p↓, miR-378d↓, miR-92b-3p↓ Trdn↓ miR-211-5p↑

Wfdc18↑ miR-744-5p↓ Ttn↓ miR-183-5p↑, miR-199a-3p↑, miR-211-5p↑,miR-338-5p↑, miR-532-3p↑, miR-673-5p↑,miR-96-5p↑

Zfp354b↑ miR-486b-5p↓ Vash2↓ miR-199a-3p↑, miR-96-5p↑

Zfp729b↑ miR-1b-5p↓ Vwf↓ miR-673-5p↑

Zfp85os↑ miR-10b-5p↓, miR-486a-3p↓ Wif1↓ miR-451a↑

Zfp867↑ miR-199a-5p↓ Xdh↓ miR-338-5p↑

Zfp874a↑ miR-133a-3p↓ Xlr4b↓ miR-211-5p↑

Zfp933↑ miR-296-5p↓ Zbtb25↓ miR-338-5p↑, miR-384-5p↑

Upward arrow indicates upregulation in the tissue of mPFC from resilient versus control mice, whereas downward arrow represents downregulation

Psychopharmacology

correlated with Pcdh17 and Plin4, respectively (Fig. 11a,c). To further verify the targeting relationship of miRNAsand mRNAs, dual-luciferase reporter assay was per-formed. First, wild-type dual-luciferase reporter plasmids

containing the binding sites of the miR-673-5p in Pcdh17and Plin4 were constructed. Mutant dual-luciferase report-er plasmids were constructed after mutation of the bindingsites. The wild-type or mutant plasmid was co-transfected

Fig. 8 MicroRNA/mRNA network in resilient mice versus control mice.MicroRNA/mRNA networks were constructed between the 34 miRNAsand 180 overlapped mRNAs using transcriptome expression data andpredicted target genes from RNAhybrid, Targetscan, and miRanda

databases. Red symbols present the upregulated miRNAs or mRNAsand the deeper the red, the more upregulated. Blue symbols present thedownregulated miRNAs or mRNAs and the deeper the blue, the moredownregulated

Table 8 The changed miRNAs predict target mRNAs in susceptible mice versus resilient mice

miRNAs The predicted target mRNAs that match DEGs intranscriptome

miRNAs The predicted target mRNAs that match DEGs intranscriptome

let-7a-1-3p↓ Tagap↑, Acer2↑ miR-219a-2-3p↓ Morf4l1b↑, H2-T10↑, Lpp↑, Tlr1↑, Ccr6↑

let-7i-3p↑ Ldb3↓, Abca13↓, Etnppl↓, 9630013A20Rik↓, Rad54b↓,Mobp↓

miR-219a-5p↓ Acer2↑, Pyroxd2↑

miR-10a-5p↑ Cd82↓, Adamts4↓, Opalin↓, Krt80↓, Bub1b↓ miR-3071-5p↑ Abca13↓, Gjc2↓, Opalin↓, Aspm↓

miR-10b-5p↑ Cd82↓, Ehd4↓, Nkx6–2↓, Spink8↓, Opalin↓ miR-338-3p↓ Mid1↑, Pcdha8↑, Slc7a15↑, Cfap206↑

miR-124-3p↑ Ldb3↓, Ldb3↓, Cd82↓, Casr↓, St18↓, Tgtp1↓ miR-338-5p↓ Lpp↑, Pla2g4e↑

miR-15b-5p↑ Tmem125↓, Cd82↓, Tnni1↓, Nudt22↓, Npcd↓, Adgrf4↓ miR-490-5p↑ Abca13↓, Dna2↓, Ermn↓, Sspo↓, 6720483E21Rik↓

miR-199a-3p↑ Ldb3↓, Josd2↓, Mapk15↓ miR-491-5p↓ Mns1↑, Ackr2↑

miR-199a-5p↑ Mbp↓, Tnni1↓, Btla↓, Adgrf4↓, Gm10037↓ miR-532-3p↓ 4930407I10Rik↑

miR-1b-5p↓ Frzb↑, Serpine1↑ miR-667-3p↓ Lpp↑, Angptl7↑, Acer2↑

miR-212-5p↑ Cd82↓, Mbp↓, Slc39a2↓, Padi6↓

Upward arrow indicates upregulation in the tissue of mPFC from susceptible versus resilient mice, whereas downward arrow represents downregulation

Psychopharmacology

with miR-673-5p mimic or negative control intoHEK293T cells. The experimental results showed thatmiR-673-5p mimic can significantly reduce the relativeactivities of wild-type dual-luciferase reporter plasmidsfor Pcdh17 and Plin4, while the relative activities of thenegative control group were not affected (Fig. 11b, d).After the binding sites of miR-673-5p in Pcdh17 andPlin4 were mutated, the relative activities of the mutantdual-luciferase reporter plasmids were not affected bymiR-673-5p mimic. These results indicated that Pcdh17and Plin4 were the targets of miR-673-5p, which wereconsistent with the results of our predicted miRNA targetgenes.

Discussion

Through high-throughput sequencing, the expressions ofmRNAs and miRNAs in the prefrontal cortex among the sus-ceptible mice, resilient mice, and control mice were quantita-tively analyzed. In susceptible mice versus control mice, theupregulated genes involved in synaptic elements includeHrh1, Ptafr, and Th. These genes encode structural proteinsinvolved in neuroactive ligand-receptor interaction, dopami-nergic synapse. Downregulated genes associated with synap-tic elements include Htr1a, Chrna1, and Cacna1s, which en-code structural proteins for serotonergic, neuroactive ligand-receptor interaction, GABAergic, and cholinergic synapses. In

Table 9 The changed mRNAspredict target miRNAs insusceptible mice versus resilientmice

mRNA The predicted target miRNAs thatmatch DEGs in transcriptome

mRNA The predicted target miRNAs thatmatch DEGs in transcriptome

4930407I10Rik↑ miR-532-3p↓ Lpp↑ miR-219a-2-3p↓, miR-338-5p↓,miR-667-3p↓

6720483E21Rik↓ miR-490-5p↑ Mapk15↓ miR-199a-3p↑

9630013A20Rik↓ let-7i-3p↑ Mbp↓ miR-199a-5p↑, miR-212-5p↑,miR-212-5p↑

Abca13↓ let-7i-3p↑, miR-3071-5p↑,miR-490-5p↑

Mid1↑ miR-338-3p↓

Acer2↑ let-7a-1-3p↓, miR-219a-5p↓,miR-667-3p↓

Mns1↑ miR-491-5p↓

Ackr2↑ miR-491-5p↓ Mobp↓ let-7i-3p↑

Adamts4↓ miR-10a-5p↑ Morf4l1b↑ miR-219a-2-3p↓

Adgrf4↓ miR-15b-5p↑, miR-199a-5p↑ Nkx6–2↓ miR-10b-5p↑

Angptl7↑ miR-667-3p↓ Npcd↓ miR-15b-5p↑

Aspm↓ miR-3071-5p↑ Nudt22↓ miR-15b-5p↑

Btla↓ miR-199a-5p↑ Opalin↓ miR-10a-5p↑, miR-10b-5p↑,miR-3071-5p↑

Bub1b↓ miR-10a-5p↑ Padi6↓

Casr↓ miR-124-3p↑ Pcdha8↑ miR-212-5p↑

Ccr6↑ miR-219a-2-3p↓ Pla2g4e↑ miR-338-3p↓

Cd82↓ miR-10a-5p↑, miR-10b-5p↑,miR-124-3p↑, miR-15b-5p↑,miR-212-5p↑

Pyroxd2↑ miR-338-5p↓

Cfap206↑ miR-338-3p↓ Rad54b↓ miR-219a-5p↓

Dna2↓ miR-490-5p↑ Serpine1↑ let-7i-3p↑

Ehd4↓ miR-10b-5p↑ Slc39a2↓ miR-1b-5p↓

Ermn↓ miR-490-5p↑ Slc7a15↑ miR-212-5p↑

Etnppl↓ let-7i-3p↑ Spink8↓ miR-338-3p↓

Frzb↑ miR-1b-5p↓ Sspo↓ miR-10b-5p↑

Gjc2↓ miR-3071-5p↑ St18↓ miR-490-5p↑

Gm10037↓ miR-199a-5p↑ Tagap↑ miR-124-3p↑

H2-T10↑ miR-219a-2-3p↓ Tgtp1↓ let-7a-1-3p↓

Josd2↓ miR-199a-3p↑ Tlr1↑ miR-124-3p↑

Krt80↓ miR-10a-5p↑ Tmem125↓ miR-219a-2-3p↓

Ldb3↓ let-7i-3p↑, miR-124-3p↑,miR-124-3p↑, miR-199a-3p↑

Tnni1↓ miR-15b-5p↑,miR-199a-5p↑

Upward arrow indicates upregulation in the tissue of mPFC from susceptible versus resilient mice, whereasdownward arrow represents downregulation

Psychopharmacology

terms of signal pathways that regulate synaptic function, theupregulated genes are Hrh1, Ptafr, and Th. These genes arerelated to calcium and prolactin signaling pathways.Downregulated genes such as Sema3b, Hhip, Ngfr, Thbs4,Atp2a1, Htr1a, Fzd4, Mmp2, Fgfr4, and Ppp1r3a are in-volved in axon guidance, Hedgehog, PI3K-Akt, cAMP, cal-cium, Wnt, GnRH, cGMP-PKG, Ras signaling pathways. It isworth noting that some genes encoding synaptic elements areupregulated in the prefrontal cortex from susceptible miceversus control mice, while some genes that regulate thesesynapses are downregulated, suggesting that the regulationof synaptic function is unbalanced. In addition to the imbal-ance between genes in the signaling pathways, the up- anddownregulation of several different signaling pathways alsoimbalances the entire molecular networks of the prefrontalcortex, which may be related to psychological stress-inducedfear memory. In summary, the differential expression of genesencoding synaptic elements may help synapse form and trans-mit fear memory.

In resilient mice versus control mice, upregulated genesassociated with synaptic elements include Glp2r, Ptafr,Gm10334, and Trhr, which encode structural elements forneuroactive ligand-receptor interaction. Downregulated genesrelated to synaptic elements includeHtr1a, Adora2b, Chrna1,Chrng, and Pla2g4e, which encode structural proteins for

neuroactive ligand-receptor interaction, serotonergic, and glu-tamatergic synapses. For the signaling pathways, upregulatedgenes include Col6a4, Itga10, Lamc2, Ptafr, Trhr, Hspa8,Ppp1r3e, and Eno1. These genes are involved in the PI3K-Akt, calcium, MAPK, insulin, and HIF-1 signaling pathways.Downregulated genes related to the signaling pathways in-clude Vwf, Col3a1, Adora2b, Tlr1, Tlr6, Fgfr4, Il1r1,Ppp1r3a, Slc2a4, Atp2a1, Mylk4, Nfatc4, Sema3b, Mmp3,Gm5431, TNF, Htr1a, and Mmp2, which are involved in thePI3K-Akt, calcium, Toll-like receptor, MAPK, insulin,cGMP-PKG, cAMP, axon guidance, and GnRH signalingpathways. These data show that some genes encoding signalpathways are upregulated, while some genes that regulatethese signal pathways are downregulated, indicating that theregulation of each signaling pathway is unbalanced. Besides,the upregulation and downregulation of different signalingpathways also make the entire molecular network of the pre-frontal cortex unbalanced, which may be related to resilience.

Compared with the control group, in the susceptible groupand the resilient group, if genes are differentially expressed inboth groups and change in the same direction, these genes andtheir translated proteins may be related to psychological stresstreatment. This hypothesis is based on the fact that both thesusceptible group and the resilient group are subjected to psy-chological stress, but their responses to psychological stress

Fig. 9 MicroRNA/mRNA network in susceptible mice versus resilientmice. MicroRNA/mRNA networks were constructed between the 18miRNAs and 53 overlapped mRNAs using transcriptome expression dataand predicted target genes from RNAhybrid, Targetscan, and miRanda

databases. Red symbols present the upregulated miRNAs or mRNAs andthe deeper the red, the more upregulated. Blue symbols present the down-regulated miRNAs or mRNAs and the deeper the blue, the moredownregulated

Psychopharmacology

are different. Analysis of the differentially expressed genes inthe susceptible group and the resilient group reveals that someof the differentially expressed genes are overlapping, whilePtafr is upregulated and Htr1a, Chrna1, Sema3b, Mmp2,Fgfr4, and so on are downregulated. These changed genesmay be related to psychological stress treatment. Thesechanged genes are involved in the calcium signaling pathway,

neuroactive ligand-receptor interaction, serotonergic synapse,axon guidance, cAMP, GnRH, estrogen, PI3K-Akt, MAPK,Rap1, Ras signal pathways, and so on. Some of these geneshave been reported to be associated with stress. For example,Htr1a, an inhibitory G protein-coupled receptor, is associatedwith a variety of mental illnesses, including anxiety, depres-sion, and dyskinesia (Staron et al. 2018).

Fig. 10 The validation of differentially expressed microRNAs in theprefrontal cortex. a The validation of differentially expressedmicroRNAs in the prefrontal cortex from susceptible mice versuscontrol mice. b The validation of differentially expressed microRNAsin the prefrontal cortex from resilient mice versus control mice. c The

validation of differentially expressed microRNAs in the prefrontal cortexfrom susceptible mice versus resilient mice. Three asterisks showp < 0.001 and two asterisks show p < 0.01, in which a two-sample t testwas used for the comparisons

Psychopharmacology

In susceptible mice versus resilient mice, the downregulatedgene associated with the synaptic element is Pla2g4e, which isinvolved in the serotonergic synapse. In terms of signaling path-ways,Vwf,Col6a3, andEno1b are upregulated genes, which areinvolved in PI3K-Akt and HIF-1 signaling pathways. In termsof signaling pathways, the downregulated genes are Col5a1,Kdr, Thbs4, Trf, Cd82, Serpine1, Ccr6, Pla2g4e, Acer2, andNaip5, which are involved in PI3K-Akt, HIF-1, VEGF, p53,chemokine, Ras, sphingolipid, GnRH, MAPK, and NOD-likereceptor signaling pathways. These results indicate that thechanged genes involved in VEGF, p53, chemokine, Ras,Sphingolipid, GnRH, MAPK, and NOD-like receptor signalingpathways may be related to the susceptibility to psychologicalstress. In addition, the increased expressions of genes in certainspecific signaling pathways and the decreased expression ofother genes in these pathways indicate an imbalance in the reg-ulation of each signaling pathway. A variety of signaling path-ways and the upregulation and downregulation of genes in thesignaling pathways cause an imbalance in the molecular net-works of the prefrontal cortex, leading to abnormal neuronaland synaptic functions in the prefrontal cortex, which can cause

stress susceptibility or resilience. Pla2g4e belongs to cytosolicphospholipase A2 (cPLA2), which selectively catalyzes the hy-drolysis of the sn-2 site of the glycerol portion of the membranephospholipids, breaking its ester bond (Desbene et al. 2012). Inprevious studies, it is considered to be related to neural structureand function, and neurobehavioral disorder (Everson et al.2019), and some literature suggests that this gene may be a riskgene for panic disorder (Morimoto et al. 2018).

Stress is a change in emotional behavior caused by changesin dangerous or unexpected external conditions (Parsons andRessler 2013). Fear memories are usually caused by stressfulevents in life (Baldi and Bucherelli 2015; Izquierdo et al.2016; Makkar et al. 2010). Long-term chronic and acute stresshave been shown to have adverse effects on biological indi-viduals and can affect the neural structure and functional plas-ticity of the brain and lead to the occurrence of various dis-eases (Popoli et al. 2011; Radley et al. 2008). The eliminationof fear memory is an important step in reducing pathologicalemotional responses and treating secondary diseases (deQuervain et al. 2017; Flores et al. 2018; Zhu et al. 2017). Inorder to find therapeutic targets for these diseases, we need to

Fig. 11 qRT-PCR and dual-luciferase reporter assay validatedmiRNA targeting mRNA. a qRT-PCR experiments verified thecorrelation between miR-673-5pand predicted target gene Pcdh17in the prefrontal cortex (r = 0.946;p < 0.05). b The dual-luciferasereporter assay was performed byco-transfection of a wild-type ormutant Pcdh17 plasmid withmiR-673-5p or a negative controlinto HEK293T cells. c qRT-PCRexperiments verified the correla-tion between miR-673-5p andpredicted target gene Plin4 in theprefrontal cortex (r = 0.960;p < 0.05). d The dual-luciferasereporter assay was performed byco-transfection of a wild-type ormutant Plin4 plasmid with miR-673-5p or a negative control intoHEK293T cells. The data aremean ± SEM, and the statisticalmethod is the unpaired t test.**p < 0.01, ***p < 0.001

Psychopharmacology

find molecular mechanisms and signaling pathways related tostress susceptibility and resilience. In this study, we focusedon analyzing the mRNA and miRNA profiles of stress sus-ceptibility and resilience in the medial prefrontal cortex. Amodel of psychological stress-induced fear memory wasadopted in our research. Compared with electrical stimulation,social stress caused by psychological stress is closer to life(Tsankova et al. 2006; Vasconcelos et al. 2015).

In verifying our research, we performed high-throughputsequencing of mRNAs and miRNAs as well as bioinformaticanalysis of the sequencing results and used RNAhybrid,Targetscan, and miRanda for target gene prediction. We se-lected a part of mRNAs and miRNAs for quantitative RT-PCR and verified the accuracy of target gene prediction bydual-luciferase reporter assay. Our results showed that in high-throughput sequencing, changes in mRNA expression wereconsistent with changes in miRNA expression. qRT-PCR ver-ified the accuracy of the sequencing results of mRNAs andmiRNAs. Analysis of the dual-luciferase reporter assay con-firmed the interaction between miR-673-5p and Plin4 andPcdh17, respectively. Combining these analyses, we are con-fident in our results, which is better than the previous analysisof mRNAs or miRNAs alone.

We also used BioJupies for analysis and obtained similarresults. L1000CDS2 Query (Duan et al. 2016) andL1000FWD (Wang et al. 2018) were used to screen potentialsmall molecules that can mimic or reverse the effects of a geneexpression signature generated from a differential gene ex-pression analysis. In general, BioJupies synthesizes informa-tion from a large number of tools and databases and providesextremely potential information for revealingmechanisms andrecommending interventions (Torre et al. 2018). In the futureresearch involving RNA-seq data processing and analysis, thiswill be one of our preferred tools.

Some of the advantages of our research are as follows.First, we focus on analyzing the mRNA and miRNA profilesthat are associated with stress susceptibility and resilience,which can help identify relevant molecules involved in stresssusceptibility and resilience. Second, the prefrontal cortex isthought to be associated with many psychiatric neurologicaldiseases, such as drug schizophrenia, drug addiction, anxiety,and depression (Kito et al. 2014; Veeraiah et al. 2014).Analysis of the molecular expression profiles in the prefrontalcortexwill help us figure out the role of the prefrontal cortex instress susceptibility and resilience.

There is a potential limitation in our study. Subsequenttesting after stress stimulation may introduce additional mo-lecular changes. However, subsequent testing is essential tostudy the effect of stress on behavior level. On the other hand,subsequent testing was conducted in the susceptible group,resilient group, and control group. The molecular changesintroduced by subsequent testing in the three groups are thesame, theoretically.

Authors’ contributions Jiuyong Yang, Jinyan Sun, Yanjun Lu, andTingting An contributed to the experiments and data analysis. Wei Luand Jin-Hui Wang contributed to the concept, project design, and paperwriting. All authors have read and approved the final version of themanuscript.

Funding information This study was funded by Natural ScienceFoundation in Shandong China (ZR2017BC067) to WL. National KeyR&D Program of China (2016YFC1307101), and Natural ScienceFoundation in China (81671071 and 81471123) to JHW.

Compliance with ethical standards

Competing interests The authors declare that they have no competinginterest.

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