Unraveling the role of CACNA1F, RASAL1, GARIN4, and TRIM56 in common opioid side effects via transcriptomic analysis of differentiated neuron-like SH-SY5Y cells

Unraveling the role of CACNA1F, RASAL1, GARIN4, and TRIM56 in common opioid side effects via transcriptomic analysis of differentiated neuron-like SH-SY5Y cells | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Unraveling the role of CACNA1F, RASAL1, GARIN4, and TRIM56 in common opioid side effects via transcriptomic analysis of differentiated neuron-like SH-SY5Y cells Aly Abotaleb, Nguyen Phan Khoi Le, Sara Tucci, Martin J. Hug, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7327879/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Opioids remain indispensable for pain management but their use is limited by significant side effects, including respiratory depression, constipation, tolerance, addiction, and immunosuppression. Although much is known about their mechanism of action, the effects of acute opioid exposure on transcriptional responses have not yet been fully characterized. We performed a transcriptomic analysis of differentiated neuron-like SH-SY5Y cells exposed to five opioid ligands, namely, morphine, TRV130, metamorphine, β-endorphin, and naloxone. After incubation for 15 minutes, the cells were harvested and processed for RNA sequencing via the Illumina NovaSeq 6000 platform. Differential gene expression analysis was performed with DESeq2, and pathway enrichment was conducted via GO, KEGG and Reactome. Individual comparisons between each opioid-treated group and the control group revealed no statistically significant transcriptional changes. However, when all the agonist-treated samples were pooled and compared with the control samples, we identified several significantly downregulated genes (adjusted p < 0.05). Specifically, we observed alterations in the expression of the genes CACNA1F, RASAL1, GARIN4, and TRIM56, which are involved in calcium signaling, synaptic plasticity, the immune response, and reproductive function. CACNA1F downregulation may affect neuronal excitability and retinal signaling; RASAL1 suppression could impact synaptic maturation and memory; GARIN4 is associated with sperm morphology; and TRIM56 downregulation has an immunomodulatory effect, all of which aligns with known opioid-induced side effects. Our findings demonstrate that even short-term opioid exposure can initiate subtle but functionally relevant transcriptional changes. These early responses highlight the potential of transcriptomic profiling to uncover the molecular mechanisms underlying opioid pharmacodynamics and side effects. This approach offers deeper insights into opioid action and supports the development of safer analgesics with fewer systemic adverse effects. Biological sciences/Molecular biology Biological sciences/Neuroscience Opioid SH-SY5Y cells Transcriptomics Differential gene expression Drug-induced transcriptomic response Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Opioid addiction and overdose deaths remain among the most persistent public health challenges worldwide. The United States exemplifies the magnitude of this crisis: in 2019, 70,630 drug overdose deaths occurred, with 49,860 (70.6%) involving opioids 1 . The economic burden is equally staggering. Recent analyses estimate that the opioid epidemic cost the U.S. nearly $ 1.5 trillion in 2020 alone, a dramatic increase from previous years, reflecting not only healthcare expenses but also lost productivity, criminal justice costs, and broader social impacts 2 , 3 . Despite the devastating consequences of opioid misuse, their therapeutic potential as analgesics remains undeniable. The World Health Organization’s (WHO) pain management ladder recommends opioids for treating mild, moderate, and severe pain 4 . However, their clinical utility is limited by significant side effects, including constipation, respiratory depression, and addiction. Addressing these limitations requires the development of novel compounds that maintain potent analgesic effects while minimizing adverse outcomes. A deeper understanding of the molecular mechanisms underlying opioid receptor signaling could provide valuable insights into achieving this goal. In 2005, Raehal et al. hypothesized that morphine induces fewer side effects in β-arrestin-2 knockout (βarr2-KO) mice than in wild-type mice 5 . On the basis of this theory, several G protein-biased opioid agonists, such as oliceridine (TRV130), PZM21, mitragynine pseudoindoxyl (MP), and SR-17018, were designed to preferentially activate G protein signaling while reducing β-arrestin-2 recruitment. These biased agonists were initially reported to exhibit superior safety profiles compared with traditional opioids such as morphine 6 – 13 . However, subsequent studies have questioned this hypothesis. Gillis et al. suggested that the improved side effect profile of these biased agonists is not due to their selectivity for G protein signaling but rather their low intrinsic efficacy 14 . Additionally, attempts to replicate the findings of Raehal et al. have failed, further challenging the β-arrestin-2 hypothesis 15 . He et al. criticized the use of βarr2-KO mice with a mixed genetic background, as one of the strains used was naturally resistant to morphine-induced respiratory depression. Moreover, their study with a "recycling MOR" (RMOR) mutant model, which was expected to increase β-arrestin-2 recruitment, did not show increased respiratory depression at equi-analgesic doses of morphine 16 . Recent findings further complicate the debate, as studies now indicate that excessive activation of G protein signaling may itself contribute to respiratory depression and is independent of the β-arrestin2 signaling pathway 17 – 19 . These conflicting results highlight the complexity of mu-opioid receptor (MOR) signaling and the challenges in delineating the pathways responsible for its pharmacological effects. The µ-opioid receptor (µOR) belongs to the class A G protein-coupled receptor (GPCR) family and consists of seven transmembrane α-helices (TM1-TM7) connected by three extracellular and three intracellular loops. This heptahelical structure is essential for signal transduction 20 . Recently, Zhuang et al. (2024) cocrystallized the active human µOR bound to different agonists, identifying key interacting residues. These findings revealed that agonists form a critical salt bridge with the amino acid Asp147 on TM3. Additionally, distinct binding patterns emerged depending on the ligand: fentanyl and morphine interact with both TM3 and the TM6/7 interface, whereas G protein-biased agonists such as TRV130 and PZM21 primarily engage TM3. These findings establish a foundation for further investigations, particularly through molecular dynamics (MD) simulations 21 . To explore the intracellular conformational changes of the µOR, Zhao et al. employed double electron–electron resonance (DEER) and single-molecule fluorescence resonance energy transfer (smFRET) techniques. These results demonstrated that different ligands induce unique µOR conformations, altering intracellular transducer coupling. Specifically, TM4 and TM6 remain in close proximity in the inactive state, whereas low-efficacy ligands, including G protein-biased agonists, maintain TM4–TM6 distances similar to those of the inactive conformation. These findings suggest that these ligands have a limited ability to fully activate the receptor for efficient G protein engagement 22 . Although progress has been made in understanding opioid receptors and the mechanism of opioid activity, little is known about the mechanisms of their transcriptional regulation. Thus, we provide a better understanding of the molecular mechanism of action of opioids through transcriptomic analysis. Each molecule is expected to have a distinctive gene expression profile, as they have unique µOR conformations, as mentioned above. To contribute to the growing body of knowledge on opioid receptor signaling, our study performs a transcriptomic analysis of differentiated neuron-like SH-SY5Y cells following exposure to five opioids with distinct pharmacological profiles: morphine (a strong agonist and clinical gold standard), metamorphine (a recently characterized opioid receptor agonist) 23 , TRV130 (a G-protein-biased agonist), β-endorphin (an endogenous opioid peptide), and naloxone (an opioid antagonist). In this study, we aimed to clarify the acute response of differentiated neuron-like SH-SY5Y cells at the transcriptomic level after exposure to different opioid receptor agonists. Here, we provide new insights into the cellular responses triggered by different opioids, further advancing the understanding of opioid receptor signaling. Results and Discussion RNA Quality and Sequencing Metrics All SH-SY5Y samples treated with opioid receptor agonists and untreated controls yielded high-quality RNA suitable for sequencing. The RNA integrity number (RIN) ranged from 4.7 to 8.4, and all the samples passed Novogene’s internal QC thresholds. Sequencing on the Illumina NovaSeq 6000 platform produced between 48–51 million paired-end 150 bp reads per sample. After quality filtering, more than 98% of the reads were retained, with Q30 scores exceeding 92% and an average GC content between 48.0% and 50.5%. Read alignment via HISAT2 revealed that more than 95% of the clean reads mapped uniquely to the human reference genome (GRCh38), indicating high sequencing consistency and accuracy across all the samples (Supplementary.1). Differential gene expression analysis Initial pairwise comparisons between each individual opioid-treated group and the control group yielded no statistically significant differentially expressed genes (DEGs) after Benjamini‒Hochberg correction at the threshold of adjusted p < 0.05. Given the short treatment duration (15 minutes) and potential for subtle early transcriptomic changes, the dataset was reanalyzed by combining all opioid agonist-treated samples into one group and comparing them to untreated controls. This combined analysis revealed 3,337 differentially expressed genes (DEGs) based on a nominal p value threshold of < 0.05, including 1,005 upregulated and 2,333 downregulated genes (Fig. 2). To gain insight into the trend inside the cells after exposure to opioids, functional pathway analysis of these genes was performed via Gene Ontology (GO) database for biological processes, the Kyoto Encyclopedia of Genes and Genomes (KEGG) for signaling and metabolic pathways, and the Reactome pathway database to identify significantly enriched molecular pathways. This revealed no significantly enriched pathways in KEGG or Reactome, likely due to the subtle and early nature of transcriptional modulation. Gene Ontology (GO) enrichment analysis revealed significant enrichment in cellular components such as the apical and basal plasma membranes, as well as biological processes such as the regulation of muscle contraction. These findings highlight biologically meaningful transcriptional shifts following opioid exposure, even when overall fold changes or adjusted p values were modest, suggesting early cellular reorganization and cytoskeletal responses in differentiated neuron-like SH-SY5Y cells. (Fig. 3 ). When an adjusted p value threshold of < 0.05 was applied following Benjamini–Hochberg correction, 11 downregulated genes remained statistically significant, with no corresponding upregulation observed (Figs. 4 – 5 )(Table S1 ). The functional annotation of these genes revealed mechanistic links to opioid pharmacodynamics, indicating that acute opioid exposure elicits early transcriptional responses aligned with known physiological effects. Among the significantly downregulated genes identified, CACNA1F, which encodes the Cav1.4 α1F subunit of L-type voltage-gated calcium channels (VGCCs), was notably suppressed. Cav1.4 channels are critical regulators of calcium influx in neurons and are particularly involved in neurotransmitter release and synaptic plasticity 24 , 25 . While the acute effects of opioids on calcium channels are typically mediated through Gβγ subunits that inhibit VGCCs at the membrane level 26 , the observed transcriptional downregulation of CACNA1F suggests a longer-term adaptive response to opioid exposure. This gene-level suppression may represent a mechanism through which opioids reduce neuronal excitability and calcium signaling beyond immediate ion channel inhibition. Such regulation could contribute to opioid-induced neuronal adaptations, including tolerance, reduced synaptic efficiency, or altered pain processing. However, it remains to be determined whether CACNA1F downregulation is a direct effect of opioid receptor signaling pathways (e.g., cAMP/PKA/CREB) or a secondary consequence of altered intracellular states. Future studies examining functional Cav1.4 activity and its interaction with other VGCC subtypes (e.g., N-type or T-type) could further clarify its role in opioid pharmacodynamics. In addition to its role in neurons, CACNA1F is essential for proper retinal function, particularly in photoreceptor cells, where it supports sustained neurotransmitter release in response to visual stimuli 27 . Mutations in CACNA1F are associated with incomplete X-linked congenital stationary night blindness (CSNB2), a disorder characterized by impaired night vision and other visual anomalies 28 . While opioid receptors have been detected in retinal tissues and some clinical studies suggest a correlation between chronic opioid use and retinal complications such as retinal vein occlusion, the underlying mechanisms remain unclear 29 . Although our finding of CACNA1F downregulation in opioid-treated differentiated neuron-like SH-SY5Y cells does not directly model retinal tissue, this finding suggests that opioid-induced modulation of calcium channel expression could have broader neurophysiological implications, potentially including visual pathways. Further investigations in retinal-specific models are needed to test this hypothesis. Another significantly downregulated gene identified in our dataset was RASAL1 (RAS protein activator-like 1), a calcium-sensitive GTPase-activating protein (GAP) that negatively regulates RAS signaling by accelerating the conversion of RAS-GTP to its inactive GDP-bound form. This modulation of RAS activity plays a critical role in controlling cellular processes such as proliferation, differentiation, and synaptic plasticity 30 . In the nervous system, RASAL1 is essential for calcium-dependent neuronal maturation. It contributes to the fine-tuning of neurite outgrowth and synapse formation. Knockdown studies in hippocampal neurons have shown that reduced RASAL1 expression leads to a 50–100% increase in total neurite length and up to a 400% increase in secondary dendritic branching, driven by prolonged RAS activity and subsequent microtubule destabilization and growth cone extension 31 . RASAL1 is also known to stabilize NMDA receptor-mediated currents and promote CaMKII phosphorylation, both of which are critical for synaptic maturation and plasticity. The downregulation of RASAL1 observed in our study may therefore result in aberrant neuronal connectivity, excessive or disorganized neurite growth, and disrupted calcium-dependent synaptic development. These molecular disturbances are consistent with behavioral outcomes such as short-term memory impairment, which has been reported following opioid administration 32 . While the connection between opioid-induced RASAL1 downregulation and memory dysfunction remains correlative in our dataset, this finding opens a compelling avenue for further investigation into the neurocognitive side effects of opioid exposure. One of the genes of interest is also GARIN4 (Golgi-Associated RAB2 Interactor Family Member 4), also known as FAM71A. GARIN4 encodes a Golgi-localized effector protein that interacts with the small GTPase RAB2B, playing a critical role in maintaining Golgi structure and vesicle trafficking integrity 33 . Although its expression is highly enriched in the testis, the role of GARIN4 in broader cellular morphology is supported by studies in knockout mouse models, where loss of GARIN4, along with related family members, led to aberrant sperm head morphogenesis and reduced zona pellucida (ZP) penetration capacity during in vitro fertilization 34 . Importantly, opioid receptors are known to be expressed in testicular tissue and spermatozoa, and opioid use has been associated with reduced sperm quality, altered morphology, and decreased motility 35 , 36 . The observed downregulation of GARIN4 in our opioid-treated samples suggests that opioids may impair male fertility at the transcriptional level by disrupting genes critical to sperm head formation and function. While GARIN4 knockout does not result in complete infertility in mice, the reduction in ZP penetration highlights a subtle but functionally relevant reproductive phenotype, which could be exacerbated by chronic opioid use. These findings suggest a novel mechanistic link between opioid exposure and compromised male fertility, warranting further investigation into GARIN4 as a potential molecular mediator of opioid-induced reproductive dysfunction. Genes related to the immune system also appear to be affected by opioids, such as TRIM56, a key regulator of innate immune signaling via the TLR3/TRIF pathway, which was significantly downregulated. TRIM56 is an E3 ubiquitin ligase known for its roles in cellular immune regulation and antiviral defense, primarily through the promotion of TLR3/TRIF-mediated signaling pathways. In multiple myeloma cells, which express functional opioid receptors, Chen et al. demonstrated that TRIM56 is downregulated and that its knockout suppressed TLR3/TRIF signaling, a pathway with both antiviral and tumor-suppressive properties. These findings suggest that opioid-induced downregulation of TRIM56 may contribute to tumor progression and increase susceptibility to viral infections in multiple myeloma patients, a population that is already heavily reliant on opioid analgesia 37 . The immunosuppressive activity of opioids has been reported in several studies and reviews. Kosciuczuk et al. reviewed how opioids suppress both innate and adaptive immune responses by impairing macrophage, T cell, and natural killer (NK) cell functions and by activating the hypothalamic‒pituitary‒adrenal (HPA) axis. Furthermore, they reported that opioid-induced immunosuppression may contribute to cancer progression by enhancing tumor cell proliferation, promoting angiogenesis, and disrupting microRNA regulatory networks 38 . These findings suggest that opioid-induced downregulation of TRIM56 may contribute to tumor progression and increased susceptibility to viral infections in multiple myeloma patients, a population that is already heavily reliant on opioid analgesia. Although the immune response and tumor progression are complex, multifactorial processes, the downregulation of TRIM56 may partially explain the immunosuppressive effects of opioids. Interestingly, the coagulation gene F2 (prothrombin) was also suppressed. Prothrombin is cleaved to generate thrombin, a serine protease that not only plays a central role in fibrin clot formation but also exerts significant effects on cellular functions such as proliferation, survival, and inflammation through the activation of protease-activated receptors (PARs) 39 . In the central nervous system, thrombin signaling influences neuronal survival, neuroinflammation, and synaptic plasticity. The downregulation of F2 following opioid treatment may therefore reduce thrombin-mediated inflammatory responses, potentially contributing to the known immunosuppressive and anti-inflammatory effects of opioids 38 – 40 . However, because thrombin signaling is also involved in maintaining neuronal integrity under stress conditions, diminished F2 expression might predispose neurons to vulnerability to prolonged opioid exposure. These findings suggest that opioids may exert complex regulatory effects on neuronal immune signaling networks at the transcriptional level, which could have long-term implications for neuronal health and opioid-induced neurotoxicity. Another important finding was the downregulation of NIBAN3 (FAM129C), a gene implicated in the stress response and protection against apoptosis 41 . NIBAN3 is known to protect cells against stress-induced apoptosis by modulating survival pathways and is highly expressed in immune tissues, including lymphoid organs and hematopoietic cells 42 . Downregulation of NIBAN3 may sensitize neurons and immune cells to apoptosis under stressful conditions such as oxidative stress, hypoxia, or inflammation, all of which are relevant to opioid pharmacodynamics 43 . These findings suggest that early transcriptional suppression of stress-protective genes such as NIBAN3 could underlie part of the neurotoxic and immunosuppressive profile of opioids, which can be linked to the known neurotoxic mechanism of opioids 44 , 45 . In addition to protein-coding genes, several long noncoding RNAs (lncRNAs), such as ENSG00000235862, ENSG00000280800, and ENSG00000279175, were significantly downregulated. These lncRNAs reside in proximity to genes such as the GARIN4 and ATF3 isoforms, indicating possible regulatory interactions. LncRNAs are emerging as critical modulators of gene expression in neurodevelopment, synaptic plasticity, and disease, and their downregulation may reflect early shifts in the epigenetic landscape following opioid exposure 46 – 48 . Finally, ADAMTS7P1, a pseudogene related to the ADAMTS metalloproteinase family, was also significantly downregulated. Although pseudogenes are traditionally considered nonfunctional, emerging evidence suggests that they can act as regulators of gene networks through various mechanisms, including microRNA sequestration or competing endogenous RNA activity. The biological relevance of ADAMTS7P1 suppression remains unclear but warrants further investigation. In summary, our transcriptomic analysis revealed that acute opioid exposure induces early, subtle yet biologically meaningful transcriptional changes in genes associated with calcium signaling, synaptic plasticity, immune modulation, and reproductive function. These findings provide a systems-level view of opioid action and highlight new molecular candidates for mitigating side effects and improving analgesic therapies. While the neuroblastoma-derived SH-SY5Y cell line offers a well-established and tractable model for investigating neuronal signaling and opioid pharmacology, it represents a simplified in vitro system lacking the full cellular complexity of primary neurons and intact tissue microenvironments. Upon retinoic acid-induced differentiation, SH-SY5Y cells acquire several neuron-like features, including axonal projections, the synaptic machinery, and the expression of key neurotransmitter receptors, making them suitable for studying early transcriptional responses to opioid receptor activation. However, they do not recapitulate multicellular interactions, regional heterogeneity, or long-term neuroadaptive processes observed in vivo. Accordingly, the transcriptomic changes identified here should be interpreted as acute, cell-intrinsic effects of opioid exposure that serve as a mechanistic foundation for hypothesis generation. Future studies in primary neuronal cultures, organoid systems, or in vivo models will be essential to validate the broader physiological relevance of these findings. Conclusion Our study suggests that acute exposure of differentiated neuron-like SH-SY5Y cells to opioid agonists results in measurable changes in gene expression, even within a short treatment window. Although the transcriptional alterations were modest, several downregulated genes appear to be linked to pathways associated with known opioid side effects. These findings highlight the value of transcriptomic analysis as a tool for revealing early molecular responses to opioid stimulation. By providing deeper insight into the gene-level effects of opioids, transcriptomics can contribute to the rational design of new opioid compounds with improved safety profiles and reduced adverse effects. Future studies, including time-course experiments and the use of more complex models, such as organoids, to further elucidate the mechanisms of opioid action and addiction are to be performed. Materials and methods Cell Culture SH-SY5Y human neuroblastoma cells (Sigma-Aldrich, Ochsenfurt, Germany) were cultured in Dulbecco’s modified Eagle’s medium (DMEM; Thermo Fisher) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin‒streptomycin (Life Technologies GmbH). The cells were maintained at 37°C in a humidified 5% CO₂ incubator and routinely passaged at 90% confluence using 0.25% trypsin-EDTA (Life Technologies GmbH). All experimental procedures were carried out under sterile conditions in a laminar flow hood, and comprehensive standard operating procedures (SOPs) were used. Differentiation of SH-SY5Y cells To induce neuron-like phenotypes, the undifferentiated cells were cultivated for 24 hours and then differentiated by 10 µM all-trans-retinoic acid (ATRA; Sigma‒Aldrich) in the DMEM medium supplemented with 2% FBS and 1% penicillin-streptomicin.The cells were differentiated 7 days before treatment and the differentiation medium was replaced every 48–72 hours. This protocol has previously been reported to induce neuron-like characteristics in SH-SY5Y cells 49 – 52 . Opioid Treatment The differentiated neuron-like SH-SY5Y cells were treated for 15 minutes with one of five opioid compounds: morphine hydrochloride trihydrate (Th. Geyer GmbH & Co. KG), naloxone, TRV-130, β-endorphin (MolPort), or synthetically produced metamorphine. Stock solutions of each compound were prepared in sterile ultrapure water (Aqua B. Braun Ecotainer, B. Braun Melsungen AG) and diluted to their respective IC₅₀-based working concentrations in serum-free DMEM (morphine: 193 nM; naloxone: 200 nM; β-endorphin: 200 nM; metamorphine: 169 nM; oliceridine: 200 nM). For each treatment, 11 µL of the respective stock solution was added to 19.8 mL of serum-free DMEM in a T75 flask. Control cells received 11 µL of Aqua B. Braun under identical conditions. To ensure reproducibility, all treatments were performed in three independent biological experiments on separate days. RNA Isolation and Transcriptomic Analysis After treatment, the cells were immediately washed with cold D-PBS to remove residual medium and detached by adding 2ml 2.5% trypsin and incubated for 4 minutes. The enzymatic reaction was stopped with DMEM, and the cells were collected by centrifugation at 300–400 × g for 5–10 minutes at 4°C. The cell pellet was washed twice with cold D-PBS, snap-frozen on dry ice, and stored at − 80°C until shipment to Novogene (Cambridge, United Kingdom) for RNA extraction. RNA quality control and library preparation RNA integrity and purity were assessed by Novogene Co., Ltd. (Cambridge, United Kingdom) upon sample receipt. Total RNA was quantified via NanoDrop spectrophotometry, and integrity was evaluated via an Agilent 2100 Bioanalyzer. All eight samples passed Novogene’s internal quality criteria for library preparation and sequencing. The RNA integrity number (RIN) ranged from 4.7 to 8.4, with all the samples classified as “Pass.” The RNA concentration ranged from 54 to 442 ng/µL, and the total RNA yield was between 1.35 and 17.24 µg per sample, which was sufficient for standard mRNA-seq library construction. These results confirmed that the extracted RNA was of adequate quality for high-throughput sequencing. cDNA libraries were prepared using the Novogene NGS RNA Library Prep Set (PT042), generating 250–300 bp insert size libraries without strand-specificity. Sequencing and Quality Control Sequencing was performed on the Illumina NovaSeq 6000 platform, generating 150 bp paired-end reads. Each sample produced an average of 50 million raw reads. The adapter sequences, low-quality reads, and reads with > 10% unknown bases were removed via Novogene’s internal quality filtering pipeline. Transcriptomic bioinformatics pipeline Transcriptomic data analysis was conducted via a standardized bioinformatics workflow. Quality control of the raw sequencing reads was performed with FastQC (v0.12.1), and summary statistics were compiled via MultiQC. Reads were aligned to the human reference genome (GRCh38) via HISAT2 (v2.2.1), and gene-level quantification was carried out with featureCounts (v2.0.5), applying strand-specific settings. Differential gene expression analysis was performed in R via DESeq2 (v1.46.0) with default median-of-ratios normalization. Genes with an adjusted p value < 0.05 (Benjamini–Hochberg correction) were considered statistically significant. To explore biological significance, pathway enrichment analysis was performed via the clusterProfiler package, which incorporates the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome databases. Pathways with a false discovery rate (FDR) < 0.05 were considered enriched. Declarations Funding This work was supported by institutional resources from the Institute of Pharmaceutical Sciences, Faculty of Chemistry and Pharmacy, University of Freiburg. No specific external grant funded this research. Data Availability The datasets generated and analysed during the current study are available in the NCBI Gene Expression Omnibus (GEO) repository, under accession number GSE306403 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE306403). AUTHOR INFORMATION Corresponding Authors Aly Abotaleb, Pharmacy, Medical Center – University of Freiburg, Freiburg, Germany. E-mail: [email protected] Stefan Günther, Institute of Pharmaceutical Sciences, Faculty of Chemistry and Pharmacy, University of Freiburg, Freiburg, Germany. E-mail: [email protected] Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. References Mattson, C. L. et al. Trends and Geographic Patterns in Drug and Synthetic Opioid Overdose Deaths — United States, 2013–2019. Morb. Mortal. Wkly. Rep. 70 , 202–207 (2021). JEC Analysis Finds Opioid Epidemic Cost U.S. Nearly $1.5 Trillion in 2020. 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The SH-SY5Y cell line in Parkinson’s disease research: a systematic review. Mol. Neurodegener. 12 , 10 (2017). Lopes, F. M. et al. Comparison between proliferative and neuron-like SH-SY5Y cells as an in vitro model for Parkinson disease studies. Brain Res. 1337 , 85–94 (2010). Shipley, M. M., Mangold, C. A. & Szpara, M. L. Differentiation of the SH-SY5Y Human Neuroblastoma Cell Line. J. Vis. Exp. JoVE 53193 (2016) doi:10.3791/53193. Additional Declarations No competing interests reported. Supplementary Files SupplementaryDataUnravelingtheroleofCACNA1FRASAL1GARIN4andTRIM56incommonopioidsideeffectsviatranscriptomicanalysisofdifferentiatedneuronlikeSHSY5Ycells.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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06:23:59","extension":"html","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":114247,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7327879/v1/88f94e2ba772971b6de18cc6.html"},{"id":91815822,"identity":"8f24ca67-694e-4df1-a3f1-b001647cb5be","added_by":"auto","created_at":"2025-09-22 06:32:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":152422,"visible":true,"origin":"","legend":"\u003cp\u003eVolcano plot visualizing differential gene expression between opioid agonist-treated and control samples. Genes are plotted on the basis of log₂ fold change and −log₁₀ p value. Red dots represent significantly differentially expressed genes (p \u0026lt; 0.05 and |log₂FC| \u0026gt; 1), blue dots indicate genes with substantial but not statistically significant fold changes, and green dots represent genes with significant p values but lower fold changes. The gray dots represent nonsignificant genes. A total of 58,735 genes were analyzed.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7327879/v1/9d71405b2ddc304ecde1fd4a.png"},{"id":91815302,"identity":"1275513b-7ff0-4089-9224-1570bd4e2d50","added_by":"auto","created_at":"2025-09-22 06:24:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":32738,"visible":true,"origin":"","legend":"\u003cp\u003eGene Ontology (GO) overrepresentation analysis (ORA) results for significantly downregulated genes. (A) The biological process category revealed enrichment in \"regulation of muscle contraction\" (p \u0026lt; 0.05). (B) Cellular component analysis highlights significant enrichment in plasma membrane-related and ribosomal subunit components, including the apical and basolateral plasma membrane, large ribosomal subunit, and lipoprotein particles. The dot size indicates the number of genes involved, while the color reflects the adjusted p value.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7327879/v1/221f15d99e5040ccd57c9f79.png"},{"id":91815821,"identity":"6827cc22-7fd6-4283-8c79-50baf18d1f96","added_by":"auto","created_at":"2025-09-22 06:32:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":95610,"visible":true,"origin":"","legend":"\u003cp\u003eVolcano plot displaying all 58,735 genes analyzed after multiple testing correction. Genes with both an adjusted p value \u0026lt; 0.05 and a |log₂-fold change| \u0026gt; 1 are highlighted in red, representing significantly downregulated transcripts in opioid-treated samples compared with controls. The green and gray points indicate genes with high fold changes or nonsignificant differences, respectively.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7327879/v1/3591bfc9c23d6181f863ec40.png"},{"id":91815282,"identity":"ea1c693c-2fe6-4965-85c6-9fba8ee1cf85","added_by":"auto","created_at":"2025-09-22 06:24:00","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":51965,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplot showing the variance-stabilized expression (VST) levels of the top seven significantly downregulated genes (adjusted p value \u0026lt; 0.05) in opioid-treated samples (M) compared with controls (C). Each box represents the expression distribution across samples for individual genes, highlighting consistent downregulation in the treatment group.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7327879/v1/e33bf4292eccfd393bdfd7e1.png"},{"id":91815288,"identity":"4c6b4db6-70df-4656-9c60-28be81f3dfbd","added_by":"auto","created_at":"2025-09-22 06:24:00","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":94095,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic overview of the experimental workflow for transcriptomic analysis, illustrating the sequence from cell treatment and RNA extraction to sequencing, data processing, and downstream bioinformatics analysis.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7327879/v1/ccc38563ed4c5a0f86c9737e.png"},{"id":92927047,"identity":"00420ed8-5884-439a-976a-d5155beaf516","added_by":"auto","created_at":"2025-10-07 08:17:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":855116,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7327879/v1/85c8b967-5595-4b1b-aa6a-c0acc28d8abf.pdf"},{"id":91815286,"identity":"a095ec41-45a5-400c-8763-315d7f1e0175","added_by":"auto","created_at":"2025-09-22 06:24:00","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":160015,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryDataUnravelingtheroleofCACNA1FRASAL1GARIN4andTRIM56incommonopioidsideeffectsviatranscriptomicanalysisofdifferentiatedneuronlikeSHSY5Ycells.docx","url":"https://assets-eu.researchsquare.com/files/rs-7327879/v1/e130fd7fbac0c2239a598d01.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unraveling the role of CACNA1F, RASAL1, GARIN4, and TRIM56 in common opioid side effects via transcriptomic analysis of differentiated neuron-like SH-SY5Y cells","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOpioid addiction and overdose deaths remain among the most persistent public health challenges worldwide. The United States exemplifies the magnitude of this crisis: in 2019, 70,630 drug overdose deaths occurred, with 49,860 (70.6%) involving opioids \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The economic burden is equally staggering. Recent analyses estimate that the opioid epidemic cost the U.S. nearly \u003cspan\u003e$\u003c/span\u003e1.5 trillion in 2020 alone, a dramatic increase from previous years, reflecting not only healthcare expenses but also lost productivity, criminal justice costs, and broader social impacts \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e .\u003c/p\u003e\u003cp\u003eDespite the devastating consequences of opioid misuse, their therapeutic potential as analgesics remains undeniable. The World Health Organization\u0026rsquo;s (WHO) pain management ladder recommends opioids for treating mild, moderate, and severe pain \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. However, their clinical utility is limited by significant side effects, including constipation, respiratory depression, and addiction. Addressing these limitations requires the development of novel compounds that maintain potent analgesic effects while minimizing adverse outcomes. A deeper understanding of the molecular mechanisms underlying opioid receptor signaling could provide valuable insights into achieving this goal.\u003c/p\u003e\u003cp\u003eIn 2005, Raehal et al. hypothesized that morphine induces fewer side effects in β-arrestin-2 knockout (βarr2-KO) mice than in wild-type mice \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. On the basis of this theory, several G protein-biased opioid agonists, such as oliceridine (TRV130), PZM21, mitragynine pseudoindoxyl (MP), and SR-17018, were designed to preferentially activate G protein signaling while reducing β-arrestin-2 recruitment. These biased agonists were initially reported to exhibit superior safety profiles compared with traditional opioids such as morphine \u003csup\u003e\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10 CR11 CR12\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. However, subsequent studies have questioned this hypothesis. Gillis et al. suggested that the improved side effect profile of these biased agonists is not due to their selectivity for G protein signaling but rather their low intrinsic efficacy \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Additionally, attempts to replicate the findings of Raehal et al. have failed, further challenging the β-arrestin-2 hypothesis \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. He et al. criticized the use of βarr2-KO mice with a mixed genetic background, as one of the strains used was naturally resistant to morphine-induced respiratory depression. Moreover, their study with a \"recycling MOR\" (RMOR) mutant model, which was expected to increase β-arrestin-2 recruitment, did not show increased respiratory depression at equi-analgesic doses of morphine \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eRecent findings further complicate the debate, as studies now indicate that excessive activation of G protein signaling may itself contribute to respiratory depression and is independent of the β-arrestin2 signaling pathway \u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. These conflicting results highlight the complexity of mu-opioid receptor (MOR) signaling and the challenges in delineating the pathways responsible for its pharmacological effects.\u003c/p\u003e\u003cp\u003eThe \u0026micro;-opioid receptor (\u0026micro;OR) belongs to the class A G protein-coupled receptor (GPCR) family and consists of seven transmembrane α-helices (TM1-TM7) connected by three extracellular and three intracellular loops. This heptahelical structure is essential for signal transduction \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eRecently, Zhuang et al. (2024) cocrystallized the active human \u0026micro;OR bound to different agonists, identifying key interacting residues. These findings revealed that agonists form a critical salt bridge with the amino acid Asp147 on TM3. Additionally, distinct binding patterns emerged depending on the ligand: fentanyl and morphine interact with both TM3 and the TM6/7 interface, whereas G protein-biased agonists such as TRV130 and PZM21 primarily engage TM3. These findings establish a foundation for further investigations, particularly through molecular dynamics (MD) simulations \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTo explore the intracellular conformational changes of the \u0026micro;OR, Zhao et al. employed double electron\u0026ndash;electron resonance (DEER) and single-molecule fluorescence resonance energy transfer (smFRET) techniques. These results demonstrated that different ligands induce unique \u0026micro;OR conformations, altering intracellular transducer coupling. Specifically, TM4 and TM6 remain in close proximity in the inactive state, whereas low-efficacy ligands, including G protein-biased agonists, maintain TM4\u0026ndash;TM6 distances similar to those of the inactive conformation. These findings suggest that these ligands have a limited ability to fully activate the receptor for efficient G protein engagement \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAlthough progress has been made in understanding opioid receptors and the mechanism of opioid activity, little is known about the mechanisms of their transcriptional regulation. Thus, we provide a better understanding of the molecular mechanism of action of opioids through transcriptomic analysis. Each molecule is expected to have a distinctive gene expression profile, as they have unique \u0026micro;OR conformations, as mentioned above. To contribute to the growing body of knowledge on opioid receptor signaling, our study performs a transcriptomic analysis of differentiated neuron-like SH-SY5Y cells following exposure to five opioids with distinct pharmacological profiles: morphine (a strong agonist and clinical gold standard), metamorphine (a recently characterized opioid receptor agonist) \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, TRV130 (a G-protein-biased agonist), β-endorphin (an endogenous opioid peptide), and naloxone (an opioid antagonist). In this study, we aimed to clarify the acute response of differentiated neuron-like SH-SY5Y cells at the transcriptomic level after exposure to different opioid receptor agonists. Here, we provide new insights into the cellular responses triggered by different opioids, further advancing the understanding of opioid receptor signaling.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003eRNA Quality and Sequencing Metrics\u003c/p\u003e\n\u003cp\u003eAll SH-SY5Y samples treated with opioid receptor agonists and untreated controls yielded high-quality RNA suitable for sequencing. The RNA integrity number (RIN) ranged from 4.7 to 8.4, and all the samples passed Novogene\u0026rsquo;s internal QC thresholds. Sequencing on the Illumina NovaSeq 6000 platform produced between 48\u0026ndash;51\u0026nbsp;million paired-end 150 bp reads per sample. After quality filtering, more than 98% of the reads were retained, with Q30 scores exceeding 92% and an average GC content between 48.0% and 50.5%. Read alignment via HISAT2 revealed that more than 95% of the clean reads mapped uniquely to the human reference genome (GRCh38), indicating high sequencing consistency and accuracy across all the samples (Supplementary.1).\u003c/p\u003e\n\u003cp\u003eDifferential gene expression analysis\u003c/p\u003e\n\u003cp\u003eInitial pairwise comparisons between each individual opioid-treated group and the control group yielded no statistically significant differentially expressed genes (DEGs) after Benjamini‒Hochberg correction at the threshold of adjusted p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Given the short treatment duration (15 minutes) and potential for subtle early transcriptomic changes, the dataset was reanalyzed by combining all opioid agonist-treated samples into one group and comparing them to untreated controls.\u003c/p\u003e\n\u003cp\u003eThis combined analysis revealed 3,337 differentially expressed genes (DEGs) based on a nominal p value threshold of \u0026lt;\u0026thinsp;0.05, including 1,005 upregulated and 2,333 downregulated genes (Fig. 2).\u003c/p\u003e\n\u003cp\u003eTo gain insight into the trend inside the cells after exposure to opioids, functional pathway analysis of these genes was performed via Gene Ontology (GO) database for biological processes, the Kyoto Encyclopedia of Genes and Genomes (KEGG) for signaling and metabolic pathways, and the Reactome pathway database to identify significantly enriched molecular pathways. This revealed no significantly enriched pathways in KEGG or Reactome, likely due to the subtle and early nature of transcriptional modulation. Gene Ontology (GO) enrichment analysis revealed significant enrichment in cellular components such as the apical and basal plasma membranes, as well as biological processes such as the regulation of muscle contraction. These findings highlight biologically meaningful transcriptional shifts following opioid exposure, even when overall fold changes or adjusted p values were modest, suggesting early cellular reorganization and cytoskeletal responses in differentiated neuron-like SH-SY5Y cells. (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003cp\u003eWhen an adjusted p value threshold of \u0026lt;\u0026thinsp;0.05 was applied following Benjamini\u0026ndash;Hochberg correction, 11 downregulated genes remained statistically significant, with no corresponding upregulation observed (Figs. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e)(Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). The functional annotation of these genes revealed mechanistic links to opioid pharmacodynamics, indicating that acute opioid exposure elicits early transcriptional responses aligned with known physiological effects.\u003c/p\u003e\n \u003cp\u003eAmong the significantly downregulated genes identified, CACNA1F, which encodes the Cav1.4 \u0026alpha;1F subunit of L-type voltage-gated calcium channels (VGCCs), was notably suppressed. Cav1.4 channels are critical regulators of calcium influx in neurons and are particularly involved in neurotransmitter release and synaptic plasticity \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. While the acute effects of opioids on calcium channels are typically mediated through G\u0026beta;\u0026gamma; subunits that inhibit VGCCs at the membrane level \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, the observed transcriptional downregulation of CACNA1F suggests a longer-term adaptive response to opioid exposure. This gene-level suppression may represent a mechanism through which opioids reduce neuronal excitability and calcium signaling beyond immediate ion channel inhibition. Such regulation could contribute to opioid-induced neuronal adaptations, including tolerance, reduced synaptic efficiency, or altered pain processing. However, it remains to be determined whether CACNA1F downregulation is a direct effect of opioid receptor signaling pathways (e.g., cAMP/PKA/CREB) or a secondary consequence of altered intracellular states. Future studies examining functional Cav1.4 activity and its interaction with other VGCC subtypes (e.g., N-type or T-type) could further clarify its role in opioid pharmacodynamics.\u003c/p\u003e\n \u003cp\u003eIn addition to its role in neurons, CACNA1F is essential for proper retinal function, particularly in photoreceptor cells, where it supports sustained neurotransmitter release in response to visual stimuli \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Mutations in CACNA1F are associated with incomplete X-linked congenital stationary night blindness (CSNB2), a disorder characterized by impaired night vision and other visual anomalies \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. While opioid receptors have been detected in retinal tissues and some clinical studies suggest a correlation between chronic opioid use and retinal complications such as retinal vein occlusion, the underlying mechanisms remain unclear \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Although our finding of CACNA1F downregulation in opioid-treated differentiated neuron-like SH-SY5Y cells does not directly model retinal tissue, this finding suggests that opioid-induced modulation of calcium channel expression could have broader neurophysiological implications, potentially including visual pathways. Further investigations in retinal-specific models are needed to test this hypothesis.\u003c/p\u003e\n \u003cp\u003eAnother significantly downregulated gene identified in our dataset was RASAL1 (RAS protein activator-like 1), a calcium-sensitive GTPase-activating protein (GAP) that negatively regulates RAS signaling by accelerating the conversion of RAS-GTP to its inactive GDP-bound form. This modulation of RAS activity plays a critical role in controlling cellular processes such as proliferation, differentiation, and synaptic\u003c/p\u003e\n \u003cp\u003eplasticity \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. In the nervous system, RASAL1 is essential for calcium-dependent neuronal maturation. It contributes to the fine-tuning of neurite outgrowth and synapse formation. Knockdown studies in hippocampal neurons have shown that reduced RASAL1 expression leads to a 50\u0026ndash;100% increase in total neurite length and up to a 400% increase in secondary dendritic branching, driven by prolonged RAS activity and subsequent microtubule destabilization and growth cone extension \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. RASAL1 is also known to stabilize NMDA receptor-mediated currents and promote CaMKII phosphorylation, both of which are critical for synaptic maturation and plasticity. The downregulation of RASAL1 observed in our study may therefore result in aberrant neuronal connectivity, excessive or disorganized neurite growth, and disrupted calcium-dependent synaptic development. These molecular disturbances are consistent with behavioral outcomes such as short-term memory impairment, which has been reported following opioid administration \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. While the connection between opioid-induced RASAL1 downregulation and memory dysfunction remains correlative in our dataset, this finding opens a compelling avenue for further investigation into the neurocognitive side effects of opioid exposure.\u003c/p\u003e\n \u003cp\u003eOne of the genes of interest is also GARIN4 (Golgi-Associated RAB2 Interactor Family Member 4), also known as FAM71A. GARIN4 encodes a Golgi-localized effector protein that interacts with the small GTPase RAB2B, playing a critical role in maintaining Golgi structure and vesicle trafficking integrity \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Although its expression is highly enriched in the testis, the role of GARIN4 in broader cellular morphology is supported by studies in knockout mouse models, where loss of GARIN4, along with related family members, led to aberrant sperm head morphogenesis and reduced zona pellucida (ZP) penetration capacity during in vitro fertilization\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Importantly, opioid receptors are known to be expressed in testicular tissue and spermatozoa, and opioid use has been associated with reduced sperm quality, altered morphology, and decreased motility \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. The observed downregulation of GARIN4 in our opioid-treated samples suggests that opioids may impair male fertility at the transcriptional level by disrupting genes critical to sperm head formation and function. While GARIN4 knockout does not result in complete infertility in mice, the reduction in ZP penetration highlights a subtle but functionally relevant reproductive phenotype, which could be exacerbated by chronic opioid use. These findings suggest a novel mechanistic link between opioid exposure and compromised male fertility, warranting further investigation into GARIN4 as a potential molecular mediator of opioid-induced reproductive dysfunction.\u003c/p\u003e\n \u003cp\u003eGenes related to the immune system also appear to be affected by opioids, such as TRIM56, a key regulator of innate immune signaling via the TLR3/TRIF pathway, which was significantly downregulated. TRIM56 is an E3 ubiquitin ligase known for its roles in cellular immune regulation and antiviral defense, primarily through the promotion of TLR3/TRIF-mediated signaling pathways. In multiple myeloma cells, which express functional opioid receptors, Chen et al. demonstrated that TRIM56 is downregulated and that its knockout suppressed TLR3/TRIF signaling, a pathway with both antiviral and tumor-suppressive properties. These findings suggest that opioid-induced downregulation of TRIM56 may contribute to tumor progression and increase susceptibility to viral infections in multiple myeloma patients, a population that is already heavily reliant on opioid analgesia \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The immunosuppressive activity of opioids has been reported in several studies and reviews. Kosciuczuk et al. reviewed how opioids suppress both innate and adaptive immune responses by impairing macrophage, T cell, and natural killer (NK) cell functions and by activating the hypothalamic‒pituitary‒adrenal (HPA) axis. Furthermore, they reported that opioid-induced immunosuppression may contribute to cancer progression by enhancing tumor cell proliferation, promoting angiogenesis, and disrupting microRNA regulatory networks \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. These findings suggest that opioid-induced downregulation of TRIM56 may contribute to tumor progression and increased susceptibility to viral infections in multiple myeloma patients, a population that is already heavily reliant on opioid analgesia. Although the immune response and tumor progression are complex, multifactorial processes, the downregulation of TRIM56 may partially explain the immunosuppressive effects of opioids.\u003c/p\u003e\n \u003cp\u003eInterestingly, the coagulation gene F2 (prothrombin) was also suppressed. Prothrombin is cleaved to generate thrombin, a serine protease that not only plays a central role in fibrin clot formation but also exerts significant effects on cellular functions such as proliferation, survival, and inflammation through the activation of protease-activated receptors (PARs) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. In the central nervous system, thrombin signaling influences neuronal survival, neuroinflammation, and synaptic plasticity. The downregulation of F2 following opioid treatment may therefore reduce thrombin-mediated inflammatory responses, potentially contributing to the known immunosuppressive and anti-inflammatory effects of opioids \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. However, because thrombin signaling is also involved in maintaining neuronal integrity under stress conditions, diminished F2 expression might predispose neurons to vulnerability to prolonged opioid exposure. These findings suggest that opioids may exert complex regulatory effects on neuronal immune signaling networks at the transcriptional level, which could have long-term implications for neuronal health and opioid-induced neurotoxicity.\u003c/p\u003e\n \u003cp\u003eAnother important finding was the downregulation of NIBAN3 (FAM129C), a gene implicated in the stress response and protection against apoptosis \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. NIBAN3 is known to protect cells against stress-induced apoptosis by modulating survival pathways and is highly expressed in immune tissues, including lymphoid organs and hematopoietic\u003c/p\u003e\n \u003cp\u003ecells \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Downregulation of NIBAN3 may sensitize neurons and immune cells to apoptosis under stressful conditions such as oxidative stress, hypoxia, or inflammation, all of which are relevant to opioid pharmacodynamics \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. These findings suggest that early transcriptional suppression of stress-protective genes such as NIBAN3 could underlie part of the neurotoxic and immunosuppressive profile of opioids, which can be linked to the known neurotoxic mechanism of opioids \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eIn addition to protein-coding genes, several long noncoding RNAs (lncRNAs), such as ENSG00000235862, ENSG00000280800, and ENSG00000279175, were significantly downregulated. These lncRNAs reside in proximity to genes such as the GARIN4 and ATF3 isoforms, indicating possible regulatory interactions. LncRNAs are emerging as critical modulators of gene expression in neurodevelopment, synaptic plasticity, and disease, and their downregulation may reflect early shifts in the epigenetic landscape following opioid exposure \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eFinally, ADAMTS7P1, a pseudogene related to the ADAMTS metalloproteinase family, was also significantly downregulated. Although pseudogenes are traditionally considered nonfunctional, emerging evidence suggests that they can act as regulators of gene networks through various mechanisms, including microRNA sequestration or competing endogenous RNA activity. The biological relevance of ADAMTS7P1 suppression remains unclear but warrants further investigation.\u003c/p\u003e\n \u003cp\u003eIn summary, our transcriptomic analysis revealed that acute opioid exposure induces early, subtle yet biologically meaningful transcriptional changes in genes associated with calcium signaling, synaptic plasticity, immune modulation, and reproductive function. These findings provide a systems-level view of opioid action and highlight new molecular candidates for mitigating side effects and improving analgesic therapies. While the neuroblastoma-derived SH-SY5Y cell line offers a well-established and tractable model for investigating neuronal signaling and opioid pharmacology, it represents a simplified in vitro system lacking the full cellular complexity of primary neurons and intact tissue microenvironments. Upon retinoic acid-induced differentiation, SH-SY5Y cells acquire several neuron-like features, including axonal projections, the synaptic machinery, and the expression of key neurotransmitter receptors, making them suitable for studying early transcriptional responses to opioid receptor activation. However, they do not recapitulate multicellular interactions, regional heterogeneity, or long-term neuroadaptive processes observed in vivo. Accordingly, the transcriptomic changes identified here should be interpreted as acute, cell-intrinsic effects of opioid exposure that serve as a mechanistic foundation for hypothesis generation. Future studies in primary neuronal cultures, organoid systems, or in vivo models will be essential to validate the broader physiological relevance of these findings.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study suggests that acute exposure of differentiated neuron-like SH-SY5Y cells to opioid agonists results in measurable changes in gene expression, even within a short treatment window. Although the transcriptional alterations were modest, several downregulated genes appear to be linked to pathways associated with known opioid side effects. These findings highlight the value of transcriptomic analysis as a tool for revealing early molecular responses to opioid stimulation. By providing deeper insight into the gene-level effects of opioids, transcriptomics can contribute to the rational design of new opioid compounds with improved safety profiles and reduced adverse effects. Future studies, including time-course experiments and the use of more complex models, such as organoids, to further elucidate the mechanisms of opioid action and addiction are to be performed.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eCell Culture\u003c/p\u003e\u003cp\u003eSH-SY5Y human neuroblastoma cells (Sigma-Aldrich, Ochsenfurt, Germany) were cultured in Dulbecco\u0026rsquo;s modified Eagle\u0026rsquo;s medium (DMEM; Thermo Fisher) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin‒streptomycin (Life Technologies GmbH). The cells were maintained at 37\u0026deg;C in a humidified 5% CO₂ incubator and routinely passaged at 90% confluence using 0.25% trypsin-EDTA (Life Technologies GmbH). All experimental procedures were carried out under sterile conditions in a laminar flow hood, and comprehensive standard operating procedures (SOPs) were used.\u003c/p\u003e\u003cp\u003eDifferentiation of SH-SY5Y cells\u003c/p\u003e\u003cp\u003eTo induce neuron-like phenotypes, the undifferentiated cells were cultivated for 24 hours and then differentiated by 10 \u0026micro;M all-trans-retinoic acid (ATRA; Sigma‒Aldrich) in the DMEM medium supplemented with 2% FBS and 1% penicillin-streptomicin.The cells were differentiated 7 days before treatment and the differentiation medium was replaced every 48\u0026ndash;72 hours. This protocol has previously been reported to induce neuron-like characteristics in SH-SY5Y cells \u003csup\u003e\u003cspan additionalcitationids=\"CR50 CR51\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOpioid Treatment\u003c/p\u003e\u003cp\u003eThe differentiated neuron-like SH-SY5Y cells were treated for 15 minutes with one of five opioid compounds: morphine hydrochloride trihydrate (Th. Geyer GmbH \u0026amp; Co. KG), naloxone, TRV-130, β-endorphin (MolPort), or synthetically produced metamorphine. Stock solutions of each compound were prepared in sterile ultrapure water (Aqua B. Braun Ecotainer, B. Braun Melsungen AG) and diluted to their respective IC₅₀-based working concentrations in serum-free DMEM (morphine: 193 nM; naloxone: 200 nM; β-endorphin: 200 nM; metamorphine: 169 nM; oliceridine: 200 nM). For each treatment, 11 \u0026micro;L of the respective stock solution was added to 19.8 mL of serum-free DMEM in a T75 flask. Control cells received 11 \u0026micro;L of Aqua B. Braun under identical conditions. To ensure reproducibility, all treatments were performed in three independent biological experiments on separate days.\u003c/p\u003e\u003cp\u003eRNA Isolation and Transcriptomic Analysis\u003c/p\u003e\u003cp\u003eAfter treatment, the cells were immediately washed with cold D-PBS to remove residual medium and detached by adding 2ml 2.5% trypsin and incubated for 4 minutes. The enzymatic reaction was stopped with DMEM, and the cells were collected by centrifugation at 300\u0026ndash;400 \u0026times; g for 5\u0026ndash;10 minutes at 4\u0026deg;C. The cell pellet was washed twice with cold D-PBS, snap-frozen on dry ice, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until shipment to Novogene (Cambridge, United Kingdom) for RNA extraction.\u003c/p\u003e\u003cp\u003eRNA quality control and library preparation\u003c/p\u003e\u003cp\u003eRNA integrity and purity were assessed by Novogene Co., Ltd. (Cambridge, United Kingdom) upon sample receipt. Total RNA was quantified via NanoDrop spectrophotometry, and integrity was evaluated via an Agilent 2100 Bioanalyzer. All eight samples passed Novogene\u0026rsquo;s internal quality criteria for library preparation and sequencing.\u003c/p\u003e\u003cp\u003eThe RNA integrity number (RIN) ranged from 4.7 to 8.4, with all the samples classified as \u0026ldquo;Pass.\u0026rdquo; The RNA concentration ranged from 54 to 442 ng/\u0026micro;L, and the total RNA yield was between 1.35 and 17.24 \u0026micro;g per sample, which was sufficient for standard mRNA-seq library construction. These results confirmed that the extracted RNA was of adequate quality for high-throughput sequencing.\u003c/p\u003e\u003cp\u003ecDNA libraries were prepared using the Novogene NGS RNA Library Prep Set (PT042), generating 250\u0026ndash;300 bp insert size libraries without strand-specificity.\u003c/p\u003e\u003cp\u003eSequencing and Quality Control\u003c/p\u003e\u003cp\u003eSequencing was performed on the Illumina NovaSeq 6000 platform, generating 150 bp paired-end reads. Each sample produced an average of 50\u0026nbsp;million raw reads. The adapter sequences, low-quality reads, and reads with \u0026gt;\u0026thinsp;10% unknown bases were removed via Novogene\u0026rsquo;s internal quality filtering pipeline.\u003c/p\u003e\u003cp\u003eTranscriptomic bioinformatics pipeline\u003c/p\u003e\u003cp\u003eTranscriptomic data analysis was conducted via a standardized bioinformatics workflow. Quality control of the raw sequencing reads was performed with FastQC (v0.12.1), and summary statistics were compiled via MultiQC. Reads were aligned to the human reference genome (GRCh38) via HISAT2 (v2.2.1), and gene-level quantification was carried out with featureCounts (v2.0.5), applying strand-specific settings.\u003c/p\u003e\u003cp\u003eDifferential gene expression analysis was performed in R via DESeq2 (v1.46.0) with default median-of-ratios normalization. Genes with an adjusted p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Benjamini\u0026ndash;Hochberg correction) were considered statistically significant.\u003c/p\u003e\u003cp\u003eTo explore biological significance, pathway enrichment analysis was performed via the clusterProfiler package, which incorporates the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome databases. Pathways with a false discovery rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered enriched.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cbr\u003e This work was supported by institutional resources from the Institute of Pharmaceutical Sciences, Faculty of Chemistry and Pharmacy, University of Freiburg. No specific external grant funded this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003cbr\u003eThe datasets generated and analysed during the current study are available in the NCBI Gene Expression Omnibus (GEO) repository, under accession number GSE306403 \u003cu\u003e(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE306403).\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAUTHOR INFORMATION\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding Authors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAly Abotaleb, Pharmacy, Medical Center – University of Freiburg, Freiburg, Germany. E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003eStefan Günther, Institute of Pharmaceutical Sciences, Faculty of Chemistry and Pharmacy, University of Freiburg, Freiburg, Germany. E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMattson, C. L. \u003cem\u003eet al.\u003c/em\u003e Trends and Geographic Patterns in Drug and Synthetic Opioid Overdose Deaths \u0026mdash; United States, 2013\u0026ndash;2019. \u003cem\u003eMorb. Mortal. Wkly. 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Differentiation of the SH-SY5Y Human Neuroblastoma Cell Line. \u003cem\u003eJ. Vis. Exp. JoVE\u003c/em\u003e 53193 (2016) doi:10.3791/53193. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Opioid, SH-SY5Y cells, Transcriptomics, Differential gene expression, Drug-induced transcriptomic response","lastPublishedDoi":"10.21203/rs.3.rs-7327879/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7327879/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOpioids remain indispensable for pain management but their use is limited by significant side effects, including respiratory depression, constipation, tolerance, addiction, and immunosuppression. Although much is known about their mechanism of action, the effects of acute opioid exposure on transcriptional responses have not yet been fully characterized.\u003c/p\u003e\u003cp\u003eWe performed a transcriptomic analysis of differentiated neuron-like SH-SY5Y cells exposed to five opioid ligands, namely, morphine, TRV130, metamorphine, β-endorphin, and naloxone. After incubation for 15 minutes, the cells were harvested and processed for RNA sequencing via the Illumina NovaSeq 6000 platform. Differential gene expression analysis was performed with DESeq2, and pathway enrichment was conducted via GO, KEGG and Reactome.\u003c/p\u003e\u003cp\u003eIndividual comparisons between each opioid-treated group and the control group revealed no statistically significant transcriptional changes. However, when all the agonist-treated samples were pooled and compared with the control samples, we identified several significantly downregulated genes (adjusted p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Specifically, we observed alterations in the expression of the genes CACNA1F, RASAL1, GARIN4, and TRIM56, which are involved in calcium signaling, synaptic plasticity, the immune response, and reproductive function. CACNA1F downregulation may affect neuronal excitability and retinal signaling; RASAL1 suppression could impact synaptic maturation and memory; GARIN4 is associated with sperm morphology; and TRIM56 downregulation has an immunomodulatory effect, all of which aligns with known opioid-induced side effects.\u003c/p\u003e\u003cp\u003eOur findings demonstrate that even short-term opioid exposure can initiate subtle but functionally relevant transcriptional changes. These early responses highlight the potential of transcriptomic profiling to uncover the molecular mechanisms underlying opioid pharmacodynamics and side effects. This approach offers deeper insights into opioid action and supports the development of safer analgesics with fewer systemic adverse effects.\u003c/p\u003e","manuscriptTitle":"Unraveling the role of CACNA1F, RASAL1, GARIN4, and TRIM56 in common opioid side effects via transcriptomic analysis of differentiated neuron-like SH-SY5Y cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 06:23:27","doi":"10.21203/rs.3.rs-7327879/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"de12b19f-be85-4acb-8f64-940467103267","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55066273,"name":"Biological sciences/Molecular biology"},{"id":55066274,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2025-10-07T08:09:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-22 06:23:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7327879","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7327879","identity":"rs-7327879","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}