Melding Synthetic Molecules and Genetically Encoded Proteins to Forge New Tools for Neuroscience.

Unraveling the complexity of the brain requires sophisticated methods to probe and perturb neurobiological processes with high spatiotemporal control. The field of chemical biology has produced general strategies to combine the molecular specificity of small-molecule tools with the cellular specificity of genetically encoded reagents. Here, we survey the application, refinement, and extension of these hybrid small-molecule:protein methods to problems in neuroscience, which yields powerful reagents to precisely measure and manipulate neural systems.

Enhancer-MDLF: a novel deep learning framework for identifying cell-specific enhancers.

Enhancers, noncoding DNA fragments, play a pivotal role in gene regulation, facilitating gene transcription. Identifying enhancers is crucial for understanding genomic regulatory mechanisms, pinpointing key elements and investigating networks governing gene expression and disease-related mechanisms. Existing enhancer identification methods exhibit limitations, prompting the development of our novel multi-input deep learning framework, termed Enhancer-MDLF. Experimental results illustrate that Enhancer-MDLF outperforms the previous method, Enhancer-IF, across eight distinct human cell lines and exhibits superior performance on generic enhancer datasets and enhancer-promoter datasets, affirming the robustness of Enhancer-MDLF. Additionally, we introduce transfer learning to provide an effective and potential solution to address the prediction challenges posed by enhancer specificity. Furthermore, we utilize model interpretation to identify transcription factor binding site motifs that may be associated with enhancer regions, with important implications for facilitating the study of enhancer regulatory mechanisms. The source code is openly accessible at https://github.com/HaoWuLab-Bioinformatics/Enhancer-MDLF.

scMultiGAN: cell-specific imputation for single-cell transcriptomes with multiple deep generative adversarial networks.

The emergence of single-cell RNA sequencing (scRNA-seq) technology has revolutionized the identification of cell types and the study of cellular states at a single-cell level. Despite its significant potential, scRNA-seq data analysis is plagued by the issue of missing values. Many existing imputation methods rely on simplistic data distribution assumptions while ignoring the intrinsic gene expression distribution specific to cells. This work presents a novel deep-learning model, named scMultiGAN, for scRNA-seq imputation, which utilizes multiple collaborative generative adversarial networks (GAN). Unlike traditional GAN-based imputation methods that generate missing values based on random noises, scMultiGAN employs a two-stage training process and utilizes multiple GANs to achieve cell-specific imputation. Experimental results show the efficacy of scMultiGAN in imputation accuracy, cell clustering, differential gene expression analysis and trajectory analysis, significantly outperforming existing state-of-the-art techniques. Additionally, scMultiGAN is scalable to large scRNA-seq datasets and consistently performs well across sequencing platforms. The scMultiGAN code is freely available at https://github.com/Galaxy8172/scMultiGAN.

P-CSN: single-cell RNA sequencing data analysis by partial cell-specific network.

Although many single-cell computational methods proposed use gene expression as input, recent studies show that replacing 'unstable' gene expression with 'stable' gene-gene associations can greatly improve the performance of downstream analysis. To obtain accurate gene-gene associations, conditional cell-specific network method (c-CSN) filters out the indirect associations of cell-specific network method (CSN) based on the conditional independence of statistics. However, when there are strong connections in networks, the c-CSN suffers from false negative problem in network construction. To overcome this problem, a new partial cell-specific network method (p-CSN) based on the partial independence of statistics is proposed in this paper, which eliminates the singularity of the c-CSN by implicitly including direct associations among estimated variables. Based on the p-CSN, single-cell network entropy (scNEntropy) is further proposed to quantify cell state. The superiorities of our method are verified on several datasets. (i) Compared with traditional gene regulatory network construction methods, the p-CSN constructs partial cell-specific networks, namely, one cell to one network. (ii) When there are strong connections in networks, the p-CSN reduces the false negative probability of the c-CSN. (iii) The input of more accurate gene-gene associations further optimizes the performance of downstream analyses. (iv) The scNEntropy effectively quantifies cell state and reconstructs cell pseudo-time.

Improving the performance of single-cell RNA-seq data mining based on relative expression orderings.

The advent of single-cell RNA-sequencing (scRNA-seq) provides an unprecedented opportunity to explore gene expression profiles at the single-cell level. However, gene expression values vary over time and under different conditions even within the same cell. There is an urgent need for more stable and reliable feature variables at the single-cell level to depict cell heterogeneity. Thus, we construct a new feature matrix called the delta rank matrix (DRM) from scRNA-seq data by integrating an a priori gene interaction network, which transforms the unreliable gene expression value into a stable gene interaction/edge value on a single-cell basis. This is the first time that a gene-level feature has been transformed into an interaction/edge-level for scRNA-seq data analysis based on relative expression orderings. Experiments on various scRNA-seq datasets have demonstrated that DRM performs better than the original gene expression matrix in cell clustering, cell identification and pseudo-trajectory reconstruction. More importantly, the DRM really achieves the fusion of gene expressions and gene interactions and provides a method of measuring gene interactions at the single-cell level. Thus, the DRM can be used to find changes in gene interactions among different cell types, which may open up a new way to analyze scRNA-seq data from an interaction perspective. In addition, DRM provides a new method to construct a cell-specific network for each single cell instead of a group of cells as in traditional network construction methods. DRM's exceptional performance is due to its extraction of rich gene-association information on biological systems and stable characterization of cells.

Spatiotemporal analysis identifies ABF2 and ABF3 as key hubs of endodermal response to nitrate.

Nitrate is a nutrient and a potent signal that impacts global gene expression in plants. However, the regulatory factors controlling temporal and cell type-specific nitrate responses remain largely unknown. We assayed nitrate-responsive transcriptome changes in five major root cell types of the Arabidopsis thaliana root as a function of time. We found that gene-expression response to nitrate is dynamic and highly localized and predicted cell type-specific transcription factor (TF)-target interactions. Among cell types, the endodermis stands out as having the largest and most connected nitrate-regulatory gene network. ABF2 and ABF3 are major hubs for transcriptional responses in the endodermis cell layer. We experimentally validated TF-target interactions for ABF2 and ABF3 by chromatin immunoprecipitation followed by sequencing and a cell-based system to detect TF regulation genome-wide. Validated targets of ABF2 and ABF3 account for more than 50% of the nitrate-responsive transcriptome in the endodermis. Moreover, ABF2 and ABF3 are involved in nitrate-induced lateral root growth. Our approach offers an unprecedented spatiotemporal resolution of the root response to nitrate and identifies important components of cell-specific gene regulatory networks.

Intermittent hypoxia increased the expression of ESM1 and ICAM-1 in vascular endothelial cells via the downregulation of microRNA-181a1.

Sleep apnea syndrome (SAS) exposes cells throughout the body to intermittent hypoxia (IH). Intermittent hypoxia is a risk factor not only for hypertension and insulin resistance but also for vascular dysfunction. We have reported correlations between IH, insulin resistance and hypertension. However, the details of why IH leads to vascular dysfunction remain unclear. In this study, we investigated inflammation-related transcripts in vascular endothelial cells (human HUEhT-1 and mouse UV2) exposed to IH by real-time RT-PCR and found that intercellular adhesion molecule-1 (ICAM-1) and endothelial cell-specific molecule-1 (ESM1) mRNAs were significantly increased. ELISA confirmed that, in the UV2 cell medium, ICAM-1 and ESM1 were significantly increased by IH. However, the promoter activities of ICAM-1 and ESM1 were not upregulated. On the other hand, IH treatment significantly decreased microRNA (miR)-181a1 in IH-treated cells. The introduction of miR-181a1 mimic but not miR-181a1 mimic NC abolished the IH-induced upregulation of Ican-1 and ESM1. These results indicated that ICAM-1 and ESM1 were upregulated by IH via the IH-induced downregulation of miR-181a1 in vascular endothelial cells and suggested that SAS patients developed atherosclerosis via the IH-induced upregulation of ICAM-1 and ESM1.

Pathogen stimulations and immune cells synergistically affect the gene expression profile characteristics of porcine peripheral blood mononuclear cells.

BACKGROUND: Pigs serve as a crucial source of protein in the human diet and play a fundamental role in ensuring food security. However, infectious diseases caused by bacteria or viruses are a major threat to effective global pig farming, jeopardizing human health. Peripheral blood mononuclear cells (PBMCs) are a mixture of immune cells that play crucial roles in immunity and disease resistance in pigs. Previous studies on the gene expression regulation patterns of PBMCs have concentrated on a single immune stimulus or immune cell subpopulation, which has limited our comprehensive understanding of the mechanisms of the pig immune response. RESULTS: Here, we integrated and re-analyzed RNA-seq data published online for porcine PBMC stimulated by lipopolysaccharide (LPS), polyinosinic acid (PolyI:C), and various unknown microorganisms (EM). The results revealed that gene expression and its functional characterization are highly specific to the pathogen, identifying 603, 254, and 882 pathogen-specific genes and 38 shared genes, respectively. Notably, LPS and PolyI:C stimulation directly triggered inflammatory and immune-response pathways, while exposure to mixed microbes (EM) enhanced metabolic processes. These pathogen-specific genes were enriched in immune trait-associated quantitative trait loci (QTL) and eGenes in porcine immune tissues and were implicated in specific cell types. Furthermore, we discussed the roles of eQTLs rs3473322705 and rs1109431654 in regulating pathogen- and cell-specific genes CD300A and CD93, using cellular experiments. Additionally, by integrating genome-wide association studies datasets from 33 complex traits and diseases in humans, we found that pathogen-specific genes were significantly enriched for immune traits and metabolic diseases. CONCLUSIONS: We systematically analyzed the gene expression profiles of the three stimulations and demonstrated pathogen-specific and cell-specific gene regulation across different stimulations in porcine PBMCs. These findings enhance our understanding of shared and distinct regulatory mechanisms of genetic variants in pig immune traits.

The bHLH transcription factor OsPRI1 activates the Setaria viridis PEPC1 promoter in rice.

Photosynthetic efficiency is reduced by the dual role of Rubisco, which acts either as a carboxylase or as an oxygenase, the latter leading to photorespiration. C4 photosynthesis evolved as a carbon-concentrating mechanism to reduce photorespiration. To engineer C4 into a C3 plant, it is essential to understand how C4 genes, such as phosphoenolpyruvate carboxylase (PEPC1), are regulated to be expressed at high levels and in a cell-specific manner. Yeast one-hybrid screening was used to show that OsPRI1, a rice bHLH transcription factor involved in iron homeostasis, binds to the Setaria viridis PEPC1 promoter. This promoter drives mesophyll-specific gene expression in rice. The role of OsPRI1 in planta was characterized using a rice line harbouring SvPEPC1pro ::GUS. We show that OsPRI1 activates the S. viridis PEPC1 promoter by binding to an N-box in the proximal promoter, and that GUS activity is highly reduced in SvPEPC1pro ::GUS lines when OsPRI1 is mutated. Cross-species comparisons showed that the SvPRI1 homolog binds to the SvPEPC1 promoter but the maize ZmPRI1 does not bind to the ZmPEPC1 promoter. Our results suggest that elements of the iron homeostasis pathway were co-opted to regulate PEPC1 gene expression during the evolution of some but not all C4 species.

Regulon active landscape reveals cell development and functional state changes of human primary osteoblasts in vivo.

BACKGROUND: While transcription factor (TF) regulation is known to play an important role in osteoblast development, differentiation, and bone metabolism, the molecular features of TFs in human osteoblasts at the single-cell resolution level have not yet been characterized. Here, we identified modules (regulons) of co-regulated genes by applying single-cell regulatory network inference and clustering to the single-cell RNA sequencing profiles of human osteoblasts. We also performed cell-specific network (CSN) analysis, reconstructed regulon activity-based osteoblast development trajectories, and validated the functions of important regulons both in vivo and in vitro. RESULTS: We identified four cell clusters: preosteoblast-S1, preosteoblast-S2, intermediate osteoblasts, and mature osteoblasts. CSN analysis results and regulon activity-based osteoblast development trajectories revealed cell development and functional state changes of osteoblasts. CREM and FOSL2 regulons were mainly active in preosteoblast-S1, FOXC2 regulons were mainly active in intermediate osteoblast, and RUNX2 and CREB3L1 regulons were most active in mature osteoblasts. CONCLUSIONS: This is the first study to describe the unique features of human osteoblasts in vivo based on cellular regulon active landscapes. Functional state changes of CREM, FOSL2, FOXC2, RUNX2, and CREB3L1 regulons regarding immunity, cell proliferation, and differentiation identified the important cell stages or subtypes that may be predominantly affected by bone metabolism disorders. These findings may lead to a deeper understanding of the mechanisms underlying bone metabolism and associated diseases.

SPIDE: A single cell potency inference method based on the local cell-specific network entropy.

For a given single cell RNA-seq data, it is critical to pinpoint key cellular stages and quantify cells' differentiation potency along a differentiation pathway in a time course manner. Currently, several methods based on the entropy of gene functions or PPI network have been proposed to solve the problem. Nevertheless, these methods still suffer from the inaccurate interactions and noises originating from scRNA-seq profile. In this study, we proposed a cell potency inference method based on cell-specific network entropy, called SPIDE. SPIDE introduces the local weighted cell-specific network for each cell to maintain cell heterogeneity and calculates the entropy by incorporating gene expression with network structure. In this study, we compared three cell entropy estimation models on eight scRNA-Seq datasets. The results show that SPIDE obtains consistent conclusions with real cell differentiation potency on most datasets. Moreover, SPIDE accurately recovers the continuous changes of potency during cell differentiation and significantly correlates with the stemness of tumor cells in Colorectal cancer. To conclude, our study provides a universal and accurate framework for cell entropy estimation, which deepens our understanding of cell differentiation, the development of diseases and other related biological research.

Potential network markers and signaling pathways for B cells of COVID-19 based on single-cell condition-specific networks.

To explore the potential network markers and related signaling pathways of human B cells infected by COVID-19, we performed standardized integration and analysis of single-cell sequencing data to construct conditional cell-specific networks (CCSN) for each cell. Then the peripheral blood cells were clustered and annotated based on the conditional network degree matrix (CNDM) and gene expression matrix (GEM), respectively, and B cells were selected for further analysis. Besides, based on the CNDM of B cells, the hub genes and 'dark' genes (a gene has a significant difference between case and control samples not in a gene expression level but in a conditional network degree level) closely related to COVID-19 were revealed. Interestingly, some of the 'dark' genes and differential degree genes (DDGs) encoded key proteins in the JAK-STAT pathway, which had antiviral effects. The protein p21 encoded by the 'dark' gene CDKN1A was a key regulator for the COVID-19 infection-related signaling pathway. Elevated levels of proteins encoded by some DDGs were directly related to disease severity of patients with COVID-19. In short, the proteins encoded by 'dark' genes complement some missing links in COVID-19 and these signaling pathways played an important role in the growth and activation of B cells.

Myofibroblast-specific inhibition of the Rho kinase-MRTF-SRF pathway using nanotechnology for the prevention of pulmonary fibrosis.

Pulmonary fibrosis is characterized by the accumulation of myofibroblasts in the lung and progressive tissue scarring. Fibroblasts exist across a spectrum of states, from quiescence in health to activated myofibroblasts in the setting of injury. Highly activated myofibroblasts have a critical role in the establishment of fibrosis as the predominant source of type 1 collagen and profibrotic mediators. Myofibroblasts are also highly contractile cells and can alter lung biomechanical properties through tissue contraction. Inhibiting signaling pathways involved in myofibroblast activation could therefore have significant therapeutic value. One of the ways myofibroblast activation occurs is through activation of the Rho/myocardin-related transcription factor (MRTF)/serum response factor (SRF) pathway, which signals through intracellular actin polymerization. However, concerns surrounding the pleiotropic and ubiquitous nature of these signaling pathways have limited the translation of inhibitory drugs. Herein, we demonstrate a novel therapeutic antifibrotic strategy using myofibroblast-targeted nanoparticles containing a MTRF/SRF pathway inhibitor (CCG-1423), which has been shown to block myofibroblast activation in vitro. Myofibroblasts were preferentially targeted via the angiotensin 2 receptor, which has been shown to be selectively upregulated in animal and human studies. These nanoparticles were nontoxic and accumulated in lung myofibroblasts in the bleomycin-induced mouse model of pulmonary fibrosis, reducing the number of these activated cells and their production of profibrotic mediators. Ultimately, in a murine model of lung fibrosis, a single injection of these drugs containing targeted nanoagents reduced fibrosis as compared with control mice. This approach has the potential to deliver personalized therapy by precisely targeting signaling pathways in a cell-specific manner, allowing increased efficacy with reduced deleterious off-target effects.

Molecular Markers of Ovarian Germ Cells of Banana Prawn (Fenneropenaeus merguiensis).

The banana prawn (Fenneropenaeus merguiensis) is a valuable prawn in the worldwide market. However, cultivation of this species is limited owing to the difficulty in culture management and limited knowledge of reproduction. Therefore, we studied the gene expression and molecular mechanisms involved in oogenesis for elucidating ovarian germ cell development in banana prawns. The tissue-specific distribution of certain genes identified from previous transcriptome data showed that FmCyclinB, FmNanos, and nuclear autoantigenic sperm protein (FmNASP) were only expressed in gonads. The in situ hybridization (ISH) of these three genes showed different expression patterns throughout oogenesis. FmCyclinB was highly expressed in pre-vitellogenic oocytes. FmNanos was expressed at almost the same level during oogenesis but showed the most expression in late pre-vitellogenic stages. Based on the highest expression of FmCyclinB and FmNanos in mid pre-vitellogenic and late pre-vitellogenic oocytes, respectively, we suggested that FmNanos may suppress FmCyclinB expression before initiation of vitellogenesis. Meanwhile, FmNASP expression was detected only in pre-vitellogenesis. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) analysis of FmNASP expression was supported by FmNASP ISH analysis based on high expression of FmNASP in sub-adult ovaries, which contain most of pre-vitellogenic oocytes. In this study, we found three reliable ovarian markers for banana prawns and also found a dynamic change of molecular mechanism during the sub-stage of pre-vitellogenesis. We determined the expression levels of these genes involved in oogenesis. Our findings provide information for further studies on banana prawn reproduction which may assist in their cultivation.

Anti-HLA antibodies in recipients of CD19 versus BCMA-targeted CAR T-cell therapy.

Antibodies against foreign human leukocyte antigen (HLA) molecules are barriers to successful organ transplantation. B cell-depleting treatments are used to reduce anti-HLA antibodies but have limited efficacy. We hypothesized that the primary source for anti-HLA antibodies is long-lived plasma cells, which are ineffectively targeted by B cell depletion. To study this, we screened for anti-HLA antibodies in a prospectively enrolled cohort of 49 patients who received chimeric antigen receptor T-cell therapy (CARTx), targeting naïve and memory B cells (CD19-targeted, n = 21) or plasma cells (BCMA-targeted, n = 28) for hematologic malignancies. Longitudinal samples were collected before and up to 1 year after CARTx. All individuals were in sustained remission. We identified 4 participants with anti-HLA antibodies before CD19-CARTx. Despite B cell depletion, anti-HLA antibodies and calculated panel reactive antibody scores were stable for 1 year after CD19-CARTx. Only 1 BCMA-CARTx recipient had pre-CARTx low-level anti-HLA antibodies, with no follow-up samples available. These data implicate CD19neg long-lived plasma cells as an important source for anti-HLA antibodies, a model supported by infrequent HLA sensitization in BCMA-CARTx subjects receiving previous plasma cell-targeted therapies. Thus, plasma cell-targeted therapies may be more effective against HLA antibodies, thereby enabling improved access to organ transplantation and rejection management.

Sialylated IVIg binding to DC-SIGN+ Hofbauer cells induces immune tolerance through the caveolin-1/NF-kB pathway and IL-10 secretion.

Although the use of IVIg has increased in various immune-driven diseases and even in pregnancy, the exact action mechanisms of IVIg are not fully understood. Dendritic cell-specific intercellular adhesion molecule-3 grabbing non-integrin (DC-SIGN) is a known receptor for α-2,6-sialylated IgG (sIVIg), which is responsible for the anti-inflammatory effect of IVIg. DC-SIGN is expressed on Hofbauer cells (HBCs) of the fetal villi of the placenta which act as an innate immune modulator at the maternal-fetal interface. Preeclampsia is a major complication in pregnancy and is related to IL-10, a cytokine with an important role in immune tolerance. DC-SIGN interaction with sIVIg in HBCs promoted IL-10 secretion through the activation of the caveolin-1/NF-κB pathway, especially in plasma lipid rafts. Consistent results were obtained for HBCs from patients with preeclampsia. Collectively, the stimulation of DC-SIGN+ HBCs with sIVIg enhanced immune tolerance in the feto-maternal environment, suggesting the therapeutic application of sIVIg to prevent preeclampsia.

Gene-Based Modeling of Methane Oxidation in Coastal Sediments: Constraints on the Efficiency of the Microbial Methane Filter.

Methane is a powerful greenhouse gas that is produced in large quantities in marine sediments. Microbially mediated oxidation of methane in sediments, when in balance with methane production, prevents the release of methane to the overlying water. Here, we present a gene-based reactive transport model that includes both microbial and geochemical dynamics and use it to investigate whether the rate of growth of methane oxidizers in sediments impacts the efficiency of the microbial methane filter. We focus on iron- and methane-rich coastal sediments and, with the model, show that at our site, up to 10% of all methane removed is oxidized by iron and manganese oxides, with the remainder accounted for by oxygen and sulfate. We demonstrate that the slow growth rate of anaerobic methane-oxidizing microbes limits their ability to respond to transient perturbations, resulting in periodic benthic release of methane. Eutrophication and deoxygenation decrease the efficiency of the microbial methane filter further, thereby enhancing the role of coastal environments as a source of methane to the atmosphere.

Hypoxia-induced factor 1α promotes osteotomy-induced regional acceleratory phenomenon via DC-STAMP mediated membrane fusion.

OBJECTIVES: The mechanisms of regional acceleratory phenomenon (RAP) induced by orthognathic osteotomy are unclear. It was not known if locally hypoxic microenvironment changes were involved in this phenomenon. METHODS: Hypoxia-induced factor-1α knockout mice harboring Cathepsin K (CTSK) Cre were used to investigate the effect of hypoxia-driven osteoclasts on alveolar bone remodeling. RAW264.7 cells were induced by CoCl2 to observe the effects of dendritic cell-specific transmembrane protein (DC-STAMP) on the fusion and differentiation of osteoclasts. RESULTS: We found mandibular osteotomy of C57 mice induced active alveolar osteoclasts and increased hypoxia-induced factor-1α (HIF-1α) positive staining areas. Alveolar bone density of the 10-week-old HIF-1α conditional knockout (CKO) mouse was increased at 10 and 14 days after bilateral mandibular osteotomy. Moreover, decreased numbers of osteoclasts and matrix metalloproteinase 9 (MMP-9)-positive cells were observed on the surface of bone resorption lacunae in the CKO group. HIF-1α could increase the expression level of DC-STAMP to enhance osteoclastogenesis and cell fusion in active RAW264.7 cells. CONCLUSION: Our data considered hypoxia-driven osteoclasts resorption to be an adaptive mechanism to permit alveolar bone loss after bilateral mandibular osteotomy of mice.

Insights into Cell-Specific Functions of Microtubules in Skeletal Muscle Development and Homeostasis.

The contractile cells of skeletal muscles, called myofibers, are elongated multinucleated syncytia formed and maintained by the fusion of proliferative myoblasts. Human myofibers can be hundreds of microns in diameter and millimeters in length. Myofibers are non-mitotic, obviating the need for microtubules in cell division. However, microtubules have been adapted to the unique needs of these cells and are critical for myofiber development and function. Microtubules in mature myofibers are highly dynamic, and studies in several experimental systems have demonstrated the requirements for microtubules in the unique features of muscle biology including myoblast fusion, peripheral localization of nuclei, assembly of the sarcomere, transport and signaling. Microtubule-binding proteins have also been adapted to the needs of the skeletal muscle including the expression of skeletal muscle-specific protein isoforms generated by alternative splicing. Here, we will outline the different roles microtubules play in skeletal muscle cells, describe how microtubule abnormalities can lead to muscle disease and discuss the broader implications for microtubule function.

Effect of stimulation intensity of a differential target multiplexed SCS program in an animal model of neuropathic pain.

BACKGROUND: Spinal cord stimulation (SCS) has been proven to be an effective treatment for patients suffering from intractable chronic neuropathic pain. Recent advances in the field include the utilization of programs that multiplex various signals to target different neural structures in the dorsal spinal cord associated with the painful area. Preclinical studies have been fundamental in understanding the mechanism by which this differential target multiplexed programming (DTMP) SCS approach works. Transcriptomic- and proteomic-based studies demonstrated that DTMP can modulate expression levels of genes and proteins involved in pain-related processes that have been affected by a neuropathic pain model. This work studied the effect of the intensity of DTMP signals on mechanical hypersensitivity and cell-specific transcriptomes. METHODS: The spared nerve injury model (SNI) of neuropathic pain was induced in 20 animals which were 1:1 randomized into two SCS groups in which the intensity of the DTMP was adjusted to either 70% or 40% of the motor threshold (MT). SCS was applied continuously for 48 h via a quadripolar lead implanted in the dorsal epidural space of animals. Controls, which included a group of implanted SNI animals that received no SCS and a group of animals naive to the SNI, were assessed in parallel to the SCS groups. Mechanical hypersensitivity was assessed before SNI, before SCS, and at 48 h of SCS. At the end of SCS, the stimulated segment of the dorsal spinal cord was dissected and subjected to RNA sequencing to quantify expression levels in all experimental groups. Differential effects were assessed via fold-change comparisons of SCS and naive groups versus the no-SCS group for transcriptomes specific to neurons and glial cells. Standard statistical analyses were employed to assess significance of the comparisons (p < 0.05). RESULTS: SCS treatments provided significant improvement in mechanical sensitivity relative to no SCS treatment. However, the change in the intensity did not provide a significant difference in the improvement of mechanical sensitivity. DTMP regulated expression levels back toward those found in the naive group in the cell-specific transcriptomes analyzed. There were no significant differences related to the intensity of the stimulation in terms of the percentage of genes in each transcriptome in which expression levels were reversed toward the naive state. CONCLUSIONS: DTMP when applied at either 40% MT or 70% MT provided similar reduction of pain-like behavior in rats and similar effects in neuron- and glia-specific transcriptomes.