The study was approved by the Fuyang People’s Hospital ethics committee (approval number: [2024]64), and all participants or their families/legal guardians provided informed consent in accordance with the ethical standards of the Helsinki declaration.

In this study, we recruited a cohort of patients diagnosed with SMA (n = 5) and matched healthy controls (n = 5) from Fuyang People’s Hospital between January 2024 and June 2024. The inclusion criteria for participant selection were as follows: (1) met the clinical diagnostic criteria for SMA [17] and (2) had a homozygous deletion of the SMN1 gene detected [4]. The inclusion criterion for the normal control group was a copy number of 2 for the SMN1 gene. The exclusion criteria for participant selection were as follows: (1) the presence of blood disorders; (2) the presence of bone tumors; (3) treatment that could influence SMA progression or symptoms, such as ongoing gene therapy or pharmacological interventions; (4) a history of other neuromuscular disorders that could confound the results; and (5) a family history of genetic disorders that might affect the interpretation of genetic data related to the SMA.

(1) Motor function assessments: Motor function was evaluated via standardized scales to measure muscle strength, coordination, and motor milestones in SMA patients. (2) Neurophysiological measurements: Electromyography (EMG) and nerve conduction studies were performed to assess the functional integrity of motor neurons and neuromuscular junctions. (3) Biochemical markers: The levels of UTS2 and other relevant proteins in the blood and spinal fluid were quantified to correlate with disease severity and response to treatment. (4) Imaging studies: Neuroimaging techniques, such as magnetic resonance imaging (MRI), have been employed to monitor changes in muscle and neuronal structure, providing insights into disease progression. (5) Histopathological examination: Tissue biopsies, when available, were examined for signs of muscle degeneration, neuronal loss, and other pathological features associated with the SMA. (6) Molecular and Cellular Analysis: The expression levels of UTS2 and related genes in patient-derived cells were analyzed to understand the underlying molecular mechanisms.

To obtain differential expression gene information, total RNA was extracted from peripheral blood samples collected from the antecubital vein of the participants. The collection process involved the use of sterile vacutainer tubes containing an appropriate anticoagulant, such as EDTA, to prevent blood clotting. Once collected, the samples were gently inverted several times to ensure thorough mixing with the anticoagulant and then stored on ice.

The total peripheral blood RNA was then extracted via TRIzol Reagent, a monophasic solution of phenol and guanidine isothiocyanate that effectively lyses cells and inactivates RNases, thus preserving the integrity of the RNA. Following extraction, the purity, concentration, and integrity of the RNA were assessed via a combination of NanoDrop (Thermo Fisher Scientific, Waltham, MA, USA) and Agilent 2100/4200 systems (Agilent Technologies, Santa Clara, CA, USA). The NanoDrop provides a rapid and accurate measurement of RNA concentration and purity by determining the absorbance at 260 nm and 280 nm, whereas the Agilent 2100/4200 systems offer a detailed electropherogram that assesses RNA integrity through the analysis of ribosomal RNA peaks.

After assessment, the RNA samples were aliquoted into RNase-free tubes and stored at –80 °C until further use. This low-temperature storage ensures the long-term preservation of RNA integrity, preventing degradation that could occur due to RNase activity or other environmental factors.

Subsequently, 3 µg of RNA was subjected to mRNA enrichment, fragmentation, and complementary DNA (cDNA) synthesis. The cDNA was processed through end-repair, A-tailing, and purification via Hieff NGS® DNA Selection Beads (Yeasen, Shanghai, China). The purified cDNA was amplified to form single-stranded circular DNA (ss-cDNA), which was then transformed into DNA nanoballs (DNBs) through rolling circle amplification (RCA). The final library was quantified with a Qubit (Thermo Fisher Scientific, Waltham, MA, USA) to confirm adequate sequencing input.

The RNA-seq library was sequenced on the DNBSEQ-T7 platform with a PE150 model, leveraging the high-throughput capabilities of next-generation sequencing. This service was provided by Bioyi Biotechnology Co., Ltd. (Wuhan, Hubei, China), ensuring the generation of high-quality paired-end reads for comprehensive transcriptome analysis.

To gain insight into the biological functions and pathways associated with these differentially expressed genes (DEGs), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. In the quality control process, the raw sequencing reads were first processed via fastp software 0.21.0 (SBGrid Consortium, Cambridge, MA, USA) to remove low-quality data, including 3^′ end sequences containing adapters and reads with an average quality score below Q20, ensuring that only high-quality reads were used for subsequent analysis. These high-quality reads were subsequently aligned to a reference genome via HISAT2 software 2.1.0 (Center for Computational Biology at Johns Hopkins University, Baltimore, MD, USA). For gene expression analysis, String Tie software 2.1.5 (Center for Computational Biology at Johns Hopkins University, Baltimore, MD, USA) was used to quantify gene expression levels, which were normalized to fragments per kilobase of transcript per million mapped reads (FPKM). Furthermore, DESeq2 software 1.30.1 (Bioconductor Project, Dortmund, Germany) was used to identify DEGs on the basis of the criteria of $|$log2FoldChange$|$ $>$ 1 and p $\le$ 0.05. To correct for multiple comparisons in gene expression and enrichment analyses, we employed a false discovery rate (FDR) control method. Specifically, we used the Benjamini‒Hochberg procedure [18] to adjust the p values, setting the significance threshold at an FDR of 0.01 for gene expression analysis and an FDR of 0.05 for GO and KEGG enrichment analyses. This approach helps to control the expected proportion of false positives among the significant results, ensuring the robustness and reliability of our findings.

Finally, to investigate the enrichment of differentially expressed genes in biological functions and pathways, Cluster Profiler software 3.18.1 (Bioconductor Project, Dortmund, Germany) was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Significance was defined as p $\le$ 0.05. We used the abovementioned FDR control method to correct for multiple comparisons in these analyses.

Human bone marrow mesenchymal stem cells (hBM-MSCs) were isolated from healthy donors via a sterile procedure, which typically involves the following steps: bone marrow aspiration under aseptic conditions, density gradient centrifugation to enrich the MSC population, initial plastic adherence to select for MSCs, and subsequent culture expansion in a sterile incubator while monitoring for cell confluence and viability, ensuring that the entire process adheres to good manufacturing practice (GMP) standards to maintain sterility and cell purity. The bone marrow was flushed with L-DMEM (Gibco, #11885084, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% FBS (Gibco, #10082147, Thermo Fisher Scientific, Waltham, MA, USA) to create a cell suspension, which was then centrifuged at 1500 rpm for 10 minutes to remove the adipose tissue and supernatant. The resulting cell pellet was resuspended in fresh L-DMEM and homogenized by gentle pipetting. Mononuclear cells were separated via lymphocyte separation medium (density of 1.077 g/mL), washed twice, counted, and plated at a density of 1 $\times$ 10⁶ cells/mL in culture flasks containing 5 mL of culture medium, resulting in hBM-MSCs.

hBM-MSCs were cultured in low-glucose complete DMEM (BL301A, Pricella, Shanghai, China) and maintained at 37 °C in a humidified atmosphere containing 5% CO₂, and the medium was subsequently changed every 3–4 days. All cell lines were validated by short tandem repeat (STR) profiling and tested negative for mycoplasma.

The experimental design included several groups to evaluate the impact of short hairpin RNA (shRNA)-mediated SMN1 knockdown and the subsequent effects of UTS2 inhibition with urantide on human bone marrow mesenchymal stem cells (hBM-MSCs). The groups included a time point group transfected with SMN1-targeting shRNA at the beginning (0 h), a group assessed 48 hours posttransfection, a nontargeting shRNA control group (pshRNA-0), and an SMN1 shRNA treatment group (pshRNA-SMN1). Additionally, a baseline control group of untransfected cells was included, alongside an SMA cell model group (SMA), and two groups were treated with low (10 nM, L-Urantide+SMA) and high (20 nM, H-Urantide+SMA) concentrations of uranide.

For transfection, hBM-MSCs were plated in 24-well plates at a density of 50,000 cells per well and allowed to adhere overnight under cell culture conditions at 37 °C and 5% CO₂. The following day, the cells were transfected with the recombinant pLKO.1-shRNA plasmids via Lipofectamine 3000 (#L3000008, Thermo Fisher Scientific, Waltham, MA, USA) in Opti-MEM (#31985062, Thermo Fisher Scientific, Waltham, MA, USA) reduced serum medium following the manufacturer’s instructions. The DNA-Lipofectamine complexes were added to the cells, which were subsequently incubated for 6 hours to facilitate complex formation and uptake, after which the medium was replaced with fresh complete growth medium. After a 48-hour incubation to allow for gene silencing, the cells were harvested for analysis, such as reverse transcription quantitative polymerase chain reaction (RT-qPCR). Western blot analysis, immunofluorescence staining and cell viability and apoptosis assays.

The efficiency of SMN1 knockdown was determined by quantifying the expression of SMN1 mRNA via reverse transcription quantitative polymerase chain reaction (RT-qPCR), and the results were normalized to those of the housekeeping gene GAPDH to determine relative expression levels. The shRNA sequences used were as follows: SMN-shRNA-1F-ATAGTATACGAAAATAGTCACTTCAAGAGAGTGACTATTTTCGTATACTAT, SMN-shRNA-1R-GACTATTTTCGTATACTATTTAAGTTCTCTAAATAGTATACGAAAATAGTC, SMN-shRNA-2F-AAATAGTATACGAAAATAGTCTTCAAGAGAGACTATTTTCGTATACTATTT, SMN-shRNA-2R-CTATTTTCGTATACTATTTCGAAGTTCTCTCGAAATAGTATACGAAAATAG, SMN-shRNA-3F-TGTAAACAGGGGTTGAAAGGTTTCAAGAGAACCTTTCAACCCCTGTTTACA, SMN-shRNA-3R-CTTTCAACCCCTGTTTACAAGAAGTTCTCTCTTGTAAACAGGGGTTGAAAG, sh-NC-F-CACCGTTCTCCGAACGTGTCACGTTTCAAGAGAACGTGACACGTTCGGAGAATTTTTTG, sh-NC-F-GATCCAAAAAATTCTCCGAACGTGTCACGTTCTCTTGAAACGTGACACGTTCGGAGAAC.

Total RNA was extracted from cells via the Cell/Tissue Total RNA Isolation Kit V2 (Vazyme, Nanjing, Jiansu, China). The HiScript lll 1st Strand cDNA Synthesis Kit (Vazyme, China) was used to synthesize cDNA, followed by RT-qPCR using Taq Pro Universal SYBR qPCR Master Mix (Vazyme, China). The relative expression levels of fl-SMN mRNA were calculated via the 2^{-Δ⁢Δ⁢Ct} method, with GAPDH serving as the endogenous control. The primers used were as follows: SMN-F-CCACTTACTATCATGCTGGCTG, SMN-R-CCACTTACTATCATGCTGGCTG, Caspase-3-F-TGCTATTGTGAGGCGGTTGT, Caspase-3-R-TCACGGCCTGGGATTTCAAG, GAPDH-F-ACCACAGTCCATGCCATCAC, and GAPDH-R-TCCACCACCCTGTTGCTGTA.

Protein extraction was performed via RIPA lysis buffer (Beyotime, Shanghai, China) supplemented with PMSF (Beyotime, China). Protein concentrations were determined via a BCA protein assay kit (NCM Biotech, Nanjing, Jiangsu, China). Equal amounts of protein were separated by SDS‒PAGE and transferred onto PVDF membranes (Sigma‒Aldrich, St. Louis, MO, USA). The membranes were probed with primary antibodies against SMN/Gemin 1 (1:1000, ab108531, Abcam, Cambridge, UK) and $\beta$-Tubulin (1:1000, 2148S, Cell Signaling Technology, Danvers, MA, USA), followed by HRP-conjugated secondary antibodies (1:20,000, bs-0295G-HRP, Bioss, Beijing, China). The protein bands were visualized via an enhanced chemiluminescence (ECL) substrate (NCM Biotech, Jiangsu, China).

The cells were fixed with 4% paraformaldehyde and permeabilized with 0.25% Triton X-100. After being blocked with goat serum, the cells were incubated with primary antibodies against neuron-specific markers [NSE (1:200, Abcam, UK) and neurofilament (NF) (1:200, Cell Signaling Technology, USA)] overnight at 4 °C, followed by incubation with fluorescently labeled secondary antibodies [goat anti-rabbit IgG H&L/HRP (1:200, Bioss, China) and goat anti-mouse IgG H&L/HRP (Bioss, China)]. Nuclei were counterstained with DAPI, and images were captured via a fluorescence microscope.

To evaluate whether the reduction in cell viability is attributed to an increase in apoptosis, we employed TUNEL fluorescence and Annexin V, which enabled us to compare the apoptotic rates among the different experimental groups.

Cell viability was assessed via the MTT assay (Beyotime, China), and apoptosis was measured via the TUNEL assay (Beyotime, China) and an Annexin V-FITC apoptosis detection kit (Beyotime, China) according to the manufacturers’ instructions.

The data were analyzed via GraphPad Prism 9.4.0 (GraphPad Software, LLC, Boston, MA, USA) and are presented as the means $\pm$ SDs. Statistical differences between groups were evaluated via a t test or one-way ANOVA, with p 0.05 considered statistically significant.

The principal component analysis (PCA) plot demonstrated distinct separation between the SMA and control groups, except for samples C1 and C2, which showed some overlap with the SMA group, indicating a unique transcriptional profile associated with SMA (Fig. 1A). The heatmap of differentially expressed genes (DEGs) further emphasized the difference between the two groups, highlighting that differential gene expression can serve as a robust classifier (Fig. 1B). Comparative analysis revealed 196 upregulated genes and 129 downregulated genes in the SMA group compared with the control group (Fig. 1C), suggesting a more pronounced effect of upregulated genes on SMA pathogenesis. The results indicated significant enrichment of upregulated genes in various biological processes and pathways (Fig. 1D,E), leading us to focus subsequent research on upregulated genes. The application of stringent criteria for gene selection based on a log2FoldChange greater than 1.5 and a p value $\le$ 0.01 resulted in the identification of 40 upregulated genes, among which HLA-DRB1, HLA-DRB5, FOS, ADAM12, BEND6, CXCL8, EYA2, FLT4, H1-4, PDZD4, and UTS2 were annotated with Gene Ontology Biological Process terms (Fig. 1F). Considering their potential relevance to the SMA context, UTS2 was selected for further investigation after a thorough literature review.

Fig. 1.

Bioinformatics analysis of clinical samples. (A) Principal component analysis (PCA) plot showing the separation between the spinal muscular atrophy (SMA) and control groups. (B) Heatmap of differentially expressed genes (DEGs) differentiating the two groups. (C) Volcano plot indicating the number of upregulated and downregulated genes in the SMA group compared with the control group. (D,E) Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the DEGs. (F) Selection of UTS2 among the upregulated genes on the basis of stringent filtering criteria.

After the knockdown of SMN1 in MSCs, we observed significant changes in cellular morphology and marker expression indicative of neuronal differentiation. The absence of CD34 expression and the presence of CD44 expression are associated with MSCs (Fig. 2A). Successful transfection was indicated by the positive signal of GFP (green fluorescent proteins) (Fig. 2B), while both the RNA (Fig. 2C) and protein (Fig. 2D) expression of SMN1 were significantly suppressed by shRNA.

Fig. 2.

Establishment and characterization of SMN1 knockdown in MSCs. (A) Bone marrow was obtained from non-SMA patients, excluding those with concurrent blood diseases or bone tumors, to isolate and purify MSCs. (B) A short hairpin RNA (shRNA) construct targeting the survival motor neuron 1 (SMN1) gene was synthesized and cloned and inserted into a vector, creating a recombinant plasmid designed to express SMN1-shRNA within cells. (C,D) SMN1 knockdown in MSCs was evaluated by measuring SMN mRNA levels via RT-qPCR (C) and full-length SMN protein levels via Western blotting (D). A significant reduction in SMN expression confirmed the efficacy of the shRNA construct in silencing the SMN1 gene. (E) Morphological changes indicative of neuronal differentiation in MSCs after infection with SMN1-targeting shRNA lentivirus. The images show that neurite outgrowth and changes in the cell body are characteristic of neuron-like cells. (F) Immunocytochemical staining confirming the expression of the neuron-specific markers NSE and NF in differentiated neuron-like cells, indicating successful differentiation. (G) RT-qPCR analysis demonstrating a sustained reduction in SMN mRNA levels in differentiated neuron-like cells compared with preinduction levels. (H) Western blot analysis showing decreased SMN protein expression in differentiated cells, which was consistent with the mRNA results and confirmed the maintenance of the SMN1 knockdown effect. * represents p 0.05, ** represents p 0.01, and *** represents p 0.001. The scale is 100 µm in (A) and (F) and 50 µm in (B) and (E). MSCs, mesenchymal stem cells; NSE, neuron-specific markers; NF, neurofilament; mRNA, messenger RNA; RT-PCR, transcription quantitative polymerase chain reaction.

After induction, the morphology of MSCs transformed into neuronal-like cells, characterized by cytoplasmic flattening and shrinkage toward the nucleus, as well as peripheral extension of cell membrane protrusions (Fig. 2E). Immunocytochemical staining confirmed the expression of neuron-specific markers, including neuron-specific enolase (NSE) and neurofilament (NF) proteins, in the differentiated cells (Fig. 2F). To assess the impact of SMN1 knockdown on the differentiation process, we measured the expression levels of SMN mRNA and protein in neuron-like cells via reverse transcription quantitative polymerase chain reaction (RT-qPCR) and Western blot methods, respectively. The results revealed a reduction in SMN expression postdifferentiation compared with preinduction levels, indicating that the knockdown effect was maintained throughout the differentiation process (Fig. 2G,H).

The cell survival curves revealed a positive proliferation trend in the SMA group, which was attenuated in a dose-dependent manner by urantide treatment, as observed in the L-urrantide group and H-urrantide group (Fig. 3A). MTT assays corroborated these findings, revealing a significant decrease in cell viability with urantide treatment (Fig. 3B). TUNEL assays and flow cytometry via Annexin V staining revealed a significant increase in the number of apoptotic cells in response to urantide treatment, with higher concentrations leading to further increases in apoptosis rates than those in the SMA group without intervention (Fig. 3C,D). RT-qPCR analysis revealed the upregulation of Caspase-3 mRNA in the urantide-treated groups, suggesting the induction of apoptotic pathways in the SMA cell model (Fig. 3F). Immunofluorescence staining revealed an increase in Caspase-3 protein expression in the urantide-treated groups, with higher expression observed in the H-urrantide+SMA group than in the L-urrantid group, and SMN protein expression was decreased in accordance with the mRNA levels (Fig. 3E).

Fig. 3.

Urantide-induced apoptosis in SMA cell models. (A) Cell survival curves depicting a dose-dependent attenuation of proliferation in SMA cells treated with urantide, as observed in the L-urrantide and H-urrantide groups. (B) MTT assays confirmed a significant decrease in cell viability with urantide treatment, indicating cytotoxic effects. (C) TUNEL fluorescence staining revealed a significant increase in apoptotic cells in response to urantide treatment, with higher concentrations leading to further increases in apoptosis rates. (D) Flow cytometry via Annexin V staining further demonstrated the proapoptotic effect of uride in a dose-dependent manner. (E) Immunofluorescence staining showing increased Caspase-3 protein expression in the urantide-treated groups, with the H-urrantide+SMA group exhibiting higher expression than the L-urrantide group and decreased SMN protein expression aligning with the mRNA levels. (F) RT-qPCR analysis confirming the upregulation of Caspase-3 mRNA in the urantide-treated groups, suggesting the activation of apoptotic pathways. * represents p 0.05, ** represents p 0.01, and *** represents p 0.001. The scale is 50 µm in (C) and 100 µm in (E). MTT, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide; RT-qPCR, reverse transcription quantitative polymerase chain reaction.