Model Of Cell Differentiation Research Articles

Mapping cells through time and space with moscot.

Single-cell genomic technologies enable the multimodal profiling of millions of cells across temporal and spatial dimensions. However, experimental limitations hinder the comprehensive measurement of cells under native temporal dynamics and in their native spatial tissue niche. Optimal transport has emerged as a powerful tool to address these constraints and has facilitated the recovery of the original cellular context1-4. Yet, most optimal transport applications are unable to incorporate multimodal information or scale to single-cell atlases. Here we introduce multi-omics single-cell optimal transport (moscot), a scalable framework for optimal transport in single-cell genomics that supports multimodality across all applications. We demonstrate the capability of moscot to efficiently reconstruct developmental trajectories of 1.7 million cells from mouse embryos across 20 time points. To illustrate the capability of moscot in space, we enrich spatial transcriptomic datasets by mapping multimodal information from single-cell profiles in a mouse liver sample and align multiple coronal sections of the mouse brain. We present moscot.spatiotemporal, an approach that leverages gene-expression data across both spatial and temporal dimensions to uncover the spatiotemporal dynamics of mouse embryogenesis. We also resolve endocrine-lineage relationships of delta and epsilon cells in a previously unpublished mouse, time-resolved pancreas development dataset using paired measurements of gene expression and chromatin accessibility. Our findings are confirmed through experimental validation of NEUROD2 as a regulator of epsilon progenitor cells in a model of human induced pluripotent stem cell islet cell differentiation. Moscot is available as open-source software, accompanied by extensive documentation.

SYSTEM VARIABLE REDUCTION AND GLOBAL SENSITIVITY ANALYSIS FOR A COMPLEX MODEL OF CANCER CELL DIFFERENTIATION

Model reduction aims to simplify complex models by decreasing the number of equations, variables, or parameters while preserving key characteristics. This approach enhances accessibility, comprehensibility, and computational efficiency, enabling a more focused analysis of relevant variables. In this study, we describe the reduction process of a population model that incorporates cancer cell differentiation and its interaction with the immune system, maintaining the fundamental dynamics and evolution of the original model. This led to a substantial reduction in variables and parameters, creating a more efficient model suitable for computational simulations, mathematical analysis, and quantitative understanding of population dynamics. Additionally, we performed a global sensitivity analysis of model parameters using the Sobol and eFast methods, revealing insights into differences and similarities in results from a biological perspective. Our findings emphasize the critical importance of understanding and controlling parameters related to the reproduction and death rates of differentiated cancer cells, as small variations in these parameters can have significant effects on model outcomes. This underscores the importance of thoroughly understanding these essential biological variables and processes in cancer treatment, as they have a significant impact on model outcomes and, consequently, on the development of more effective therapies.

Accurate isoform quantification by joint short- and long-read RNA-sequencing.

Accurate quantification of transcript isoforms is crucial for understanding gene regulation, functional diversity, and cellular behavior. Existing RNA sequencing methods have significant limitations: short-read (SR) sequencing provides high depth but struggles with isoform deconvolution, whereas long-read (LR) sequencing offers isoform resolution at the cost of lower depth, higher noise, and technical biases. Addressing this gap, we introduce Multi-Platform Aggregation and Quantification of Transcripts (MPAQT), a generative model that combines the complementary strengths of different sequencing platforms to achieve state-of-the-art isoform-resolved transcript quantification, as demonstrated by extensive simulations and experimental benchmarks. By applying MPAQT to an in vitro model of human embryonic stem cell differentiation into cortical neurons, followed by machine learning-based modeling of transcript abundances, we show that untranslated regions (UTRs) are major determinants of isoform proportion and exon usage; this effect is mediated through isoform-specific sequence features embedded in UTRs, which likely interact with RNA-binding proteins that modulate mRNA stability. These findings highlight MPAQT's potential to enhance our understanding of transcriptomic complexity and underline the role of splicing-independent post-transcriptional mechanisms in shaping the isoform and exon usage landscape of the cell.

Approximate Bayesian computation for inferring Waddington landscapes fromsingle-cell data.

Single-cell technologies allow us to gain insights into cellular processes at unprecedented resolution. In stem cell and developmental biology snapshot data allow us to characterize how the transcriptional states of cells change between successive cell types. Here, we show how approximate Bayesian computation (ABC) can be employed to calibrate mathematical models against single-cell data. In our simulation study, we demonstrate the pivotal role of the adequate choice of distance measures appropriate for single-cell data. We show that for good distance measures, notably optimal transport with the Sinkhorn divergence, we can infer parameters for mathematical models from simulated single-cell data. We show that the ABC posteriors can be used (i) to characterize parameter sensitivity and identify dependencies between different parameters and(ii) to construct representations of the Waddington or epigenetic landscape, which forms a popular and interpretable representation of the developmental dynamics. In summary, these results pave the way for fitting mechanistic models of stem cell differentiation to single-cell data.

Hopf-bifurcation analysis of a stage-structured population model of cell differentiation

A cell differentiation model with maturity structure in progenitor cells is described by a system of nonlinear ODEs coupled to a PDE. The work mainly discusses Hopf-bifurcation for the model when the maturation rate of progenitor cells only depends on the number of mature cells, and is a continuation of the previous work (Doumic et al., 2011). Using the methods of characteristics and a change in variable, the system can be transformed into one of state-dependent delay differential equations and then into constant delay differential equations. A qualitative analysis of the solutions is performed, which includes well-posedness, non-negativity, uniform boundedness and linearized stability. Furthermore, we conduct Hopf-bifurcation analysis by taking the maturation level of progenitor as the bifurcation parameter, which means that the levels of stem and mature cells may vary with persistent oscillations. A numerical analysis stresses the role of some important parameters on the stability and Hopf-bifurcation.

Abstract 254: Triggering head and neck cancer cell cornification leads to mucosa-like differentiation, chromatin remodeling, and loss of cell malignancy

Abstract Head and neck squamous cell carcinoma (HNSCC) is the 6th most common tumor disease worldwide with a death rate of about 50%. As mortality and morbidity of affected patients were not substantially improved in recent decades, new treatment options are urgently needed. HNSCCs that are negative for the human papillomavirus are characterized by areas of differentiated keratinized tissue. Dissecting the mechanisms regulating this terminal differentiation of HNSCC cells may unravel targets with high potential for anti-tumor therapy. Using primary tumor-initiating spheroid cells, we established a model of HNSCC cell differentiation by cornification and observed a deprivation of cell malignancy leading to the adhesion of spheroid cells, loss of single-cell cloning capacity, and diminished tumor-initiating potential in immunodeficient mice. Analysis of our differentiation model employing ATAC-seq, RNA-seq, and proteomics showed an increased accessibility of small promoter regions despite overall genome closure, activation of a wound healing-associated signaling program, and upregulation of the stress keratin 17 (KRT17) as well as cornification markers including SPRR3. These results suggest that the differentiation of HNSCC cells resembles the differentiation process in other stem cell-maintained tissue systems. Multi-marker immunofluorescence analysis of human tissue revealed a reversion of the role of KRT17 from a basal stem-cell marker in normal mucosa to an early differentiation marker in HNSCC tissue and dysplastic mucosa preceding cornification. This proposes KRT17 as potential biomarker for HNSCC prevention screening. Human tissue analysis identified distinct cell differentiation states shared between HNSCC tissue and normal mucosa that were detected in higher and lower differentiated tumor tissue of distinct anatomical sub-locations. Cornification was observed to be induced at the interface between vital tumor tissue and necrotic, immune-infiltrated areas in human HNSCCs, suggesting a promoting influence of pro-inflammatory stimuli on cell differentiation. Treatment of tumor spheroids with inflammatory mediators resulted in cell attachment and cornification, indicating a potential strategy to stop the self-renewal of HNSCC cells. Our study thus reveals that the targeted differentiation of HNSCC tumor-initiating cells could be used as a future therapy approach against squamous cell carcinomas of the head and neck and other tissues. Citation Format: Felix Oppel, Sarah Gendreizig, Laura Martinez-Ruiz, Javier Florido, Alba López-Rodríguez, Harkiren Pabla, Lakshna Loganathan, Leonie Hose, Philipp Kühnel, Pascal Schmidt, Matthias Schürmann, Judith M. Neumann, Flavian Viyof Ful, Lars Uwe Scholtz, Ingo Todt, Ligum Dina, Frank Brasch, Niehaus Karsten, Germaine Escames, Tobias Busche, Jörn Kalinowski, Peter Goon, Holger Sudhoff. Triggering head and neck cancer cell cornification leads to mucosa-like differentiation, chromatin remodeling, and loss of cell malignancy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 254.

An in vitro agent-based modelling approach to optimization of culture medium for generating muscle cells.

Methodologies for culturing muscle tissue are currently lacking in terms of quality and quantity of mature cells produced. We analyse images from in vitro experiments to quantify the effects of culture media composition on mouse-derived myoblast behaviour and myotube quality. Metrics of early indicators of cell quality were defined. Images of muscle cell differentiation reveal that altering culture media significantly affects quality indicators and myoblast migratory behaviours. To study the effects of early-stage cell behaviours on mature cell quality, metrics drawn from experimental images or inferred by approximate Bayesian computation (ABC) were applied as inputs to an agent-based model (ABM) of skeletal muscle cell differentiation with quality indicator metrics as outputs. Computational modelling was used to inform further in vitro experiments to predict the optimum media composition for culturing muscle cells. Our results suggest that myonuclei production in myotubes is inversely related to early-stage nuclei fusion index and that myonuclei density and spatial distribution are correlated with residence time of fusing myoblasts, the age at which myotube-myotube fusion ends and the repulsion force between myonuclei. Culture media with 5% serum was found to produce the optimum cell quality and to make muscle cells cultured in a neuron differentiation medium viable.

Mathematical model of irreversible cell differentiation under asynchronous division considering survival

Mathematical model of irreversible cell differentiation under asynchronous division considering survival

Selenium Deficiency Can Promote the Expression of VEGF and Inflammatory Factors in Cartilage Differentiation and Mediates Cartilage Injury.

Selenium plays a crucial role as a micronutrient, primarily exerting its biological functions through selenoproteins. It has been established that selenium deficiency adversely impacts cartilage development, leading to alterations in chondrocyte function. In regions with low selenium intake, endemic osteochondrosis has been documented, characterized by compromised growth plate and articular cartilage formation. Vascular endothelial growth factor (VEGF) stands out as a pivotal angiogenic factor, with elevated levels contributing significantly to vascular invasion into chondrocytes. This VEGF-mediated invasion serves as a key signal, prompting morphological changes in the growth plate and initiating cartilage remodeling. In animal models, the selenium deficiency group exhibited heightened levels of the cartilage damage marker matrix metalloproteinases 13 (MMP13). This resulted in articular cartilage degeneration, accompanied by a substantial increase in VEGF expression within the growth plate and articular cartilage, as compared to the normal group. In a chondrogenic progenitor cell (CPC) differentiation model, insufficient selenium induced chondrocyte damage and upregulated inflammatory factors such as inducible NO synthase (iNOS) and cyclooxygenase-2 (COX2). The selenium-deficient groups showed elevated expressions of VEGF, VEGFR2, MMP13, Collagen X, and Angiopoietin 1, accelerating the degradation of the extracellular matrix (ECM), which further promoted the development of cartilage-related diseases. Taken together, these findings provide novel insights for a better understanding of the role of low selenium in cartilage degeneration and angiogenesis. They shed light on the intricate influence of low selenium levels on the development of articular cartilage, emphasizing the interconnected pathways and processes involved.

Evolution of hierarchy and irreversibility in theoretical cell differentiation model.

The process of cell differentiation in multicellular organisms is characterized by hierarchy and irreversibility in many cases. However, the conditions and selection pressures that give rise to these characteristics remain poorly understood. By using a mathematical model, here we show that the network of differentiation potency (differentiation diagram) becomes necessarily hierarchical and irreversible by increasing the number of terminally differentiated states under certain conditions. The mechanisms generating these characteristics are clarified using geometry in the cell state space. The results demonstrate that the hierarchical organization and irreversibility can manifest independently of direct selection pressures associated with these characteristics, instead they appear to evolve as byproducts of selective forces favoring a diversity of differentiated cell types. The study also provides a new perspective on the structure of gene regulatory networks that produce hierarchical and irreversible differentiation diagrams. These results indicate some constraints on cell differentiation, which are expected to provide a starting point for theoretical discussion of the implicit limits and directions of evolution in multicellular organisms.

Optogenetic manipulation of BMP signaling to drive chondrogenic differentiation of hPSCs

Optogenetics is a rapidly advancing technology combining photochemical, optical, and synthetic biology to control cellular behavior. Together, sensitive light-responsive optogenetic tools and human pluripotent stem cell differentiation models have the potential to fine-tune differentiation and unpick the processes by which cell specification and tissue patterning are controlled by morphogens. We used an optogenetic bone morphogenetic protein (BMP) signaling system (optoBMP) to drive chondrogenic differentiation of human embryonic stem cells (hESCs). We engineered light-sensitive hESCs through CRISPR-Cas9-mediated integration of the optoBMP system into the AAVS1 locus. The activation of optoBMP with blue light, in lieu of BMP growth factors, resulted in the activation of BMP signaling mechanisms and upregulation of a chondrogenic phenotype, with significant transcriptional differences compared to cells in the dark. Furthermore, cells differentiated with light could form chondrogenic pellets consisting of a hyaline-like cartilaginous matrix. Our findings indicate the applicability of optogenetics for understanding human development and tissue engineering.

Dynamics of cell-type transition mediated by epigenetic modifications

Maintaining tissue homeostasis requires appropriate regulation of stem cell differentiation. The Waddington landscape posits that gene circuits in a cell form a potential landscape of different cell types, wherein cells follow attractors of the probability landscape to develop into distinct cell types. However, how adult stem cells achieve a delicate balance between self-renewal and differentiation remains unclear. We propose that random inheritance of epigenetic states plays a pivotal role in stem cell differentiation and present a hybrid model of stem cell differentiation induced by epigenetic modifications. Our comprehensive model integrates gene regulation networks, epigenetic state inheritance, and cell regeneration, encompassing multi-scale dynamics ranging from transcription regulation to cell population. Through model simulations, we demonstrate that random inheritance of epigenetic states during cell divisions can spontaneously induce cell differentiation, dedifferentiation, and transdifferentiation. Furthermore, we investigate the influences of interfering with epigenetic modifications and introducing additional transcription factors on the probabilities of dedifferentiation and transdifferentiation, revealing the underlying mechanism of cell reprogramming. This in silico model provides valuable insights into the intricate mechanism governing stem cell differentiation and cell reprogramming and offers a promising path to enhance the field of regenerative medicine.

Expression and electrophysiological characteristics of VGSC during mouse myoblasts differentiation

Voltage-gated sodium channels (VGSC) are essential for triggering and relaying action potentials (AP), which perform critical functions in a variety of physiological processes, such as controlling muscle contractions and facilitating the release of neurotransmitters. In this study, we used a mouse C2C12 cell differentiation model to study the molecular expression and channel dynamics of VGSC and to investigate the exact role of VGSC in the development of muscle regeneration. Immunofluorescence, Real-time quantitative polymerase chain reaction, Western blot, and whole-cell patch clamp were employed for this purpose in mouse myoblasts. The findings revealed an increase in intracellular sodium concentration, NaV1.4 gene expression, and protein expression with the progress of differentiation (days 0, 1, 3, 5 and 7). Furthermore, VGSC dynamics exhibit the following characteristics: ① The increase of sodium current (INa); ② The decrease in the activation threshold and the voltage trigger maximum of INa; ③ A positive shift in the steady-state inactivation curve; ④ The recovery of INa during repolarization is delayed, the activity-dependent decay rate of INa was accelerated, and the proportionate amount of the fraction of activated channels was reduced. Based on these results, it is postulated that the activation threshold of AP could be decreased, and the refractory period could be extended with the extension of differentiation duration, which may contribute to muscle contraction. Taken together, VGSC provides a theoretical and empirical basis for exploring potential targets for neuromuscular diseases and other therapeutic muscle regeneration dysfunctions.

γH2AX in mouse embryonic stem cells: Distribution during differentiation and following γ-irradiation

Phosphorylated histone H2AX (γH2AX) represents a sensitive molecular marker of DNA double-strand breaks (DSBs) and is implicated in stem cell biology. We established a model of mouse embryonic stem cell (mESC) differentiation and examined the dynamics of γH2AX foci during the process. Our results revealed high numbers of γH2AX foci in undifferentiated mESCs, decreasing as the cells differentiated towards the endothelial cell lineage. Notably, we observed two distinct patterns of γH2AX foci: the typical discrete γH2AX foci, which colocalize with the transcriptionally permissive chromatin mark H3K4me3, and the less well-characterized clustered γH2AX regions, which were only observed in intermediate progenitor cells. Next, we explored responses of mESCs to γ-radiation (137Cs). Following exposure to γ-radiation, mESCs showed a reduction in cell viability and increased γH2AX foci, indicative of radiosensitivity. Despite irradiation, surviving mESCs retained their differentiation potential. To further exemplify our findings, we investigated neural stem progenitor cells (NSPCs). Similar to mESCs, NSPCs displayed clustered γH2AX foci associated with progenitor cells and discrete γH2AX foci indicative of embryonic stem cells or differentiated cells. In conclusion, our findings demonstrate that γH2AX serves as a versatile marker of DSBs and may have a role as a biomarker in stem cell differentiation. The distinct patterns of γH2AX foci in differentiating mESCs and NSPCs provide valuable insights into DNA repair dynamics during differentiation, shedding light on the intricate balance between genomic integrity and cellular plasticity in stem cells. Finally, the clustered γH2AX foci observed in intermediate progenitor cells is an intriguing feature, requiring further exploration.

Single-cell transcriptomics identifies a WNT7A-FZD5 signaling axis that maintains fallopian tube stem cells in patient-derived organoids

The study of fallopian tube (FT) function in health and disease has been hampered by limited knowledge of FT stem cells and lack of invitro models of stem cell renewal and differentiation. Using optimized organoid culture conditions to address these limitations, we find that FT stem cell renewal is highly dependent on WNT/β-catenin signaling and engineer endogenous WNT/β-catenin signaling reporter organoids to biomark, isolate, and characterize these cells. Using functional approaches, as well as bulk and single-cell transcriptomics analyses, we show that an endogenous hormonally regulated WNT7A-FZD5 signaling axis is critical for stem cell renewal and that WNT/β-catenin pathway-activated cells form a distinct transcriptomic cluster of FT cells enriched in extracellular matrix (ECM) remodeling and integrin signaling pathways. Overall, we provide a deep characterization of FT stem cells and their molecular requirements for self-renewal, paving the way for mechanistic work investigating the role of stem cells in FT health and disease.

In Situ Spatial Reconstruction of Distinct Normal and Pathological Cell Populations Within the Human Adrenal Gland.

The human adrenal gland consists of concentrically organized, functionally distinct regions responsible for hormone production. Dysregulation of adrenocortical cell differentiation alters the proportion and organization of the functional zones of the adrenal cortex leading to disease. Current models of adrenocortical cell differentiation are based on mouse studies, but there are known organizational and functional differences between human and mouse adrenal glands. This study aimed to investigate the centripetal differentiation model in the human adrenal cortex and characterize aldosterone-producing micronodules (APMs) to better understand adrenal diseases such as primary aldosteronism. We applied spatially resolved in situ transcriptomics to human adrenal tissue sections from 2 individuals and identified distinct cell populations and their positional relationships. The results supported the centripetal differentiation model in humans, with cells progressing from the outer capsule to the zona glomerulosa, zona fasciculata, and zona reticularis. Additionally, we characterized 2 APMs in a 72-year-old woman. Comparison with earlier APM transcriptomes indicated a subset of core genes, but also heterogeneity between APMs. The findings contribute to our understanding of normal and pathological cellular differentiation in the human adrenal cortex.

Quercetin-3-O-β-d-glucuronide in the Nuciferine Leaf Polyphenol Extract Promotes Neurogenesis Involving the Upregulation of the Tropomyosin Receptor Kinase (Trk) Receptor and AKT/Phosphoinositide 3-Kinase Signaling Pathway.

Neurogenesis is crucial during the human lifespan for the maintenance of synaptic plasticity and normal function. The impairment of hippocampal neurogenesis in adults may lead to neurodegenerative disease, such as Alzheimer's disease. Miquelianin (quercetin-3-O-β-d-glucuronide, Q3GA) is a constituent of the nuciferine leaf polyphenol extract (NLPE), and it has protective effects against neurodegeneration. In this study, we examined the effect of the NLPE on neurogenesis and the mechanisms underlying Q3GA on neurogenesis. We fed 24-week-old male C57BL/6 mice with 0.1 or 0.25% NLPE for 2 weeks. NLPE treatment increased small spindle-shaped stem cell numbers in the subgranular zone and the number of doublecortin (DCX)- and neuron-specific nuclear protein (NeuN)-expressing neurons. HT22, a hippocampal cell line, treated with Q3GA revealed significant neurite growth and upregulated TrkR and PI3K/Akt levels. The evidence from a model of retinoic acid-induced SH-SY5Y cell differentiation showed that Q3GA or NLPE increases neurite growth significantly. Taken together, the NLPE containing Q3GA to promote neurogenesis involving the upregulation of TrkR and the PI3K/Akt signaling pathway might be potentiated as an alternative strategy for the treatment of neurodegeneration.

Scalable inference of cell differentiation networks in gene therapy clonal tracking studies of haematopoiesis.

Investigating cell differentiation under a genetic disorder offers the potential for improving current gene therapy strategies. Clonal tracking provides a basis for mathematical modelling of population stem cell dynamics that sustain the blood cell formation, a process known as haematopoiesis. However, many clonal tracking protocols rely on a subset of cell types for the characterization of the stem cell output, and the data generated are subject to measurement errors and noise. We propose a stochastic framework to infer dynamic models of cell differentiation from clonal tracking data. A state-space formulation combines a stochastic quasi-reaction network, describing cell differentiation, with a Gaussian measurement model accounting for data errors and noise. We developed an inference algorithm based on an extended Kalman filter, a nonlinear optimization, and a Rauch-Tung-Striebelsmoother. Simulations show that our proposed method outperforms the state-of-the-art and scales to complex structures of cell differentiations in terms of nodes size and network depth. The application of our method to five in vivo gene therapy studies reveals different dynamics of cell differentiation. Our tool can provide statistical support to biologists and clinicians to better understand cell differentiation and haematopoietic reconstitution after a gene therapy treatment. The equations of the state-space model can be modified to infer other dynamics besides cell differentiation. The stochastic framework is implemented in the R package Karen which is available for download at https://cran.r-project.org/package=Karen. The code that supports the findings of this study is openly available at https://github.com/delcore-luca/CellDifferentiationNetworks.

Novel In Vitro Models for Cell Differentiation and Drug Transport Studies of the Human Intestine.

The most common in vitro model for absorption, distribution, metabolism, and excretion (ADME) purposes is currently the Caco-2 cell line. However, clear differences in gene and protein expression towards the small intestine and an, at best, fair prediction accuracy of intestinal drug absorption restrict the usefulness of a model for intestinal epithelial cells. To overcome these limitations, we evaluated a panel of low-passaged patient-derived colorectal cancer cell lines of the HROC collection concerning similarities to small intestinal epithelial cells and their potential to predict intestinal drug absorption. After initial screening of a larger panel, ten cell lines with confluent outgrowth and long-lasting barrier-forming potential were further characterized in close detail. Tight junctional complexes and microvilli structures were detected in all lines, anda higher degree of differentiation was observed in 5/10 cell lines. All lines expressed multiple transporter molecules, with the expression levels in three lines being close to those of small intestinal epithelial cells. Compared with the Caco-2 model, three HROC lines demonstrated both higher similarity to jejunal epithelial tissue cells and higher regulatory potential of relevant drug transporters. In summary, these lines would be better-suited human small intestinal epithelium models for basic and translational research, especially for ADME studies.

Dulaglutide Protects Mice against Diabetic Sarcopenia-Mediated Muscle Injury by Inhibiting Inflammation and Regulating the Differentiation of Myoblasts.

Type 2 diabetes mellitus increases the risk of sarcopenia, which is characterized by decreased muscle mass, strength, and function. However, there are no effective drugs to treat diabetic sarcopenia, and its underlying mechanism remains unknown. Here, we aimed to determine whether the GLP-1 receptor agonist (GLP-1RA) dulaglutide (Dul) affects the progression of diabetic sarcopenia. db/db mice were injected intraperitoneally with 0.6 mg/kg dulaglutide for 10 weeks. Mouse muscle tissues were then pathologically evaluated and stained with F4/80 or MPO to detect macrophages and neutrophils, respectively. In addition, inflammatory factors and FNDC5 in the muscle tissues were detected using qRT-PCR. Moreover, C2C12 cells were induced to enable their differentiation into skeletal muscle cells, and muscle factor levels were then detected. Furthermore, changes in muscle factor levels were detected at various glucose concentrations (11 mM, 22 mM, and 44 mM). In vivo, dulaglutide alleviated muscle tissue injury; reduced levels of the inflammatory factors, IL-1β, IL-6, CCL2, and CXCL1; and reversed the level of FNDC5 in the muscle tissues of db/db mice. In vitro, a C2C12 cell differentiation model was established through the observation of cell morphology and determination of myokine levels. Upon stimulation with high glucose, the differentiation of C2C12 cells was inhibited. Dulaglutide improved this inhibitory state by upregulating the levels of both FNDC5 mRNA and protein. Treatment with the GLP-1RA dulaglutide protects db/db mice against skeletal muscle injury by inhibiting inflammation and regulating the differentiation of myoblasts. High glucose inhibited the differentiation of C2C12 cells and decreased the mRNA and protein levels of myokines. Dulaglutide could reverse the differentiation state induced in C2C12 cells by high glucose.