Attosecond delays in X-ray molecular ionization.

The photoelectric effect is not truly instantaneous but exhibits attosecond delays that can reveal complex molecular dynamics1-7. Sub-femtosecond-duration light pulses provide the requisite tools to resolve the dynamics of photoionization8-12. Accordingly, the past decade has produced a large volume of work on photoionization delays following single-photon absorption of an extreme ultraviolet photon. However, the measurement of time-resolved core-level photoionization remained out of reach. The required X-ray photon energies needed for core-level photoionization were not available with attosecond tabletop sources. Here we report measurements of the X-ray photoemission delay of core-level electrons, with unexpectedly large delays, ranging up to 700 as in NO near the oxygen K-shell threshold. These measurements exploit attosecond soft X-ray pulses from a free-electron laser to scan across the entire region near the K-shell threshold. Furthermore, we find that the delay spectrum is richly modulated, suggesting several contributions, including transient trapping of the photoelectron owing to shape resonances, collisions with the Auger-Meitner electron that is emitted in the rapid non-radiative relaxation of the molecule and multi-electron scattering effects. The results demonstrate how X-ray attosecond experiments, supported by comprehensive theoretical modelling, can unravel the complex correlated dynamics of core-level photoionization.

Minimizing the diffusivity difference between vacancies and interstitials in multi-principal element alloys.

Interstitial atoms usually diffuse much faster than vacancies, which is often the root cause for the ineffective recombination of point defects in metals under irradiation. Here, via ab initio modeling of single-defect diffusion behavior in the equiatomic NiCoCrFe(Pd) alloy, we demonstrate an alloy design strategy that can reduce the diffusivity difference between the two types of point defects. The two diffusivities become almost equal after substituting the NiCoCrFe base alloy with Pd. The underlying mechanism is that Pd, with a much larger atomic size (hence larger compressibility) than the rest of the constituents, not only heightens the activation energy barrier (Ea) for interstitial motion by narrowing the diffusion channels but simultaneously also reduces Ea for vacancies due to less energy penalty required for bond length change between the initial and the saddle states. Our findings have a broad implication that the dynamics of point defects can be manipulated by taking advantage of the atomic size disparity, to facilitate point-defect annihilation that suppresses void formation and swelling, thereby improving radiation tolerance.

A microbial knowledge graph-based deep learning model for predicting candidate microbes for target hosts.

Predicting interactions between microbes and hosts plays critical roles in microbiome population genetics and microbial ecology and evolution. How to systematically characterize the sophisticated mechanisms and signal interplay between microbes and hosts is a significant challenge for global health risks. Identifying microbe-host interactions (MHIs) can not only provide helpful insights into their fundamental regulatory mechanisms, but also facilitate the development of targeted therapies for microbial infections. In recent years, computational methods have become an appealing alternative due to the high risk and cost of wet-lab experiments. Therefore, in this study, we utilized rich microbial metagenomic information to construct a novel heterogeneous microbial network (HMN)-based model named KGVHI to predict candidate microbes for target hosts. Specifically, KGVHI first built a HMN by integrating human proteins, viruses and pathogenic bacteria with their biological attributes. Then KGVHI adopted a knowledge graph embedding strategy to capture the global topological structure information of the whole network. A natural language processing algorithm is used to extract the local biological attribute information from the nodes in HMN. Finally, we combined the local and global information and fed it into a blended deep neural network (DNN) for training and prediction. Compared to state-of-the-art methods, the comprehensive experimental results show that our model can obtain excellent results on the corresponding three MHI datasets. Furthermore, we also conducted two pathogenic bacteria case studies to further indicate that KGVHI has excellent predictive capabilities for potential MHI pairs.

Multi-Omics Profiling Identifies Microglial Annexin A2 as a Key Mediator of NF-κB Pro-inflammatory Signaling in Ischemic Reperfusion Injury.

Cerebral stroke is one of the leading causes of mortality and disability worldwide. Restoring the cerebral circulation following a period of occlusion and subsequent tissue oxygenation leads to reperfusion injury. Cerebral ischemic reperfusion (I/R) injury triggers immune and inflammatory responses, apoptosis, neuronal damage, and even death. However, the cellular function and molecular mechanisms underlying cerebral I/R-induced neuronal injury are incompletely understood. By integrating proteomic, phosphoproteomic, and transcriptomic profiling in mouse hippocampi after cerebral I/R, we revealed that the differentially expressed genes and proteins mainly fall into several immune inflammatory response-related pathways. We identified that Annexin 2 (Anxa2) was exclusively upregulated in microglial cells in response to cerebral I/R in vivo and oxygen-glucose deprivation and reoxygenation (OGD/R) in vitro. RNA-seq analysis revealed a critical role of Anxa2 in the expression of inflammation-related genes in microglia via the NF-κB signaling. Mechanistically, microglial Anxa2 is required for nuclear translocation of the p65 subunit of NF-κB and its transcriptional activity upon OGD/R in BV2 microglial cells. Anxa2 knockdown inhibited the OGD/R-induced microglia activation and markedly reduced the expression of pro-inflammatory factors, including TNF-α, IL-1ß, and IL-6. Interestingly, conditional medium derived from Anxa2-depleted BV2 cell cultures with OGD/R treatment alleviated neuronal death in vitro. Altogether, our findings revealed that microglia Anxa2 plays a critical role in I/R injury by regulating NF-κB inflammatory responses in a non-cell-autonomous manner, which might be a potential target for the neuroprotection against cerebral I/R injury.

NUDT16 regulates CtIP PARylation to dictate homologous recombination repair.

CtIP initiates DNA end resection and mediates homologous recombination (HR) repair. However, the underlying mechanisms of CtIP regulation and how the control of its regulation affects DNA repair remain incompletely characterized. In this study, NUDT16 loss decreases CtIP protein levels and impairs CtIP recruitment to double-strand breaks (DSBs). Furthermore, overexpression of a catalytically inactive NUDT16 mutant is unable to rescue decreased CtIP protein and impaired CtIP recruitment to DSBs. In addition, we identified a novel posttranslational modification of CtIP by ADP-ribosylation that is targeted by a PAR-binding E3 ubiquitin ligase, RNF146, leading to CtIP ubiquitination and degradation. These data suggest that the hydrolase activity of NUDT16 plays a major role in controlling CtIP protein levels. Notably, ADP-ribosylation of CtIP is required for its interaction with NUDT16, its localization at DSBs, and for HR repair. Interestingly, NUDT16 can also be ADP-ribosylated. The ADP-ribosylated NUDT16 is critical for CtIP protein stability, CtIP recruitment to DSBs, and HR repair in response to DNA damage. In summary, we demonstrate that NUDT16 and its PARylation regulate CtIP stability and CtIP recruitment to DSBs, providing new insights into our understanding of the regulation of CtIP-mediated DNA end resection in the HR repair pathway.

MdMYB44-like positively regulates salt and drought tolerance via the MdPYL8-MdPP2CA module in apple.

Abscisic acid (ABA) is involved in salt and drought stress responses, but the underlying molecular mechanism remains unclear. Here, we demonstrated that the overexpression of MdMYB44-like, an R2R3-MYB transcription factor, significantly increases the salt and drought tolerance of transgenic apples and Arabidopsis. MdMYB44-like inhibits the transcription of MdPP2CA, which encodes a type 2C protein phosphatase that acts as a negative regulator in the ABA response, thereby enhancing ABA signaling-mediated salt and drought tolerance. Furthermore, we found that MdMYB44-like and MdPYL8, an ABA receptor, form a protein complex that further enhances the transcriptional inhibition of the MdPP2CA promoter by MdMYB44-like. Significantly, we discovered that MdPP2CA can interfere with the physical association between MdMYB44-like and MdPYL8 in the presence of ABA, partially blocking the inhibitory effect of the MdMYB44-like-MdPYL8 complex on the MdPP2CA promoter. Thus, MdMYB44-like, MdPYL8, and MdPP2CA form a regulatory loop that tightly modulates ABA signaling homeostasis under salt and drought stress. Our data reveal that MdMYB44-like precisely modulates ABA-mediated salt and drought tolerance in apples through the MdPYL8-MdPP2CA module.

GhHAM regulates GoPGF-dependent gland development and contributes to broad-spectrum pest resistance in cotton.

Cotton is a globally cultivated crop, producing 87% of the natural fiber used in the global textile industry. The pigment glands, unique to cotton and its relatives, serve as a defense structure against pests and pathogens. However, the molecular mechanism underlying gland formation and the specific role of pigment glands in cotton's pest defense are still not well understood. In this study, we cloned a gland-related transcription factor GhHAM and generated the GhHAM knockout mutant using CRISPR/Cas9. Phenotypic observations, transcriptome analysis, and promoter-binding experiments revealed that GhHAM binds to the promoter of GoPGF, regulating pigment gland formation in cotton's multiple organs via the GoPGF-GhJUB1 module. The knockout of GhHAM significantly reduced gossypol production and increased cotton's susceptibility to pests in the field. Feeding assays demonstrated that more than 80% of the cotton bollworm larvae preferred ghham over the wild type. Furthermore, the ghham mutants displayed shorter cell length and decreased gibberellins (GA) production in the stem. Exogenous application of GA3 restored stem cell elongation but not gland formation, thereby indicating that GhHAM controls gland morphogenesis independently of GA. Our study sheds light on the functional differentiation of HAM proteins among plant species, highlights the significant role of pigment glands in influencing pest feeding preference, and provides a theoretical basis for breeding pest-resistant cotton varieties to address the challenges posed by frequent outbreaks of pests.

Characteristics and mechanisms of T-cell senescence: A potential target for cancer immunotherapy.

Immunosenescence, the aging of the immune system, leads to functional deficiencies, particularly in T cells, which undergo significant changes. While numerous studies have investigated age-related T-cell phenotypes in healthy aging, senescent T cells have also been observed in younger populations during pathological conditions like cancer. This review summarizes the recent advancements in age-associated alterations and markers of T cells, mechanisms, and the relationship between senescent T cells and the tumor microenvironment. We also discuss potential strategies for targeting senescent T cells to prevent age-related diseases and enhance tumor immunotherapy efficacy.

DDN3.0: determining significant rewiring of biological network structure with differential dependency networks.

MOTIVATION: Complex diseases are often caused and characterized by misregulation of multiple biological pathways. Differential network analysis aims to detect significant rewiring of biological network structures under different conditions and has become an important tool for understanding the molecular etiology of disease progression and therapeutic response. With few exceptions, most existing differential network analysis tools perform differential tests on separately learned network structures that are computationally expensive and prone to collapse when grouped samples are limited or less consistent. RESULTS: We previously developed an accurate differential network analysis method-differential dependency networks (DDN), that enables joint learning of common and rewired network structures under different conditions. We now introduce the DDN3.0 tool that improves this framework with three new and highly efficient algorithms, namely, unbiased model estimation with a weighted error measure applicable to imbalance sample groups, multiple acceleration strategies to improve learning efficiency, and data-driven determination of proper hyperparameters. The comparative experimental results obtained from both realistic simulations and case studies show that DDN3.0 can help biologists more accurately identify, in a study-specific and often unknown conserved regulatory circuitry, a network of significantly rewired molecular players potentially responsible for phenotypic transitions. AVAILABILITY AND IMPLEMENTATION: The Python package of DDN3.0 is freely available at https://github.com/cbil-vt/DDN3. A user's guide and a vignette are provided at https://ddn-30.readthedocs.io/.

CAM3.0: determining cell type composition and expression from bulk tissues with fully unsupervised deconvolution.

MOTIVATION: Complex tissues are dynamic ecosystems consisting of molecularly distinct yet interacting cell types. Computational deconvolution aims to dissect bulk tissue data into cell type compositions and cell-specific expressions. With few exceptions, most existing deconvolution tools exploit supervised approaches requiring various types of references that may be unreliable or even unavailable for specific tissue microenvironments. RESULTS: We previously developed a fully unsupervised deconvolution method-Convex Analysis of Mixtures (CAM), that enables estimation of cell type composition and expression from bulk tissues. We now introduce CAM3.0 tool that improves this framework with three new and highly efficient algorithms, namely, radius-fixed clustering to identify reliable markers, linear programming to detect an initial scatter simplex, and a smart floating search for the optimum latent variable model. The comparative experimental results obtained from both realistic simulations and case studies show that the CAM3.0 tool can help biologists more accurately identify known or novel cell markers, determine cell proportions, and estimate cell-specific expressions, complementing the existing tools particularly when study- or datatype-specific references are unreliable or unavailable. AVAILABILITY AND IMPLEMENTATION: The open-source R Scripts of CAM3.0 is freely available at https://github.com/ChiungTingWu/CAM3/(https://github.com/Bioconductor/Contributions/issues/3205). A user's guide and a vignette are provided.

A nuclease-dead Cas9-derived tool represses target gene expression.

Manipulation of gene expression is central to understanding gene function, engineering cell behavior, and altering biological traits according to production demands. Nuclease-dead Cas9 (dCas9), a variant of active Cas9, offers a versatile platform for the precise control of genome function without DNA cleavage. Notably, however, an effective and universal dCas9-based transcriptional repression system remains unavailable in plants. The noncanonical histone acetyltransferase TENDRIL-LESS (CsTEN) is responsible for chromatin loosening and histone modification in cucumber (Cucumis sativus). In this study, we engineered a gene regulation tool by fusing TEN and its truncated proteins with dCas9. The full-length dCas9-TEN protein substantially repressed gene expression, with the N-terminal domain identified as the core repression domain. We subsequently validated the specificity and efficacy of this system through both transient infection and genetic transformation in cucumber and Arabidopsis (Arabidopsis thaliana). The electrophoretic mobility shift assay (EMSA) revealed the ability of the N-terminal domain of TEN to bind to chromatin, which may promote target binding of the dCas9 complex and enhance the transcriptional repression effect. Our tool enriches the arsenal of genetic regulation tools available for precision breeding in crops.

A genome-wide association study identifies candidate genes for sleep disturbances in depressed individuals.

OBJECTIVE: This study aimed to identify candidate loci and genes related to sleep disturbances in depressed individuals and clarify the co-occurrence of sleep disturbances and depression from the genetic perspective. METHODS: The study subjects (including 58,256 self-reported depressed individuals and 6,576 participants with PHQ-9 score ≥ 10, respectively) were collected from the UK Biobank, which were determined based on the Patient Health Questionnaire (PHQ-9) and self-reported depression status, respectively. Sleep related traits included chronotype, insomnia, snoring and daytime dozing. Genome-wide association studies (GWASs) of sleep related traits in depressed individuals were conducted by PLINK 2.0 adjusting age, sex, Townsend deprivation index and 10 principal components as covariates. The CAUSALdb database was used to explore the mental traits associated with the candidate genes identified by the GWAS. RESULTS: GWAS detected 15 loci significantly associated with chronotype in the subjects with self-reported depression, such as rs12736689 at RNASEL (P = 1.00 × 10- 09), rs509476 at RGS16 (P = 1.58 × 10- 09) and rs1006751 at RFX4 (P = 1.54 × 10- 08). 9 candidate loci were identified in the subjects with PHQ-9 ≥ 10, of which 2 loci were associated with insomnia such as rs115379847 at EVC2 (P = 3.50 × 10- 08), and 7 loci were associated with daytime dozing, such as rs140876133 at SMYD3 (P = 3.88 × 10- 08) and rs139156969 at ROBO2 (P = 3.58 × 10- 08). Multiple identified genes, such as RNASEL, RGS16, RFX4 and ROBO2 were reported to be associated with chronotype, depression or cognition in previous studies. CONCLUSION: Our study identified several candidate genes related to sleep disturbances in depressed individuals, which provided new clues for understanding the biological mechanism underlying the co-occurrence of depression and sleep disorders.

Multi-omics reveals the role of MCM2 and hnRNP K phosphorylation in mouse renal aging through genomic instability.

The process of aging is characterized by structural degeneration and functional decline, as well as diminished adaptability and resistance. The aging kidney exhibits a variety of structural and functional impairments. In aging mice, thinning and graying of fur were observed, along with a significant increase in kidney indices compared to young mice. Biochemical indicators revealed elevated levels of creatinine, urea nitrogen and serum uric acid, suggesting impaired kidney function. Histological analysis unveiled glomerular enlargement and sclerosis, severe hyaline degeneration, capillary occlusion, lymphocyte infiltration, tubular and glomerular fibrosis, and increased collagen deposition. Observations under electron microscopy showed thickened basement membranes, altered foot processes, and increased mesangium and mesangial matrix. Molecular marker analysis indicated upregulation of aging-related ß-galactosidase, p16-INK4A, and the DNA damage marker γH2AX in the kidneys of aged mice. In metabolomics, a total of 62 significantly different metabolites were identified, and 10 pathways were enriched. We propose that citrulline, dopamine, and indoxyl sulfate have the potential to serve as markers of kidney damage related to aging in the future. Phosphoproteomics analysis identified 6656 phosphosites across 1555 proteins, annotated to 62 pathways, and indicated increased phosphorylation at the Ser27 site of Minichromosome maintenance complex component 2 (Mcm2) and decreased at the Ser284 site of heterogeneous nuclear ribonucleoprotein K (hnRNP K), with these modifications being confirmed by western blotting. The phosphorylation changes in these molecules may contribute to aging by affecting genome stability. Eleven common pathways were detected in both omics, including arginine biosynthesis, purine metabolism and biosynthesis of unsaturated fatty acids, etc., which are closely associated with aging and renal insufficiency.

Bioinspired 2D nanofluidic membranes for energy applications.

Bioinspired two-dimensional (2D) nanofluidic membranes have been explored for the creation of high-performance ion transport systems that can mimic the delicate transport functions of living organisms. Advanced energy devices made from these membranes show excellent energy storage and conversion capabilities. Further research and development in this area are essential to unlock the full potential of energy devices and facilitate the development of high-performance equipment toward real-world applications and a sustainable future. However, there has been minimal review and summarization of 2D nanofluidic membranes in recent years. Thus, it is necessary to carry out an extensive review to provide a survey library for researchers in related fields. In this review, the classification and the raw materials that are used to construct 2D nanofluidic membranes are first presented. Second, the top-down and bottom-up methods for constructing 2D membranes are introduced. Next, the applications of bioinspired 2D membranes in osmotic energy, hydraulic energy, mechanical energy, photoelectric conversion, lithium batteries, and flow batteries are discussed in detail. Finally, the opportunities and challenges that 2D nanofluidic membranes are likely to face in the future are envisioned. This review aims to provide a broad knowledge base for constructing high-performance bioinspired 2D nanofluidic membranes for advanced energy applications.

Interlayer Charge Transfer Induced Electrical Behavior Transition in 1D AgI@sSWCNT van der Waals Heterostructures.

The emergence of one-dimensional van der Waals heterostructures (1D vdWHs) opens up potential fields with unique properties, but precise synthesis remains a challenge. The utilization of mixed conductive types of carbon nanotubes as templates has imposed restrictions on the investigation of the electrical behavior and interlayer interaction of 1D vdWHs. In this study, we efficiently encapsulated silver iodide in high-purity semiconducting single-walled carbon nanotubes (sSWCNTs), forming 1D AgI@sSWCNT vdWHs. We characterized the semiconductor-metal transition and increased the carrier concentration of individual AgI@sSWCNTs via sensitive dielectric force microscopy and confirmed the results through electrical device tests. The electrical behavior transition was attributed to an interlayer charge transfer, as demonstrated by Kelvin probe force microscopy. Furthermore, we showed that this method of synthesizing 1D heterostructures can be extended to other metal halides. This work opens the door for the further exploration of the electrical properties of 1D vdWHs.

Analysis of secreted small extracellular vesicles from activated human microglial cell lines reveals distinct pro- and anti-inflammatory proteomic profiles.

Microglia are a specialized population of innate immune cells located in the central nervous system. In response to physiological and pathological changes in their microenvironment, microglia can polarize into pro-inflammatory or anti-inflammatory phenotypes. A dysregulation in the pro-/anti-inflammatory balance is associated with many pathophysiological changes in the brain and nervous system. Therefore, the balance between microglia pro-/anti-inflammatory polarization can be a potential biomarker for the various brain pathologies. A non-invasive method of detecting microglia polarization in patients would have promising clinical applications. Here, we perform proteomic analysis of small extracellular vesicles (sEVs) derived from microglia cells to identify sEVs biomarkers indicative of pro-inflammatory and anti-inflammatory phenotypic changes. sEVs were isolated from microglia cell lines under different inflammatory conditions and analyzed by proteomics by liquid chromatography with mass spectrometry. Our findings provide the potential roles of sEVs that could be related to the pathogenesis of various brain diseases.

A novel microbe-drug association prediction model based on graph attention networks and bilayer random forest.

BACKGROUND: In recent years, the extensive use of drugs and antibiotics has led to increasing microbial resistance. Therefore, it becomes crucial to explore deep connections between drugs and microbes. However, traditional biological experiments are very expensive and time-consuming. Therefore, it is meaningful to develop efficient computational models to forecast potential microbe-drug associations. RESULTS: In this manuscript, we proposed a novel prediction model called GARFMDA by combining graph attention networks and bilayer random forest to infer probable microbe-drug correlations. In GARFMDA, through integrating different microbe-drug-disease correlation indices, we constructed two different microbe-drug networks first. And then, based on multiple measures of similarity, we constructed a unique feature matrix for drugs and microbes respectively. Next, we fed these newly-obtained microbe-drug networks together with feature matrices into the graph attention network to extract the low-dimensional feature representations for drugs and microbes separately. Thereafter, these low-dimensional feature representations, along with the feature matrices, would be further inputted into the first layer of the Bilayer random forest model to obtain the contribution values of all features. And then, after removing features with low contribution values, these contribution values would be fed into the second layer of the Bilayer random forest to detect potential links between microbes and drugs. CONCLUSIONS: Experimental results and case studies show that GARFMDA can achieve better prediction performance than state-of-the-art approaches, which means that GARFMDA may be a useful tool in the field of microbe-drug association prediction in the future. Besides, the source code of GARFMDA is available at https://github.com/KuangHaiYue/GARFMDA.git.

Amentoflavone reverses epithelial-mesenchymal transition in hepatocellular carcinoma cells by targeting p53 signalling pathway axis.

Epithelial-mesenchymal transition (EMT) and its reversal process are important potential mechanisms in the development of HCC. Selaginella doederleinii Hieron is widely used in Traditional Chinese Medicine for the treatment of various tumours and Amentoflavone is its main active ingredient. This study investigates the mechanism of action of Amentoflavone on EMT in hepatocellular carcinoma from the perspective of bioinformatics and network pharmacology. Bioinformatics was used to screen Amentoflavone-regulated EMT genes that are closely related to the prognosis of HCC, and a molecular prediction model was established to assess the prognosis of HCC. The network pharmacology was used to predict the pathway axis regulated by Amentoflavone. Molecular docking of Amentoflavone with corresponding targets was performed. Detection and evaluation of the effects of Amentoflavone on cell proliferation, migration, invasion and apoptosis by CCK-8 kit, wound healing assay, Transwell assay and annexin V-FITC/propidium iodide staining. Eventually three core genes were screened, inculding NR1I2, CDK1 and CHEK1. A total of 590 GO enrichment entries were obtained, and five enrichment results were obtained by KEGG pathway analysis. Genes were mainly enriched in the p53 signalling pathway. The outcomes derived from both the wound healing assay and Transwell assay demonstrated significant inhibition of migration and invasion in HCC cells upon exposure to different concentrations of Amentoflavone. The results of Annexin V-FITC/PI staining assay showed that different concentrations of Amentoflavone induces apoptosis in HCC cells. This study revealed that the mechanism of Amentoflavone reverses EMT in hepatocellular carcinoma, possibly by inhibiting the expression of core genes and blocking the p53 signalling pathway axis to inhibit the migration and invasion of HCC cells.

Chondroitin polymerizing factor promotes development and progression of colorectal cancer via facilitating transcription of VEGFB.

Colorectal cancer (CRC) is a highly prevalent malignancy affecting the digestive system on a global scale. This study aimed to explore the previously unexplored role of CHPF in the progression of CRC. Our results revealed a significant upregulation of CHPF expression in CRC tumour tissues compared to normal tissues, with its levels correlating with tumour malignancy. In vitro experiments using CRC cell lines demonstrated that inhibiting CHPF expression suppressed cell proliferation, colony formation and cell migration, while promoting apoptosis. Conversely, overexpressing CHPF had the opposite effect. Additionally, our xenograft models in mice confirmed the inhibitory impact of CHPF knockdown on CRC progression using various cell models. Mechanistic investigations unveiled that CHPF may enhance VEGFB expression through E2F1-mediated transcription. Functionally, suppressing VEGFB expression successfully mitigated the oncogenic effects induced by CHPF overexpression. Collectively, these findings suggest that CHPF may act as a tumour promoter in CRC, operating in a VEGFB-dependent manner and could be a potential target for therapeutic interventions in CRC treatment.

circUSP13 facilitates the fast-to-slow myofiber shift via the MAPK/ERK signaling pathway in goat skeletal muscles.

Understanding how skeletal muscle fiber proportions are regulated is essential for understanding muscle function and improving the quality of mutton. While circular RNA (circRNA) has a critical function in myofiber type transformation, the specific mechanisms are not yet fully understood. Prior evidence indicates that circular ubiquitin-specific peptidase 13 (circUSP13) can promote myoblast differentiation by acting as a ceRNA, but its potential role in myofiber switching is still unknown. Herein, we found that circUSP13 enhanced slow myosin heavy chain (MyHC-slow) and suppressed MyHC-fast expression in goat primary myoblasts (GPMs). Meanwhile, circUSP13 evidently enhanced the remodeling of the mitochondrial network while inhibiting the autophagy of GPMs. We obtained fast-dominated myofibers, via treatment with rotenone, and further demonstrated the positive role of circUSP13 in the fast-to-slow transition. Mechanistically, activation of the mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathway significantly impaired the slow-to-fast shift in fully differentiated myotubes, which was restored by circUSP13 or IGF1 overexpression. In conclusion, circUSP13 promoted the fast-to-slow myofiber type transition through MAPK/ERK signaling in goat skeletal muscle. These findings provide novel insights into the role of circUSP13 in myofiber type transition and contribute to a better understanding of the genetic mechanisms underlying meat quality.