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During follicular development, changes in the composition of the follicular fluid are synchronized with the development of oocytes. Our aim was to screen the key factors affecting oocyte maturation and optimize the in vitro culture protocol by understanding the changes of proteins and metabolites in follicular fluid. Follicles are divided into three groups according to their diameter (small follicle fluid (SFF): 10 mm < d < 20 mm; medium follicle fluid (MFF): 20 mm < d < 30 mm; large follicle fluid (LFF): 30 mm < d). Proteins and metabolites from the follicular fluid were analyzed by mass spectrometry. The results showed that: in LFF vs MFF, 20 differential abundant protein (DAP) and 88 differential abundant metabolites (DAM) were screened out; In SFF vs MFF, 3 DAPs and 65 DAMs were screened out; In MFF vs SFF, 24 DAPs and 35 DAMs were screened out. The analysis of differential proteins and metabolites showed that glycerophosphate hydrolysis decreased during follicular development, and proteins played a major role in metabolism and binding. In addition, DAMs and DAPs are co-enriched in the "linoleic acid metabolism" pathway. Combinatorial analysis reveals the dynamic profile of follicular fluid during follicular development and provides fundation for further exploring the function of follicular fluid in Mongolian horse.
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Líquido Folicular , Metaboloma , Folículo Ovárico , Proteoma , Líquido Folicular/metabolismo , Animales , Caballos , Proteoma/metabolismo , Proteoma/análisis , Folículo Ovárico/metabolismo , Folículo Ovárico/crecimiento & desarrollo , Femenino , Metabolómica/métodos , Oocitos/metabolismo , Oocitos/crecimiento & desarrolloRESUMEN
Microorganisms residing in the cecum of donkeys are crucial for physiological processes, nutrient metabolism, and immune function. Feeding methods can affect the dynamic balance of animal gut microbiota, thereby affecting indicators such as volatile fatty acids. This study explores suitable feeding methods to promote actual production by changing the feeding order of concentrate. Fifteen Dezhou donkeys with similar age and weight profiles were randomly divided into three groups with the concentrate feeding sequence: fiber-to-concentrate (FC), concentrate-to-fiber (CF), and total mixed ration (TMR). The experiment spanned a duration of 82 days. The analyses conducted were primarily aimed at determining the effects of feeding on gut microbes, primarily using metagenomic sequencing techniques. The experimental findings revealed that the levels of valeric acid were notably higher in the CF and TMR groups compared to the FC group (p < 0.05). These results suggest that the feeding sequence exerts a certain impact on the microbial composition within the cecum of Dezhou donkeys. At the phylum level, the predominant microbiota consisted of Firmicutes and Bacteroidetes, with the CF group displaying a higher relative abundance of Firmicutes compared to both the FC and TMR groups. At the genus level, Prevotella, Bacteroides, and Fibrobacter were the dominant bacterial genera identified in cecum. The functional gene annotation analysis indicated a significantly lower abundance of lacZ (K01190), Por/nifJ (K03737), and ppdK (K01006) genes in CF group relative to the FC and TMR groups (p < 0.05), highlighting their roles in galactose metabolism and glycolysis, respectively. Moreover, the CF group exhibited a higher concentration of antibiotic resistance genes (tetO and tet44) in the gut microbiota compared to the TMR and FC groups (p < 0.05), underscoring the presence of numerous antibiotic resistance genes within the phyla Bacteroidetes, Firmicutes, and Proteobacteria. In conclusion, different precision feed sequences significantly impact the levels of volatile fatty acids in Dezhou fattening donkeys, modify the composition and functional genes of the cecal microbiota, and elucidate the microbial mechanisms influenced by the feeding sequence on the growth and metabolism. These insights are anticipated to provide a foundation for the rational design of precision feed sequences in practical agricultural settings.
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Previous research has shown that leucine (Leu) can stimulate and enhance the proliferation of equine skeletal muscle satellite cells (SCs). The gene expression profile associated with Leu-induced proliferation of equine SCs has also been documented. However, the specific role of Leu in regulating the expression of slow-twitch muscle fibers (slow-MyHC) and mitochondrial function in equine SCs, as well as the underlying mechanism, remains unclear. During this investigation, equine SCs underwent culturing in differentiation medium and were subjected to varying concentrations of Leu (0 mM, 0.5 mM, 1 mM, 2 mM, 5 mM, and 10 mM) over a span of 3 days. AMP-activated protein kinase (AMPK) inhibitor Compound C and mammalian target of rapamycin complex (mTOR) inhibitor Rapamycin were utilized to explore its underlying mechanism. Here we showed that the expression of slow-MyHC at 2 mM Leu level was significantly higher than the concentration levels of 0 mM,0.5 mM and 10 mM (P <0.01), and there was no significant difference compared to other groups (P > 0.05); the basal respiration, maximum respiration, standby respiration and the expression of slow-MyHC, PGC-1α, Cytc, ND1, TFAM, and COX1 were significantly increased with Leu supplementation (P < 0.01). We also found that Leu up-regulated the expression of key proteins on AMPK and mTOR signaling pathways, including LKB1, p-LKB1, AMPK, p-AMPK, S6, p-S6, 4EBP1, p-4EBP1, mTOR and p-mTOR (P < 0.05 or P < 0.01). Notably, when we treated the equine SCs with the AMPK inhibitor Compound C and the mTOR inhibitor Rapamycin, we observed a reduction in the beneficial effects of Leu on the expression of genes related to slow-MyHC and signaling pathway-related gene expressions. This study provides novel evidence that Leu promotes slow-MyHC expression and enhances mitochondrial function in equine SCs through the AMPK/mTOR signaling pathways, shedding light on the underlying mechanisms involved in these processes for the first time.
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Proteínas Quinasas Activadas por AMP , Metabolismo Energético , Leucina , Fibras Musculares de Contracción Lenta , Células Satélite del Músculo Esquelético , Transducción de Señal , Serina-Treonina Quinasas TOR , Animales , Leucina/farmacología , Serina-Treonina Quinasas TOR/metabolismo , Células Satélite del Músculo Esquelético/metabolismo , Células Satélite del Músculo Esquelético/efectos de los fármacos , Transducción de Señal/efectos de los fármacos , Caballos , Proteínas Quinasas Activadas por AMP/metabolismo , Proteínas Quinasas Activadas por AMP/genética , Metabolismo Energético/efectos de los fármacos , Fibras Musculares de Contracción Lenta/metabolismo , Fibras Musculares de Contracción Lenta/efectos de los fármacos , Células CultivadasRESUMEN
Molecular dynamics simulations produce trajectories that correspond to vast amounts of structure when exploring biochemical processes. Extracting valuable information, e.g., important intermediate states and collective variables (CVs) that describe the major movement modes, from molecular trajectories to understand the underlying mechanisms of biological processes presents a significant challenge. To achieve this goal, we introduce a deep learning approach, coined DIKI (deep identification of key intermediates), to determine low-dimensional CVs distinguishing key intermediate conformations without a-priori assumptions. DIKI dynamically plans the distribution of latent space and groups together similar conformations within the same cluster. Moreover, by incorporating two user-defined parameters, namely, coarse focus knob and fine focus knob, to help identify conformations with low free energy and differentiate the subtle distinctions among these conformations, resolution-tunable clustering was achieved. Furthermore, the integration of DIKI with a path-finding algorithm contributes to the identification of crucial intermediates along the lowest free-energy pathway. We postulate that DIKI is a robust and flexible tool that can find widespread applications in the analysis of complex biochemical processes.
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Inteligencia Artificial , Simulación de Dinámica Molecular , Algoritmos , EntropíaRESUMEN
We present a novel strategy to explore conformational changes and identify stable states of molecular objects, eliminating the need for a priori knowledge. The approach applies a deep learning method to extract information about the movement modes of the molecular object from a short, high-dimensional, and parameter-free preliminary enhanced-sampling simulation. The gathered information is described by a small set of deep-learning-based collective variables (dCVs), which steer the production-enhanced-sampling simulation. Considering the challenge of adequately exploring the configurational space using the low-dimensional, suboptimal dCVs, we incorporate a method designed for ergodic sampling, namely, Gaussian-accelerated molecular dynamics (MD), into the framework of CV-based enhanced sampling. MD simulations on both toy models and nontrivial examples demonstrate the remarkable computational efficiency of the strategy in capturing the conformational changes of molecular objects without a priori knowledge. Specifically, we achieved the blind folding of two fast folders, chignolin and villin, within a time scale of hundreds of nanoseconds and successfully reconstructed the free-energy landscapes that characterize their reversible folding. All in all, the presented strategy holds significant promise for investigating conformational changes in macromolecules, and it is anticipated to find extensive applications in the fields of chemistry and biology.
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In this study, effects on the growth performance, nutrient digestibility, volatile fatty acids (VFA) production, and fecal microbiota of weaned donkeys were observed using different concentrate feeding sequences. Fifteen healthy 6-month-old weaned male donkeys with a body weight of 117.13 ± 10.60 kg were randomly divided into three treatment groups, including group C1 (roughage-then-concentrate), group C2 (concentrate-then-roughage), and group C3 (total mixed ration, TMR). The experiment lasted 35 d. We measured nutrient digestion by the acid-insoluble ash method and analyzed the fecal microbiota of the weaned donkeys by high-throughput sequencing of 16s rRNA genes in the V3-V4 region. The results show that group C3 obtained the best growth performance, and the digestibility of crude protein (CP) and crude extract (EE) was significantly higher than that of group C1 (p < 0.05). Acetic acid, isobutyric acid, valeric acid, isovaleric acid, and caproic acid were notably different among all groups (p < 0.05). In addition, we observed that Firmicutes and Bacteroidetes were dominant in the fecal microbes of each group, and Firmicutes was significantly higher in group C3 (p < 0.05). At the genus level, the different genera were Treponema, Rikenellaceae-RC9-gut-group, Unidentified-F082, and Bacteroidales-RF16-group (p < 0.05). The prediction of fecal microbiota function by PICRUSt indicated that different feeding sequences had minimal impact on the function of the fecal microbiota, particularly on the high-abundance pathway. In summary, the concentrate feeding sequence changed the composition of the fecal microbe of weaned donkeys.
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The proliferation and differentiation of skeletal muscle satellite cells (SCs) are necessary for the development of mature skeletal muscle. Leucine (Leu) is both an essential amino acid (EAA) and a branched-chain amino acid (BCAA), which has attracted worldwide attention due to its ability to repair and become new fibers. We separated the equine SCs into the control group (CON) and the Leu-supplemented group (LEU), which the cells were cultured in Leu-deprived and Leu-supplemented media respectively. We combined the transcriptome (RNA-Seq) and quantitative proteome (TMT) profiling analyses on proliferation of equine SCs associated with Leu. 1839 up-regulated and 631 down-regulated genes made up the 2470 differentially expressed genes (DEGs), and the 253 differentially abundant proteins (DEPs) included 118 up-regulated and 135 down-regulated proteins. 110 overlapping genes were verified based on the mRNA and protein translation relationship. Moreover, by comparing overlapped pathways through enrichment analysis, we found 13 genes not only appeared among 110 key DEGs/DEPs but also enriched in the KEGG overlapping signaling pathway, including CCL26, STAT2, PCK2, ASNS, GPT2, SHMT2, PHGDH, PGAM2, PSAT1, FTL, HMOX1, STEAP1 and STEAP2. To our knowledge, this is the first report in the world to systematically show how Leu regulated the growth of equine SCs. Leu deficiency inhibits the proliferation of equine SCs and development of fresh muscle fibers was proved in this paper. The main genes in charge of the Leu-induced proliferation of horse SCs have been found. These genes will make it easier to understand the mechanism at work and offer new information for enhancing the performance of sport horses and alleviating the equine muscle damage during exercise in the future.
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Células Satélite del Músculo Esquelético , Transcriptoma , Caballos/genética , Animales , Leucina/genética , Leucina/metabolismo , Leucina/farmacología , Células Satélite del Músculo Esquelético/metabolismo , Proteoma/metabolismo , Proliferación CelularRESUMEN
Colon cancer is one of the typical malignant tumors, and its prevalence has increased yearly. The ketogenic diet (KD) is a low-carbohydrate and high-fat dietary regimen that inhibits tumor growth. Donkey oil (DO) is a product with a high nutrient content and a high bioavailability of unsaturated fatty acids. Current research investigated the impact of the DO-based KD (DOKD) on CT26 colon cancer in vivo. Our findings revealed that DOKD administration significantly lowered CT26+ tumor cell growth in mice, and the blood ß-hydroxybutyrate levels in the DOKD group was significantly higher than those in the natural diet group. Western blot results showed that DOKD significantly down-regulated Src, hypoxia inducible factor-1α (HIF-1α), extracellular signal-related kinases 1 and 2 (Erk1/2), snail, neural cadherin (N-cadherin), vimentin, matrix metallopeptidase 9 (MMP9), signal transducer and activator of transcription 3 (STAT3), and vascular endothelial growth factor A (VEGFA), and it significantly up-regulated the expressions of Sirt3, S100a9, interleukin (IL)-17, nuclear factor-kappaB (NF-κB) p65, Toll-like receptor 4 (TLR4), MyD88, and tumor necrosis factor-α. Meanwhile, in vitro validation results showed that LW6 (a HIF-1α inhibitor) significantly down-regulated the expressions of HIF-1α, N-cadherin, vimentin, MMP9, and VEGFA, which supported those of the in vivo findings. Furthermore, we found that DOKD inhibited CT26+ tumor cell growth by regulating inflammation, metastasis, and angiogenesis by activating the IL-17/TLR4/NF-κB p65 pathway and inhibiting the activation of the Src/HIF-1α/Erk1/2/Snail/N-cadherin/Vimentin/MMP9 and Erk1/2/HIF-1α/STAT3/VEGFA pathways. Our findings suggest that DOKD may suppress colon cancer progression and help prevent colon cancer cachexia.
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Neoplasias del Colon , Dieta Cetogénica , Animales , Ratones , Factor A de Crecimiento Endotelial Vascular/genética , Factor A de Crecimiento Endotelial Vascular/metabolismo , Vimentina , Receptor Toll-Like 4 , FN-kappa B , Metaloproteinasa 9 de la Matriz , Línea Celular Tumoral , Neoplasias del Colon/genética , Neoplasias del Colon/patología , InflamaciónRESUMEN
In response to muscle injury, muscle stem cells are stimulated by environmental signals to integrate into damaged tissue to mediate regeneration. L-leucine (L-leu), a branched-chain amino acid (BCAA) that belongs to the essential amino acids (AAs) of the animal, has gained global interest on account of its muscle-building and regenerating effects. The present study was designed to investigate the impact of L-leu exposure to promote the proliferation of equine skeletal muscle satellite cells (SCs) on the regulation of RNA networks, including mRNA, long non-coding RNA (lncRNA), covalently closed circular RNA (circRNA), and microRNA (miRNA) in skeletal muscles. Equine SCs were used as a cell model and cultured in different concentrations of L-leu medium. The cell proliferation assay found that the optimal concentration of L-leu was 2 mM, so we selected cells cultured with L-leu concentrations of 0 mM and 2 mM for whole-transcriptiome sequencing, respectively. By high-throughput sequencing analysis, 2470 differentially expressed mRNAs (dif-mRNAs), 363 differentially expressed lncRNAs (dif-lncRNAs), 634 differentially expressed circRNAs (dif-circRNAs), and 49 differentially expressed miRNAs (dif-miRNAs) were significantly altered in equine SCs treated with L-leu. To identify the function of autoimmunity and anti-inflammatory responses after L-leu exposure, enrichment analysis was conducted on those differentially expressed genes (DEGs) related to lncRNA, circRNA, and miRNA. The hub genes were selected from PPI Network, including ACACB, HMGCR, IDI1, HAO1, SHMT2, PSPH, PSAT1, ASS1, PHGDH, MTHFD2, and DPYD, and were further identified as candidate biomarkers to regulate the L-leu-induced proliferation of equine SCs. The up-regulated novel 699_star, down-regulated novel 170_star, and novel 360_mature were significantly involved in the competing endogenous RNA (ceRNA) complex network. The hub genes involved in cell metabolism and dif-miRNAs may play fundamental roles in the L-leu-induced proliferation of equine SCs. Our findings suggested that the potential network regulation of miRNAs, circ-RNAs, lncRNAs, and mRNAs plays an important role in the proliferation of equine SCs, so as to build up new perspectives on improving equine performance and treatment strategies for the muscle injuries of horses.
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The follicular fluid and oviduct fluid play major roles in oocyte maturation, sperm activation, and fertilization. To better understand the physiological environments for equine oocyte maturation and fertilization, here we conducted the proteome analysis and comparison on follicular fluids and oviduct fluids from the ovulatory side and the anovulatory side. The results showed that there is no significant difference between two side oviduct fluids, but a total of 71 differential abundance proteins (DAPs) were identified between two side follicular fluids, of which 9 are up-regulated and 62 are down-regulated in ovulatory side follicle fluid versus anovulatory side follicle fluid. As we expected, the function classification and enrichment results indicate that up- and down-regulated proteins are largely related to oocyte meiosis, maturation and ovulation. Noticeably, among 9 up-regulated DAPs in ovulatory side follicle fluid, as the DAP with the greatest fold change, PLA2G1B may be a newly discovered component that influences the efficacy of horse IVM/IVF. The current findings add to our knowledge of the in vivo conditions and regulation of equine reproduction, as well as the regulatory mechanism underpinning alternative ovulation.
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Anovulación , Enfermedades de los Caballos , Animales , Caballos , Femenino , Masculino , Folículo Ovárico/metabolismo , Proteómica , Semen , Oocitos/metabolismo , Anovulación/veterinaria , Oviductos , Enfermedades de los Caballos/metabolismoRESUMEN
The community of microorganisms inhabiting the gastrointestinal tract of monogastric herbivores played critical roles in the absorption of nutrients and keeping the host healthy. However, its establishment at different age groups has not been quantitatively and functionally examined. The knowledge of microbial colonization and its function in the intestinal tract of different-age donkeys is still limited. By applying the V3-V4 region of the bacterial 16S rRNA gene and functional prediction on fecal samples from different-age donkeys, we characterized the gut microbiota during the different age groups. In contrast to the adult donkeys, the gut microbiota diversity and richness of the young donkeys showed significantly less resemblance. The microbial data showed that diversity and richness increased with age, but a highly individual variation of microbial composition was observed at month 1. Principal coordinate analysis (PCoA) revealed a significant difference across five time points in the feces. The abundance of Bacteroides, Lactobacillus, and Odoribacter tended to decrease, while the proportion of Streptococcus was significantly increased with age. For functional prediction, the relative abundance of pathways had a significant difference in the feces across different age groups, for example, Terpenoids and Polyketides and Folding, Sorting, and Degradation (P < 0.05 or P < 0.01). The analysis of beta diversity (PCoA and LEfSe) and microbial functions predicted with PICRUSt (NSTIs) clearly divided the donkeys into foals (≤3 months old) and adults (≥7 months old). Microbial community composition and structure had distinctive features at each age group, in accordance with functional stability of the microbiota. Our findings established a framework for understanding the composition and function of the fecal microbiota to differ between young and adult donkeys.
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Gastrointestinal microbiota has significant impact on the nutrition and health of monogastric herbivores animals including donkey. However, so far the microbiota in different gastrointestinal compartments of healthy donkey has not been described. Therefore, we investigated the abundance and function of microbiota at different sites of the gastrointestinal tract (GIT) (foregut: stomach, duodenum, jejunum and ileum; hindgut: cecum, ventral colon, dorsal colon, and rectum) of healthy adult donkeys mainly based on 16S rRNA gene sequencing and phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) analysis. Collectively, our results showed that donkey has a rich, diverse and multi-functional microbiota along the GIT. In general, the richness and diversity of the microbiota are much higher in the hindgut relative to that in the foregut; at phylum level, the Firmicutes is dominant in the foregut while both Firmicutes and Bacteroides are abundant in the hindgut; at the genus level, Lactobacillus was dominant in the foregut while Streptococcus was more dominant in the hindgut. Our further PICRUSt analysis showed that varying microbiota along the GIT is functionally compatible with the corresponding physiological function of different GIT sites. For example, the microbes in the foregut are more active at carbohydrate metabolism, and in the hindgut are more active at amino acid metabolism. This work at the first time characterized the donkey digestive system from the aspects of microbial composition and function, provided an important basic data about donkey healthy gastrointestinal microbiota, which may be utilized to evaluate donkey health and also offer clues to further investigate donkey digestive system, nutrition, even to develop the microbial supplements.
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Bacterias/clasificación , ADN Bacteriano/análisis , Microbioma Gastrointestinal/genética , Tracto Gastrointestinal/microbiología , Animales , Bacterias/genética , ADN Bacteriano/genética , Equidae , Masculino , Filogenia , ARN Ribosómico 16S/análisis , ARN Ribosómico 16S/genéticaRESUMEN
Food restriction (FR) and refeeding (Re) have been suggested to impair body mass regulation and thereby making it easier to regain the lost weight and develop over-weight when FR ends. However, it is unclear if this is the case in small mammals showing seasonal forging behaviors. In the present study, energy budget, body fat and serum leptin level were measured in striped hamsters that were exposed to FR-Re. The effects of leptin on food intake, body fat and genes expressions of several hypothalamus neuropeptides were determined. Body mass, fat content and serum leptin level decreased during FR and then increased during Re. Leptin supplement significantly attenuated the increase in food intake during Re, decreased genes expressions of neuropepetide Y (NPY) and agouti-related protein (AgRP) of hypothalamus and leptin of white adipose tissue (WAT). Hormone-sensitive lipase (HSL) gene expression of WAT increased in leptin-treated hamsters that were fed ad libitum, but decreased in FR-Re hamsters. This indicates that the adaptive regulation of WAT HSL gene expression may be involved in the mobilization of fat storage during Re, which partly contributes to the resistance to FR-Re-induced overweight. Leptin may be involved in the down regulations of hypothalamus orexigenic peptides gene expression and consequently plays a crucial role in controlling food intake when FR ends.