Bioorthogonal labeling and enrichment of histone monoaminylation reveal its accumulation and regulatory function in cancer cell chromatin.

Histone monoaminylation ( i . e ., serotonylation and dopaminylation) is an emerging category of epigenetic mark occurring on the fifth glutamine (Q5) residue of H3 N-terminal tail, which plays significant roles in gene transcription. Current analysis of histone monoaminylation is mainly based on site-specific antibodies and mass spectrometry, which either lacks high resolution or is time-consuming. In this study, we report the development of chemical probes for bioorthogonal labeling and enrichment of histone serotonylation and dopaminylation. These probes were successfully applied for the monoaminylation analysis of in vitro biochemical assays, cells, and tissue samples. The enrichment of monoaminylated histones by the probes further confirmed the crosstalk between H3Q5 monoaminylation and H3K4 methylation. Finally, combining the ex vivo and in vitro analyses based on the developed probes, we have shown that both histone serotonylation and dopaminylation are highly enriched in tumor tissues that overexpress transglutaminase 2 (TGM2) and regulate the three-dimensional architecture of cellular chromatin.

A green tea extract confection decreases circulating endotoxin and fasting glucose by improving gut barrier function but without affecting systemic inflammation: A double-blind, placebo-controlled randomized trial in healthy adults and adults with metabolic syndrome.

Anti-inflammatory activities of catechin-rich green tea extract (GTE) in obese rodents protect against metabolic endotoxemia by decreasing intestinal permeability and absorption of gut-derived endotoxin. However, translation to human health has not been established. We hypothesized that GTE would reduce endotoxemia by decreasing gut permeability and intestinal and systemic inflammation in persons with metabolic syndrome (MetS) compared with healthy persons. A randomized, double-blind, placebo-controlled, crossover trial in healthy adults (n = 19, 34 ± 2 years) and adults with MetS (n = 21, 40 ± 3 years) examined 4-week administration of a decaffeinated GTE confection (890 mg/d total catechins) on serum endotoxin, intestinal permeability, gut and systemic inflammation, and cardiometabolic parameters. Compared with the placebo, the GTE confection decreased serum endotoxin (P = .023) in both healthy persons and those with MetS, while increasing concentrations of circulating catechins (P < .0001) and γ-valerolactones (P = .0001). Fecal calprotectin (P = .029) and myeloperoxidase (P = .048) concentrations were decreased by GTE regardless of health status. Following the ingestion of gut permeability probes, urinary lactose/mannitol (P = .043) but not sucralose/erythritol (P > .05) was decreased by GTE regardless of health status. No between-treatment differences (P > .05) were observed for plasma aminotransferases, blood pressure, plasma lipids, or body mass nor were plasma tumor necrosis factor-α, interleukin-6, or the ratio of lipopolysaccharide-binding protein/soluble cluster of differentiation-14 affected. However, fasting glucose in both study groups was decreased (P = .029) by the GTE confection compared with within-treatment arm baseline concentrations. These findings demonstrate that catechin-rich GTE is effective to decrease circulating endotoxin and improve glycemic control in healthy adults and those with MetS, likely by reducing gut inflammation and small intestinal permeability but without affecting systemic inflammation.

Crosstalk between innate immunity and rumen-fecal microbiota under the cold stress in goats.

The balance of the microbiome, which is sensitive to temperature changes, plays a crucial role in maintaining overall health and reducing the risk of diseases. However, the specific mechanisms by which immunity and microbiota interact to adapt to cold stress have yet to be addressed. In this study, Nanjiang Yellow goats were chosen as a model and sampled during the cold (winter, cold stress) and warm (spring) seasons, respectively. Analyses of serum immune factors, as well as the composition of rumen and fecal microbial communities, were conducted to explore the crosstalk between microbiota and innate immunity under cold stress. Significantly increased levels of IgA (P < 0.01) were observed in the cold season compared to the warm season. Conversely, the levels of IL-2 (P = 0.02) and IL-6 (P < 0.01) diminished under cold stress. However, no significant differences were observed in IgG (P = 0.89), IgM (P = 0.42), and IL-4 (P = 0.56). While there were no significant changes in the diversity of bacterial communities between the warm and cold seasons, positive correlations between serum IgA, IL-2, IL-6 concentrations and several genera were observed. Furthermore, the weighted gene co-expression network analysis indicated that the microbiota enriched in the MEbrown module positively correlated with IgA, while the microbiota enriched in the MEblue module positively correlated with IL-2 and IL-6. The strong correlation between certain probiotics, including Alistipes, Bacteroides, Blautia, and Prevotellaceae_UCG.004, and the concentration of IL-2, and IL-6 suggests their potential role in immunomodulatory properties. This study provides valuable insights into the crosstalk between microbial communities and immune responses under the challenge of cold stress. Further studies on the immunomodulatory properties of these probiotics would contribute to the development of strategies to enhance the stress resistance of animals for improved overall health and survival.

Plasma and serum metabolic analysis of healthy adults shows characteristic profiles by subjects' sex and age.

INTRODUCTION: Pre-analytical factors like sex, age, and blood processing methods introduce variability and bias, compromising data integrity, and thus deserve close attention. OBJECTIVES: This study aimed to explore the influence of participant characteristics (age and sex) and blood processing methods on the metabolic profile. METHOD: A Thermo UPLC-TSQ-Quantiva-QQQ Mass Spectrometer was used to analyze 175 metabolites across 9 classes in 208 paired serum and lithium heparin plasma samples from 51 females and 53 males. RESULTS: Comparing paired serum and plasma samples from the same cohort, out of the 13 metabolites that showed significant changes, 4 compounds related to amino acids and derivatives had lower levels in plasma, and 5 other compounds had higher levels in plasma. Sex-based analysis revealed 12 significantly different metabolites, among which most amino acids and derivatives and nitrogen-containing compounds were higher in males, and other compounds were elevated in females. Interestingly, the volcano plot also confirms the similar patterns of amino acids and derivatives higher in males. The age-based analysis suggested that metabolites may undergo substantial alterations during the 25-35-year age range, indicating a potential metabolic turning point associated with the age group. Moreover, a more distinct difference between the 25-35 and above 35 age groups compared to the below 25 and 25-35 age groups was observed, with the most significant compound decreased in the above 35 age groups. CONCLUSION: These findings may contribute to the development of comprehensive metabolomics analyses with confounding factor-based adjustment and enhance the reliability and interpretability of future large-scale investigations.

Multiple and Optimal Screening Subset: a method selecting global characteristic congeners for robust foodomics analysis.

Metabolomics and foodomics shed light on the molecular processes within living organisms and the complex food composition by leveraging sophisticated analytical techniques to systematically analyze the vast array of molecular features. The traditional feature-picking method often results in arbitrary selections of the model, feature ranking, and cut-off, which may lead to suboptimal results. Thus, a Multiple and Optimal Screening Subset (MOSS) approach was developed in this study to achieve a balance between a minimal number of predictors and high predictive accuracy during statistical model setup. The MOSS approach compares five commonly used models in the context of food matrix analysis, specifically bourbons. These models include Student's t-test, receiver operating characteristic curve, partial least squares-discriminant analysis (PLS-DA), random forests, and support vector machines. The approach employs cross-validation to identify promising subset feature candidates that contribute to food characteristic classification. It then determines the optimal subset size by comparing it to the corresponding top-ranked features. Finally, it selects the optimal feature subset by traversing all possible feature candidate combinations. By utilizing MOSS approach to analyze 1406 mass spectral features from a collection of 122 bourbon samples, we were able to generate a subset of features for bourbon age prediction with 88% accuracy. Additionally, MOSS increased the area under the curve performance of sweetness prediction to 0.898 with only four predictors compared with the top-ranked four features at 0.681 based on the PLS-DA model. Overall, we demonstrated that MOSS provides an efficient and effective approach for selecting optimal features compared with other frequently utilized methods.

Lipidome isotope labelling of gut microbes (LILGM): A method of discovering endogenous microbial lipids.

Lipidomics analysis of gut microbiome has become critical in recent surge of extensive human disease studies that investigate microbiome contributions. However, challenges remain in comprehending the origins of thousands of lipid species produced by the diverse microbes. Here, we proposed the development and utilization of a liquid chromatography-mass spectrometry-based approach, named lipidome isotope labelling of gut microbes (LILGM), which enables confident detection and identification of endogenous gut microbial lipidome via 13C/15N labeling strategy and high-resolution mass spectrometry. Our method leveraged in vitro microbial cultures and stable isotope-labeled 13C and 15N, allowing a reasonable degree of isotope incorporation into microbial lipids over short-term of inoculation. We then systematically detected the mass spectral patterns of 182 labeled lipid species by our in-house data analysis pipeline. Further bioinformatics analyses confidently identified biologically relevant microbial lipids from lipid classes such as diacylglycerols (DGs), fatty acids (FAs), phosphatidylglycerols (PGs), and phosphatidylethanolamines (PEs) that may have profound impacts to human physiology. Our study also demonstrated the application of LILGM by showcasing the confident detection of dysregulated microbial lipids post antibiotic perturbation. The debiased sparse partial correlation analysis provides insights into lipid metabolism intricacies. Overall, our method can provide unambiguous analyses to the endogenous microbial lipids in given biological context, and can also instantly reflect the lipidomic changes of gut microbes in response to environmental factors. We believe our LILGM approach has the potential to provide new body of knowledge by combining promising analytical approaches for sensitive and specific lipid detection to support functional microbiome studies.

Integrated analysis of differently expressed microRNAs and mRNAs at different postnatal stages reveals intramuscular fat deposition regulation in goats (Capra hircus).

Intramuscular fat refers to the adipose tissue distributed in the muscle. It is an important indicator that affects the quality of goat meat, and can directly affect the tenderness and flavor of goat meat. Our previous study revealed the mRNA that may be crucial for intramuscular fat deposition during goat growth; however, how the microRNAs (miRNAs) are involved in the process is largely unclear. In the present study, a total of 401 known miRNAs and 120 goat novel miRNAs, including 110 differentially expressed (DE) miRNAs, were identified among longissimus dorsi from three growth stages (2, 9, and 24 months) by miRNA sequencing. Combining analysis of the DE mRNAs and DE miRNAs was then performed by miRDB and miRwalk, and miR-145-5p and FOXO1, miR-487b-3p, and PPARG coactivator 1 α (PPARGC1A), miR-345-3p, and solute carrier family 2 member 4 (SLC2A4), etc. were shown to closely associate with lipid metabolism, which was then validated by a correlation analysis. The final DE mRNAs were significantly enriched in fatty acid transmembrane transport, fatty acid homeostasis, apelin signaling pathway, glucagon signaling pathway, insulin signaling pathway, and AMPK signaling pathway by gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Besides, miR-145-5p showed a certain effect on goat intramuscular fat metabolism by acting on the possible target gene Forkhead Box O1 (FOXO1). These data provide some theoretical support for improving the quality of goat meat.

Distinct plasma molecular profiles between early-onset and late-onset colorectal cancer patients revealed by metabolic and lipidomic analyses.

Colorectal cancer (CRC) incidence in younger adults has been steadily rising, warranting an in-depth investigation into the distinctions between early-onset CRC (EOCRC, < 50 years) and late-onset CRC (LOCRC, ≥ 50 years). Despite extensive study of clinical, pathological, and molecular traits, differentiating EOCRC from LOCRC and identifying potential biomarkers remain elusive. We analyzed plasma samples from healthy individuals, EOCRC, and LOCRC patients using liquid-chromatography mass spectrometry (LC/MS)-based metabolomics and lipidomics. Distinct polar metabolite and lipid profiles with significant metabolites altered in CRC group (e.g., choline and DG 40:4) were identified. Notably, EOCRC exhibited distinct polar metabolomic and differential lipidomic profiles compared to LOCRC, with polar metabolites like aminoadipate and uridine contributing significantly to the difference, and originating from pathways such as lysine biosynthesis and nucleotide metabolism. Furthermore, gene set enrichment analysis (GSEA) using independent TCGA gene expression data identified pathways significantly enriched in either EOCRC or LOCRC. Integrating gene expression and metabolomics data revealed numerous associations differentiating EOCRC and LOCRC. Our multi-omics integration underscores critical molecular distinctions, offers insights into the EOCRC development mechanisms and potential plasma biomarkers for diagnosis.

A Bioinformatics Tool for Identifying Intratumoral Microbes from the ORIEN Dataset.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10%-20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, microbial graph attention (MEGA), to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of nine cancer centers in the Oncology Research Information Exchange Network. This package has three unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2,704 tumor RNA sequencing samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors. SIGNIFICANCE: Studying the tumor microbiome in high-throughput sequencing data is challenging because of the extremely sparse data matrices, heterogeneity, and high likelihood of contamination. We present a new deep learning tool, MEGA, to refine the organisms that interact with tumors.

Meeting Report on the 3rd Chinese American Society for Mass Spectrometry Conference-Advancing Biological and Pharmaceutical Mass Spectrometry.

Following the highly successful Chinese American Society for Mass Spectrometry (CASMS) conferences in the previous 2 years, the 3rd CASMS Conference was held virtually on August 28-31, 2023, using the Gather.Town platform to bring together scientists in the MS field. The conference offered a 4-day agenda with a scientific program consisting of two plenary lectures, and 14 parallel symposia in which a total of 70 speakers presented technological innovations and their applications in proteomics and biological MS and metabo-lipidomics and pharmaceutical MS. In addition, 16 invited speakers/panelists presented at two research-focused and three career development workshops. Moreover, 86 posters, 12 lightning talks, 3 sponsored workshops, and 11 exhibitions were presented, from which 9 poster awards and 2 lightning talk awards were selected. Furthermore, the conference featured four young investigator awardees to highlight early-career achievements in MS from our society. The conference provided a unique scientific platform for young scientists (i.e. graduate students, postdocs, and junior faculty/investigators) to present their research, meet with prominent scientists, learn about career development, and job opportunities (http://casms.org).

Secondary-Electrospray Ionization Mass Spectrometry-Based Online Analyses of Mouse Volatilome Uncover Gut Microbiome-Dictated Metabolic Changes in the Host.

The symbiotic relationship between the gut microbial population is capable of regulating numerous aspects of host physiology, including metabolism. Bacteria can modulate the metabolic processes of the host by feeding on nutritional components within the lumen and releasing bioactive components into circulation. Endogenous volatile organic compound (VOC) synthesis is dependent on the availability of precursors found in mammalian metabolism. Herein, we report that microbial-mediated metabolic influences can alter the host volatilome and the prominent volatile changes can be uncovered by a novel volatile analysis technique named secondary electrospray ionization mass spectrometry. Mice were subjected to an antibiotic cocktail to deplete the microbiome and then inoculated with either single strain bacteria or fecal matter transplantation (FMT) to replete the microbial population in the gut. VOC sampling was achieved by using an advanced secondary electrospray ionization (SESI) source that directly mounted onto a Thermo Q-Exactive high-resolution mass spectrometer (HRMS). A principal component analysis summarizing the volatile profiles of the mice revealed independent clustering of each strain of the FMT-inoculated groups, suggesting unique volatile profiles. The Mummichog algorithm uncovered phenylalanine metabolism as a significantly altered metabolic profile in the volatilome of the microbiome-repleted mice. Our results indicated that the systemic metabolic changes incurred by the host are translated to unique volatile profiles correlated to the diversity of the microbial population colonized within the host. It is thus possible to take advantage of SESI-HRMS-based platforms for noninvasive screening of VOCs to determine the contribution of various microbial colonization within human gut that may impact host health.

2'-Fucosyllactose (2'-FL) changes infants gut microbiota composition and their metabolism in a host-free human colonic model.

BACKGROUND: Breast milk is critical for neonates, providing the necessary energy, nutrients, and bioactive compounds for growth and development. Research indicated that human milk oligosaccharides (HMOs) have been shown to shape a beneficial gut microbiota, as well as their metabolism (e.g. short-chain fatty acids). 2'-Fucosyllactose (2'-FL) is one major HMO that composed of 30% of total HMOs. OBJECTIVES: This study aimed to understand the impact of 2'-FL on the composition and metabolism of infant gut microbiota. METHODS: Our study utilized an in-vitro human colonic model (HCM) to investigate the host-free interactions between 2'-FL and infant gut microbiota. To simulate the infant gut microbiota, we inoculated the HCM system with eight representative bacterial species from infant gut microbiota. The effects of 2'-FL on the gut microbial composition and their metabolism were determined through real-time quantitative PCR and liquid-chromatography mass spectrometry (LC/MS). The obtained data were analyzed using Compound Discoverer 3.1 and MetaboAnalyst 4.0. RESULTS: Our study findings suggest that the intervention of 2'-FL in HCM resulted in a significant change in the abundance of representative bacterial species. PCR analysis showed a consistent increase in the abundance of Parabacteroides. distasonis in all three colon sections. Furthermore, analysis of free fatty acids revealed a significant increase in their levels in the ascending, transverse, and descending colons, except for caproic acid, which was significantly reduced to a non-detectable level. The identification of significant extracellular polar metabolites, such as glutathione and serotonin, enabled us to distinguish between the metabolomes before and after 2'-FL intervention. Moreover, correlation analysis revealed a significant association between the altered microbes and microbial metabolites. CONCLUSIONS: In summary, our study demonstrated the impact of 2'-FL intervention on the defined composition of infant gut microbiota and their metabolic pathways in an in vitro setting. Our findings provide valuable insights for future follow-up investigations into the role of 2'-FL in regulating the growth and development of infant gut microbiota in vivo.

Database-assisted, globally optimized targeted secondary electrospray ionization high resolution mass spectrometry (dGOT-SESI-HRMS) and spectral stitching enhanced volatilomics analysis of bacterial metabolites.

Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an innovative analytical technique for the rapid and non-invasive analysis of volatile organic compounds (VOCs). However, compound annotation and ion suppression in the SESI source has hindered feature detection, stability and reproducibility of SESI-HRMS in untargeted volatilomics. To address this, we have developed and optimized a novel pseudo-targeted approach, database-assisted globally optimized targeted (dGOT)-SESI-HRMS using the microbial-VOC (mVOC) database, and spectral stitching methods to enhance metabolite detection in headspace of anaerobic bacterial cultures. Headspace volatiles from representative bacteria strains were assessed using full scan with data dependent acquisition (DDA), conventional globally optimized targeted (GOT) method, and spectral stitching supported dGOT experiments based on a MS peaks list derived from mVOC. Our results indicate that spectral stitching supported dGOT-SESI-HRMS can proportionally fragment peaks with respect to different analysis windows, with a total of 109 VOCs fragmented from 306 targeted compounds. Of the collected spectra, 88 features were confirmed as culture derived volatiles with respect to media blanks. Annotation was also achieved with a total of 25 unique volatiles referenced to standard databases allowing for biological interpretation. Principal component analysis (PCA) summarizing the headspace volatile demonstrated improved separation of clusters when data was acquired using the dGOT method. Collectively, our dGOT-SESI-HRMS method afforded robust capability of capturing unique VOC profiles from different bacterial strains and culture conditions when compared to conventional GOT and DDA modes, suggesting the newly developed approach can serve as a more reliable analytical method for the sensitive monitoring of gut microbial metabolism.

Expression Variation of CPT1A Induces Lipid Reconstruction in Goat Intramuscular Precursor Adipocytes.

Intramuscular fat (IMF) deposition is one of the most important factors affecting meat quality and is closely associated with the expression of carnitine palmitoyl transferase 1A (CPT1A) which facilitates the transfer of long-chain fatty acids (LCFAs) into the mitochondria. However, the role of how CPT1A regulates the IMF formation remains unclear. Herein, we established the temporal expression profile of CPT1A during the differentiation of goat intramuscular precursor adipocytes. Functionally, the knockdown of CPT1A by siRNA treatment significantly increased the mRNA expression of adipogenic genes and promoted lipid deposition in goat intramuscular precursor adipocytes. Meanwhile, a CPT1A deficiency inhibited cell proliferation and promoted cell apoptosis significantly. CPT1A was then supported by the overexpression of CPT1A which significantly suppressed the cellular triglyceride deposition and promoted cell proliferation although the cell apoptosis also was increased. For RNA sequencing, a total of 167 differential expression genes (DEGs), including 125 upregulated DEGs and 42 downregulated DEGs, were observed after the RNA silencing of CPT1A compared to the control, and were predicted to enrich in the focal adhesion pathway, cell cycle, apoptosis and the MAPK signaling pathway by KEGG analysis. Specifically, blocking the MAPK signaling pathway by a specific inhibitor (PD169316) rescued the promotion of cell proliferation in CPT1A overexpression adipocytes. In conclusion, the expression variation of CPT1A may reconstruct the lipid distribution between cellular triglyceride deposition and cell proliferation in goat intramuscular precursor adipocyte. Furthermore, we demonstrate that CPT1A promotes the proliferation of goat adipocytes through the MAPK signaling pathway. This work widened the genetic regulator networks of IMF formation and delivered theoretical support for improving meat quality from the aspect of IMF deposition.

Distinctive patterns of sulfide- and butyrate-metabolizing bacteria after bariatric surgery: potential implications for colorectal cancer risk.

Despite improved cardiometabolic outcomes following bariatric surgery, its long-term impact on colorectal cancer (CRC) risk remains uncertain. In parallel, the influence of bariatric surgery on the host microbiome and relationships with disease outcomes is beginning to be appreciated. Therefore, we investigated the impact of Roux-en-Y gastric bypass (RYGB) and vertical sleeve gastrectomy (VSG) on the patterns of sulfide-reducing and butyrate-producing bacteria, which are hypothesized to modulate CRC risk after bariatric surgery. In this single-center, cross-sectional study, we included 15 pre-surgery subjects with severe obesity and patients who are at a median (range) of 25.6 (9.9-46.5) months after RYGB (n = 16) or VSG (n = 10). The DNA abundance of fecal bacteria and enzymes involved in butyrate and sulfide metabolism were identified using metagenomic sequencing. Differences between pre-surgery and post-RYGB or post-VSG cohorts were quantified using the linear discriminant analysis (LDA) effect size (LEfSe) method. Our sample was predominantly female (87%) with a median (range) age of 46 (23-71) years. Post-RYGB and post-VSG patients had a higher DNA abundance of fecal sulfide-reducing bacteria than pre-surgery controls (LDA = 1.3-4.4, p < .05). The most significant enrichments were for fecal E. coli, Acidaminococcus and A. finegoldii after RYGB, and for A. finegoldii, S. vestibularis, V. parvula after VSG. As for butyrate-producing bacteria, R. faecis was more abundant, whereas B. dentium and A. hardus were lower post-RYGB vs. pre-surgery. B. dentium was also lower in post-VSG vs. pre-surgery. Consistent with these findings, our analysis showed a greater enrichment of sulfide-reducing enzymes after bariatric surgery, especially RYGB, vs. pre-surgery. The DNA abundance of butyrate-producing enzymes was lower post-RYGB. In conclusion, the two most used bariatric surgeries, RYGB and VSG, are associated with microbiome patterns that are potentially implicated in CRC risk. Future studies are needed to validate and understand the impact of these microbiome changes on CRC risk after bariatric surgery.

miR-130b duplex (miR-130b-3p/miR-130b-5p) negatively regulates goat intramuscular preadipocyte lipid droplets accumulation by inhibiting Krüppel-like factor 3 expression.

Intramuscular lipid deposition is important for meat quality improvement. microRNAs and their target mRNAs provide a new approach for studying the mechanism of fat deposition. The present study aimed to investigate the effect of miR-130b duplex (miR-130b-5p, miR-130b-3p) and its target gene KLF3 in regulating goat intramuscular adipocyte differentiation. Goat intramuscular preadipocytes were isolated from 7-d-old male Jianzhou big-ear goats and identified by Oil red O staining after differentiation induction. miR-130b-5p and miR-130b-3p mimics or inhibitors and their corresponding controls were transfected into goat intramuscular preadipocytes, respectively, and differentiation was induced by 50µM oleic acid for 48 h. Oil red O and Bodipy staining indicated that both miR-130b-5p and miR-130b-3p can reduce lipid droplets accumulation and triglyceride (TG) content (P < 0.01). Differentiation markers C/EBPα, C/EBPß, PPARγ, pref1, fatty acids synthesis markers ACC, FASN, DGAT1, DGAT2, AGPAT6, TIP47, GPAM, ADRP, AP2, SREBP1, and TG markers LPL, ATGL, HSL were assessed by qPCR. All the markers measured were downregulated by miR-130b-5p and miR-130b-3p analog (P < 0.01), suggesting that miR-130b inhibits goat intramuscular adipocyte adipogenic differentiation, fatty acids synthesis, and lipid lipolysis. To examine the mechanism of miR-130b duplex inhibition of lipid deposition, TargetScan, miRDB, and starBase were used to predict the potential targets, KLF3 was found to be the only one intersection. Furthermore, the 3'UTR of KLF3 was cloned, qPCR analysis and dual luciferase activity assay showed that both miR-130b-5p and miR-130b-3p could directly regulate KLF3 expression (P < 0.01). In addition, overexpression and interference of KLF3 were conducted, it was found that KLF3 positively regulated lipid droplets accumulation by Oil red O, Bodipy staining, and TG content detection (P < 0.01). Quantitative PCR result indicated that KLF3 overexpression promoted lipid droplets accumulation relative genes C/EBPß, PPARγ, pref1, ACC, FASN, DGAT1, DGAT2, AGPAT6, TIP47, GPAM, ADRP, SREBP1, LPL, and ATGL expression (P < 0.01). Downregulation of KLF3 inhibited the expression of genes such as C/EBPα, C/EBPß, PPARγ, pref1, TIP47, GPAM, ADRP, AP2, LPL, and ATGL expression (P < 0.01). Taken together, these results indicate that miR-130b duplex could directly inhibit KLF3 expression, then attenuated adipogenic and TG synthesis genes expression, thus leading to its anti-adipogenic effect.

microRNAs (miRNAs) are small (19 to 24 nucleotides), single-stranded, noncoding RNAs that are evolutionarily conserved and can be complimentary bound to the 3ʹ-untranslated region (3ʹUTR) of their target mRNA for cleavage or translation inhibition to participate in almost all biological processes. We demonstrated miR-130b duplex (miR-130b-3p/miR-130b-5p) negatively regulates goat intramuscular preadipocyte lipid droplets accumulation by targeting Krüppel-like factor 3 (KLF3) expression. This research opens new visions to study and understand the functions and mechanisms of goat miRNAs in lipid deposition.

The orf virus 129 protein can inhibit immune responses by interacting with host complement C1q binding protein in goat turbinate bone cells.

OBJECTIVE: Contagious ecthyma is a severe and highly contagious disease caused by an orf virus (ORFV). The virus is responsible for substantial economic losses in the goat industry and threatens humans. We previously determined the role of ORFV129 protein, one of the five ankyrin-repeat proteins coded by the orf genome, in suppressing the transcription of pro-inflammatory cytokines IL-6, IL-1ß and IFN-γ. In the present study, we identified 14 cellular proteins (complement C1q binding protein [C1QBP], MCM7, EIF5A, PKM, SLC6A, TSPAN6, ATP6AP2, GPS1, MMADHC, HSPB6, SLC35B1, MTF1, P3H4, and IL15RA) that interact with ORFV129 using a yeast two-hybrid system in goat turbinate bone cells (GFTCs). The interaction between ORFV129 and (C1QBP), an immune-related protein, was confirmed using immunofluorescence co-localization and co-immunoprecipitation assays. C1QBP overexpression inhibited ORFV replication, whereas the knockdown of C1QBP promoted ORFV replication in GFTCs. Furthermore, ORFV or ORFV129 increased C1QBP expression in GFTCs, indicated that ORFV129-C1QBP interaction might contribute to the ORFV-induced host immune process. In addition, our research showed that ORFV increased the expression of ORFV129, cytokine IL-6, IL-1ß and IFN-γ. C1QBP overexpression induced IFN-γ production and reduced IL-6 and IL-1ß production. Conversely, C1QBP knockdown induced IL-1ß production and reduced IFN-γ and IL-1ß production. Moreover, augmentation of ORFV129 expression enhanced the inhibition of the secretion of cytokines IL-6, IL-1ß, and IFN-γ induced by the altered expression of C1QBP. These findings suggest different downstream pathways might be involved in regulating different cytokines induced by ORFV129 expression in GFTCs.

Characterizing bourbon whiskey via the combination of LC-MS and GC-MS based molecular fingerprinting.

To discover molecular fingerprints that vary by bourbon's age or color, 121 commercial bourbon samples were analyzed using both gas chromatography and liquid chromatography combined with mass spectrometry. In total, 81 non-volatile compounds and 102 volatile compounds were identified. A subset of samples containing age information was divided into training (n = 70) and testing (n = 12) groups to build and validate the Partial Least Square - Discriminant Analysis models for age-based classification. After internal and external validation, our models showed that 8 molecular markers unitedly provided up to 100% accuracy of prediction in distinguishing unaged (0 years), younger (0-4 years), and older (>4 years) bourbons. Additional efforts were also made to detect molecular signatures that contributed to the color differences in bourbon. Overall, our study provided a powerful strategy for the confident identification of high-quality products and robust evaluation of their commercial values.

Dynamic and Wearable Electro-responsive Hydrogel with Robust Mechanical Properties for Drug Release.

Electro-responsive dynamic hydrogels, which possess robust mechanical properties and precise spatiotemporal resolution, have a wide range of applications in biomedicine and energy science. However, it is still challenging to design and prepare electro-responsive hydrogels (ERHs) which have all of these properties. Here, we report one such class of ERHs with these features, based on the direct current voltage (DCV)-induced rearrangement of sodium dodecyl sulfate (SDS) micelles, where the rearrangement can tune the hydrogel networks that are originally maintained by the SDS micelle-assisted hydrophobic interactions. An enlarged mesh size is demonstrated for these ERHs after DCV treatment. Given the unique structure and properties of these ERHs, hydrophobic cargo (thiostrepton) has been incorporated into the hydrogels and is released upon DCV loading. Additionally, these hydrogels are highly stretchable (>6000%) and tough (507 J/m2), showing robust mechanical properties. Moreover, these hydrogels have a high spatiotemporal resolution. As the cross-links within our ERHs are enabled by the non-covalent (i.e., hydrophobic) interactions, these hydrogels are self-healing and malleable. Considering the robust mechanical properties, precise spatiotemporal resolution, dynamic nature (e.g., injectable and self-healing), and on-demand drug delivery ability, this class of ERHs will be of great interest in the fields of wearable bioelectronics and smart drug delivery systems.

Transcriptional and open chromatin analysis of bovine skeletal muscle development by single-cell sequencing.

Skeletal muscle is a complex heterogeneous tissue and characterizing its cellular heterogeneity and transcriptional and epigenetic signatures are important for understanding the details of its ontogeny. In our study, we applied scRNA-seq and scATAC-seq to investigate the cell types, molecular features, transcriptional and epigenetic regulation, and patterns of developing bovine skeletal muscle from gestational, lactational and adult stages. Detailed molecular analyses were used to dissect cellular heterogeneity, and we deduced the differentiation trajectory of myogenic cells and uncovered their dynamic gene expression profiles. SCENIC analysis was performed to demonstrate key regulons during cell fate decisions. We explored the future expression states of these heterogeneous cells by RNA velocity analysis and found extensive networks of intercellular communication using the toolkit CellChat. Moreover, the transcriptomic and chromatin accessibility modalities were confirmed to be highly concordant, and integrative analysis of chromatin accessibility and gene expression revealed key transcriptional regulators acting during myogenesis. In bovine skeletal muscle, by scRNA-seq and scATAC-seq analysis, different cell types such as adipocytes, endothelial cells, fibroblasts, lymphocytes, monocytes, pericyte cells and eight skeletal myogenic subpopulations were identified at the three developmental stages. The pseudotime trajectory exhibited a distinct sequential ordering for these myogenic subpopulations and eight distinct gene clusters were observed according to their expression pattern. Moreover, specifically expressed TFs (such as MSC, MYF5, MYOD1, FOXP3, ESRRA, BACH1, SIX2 and ATF4) associated with muscle development were predicted, and likely future transcriptional states of individual cells and the developmental dynamics of differentiation among neighbouring cells were predicted. CellChat analysis on the scRNA-seq data set then classified many ligand-receptor pairs among these cell clusters, which were further categorized into significant signalling pathways, including BMP, IGF, WNT, MSTN, ANGPTL, TGFB, TNF, VEGF and FGF. Finally, scRNA-seq and scATAC-seq results were successfully integrated to reveal a series of specifically expressed TFs that are likely to be candidates for the promotion of cell fate transition during bovine skeletal muscle development. Overall, our results outline a single-cell dynamic chromatin/transcriptional landscape for normal bovine skeletal muscle development; these provide an important resource for understanding the structure and function of mammalian skeletal muscle, which will promote research into its biology.