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Background During maturation, spermatozoa acquire motility and fertilizing capacity as they transit through the epididymis. In recent years, two-dimensional gel electrophoresis has been employed in proteomics studies conducted in rat, boar and human. However, there has not been a complete information regarding the proteins associated with sperm maturation in the epididymis. In this study, we employed iTRAQ proteomics to investigate proteins associated with sperm maturation between yak and cattleyak epididymis. Results After a successful sampling and protein extraction, the iTRAQ coupled with LC-MS/MS mass spectrometry and bioinformatics analysis were performed. We identified 288 differentially abundant proteins (DAPs) between yak and cattleyak epididymis; 151 were up-regulated while 137 were down-regulated in cattleyak relative to yak. Gene Ontology analysis identified that down-regulated DAPs in cattleyak were mostly enriched in the acetylation of protein component, along with negative and positive regulatory activities. iTRAQ proteomics data showed that the top up-regulated DAPs were mainly enriched in cell communication, cell adhesion, cytoskeleton organization, stress response, post-translational modifications and metabolic functions while the down-regulated DAPs were predominantly associated with sperm maturation, long-term sperm storage, sperm forward motility, sperm-oocyte fusion and regulatory functions. Conclusion These results provide insight into the molecular mechanisms underlying male cattleyak sterility.

This study aimed to clone the full-length open reading frame (ORF) of goat ANGPTL8 gene sequence, reveal its molecular and expression characteristics, and explore its effect on the differentiation of goat intramuscular preadipocytes. The full-length ORF sequence of goat ANGPTL8 gene was cloned by RT-PCR technology, and bioinformatics analysis was performed by related biological software. RT-qPCR was used to detect the expression of ANGPTL8 mRNA in goat tissues. Further use of RNA interference to study the effect of ANGPTL8 on the differentiation of goat intramuscular preadipocytes. The total length of the ANGPTL8 gene nucleotide sequence is 717 bp, including 597 bp of ORF, encoding 198 amino acids. Goat ANGPTL8 has the closest relationship with sheep, it was widely expressed in different tissues, and relatively enriched in liver. The silence of ANGPTL8 inhibited the accumulation of lipid droplets by 5.76% in goat intramuscular preadipocytes (p > 0.05) and significantly suppressed the expression of the genes related to preadipocytes differentiation, fatty acid synthesis and transport (p＜0.05 or p＜0.01). These data illuminate the speculation that ANGPTL8 may involve in the lipid accumulation regulation via the control of PPARγ and C/EBPβ in goat adipocytes.

Adipocyte differentiation, which plays an important role in fat deposition, involves a complex molecular mechanism. MicroRNAs (miRNAs) are essential in this progress. Here, we showed that miR-25-3p expression had increased during goat intramuscular preadipocyte differentiation, which peaked at day 3. Using liposome transfection and qRT-PCR techniques, we found that knocking down miR-25-3p reduced the accumulation of lipid droplets by downregulating or upregulating the expression of LPL, PPARγ, AP2, SREBP1, and C/EBPβ but upregulating the expression of KLF4. Overexpression of miR-25-3p results in the opposite. Furthermore, the dual luciferase assay showed that overexpression of miR-25-3p significantly inhibited luciferase activity of KLF4. These results showed that miR-25-3p has a binding site within the 3′-UTR of KLF4 mRNA. Together, these findings indicate that miR-25-3p is a positive regulator of intramuscular preadipocyte differentiation via targeting to KLF4 in goats.

As an alternative to pharmacological treatment to diseases, lifestyle interventions, such as dietary changes and physical activities, can help maintain healthy metabolic conditions. Recently, the emerging analyses of volatile organic compounds (VOCs) from breath and short-chain fatty acids (SCFAs) from plasma/feces have been considered as useful tools for the diagnosis and mechanistic understanding of metabolic diseases. Furthermore, diet-induced changes of SCFAs in individuals with diagnosed metabolic abnormalities have been correlated with the composition changes of the gut microbiome. More interestingly, the analysis of exhaled breath (breathomics) has gained attention as a useful technique to measure the human VOC profile altered as a result of dietary interventions. In this mini-review, we examined recent clinical trials that performed promising dietary interventions, SCFAs analysis in plasma/feces, and VOC profile analysis in exhaling breath to understand the relationship between dietary intervention and metabolic health.

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma; 40% of patients relapse after a complete response or are refractory to therapy. To survive, the activated B-cell (ABC) subtype of DLBCL relies upon B-cell receptor signaling, which can be modulated by the activity of Bruton tyrosine kinase (BTK). Targeting BTK with ibrutinib, an inhibitor, provides a therapeutic approach for this subtype of DLBCL. However, non-Hodgkin lymphoma is often resistant to ibrutinib or acquires resistance soon after exposure. We explored how this resistance develops. We generated 3 isogenic ibrutinib-resistant DLBCL cell lines and investigated the deregulated pathways known to be associated with tumorigenic properties. Reduced levels of BTK and enhanced phosphatidylinositol 3-kinase (PI3K)/AKT signaling were hallmarks of these ibrutinib-resistant cells. Upregulation of PI3K-β expression was demonstrated to drive resistance in ibrutinib-resistant cells, and resistance was reversed by the blocking activity of PI3K-β/δ. Treatment with the selective PI3K-β/δ dual inhibitor KA2237 reduced both tumorigenic properties and survival-based PI3K/AKT/mTOR signaling of these ibrutinib-resistant cells. In addition, combining KA2237 with currently available chemotherapeutic agents synergistically inhibited metabolic growth. This study elucidates the compensatory upregulated PI3K/AKT axis that emerges in ibrutinib-resistant cells.

In metabolomics, identification of metabolic pathways altered by disease, genetics, or environmental perturbations is crucial to uncover the underlying biological mechanisms. A number of pathway analysis methods are currently available, which are generally based on equal-probability, topological-centrality, or model-separability methods. In brief, prior identification of significant metabolites is needed for the first two types of methods, while each pathway is modeled separately in the model-separability-based methods. In these methods, interactions between metabolic pathways are not taken into consideration. The current study aims to develop a novel metabolic pathway identification method based on multi-block partial least squares (MB-PLS) analysis by including all pathways into a global model to facilitate biological interpretation. The detected metabolites are first assigned to pathway blocks based on their roles in metabolism as defined by the KEGG pathway database. The metabolite intensity or concentration data matrix is then reconstructed as data blocks according to the metabolite subsets. Then, a MB-PLS model is built on these data blocks. A new metric, named the pathway importance in projection (PIP), is proposed for evaluation of the significance of each metabolic pathway for group separation. A simulated dataset was generated by imposing artificial perturbation on four pre-defined pathways of the healthy control group of a colorectal cancer study. Performance of the proposed method was evaluated and compared with seven other commonly used methods using both an actual metabolomics dataset and the simulated dataset. For the real metabolomics dataset, most of the significant pathways identified by the proposed method were found to be consistent with the published literature. For the simulated dataset, the significant pathways identified by the proposed method are highly consistent with the pre-defined pathways. The experimental results demonstrate that the proposed method is effective for identification of significant metabolic pathways, which may facilitate biological interpretation of metabolomics data.

Retinoid X receptor α (RXRα) is thought to be a key regulator in lipid metabolism, glucose metabolism, adipogenic differentiation, gene expression, and inflammatory response. However, it is not clear whether RXRα has any role in intramuscular preadipocyte of goat. In the current investigation, we report that adenovirus overexpression of RXRα promotes lipid accumulation in intramuscular adipocyte and up-regulates the expression of positive indicator genes (PPARγ and GLUT4). Next, knockdown of RXRα does not affect adipogenesis of intramuscular adipocyte. This phenomenon may be caused by the compensatory increase of RXRγ. In addition, we found that KLF8 mediates the positive role of RXRα. Knockdown of KLF8 by siRNA attenuated the effect of RXRα on adipocyte differentiation. Importantly, the promoter activity of KLF8 is enhanced when overexpression of RXRα. Taken together, our data suggest that RXRα promotes the differentiation of intramuscular preadipocytes in goat through targeting KLF8, but it could be replaced by RXRγ. These results provide new insights into the quality improvement of goat meat.

Intramuscular fat (IMF) deposition is a complicated process, and most of the underlying regulators of this biological process are unknown. Here, we cloned the intact CDS of KLF4 gene, investigated the role of KLF4 by gaining or losing function in vitro and further explored the pathways of KLF4 regulating differentiation of intramuscular preadipocytes in goat. Our results show that goat KLF4 gene consists of 1,536 bp encoding a protein of 486 amino acids. The expression of KLF4 is higher in the lung while lower in the heart and muscle in goat. Knockdown of KLF4 mediated by siRNA technique significantly promotes intramuscular preadipocyte lipid accumulation and upregulates mRNA expression of adipogenic related genes including C/EBPα, C/EBPβ, and PPARγ in vivo cultured cells. Consistently, overexpression of KLF4 inhibits intramuscular adipocyte lipid accumulation and significantly downregulation gene expression of C/EBPβ, PPARγ, aP2, and Pref-1. Further, we found that other members of KLFs were upregulated or downregulated after interference or overexpression of KLF4, including KLF2 and KLF5–7. We also found that C/EBPβ was a potential target of KLF4, because it had an opposite expression pattern with KLF4 during the differentiation of intramuscular preadipocytes and had putative binding sites of KLF4. The dual-luciferase reporter assay indicated that overexpression of KLF4 inhibited the transcriptional activity of C/EBPβ. These results demonstrate that KLF4 inhibits the differentiation of intramuscular preadipocytes in goat by targeting C/EBPβ.

Resistin (RETN) is a hormone secreted by adipocytes, which plays an important role in glucose and lipid metabolism. The aim of this study is to clone and obtain the full length open reading frame (ORF) of goat RETN gene sequence, and to reveal its molecular and expression characteristics. Simultaneously, we explore its effect on the differentiation of intramuscular preadipocytes in goat. The full length ORF sequence of goat RETN gene was cloned by RT-PCR technique, and bioinformatics analysis was performed though relevant biological softwares. In this study, the expression of RETN mRNA in goat tissues and intramuscular preadipocytes during differentiation was detected by qPCR technique. Furthermore, RNA interference was used to explore the effects of RETN on intramuscular preadipocytes differentiation in goat. The results showed that the cloned goat RETN gene sequence was 428 bp in length, of which the ORF was 330 bp, encoding 109 amino acids. Sequence analysis revealed that it had 12 phosphorylation sites and an O-glycosylation site, and its protein contained a signal peptide sequence. Also, the RETN gene is expressed in goat various analyzed tissues, and the results showed that the expression of RETN gene in lung tissue was higher than that in other analyzed tissues of goat (p

Chemerin is a cytokine secreted by adipose cells and plays an important regulatory role in adipocyte differentiation and lipid metabolism. However, the function of Chemerin on intramuscular fat (IMF) deposition is still unknown in goat. Here, we cloned the cDNA of goat Chemerin gene using quantitative real-time PCR (qRT-PCR) technique and further clarified the expression pattern of Chemerin in various tissues of goat. The siRNA against Chemerin were synthesized to explore the potential role in intramuscular preadipocyte differentiation of goat. Our results showed that the full-length open reading frame (ORF) of Chemerin was 489 bp encoding 162 amino acids, mainly expressed in liver and Kidney. The interference of Chemerin significantly inhibited the differentiation of goat intramuscular preadipocyte and down-regulated significantly the expression levels of adipogenic marker genes LPL, AP2, SREBP1, PPARγ, C/EBPα, and C/EBPβ. These data suggest that Chemerin is a positive regulator of lipogenesis in goat intramuscular preadipocytes. Interestingly, the temporal expression pattern of Chemerin was similar to CMKLR1 during preadipocytre differentiation. These results will facilitate the research on the action of Chemerin gene in goat intramuscular fat deposition.

Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma (NHL). B-cell NHLs rely on Bruton’s tyrosine kinase (BTK) mediated B-cell receptor signaling for survival and disease progression. However, they are often resistant to BTK inhibitors or soon acquire resistance after drug exposure resulting in the drug-tolerant form. The drug-tolerant clones proliferate faster, have increased metabolic activity, and shift to oxidative phosphorylation, however, how this metabolic programming occurs in the drug-resistant tumor is poorly understood. In this study, we explored for the first time the metabolic regulators of ibrutinib-resistant activated B-cell (ABC) DLBCL using a multi-omics analysis that integrated metabolomics (using high-resolution mass spectrometry) and transcriptomic (gene expression analysis). Overlay of the unbiased statistical analyses, genetic perturbation, and pharmaceutical inhibition was further used to identify the key players contributing to the metabolic reprogramming of the drug-resistant clone. Gene-metabolite integration revealed interleukin four induced 1 (IL4I1) at the crosstalk of two significantly altered metabolic pathways involved in producing various amino acids. We showed for the first time that drug-resistant clones undergo metabolic reprogramming towards oxidative phosphorylation and are modulated via the BTK-PI3K-AKT-IL4I1 axis. Our report shows how these cells become dependent on PI3K/AKT signaling for survival after acquiring ibrutinib resistance and shift to sustained oxidative phosphorylation, additionally, we outline the compensatory pathway that might regulate this metabolic reprogramming in the drug-resistant cells. These findings from our unbiased analyses highlight the role of metabolic reprogramming during drug resistance development. Our work demonstrates that a multi-omics approach can be a robust and impartial strategy to uncover genes and pathways that drive metabolic deregulation in cancer cells.

Nutrient-dense dairy foods are an important component of a healthy diet. Recommendations, however, advise non- and low-fat dairy foods despite controversy concerning whether full-fat dairy foods adversely impact cardiometabolic health. Therefore, in this study, our objective is to examine the differential plasma lipidomic responses to non-fat or full-fat milk ingestion during postprandial hyperglycemia. Seven adults with prediabetes completed a randomized cross-over study in which glucose was consumed alone or with non-fat or full-fat dairy milk. Plasma samples collected at 90 min and 180 min post milk ingestion were used to perform untargeted lipidomics analysis. A total of 332 lipids from 20 classes and five lipid categories were detected at different time points during the postprandial period. Dairy milk, especially non-fat milk, protected against lipid changes otherwise induced by glucose ingestion. Co-ingestion of dairy milk with glucose, regardless of fat content, significantly altered lipid profiles although full-fat milk more substantially modulated lipid profiles. For the identified lipid biomarkers, 68.0% and 66.7% of the lipids significantly increased at 90 and 180 min, respectively, while phosphatidylcholines (GPs) contributed most for the significant increase. Comparative lipidomics analysis indicated that both types of dairy milk induced significant changes in several lipid pathways, including glycerophospholipid metabolism and α-linolenic acid metabolism, to protect against postprandial hyperglycemia. In summary, our comparative lipidomics results suggested that dairy milk-mediated lipid modulation may be an effective dietary approach to reduce the risk of metabolic diseases among those with prediabetes.

Hepatocellular carcinoma (HCC) that is triggered by metabolic defects is one of the most malignant liver cancers. A much higher incidence of HCC among men than women suggests the protective roles of estrogen in HCC development and progression. To begin to understand the mechanisms involving estrogenic metabolic effects, we compared cell number, viability, cytotoxicity, and apoptosis among HCC-derived HepG2 cells that were treated with different concentrations of 2-deoxy-d-glucose (2-DG) that blocks glucose metabolism, oxamate that inhibits lactate dehydrogenase and glycolysis, or oligomycin that blocks ATP synthesis and mitochondrial oxidative phosphorylation. We confirmed that HepG2 cells primarily utilized glycolysis followed by lactate fermentation, instead of mitochondrial oxidative phosphorylation, for cell growth. We hypothesized that estrogen altered energy metabolism via its receptors to carry out its anticancer effects in HepG2 cells. We treated cells with 17β-estradiol (E2), 1,3,5-tris(4-hydroxyphenyl)-4-propyl-1H-pyrazole (PPT) an estrogen receptor (ER) α (ERα) agonist, or 2,3-bis(4-hydroxyphenyl)-propionitrile (DPN), an ERβ agonist. We then used transcriptomic and metabolomic analyses and identified differentially expressed genes and unique metabolite fingerprints that are produced by each treatment. We further performed integrated multi-omics analysis, and identified key genes and metabolites in the gene–metabolite interaction contributed by E2 and ER agonists. This integrated transcriptomic and metabolomic study suggested that estrogen acts on estrogen receptors to suppress liver cancer cell growth via altering metabolism. This is the first exploratory study that comprehensively investigated estrogen and its receptors, and their roles in regulating gene expression, metabolites, metabolic pathways, and gene–metabolite interaction in HCC cells using bioinformatic tools. Overall, this study provides potential therapeutic targets for future HCC treatment.

Milk fatty acids secreted by the mammary gland are one of the most important determinants of the nutritional value of goat milk. Unlike cow milk, limited data are available on the transcriptome-wide changes across stages of lactation in dairy goats. In this study, goat mammary gland tissue collected at peak lactation, cessation of milking, and involution were analyzed with digital gene expression (DGE) sequencing to generate longitudinal transcript profiles. A total of 51,299 unigenes were identified and further annotated to 12,763 genes, of which 9,131 were differentially expressed across various stages of lactation. Most abundant genes and differentially expressed genes (DEGs) were functionally classified through clusters of euKaryotic Orthologous Groups (KOG), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. A total of 16 possible expression patterns were uncovered, and 13 genes were deemed novel candidates for regulation of lactation in the goat: POLG, SPTA1, KLC, GIT2, COPS3, PDP, CD31, USP16/29/37, TLL1, NCAPH, ABI2, DNAJC4, and MAPK8IP3. In addition, PLA2, CPT1, PLD, GGA, SRPRB, and AP4S1 are proposed as novel and promising candidates regulating mammary fatty acid metabolism. "Butirosin and neomycin biosynthesis" and "Glyoxylate and dicarboxylate metabolism" were the most impacted pathways, and revealed novel metabolic alterations in lipid metabolism as lactation progressed. Overall, the present study provides new insights into the synthesis and metabolism of fatty acids and lipid species in the mammary gland along with more detailed information on molecular regulation of lactogenesis. The major findings will benefit efforts to further improve milk quality in dairy goats.

Intramuscular fat (IMF) content determined by the intramuscular preadipocytes differentiation has a huge influence on the sensory quality traits of meats. It was reported that the adiponectin (ADIPOQ) gene could promote adipocytes differentiation, but the underlying molecular and functional characterization of the ADIPOQ for regulating goat IMF deposition remained unknown. Herein, the knockdown of ADIPOQ was mediated by siRNAs during goat intramuscular preadipocytes differentiation. Also, the qRT-PCR technique was performed to detect the mRNA levels of target genes in multiply experiment groups. These results showed that the ADIPOQ was expressed more than ∼400 folds in subcutaneous adipose tissue compared to that of heart tissue, and the mRNA level of ADIPOQ reached a peak at Hour 60 during the differentiation process, while at Hour 36 did ADIPOR1 and ADIPOR2. Moreover, the knockdown of ADIPOQ promoted the intramuscular preadipocytes differentiation and accelerated the lipid accumulation in the mature adipocytes with down-regulating the ADIPOR1 and preadipocyte factor 1 (Pref-1) mRNA levels and up-regulating the mRNA expression levels of the CAAT/enhancer-binding proteins (C/EBPs) and transcription factor peroxisomal proliferator-activated receptor γ (PPARγ), etc. Our study will provide a new opposite insight that the inhibition of ADIPOQ expression during intramuscular preadipocytes differentiation promotes goat IMF deposition.

Gut microbiota plays essential roles in maintaining gut homeostasis. The composition of gut microbes and their metabolites are altered in response to diet and remedial agents such as antibiotics. However, little is known about the effect of antibiotics on the gut microbiota and their volatile metabolites. In this study, we evaluated the impact of a moderate level of ampicillin treatment on volatile fatty acids (VFAs) of gut microbial cultures using an optimized real-time secondary electrospray ionization coupled with high-resolution mass spectrometry (SESI-HRMS). To evaluate the ionization efficiency, different types of electrospray solvents and concentrations of formic acid as an additive (0.01, 0.05, and 0.1%, v/v) were tested using VFAs standard mixture (C2–C7). As a result, the maximum SESI-HRMS signals of all studied m/z values were observed from water with 0.01% formic acid than those from the aqueous methanolic solutions. Optimal temperatures of sample inlet and ion chamber were set at 130 °C and 85 °C, respectively. SESI spray pressure at 0.5 bar generated the maximum intensity than other tested values. The optimized SESI-HRMS was then used for the analysis of VFAs in gut microbial cultures. We detected that the significantly elevated C4 and C7 VFAs in the headspace of gut microbial cultures six hours after ampicillin treatment (1 mg/L). In conclusion, our results suggested that the optimized SESI-HRMS method can be suitable for the analysis of VFAs from gut microbes in a rapid, sensitive, and non-invasive manner.

KLF9 is reported to promote adipocyte differentiation in 3T3-L1 cells and pigs. However, the roles of KLF9 in adipocytes differentiation of goat remain unknown. In this study, the expression profiles of KLF9 were different between subcutaneous and intramuscular preadipocytes of goat during differentiation process. After silencing KLF9 gene, the lipid droplets were increased in both two types of adipocytes. In subcutaneous preadipocyte with silencing KLF9, the expressions of C/EBPβ, PPARγ, LPL, KLF1-2, KLF5, and KLF17 genes were up-regulated, while KLF12, KLF4, and KLF13 genes were down-regulated in expression level. In intramuscular preadipocyte, aP2, C/EBPα, KLF2-3, KLF5, and KLF7 gene were up-regulated, and Pref-1 gene was down-regulated. In addition, the binding sites of KLF9 existed in the promoters of aP2, C/EBPα, C/EBPβ, LPL and Pref-1. Taken together, KLF9 play a negative role in the differentiation of both intramuscular and subcutaneous preadipocytes in goats, but the functional mechanism may be different.

Gut microbiome plays fundamental roles in host physiology, and gut microbial metabolism is important to the host-microbiome homeostasis. As major contributors to gut microbial metabolism, the medium nutritional components are essential to in vitro gut microbiome growths, and four nutrients, namely, inorganic salts, bile salts, short-chain fatty acids (SCFAs), and mucin, have gained particular attention because of their significant variation found in different growth environments and their ability to modulate the gut microbial population and functions. However, a systematic study is lacking to evaluate the effects of these four nutrients on the gut microbiome in terms of their impact on the microbial metabolic profiles. To fill the gap of the knowledge, we applied mass-spectrometry-based targeted metabolomics approach to study the regulation effects of these four medium components on in vitro-cultured gut microbiota. Our results show that inorganic salts and mucin had the greatest impacts on the gut microbiome metabolic profile compared to the other components studied, with gut microbial cultures grown with low-concentration inorganic salts and mucin-supplemented medium demonstrating greater numbers of metabolites detected. We also applied metabolic pathway impact analysis, which revealed several significantly impacted metabolic pathways during the comparison of different medium supplements, which could further assist our understanding of the overall impacts of certain critical nutrients on gut microbial metabolism. In summary, this pilot study can serve as a first attempt to evaluate the individual nutritional component in their contribution to gut microbial metabolic functions.

The human gut microbiome plays a central role in human health, and has been implicated in the development of a number of chronic gastrointestinal and systemic diseases. For example, microorganisms can serve as microbial endocrine mediators and can respond to stimuli and produce neurochemicals, ultimately influencing the brain-gut-microbiome axis of their host, a bidirectional communication system between the central nervous system and the gastrointestinal tract, especially during developmental stages. To begin to explore potential dynamic changes of the gut microbiome, we characterized gut microbiota in adolescent rats that underwent a fixed period of restraint stress, examined whether the gut microbial population and their metabolic functions were changed by stress, and if such changes during adolescence persist or recover in young adulthood. Integrated 16S ribosomal DNA sequencing and liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) based metabolic profiling were utilized to discover any significant differences in gut microbial genus and microbial metabolites immediately at the end of the chronic restraint stress and three weeks after the stress treatment, compared to control rats that did not receive stress treatment. Interestingly, while adolescent chronic stress-induced differences in relative microbial abundance (i.e., microbial species and distribution) disappeared three weeks after the stress treatment ended, the differences in microbial metabolic profiles persisted into adulthood. In addition, a number of significantly altered metabolites and their correlated gut microbes detected in our study facilitated a possible connection between gut microbiota and host stress response, which can be further investigated in the future to study the causal relationship between gut microbial metabolites and their impact on human health.

Lactobacillus , the major genus of lactic acid bacteria group, plays functional roles in the human body, for example, convert sugars to lactic acid. They are the significant microbiota which can be found at a number of human body sites, such as the digestive system, urinary system, and genital system . A number of Lactobacillus species are often used as probiotics and can benefit host health when administered in adequate amounts. Due to their diverse functional characteristics, it is essential to have identification and high-resolution typing techniques to support the need in health and nutritional research of Lactobacillus species. In this study, we took advantages of both targeted and untargeted metabolomic technologies by using a triple quadrupole mass spectrometer (MS) in combination with a linear ion trap-Orbitrap hybrid MS, to investigate their capability and performance in deciphering the subtle metabolic difference in four closely related Lactobacillus species/strains. First, we evaluated the selected reaction monitoring (SRM) and high-resolution MS data for metabolite quantitation. Then the acquired data quality was further evaluated via the number of metabolites detected, the coefficient variation (CV) distribution, signal intensity distribution and so on. The established platforms were eventually applied to differentiate four Lactobacillus species in identical growth conditions. The proposed workflow demonstrated the capability of targeted and untargeted metabolomics in differentiating closely related bacterial strains/species.

Aging is a major risk factor for age-related ocular diseases including age-related macular degeneration in the retina and retinal pigment epithelium (RPE), cataracts in the lens, glaucoma in the optic nerve, and dry eye syndrome in the cornea. We used targeted metabolomics to analyze metabolites from young (6 weeks) and old (73 weeks) eyes in C57 BL6/J mice. Old mice had diminished electroretinogram responses and decreased number of photoreceptors in their retinas. Among the 297 detected metabolites, 45–114 metabolites are significantly altered in aged eye tissues, mostly in the neuronal tissues (retina and optic nerve) and less in cornea, RPE/choroid, and lens. We noted that changes of metabolites in mitochondrial metabolism and glucose metabolism are common features in the aged retina, RPE/choroid, and optic nerve. The aging retina, cornea, and optic nerve also share similar changes in Nicotinamide adenine dinucleotide (NAD), 1-methylnicotinamides, 3-methylhistidine, and other methylated metabolites. Metabolites in taurine metabolism are strikingly influenced by aging in the cornea and lens. In conclusion, the aging eye has both common and tissue-specific metabolic signatures. These changes may be attributed to dysregulated mitochondrial metabolism, reprogrammed glucose metabolism and impaired methylation in the aging eye. Our findings provide biochemical insights into the mechanisms of age-related ocular changes.

Fibroblast growth factor 10 (FGF10) is an adipokine that is found to participate in the regulation of adipogenesis. However, its function remains to be elucidated in intramuscular fat (IMF) deposition of goat. The purpose of this study was to explore the role of FGF10 in goat IMF deposition. Here, we investigated the expression of FGF10 in goat intramuscular adipocytes inducing 0, 2, 4, 6 and 8 days. Effect of FGF10 on adipogenesis was investigated by gaining and losing function of FGF10 in vitro. And then, we examined several lipid metabolism-related genes, including peroxisome proliferator activated receptor γ (PPARγ), sterol regulatory element binding protein 1 (SREBP1), preadipocyte factor-1 (Pref-1), CCAAT/enhancer binding protein-α (C/EBPα) and CCAAT/enhancer binding protein-β (C/EBPβ), as well as, Krüppel-like factor (KLF) family. We found that the sharp expression of FGF10 appeared at 2 days. Overexpression of FGF10 mediated by adenovirus promotes lipid accumulation, accompanied by up-regulating of LPL and C/EBPα with the down-regulating of C/EBPβ. Conversely, the expression of LPL, C/EBPα and SREBP1 was significantly decreased by the siRNAs of FGF10. Meanwhile, we showed that FGF10 regulated the expression of many KLFs members and interacted synergistically or antagonistically with them. Thus, our results demonstrated a key role of FGF10 as a positively factor in the regulation of adipogenic differentiation of intramuscular preadipocyte in goat.

Although higher intakes of dairy milk are associated with a lower risk of metabolic syndrome (MetS), the underlying protective mechanism remains unclear. This study investigated the dynamic metabolic profile shift following the ingestion of low-fat milk or an isocaloric volume of rice milk in obese individuals with metabolic syndrome (MetS). In a randomized, double-blind, crossover study, postprandial plasma samples ( n = 266) were collected from 19 MetS participants. Plasma samples were analyzed by a targeted metabolomics platform which specifically detects 117 metabolites from 25 metabolic pathways. The comprehensive time-course metabolic profiling in MetS participants indicated that the postprandial metabolic profiles distinguish low-fat milk and rice milk consumption in a time-dependent manner. Metabolic biomarkers, such as orotate, leucine/isoleucine and adenine, showed significantly different trends in the two test beverages. Bayesian statistics identified 12 metabolites associated with clinical characteristics of postprandial vascular endothelial function, such as flow-mediated dilation (FMD), postprandial plasma markers of oxidative stress and NO status. Furthermore, metabolic pathway analysis based on these metabolite data indicated the potential utility of metabolomics to provide mechanistic insights of dietary interventions to regulate postprandial metabolic excursions.

This study examined the ability of Lactobacillus acidophilus (LA) to ferment black tea extract (BTE) and the enhancement of Escherichia coli cellular uptake of phenolic compounds when these bacteria were incubated with fermented BTE. The inhibitory effects of BTE to E. coli bacteria with and without fermentation were compared. Several intracellular phenolic compounds as well as metabolic profiles of E. coli with and without treatments were also determined using a high-performance liquid chromatography-tandem mass spectrometry-based approach. Our results showed that of three concentrations from the non-fermented BTE treatment, only the extract from the 25 mg/mL tea leaves solution could inhibit E. coli survival, while LA-fermented BTE extract from 5, 10, and 25 mg/mL tea leaves solutions all inhibited E. coli growth significantly. Intracellular concentrations of (+)-catechin-3-gallate/(-)-epicatechin-3-gallate and (+)-catechin/(-)-epicatechin were significantly higher when E. coli was treated with fermented BTE in comparison to non-fermented BTE. Scanning electron microscopy images indicated that the intracellular phenolic compounds inhibited E. coli growth by increasing endogenous oxidative stress. Metabolic profiles of E. coli were also investigated to understand their metabolic response when treated with BTE, and significant metabolic changes of E. coli were observed. Metabolic profile data were further analyzed using partial least squares discriminant analysis to distinguish the fermented BTE treatment group from the control group and the non-fermented BTE treatment group. The results indicated a large-scale E. coli metabolic dysregulation induced by the fermented BTE. Our findings showed that LA fermentation can be an efficient approach to enhance phenolic inhibition of bacterial cells through increased endogenous oxidative stress and dysregulated metabolic activities.

Microbial communities of human gut directly influence health and bear adaptive potential to different geography environment and lifestyles. However, knowledge about the influences of altitude and geography on the gut microbiota of Tibetans is currently limited. In this study, fecal microbiota from 208 Tibetans across six different locations were analyzed by MiSeq sequencing; these locations included Gannan, Gangcha, Tianzhu, Hongyuan, Lhasa and Nagqu, with altitudes above sea level ranging from 2800 m to 4500 m across the Tibetan plateau. Significant differences were observed in microbial diversity and richness in different locations. At the phylum level, gut populations of Tibetans comprised Bacteroidetes (60.00%), Firmicutes (29.04%), Proteobacteria (5.40%), and Actinobacteria (3.85%) and were marked by a low ratio (0.48) of Firmicutes to Bacteroidetes. Analysis based on operational taxonomic unit level revealed that core microbiotas included Prevotella, Faecalibacterium, and Blautia, whereas Prevotella predominated all locations, except Gangcha. Four community state types were detected in all samples, and they mainly belong to Prevotella, Bacteroides, and Ruminococcaceae. Principal component analysis and related correspondence analysis results revealed that bacterial profiles in Tibetan guts varied significantly with increasing altitude, BMI, and age, and facultative anaerobes were rich in Tibetan guts. Gut microbiota may play important roles in regulating high-altitude and geographical adaptations.

Rationale Pathogenic foodborne bacteria have been associated with severe infectious disease in humans and animals worldwide. Rapid detection and screening of these foodborne pathogens are critical for our food safety. This study aimed at detecting Escherichia coli and Staphylococcus aureus, two important foodborne bacteria, at the species and strain/serovar level using a mass spectrometry (MS)-based targeted metabolic profiling approach. Methods Ten E. coli strains (8 out of 10 were foodborne outbreak isolates) and four S. aureus strains were tested at two growth time points. A high-performance liquid chromatography/tandem mass spectrometry (HPLC/MS/MS)-based targeted metabolomics approach was applied for metabolic profile based bacteria detection. A total of 108 metabolites from multiple metabolic pathways were confidently detected from these bacteria. Results Our study demonstrated that with only 4 h of enrichment in the same medium, the metabolic profiles from E. coli and S. aureus showed significant difference. Furthermore, seven out of ten E. coli strains and all four tested S. aureus strains showed strain/serovar-level differentiation at the 4-h time point, which indicated great potential for strain level stratification in future food screening using our MS-based targeted metabolic profiling approach. Conclusions A targeted metabolomics method was developed to demonstrate the utility of HPLC/MS/MS-based metabolic profiling in rapidly (4 h) differentiating E. coli and S. aureus bacteria, two of the most notorious foodborne bacteria, at both the species and strain/serovar levels. The results indicated that our approach has great potential in the future for fast and specific detection of foodborne pathogenic bacteria based on their metabolic diversity.

Summary It is known that changes in bacterial metabolism can contribute to the modulation of bacterial susceptibility to antibiotics. Understanding how bacterial metabolism is impacted by antibiotics may improve our understanding of the antibiotic mechanism of actions from a metabolic perspective. Here, we utilized a mass spectrometry-based targeted metabolic profiling technique to characterize the metabolome of a pair of isogenic methicillin-susceptible and resistant Staphylococcus aureus (MSSA and MRSA) strains RN450 and 450M treated with the sublethal dose of three antibiotics from different classes (β-lactams, aminoglycosides and quinolones). These treatments induced a set of metabolic alterations after 6 h of co-incubation with antibiotics. Similar and divergent metabolic perturbations were observed from different antibiotics to the tested strains. Different metabolic response from MSSA and MRSA to the same antibiotics was also detected in the study and indicated the potentially different stress response mechanism in MSSA and MRSA metabolism. This work has shown that a complex set of metabolic changes can be induced by a variety of antibiotics, and the comparative metabolomics strategy can provide a good understanding of this process from a metabolic perspective.

Staphylococcus aureus is a world-wide health threat due to its prevalence and possible resistance to antibiotic treatment. A variety reasons can contribute to S. aureus antibiotic resistance and one group of phenotypes that may be discovered from S. aureus is named small-colony variants (SCVs). This study focused on applying a HPLC-MS/MS based targeted metabolic profiling approach to detect a set of metabolites that are dysregulated during S. aureus SCVs formation. Over one hundred and eighty metabolites were confidently detected and their difference between S. aureus SCVs and wild type control groups was compared via univariate and multivariate statistical analyses. Twenty metabolites, including 3',5'-cyclic AMP, tyrosine and adenine were identified as SCV specific metabolic features in comparison to the control group. Metabolic profile differences between individually isolated SCV were also observed and compared. Principal component analyses demonstrated clear metabolic profile differentiation between wild type control to SCVs. Metabolic pathway impact analysis also identified multiple metabolic pathways, including alanine, aspartate and glutamate metabolism, glycine, serine and threonine metabolism, that were significantly impacted during SCV formation. To the best of our knowledge, our study is the very first report to detect a large set of altered metabolites induced by S. aureus SCV formation. We believe our method can be used in combination with genomic, transcriptomic and proteomic approaches to achieve a better understanding of the unique physiological and metabolic changes during S. aureus SCV formation, and to assist the potential future development of targeted treatment for S. aureus SCV infections.

Both obesity and the metabolic syndrome are risk factors for type 2 diabetes and cardiovascular disease. Identification of novel biomarkers are needed to distinguish metabolic syndrome from equally obese individuals in order to direct them to early interventions that reduce their risk of developing further health problems. We utilized mass spectrometry-based targeted metabolic profiling of 221 metabolites to evaluate the associations between metabolite profiles and established metabolic syndrome criteria (i.e. elevated waist circumference, hypertension, elevated fasting glucose, elevated triglycerides, and low high-density lipoprotein cholesterol) in plasma samples from obese men ( n = 29; BMI = 35.5 ± 5.2 kg/m2) and women ( n = 40; 34.9 ± 6.7 kg/m2), of which 26 met the criteria for metabolic syndrome (17 men and 9 women). Compared to obese individuals without metabolic syndrome, univariate statistical analysis and partial least squares discriminant analysis showed that a specific group of metabolites from multiple metabolic pathways (i.e. purine metabolism, valine, leucine and isoleucine degradation, and tryptophan metabolism) were associated with the presence of metabolic syndrome. Receiver operating characteristic curves generated based on the PLS–DA models showed excellent areas under the curve (0.85 and 0.96, for metabolites only model and enhanced metabolites model, respectively), high specificities (0.86 and 0.93), and good sensitivities (0.71 and 0.91). Moreover, principal component analysis revealed that metabolic profiles can be used to further differentiate metabolic syndrome with 3 versus 4–5 metabolic syndrome criteria. Collectively, these findings support targeted metabolomics approaches to distinguish metabolic syndrome from obesity alone, and to stratify metabolic syndrome status based on the number of criteria met. Impact statement We utilized mass spectrometry-based targeted metabolic profiling of 221 metabolites to evaluate the associations between metabolite profiles and established MetS criteria. To our best knowledge, the findings of this study provide the first evidence that metabolic profiles can be used to differentiate participants with MetS from similarly obese individuals who do not meet established criteria of MetS. Furthermore, the study demonstrated that within MetS participants, their unique metabolic profiles correlated to the number of criteria used for MetS determination. Taken together, this metabolic profiling approach can potentially serve as a novel tool for MetS detection and monitoring, and provide useful metabolic information for future interventions targeting obesity and MetS.

MicroRNAs are a class of highly conserved and widely distributed non-coding RNAs. It is known that miR-26b has a high abundance in adipose tissue and is considered to be an effective regulator of adipogenesis. However, it is unclear whether miR-26b-5p, the product of miR-26b precursor, has the same effect as miR-26b. In the present study, we explored the potential role of miR-26b-5p in preadipocyte differentiation of goats. We found that the expression of miR-26b-5p had dramatic change during goat intramuscular preadipocyte differentiation. Transfection and RT-qPCR revealed that overexpression of miR-26b-5p increased the level of adipogenic marker genes and lipid accumulation in goat preadipocyte, suggesting that miR-26b-5p positively regulates goat preadipocyte differentiation. Furthermore, bioinformatics analysis and dual fluorescein reporter assays were performed to predict and validate the targets of miR-26b-5p. The results showed that miR-26b-5p has a binding site in the 3'UTR of FGF21 and overexpression of miR-26b-5p significantly down-regulated the expression of FGF21 mRNA. Luciferase activity assays confirmed that miR-26b-5p is a positive regulator of goat intramuscular preadipocyte via targeting FGF21. These findings provide reference for further revealing of the regulatory networks of goat fat metabolism and contribute to a better understanding of intramuscular fat deposition in goats.

Fibroblast growth factor 21 (FGF21) plays a critical role in the regulation of lipid metabolism; however, its function in goat intramuscular fat (IMF) deposition remains unknown. To explore the role of FGF21 for goat IMF deposition, we performed gain and loss function of FGF21 in intramuscular adipocyte. Our results showed that overexpression of FGF21 mediated by adenovirus inhibits lipid accumulation of goat intramuscular adipocyte, accompanied by down-regulating the mRNA levels of peroxisome proliferator activated receptor γ (PPARγ), adipocyte fatty acid-binding protein 2 (aP2) and sterol regulatory element-binding protein 1 (SREBP1), but up-regulating counterpart of preadipocyte factor1 (Pref1). Conversely, siRNAs knocking down FGF21 promotes the expression of PPARγ and CCAAT/enhancer binding protein-α (C/EBPα) but suppressed that of lipoprotein lipase (LPL) and Pref1. Meanwhile, we found that FGF21 regulates the expression of many KLFs transcription factors, such as KLF3, 7, 9, 11, 14, and 16. These findings demonstrate a key role of FGF21 as a negative factor in the regulation of adipogenic differentiation in goat intramuscular preadipocyte.

The balance between metabolism and biomass is very important in biological systems; however, to date there has been no quantitative method to characterize the balance. In this methodological study, we propose to use the distribution of amino acids in different domains to investigate this balance. It is well known that endogenous or exogenous amino acids in a biological system are either metabolized or incorporated into free amino acids (FAAs) or proteome amino acids (PAAs). Using glycine (Gly) as an example, we demonstrate a novel method to accurately determine the amounts of amino acids in various domains using serum, urine, and cell samples. As expected, serum and urine had very different distributions of FAA- and PAA-Gly. Using Tet21N human neuroblastoma cells, we also found that Myc(oncogene)-induced metabolic reprogramming included a higher rate of metabolizing Gly, which provides additional evidence that the metabolism of proliferating cells is adapted to facilitate producing new cells. It is therefore anticipated that our method will be very valuable for further studies of the metabolism and biomass balance that will lead to a better understanding of human cancers.

This mini-review aims to discuss the development and applications of mass spectrometry (MS)-based hybrid approaches in metabolomics. Several recently developed hybrid approaches are introduced. Then, the overall workflow, frequently used instruments, data handling strategies, and applications are compared and their pros and cons are summarized. Overall, the improved repeatability and quantitative capability in large-scale MS-based metabolomics studies are demonstrated, in comparison to either targeted or untargeted metabolomics approaches alone. In summary, we expect this review to serve as a first attempt to highlight the development and applications of emerging hybrid approaches in metabolomics, and we believe that hybrid metabolomics approaches could have great potential in many future studies.

Secondary electrospray ionization mass spectrometry (SESI-MS) is an innovative metabolomics approach that primarily focuses on the gas-phase analyte detection. In this study, we developed a secondary electrospray ionization tandem mass spectrometry (SESI-MS/MS) method with a homemade SESI-MS front end, for sensitive, reproducible and selective detection of headspace volatile organic compounds (VOCs) emitted from bacterial culture. The optimized SESI-MS/MS was applied to examine the VOC metabolome of a pair of isogenic methicillin-susceptible and resistant Staphylococcus aureus (MSSA and MRSA) strains. From the headspace of bacterial culture, twelve organic acids, and eight amino acids with the mass range of 40-300 Da were specifically targeted with two selected reaction monitoring (SRM) transitions. Our results indicated that MSSA and MRSA strains can be clearly differentiated via partial least-squares discriminant analysis (PLS-DA) based on their headspace metabolic profiles. Furthermore, we studied the stress response of MSSA and MRSA to antibiotics treatment. Our result showed that MSSA and MRSA generated dramatically changed VOC metabolic profiles in response to ampicillin, which indicated that SESI-MS/MS could also be used for antibiotic treatment response monitoring in future studies. This study showed that SESI-MS/MS VOC analysis provides an additional approach to the bacterial metabolome detection complementary to traditional aqueous phase metabolite analysis. To the best of our knowledge, this was the first time that SESI-MS/MS was applied to investigate the bacterial metabolic perturbations caused by antibiotic treatment.

Goat intramuscular fat (IMF) content is mainly determined by the processes of intramuscular preadipocytes adipogenic differentiation and mature adipocyte lipid accumulation. However, the underlying regulators of these biological processes remain largely unknown. Here, we report that the expression of Liver X receptor alpha (LXR&alpha, ) reaches a peak at early stage and then gradually decreases during goat intramuscular adipogenesis. Knockdown of LXR&alpha, mediated by two independent siRNAs significantly inhibits intramuscular adipocytes lipid accumulation and upregulates preadipocytes marker- preadipocyte factor 1 (pref1) expression. Consistently, siRNA treatments robustly decrease mRNA level of adipogenic related genes, including CCAAT enhancer binding protein alpha (Cebp&alpha, ), Peroxisome proliferator activated receptor gamma (Pparg), Sterol regulatory element binding protein isoform 1c (Srebp1c), Fatty acids binding protein (aP2) and Lipoprotein lipase (Lpl). Next, adenovirus overexpression of LXR&alpha, does not affect intramuscular adipocytes adipogenesis manifested by Oil Red O signal measurement and adipogenic specific genes detection. Mechanically, we found that both CCAAT enhancer binding protein beta (Cebp&beta, ) and Kruppel like factor 8 (Klf8) are potential targets of LXR&alpha, indicated by having putative binding sites of LXR&alpha, at the promoter of these genes and similar expression pattern during adipogenesis comparing to LXR&alpha, Importantly, mRNA levels of Cebp&beta, and Klf8 are downregulated significantly in goat LXR&alpha, knockdown intramuscular adipocyte. These results demonstrate that loss function of LXR&alpha, inhibits intramuscular adipogenesis possibly through down-regulation of Cebp&beta, and Klf8. Our research will provide new insights into mechanical regulation of goat IMF deposition.

Gut-derived endotoxin translocation provokes obesity by inducing TLR4/NFκB inflammation. We hypothesized that catechin-rich green tea extract (GTE) would protect against obesity-associated TLR4/NFκB inflammation by alleviating gut dysbiosis and limiting endotoxin translocation. Male C57BL/6J mice were fed a low-fat (LF) or high-fat (HF) diet containing 0% or 2% GTE for 8 weeks. At Week 7, fluorescein isothiocyanate (FITC)-dextran was administered by oral gavage before assessing its serum concentrations as a gut permeability marker. HF-feeding increased (P

microRNA (miRNA) are small noncoding RNA that regulate protein abundance and are involved in diverse aspects of cellular function including aspects of lipid metabolism in mammary gland of ruminants. Although our previous studies showed that the miR-26 family and its host genes control components of the cellular fatty acid metabolic machinery in goat mammary epithelial cells, a direct relationship between the miR-26 family and milk fatty acids remains unknown. Bioinformatics analysis in this study indicated that the miR-26 family targets belong to the PI3K-Akt signalling pathway, MAPK signalling pathway, and fatty acid biosynthesis pathway. Studies on the relationship of miR-26 family and their host genes with milk composition during mid-lactation revealed that the expression of the miR-26 family and their host genes were associated with total fat yield and short-chain, medium-chain and long-chain fatty acid content, but not lactose or milk protein content. In addition, a significant positive correlation was detected for the expression of the miR-26 family with C16:1 and C18:3 in milk fat. Taken together, our findings demonstrate that the expression of miR-26 is directly related to milk fatty acid composition and underscores the significance of miRNAs in milk fat synthesis regulation.

INTRODUCTION: Metabolomics technologies enable the identification of putative biomarkers for numerous diseases; however, the influence of confounding factors on metabolite levels poses a major challenge in moving forward with such metabolites for pre-clinical or clinical applications. OBJECTIVES: To address this challenge, we analyzed metabolomics data from a colorectal cancer (CRC) study, and used seemingly unrelated regression (SUR) to account for the effects of confounding factors including gender, BMI, age, alcohol use, and smoking. METHODS: A SUR model based on 113 serum metabolites quantified using targeted mass spectrometry, identified 20 metabolites that differentiated CRC patients (n = 36), patients with polyp (n = 39), and healthy subjects (n = 83). Models built using different groups of biologically related metabolites achieved improved differentiation and were significant for 26 out of 29 groups. Furthermore, the networks of correlated metabolites constructed for all groups of metabolites using the ParCorA algorithm, before or after application of the SUR model, showed significant alterations for CRC and polyp patients relative to healthy controls. RESULTS: The results showed that demographic covariates, such as gender, BMI, BMI(2), and smoking status, exhibit significant confounding effects on metabolite levels, which can be modeled effectively. CONCLUSION: These results not only provide new insights into addressing the major issue of confounding effects in metabolomics analysis, but also shed light on issues related to establishing reliable biomarkers and the biological connections between them in a complex disease.

At the onset of lactation, there are three distinct stages of mammary tissue development and function including mammogenesis, colostrogenesis, and lactogenesis. The mechanism of the transition from colostrogenesis to lactogenesis of Maiwa Yak is still unknown. In this study, mammary tissues from three Maiwa Yaks were collected at 1 and 30 d after parturition for transcriptome exploration using Affymetrix Bovine Genome Arrays. Comparing 1 and 30 d results, a total of 517 annotated differentially expressed genes (DEGs) were identified at the criteria of a P ≤ 0.05. The ratio of up-regulated genes to the down-regulated ones was around 1:2 (more specifically, 164:353). To depict the profile of DEGs, a dynamic impact approach (DIA) was used to analyse the microarray data based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. GO terms “fatty acid transport” and “monocarboxylic acid transport” were significantly induced during the colostrum period. The strongly impacted KEGG pa...

Incidence of esophageal adenocarcinoma (EA), an often fatal cancer, has increased sharply over recent decades. Several important risk factors (reflux, obesity, smoking) have been identified for EA and its precursor, Barrett’s esophagus (BE), but a key challenge remains in identifying individuals at highest risk, since most with reflux do not develop BE, and most with BE do not progress to cancer. Metabolomics represents an emerging approach for identifying novel biomarkers associated with cancer development. We used targeted liquid chromatography-mass spectrometry (LC-MS) to profile 57 metabolites in 322 serum specimens derived from individuals with gastroesophageal reflux disease (GERD), BE, high-grade dysplasia (HGD), or EA, drawn from two well-annotated epidemiologic parent studies. Multiple metabolites differed significantly (P

Alterations of gut bacterial metabolism play an important role in their host metabolism, and can result in diseases such as obesity and diabetes. While many factors were discovered influencing the gut bacterial metabolism, exposure to ultrafine particles (UFPs) from engine combustions were recently proposed to be a potential risk factor for the perturbation of gut bacterial metabolism, and consequentially to obesity and diabetes development. This study focused on evaluation of how UFPs from diesel engine combustions impact gut bacterial metabolism. We hypothesize that UFPs from different type of diesel (petrodiesel vs. biodiesel) will both impact bacterial metabolism, and the degree of impact is also diesel type-dependent. Targeted metabolic profiling of 221 metabolites were applied to three model gut bacteria in vitro, Streptococcus salivarius, Lactobacillus acidophilus and Lactobacillus fermentum. UFPs from two types of fuels, petrodiesel (B0) and a biodiesel blend (B20: 20% soy biodiesel/80% B0 by volume), were exposed to the bacteria and their metabolic changes were compared. For each bacterial strain, metabolites with significantly changed abundance were observed in both perturbations, and all three strains have increased number of altered metabolites detected from B20 UFPs perturbation in comparison to B0 UFPs. Multivariate statistical analysis further confirmed that the metabolic profiles were clearly different between testing groups. Metabolic pathway analyses also demonstrated several important metabolic pathways, including pathways involves amino acids biosynthesis and sugar metabolism, were significantly impacted by UFPs exposure.

This study reported metabolic profiles of three representative strains from Lactobacillus species, and explored their metabolic response to visible light exposure. We utilized strains from three Lactobacillus species, Lactobacillus acidophilus, Lactobacillus fermentum and Lactobacillus delbrueckii as our model bacteria and applied mass spectrometry base targeted metabolomics to specifically investigate 221 metabolites within multiple metabolic pathways. Similar and diverse metabolome from three tested strains were discovered. Furthermore, all three Lactobacillus strains demonstrated different metabolic profiles in comparison between light expose verse control. In all three strains, 12 metabolites were detected to have significant differences (p-value

Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical technologies.

Recently, novel bioanalytical methods, such as NMR and mass spectrometry based metabolomics approaches, have started to show promise in providing rapid, sensitive and reproducible detection of Staphylococcus aureus antibiotic resistance. Here we performed a proof-of-concept study focused on the application of HPLC-MS/MS based targeted metabolic profiling for detecting and monitoring the bacterial metabolic profile changes in response to sub-lethal levels of methicillin exposure. One hundred seventy-seven targeted metabolites from over 20 metabolic pathways were specifically screened and one hundred and thirty metabolites from in vitro bacterial tests were confidently detected from both methicillin susceptible and methicillin resistant Staphylococcus aureus (MSSA and MRSA, respectively). The metabolic profiles can be used to distinguish the isogenic pairs of MSSA strains from MRSA strains, without or with sub-lethal levels of methicillin exposure. In addition, better separation between MSSA and MRSA strains can be achieved in the latter case using principal component analysis (PCA). Metabolite data from isogenic pairs of MSSA and MRSA strains were further compared without and with sub-lethal levels of methicillin exposure, with metabolic pathway analyses additionally performed. Both analyses suggested that the metabolic activities of MSSA strains were more susceptible to the perturbation of the sub-lethal levels of methicillin exposure compared to the MRSA strains.

Serous ovarian carcinoma (OC) represents a leading cause of cancer-related death among U.S. women. Non-invasive tools have recently emerged for discriminating benign from malignant ovarian masses, but evaluation remains ongoing, without widespread implementation. In the last decade, metabolomics has matured into a new avenue for cancer biomarker development. Here, we sought to identify novel plasma metabolite biomarkers to distinguish serous ovarian carcinoma and benign serous ovarian tumor.Using liquid chromatography-mass spectrometry, we conducted global and targeted metabolite profiling of plasma isolated at the time of surgery from 50 serous OC cases and 50 serous benign controls.Global lipidomics analysis identified 34 metabolites (of 372 assessed) differing significantly (P0.05) between cases and controls in both training and testing sets, with 17 candidates satisfying FDR q0.05, and two reaching Bonferroni significance. Targeted profiling of ~150 aqueous metabolites identified a single amino acid, alanine, as differentially abundant (P0.05). A multivariate classification model built using the top four lipid metabolites achieved an estimated AUC of 0.85 (SD=0.07) based on Monte Carlo cross validation. Evaluation of a hybrid model incorporating both CA125 and lipid metabolites was suggestive of increased classification accuracy (AUC=0.91, SD=0.05) relative to CA125 alone (AUC=0.87, SD=0.07), particularly at high fixed levels of sensitivity, without reaching significance.Our results provide insight into metabolic changes potentially correlated with the presence of serous OC versus benign ovarian tumor and suggest that plasma metabolites may help differentiate these two conditions.

Short-chain fatty acids (SCFAs) are the major energy sources for ruminants and are known to regulate various physiological functions in other species. However, their roles in ruminant milk fat metabolism are still unclear. In this study, goat mammary gland epithelial cells (GMECs) were treated with 3 mmol/L acetate, propionate or butyrate for 24 h to assess their effects on lipogenesis. Data revealed that the content of triacylglycerol (TAG) and lipid droplet formation were significantly stimulated by propionate and butyrate. The expression of FABP3, SCD1, PPARG, SREBP1, DGAT1, AGPAT6 and ADRP were upregulated by propionate and butyrate treatment. In contrast, the messenger RNA (mRNA) expression of FASN and LXRα was not affected by propionate, but reduced by butyrate. Acetate had no obvious effect on the content of TAG and lipid droplets but increased the mRNA expression of SCD1 and FABP3 in GMECs. Additionally, it was observed that propionate significantly increased the relative content of mono-unsaturated fatty acids (C18:1 and C16:1) at the expense of decreased saturated fatty acids (C16:0 and C18:0). Butyrate and acetate had no significant effect on fatty acid composition. Overall, the results from this work help enhance our understanding of the regulatory role of SCFAs on goat mammary cell lipid metabolism.

Fatty acid synthase (FASN) is the key enzyme for de novo fatty acid synthesis from acetyl-CoA and malonyl-CoA. All the steps involved in fatty acid synthesis by FASN have been clearly defined in monogastrics and ruminants. However, there are no data on the mechanism of how FASN affects triglyceride synthesis. Inhibition of FASN in goat mammary epithelial cells by C75, a synthetic inhibitor of FASN activity, and shRNA markedly suppressed the accumulation of triglyceride in goat mammary epithelial cells. Meanwhile, C75 treatment significantly reduced the relative content of monounsaturated fatty acids (C16:1 and C18:1). Corresponding to the suppression of lipid accumulation, both of C75 and shRNA also decreased the mRNA expression of GPAM, AGPAT6 and DGAT2, all of which are related to triglyceride synthesis. The fact that treatment of malonyl-CoA decreased the expression of these genes is consistent with the results of shRNA treatment. Furthermore, the supplement of malonyl-CoA enhanced the suppression on GPAM, AGPAT6, LPIN1, DGAT1 and DGAT2. The results underscore the role of malonyl-CoA in inhibition of FASN in regulating triglyceride synthesis in goat mammary epithelial cells.

Background: Colorectal cancer (CRC) represents the third most prevalent cancer in the US, despite being one of the most preventable. Given the strong connection between CRC and metabolism, a number of these efforts have been made using metabolomics. Currently, the majority of metabolomics studies use either nuclear magnetic resonance (NMR) or mass spectrometry (MS) separately. However, thus far the potential of combining NMR and MS for biomarker discovery and statistical modeling is still poorly recognized and not well developed (such as the challenges of variable selection in the combined data sets). In this study we examine the potential of combining NMR and MS metabolomics for the detection of patients with either CRC or polyps. Methods: A total of 127 serum samples from three groups of age, gender, and BMI-matched subjects (CRC (N=28), polyp patients (N=44) and healthy controls (N=55)) were analyzed, and potential biomarkers were selected from backward variable elimination incorporated multi-block partial least squares-discriminant analysis (BVE-PLSDA). In each iteration, one variable was dropped out, and the remaining variables were used for PLS-DA. The variables with the highest prediction accuracy for the test samples in Monte Carlo cross validation (MCCV) were kept for the next iteration. Results: For all the three pairwise comparisons among CRC, polyps, and healthy controls, the highest classification accuracy of the NMR+MS data was obviously better than that from NMR or MS alone. For example, in the case of CRC Vs healthy controls, the NMR+MS data provided the highest classification accuracy of 0.95±0.05 after BVE, compared to 0.84±0.07 from NMR and 0.93±0.05 from MS. As expected, an excessive number of variables deteriorated statistical models, and there was an optimal number/range of variables which could produce the best statistical performance. Our approach was able to select an optimal set of metabolites for each pairwise comparison, and we achieved a comprehensive profile of altered metabolites from the combined (NMR+MS) data that were related to CRC and polyps, including those in glycolysis, the TCA cycle, amino acid metabolism, etc. Both NMR and MS detected metabolites contributed to the mixed panel of biomarker candidates, and thus both analytical platforms are very valuable methods to identify metabolic changes occurring in patients with CRC and polyps. The combined set of metabolite biomarkers should be helpful to comprehensively understand metabolite alterations of CRC and the mechanisms during disease progression. The majority of important NMR and MS metabolites were different from each other, evidencing that both NMR and MS can provide unique contributions to statistical modeling in metabolomics. Interestingly, CRC had the lowest adenosine levels while the controls had the highest levels. However, orotate (and some other metabolites) did not continuously increase or decrease from controls to polyps, and then to CRC, which indicates that disease progression could be a very complex process metabolically. Conclusions: The metabolic profiles of blood serum from CRC patients, polyps, and healthy controls were measured by NMR and LC-MS/MS and showed significant changes in metabolism with the onset of CRC. BVE-PLSDA identified optimal sets of metabolites that could be further validated for the diagnosis of CRC and polyps. The combination of NMR and MS showed significantly better statistical performance than NMR or MS alone. Therefore, we recommend the combined approach of NMR and MS through appropriate variable selection methods in metabolomics, especially for the purpose of discovering biomarker candidates. Notably, our approach is relatively universal and can be expanded to combine other analytical technologies. Citation Format: Lingli Deng, Haiwei Gu, Jiangjiang Zhu, Nagana Gowda, Danijel Djukovic, Daniel Raftery. Detecting colorectal cancer and polyps using nuclear magnetic resonance spectroscopy and mass spectrometry based metabolomics. [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr B50.