PubMed

J Anim Sci. 2023 Mar 17:skad080. doi: 10.1093/jas/skad080. Online ahead of print.ABSTRACTTwo experiments were carried out to evaluate the effects of betaine (BET) supplementation in diets with reduced net energy (NE) levels on growth performance, nutrient digestibility and serum metabolomic profiles in growing pigs. In Exp. 1, 24 growing pigs (initial body weight, BW, 30.83 ± 2.50 kg) were allotted to one of the four treatments (six replications with one pig per pen) in a 2 × 2 factorial arrangement, including two dietary NE levels (2475 [N-NE] or 2395 [R80-NE] kcal/kg) and two BET doses (0 or 1500 mg/kg). In Exp. 2, 72 growing pigs were used in a 2 × 3 factorial arrangement, including three dietary NE levels (2475 [N-NE], 2415 [R60-NE] or 2355 [R120-NE] kcal/kg) and two BET doses (0 or 1500 mg/kg). Pigs with initial BW of 31.44 ± 1.65 kg were divided to one of the six treatments (six replications with two pigs per pen). In Exp. 1, lowing NE concentrations increased average daily feed intake (ADFI) by 10.69% in pigs fed the diet without BET (P > 0.05). BET significant increased ADFI in N-NE diet (P < 0.05) but had no influence on ADFI in R80-NE diet (P > 0.05). BET enhanced the apparent digestibility of crude protein (CP), dry matter (DM), organic matter (OM), gross energy (GE) and ether extract (EE) in R80-NE diet (P < 0.05). In Exp. 2, lowing NE concentrations enhanced ADFI (P > 0.05) and decreased average daily gain (ADG) (P < 0.05). The reduction in feed intake by BET was further enhanced as NE concentrations decreased from 2415 to 2355 kcal/kg (P < 0.10). BET reversed the elevation of serum triglyceride, alkaline phosphatase, aspartate aminotransferase and alanine aminotransferase levels caused by R120-NE diet (P < 0.05). The concentrations of cholecystokinin and glucagon-like peptide 1 were increased by BET in pigs fed R120-NE diet (P < 0.05). Serum metabolomics reveals that lowing dietary NE concentrations affected mainly amino acid biosynthetic pathways (P < 0.05). BET supplementation in R120-NE diet up-regulated serum BET levels and down-regulated homocysteine, DL-carnitine and four amino acid secondary metabolites (P < 0.05). In conclusion, lowing dietary NE contents reduced the growth performance and caused metabolic abnormalities in growing pigs. However, BET decreased feed intake to a certain extent and improved the metabolic health of pigs fed low-NE diets, which may be related to the dual regulation of amino acid metabolism and the secretion of appetite related hormones by BET.PMID:36930062 | DOI:10.1093/jas/skad080

J AOAC Int. 2023 Mar 17:qsad039. doi: 10.1093/jaoacint/qsad039. Online ahead of print.ABSTRACTBACKGROUND: Schizonepetae Herba (SH, Jingjie) and Schizonepetae Herba Carbonisata (SHC, Jingjie Tan) are two different forms of the same herbal material, with SHC being the processed product of SH. The different clinical efficacies of SH and SHC may be caused by changes in their chemical compositions. Despite this, there have been few studies that have reported on the comparative identification of SH and SHC. Therefore, the aims of this experiment are to investigate the differential changes of non-volatile and volatile components before and after SH processing.OBJECTIVES: To establish combination strategies for identifying the chemical markers in SH and SHC, ultra-high-performance liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-Q-TOF-MS) and headspace gas chromatography mass spectrometry (HS-GC-MS) to use.METHODS: An untargeted metabolomics approach using UHPLC-Q-TOF-MS and HS-GC-MS was utilized to comprehensively discriminate between SH and SHC. To identify chemical markers, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed on 14 batches of SH and SHC.RESULTS: A total of 71 non-volatile compounds and 81 volatile compounds were tentatively identified in SH and SHC. Among these, 14 non-volatile compounds and 18 volatile oils were found to be potential characteristic markers that can differentiate between SH and SHC.CONCLUSIONS: The present work provides valuable information for understanding the chemical differences between SH and SHC. The results obtained from this research may serve as a scientific foundation for comprehensively revealing the mechanisms involved in the carbonizing processing method of stir-frying SH.HIGHLIGHTS: The chemical changes that occur before and after carbonizing Schizonepetae Herba were investigated using integrated methods based on LC-MS and GC-MS, and chemical markers in SH and SHC were identified.PMID:36929943 | DOI:10.1093/jaoacint/qsad039

Metabolomics. 2023 Mar 16;19(4):19. doi: 10.1007/s11306-023-01995-y.NO ABSTRACTPMID:36929444 | DOI:10.1007/s11306-023-01995-y

Methods Mol Biol. 2023;2629:247-269. doi: 10.1007/978-1-0716-2986-4_12.ABSTRACTIn this chapter, we review the cutting-edge statistical and machine learning methods for missing value imputation, normalization, and downstream analyses in mass spectrometry metabolomics studies, with illustration by example datasets. The missing peak recovery includes simple imputation by zero or limit of detection, regression-based or distribution-based imputation, and prediction by random forest. The batch effect can be removed by data-driven methods, internal standard-based, and quality control sample-based normalization. We also summarize different types of statistical analysis for metabolomics and clinical outcomes, such as inference on metabolic biomarkers, clustering of metabolomic profiles, metabolite module building, and integrative analysis with transcriptome.PMID:36929081 | DOI:10.1007/978-1-0716-2986-4_12

Methods Mol Biol. 2023;2629:1-9. doi: 10.1007/978-1-0716-2986-4_1.ABSTRACTIn the current era of multi-omics, new sequencing and molecular profiling technologies have facilitated our quest for a deeper and broader understanding of the variations and dynamic regulations in human genomes. However, analyzing and integrating data generated from diverse platforms, modalities, and large-scale heterogeneous samples to extract functional and clinically valuable information remains a significant challenge. Here, we first discuss recent advances in methods and algorithms for analyzing data at the genome, transcriptome, proteome, metabolome, and microbiome levels, followed by emerging methods for leveraging single-cell sequencing and spatial transcriptomic data. We also highlight the mechanistic insights that these advances can bring to the field, as well as the current challenges and outlooks relating to their translational and reproducible adoption at the population level. It is evident that novel statistical methods, which were inspired by new assays, will enable the associated molecular profiling pipelines and experimental designs to continuously improve our understanding of the human genome and the downstream consequences in the transcriptome, epigenome, proteome, metabolome, regulome, and microbiome.PMID:36929070 | DOI:10.1007/978-1-0716-2986-4_1

JAMA Otolaryngol Head Neck Surg. 2023 Mar 16. doi: 10.1001/jamaoto.2023.0052. Online ahead of print.ABSTRACTIMPORTANCE: Persistent tinnitus is common, disabling, and difficult to treat.OBJECTIVE: To evaluate the association between circulating metabolites and persistent tinnitus.DESIGN, SETTING, AND PARTICIPANTS: This was a population-based case-control study of 6477 women who were participants in the Nurses' Health Study (NHS) and NHS II with metabolomic profiles and tinnitus data. Information on tinnitus onset and frequency was collected on biennial questionnaires (2009-2017). For cases, metabolomic profiles were measured (2015-2021) in blood samples collected after the date of the participant's first report of persistent tinnitus (NHS, 1989-1999 and 2010-2012; NHS II, 1996-1999). Data analyses were performed from January 24, 2022, to January 14, 2023.EXPOSURES: In total, 466 plasma metabolites from 488 cases of persistent tinnitus and 5989 controls were profiled using 3 complementary liquid chromatography tandem mass spectrometry approaches.MAIN OUTCOMES AND MEASURES: Logistic regression was used to estimate odds ratios (ORs) of persistent tinnitus (per 1 SD increase in metabolite values) and 95% CIs for each individual metabolite. Metabolite set enrichment analysis was used to identify metabolite classes enriched for associations with tinnitus.RESULTS: Of the 6477 study participants (mean [SD] age, 52 [9] years; 6477 [100%] female; 6121 [95%] White individuals) who were registered nurses, 488 reported experiencing daily persistent (≥5 minutes) tinnitus. Compared with participants with no tinnitus (5989 controls), those with persistent tinnitus were slightly older (53.0 vs 51.8 years) and more likely to be postmenopausal, using oral postmenopausal hormone therapy, and have type 2 diabetes, hypertension, and/or hearing loss at baseline. Compared with controls, homocitrulline (OR, 1.32; (95% CI, 1.16-1.50); C38:6 phosphatidylethanolamine (PE; OR, 1.24; 95% CIs, 1.12-1.38), C52:6 triglyceride (TAG; OR, 1.22; 95% CIs, 1.10-1.36), C36:4 PE (OR, 1.22; 95% CIs, 1.10-1.35), C40:6 PE (OR, 1.22; 95% CIs, 1.09-1.35), and C56:7 TAG (OR, 1.21; 95% CIs, 1.09-1.34) were positively associated, whereas α-keto-β-methylvalerate (OR, 0.68; 95% CIs, 0.56-0.82) and levulinate (OR, 0.60; 95% CIs, 0.46-0.79) were inversely associated with persistent tinnitus. Among metabolite classes, TAGs (normalized enrichment score [NES], 2.68), PEs (NES, 2.48), and diglycerides (NES, 1.65) were positively associated, whereas phosphatidylcholine plasmalogens (NES, -1.91), lysophosphatidylcholines (NES, -2.23), and cholesteryl esters (NES,-2.31) were inversely associated with persistent tinnitus.CONCLUSIONS AND RELEVANCE: This population-based case-control study of metabolomic profiles and tinnitus identified novel plasma metabolites and metabolite classes that were significantly associated with persistent tinnitus, suggesting that metabolomic studies may help improve understanding of tinnitus pathophysiology and identify therapeutic targets for this challenging disorder.PMID:36928544 | DOI:10.1001/jamaoto.2023.0052

Int J Surg. 2023 Mar 17. doi: 10.1097/JS9.0000000000000006. Online ahead of print.ABSTRACTBACKGROUND: Multiple primary lung cancer (MPLC) is becoming increasingly common in clinical practice. Imaging examination is sometimes difficult to differentiate from intrapulmonary metastasis (IM) or single primary lung cancer (SPLC) before surgery. There is a lack of effective blood biomarkers as an auxiliary diagnostic method.PARTICIPANTS AND METHODS: A total of 179 patients who were hospitalized and operated in our department from January to June 2019 were collected, and they were divided into SPLC with 136 patients, MPLC with 24 patients, and IM with 19 patients. In total, 96 healthy people without lung cancer were enrolled. Medical history, imaging, and pathology data were assembled from all participants. Plasma metabolomics analysis was performed by quadrupole time-of-flight tandem mass spectrometry, and data were analyzed using SPSS19.0/Simca 14.1/MetaboAnalyst5.0 software. Significant metabolites were selected by variable importance in projection, P value, and fold change. The area under the receiver operating characteristic curve was used to evaluate their diagnostic ability.RESULTS: There were significant differences in plasma metabolite profiles between IM and MPLC. Seven metabolites were screened out. Two metabolites had higher levels in IM, and five metabolites had higher levels in MPLC. All had favorable discriminating capacity. Phosphatidyl ethanolamine (38:5) showed the highest sensitivity (0.95) and specificity (0.92). It was followed by l-histidine with sensitivity 0.92 and specificity 0.84. l-tyrosine can be used to identify SPLC and MPLC. The panel composed of related metabolites exhibited higher diagnostic ability. Eight principal metabolites caused remarkable differences between healthy people and MPLC, and five of them had area under the curves greater than 0.85, showing good discriminating power.CONCLUSION: Through the study of plasma metabolomics, it was found that there were obvious differences in the metabolite profiles of MPLC, IM, SPLC, and the healthy population. Some discovered metabolites possessed excellent diagnostic competence with high sensitivity and specificity. They had the potential to act as biomarkers for the screening and differential diagnosis of MPLCs.PMID:36928390 | DOI:10.1097/JS9.0000000000000006

NPJ Sci Food. 2023 Mar 16;7(1):7. doi: 10.1038/s41538-023-00187-1.ABSTRACTThe geographic origin of agri-food products contributes greatly to their quality and market value. Here, we developed a robust method combining metabolomics and machine learning (ML) to authenticate the geographic origin of Wuyi rock tea, a premium oolong tea. The volatiles of 333 tea samples (174 from the core region and 159 from the non-core region) were profiled using gas chromatography time-of-flight mass spectrometry and a series of ML algorithms were tested. Wuyi rock tea from the two regions featured distinct aroma profiles. Multilayer Perceptron achieved the best performance with an average accuracy of 92.7% on the training data using 176 volatile features. The model was benchmarked with two independent test sets, showing over 90% accuracy. Gradient Boosting algorithm yielded the best accuracy (89.6%) when using only 30 volatile features. The proposed methodology holds great promise for its broader applications in identifying the geographic origins of other valuable agri-food products.PMID:36928372 | DOI:10.1038/s41538-023-00187-1

AIDS. 2023 Mar 14. doi: 10.1097/QAD.0000000000003546. Online ahead of print.ABSTRACTOBJECTIVE: We aimed to determine the contribution of inflammasome activation in chronic low-grade systemic inflammation observed in patients with HIV (PWH) on long-term suppressive antiretroviral therapy (ART) and to explore mechanisms of such activation.DESIGN: Forty-two PWH on long-term suppressive ART (HIV-RNA < 40 copies/ml) were compared with 10 HIV-negative healthy controls (HC).METHODS: Inflammasome activation was measured by dosing mature interleukin (IL)-1β and IL-18 cytokines in patient serum. We explored inflammasome pathways through ex vivo stimulation of PWH primary monocytes with inflammasome activators; expression of inflammasome components by transcriptomic analysis; and metabolomics analysis of patient sera.RESULTS: Median (Q1; Q3) age, ART and viral suppression duration in PWH were 54 (48; 60), 15 (9; 20) and 7.5 (5; 12) years, respectively. Higher serum IL-18 was measured in PWH than in HC (61 (42; 77) vs. 36 (27-48 pg/ml), P = 0.009); IL-1β was detected in 10/42 PWH (0.5 (0.34; 0.80) pg/ml) but not in HC. Monocytes from PWH did not produce more inflammatory cytokines in vitro, but secretion of IL-1β in response to NLRP3 inflammasome stimulation was higher than in HC. This was not explained at the transcriptional level. We found an oxidative stress molecular profile in PWH sera.CONCLUSION: HIV infection with long-term effective ART is associated with a serum inflammatory signature, including markers of inflammasome activation, and an increased activation of monocytes upon inflammasome stimulation. Other cells should be investigated as sources of inflammatory cytokines in PWH. Oxidative stress might contribute to this chronic low-grade inflammation.PMID:36928274 | DOI:10.1097/QAD.0000000000003546

Pharmacol Rev. 2023 Mar 16:PHARMREV-AR-2022-000810. doi: 10.1124/pharmrev.122.000810. Online ahead of print.ABSTRACTPersonalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all 'omics' fields, e.g., proteomics, transcriptomics, metabolomics, and metagenomics. This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. FDA approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multi-component biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review will address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues - providing insights into the current status and future direction of health care. Significance Statement Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.PMID:36927888 | DOI:10.1124/pharmrev.122.000810

J Transl Med. 2023 Mar 16;21(1):199. doi: 10.1186/s12967-023-04050-5.ABSTRACTBACKGROUND: Increased circulating uric acid (UA) concentration may disrupt cardiac function in heart failure patients, but the specific mechanism remains unclear. Here, we postulate that hyperuremia induces sterol regulatory element binding protein 1 (SREBP1), which in turn activate hepatic fatty acid biosynthesis response, leading to cardiac dysfunction.METHODS AND RESULTS: Increased circulating uric acid was observed in heart failure patients and inversely correlated to cardiac function. Besides, uric acid correlated to circulating lipids profile based on metabolomics in heart failure patients. Using cultured human hepatoellular carcinomas (HepG2) and Tg(myl7:egfp) zebrafish, we demonstrated that UA regulated fatty acid synthase (FASN) via SREBP1 signaling pathway, leading to FFA accumulation and impaired energy metabolism, which could be rescued via SREBP1 knockdown. In ISO treated zebrafish, UA aggravated heart failure via increased cardiovascular cavity size, decreased heart beats, pericardial edema and long-stretched heart deformation.CONCLUSIONS: Our findings suggest that UA-SREBP1-FASN signaling exacerbates cardiac dysfunction during FFA accumulation. Identification of this mechanism may help in treatment and prevention of heart failure.PMID:36927819 | DOI:10.1186/s12967-023-04050-5

Arthritis Res Ther. 2023 Mar 16;25(1):42. doi: 10.1186/s13075-023-03022-w.ABSTRACTBACKGROUND: The roles of gut microbiota in the pathogenesis of SLE have been receiving much attention during recent years. However, it remains unknown how fecal microbiota transplantation (FMT) and microbial metabolites affect immune responses and lupus progression.METHODS: We transferred fecal microbiota from MRL/lpr (Lpr) mice and MRL/Mpj (Mpj) mice or PBS to pristane-induced lupus mice and observed disease development. We also screened gut microbiota and metabolite spectrums of pristane-induced lupus mice with FMT via 16S rRNA sequencing, metagenomic sequencing, and metabolomics, followed by correlation analysis.RESULTS: FMT from MRL/lpr mice promoted the pathogenesis of pristane-induced lupus and affected immune cell profiles in the intestine, particularly the plasma cells. The structure and composition of microbial communities in the gut of the FMT-Lpr mice were different from those of the FMT-Mpj mice and FMT-PBS mice. The abundances of specific microbes such as prevotella taxa were predominantly elevated in the gut microbiome of the FMT-Lpr mice, which were positively associated with functional pathways such as cyanoamino acid metabolism. Differential metabolites such as valine and L-isoleucine were identified with varied abundances among the three groups. The abundance alterations of the prevotella taxa may affect the phenotypic changes such as proteinuria levels in the pristane-induced lupus mice.CONCLUSION: These findings further confirm that gut microbiota play an important role in the pathogenesis of lupus. Thus, altering the gut microbiome may provide a novel way to treat lupus.PMID:36927795 | DOI:10.1186/s13075-023-03022-w

Nat Commun. 2023 Mar 16;14(1):1459. doi: 10.1038/s41467-023-37170-z.ABSTRACTThere has been considerable scientific effort dedicated to understanding the biologic consequence and therapeutic implications of aberrant tryptophan metabolism in brain tumors and neurodegenerative diseases. A majority of this work has focused on the upstream metabolism of tryptophan; however, this has resulted in limited clinical application. Using global metabolomic profiling of patient-derived brain tumors, we identify the downstream metabolism of tryptophan and accumulation of quinolinate (QA) as a metabolic node in glioblastoma and demonstrate its critical role in promoting immune tolerance. QA acts as a metabolic checkpoint in glioblastoma by inducing NMDA receptor activation and Foxo1/PPARγ signaling in macrophages, resulting in a tumor supportive phenotype. Using a genetically-engineered mouse model designed to inhibit production of QA, we identify kynureninase as a promising therapeutic target to revert the potent immune suppressive microenvironment in glioblastoma. These findings offer an opportunity to revisit the biologic consequence of this pathway as it relates to oncogenesis and neurodegenerative disease and a framework for developing immune modulatory agents to further clinical gains in these otherwise incurable diseases.PMID:36927729 | DOI:10.1038/s41467-023-37170-z

J Transl Med. 2023 Mar 16;21(1):198. doi: 10.1186/s12967-023-04042-5.ABSTRACTBACKGROUND: Temozolomide (TMZ) is the preferred chemotherapy strategy for glioma therapy. As a second-generation alkylating agent, TMZ provides superior oral bio-availability. However, limited response rate (less than 50%) and high incidence of drug resistance seriously restricts TMZ's application, there still lack of strategies to increase the chemotherapy sensitivity.METHODS: Luci-GL261 glioma orthotopic xenograft model combined bioluminescence imaging was utilized to evaluate the anti-tumor effect of TMZ and differentiate TMZ sensitive (S)/non-sensitive (NS) individuals. Integrated microbiomics and metabolomics analysis was applied to disentangle the involvement of gut bacteria in TMZ sensitivity. Spearman's correlation analysis was applied to test the association between fecal bacteria levels and pharmacodynamics indices. Antibiotics treatment combined TMZ treatment was used to confirm the involvement of gut microbiota in TMZ response. Flow cytometry analysis, ELISA and histopathology were used to explore the potential role of immunoregulation in gut microbiota mediated TMZ response.RESULTS: Firstly, gut bacteria composition was significantly altered during glioma development and TMZ treatment. Meanwhile, in vivo anti-cancer evaluation suggested a remarkable difference in chemotherapy efficacy after TMZ administration. Moreover, 16s rRNA gene sequencing and non-targeted metabolomics analysis revealed distinct different gut microbiota and immune infiltrating state between TMZ sensitive and non-sensitive mice, while abundance of differential gut bacteria and related metabolites was significantly correlated with TMZ pharmacodynamics indices. Further verification suggested that gut microbiota deletion by antibiotics treatment could accelerate glioma development, attenuate TMZ efficacy and inhibit immune cells (macrophage and CD8α+ T cell) recruitment.CONCLUSIONS: The current study confirmed the involvement of gut microbiota in glioma development and individualized TMZ efficacy via immunomodulation, hence gut bacteria may serve as a predictive biomarker as well as a therapeutic target for clinical TMZ application.PMID:36927689 | DOI:10.1186/s12967-023-04042-5

Biotechnol Biofuels Bioprod. 2023 Mar 16;16(1):48. doi: 10.1186/s13068-023-02296-1.ABSTRACTBACKGROUND: The exact mechanism by which fungal strains sense insoluble cellulose is unknown, but research points to the importance of transglycosylation products generated by fungi during cellulose breakdown. Here, we used multi-omics approach to identify the transglycosylation metabolites and determine their function in cellulase induction in a model strain, Talaromyces cellulolyticus MTCC25456.RESULTS: Talaromyces sp. is a novel hypercellulolytic fungal strain. Based on genome scrutiny and biochemical analysis, we predicted the presence of cellulases on the surface of its spores. We performed metabolome analysis to show that these membrane-bound cellulases act on polysaccharides to form a mixture of disaccharides and their transglycosylated derivatives. Inevitably, a high correlation existed between metabolite data and the KEGG enrichment analysis of differentially expressed genes in the carbohydrate metabolic pathway. Analysis of the contribution of the transglycosylation product mixtures to cellulase induction revealed a 57% increase in total cellulase. Further research into the metabolites, using in vitro induction tests and response surface methodology, revealed that Talaromyces sp. produces cell wall-breaking enzymes in response to cellobiose and gentiobiose as a stimulant. Precisely, a 2.5:1 stoichiometric ratio of cellobiose to gentiobiose led to a 2.4-fold increase in cellulase synthesis. The application of the optimized inducers in cre knockout strain significantly increased the enzyme output.CONCLUSION: This is the first study on the objective evaluation and enhancement of cellulase production using optimized inducers. Inducer identification and genetic engineering boosted the cellulase production in the cellulolytic fungus Talaromyces sp.PMID:36927685 | DOI:10.1186/s13068-023-02296-1

BMC Med. 2023 Mar 16;21(1):99. doi: 10.1186/s12916-023-02819-5.ABSTRACTBACKGROUND: Metabolomic changes during pregnancy have been suggested to underlie the etiology of gestational diabetes mellitus (GDM). However, research on metabolites during preconception is lacking. Therefore, this study aimed to investigate distinctive metabolites during the preconception phase between GDM and non-GDM controls in a nested case-control study in Singapore.METHODS: Within a Singapore preconception cohort, we included 33 Chinese pregnant women diagnosed with GDM according to the IADPSG criteria between 24 and 28 weeks of gestation. We then matched them with 33 non-GDM Chinese women by age and pre-pregnancy body mass index (ppBMI) within the same cohort. We performed a non-targeted metabolomics approach using fasting serum samples collected within 12 months prior to conception. We used generalized linear mixed model to identify metabolites associated with GDM at preconception after adjusting for maternal age and ppBMI. After annotation and multiple testing, we explored the additional predictive value of novel signatures of preconception metabolites in terms of GDM diagnosis.RESULTS: A total of 57 metabolites were significantly associated with GDM, and eight phosphatidylethanolamines were annotated using HMDB. After multiple testing corrections and sensitivity analysis, phosphatidylethanolamines 36:4 (mean difference β: 0.07; 95% CI: 0.02, 0.11) and 38:6 (β: 0.06; 0.004, 0.11) remained significantly higher in GDM subjects, compared with non-GDM controls. With all preconception signals of phosphatidylethanolamines in addition to traditional risk factors (e.g., maternal age and ppBMI), the predictive value measured by area under the curve (AUC) increased from 0.620 to 0.843.CONCLUSIONS: Our data identified distinctive signatures of GDM-associated preconception phosphatidylethanolamines, which is of potential value to understand the etiology of GDM as early as in the preconception phase. Future studies with larger sample sizes among alternative populations are warranted to validate the associations of these signatures of metabolites and their predictive value in GDM.PMID:36927416 | DOI:10.1186/s12916-023-02819-5

Anim Biotechnol. 2023 Mar 16:1-20. doi: 10.1080/10495398.2023.2187404. Online ahead of print.ABSTRACTIn poultry production, there has been a trend of continuous increase in cost of feed ingredients which represents the major proportion of the production costs. Feed costs can be reduced by improving feed efficiency traits which increase the possibility of using various indigestible feed sources and decrease the environmental impact of the enhanced poultry production. Therefore, feed efficiency has been used as one of the most important economic traits of selection in the breeding program of chickens. Recently, many OMICs experimental studies have been designed to characterize biological differences between the high and low feed efficiency chicken phenotypes. Biological complexity cannot be fully captured by main individual OMICs such as genomics, transcriptomics, proteomics and metabolomics. Therefore, researchers have combined multiple assays from the same set of samples to create multi-OMICs datasets. OMICs findings are crucial in improving existing approaches to poultry breeding. The current review aimed to highlight the components of feed efficiency and general OMICs approaches and technologies. Besides, individual and multi-OMICs based understanding of chicken feed efficiency traits and the application of the acquired knowledge in the chicken breeding program were addressed.PMID:36927292 | DOI:10.1080/10495398.2023.2187404

J Agric Food Chem. 2023 Mar 16. doi: 10.1021/acs.jafc.2c07945. Online ahead of print.ABSTRACTA high-carbohydrate diet (HCD) can induce excessive fat accumulation in fish, and intestinal microbiota are thought to play important roles in host metabolism. Whether and how intestinal bacteria alleviate the HCD-induced metabolic disorders in fish have attracted more attention. Bacillus cereus was isolated from the intestine content of Nile tilapia. The control diet, high-carbohydrate diet (HC), and HC supplemented with B. cereus Su1 (HCS) were used to feed juvenile Nile tilapia for 8 weeks. The results of the present study showed that B. cereus Su1 supplementation decreased the serum glucose, triglycerides (TG), and reduced hepatic lipid accumulation compared with the HC group. The intestinal bacterial composition analysis suggested that HCS elevated bacterial diversity and the enriched bacteria were closely related to bile acid (BA) metabolism. Higher bile salt hydrolase (BSH) activity was found in the HCS group and B-targeted metabolomic analysis revealed that HCS increased BA content in the intestine and liver compared with HC, including unconjugated BAs (CA and CDCA) and conjugated BAs (TCA, GCA, TCDCA, GCDCA, TDCA, and TUDCA). Furthermore, a high-carbohydrate diet supplemented with B. cereus Su1 significantly enhanced the protein expression of the BA receptor farnesoid X receptor in the liver and decreased significantly the expression level of lipid synthesis-related genes and proteins, while it had no significant effect on lipolysis-related genes and proteins. This study found that B. cereus Su1 altered the intestinal microbiota and bile acid content and composition to regulate the lipid metabolism, revealing the function of the crosstalk among probiotics, intestinal microbiota, and BAs in ameliorating lipid accumulation induced by a high-carbohydrate diet in fish.PMID:36926869 | DOI:10.1021/acs.jafc.2c07945

Indian J Med Res. 2022 Oct-Nov;156(4&5):659-668. doi: 10.4103/ijmr.ijmr_3475_21.ABSTRACTBACKGROUND & OBJECTIVES: COVID-19 has been a global pandemic since early 2020. It has diverse clinical manifestations, but consistent immunological and metabolic correlates of disease severity and protection are not clear. This study was undertaken to compare seropositivity rate, antibody levels against nucleocapsid and spike proteins, virus neutralization and metabolites between adult and child COVID-19 patients.METHODS: Plasma samples from naïve control (n=14) and reverse transcription (RT)-PCR positive COVID-19 participants (n=132) were tested for reactivity with nucleocapsid and spike proteins by ELISA, neutralization of SARS-CoV-2 infectivity in Vero cells and metabolites by [1]H nuclear magnetic resonance (NMR) spectroscopy.RESULTS: An ELISA platform was developed using nucleocapsid and spike proteins for COVID-19 serosurvey. The participants showed greater seropositivity for nucleocapsid (72%) than spike (55.3%), and males showed higher seropositivity than females for both the proteins. Antibody levels to both the proteins were higher in intensive care unit (ICU) than ward patients. Children showed lower seropositivity and antibody levels than adults. In contrast to ICU adults (81.3%), ICU children (33.3%) showed lower seropositivity for spike. Notably, the neutralization efficiency correlated with levels of anti-nucleocapsid antibodies. The levels of plasma metabolites were perturbed differentially in COVID-19 patients as compared with the naive controls.INTERPRETATION & CONCLUSIONS: Our results reflect the complexity of human immune response and metabolome to SARS-CoV-2 infection. While innate and cellular immune responses are likely to be a major determinant of disease severity and protection, antibodies to multiple viral proteins likely affect COVID-19 pathogenesis. In children, not adults, lower seropositivity rate for spike was associated with disease severity.PMID:36926783 | DOI:10.4103/ijmr.ijmr_3475_21

World J Clin Cases. 2023 Feb 26;11(6):1236-1244. doi: 10.12998/wjcc.v11.i6.1236.ABSTRACTMetabolic-associated fatty liver disease (MAFLD) refers to the build-up of fat in the liver associated with metabolic dysfunction and has been estimated to affect a quarter of the population worldwide. Although metabolism is highly influenced by the effects of sex hormones, studies of sex differences in the incidence and progression of MAFLD are scarce. Metabolomics represents a powerful approach to studying these differences and identifying potential biomarkers and putative mechanisms. First, metabolomics makes it possible to obtain the molecular phenotype of the individual at a given time. Second, metabolomics may be a helpful tool for classifying patients according to the severity of the disease and obtaining diagnostic biomarkers. Some studies demonstrate associations between circulating metabolites and early and established MAFLD, but little is known about how metabolites relate to and encompass sex differences in disease progression and risk management. In this review, we will discuss the epidemiological metabolomic studies for sex differences in the development and progression of MAFLD, the role of metabolic profiles in understanding mechanisms and identifying sex-dependent biomarkers, and how this evidence may help in the future management of the disease.PMID:36926130 | PMC:PMC10013124 | DOI:10.12998/wjcc.v11.i6.1236