PubMed

EMBO J. 2023 May 4:e112712. doi: 10.15252/embj.2022112712. Online ahead of print.ABSTRACTcGAS-STING signalling is induced by detection of foreign or mislocalised host double-stranded (ds)DNA within the cytosol. STING acts as the major signalling hub, where it controls production of type I interferons and inflammatory cytokines. Basally, STING resides on the ER membrane. Following activation STING traffics to the Golgi to initiate downstream signalling and subsequently to endolysosomal compartments for degradation and termination of signalling. While STING is known to be degraded within lysosomes, the mechanisms controlling its delivery remain poorly defined. Here we utilised a proteomics-based approach to assess phosphorylation changes in primary murine macrophages following STING activation. This identified numerous phosphorylation events in proteins involved in intracellular and vesicular transport. We utilised high-temporal microscopy to track STING vesicular transport in live macrophages. We subsequently identified that the endosomal complexes required for transport (ESCRT) pathway detects ubiquitinated STING on vesicles, which facilitates the degradation of STING in murine macrophages. Disruption of ESCRT functionality greatly enhanced STING signalling and cytokine production, thus characterising a mechanism controlling effective termination of STING signalling.PMID:37139896 | DOI:10.15252/embj.2022112712

J Investig Med. 2023 May 4:10815589231169452. doi: 10.1177/10815589231169452. Online ahead of print.ABSTRACTThe therapeutic response heterogeneity in acromegaly persists, despite the medical-surgical advances of recent years. Thus, personalized medicine implementation, which focuses on each patient, is justified. Metabolomics would decipher the molecular mechanisms underlying the therapeutic response heterogeneity. Identification of altered metabolic pathways would open new horizons in the therapeutic management of acromegaly. This research aimed to evaluate the metabolomic profile in acromegaly and metabolomics' contributions to understanding disease pathogenesis. A systematic review was carried out by querying four electronic databases and evaluating patients with acromegaly through metabolomic techniques. In all, 21 studies containing 362 patients were eligible. Choline, the ubiquitous metabolite identified in growth hormone (GH)-secreting pituitary adenomas (Pas) by in vivo magnetic resonance spectroscopy (MRS), negatively correlated with somatostatin receptors type 2 expression and positively correlated with magnetic resonance imaging T2 signal and Ki-67 index. Moreover, elevated choline and choline/creatine ratio differentiated between sparsely and densely granulated GH-secreting PAs. MRS detected low hepatic lipid content in active acromegaly, which increased after disease control. The panel of metabolites of acromegaly deciphered by mass spectrometry (MS)-based techniques mainly included amino acids (especially branched-chain amino acids and taurine), glyceric acid, and lipids. The most altered pathways in acromegaly were the metabolism of glucose (particularly the downregulation of the pentose phosphate pathway), linoleic acid, sphingolipids, glycerophospholipids, arginine/proline, and taurine/hypotaurine. Matrix-assisted laser desorption/ionization coupled with MS imaging confirmed the functional nature of GH-secreting PAs and accurately discriminated PAs from healthy pituitary tissue.PMID:37139720 | DOI:10.1177/10815589231169452

Mol Omics. 2023 May 4. doi: 10.1039/d2mo00338d. Online ahead of print.ABSTRACTFood metabolomics is described as the implementation of metabolomics to food systems such as food materials, food processing, and food nutrition. These applications generally create large amounts of data, and although technologies exist to analyze these data and different tools exist for various ecosystems, downstream analysis is still a challenge and the tools are not integrated into a single method. In this article, we developed a data processing method for untargeted LC-MS data in metabolomics, derived from the integration of computational MS tools from OpenMS into the workflow system Konstanz Information Miner (KNIME). This method can analyze raw MS data and produce high-quality visualization. A MS1 spectra-based identification, two MS2 spectra-based identification workflows and a GNPSExport-GNPS workflow are included in this method. Compared with conventional approaches, the results of MS1&MS2 spectra-based identification workflows are combined in this approach via the tolerance of retention times and mass to charge ratios (m/z), which can greatly reduce the rate of false positives in metabolomics datasets. In our example, filtering with the tolerance removed more than 50% of the possible identifications while retaining 90% of the correct identification. The results demonstrated that the developed method is a rapid and reliable method for food metabolomics data processing.PMID:37139637 | DOI:10.1039/d2mo00338d

MedComm (2020). 2023 Apr 30;4(3):e252. doi: 10.1002/mco2.252. eCollection 2023 Jun.ABSTRACTSleep insufficiency is associated with various disorders; the molecular basis is unknown until now. Here, 14 males and 18 females were subjected to short-term (24 h) sleep deprivation, and donated fasting blood samples prior to (day 1) and following (days 2 and 3) short-term sleep deprivation. We used multiple omics techniques to examine changes in volunteers' blood samples that were subjected to integrated, biochemical, transcriptomic, proteomic, and metabolomic analyses. Sleep deprivation caused marked molecular changes (46.4% transcript genes, 59.3% proteins, and 55.6% metabolites) that incompletely reversed by day 3. The immune system in particular neutrophil-mediated processes associated with plasma superoxidase dismutase-1 and S100A8 gene expression was markedly affected. Sleep deprivation decreased melatonin levels and increased immune cells, inflammatory factors and c-reactive protein. By disease enrichment analysis, sleep deprivation induced signaling pathways for schizophrenia and neurodegenerative diseases enriched. In sum, this is the first multiomics approach to show that sleep deprivation causes prominent immune changes in humans, and clearly identified potential immune biomarkers associated with sleep deprivation. This study indicated that the blood profile following sleep disruption, such as may occur among shift workers, may induce immune and central nervous system dysfunction.PMID:37139463 | PMC:PMC10149526 | DOI:10.1002/mco2.252

Acta Pharm Sin B. 2023 Apr;13(4):1699-1710. doi: 10.1016/j.apsb.2022.11.011. Epub 2022 Nov 10.ABSTRACTDeconvolution of potential drug targets of the central nervous system (CNS) is particularly challenging because of the complicated structure and function of the brain. Here, a spatiotemporally resolved metabolomics and isotope tracing strategy was proposed and demonstrated to be powerful for deconvoluting and localizing potential targets of CNS drugs by using ambient mass spectrometry imaging. This strategy can map various substances including exogenous drugs, isotopically labeled metabolites, and various types of endogenous metabolites in the brain tissue sections to illustrate their microregional distribution pattern in the brain and locate drug action-related metabolic nodes and pathways. The strategy revealed that the sedative-hypnotic drug candidate YZG-331 was prominently distributed in the pineal gland and entered the thalamus and hypothalamus in relatively small amounts, and can increase glutamate decarboxylase activity to elevate γ-aminobutyric acid (GABA) levels in the hypothalamus, agonize organic cation transporter 3 to release extracellular histamine into peripheral circulation. These findings emphasize the promising capability of spatiotemporally resolved metabolomics and isotope tracing to help elucidate the multiple targets and the mechanisms of action of CNS drugs.PMID:37139420 | PMC:PMC10149982 | DOI:10.1016/j.apsb.2022.11.011

Front Psychiatry. 2023 Apr 17;14:1142682. doi: 10.3389/fpsyt.2023.1142682. eCollection 2023.ABSTRACTIn recent times, advances in the field of metabolomics have shed greater light on the role of metabolic disturbances in neuropsychiatric conditions. The following review explores the role of ketone bodies and ketosis in both the diagnosis and treatment of three major psychiatric disorders: major depressive disorder, anxiety disorders, and schizophrenia. Distinction is made between the potential therapeutic effects of the ketogenic diet and exogenous ketone preparations, as exogenous ketones in particular offer a standardized, reproducible manner for inducing ketosis. Compelling associations between symptoms of mental distress and dysregulation in central nervous system ketone metabolism have been demonstrated in preclinical studies with putative neuroprotective effects of ketone bodies being elucidated, including effects on inflammasomes and the promotion of neurogenesis in the central nervous system. Despite emerging pre-clinical data, clinical research on ketone body effectiveness as a treatment option for psychiatric disorders remains lacking. This gap in understanding warrants further investigating, especially considering that safe and acceptable ways of inducing ketosis are readily available.PMID:37139329 | PMC:PMC10149735 | DOI:10.3389/fpsyt.2023.1142682

Front Psychiatry. 2023 Apr 17;14:1151200. doi: 10.3389/fpsyt.2023.1151200. eCollection 2023.ABSTRACTOBJECTIVE: Alcohol dependence (AD) is a chronic recurrent mental disease caused by long-term drinking. It is one of the most prevalent public health problems. However, AD diagnosis lacks objective biomarkers. This study was aimed to shed some light on potential biomarkers of AD patients by investigating the serum metabolomics profiles of AD patients and the controls.METHODS: Liquid chromatography-mass spectrometry (LC-MS) was used to detect the serum metabolites of 29 AD patients (AD) and 28 controls. Six samples were set aside as the validation set (Control: n = 3; AD group: n = 3), and the remaining were used as the training set (Control: n = 26; AD group: n = 25). Principal component analysis (PCA) and partial least squares discriminant analysis (PCA-DA) were performed to analyze the training set samples. The metabolic pathways were analyzed using the MetPA database. The signal pathways with pathway impact >0.2, value of p <0.05, and FDR < 0.05 were selected. From the screened pathways, the metabolites whose levels changed by at least 3-fold were screened. The metabolites with no numerical overlap in their concentrations in the AD and the control groups were screened out and verified with the validation set.RESULTS: The serum metabolomic profiles of the control and the AD groups were significantly different. We identified six significantly altered metabolic signal pathways, including protein digestion and absorption; alanine, aspartate, and glutamate metabolism; arginine biosynthesis; linoleic acid metabolism; butanoate metabolism; and GABAergic synapse. In these six signal pathways, the levels of 28 metabolites were found to be significantly altered. Of these, the alterations of 11 metabolites changed by at least 3-fold compared to the control group. Of these 11 metabolites, those with no numerical overlap in their concentrations between the AD and the control groups were GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid and L-glutamine.CONCLUSION: The metabolite profile of the AD group was significantly different from that of the control group. GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid, and L-glutamine could be used as potential diagnostic markers for AD.PMID:37139316 | PMC:PMC10150058 | DOI:10.3389/fpsyt.2023.1151200

Cureus. 2023 Mar 31;15(3):e36986. doi: 10.7759/cureus.36986. eCollection 2023 Mar.ABSTRACTFetal and perinatal periods are critical phases for long-term development. Early diagnosis of maternal complications is challenging due to the great complexity of these conditions. In recent years, amniotic fluid has risen in a prominent position in the latest efforts to describe and characterize prenatal development. Amniotic fluid may provide real-time information on fetal development and metabolism throughout pregnancy as substances from the placenta, fetal skin, lungs, gastric fluid, and urine are transferred between the mother and the fetus. Applying metabolomics to monitor fetal well-being, in such a context, could help in the understanding, diagnosis, and treatment of these conditions and is a promising area of research. This review shines a spotlight on recent amniotic fluid metabolomics studies and their methods as an interesting tool for the assessment of many conditions and the identification of biomarkers. Platforms in use, such as proton nuclear magnetic resonance (1H NMR) and ultra-high-performance liquid chromatography (UHPLC), have different merits, and a combinatorial approach could be valuable. Metabolomics may also be used in the quest for habitual diet-induced metabolic signals in amniotic fluid. Finally, analysis of amniotic fluid can provide information on exposure to exogenous substances by detecting the exact levels of metabolites carried to the fetus and associated metabolic effects.PMID:37139280 | PMC:PMC10150141 | DOI:10.7759/cureus.36986

Front Genet. 2023 Apr 17;14:1113470. doi: 10.3389/fgene.2023.1113470. eCollection 2023.ABSTRACTIntroduction: Adiantum nelumboides (Adiantum) is an endangered fern with a narrow distribution along the Yangtze River in China. Due to its cliff-dwelling habit, it experiences water stress conditions, which further endangers its survival. However, no information is available about its molecular responses to drought and half-waterlogging conditions. Methods: Here, we applied five and ten days of half-waterlogging stress, five days of drought stress, and rewatering after five days of drought stress, and studied the resulting metabolome profiles and transcriptome signatures of Adiantum leaves. Results and Discussion: The metabolome profiling detected 864 metabolites. The drought and half-waterlogging stress induced up-accumulation of primary and secondary metabolites including amino acids and derivatives, nucleotides and derivatives, flavonoids, alkaloids, and phenolic acid accumulation in Adiantum leaves. Whereas, rewatering the drought-stressed seedlings reversed most of these metabolic changes. Transcriptome sequencing confirmed the differential metabolite profiles, where the genes enriched in pathways associated with these metabolites showed similar expression patterns. Overall, the half-waterlogging stress for 10 days induced large-scale metabolic and transcriptomic changes compared to half-waterlogging stress for 05 days, drought stress for 05 days or rewatering for 05 days. Conclusion: This pioneering attempt provides a detailed understanding of molecular responses of Adiantum leaves to drought and half-waterlogging stresses and rewater conditions. This study also provides useful clues for the genetic improvement of Adiantum for drought/half-waterlogging stress tolerance.PMID:37139233 | PMC:PMC10149873 | DOI:10.3389/fgene.2023.1113470

Front Vet Sci. 2023 Apr 17;10:1146626. doi: 10.3389/fvets.2023.1146626. eCollection 2023.ABSTRACTThe early diagnosis of Mycobacterium avium subsp. paratuberculosis (MAP) is one of the current challenges of farmers and veterinarians. This work aimed to investigate the changes in metabolic levels associated with natural MAP infection in infected and infectious dairy cattle. The study included sera from 23 infectious/seropositive, 10 infected but non-infectious/seronegative, and 26 negative Holstein Fresian cattle. The samples were selected from a collection of samples gathered during a prospective study. The samples were analyzed by quantitative nuclear magnetic resonance (NMR) spectroscopy and routine blood chemistry. The blood indices and the 1H NMR data were concatenated by low-level data fusion, resulting in a unique global fingerprint. Afterwards, the merged dataset was statistically analyzed by the least absolute shrinkage and selection operator (LASSO), which is a shrinkage and selection method for supervised learning. Finally, pathways analysis was performed to get more insights on the possible dysregulated metabolic pathways. The LASSO model achieved, in a 10 time repeated 5-fold cross-validation, an overall accuracy of 91.5% with high values of sensitivity and specificity in classifying correctly the negative, infected, and infectious animals. The pathway analysis revealed MAP-infected cattle have increased tyrosine metabolism and enhanced phenylalanine, tyrosine and tryptophan biosynthesis. The enhanced synthesis and degradation of ketone bodies was observed both in infected and infectious cattle. In conclusion, fusing data from multiple sources has proved to be useful in exploring the altered metabolic pathways in MAP infection and potentially diagnosing negative animals within paratuberculosis-infected herds.PMID:37138915 | PMC:PMC10150450 | DOI:10.3389/fvets.2023.1146626

Front Vet Sci. 2023 Apr 17;10:1143649. doi: 10.3389/fvets.2023.1143649. eCollection 2023.ABSTRACTINTRODUCTION: The experiment was conducted to evaluate the effects of Ganoderma lingzhi culture (GLC) as a fermented feed on growth performance, serum biochemical profile, meat quality, and intestinal morphology and microbiota in Sanhuang broilers. In addition, the association between gut bacteria and metabolites was investigated via untargeted metabolomic analysis.METHODS: A total of 192 Sanhuang broilers (112 days old) with an initial body weight of 1.62 ± 0.19 kg were randomly allocated to four treatments, six replicate pens per treatment with 8 broilers per pen. The four treatments contain a control diet (corn-soybean meal basal diet, CON), a positive control diet (basal diet + 75 mg/kg chlortetracycline, PCON), and the experimental diets supplemented with 1.5 and 3% of GLC, respectively. The trial includes phase 1 (day 1-28) and phase 2 (day 29-56).RESULTS: The results showed that broilers in PCON and GLC-added treatments showed a lower FCR (P < 0.05) in phase 2 and overall period and a higher ADG (P < 0.05) in phase 2. On day 56, the concentrations of serum SOD (P < 0.05), and HDL (P < 0.05) and cecal SCFA contents (P < 0.05) were increased in broilers fed GLC diets. Broilers fed GLC also showed a higher microbiota diversity and an elevated abundance of SCFA-related bacteria in the caecum. The association between intestinal bacteria and metabolites was investigated via correlation analysis. The differential metabolites in the caecum, such as L-beta-aspartyl-L-aspartic acid and nicotinamide riboside, were identified.CONCLUSION: In summary, dietary GCL supplementation could increase growth performance to some extent. Moreover, GLC might benefit broilers' health by improving serum HDL content, antioxidant status, SCFAs contents, bacterial diversity, and probiotic proliferation in the caecum.PMID:37138906 | PMC:PMC10150954 | DOI:10.3389/fvets.2023.1143649

Front Immunol. 2023 Apr 17;14:1031968. doi: 10.3389/fimmu.2023.1031968. eCollection 2023.ABSTRACTPlatelet concentrate (PC) transfusion seeks to provide haemostasis in patients presenting severe central thrombocytopenia or severe bleeding. PCs may induce adverse reactions (AR) that can occasionally be severe (SAR). PCs contain active biomolecules such as cytokines and lipid mediators. The processing and storage of PCs creates so-called structural and biochemical storage lesions that accumulate when blood products reach their shelf life. We sought to investigate lipid mediators as bioactive molecules of interest during storage and review associations with adverse reactions post-transfusion. To facilitate understanding, we focused on single donor apheresis (SDA) PCs with approximately 31.8% of PCs being delivered in our setting. Indeed, pooled PCs are the most widely transfused products, but the study of a single donor lipid mediator is easier to interpret. We are investigating key lipid mediators involved in AR. Adverse reactions were closely monitored in accordance with current national and regional haemovigilance protocols. Residual PCs were analysed post-transfusion in a series of observations, both with and without severe reactions in recipients. A decrease in the lysophosphatidylcholine species to produce the lysophosphatidic acid species has been observed during storage and in the case of AR. Lysophosphatidic acid increased with primarily platelet-inhibitor lipids. Anti-inflammatory platelet-induced inhibition lipids were weakly expressed in cases of severe adverse reactions. We therefore propose that a decrease in lysophosphatidylcholine and an increase in lysophosphatidic acid can prospectively predict serious adverse transfusion reactions.PMID:37138863 | PMC:PMC10149858 | DOI:10.3389/fimmu.2023.1031968

J Adv Res. 2023 May 1:S2090-1232(23)00123-6. doi: 10.1016/j.jare.2023.04.017. Online ahead of print.ABSTRACTINTRODUCTION: The continuous emergence and rapid spread of multidrug-resistant bacteria have accelerated the demand for the discovery of alternative antibiotics. Natural plants contain a variety of antibacterial components, which is an important source for the discovery of antimicrobial agents.OBJECTIVE: To explore the antimicrobial activities and related mechanisms of two lavandulylated flavonoids, sophoraflavanone G and kurarinon in Sophora flavescens against methicillin-resistant Staphylococcus aureus.METHODS: The effects of sophoraflavanone G and kurarinone on methicillin-resistant Staphylococcus aureus were comprehensively investigated by a combination of proteomics and metabolomics studies. Bacterial morphology was observed by scanning electron microscopy. Membrane fluidity, membrane potential, and membrane integrity were determined using the fluorescent probes Laurdan, DiSC3(5), and propidium iodide, respectively. Adenosine triphosphate and reactive oxygen species levels were determined using the adenosine triphosphate kit and reactive oxygen species kit, respectively. The affinity activity of sophoraflavanone G to the cell membrane was determined by isothermal titration calorimetry assays.RESULTS: Sophoraflavanone G and kurarinone showed significant antibacterial activity and anti-multidrug resistance properties. Mechanistic studies mainly showed that they could target the bacterial membrane and cause the destruction of the membrane integrity and biosynthesis. They could inhibit cell wall synthesis, induce hydrolysis and prevent bacteria from synthesizing biofilms. In addition, they can interfere with the energy metabolism of methicillin-resistant Staphylococcus aureus and disrupt the normal physiological activities of the bacteria. In vivo studies have shown that they can significantly improve wound infection and promote wound healing.CONCLUSION: Kurarinone and sophoraflavanone G showed promising antimicrobial properties against methicillin-resistant Staphylococcus aureus, suggesting that they may be potential candidates for the development of new antibiotic agents against multidrug-resistant bacteria.PMID:37137428 | DOI:10.1016/j.jare.2023.04.017

Comp Biochem Physiol Part D Genomics Proteomics. 2023 Apr 28;46:101083. doi: 10.1016/j.cbd.2023.101083. Online ahead of print.ABSTRACTCultivation of Larimichthys crocea in low salinity water has been regarded as an effective way to treat diseases induced by pathogens in seawater. The kidney of euryhaline teleost plays important roles in not only osmoregulation but also regulation of intermediary metabolism. However, the renal responses of metabolism and osmoregulation in L. crocea to low salinity waters are still rarely reported. In this work, renal metabolomic analysis based on MS technique was conducted on the L. crocea following cultivation in salinities of 24, 8, 6, 4, and 2 ppt for 40 days. A total of 485 metabolites covering organic acids and derivatives (34.17 %), lipids and lipid-like molecules (17.55 %), organoheterocyclic compounds (12.22 %), nucleosides, nucleotides, and analogues (11.91 %), and organic oxygen compounds (10.97 %), were identified in L. crocea kidney. Compared with control group (salinity 24), nearly all amino acids, nucleotides, and their derivatives were decreased in the kidney of L. crocea, whereas most of lipid-related metabolites including phospholipid, glycerophospholipids, and fatty acids were increased. The decrease in urea and inorganic ions as well as TMAO, betaine and taurine in L. crocea kidney suggested the less demand for maintaining osmotic homeostasis. Several intermediary metabolites covering amino acids, TCA cycle intermediates, and fatty acids were also significantly changed to match with the shift of energy allocation from osmoregulation to other biological processes. The reduced energy demand for osmoregulation might contribute to the promotion of L. crocea growth under low salinity environment. What is more, carbamoylphosphate and urea that showed linear salinity response curves and higher ED50 values were potential biomarkers to adaptation to low salinity water. Overall, the characterization of metabolomes of L. crocea kidney under low salinity provided a better understanding of the adaptive mechanisms to low salinity water and potentially contributed to a reference for optimal culture salinity and feed formula of L. crocea culture in low salinity water.PMID:37137257 | DOI:10.1016/j.cbd.2023.101083

Bioinformatics. 2023 May 3:btad210. doi: 10.1093/bioinformatics/btad210. Online ahead of print.ABSTRACTMOTIVATION: There is a need for easily accessible implementations that measure the strength of both linear and non-linear relationships between metabolites in biological systems as an approach for data-driven network development. While multiple tools implement linear Pearson and Spearman methods, there are no such tools that assess distance correlation.RESULTS: We present here SIgned Distance COrrelation (SiDCo). SiDCo is a GUI-platform for calculation of distance correlation in omics data, measuring linear and non-linear dependences between variables, as well as correlation between vectors of different lengths, e.g., different sample sizes. By combining the sign of the overall trend from Pearson's correlation with distance correlation values, we further provide a novel signed distance correlation of particular use in metabolomic and lipidomic analyses. Distance correlations can be selected as one-to-one or one-to-all correlations, showing relationships between each feature and all other features one at a time or in combination. Additionally, we implement partial distance correlation, calculated using the Gaussian Graphical model approach adapted to distance covariance. Our platform provides an easy-to-use software implementation that can be applied to the investigation of any dataset.AVAILABILITY: The SiDCo software application is freely available at https://complimet.ca/sidco.SUPPLEMENTARY INFORMATION: Supplementary help pages are provided at https://complimet.ca/sidco. Supplementary Material shows an example of an application of SiDCo in metabolomics.PMID:37137236 | DOI:10.1093/bioinformatics/btad210

J Anim Sci Biotechnol. 2023 May 4;14(1):60. doi: 10.1186/s40104-023-00859-8.ABSTRACTBACKGROUND: Bovine milk is an important source of nutrition for human consumption, and its quality is closely associated with the microbiota and metabolites in it. But there is limited knowledge about the milk microbiome and metabolome in cows with subacute ruminal acidosis.METHODS: Eight ruminally cannulated Holstein cows in mid lactation were selected for a 3-week experiment. The cows were randomly allocated into 2 groups, fed either a conventional diet (CON; 40% concentrate; dry matter basis) or a high-concentrate diet (HC; 60% concentrate; dry matter basis).RESULTS: The results showed that there was a decreased milk fat percentage in the HC group compared to the CON group. The amplicon sequencing results indicated that the alpha diversity indices were not affected by the HC feeding. At the phylum level, the milk bacteria were dominated by Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes both in the CON and HC groups. At the genus level, the HC cows displayed an improved proportion of Labrys (P = 0.015) compared with the CON cows. Results of both the principal components analysis and partial least squares of discriminant analysis of milk metabolome revealed that samples of the CON and HC groups clustered separately. A total of 31 differential metabolites were identified between the two groups. Of these, the levels of 11 metabolites decreased (α-linolenic acid, prostaglandin E2, L-lactic acid, L-malic acid, 3-hydroxysebacic acid, succinyladenosine, guanosine, pyridoxal, L-glutamic acid, hippuric acid, and trigonelline), whereas the levels of the other 20 metabolites increased in the HC group with respect to the CON group (P < 0.05).CONCLUSION: These results suggested that subacute ruminal acidosis less impacted the diversity and composition of milk microbiota, but altered the milk metabolic profiles, which led to the decline of the milk quality.PMID:37138330 | DOI:10.1186/s40104-023-00859-8

J Anim Sci Biotechnol. 2023 May 4;14(1):69. doi: 10.1186/s40104-023-00868-7.ABSTRACTBACKGROUND: Chickens provide globally important livestock products. Understanding the genetic and molecular mechanisms underpinning chicken economic traits is crucial for improving their selective breeding. Influenced by a combination of genetic and environmental factors, metabolites are the ultimate expression of physiological processes and can provide key insights into livestock economic traits. However, the serum metabolite profile and genetic architecture of the metabolome in chickens have not been well studied.RESULTS: Here, comprehensive metabolome detection was performed using non-targeted LC-MS/MS on serum from a chicken advanced intercross line (AIL). In total, 7,191 metabolites were used to construct a chicken serum metabolomics dataset and to comprehensively characterize the serum metabolism of the chicken AIL population. Regulatory loci affecting metabolites were identified in a metabolome genome-wide association study (mGWAS). There were 10,061 significant SNPs associated with 253 metabolites that were widely distributed across the entire chicken genome. Many functional genes affect metabolite synthesis, metabolism, and regulation. We highlight the key roles of TDH and AASS in amino acids, and ABCB1 and CD36 in lipids.CONCLUSIONS: We constructed a chicken serum metabolite dataset containing 7,191 metabolites to provide a reference for future chicken metabolome characterization work. Meanwhile, we used mGWAS to analyze the genetic basis of chicken metabolic traits and metabolites and to improve chicken breeding.PMID:37138301 | DOI:10.1186/s40104-023-00868-7

BMC Womens Health. 2023 May 3;23(1):221. doi: 10.1186/s12905-023-02355-7.ABSTRACTOBJECTIVE: Early-stage breast cancer (BC) is the second most common malignancy in women, worldwide. Early-detection and treatment advances have led to 5-year survival rates of 90% for early-stage breast cancer. However, the long-term morbidity of breast cancer remains high, with a majority of survivors facing increased risk of cardiometabolic conditions as well as secondary cancers. In particular, African American women with breast cancer experience higher morbidity and mortality than other women. Metabolomics is the comprehensive study of metabolites in biological samples to elucidate the role of monosaccharides, amino acids, and their respective metabolic pathways. Although some studies have found differential metabolites in women with breast cancer compared to normal controls, there has been little study of women with breast cancer across time and the active treatment trajectory. This study examines and compares the serum metabolomic profile of women with BC, prior to initial chemotherapy and at 1 year after inception of chemotherapy.METHODS: This study examined serum metabolites through a secondary analysis of a longitudinal parent study (EPIGEN) of women diagnosed with early-stage BC. Participants were evaluated across 5 time points: prior to their receipt of chemotherapy (T1), at the time of their 4th chemotherapy treatment (T2), 6 months after the initiation of chemotherapy (T3), one year after the initiation of chemotherapy (T4) and two years after the initiation of chemotherapy (T5). This analysis focused on the metabolomic data from 70 participants from T1 to T4. Using ultra high-pressure liquid chromatography high resolution mass spectrometry (UHPLC-HRMS), we performed Friedman Rank Sum Test followed by Nemenyi post-hoc pairwise tests to identify which metabolite levels differed between time points, focusing on metabolites with a Benjamini-Hochberg false discovery rate (FDR) from the overall Friedman test < 0.05 and then specifically examined the p-values from the T1 vs. T4 pairwise comparison.RESULTS: The untargeted serum metabolomics yielded a total of 2,395 metabolites identified on the basis of the accurate mass and MS/MS fragmentation, 1,264 of which were significant after Friedman's test (FDR < 0.05). The analysis then focused on the levels of 124 metabolites from the T1 vs. T4 post-hoc comparison that had a combined FDR < 0.05 and fold change (FC) > 2.0. Metabolite set enrichment analysis (MSEA) as part of Metaboanalyst 3.0 was performed to identify pathways that were significantly altered. The known metabolites identified from the functional analysis were used to evaluate the up and down regulated pathways. The 40metabolites from the Functional Analysis were mainly attributed to amino acids (specifically lysine regulation), fatty acids (particularly unsaturated) and steroid hormone synthesis (lysophosphatidic acid).CONCLUSION: There were multiple significant changes in the serum metabolomic profile of women with breast cancer at one-year post inception of chemotherapy compared to pre-chemotherapy, most notably associated with lysine degradation, branched-chain amino acid synthesis, linoleic acid metabolism, tyrosine metabolism and biosynthesis of unsaturated fatty acids as the top 5 metabolic pathways. Some of these changes could be associated with metabolic perturbations that are consistent with heightened risk of cardiometabolic morbidity. Our results provide new insights into the mechanisms underlying potential heightened cardiovascular health risks in this population.PMID:37138260 | DOI:10.1186/s12905-023-02355-7

Environ Sci Pollut Res Int. 2023 May 3. doi: 10.1007/s11356-023-27314-5. Online ahead of print.ABSTRACTIn this study, a lactic acid bacterium, Enterococcus faecium, was found to prevent CaCO3 precipitation through its metabolism. On analysis of all stages of E. faecium growth, static jar tests demonstrated that stationary phase E. faecium broth possessed the highest inhibition efficiency of 97.3% at a 0.4% inoculation dosage, followed by the decline and log phases with efficiencies of 90.03% and 76.07%, respectively. Biomineralization experiments indicated that E. faecium fermented the substrate to produce organic acid, which resulted in modulation of the pH and alkalinity of the environment and thus inhibited CaCO3 precipitation. Surface characterization techniques indicated that the CaCO3 crystals precipitated by the E. faecium broth tended to be significantly distorted and formed other organogenic calcite crystals. The scale inhibition mechanisms were revealed by untargeted metabolomic analysis on log and stationary phase E. faecium broth. In total, 264 metabolites were detected, 28 of which were differential metabolites (VIP ≥ 1 and p < 0.05). Of these, 15 metabolites were upregulated in stationary phase broth, and 13 metabolites were downregulated in log phase broth. Metabolic pathway analysis suggested that improved glycolysis and the TCA cycle were the main reasons for enhancement of the antiscaling performance of E. faecium broth. These findings have significant implications for microbial metabolism-induced CaCO3 scale inhibition.PMID:37138126 | DOI:10.1007/s11356-023-27314-5

Cell Biol Toxicol. 2023 May 4. doi: 10.1007/s10565-023-09809-6. Online ahead of print.ABSTRACTCell-based metabolomics provides multiparametric physiologically relevant readouts that can be highly advantageous for improved, biologically based decision making in early stages of compound development. Here, we present the development of a 96-well plate LC-MS/MS-based targeted metabolomics screening platform for the classification of liver toxicity modes of action (MoAs) in HepG2 cells. Different parameters of the workflow (cell seeding density, passage number, cytotoxicity testing, sample preparation, metabolite extraction, analytical method, and data processing) were optimized and standardized to increase the efficiency of the testing platform. The applicability of the system was tested with seven substances known to be representative of three different liver toxicity MoAs (peroxisome proliferation, liver enzyme induction, and liver enzyme inhibition). Five concentrations per substance, aimed at covering the complete dose-response curve, were analyzed and 221 uniquely identified metabolites were measured, annotated, and allocated in 12 different metabolite classes such as amino acids, carbohydrates, energy metabolism, nucleobases, vitamins and cofactors, and diverse lipid classes. Multivariate and univariate analyses showed a dose response of the metabolic effects, a clear differentiation between liver toxicity MoAs and resulted in the identification of metabolite patterns specific for each MoA. Key metabolites indicative of both general and mechanistic specific hepatotoxicity were identified. The method presented here offers a multiparametric, mechanistic-based, and cost-effective hepatotoxicity screening that provides MoA classification and sheds light into the pathways involved in the toxicological mechanism. This assay can be implemented as a reliable compound screening platform for improved safety assessment in early compound development pipelines.PMID:37138123 | DOI:10.1007/s10565-023-09809-6