PubMed

Front Plant Sci. 2024 Feb 2;15:1342639. doi: 10.3389/fpls.2024.1342639. eCollection 2024.ABSTRACTEnzymatic browning reactions, triggered by oxidative stress, significantly compromise the quality of harvested crops during postharvest handling. This has profound implications for the agricultural industry. Recent advances have employed a systematic, multi-omics approach to developing anti-browning treatments, thereby enhancing our understanding of the resistance mechanisms in harvested crops. This review illuminates the current multi-omics strategies, including transcriptomic, proteomic, and metabolomic methods, to elucidate the molecular mechanisms underlying browning. These strategies are pivotal for identifying potential metabolic markers or pathways that could mitigate browning in postharvest systems.PMID:38371411 | PMC:PMC10869537 | DOI:10.3389/fpls.2024.1342639

Front Plant Sci. 2024 Feb 2;15:1260140. doi: 10.3389/fpls.2024.1260140. eCollection 2024.ABSTRACTWith environmental problems such as climate global warming, drought has become one of the major stress factors, because it severely affects the plant growth and development. Silicon dioxide nanoparticles (SiO2 NPs) are crucial for mitigating abiotic stresses suffered by plants in unfavorable environmental conditions and further promoting plant growth, such as drought. This study aimed to investigate the effect of different concentrations of SiO2 NPs on the growth of the Ehretia macrophylla Wall. seedlings under severe drought stress (water content in soil, 30-35%). The treatment was started by starting spraying different concentrations of SiO2 NPs on seedlings of Ehretia macrophyla, which were consistently under normal and severe drought conditions (soil moisture content 30-35%), respectively, at the seedling stage, followed by physiological and biochemical measurements, transcriptomics and metabolomics analyses. SiO2 NPs (100 mg·L-1) treatment reduced malondialdehyde and hydrogen peroxide content and enhanced the activity of antioxidant enzymes under drought stress. Transcriptomic analysis showed that 1451 differentially expressed genes (DEGs) in the leaves of E. macrophylla seedlings were regulated by SiO2 NPs under drought stress, and these genes mainly participate in auxin signal transduction and mitogen-activated protein kinase signaling pathways. This study also found that the metabolism of fatty acids and α-linolenic acids may play a key role in the enhancement of drought tolerance in SiO2 NP-treated E. macrophylla seedlings. Metabolomics studies indicated that the accumulation level of secondary metabolites related to drought tolerance was higher after SiO2 NPs treatment. This study revealed insights into the physiological mechanisms induced by SiO2 NPs for enhancing the drought tolerance of plants.PMID:38371410 | PMC:PMC10869631 | DOI:10.3389/fpls.2024.1260140

bioRxiv. 2024 Feb 9:2024.02.07.579219. doi: 10.1101/2024.02.07.579219. Preprint.ABSTRACTRecurrent C. difficile infection (rCDI) is an urgent public health threat for which the last resort and lifesaving treatment is a fecal microbiota transplant (FMT). However, the exact mechanisms which mediate a successful FMT are not well understood. Here we use longitudinal stool samples collected from patients undergoing FMT to evaluate changes in the microbiome, metabolome, and lipidome after successful FMTs. We show changes in the abundance of many lipids, specifically acylcarnitines and bile acids, in response to FMT. These changes correlate with Enterobacteriaceae, which encode carnitine metabolism genes, and Lachnospiraceae, which encode bile salt hydrolases and baiA genes. LC-IMS-MS revealed a shift from microbial conjugation of primary bile acids pre-FMT to secondary bile acids post-FMT. Here we define the structural and functional changes in successful FMTs. This information will help guide targeted Live Biotherapeutic Product development for the treatment of rCDI and other intestinal diseases.PMID:38370838 | PMC:PMC10871284 | DOI:10.1101/2024.02.07.579219

bioRxiv. 2024 Feb 10:2024.02.07.579333. doi: 10.1101/2024.02.07.579333. Preprint.ABSTRACTWith a long evolutionary history and a need to adapt to a changing environment, cyanobacteria in freshwater systems use specialized metabolites for communication, defense, and physiological processes. However, the role that these metabolites play in differentiating species, maintaining microbial communities, and generating niche persistence and expansion is poorly understood. Furthermore, many cyanobacterial specialized metabolites and toxins present significant human health concerns due to their liver toxicity and their potential impact to drinking water. Gaps in knowledge exist with respect to changes in species diversity and toxin production during a cyanobacterial bloom (cyanoHAB) event; addressing these gaps will improve understanding of impacts to public and ecological health. In the current project, we utilized a multi-omics strategy (DNA metabarcoding and metabolomics) to determine the cyanobacterial community composition, toxin profile, and the specialized metabolite pool at three freshwater lakes in Providence, RI during summer-fall cyanoHABs. Species diversity decreased at all study sites over the course of the bloom event, and toxin production reached a maximum at the midpoint of the event. Additionally, LC-MS/MS-based molecular networking identified new toxin congeners. This work provokes intriguing questions with respect to the use of allelopathy by organisms in these systems and the presence of emerging toxic compounds that can impact public health.SYNOPSIS: This study reports on cyanobacterial community succession and toxin dynamics during cyanobacterial bloom events. Results show relationships and temporal dynamics that are relevant to public health.PMID:38370816 | PMC:PMC10871351 | DOI:10.1101/2024.02.07.579333

bioRxiv. 2024 Feb 7:2024.02.02.578679. doi: 10.1101/2024.02.02.578679. Preprint.ABSTRACTOBJECTIVE: Overweight/obesity is the strongest risk factor for endometrial cancer (EC), and weight management can reduce that risk and improve survival. We aimed to establish the differential abilities of intermittent energy restriction (IER) and low-fat diet (LFD), alone and in combination with paclitaxel, to reverse the procancer effects of high-fat diet (HFD)-induced obesity in a mouse model of EC.METHODS: Lkb1 fl/fl p53 fl/fl mice were fed high-fat diet (HFD) or LFD to generate obese and lean phenotypes, respectively. Obese mice were maintained on HFD or switched to LFD (HFD-LFD) or IER (HFD-IER). Ten weeks after induction of endometrial tumor, mice in each group received paclitaxel or placebo for 4 weeks. Body and tumor weights; tumoral transcriptomic, metabolomic and oxylipin profiles; and serum metabolic hormones and chemocytokines were assessed.RESULTS: HFD-IER and HFD-LFD, relative to HFD, reduced body weight; reversed obesity-induced alterations in serum insulin, leptin and inflammatory factors; and decreased tumor incidence and mass, often to levels emulating those associated with continuous LFD. Concurrent paclitaxel, versus placebo, enhanced tumor suppression in each group, with greatest benefit in HFD-IER. The diets produced distinct tumoral gene expression and metabolic profiles, with HFD-IER associated with a more favorable (antitumor) metabolic and inflammatory environment.CONCLUSION: In Lkb1 fl/fl p53 fl/fl mice, IER is generally more effective than LFD in promoting weight loss, inhibiting obesity-related endometrial tumor growth (particularly in combination with paclitaxel), and reversing detrimental obesity-related metabolic effects. These findings lay the foundation for further investigations of IER as a EC prevention strategy in women with overweight/obesity.PMID:38370796 | PMC:PMC10871198 | DOI:10.1101/2024.02.02.578679

bioRxiv. 2024 Feb 8:2024.02.04.578795. doi: 10.1101/2024.02.04.578795. Preprint.ABSTRACTAlthough untargeted mass spectrometry-based metabolomics is crucial for understanding life's molecular underpinnings, its effectiveness is hampered by low annotation rates of the generated tandem mass spectra. To address this issue, we introduce a novel data-driven approach, Biotransformation-based Annotation Method (BAM), that leverages molecular structural similarities inherent in biochemical reactions. BAM operates by applying biotransformation rules to known 'anchor' molecules, which exhibit high spectral similarity to unknown spectra, thereby hypothesizing and ranking potential structures for the corresponding 'suspect' molecule. BAM's effectiveness is demonstrated by its success in annotating suspect spectra in a global molecular network comprising hundreds of millions of spectra. BAM was able to assign correct molecular structures to 24.2 % of examined anchor-suspect cases, thereby demonstrating remarkable advancement in metabolite annotation.PMID:38370723 | PMC:PMC10871291 | DOI:10.1101/2024.02.04.578795

bioRxiv. 2024 Feb 10:2024.02.07.579252. doi: 10.1101/2024.02.07.579252. Preprint.ABSTRACTINTRODUCTION: Multiple sclerosis (MS) is the most common inflammatory neurodegenerative disease of the central nervous system (CNS) in young adults and results in progressive neurological defects. The relapsing-remitting phenotype (RRMS) is the most common disease course in MS and may progress to the progressive form (PPMS).OBJECTIVES: There is a gap in knowledge regarding whether the relapsing form can be distinguished from the progressive course or healthy subjects (HS) based on an altered serum metabolite profile. In this study, we performed global untargeted metabolomics with the 2D GCxGC-MS platform to identify altered metabolites between RRMS, PPMS, and HS.METHODS: We profiled 235 metabolites in the serum of patients with RRMS (n=41), PPMS (n=31), and HS (n=91). A comparison of RRMS and HS patients revealed 22 significantly altered metabolites at p<0.05 (false discovery rate [FDR]=0.3). The PPMS and HS comparisons revealed 28 altered metabolites at p<0.05 (FDR=0.2).RESULTS: Pathway analysis using MetaboAnalyst revealed enrichment of four metabolic pathways in both RRMS and PPMS (hypergeometric test p<0.05): 1) galactose metabolism; 2) amino sugar and nucleotide sugar metabolism; 3) phenylalanine, tyrosine, and tryptophan biosynthesis; and 4) aminoacyl-tRNA biosynthesis. The Qiagen IPA enrichment test identified the sulfatase 2 (SULF2) (p=0.0033) and integrin subunit beta 1 binding protein 1 (ITGB1BP1) (p=0.0067) genes as upstream regulators of altered metabolites in the RRMS vs. HS groups. However, in the PPMS vs. HS comparison, valine was enriched in the neurodegeneration of brain cells (p=0.05), and heptadecanoic acid, alpha-ketoisocaproic acid, and glycerol participated in inflammation in the CNS (p=0.03).CONCLUSION: Overall, our study suggested that RRMS and PPMS may contribute metabolic fingerprints in the form of unique altered metabolites for discriminating MS disease from HS, with the potential for constructing a metabolite panel for progressive autoimmune diseases such as MS.PMID:38370675 | PMC:PMC10871325 | DOI:10.1101/2024.02.07.579252

bioRxiv. 2024 Jan 30:2024.01.26.577518. doi: 10.1101/2024.01.26.577518. Preprint.ABSTRACTQuantitative trait loci (QTL) denote regions of DNA whose variation is associated with variations in quantitative traits. QTL discovery is a powerful approach to understand how changes in molecular and clinical phenotypes may be related to DNA sequence changes. However, QTL discovery analysis encompasses multiple analytical steps and the processing of multiple input files, which can be laborious, error prone, and hard to reproduce if performed manually. In order to facilitate and automate large-scale QTL analysis, we developed the yQTL Pipeline, where the 'y' indicates the dependent quantitative variable being modeled. Prior to genome-wide association test, the pipeline supports the calculation or the direct input of pre-defined genome-wide principal components and genetic relationship matrix when applicable. User-specified covariates can also be provided. Depending on whether familial relatedness exists among the subjects, genome-wide association tests will be performed using either a linear mixed-effect model or a linear model. Using the workflow management tool Nextflow, the pipeline parallelizes the analysis steps to optimize run-time and ensure results reproducibility. In addition, a user-friendly R Shiny App is developed to facilitate result visualization. Upon uploading the result file, it can generate Manhattan plots of user-selected phenotype traits and trait-QTL connection networks based on user-specified p-value thresholds. We applied the yQTL Pipeline to analyze metabolomics profiles of blood serum from the New England Centenarians Study (NECS) participants. A total of 9.1M SNPs and 1,052 metabolites across 194 participants were analyzed. Using a p-value cutoff 5e-8, we found 14,983 mQTLs cumulatively associated with 312 metabolites. The built-in parallelization of our pipeline reduced the run time from ~90 min to ~26 min. Visualization using the R Shiny App revealed multiple mQTLs shared across multiple metabolites. The yQTL Pipeline is available with documentation on GitHub at https://github.com/montilab/yQTL-Pipeline.PMID:38370654 | PMC:PMC10874520 | DOI:10.1101/2024.01.26.577518

Front Pharmacol. 2024 Jan 29;15:1353325. doi: 10.3389/fphar.2024.1353325. eCollection 2024.ABSTRACTIntroduction: Zhusha Anshen Wan (ZSASW) is a traditional Chinese medicine compound mainly composed of mineral drugs. In clinical practice, ZSASW did not show the toxicity of administering equal doses of cinnabar alone, suggesting that the four combination herbs in ZSASW can alleviate the damage of cinnabar. The effect of each herb on reducing the toxicity of cinnabar has not been fully explained. Methods: In our study, we utilized a metabonomics approach based on high-resolution 1H nuclear magnetic resonance spectroscopy to investigate the reduction of toxicity by each herb in ZSASW. Liver, kidney and intestinal histopathology examinations and biochemical analysis of the serum were also performed. Results: Partial least squares-discriminant analysis (PLS-DA) was conducted to distinct different metabolic profiles in the urine and serum from the rats. Liver and kidney histopathology examinations, as well as analysis of serum clinical chemistry analysis, were also carried out. The metabolic profiles of the urine and serum of the rats in the CGU (treated with cinnabar and Glycyrrhiza uralensis Fisch) and CCC (treated with cinnabar and Coptis chinensis French) groups were remarkably similar to those of the control group, while those of the CRG (treated with cinnabar and Rehmannia glutinosa Libosch) and CAS (treated with cinnabar and Angelica sinensis) groups were close to those of the cinnabar group. The metabolic profiles of the urine and serum of the rats in the CGU and CCC groups were remarkably similar to those of the control group, while those of the CRG and CAS groups were close to those of the cinnabar group. Changes in endogenous metabolites associated with toxicity were identified. Rehmannia glutinosa, Rhizoma Coptidis and Glycyrrhiza uralensis Fisch could maintain the dynamic balance of the intestinal flora. These results were also verified by liver, kidney and intestinal histopathology examinations and biochemical analysis of the serum. The results suggested that Discussion: The metabolic mechanism of single drug detoxification in compound prescriptions has been elucidated. Coptis chinensis and Glycyrrhiza uralensis serve as the primary detoxification agents within ZSASW for mitigating liver, kidney, and intestinal damage caused by cinnabar. Detoxification can be observed through changes in the levels of various endogenous metabolites and related metabolic pathways.PMID:38370476 | PMC:PMC10871036 | DOI:10.3389/fphar.2024.1353325

Front Endocrinol (Lausanne). 2024 Feb 2;15:1313597. doi: 10.3389/fendo.2024.1313597. eCollection 2024.ABSTRACTBACKGROUND: Metformin is a drug with a long history of providing benefits in diabetes management and beyond. The mechanisms of action of metformin are complex, and continue to be actively debated and investigated. The aim of this study is to identify metabolic signatures associated with metformin treatment, which may explain the pleiotropic mechanisms by which metformin works, and could lead to an improved treatment and expanded use.METHODS: This is a cross-sectional study, in which clinical and metabolomic data for 146 patients with type 2 diabetes were retrieved from Qatar Biobank. Patients were categorized into: Metformin-treated, treatment naïve, and non-metformin treated. Orthogonal partial least square discriminate analysis and linear models were used to analyze differences in the level of metabolites between the metformin treated group with each of the other two groups.RESULTS: Patients on metformin therapy showed, among other metabolites, a significant increase in 3-hydroxyoctanoate and 3-hydroxydecanoate, which may have substantial effects on metabolism.CONCLUSIONS: This is the first study to report an association between 3-hydroxy medium chain fatty acids with metformin therapy in patients with type 2 diabetes. This opens up new directions towards repurposing metformin by comprehensively understanding the role of these metabolites.PMID:38370354 | PMC:PMC10869496 | DOI:10.3389/fendo.2024.1313597

Food Chem X. 2024 Feb 6;21:101173. doi: 10.1016/j.fochx.2024.101173. eCollection 2024 Mar 30.ABSTRACTTo better understand the effect of oxygen levels in the storage environment on peanut protein oxidation and explore the mechanism, the functional properties and the oxidation degree of peanut proteins extracted from peanuts under conventional storage (CS), nitrogen modified atmosphere storage (NS, hypoxic) and re-aeration storage (RS) were investigated. Metabolomics and proteomics were employed to analyze peanut's response to hypoxic/re-aeration storage environment. The results showed that NS retarded the decline of the functional properties and the oxidation of peanut proteins, while the process were accelerated after re-aeration. That was the result of the metabolic changes of peanuts under different storage environments. The omics results presented the decreased (NS)/increased (RS) levels of the antioxidant-related proteins acetaldehyde dehydrogenase and glutathione S-transferase, and the inhibition (NS)/activation (RS) of metabolic pathways such as the TCA cycle and the pentose phosphate pathway. This study provided a reference for the re-aeration storage of other agricultural products.PMID:38370304 | PMC:PMC10869743 | DOI:10.1016/j.fochx.2024.101173

Expert Rev Mol Diagn. 2024 Feb 19:1-13. doi: 10.1080/14737159.2024.2316755. Online ahead of print.ABSTRACTBACKGROUND: Breathomics is an emerging area focusing on monitoring and diagnosing pulmonary diseases, especially lung cancer. This research aims to employ metabolomic methods to create a breathprint in human-expelled air to rapidly identify lung cancer and its stages.RESEARCH DESIGN AND METHODS: An electronic nose (e-nose) system with five metal oxide semiconductor (MOS) gas sensors, a microcontroller, and machine learning algorithms was designed and developed for this application. The volunteers in this study include 114 patients with lung cancer and 147 healthy controls to understand the clinical potential of the e-nose system to detect lung cancer and its stages.RESULTS: In the training phase, in discriminating lung cancer from controls, the XGBoost classifier model with 10-fold cross-validation gave an accuracy of 91.67%. In the validation phase, the XGBoost classifier model correctly identified 35 out of 42 patients with lung cancer samples and 44 out of 51 healthy control samples providing an overall sensitivity of 83.33% and specificity of 86.27%.CONCLUSIONS: These results indicate that the exhaled breath VOC analysis method may be developed as a new diagnostic tool for lung cancer detection. The advantages of e-nose based diagnostics, such as an easy and painless method of sampling, and low-cost procedures, will make it an excellent diagnostic method in the future.PMID:38369930 | DOI:10.1080/14737159.2024.2316755

Sheng Wu Gong Cheng Xue Bao. 2024 Feb 25;40(2):542-561. doi: 10.13345/j.cjb.230371.ABSTRACTThe leaves and roots of Sarcandra glabra (thunb) nakai have different therapeutic effects in some clinical applications. In order to explore the tissue specific distribution differences of terpenoids in the leaves and roots of S. glabra, and to analyze the molecular mechanism of the formation of their pharmacodynamic quality differences. In this study, liquid chromatography-mass spectrometry (LC-MS) and Illumina HiSeqTM high-throughput sequencing techniques were respectively used to obtain the metabolome and transcriptome data of the leaves and roots of S. glabra. The metabolomics analysis showed that there were 50 differential terpenoids metabolites between the leaves and roots, including farnesylcysteine, d-glyceraldehyde 3-phosphate, and (R)-5-phosphomevalonate. The transcriptomics analysis indicated that there were 57 differentially expressed metabolic enzyme coding genes, including ACTC, HMGCR, MVK, DXS, and KS. Moreover, there were seven transcription factors, including MYB, C2H2, AP2/ERF-ERF, which were predicted to participate in regulating the differences in terpenoid synthesis and accumulation between the leaves and roots of S. glabra. qRT-PCR results demonstrated that the expression changes of eight randomly selected enzyme genes involved in terpene synthesis between the leaves and roots of S. glabra, which were consistent with the transcriptome sequencing results. This study will help to elucidate the molecular mechanisms underlying the clinical efficacy differences between the leaves and roots of S. glabra, and facilitate the extraction, utilization, and resource development of S. glabra.PMID:38369840 | DOI:10.13345/j.cjb.230371

Development. 2024 Feb 15;151(4):dev202020. doi: 10.1242/dev.202020. Epub 2024 Feb 19.ABSTRACTMalrotation of the intestine is a prevalent birth anomaly, the etiology of which remains poorly understood. Here, we show that late-stage exposure of Xenopus embryos to atrazine, a widely used herbicide that targets electron transport chain (ETC) reactions, elicits intestinal malrotation at high frequency. Interestingly, atrazine specifically inhibits the cellular morphogenetic events required for gut tube elongation, including cell rearrangement, differentiation and proliferation; insufficient gut lengthening consequently reorients the direction of intestine rotation. Transcriptome analyses of atrazine-exposed intestines reveal misexpression of genes associated with glycolysis and oxidative stress, and metabolomics shows that atrazine depletes key glycolytic and tricarboxylic acid cycle metabolites. Moreover, cellular bioenergetics assays indicate that atrazine blocks a crucial developmental transition from glycolytic ATP production toward oxidative phosphorylation. Atrazine-induced defects are phenocopied by rotenone, a known ETC Complex I inhibitor, accompanied by elevated reactive oxygen species, and rescued by antioxidant supplementation, suggesting that malrotation may be at least partly attributable to redox imbalance. These studies reveal roles for metabolism in gut morphogenesis and implicate defective gut tube elongation and/or metabolic perturbations in the etiology of intestinal malrotation.PMID:38369735 | DOI:10.1242/dev.202020

Sci Rep. 2024 Feb 19;14(1):4037. doi: 10.1038/s41598-024-54717-2.ABSTRACTGut microbiota and their metabolic products might play important roles in regulating the pathogenesis of autism spectrum disorder (ASD). The purpose of this study was to characterize gut microbiota and serum amino acid metabolome profiles in children with ASD. A non-randomized controlled study was carried out to analyze the alterations in the intestinal microbiota and their metabolites in patients with ASD (n = 30) compared with neurotypical controls (NC) (n = 30) by metagenomic sequencing to define the gut microbiota community and liquid chromatography/mass spectrometry (LC/MS) analysis to characterize the metabolite profiles. Compared with children in the NC group, those in the ASD group showed lower richness, higher evenness, and an altered microbial community structure. At the class level, Deinococci and Holophagae were significantly lower in children with ASD compared with TD. At the phylum level, Deinococcus-Thermus was significantly lower in children with ASD compared with TD. In addition, the functional properties (such as galactose metabolism) displayed significant differences between the ASD and NC groups. Five dominant altered species were identified and analyzed (LDA score > 2.0, P < 0.05), including Subdoligranulum, Faecalibacterium_praushitzii, Faecalibacterium, Veillonellaceae, and Rumminococcaceae. The peptides/nickel transport system was the main metabolic pathway involved in the differential species in the ASD group. Decreased ornithine levels and elevated valine levels may increase the risk of ASD through a metabolic pathway known as the nickel transport system. The microbial metabolism in diverse environments was negatively correlated with phascolarctobacterium succinatutens. Our study provides novel insights into compositional and functional alterations in the gut microbiome and metabolite profiles in ASD and the underlying mechanisms between metabolite and ASD.PMID:38369656 | DOI:10.1038/s41598-024-54717-2

Biotechnol Biofuels Bioprod. 2024 Feb 18;17(1):27. doi: 10.1186/s13068-024-02476-7.ABSTRACTBACKGROUND: The demand for melatonin is increasing due to its health-promoting bioactivities such as antioxidant and sleep benefits. Although melatonin is present in various organisms, its low content and high extraction cost make it unsustainable. Biosynthesis is a promising alternative method for melatonin production. However, the ectopic production of melatonin in microorganisms is very difficult due to the low or insoluble expression of melatonin synthesis genes. Hence, we aim to explore the biosynthesis of melatonin using Escherichia coli as a cell factory and ways to simultaneously coordinated express genes from different melatonin synthesis pathways.RESULTS: In this study, the mXcP4H gene from Xanthomonas campestris, as well as the HsAADC, HsAANAT and HIOMT genes from human melatonin synthesis pathway were optimized and introduced into E. coli via a multi-monocistronic vector. The obtained strain BL7992 successfully synthesized 1.13 mg/L melatonin by utilizing L-tryptophan (L-Trp) as a substrate in a shake flask. It was determined that the rate-limiting enzyme for melatonin synthesis is the arylalkylamine N-acetyltransferase, which is encoded by the HsAANAT gene. Targeted metabolomics analysis of L-Trp revealed that the majority of L-Trp flowed to the indole pathway in BL7992, and knockout of the tnaA gene may be beneficial for increasing melatonin production.CONCLUSIONS: A metabolic engineering approach was adopted and melatonin was successfully synthesized from low-cost L-Trp in E. coli. This study provides a rapid and economical strategy for the synthesis of melatonin.PMID:38369525 | DOI:10.1186/s13068-024-02476-7

J Dairy Sci. 2024 Feb 16:S0022-0302(24)00489-2. doi: 10.3168/jds.2023-24147. Online ahead of print.ABSTRACTThrough its influence on the gut microbiota, feeding of Saccharomyces cerevisiae fermentation products (SCFP) has been a successful strategy to enhance the health of dairy cows during periods of physiological stresses. Although production and metabolic outcomes from feeding SCFP are well-known, combined impacts on the ruminal microbiota and metabolome during gut barrier challenges remain unclear. To address this gap in knowledge, multiparous Holstein cows (97.1 ± 7.6 DIM; n = 8/group) fed a control diet (CON) or CON plus 19 g/d SCFP for 9 wk were subjected to a feed restriction (FR) challenge for 5 d, during which they were fed 40% of their ad-libitum intake from the 7 d before FR. DNA extracted from ruminal fluid was subjected to PacBio Full-Length 16S rRNA gene sequencing, RT-PCR of 12 major ruminal bacteria, and metabolomics analysis of up to 189 metabolites via GC-MS. High-quality amplicon sequence analyses were performed with Targeted Amplicon Diversity Analysis (TADA), MicrobiomeAnalyst, PICRUSt2, and STAMP software, while metabolomics data were analyzed via MetaboAnalyst 5.0. Ruminal fluid metabolites from the SCFP group exhibited a greater α diversity Chao 1 (P = 0.03) and Shannon indices (P = 0.05), and the PLS-DA analysis clearly discriminated metabolite profiles between dietary groups. The abundance of CPla_4_termite_group, Candidatus_Saccharimonas, Oribacterium, and Pirellula genus in cows fed SCFP was greater. In the SCFP group, concentrations of ethanolamine, 2-amino-4,6-dihydroxypyrimidine, glyoxylic acid, serine, threonine, cytosine, stearic acid, and pyrrole-2-carboxylic acid were greater in ruminal fluid. Both Fretibacterium and Succinivibrio abundance were positively correlated with metabolites across various biological processes: gamma-aminobutyric acid, galactose, butane-2,3-diol, fructose, 5-amino pentanoic acid, β-aminoisobutyric acid, ornithine, malonic acid, 3-hydroxy-3-methylbutyric acid, hexanoic acid, heptanoic acid, cadaverine, glycolic acid, β-alanine, 2-hydroxybutyric acid, methyl alanine, and alanine. In the SCFP group, compared with CON, the mean proportion of 14 predicted pathways based on metabolomics data was greater, while 10 predicted pathways were lower. Integrating metabolites and upregulated predicted enzymes (NADP+-dependent glucose-6-phosphate dehydrogenase, 6-phosphogluconate dehydrogenase, serine: glyoxylate aminotransferase, and D-glycerate 3-kinase) indicated that the pentose phosphate pathway and photorespiration pathway were most upregulated by SCFP. Overall, SCFP during FR led to alterations in ruminal microbiota composition and key metabolic pathways. Among those, there was a shift from the tricarboxylic acid (TCA) cycle to the glyoxylate cycle and nitrogenous base production was enhanced.PMID:38369118 | DOI:10.3168/jds.2023-24147

J Dairy Sci. 2024 Feb 16:S0022-0302(24)00484-3. doi: 10.3168/jds.2023-23984. Online ahead of print.ABSTRACTEstimating feed efficiency (FE) in dairy sheep is challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by 2 metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced data sets were investigated using 4 machine-learning algorithms and a multivariate regression method. The Orthogonal Partial Least Square algorithm outperformed other ML algorithms for the FCR prediction in the scenarios using the complete milk metabolite signature (r2 = 0.62 ± 0.06) and the 26 selected features (0.62 ± 0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the Multilayer feedforward artificial neural network (r2 = 0.18 ± 0.14) and extreme gradient boosting (r2 = 0.17 ± 0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared with the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.PMID:38369116 | DOI:10.3168/jds.2023-23984

Environ Pollut. 2024 Feb 16:123595. doi: 10.1016/j.envpol.2024.123595. Online ahead of print.ABSTRACTThe zirconium metal-organic framework UiO-66-NH2 has garnered considerable attention for their potentials of removing environmental contaminants from water. The production and application of UiO-66-NH2 make their releases into the aquatic environment inevitable. Nevertheless, little information is available regarding its potential risk to the environment and aquatic organisms, thus limiting the evaluation of its safe and sustainable use. In this study, the ecotoxicity of UiO-66-NH2 was evaluated, specifically its impacts on growth, extracellular organic matter release, and metabolomic changes of the model phytoplankton Microcystis aeruginosa (M. aeruginosa). UiO-66-NH2 exhibited moderate effects on algal physiology including growth, viability, and photosynthetic system. At concentrations below 20 mg/L, UiO-66-NH2 induced negligible inhibition of algal growth, algal viability, and photosynthesis. In contrast, UiO-66-NH2 boosted the release of extracellular organic matter even at concentration as low as 0.02 mg/L. These findings indicated that, while no evident damage to algal cells was observed, UiO-66-NH2 was hazardous to the aquatic environment as it stimulated the release of algal toxins. Moreover, UiO-66-NH2 entered algal cells rather than adhering to the surface of M. aeruginosa as observed by the fluorescence imaging. Based on metabolic analysis, UiO-66-NH2 influenced the cyanobacteria mainly through interference with purine metabolism and ABC transporter. This study sheds light on the potential threat UiO-66-NH2 posing to microalgae, and has potential implications for its safe utilization in the environmental field.PMID:38369089 | DOI:10.1016/j.envpol.2024.123595

EBioMedicine. 2024 Feb 17;101:105008. doi: 10.1016/j.ebiom.2024.105008. Online ahead of print.ABSTRACTGestational diabetes mellitus (GDM) is one of the most common metabolic complications during pregnancy, threatening both maternal and fetal health. Prediction and diagnosis of GDM is not unified. Finding effective biomarkers for GDM is particularly important for achieving early prediction, accurate diagnosis and timely intervention. Urine, due to its accessibility in large quantities, noninvasive collection and easy preparation, has become a good sample for biomarker identification. In recent years, a number of studies using metabolomics and proteomics approaches have identified differential expressed urine metabolites and proteins in GDM patients. In this review, we summarized these potential urine biomarkers for GDM prediction and diagnosis and elucidated their role in development of GDM.PMID:38368766 | DOI:10.1016/j.ebiom.2024.105008