LuYuxing/MetaBench huggingface dataset:
Question: Write a study description for the study titled 'The nasal microbiome and metabolites are altered in depression patients'.
Answer: Depressive disorder is a heterogeneous neuropsychiatric disorder. It affects millions of people worldwide. The exact causes of depressive behavior remain unclear and are believed to implicate both genetic and environmental factors. In the past decade, there have been numerous studies on the dysbiosis of gut microbiota in patients with depression and animal models. Of particular note is the role of gut brain axis regulation, in which a series of continuously expanding microbial metabolites, including short chain fatty acids and neurotransmitters, have been identified as signaling molecules that affect behavioral outcomes. However, most insights about the association between microbiota and depression still focus on the gut-brain axis and ignore that nasal microbiota could form a complex and essential link with the nervous system via the nose-to-brain pathway. So far, the potential influence of the nasal microbiome on neurological disorders has been largely overlooked. We investigated the impact of nasal microbiota and nasal metabolites on depression in this study.
Question: Write a study description for the study titled 'The cardiovascular risk of healthy individuals studied by NMR metabonomics of plasma samples'.
Answer: The identification and the present wide acceptance of cardiovascular risk factors such as age, sex, hypertension, hyperlipidemia, smoking, obesity, diabetes, and physical inactivity have led to dramatic reductions in cardiovascular morbidity and mortality. However, novel risk predictors present opportunities to identify more patients at risk and to more accurately define the biochemical signature of that risk. In this paper, we present a comprehensive metabonomic analysis of 864 plasma samples from healthy volunteers, through Nuclear Magnetic Resonance (NMR) and multivariate statistical analysis (regression and classification). We have found that subjects that are classified as at high or at low risk using the common clinical markers can also be discriminated using NMR metabonomics. This discrimination is not only due to common markers (such as total cholesterol, triglycerides, LDL, HDL), but also to (p < 0.05 after Bonferroni correction) other metabolites (e.g., 3-hydroxybutyrate, α-ketoglutarate, threonine, dimethylglycine) previously not associated with cardiovascular diseases.
Question: Write a study description for the study titled 'Proteome allocations change linearly with the specific growth rate of Saccharomyces cerevisiae under glucose limitation'.
Answer: Saccharomyces cerevisiae is a widely used cell factory; therefore, it is important to understand how it organizes key functional parts when cultured under different conditions. Here, we perform a multiomics analysis of S. cerevisiae by culturing the strain with a wide range of specific growth rates using glucose as the sole limiting nutrient. Under these different conditions, we measure the absolute transcriptome, the absolute proteome, the phosphoproteome, and the metabolome. Most functional protein groups show a linear dependence on the specific growth rate. Proteins engaged in translation show a perfect linear increase with the specific growth rate, while glycolysis and chaperone proteins show a linear decrease under respiratory conditions. Glycolytic enzymes and chaperones, however, show decreased phosphorylation with increasing specific growth rates; at the same time, an overall increased flux through these pathways is observed. Further analysis show that even though mRNA levels do not correlate with protein levels for all individual genes, the transcriptome level of functional groups correlates very well with its corresponding proteome. Finally, using enzyme-constrained genome-scale modeling, we find that enzyme usage plays an important role in controlling flux in amino acid biosynthesis.
Question: Write a study description for the study titled 'Metabolite profiling of the fermentation process of yamahai-ginjo-shikomi Japanese sake'.
Answer: Sake is a traditional Japanese alcoholic beverage prepared by multiple parallel fermentation of rice. The fermentation process of yamahai-ginjo-shikomi sake is mainly performed by three microbes, Aspergillus oryzae, Saccharomyces cerevisiae, and Lactobacilli; the levels of various metabolites fluctuate during the fermentation of sake. For evaluation of the fermentation process, we monitored the concentration of moderate-sized molecules (m/z: 200-1000) dynamically changed during the fermentation process of yamahai-ginjo-shikomi Japanese sake. This analysis revealed that six compounds were the main factors with characteristic differences in the fermentation process. Among the six compounds, four were leucine- or isoleucine-containing peptides and the remaining two were predicted to be small molecules. Quantification of these compounds revealed that their quantities changed during the month of fermentation process. Our metabolomic approach revealed the dynamic changes observed in moderate-sized molecules during the fermentation process of sake, and the factors found in this analysis will be candidate molecules that indicate the progress of yamahai-ginjo-shikomi sake fermentation.
Question: Write a study description for the study titled 'Bacteria regulate aging physiology in microalgae via induced vesicle production and the methionine cycle (Metabolomics profiling of FACS purified EVs)'.
Answer: In annually reoccurring patterns, microalgae form blooms that persist and decline thereby contributing massively to global biogeochemical cycles. The decline of blooms is mainly caused by nutrient limitation and goes ahead with the aging of individual algal cells. Nutrient intake can re-initiate proliferation, but the processes involved are poorly understood. By investigating the bloom-forming diatom Coscinodiscus radiatus, we demonstrate how algae recover after nutrient influx. The rejuvenation physiology of the algae is characterized by metabolomic re-organization and the formation of extracellular vesicles. Regulated pathways mediating aging are centered around the methionine cycle in C. radiatus. Vesicles shuttle reactive oxygen species, oxylipins and other harmful metabolites out of the old cells, thereby re-enabling their proliferation. Metabolic processes involved in aging and vesicle production are modulated by bacteria. Using chemical signaling bacteria can trigger vesicle production thereby releasing organic nutrients for their growth and supporting algal growth as well.Metabolomics profiling of FACS purified EVs is reported in the current study MTBLS5401.Metabolomics analysis is reported in MTBLS5368.
Question: Write a study description for the study titled 'Multi-country metabolic signature discovery for chicken health classification'.
Answer: INTRODUCTION: To decrease antibiotic resistance, their use as growth promoters in the agricultural sector has been largely abandoned. This may lead to decreased health due to infectious disease or microbiome changes leading to gut inflammation.OBJECTIVES: We aimed to generate a m/z signature classifying chicken health in blood, and obtain biological insights from the resulting m/z signature.METHODS: We used direct infusion mass-spectrometry to determine a machine-learned metabolomics signature that classifies chicken health from a blood sample. We then challenged the resulting models by investigating the classification capability of the signature on novel data obtained at poultry houses in previously unseen countries using a leave-one-country-out (LOCO) cross-validation strategy. Additionally, we optimised the number of mass/charge (m/z) values required to maximise the classification capability of Random Forest models, by developing a novel ranking system based on combined univariate t-test and fold-change analyses and building models based on this ranking through forward and reverse feature selection.RESULTS: The multi-country and LOCO models could classify chicken health. Both resulting 25-m/z and 3784-m/z signatures reliably classified chicken health worldwide. Through mummichog enrichment analysis on the large m/z signature, we found changes to amino acid metabolism, including branched chain amino acids and polyamines.CONCLUSION: We reliably classified chicken health from blood, independent of genetic-, farm-, feed- and country-specific confounding factors. The 25-m/z signature can be used to aid development of a per-metabolite panel. The extended 3784-m/z version can be used to gain a deeper understanding of the metabolic causes and consequences of low chicken health. Together, they may facilitate future treatment, prevention and intervention.
Question: Write a study description for the study titled 'Examining the effects of cigarette smoke on mouse lens through a multi OMIC approach'.
Answer: Here, we report a multi OMIC (transcriptome, proteome, and metabolome) approach to investigate molecular changes in lens fiber cells (FC) of mice exposed to cigarette smoke (CS). Pregnant mice were placed in a whole-body smoke chamber and a few days later pups were born, which were exposed to CS for 5 hours/day, 5 days/week for a total of 3½ months. We examined the mice exposed to CS for CS-related cataractogenesis after completion of the CS exposure but no cataracts were observed. Lenses of CS-exposed and age-matched, untreated control mice were extracted and lens FC were subjected to multi OMIC profiling. We identified 348 genes, 130 proteins, and 14 metabolites exhibiting significant (p < 0.05) differential levels in lens FC of mice exposed to CS, corresponding to 3.6%, 4.3%, and 5.0% of the total genes, protein, and metabolites, respectively identified in this study. Our multi OMIC approach confirmed that only a small fraction of the transcriptome, the proteome, and the metabolome was perturbed in the lens FC of mice exposed to CS, which suggests that exposure of CS had a minimal effect on the mouse lens. It is worth noting that while our results confirm that CS exposure does not have a substantial impact on the molecular landscape of the mouse lens FC, we cannot rule out that CS exposure for longer durations and/or in combination with other morbidities or environmental factors would have a more robust effect and/or result in cataractogenesis.
Question: Write a study description for the study titled 'An Evolutionarily Conserved Metabolite Inhibits Biofilm Formation in Escherichia coli K-12'.
Answer: Methylerythritol cyclodiphosphate (MEcPP) is an intermediate in the biosynthesis of isoprenoids in plant plastids and in bacteria, and acts as a stress signal in plants. Here, we show that MEcPP regulates biofilm formation in Escherichia coli K-12 MG1655. Increased MEcPP levels, triggered by genetic manipulation or oxidative stress, inhibit biofilm development and production of fimbriae. Deletion of fimE, encoding a protein known to downregulate production of adhesive fimbriae, restores biofilm formation in cells with elevated MEcPP levels. Limited proteolysis-coupled mass spectrometry (LiP-MS) reveals that MEcPP interacts with the global regulatory protein H-NS, which is known to repress transcription of fimE. MEcPP prevents the binding of H-NS to the fimE promoter. Therefore, our results indicate that MEcPP can regulate biofilm formation by modulating H-NS activity and thus reducing fimbriae production. Further research is needed to test whether MEcPP plays similar regulatory roles in other bacteria.
Question: Write a study description for the study titled 'Plasma metabolite changes in dairy cows during parturition identified using untargeted metabolomics'.
Answer: The metabolic responses of cows undergo substantial changes during the transition from late pregnancy to early lactation. However, the molecular mechanisms associated with these changes in physiological metabolism have not been clearly elucidated. The objective of this study was to investigate metabolic changes in transition cows from the perspective of plasma metabolites. Plasma samples collected from 24 multiparous dairy cows on approximately d 21 prepartum and immediately postpartum were analyzed using ultra-high-performance liquid chromatography/time-of-flight mass spectrometry in positive and negative ion modes. In conjunction with multidimensional statistical methods (principal component analysis and orthogonal partial least squares discriminant analysis), differences in plasma metabolites were identified using the t-test and fold change analysis. Sixty-seven differential metabolites were identified consisting of AA, lipids, saccharides, and nucleotides. The levels of 32 plasma metabolites were significantly higher and those of 35 metabolites significantly lower after parturition than on d 21 prepartum. Pathway analysis indicated that the metabolites that increased from late pregnancy to early lactation were primarily involved in lipid metabolism and energy metabolism, whereas decreased metabolites were related to AA metabolism.
Question: Write a study description for the study titled 'Direct infusion mass spectrometry metabolomics dataset: a benchmark for data processing and quality control'.
Answer: Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach for characterising molecular responses of organisms to disease, drugs and the environment. Increasingly large-scale metabolomics studies are being conducted, necessitating improvements in both bioanalytical and computational workflows to maintain data quality. This dataset represents a systematic evaluation of the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue extracts. It comprises of twenty biological samples (cow vs. sheep) that were analysed repeatedly, in 8 batches across 7 days, together with a concurrent set of quality control (QC) samples. Data are presented from each step of the workflow and are available in MetaboLights. The strength of the dataset is that intra- and inter-batch variation can be corrected using QC spectra and the quality of this correction assessed independently using the repeatedly-measured biological samples. Originally designed to test the efficacy of a batch-correction algorithm, it will enable others to evaluate novel data processing algorithms. Furthermore, this dataset serves as a benchmark for DIMS metabolomics, derived using best-practice workflows and rigorous quality assessment.
Question: Write a study description for the study titled 'A cytochrome P450 CYP87A4 imparts sterol side-chain cleavage in digoxin biosynthesis'.
Answer: Digoxin extracted from the foxglove plant is a widely prescribed natural product for treating heart failure. It is listed as an essential medicine by the World Health Organization. However, how the foxglove plant synthesizes digoxin is mostly unknown, especially the cytochrome P450 sterol side chain cleaving enzyme (P450scc), which catalyzes the first and rate-limiting step. Here we identify the long-speculated foxglove P450scc through differential transcriptomic analysis. This enzyme converts cholesterol and campesterol to pregnenolone, suggesting that digoxin biosynthesis starts from both sterols, unlike previously reported. Phylogenetic analysis indicates that this enzyme arises from a duplicated cytochrome P450 CYP87A gene and is distinct from the well-characterized mammalian P450scc. Protein structural analysis reveals two amino acids in the active site critical for the foxglove P450scc's sterol cleavage ability. Identifying the foxglove P450scc is a crucial step toward completely elucidating digoxin biosynthesis and expanding the therapeutic applications of digoxin analogs in future work.
Question: Write a study description for the study titled 'Unravelling the interaction between the phageome and bacteriome in the rumen and its role in influencing metabolome dynamics in dairy cows at different lactation stages'.
Answer: Background: Although the roles of rumen microbiome in milk yield and milk protein synthesis have been widely recognized, knowledge on how ruminal microbiome dynamic changes affect these two traits during the whole lactation is lacking. Phages have been shown to affect the microbiota, but little is known about the shift patterns of ruminal phages and if they may modulate rumen microbiome during lactation. Herein, a longitudinal study was performed to identify the potential roles of ruminal phageome and bacteriome interactions, and metabolic function shift in affecting milk yield and protein content using metagenomic and metabolomic profiling of rumen microbiome from the peak, early and later mid-lactation stages.Results: A total of 780 ruminal bacterial phages were identified, which exhibited two primary shifting patterns: 1) decreasing then increasing; 2) decreasing then stabilizing through the lactation. Bacteriome also showed first increasing then stabilizing or continuously decline besides exhibiting two similar shifting patterns to those of phages. By associating the differentially abundant phages with their host bacteria, we observed that significantly increased Lactococcus phage BM13, Corynebacterium phage P1201 and Campylobacter phage CJIE4-5 in peak lactation, along with Lactobacillus phage Lv-1 in early and later mid-lactation, and they were positively correlated with the relative abundance of their hosts. However, significantly increased Bacillus phage BCU4 and the Enterococcus phage phiNASRA1 in early mid-lactation were negatively related to their host abundance. In terms of bacteria, such as Ruminococcus flavefaciens and Faecalibacterium sp. CAG 74 had the highest abundance in peak lactation, whereas most Prevotella species were more abundant in early and later mid-lactation. Notably, ruminal carbohydrate and amino acid metabolism functions were enhanced in early mid-lactation. Further structural equation model and network analysis revealed that abundant Bacillus phage BCU4 and Enterococcus phage phiNASRA1 in early mid-lactation were associated with increased relative abundance of Prevotella species, possibly due to a reduction in Bacillus cereus and Enterococcus faecalis. Additionally, these Prevotella species exhibited positive relationships with rumen metabolites, such as L-phenylalanine, phenylacetylglycine, N-acetyl-D-phenylalanine, as well as propionate content, which contributed to the improved milk protein yield.Conclusions: This study revealed the bacteriome and phageome interactions at different lactation stages, and the key phages and bacteria regulating the rumen function and metabolism thus contributing to the milk traits of cows. The potential regulatory roles of phages in affecting the rumen bacteriome suggest that they can be powerful targets for future interventions to improve rumen functions.
Question: Write a study description for the study titled 'Fecal microbiota transplantation treatment maintains post antibiotics gut function by change the gut microbiome and fecal metabolome to reduce gut inflammation and oxidative stress in nile tilapia (Oreochromis niloticus)'.
Answer: The imbalance of intestinal flora can affect the immune function and structural integrity of the intestinal barrier, leading to the colonization and reproduction of opportunistic pathogenic bacteria in the intestine to become the dominant flora, eventually inducing enteritis. This study aimed to investigate whether fecal microbiota transplantation (FMT) could improve the gut barrier in Nile tilapia (Oreochromis niloticus). The experiment involved administering normal saline (NS group) and fecal microbiota (FMT group) (from the negative control group (C group)) to tilapia that had been treated with oxytetracycline hydrochloride (OTC) (M group) by gavage. A total of 300 male tilapia (mean body weight 596.65 ± 47.18 g) were used, with 180 of them being fed OTC (120 mg/kg body weight/day) for 7 days to induce intestinal oxidative stress, while the rest served as the control group. After confirmation of mild chronic enteritis, the tilapia were treated in different ways.
Question: Write a study description for the study titled 'Bioaccumulation of therapeutic drugs by human gut bacteria (L.saccharolytica;Standards assays)'.
Answer: Bacteria in the gut can modulate the availability and efficacy of therapeutic drugs. Interactions at this level have only recently started to being systematically mapped and the main underlying mechanism proposed is chemical transformation of drugs by microbes (biotransformation). Here, we investigated the depletion of structurally diverse drugs by 25 representative gut bacterial strains. This revealed 70 bacteria-drug interactions, 29 of which had not been reported before. Over half of the new interactions can be ascribed to bioaccumulation, that is bacteria storing the drug intracellularly without chemically modifying it, and in most cases without their growth being affected. As a case in point, we studied the molecular basis of bioaccumulation of the widely used antidepressant duloxetine by using click-chemistry, thermal proteome profiling and metabolomics. We find that duloxetine binds to several metabolic enzymes and changes metabolite secretion of the respective bacteria. When tested in a defined microbial community of accumulators and non-accumulators, duloxetine markedly altered the community composition through metabolic cross-feeding. We further validated our findings in an animal model, showing that bioaccumulating bacteria attenuate the behavioral response of Caenorhabditis elegans to duloxetine. Taken together, bioaccumulation by gut bacteria may be a common mechanism that alters drug availability and bacterial metabolism, with implications for microbiota composition, pharmacokinetics, side effects and drug responses, likely in an individual manner.Linked studies:UPLC-MS/MS assays of Bifidobacterium animalis subsp. lactis are reported in MTBLS1264.UPLC-MS/MS assay of Lacrimispora saccharolytica and Escherichia coli IAI1 is reported in MTBLS1319.UPLC-MS/MS assays of Escherichia coli ED1a, Clostridium saccharolyticum, Escherichia coli IAI1, Streptococcus salivarius, Eubacterium rectale, Lactobacillus plantarum WCFS1 and Lactococcus lactis subsp. lactis Il1403 are reported in MTBLS1627.UPLC-MS/MS assay of Bacteroides uniformis and Clostridium saccharolyticum is reported in MTBLS1757.UPLC-MS/MS assay of Clostridium saccharolyticum, Escherichia coli ED1a, Escherichia coli IAI1, Lactobacillus plantarum WCFS1, Lactococcus lactis subsp. lactis Il1403 and Streptococcus salivarius is reported in MTBLS1791.UPLC-MS/MS assay of Eubacterium rectale and Streptococcus salivarius is reported in MTBLS1792.
Question: Write a study description for the study titled 'Antidiabetic and cardiovascular beneficial effects of a liver-localized mitochondrial uncoupler'.
Answer: Inducing mitochondrial uncoupling (mUncoupling) is an attractive therapeutic strategy for treating metabolic diseases because it leads to calorie-wasting by reducing the efficiency of oxidative phosphorylation (OXPHOS) in mitochondria. Here we report a safe mUncoupler, OPC-163493, which has unique pharmacokinetic characteristics. OPC-163493 shows a good bioavailability upon oral administration and primarily distributed to specific organs: the liver and kidneys, avoiding systemic toxicities. It exhibits insulin-independent antidiabetic effects in multiple animal models of type I and type II diabetes and antisteatotic effects in fatty liver models. These beneficial effects can be explained by the improvement of glucose metabolism and enhancement of energy expenditure by OPC-163493 in the liver. Moreover, OPC-163493 treatment lowered blood pressure, extended survival, and improved renal function in the rat model of stroke/hypertension, possibly by enhancing NO bioavailability in blood vessels and reducing mitochondrial ROS production. OPC-163493 is a liver-localized/targeted mUncoupler that ameliorates various complications of diabetes.