LuYuxing/MetaBench huggingface dataset:
Question: Write a study description for the study titled 'Metabolomic Profiling of the Striatum in Shank3 Knockout ASD Rats: Effects of Early Swimming Regulation'.
Answer: OBJECTIVE: This study aimed to investigate the regulatory impact of early swimming intervention on striatal metabolism in Shank3 gene knockout ASD model rats. METHODS: Shank3 gene knockout exon 11-21 male 8-day-old SD rats were used as experimental subjects and randomly divided into three groups: Shank3 knockout control group (KC), wild-type control group (WC) from the same litter and Shank3 knockout swimming group (KS). Rats in the exercise group received early swimming intervention for 8 weeks starting at 8 days old. GC-MS metabolism was employed to detect the changes of metabolites in striatum. RESULTS: There were 17 differential metabolites (14 down-regulated) between the KC and WC groups, 19 differential metabolites (18 up-regulated) between the KS and KC groups and 22 differential metabolites (18 up-regulated) between the KS and WC groups. CONCLUSION: The metabolism of striatum in Shank3 knockout ASD model rats is disrupted, involving metabolites related to synaptic morphology, Glu and GABAergic synapses are abnormal. Early swimming intervention regulated the striatal metabolome group of ASD model rats, with differential metabolites primarily related to nerve development, synaptic membrane structure and synaptic signal transduction.
Question: Write a study description for the study titled 'Microbial Diversity and Non-volatile Metabolites Profile of Low-Temperature Sausage Stored at Room Temperature'.
Answer: Sausage is a highly perishable food with unique spoilage characteristics primarily because of its specific means of production. The quality of sausage during storage is determined by its microbial and metabolite changes. This study developed a preservative-free low-temperature sausage model and coated it with natural casing. We characterized the microbiota and non-volatile metabolites in the sausage after storage at 20°C for up to 12 days. Bacillus velezensis was the most prevalent species observed after 4 days. Lipids and lipid-like molecules, organoheterocyclic compounds, and organic acids and their derivatives were the primary non-volatile metabolites. The key non-volatile compounds were mainly involved in protein catabolism and β-lipid oxidation. These findings provide useful information for the optimization of sausage storage conditions.
Question: Write a study description for the study titled 'PFKFB3 activates CAD to enhance de novo pyrimidine synthesis for cell growth'.
Answer: Aerobic glycolysis, termed the Warburg effect, is one of the aberrant metabolic pathways in highly proliferating cells. Glycolysis provides glycolytic metabolites to support the generation of biomass, such as nucleotides, amino acids, and lipids. To date, research on the direct interactions between glycolysis and other metabolic pathways is an emerging field that has garnered significant interest. Phosphofructokinase-2/fructose-2,6-bisphosphatase 3 (PFKFB3) activates glycolysis by synthesizing fructose-2,6-bisphosphate (F2,6BP), which allosterically activates the rate-limiting enzyme 6-phosphofructo-1-kinase (PFK-1). In this study, we found that PFKFB3 directly interacts with and regulates the phosphorylation of carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD), the enzyme catalyzing the first three steps of de novo pyrimidine synthesis. PFKFB3 inactivation reduced de novo pyrimidine synthesis, RNA and DNA production, and growth of cancer cells. Thus, the glycolytic activator PFKFB3 bridges glycolysis with pyrimidine synthesis, unites both glucose metabolism and nucleic acid metabolism, and contributes to cell proliferation under pathological conditions.
Question: Write a study description for the study titled 'Mass spectrometry imaging of phosphatidylcholine metabolism in lungs administered with therapeutic surfactants and isotopic tracers'.
Answer: Mass spectrometry imaging (MSI) visualises molecular distributions throughout tissues but is blind to dynamic metabolic processes. Here, MSI with high mass resolution together with multiple stable isotope labelling provided spatial analyses of phosphatidylcholine (PC) metabolism in mouse lungs. Dysregulated surfactant metabolism is central to many respiratory diseases. Metabolism and turnover of therapeutic pulmonary surfactants were imaged from distributions of intact and metabolic products of an added tracer, universally 13C-labelled dipalmitoyl PC (U[13C]DPPC). The parenchymal distributions of newly synthesised PC species were also imaged from incorporations of methyl-D9-choline. This dual labelling strategy demonstrated both lack of inhibition of endogenous PC synthesis by exogenous surfactant and location of acyl chain remodelling processes acting on the U[13C]DPPC-labelled surfactant, leading to formation of polyunsaturated PC lipids. This ability to visualise discrete metabolic events will greatly enhance our understanding of lipid metabolism in diverse tissues, and has potential application to both clinical and experimental studies.
Question: Write a study description for the study titled 'Metabolomics to elucidate the effects of novel sustainable feed additives in the feed of farmed salmon (HoloFood Trial B - blue mussel-dose response)'.
Answer: An experimental trial was conducted on juvenile farmed Atlantic salmon (Salmo salar) in the framework of the HoloFood project, which aims to test the effect of novel sustainable feed additives in the feed of farmed salmon. Trial B blue mussel was used as a novel sustainable protein feed source in the diet of Atlantic salmon. Blue mussel represents an alternative, more sustainable protein source than traditional fishmeal. The blue mussel meal was produced by de-shelled blue mussels, which were subsequently spray-dried. It was integrated into the diet, mainly replacing fishmeal as the protein source.HoloFood Trial B - blue mussel-dose response is reported in the current study MTBLS4382.HoloFood Trial A - seaweed-dose response is reported in MTBLS4381.HoloFood Trial C - blue mussel ensilage-dose response is reported in MTBLS4384.HoloFood Trial D - fermented seaweed open water-dose response is reported in MTBLS6733.HoloFood Trial 1/2/3 is reported in MTBLS6988.Linked cross omic data sets:Nucleic acid data associated with this study are available in the European Nucleotide Archive (ENA): accession number PRJEB43192.Metagenomic data associated with this study are available from MGnify under the Super Study 'holofood'.
Question: Write a study description for the study titled 'Refining the seminal biomarker detection: metabolome profiles before and after the liquefaction procedure'.
Answer: Semen metabolome analysis presents a promising approach to identify potential biomarkers. However, it remains unclear whether metabolites should be analyzed immediately from fresh ejaculate or after the liquefaction process in conjunction with routine semen quality assessments. To address this question, we set out to evaluate metabolome profiles in semen before and after liquefaction using untargeted metabolomics, with the goal of establishing a protocol for biomarker discovery. Thirty semen samples were collected from 15 healthy donors before and after the liquefaction process and a total of 1664 metabolites were detected in two different analytical approaches. The semen liquefaction process does not affect the overall metabolic profile.
Question: Write a study description for the study titled 'Temporal characterization of serum metabolite signatures in lung cancer patients undergoing treatment'.
Answer: Lung cancer causes more deaths in men and women than any other cancer related disease. Currently, few effective strategies exist to predict how patients will respond to treatment. We evaluated the serum metabolomic profiles of 25 lung cancer patients undergoing chemotherapy ± radiation to evaluate the feasibility of metabolites as temporal biomarkers of clinical outcomes . Methods: Serial serum specimens collected prospectively from lung cancer patients were analyzed using both nuclear magnetic resonance (1H-NMR) spectroscopy and gas chromatography mass spectrometry (GC-MS). Multivariate statistical analysis consisted of unsupervised principal component analysis or orthogonal partial least squares discriminant analysis with significance assessed using a cross-validated ANOVA. Results: The metabolite profiles were reflective of the temporal distinction between patient samples before during and after receiving therapy (1H-NMR p<0.001 and GC-MS p<0.01). Disease progression and survival were strongly correlative with the GC-MS metabolite data whereas stage and cancer type were associated with 1H-NMR data. Metabolites such as hydroxylamine, tridecan-1-ol, octadecan-1-ol, were indicative of survival (GC-MS p<0.05) and metabolites such as tagatose, hydroxylamine, glucopyranose, and threonine that were reflective of progression (GC-MS p<0.05). Conclusions: Metabolite profiles have the potential to act as prognostic markers of clinical outcomes for lung cancer patients. Serial 1H-NMR measurements appear to detect metabolites diagnostic of tumor pathology, while GC-MS provided data better related to prognostic clinical outcomes warranting further study in a larger cohort and with various treatment options.
Question: Write a study description for the study titled 'Susceptibility to febrile malaria is associated with an inflammatory gut microbiome'.
Answer: Malaria is a major public health problem, but many of the factors underlying the pathogenesis of this disease are not well understood. Here, we demonstrate in Malian children that susceptibility to febrile malaria following infection with Plasmodium falciparum is associated with the composition of the gut microbiome prior to the malaria season. Gnotobiotic mice colonized with the fecal samples of malaria-susceptible children had a significantly higher parasite burden following Plasmodium infection compared to gnotobiotic mice colonized with the fecal samples of malaria-resistant children. Shotgun metagenomics analysis revealed that the fecal microbiome of the susceptible children was enriched for bacteria associated with inflammation, mucin degradation, gut permeability and inflammatory bowel disorders (e.g., Ruminococcus gauvreauii, Ruminococcus torques, Dorea formicigenerans, Dorea longicatena, Lachnoclostridium phocaeense and Lachnoclostridium sp. YL32). However, the susceptible children also had a greater abundance of bacteria known to produce anti-inflammatory short-chain fatty acids and those associated with favorable prognosis and remission following dysbiotic intestinal events (e.g., Anaerobutyricum hallii, Blautia producta and Sellimonas intestinalis). Metabolomics analysis of the human fecal samples corroborated the existence of inflammatory and recovery-associated features within the gut microbiome of the susceptible children. There was an enrichment of nitric oxide-derived DNA adducts (deoxyinosine and deoxyuridine) and long-chain fatty acids, the absorption of which has been shown to be inhibited by inflamed intestinal epithelial cells, and a decrease in the abundance of mucus phospholipids. Nevertheless, there were also increased levels of pseudouridine and hypoxanthine, which have been shown to be regulated in response to cellular stress and to promote recovery following injury or hypoxia. Overall, these results indicate that the gut microbiome may contribute malaria pathogenesis and suggest that therapies targeting intestinal inflammation could decrease malaria susceptibility.
Question: Write a study description for the study titled 'MaHPIC Experiment HuB - Metabolomics analysis of human plasma from patients infected with Plasmodium falciparum and P.vivax for discovery of diagnostic markers of malaria'.
Answer: MaHPIC Experimental Description: This study is based on archived plasma from samples collected between 2011 and 2014. Patients in Thailand who were infected with Plasmodium falciparum (30 subjects), P. vivax (30 subjects), co-infected with P. falciparum and P. vivax (22 subjects) were included, alongside two sets of non-malaria cases: non-malarial febrile illnesses (30 subjects) and healthy controls (30 subjects). Malaria subjects were enrolled under ethics research protocol TMEC 11-033, and non-malaria cases were enrolled under TMEC 14-025, both approved by the Ethical Review Committee of the Faculty of Tropical Medicine, Mahidol University, Thailand. All protocols and documentation were reviewed and sample shipments approved by the Emory IRB. Subjects were enrolled at the Ministry of Public Health (MOPH) Malaria Clinics in the Kanchanaburi and Tak provinces clinic between August 2011 and August 2014.Within the MaHPIC, this project is known as ‘Experiment HuB’. Samples were obtained in collaborations with Jetsumon Prachumsri, Rapathborn Patrapuvich, Viravarn Luvira, Siriwan Rungin, Teerawat Saeseu, and Nattawan Rachaphaew at the Mahidol Vivax Research Unit and the Hospital for Tropical Diseases at Mahidol University. Untargeted metabolomics results were produced by Dean Jones at Emory University. Quantitative Metabolomics using the Biocrates platform results were produced by Dr. Regina Cordy and Manoj Khadka at Emory University. To access other publicly available results from HuB and other MaHPIC Experiments visit http://plasmodb.org/plasmo/mahpic.jsp. This page will be updated as datasets are released to the public.Complete list of dataset contributors:The MaHPIC Consortium, Jeremy D. DeBarry, Mary R. Galinski, Dean P. Jones, Manoj Khadka, Jessica C. Kissinger, Shuzhao Li, Viravarn Luvira, Regina Joice Cordy, Esmeralda VS Meyer, Mustafa Nural, Eric A. Ortland, Rapathborn Patrapuvich, Suman B. Pakala, Nattawan Rachaphaew, Teerawat Saeseu, Siriwan Rungin, ViLinh Tran, Jetsumon P. Sattabongkot, Karan UppalPlease contact the Informatics Core with any questions / concerns / suggestions - mahpic-infocore@uga.eduLinked Studies: Malaria Host-Pathogen Interaction Center (MaHPIC)
Question: Write a study description for the study titled 'DIVA Metabolomics: Differentiating Vaccination Status Following Viral Challenge Using Metabolomic Profiles'.
Answer: This study employed metabolomic profiling technologies, to identify metabolites (small molecules) in blood which are found at different levels in vaccinated compared to non-vaccinated animals exposed to virus.
Question: Write a study description for the study titled 'Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type-2 diabetes'.
Answer: In this study we explored a unique cohort of 43 samples to build a map of metabolites varying in T2D across five different tissues (subcutaneous adipose tissue, liver, pancreatic islets, skeletal muscle and blood serum). The samples originate from the Excellence in Diabetes biobank (EXODIAB) in Sweden. To our knowledge, this is the first attempt to create a map of metabolites across various metabolic-relevant tissues for the same cohort of individuals. In total we identified 286 unique metabolites, 32% of which were significantly altered between non-diabetes and T2D. We found evidence that amino acids (AAs) and bile acids are elevated for specific tissues in T2D and significantly associated to the percentage of glycosylated hemoglobin A1c (HbA1c). We showed that carnitines and lysophosphatidylcholines (LPCs) are the most significantly altered metabolites in muscle, liver and serum in T2D. Finally, we attempted to explore the progression to overt T2D and suggest potential biomarkers in the early development of T2D, i.e. from non-diabetes to pre-diabetes to T2D.
Question: Write a study description for the study titled 'Mining for metabolic responses to long-term salt stress: a case study on Arabidopsis thaliana Col-0 (B)'.
Answer: New metabolic profiling technologies provide data on a wider range of metabolites than traditional targeted approaches. Metabolomic technologies currently facilitate acquisition of multivariate metabolic data using diverse, mostly hyphenated, chromatographic detection systems, such as GC-MS or liquid chromatography coupled to mass spectrometry, Fourier-transformed infrared spectroscopy or NMR-based methods. Analysis of the resulting data can be performed through a combination of non-supervised and supervised statistical methods, such as independent component analysis and analysis of variance, respectively. These methods reduce the complex data sets to information, which is relevant for the discovery of metabolic markers or for hypothesis-driven, pathway-based analysis. Plant responses to salinity involve changes in the activity of genes and proteins, which invariably lead to changes in plant metabolism. Here, we highlight a selection of recent publications in the salt stress field, and use gas chromatography time-of-flight mass spectrometry profiles of polar fractions from the plant models, Arabidopsis thaliana, Lotus japonicus and Oryza sativa to demonstrate the power of metabolite profiling. We present evidence for conserved and divergent metabolic responses among these three species and conclude that a change in the balance between amino acids and organic acids may be a conserved metabolic response of plants to salt stress.
Question: Write a study description for the study titled 'Untargeted metabolomic investigate milk and ruminal fluid of Holstein cows supplemented with Perilla frutescens leaf'.
Answer: Milk compounds are important for human nutrient requirements and health. The ruminal metabolic profile is responsible for dietary nutrition and determines milk production. Perilla frutescens leaf (PFL) is a commonly used medicinal herb due to its bioactive metabolites. This study elucidated the effects of PFL on the metabolome of two biofluids (rumen fluid and milk) of 14 cows fed a basic total mixed ration diet (CON, n = 7) and supplemented with 300 g/d PFL per cow (PFL, n = 7) by ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. Milk PE-NMe (18:1(9Z)/18:1(9Z)) and DG (18:0/20:4(5Z,8Z,11Z,14Z)/0:0), oleanolic acid, and nucleotides were upregulated, and milk medium-chain fatty acids (2-hydroxycaprylic acid) and isoflavones (daidzin, ononin) were down-regulated in response to PFL. The supplementation of PFL increased the abundance of pyrimidine nucleotides both in rumen fluid and milk. The pathways of pyrimidine metabolism and biosynthesis of unsaturated fatty acids were enriched both in the rumen fluid and milk. We also found the milk 2-hydroxycaprylic acid was positively correlated with ruminal uridine 5-monophosphate, and was negatively correlated with ruminal deoxycytidine, and the milk thymidine was positively correlated with ruminal icosenoic acid. This study found that the supplementation of PFL could alter the ruminal metabolic profiles and milk synthesis through regulation of the pathways of pyrimidine metabolism and biosynthesis of unsaturated fatty acids. Our new findings provide comprehensive insights into the metabolomics profile of rumen fluid and milk, supporting the potential production of Perilla frutescens milk in dairy cows.
Question: Write a study description for the study titled 'Bone loss with aging is independent of gut microbiome in mice.'.
Answer: Emerging evidence suggests a significant role of gut microbiome in bone health. Aging is well recognized as a crucial factor influencing the gut microbiome. In this study, we investigated whether age-dependent microbial change contributes to age-related bone loss in CB6F1 mice. The bone phenotype of 24-month-old germ-free (GF) mice were indistinguishable compared to their littermates colonized by fecal transplant at 1-month-old. Moreover, bone loss from 3 to 24-month-old was comparable between GF and specific pathogen-free (SPF) mice. Thus, GF mice were not protected from age-related bone loss. 16S rRNA gene sequencing of fecal samples from 3-month and 24-month-old SPF males indicated an age-dependent microbial shift with an alteration in energy and nutrient metabolism potential. An integrative analysis of 16S predicted metagenome function and LC-MS fecal metabolome revealed an enrichment of protein and amino acid biosynthesis pathways in aged mice. Microbial S-adenosyl methionine metabolism was increased in the aged mice, which has previously been associated with the host aging process. Collectively, aging caused microbial taxonomic and functional alteration in mice. To functionally prove that the young and old microbiome impacts differently on the bone, we colonized GF mice with fecal microbiome from 3-month or 24-month-old SPF donor mice for 1 and 8 months. The effect of microbial colonization on bone phenotypes was independent of the microbiome donors' age. In conclusion, our study indicates age-related bone loss occurs independent of gut microbiome.
Question: Write a study description for the study titled 'Two apples a day modulate human:microbiome co-metabolic processing of polyphenols, tyrosine and tryptophan'.
Answer: PURPOSE: Validated biomarkers of food intake (BFIs) have recently been suggested as a useful tool to assess adherence to dietary guidelines or compliance in human dietary interventions. Although many new candidate biomarkers have emerged in the last decades for different foods from metabolic profiling studies, the number of comprehensively validated biomarkers of food intake is limited. Apples are among the most frequently consumed fruits and a rich source of polyphenols and fibers, an important mediator for their health-protective properties.﻿METHODS: Using an untargeted metabolomics approach, we aimed to identify biomarkers of long-term apple intake and explore how apples impact on the human plasma and urine metabolite profiles. Forty mildly hypercholesterolemic volunteers consumed two whole apples or a sugar and energy-matched control beverage, daily for 8 weeks in a randomized, controlled, crossover intervention study. The metabolome in plasma and urine samples was analyzed via untargeted metabolomics.RESULTS: We found 61 urine and 9 plasma metabolites being statistically significant after the whole apple intake compared to the control beverage, including several polyphenol metabolites that could be used as BFIs. Furthermore, we identified several endogenous indole and phenylacetyl-glutamine microbial metabolites significantly increasing in urine after apple consumption. The multiomic dataset allowed exploration of the correlations between metabolites modulated significantly by the dietary intervention and fecal microbiota species at genus level, showing interesting interactions between Granulicatella genus and phenyl-acetic acid metabolites. Phloretin glucuronide and phloretin glucuronide sulfate appeared promising biomarkers of apple intake; however, robustness, reliability and stability data are needed for full BFI validation.CONCLUSION: The identified apple BFIs can be used in future studies to assess compliance and to explore their health effects after apple intake. Moreover, the identification of polyphenol microbial metabolites suggests that apple consumption mediates significant gut microbial metabolic activity which should be further explored.