Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

GNPS_Sytem wide MS class 2018 Food group 1 meat

ABSTRACT: Metabolite analysis of meat samples (with and without tetracycline addition). Samples were extracted in ethanol using FoodOmics protocols. Data were acquired using a Bruker Daltonics maXis Impact and C18 RP-UHPLC. Positive polarity acquisition of LC-MS and LC-MS/MS.

INSTRUMENT(S): maXis

ORGANISM(S): Food Metagenome (ncbitaxon:870726)

SUBMITTER: Pieter Dorrestein

PROVIDER: MSV000082423 | GNPS | Thu May 31 11:33:00 BST 2018

REPOSITORIES: GNPS

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

GNPS_Sytem wide MS class 2018 Food group 2 tomato

Project description:Metabolite analysis of tomato samples. Samples were extracted in ethanol using FoodOmics protocols. Data were acquired using a Bruker Daltonics maXis Impact and C18 RP-UHPLC. Positive polarity acquisition of LC-MS and LC-MS/MS.

2018-05-23 | MSV000082391 | GNPS

GNPS_Sytem wide MS class 2018 Food group 4 milk_yogurt

Project description:Metabolite analysis of milk and yogurt samples. Samples were extracted in ethanol using FoodOmics protocols. Data were acquired using a Bruker Daltonics maXis Impact and C18 RP-UHPLC. Positive polarity acquisition of LC-MS and LC-MS/MS.

2018-05-23 | MSV000082387 | GNPS

GNPS_Sytem wide MS class 2018 Food group 3 coffee

Project description:Metabolite analysis of coffee samples (brewed with hot water and from whole beans). Samples were extracted in ethanol using FoodOmics protocols. Data were acquired using a Bruker Daltonics maXis Impact and C18 RP-UHPLC. Positive polarity acquisition of LC-MS and LC-MS/MS.

2018-05-23 | MSV000082386 | GNPS

GNPS_Sytem wide MS class 2018 Food group 5 tea

Project description:Metabolite analysis of tea samples (brewed with hot water and from tea leaves). Samples were extracted in ethanol using FoodOmics protocols. Data were acquired using a Bruker Daltonics maXis Impact and C18 RP-UHPLC. Positive polarity acquisition of LC-MS and LC-MS/MS.

2018-05-23 | MSV000082388 | GNPS

GNPS Sytem wide MS class 2018 FoodOmics - Full

Project description:Metabolite analysis of food and beverage samples. Samples were extracted in ethanol using FoodOmics protocols. Data were acquired using a Bruker Daltonics maXis Impact and C18 RP-UHPLC. Positive polarity acquisition of LC-MS and LC-MS/MS.

2018-10-09 | MSV000083014 | GNPS

Simplifying adipogenic differentiation – a step towards a food compatible media

Project description:Cultivated meat is a promising technology with the potential to mitigate the ethical and environmental problems associated with traditional meat. Fat plays a key role in meat flavour and texture, however little academic research has focused on fat production resulting in a paucity of adequate adipogenesis protocols for most livestock-derived cells. The development of a suitable protocol is essential to pave the way for cultivated fat as an ingredient, as the traditional cocktail of IBMX, dexamethasone, insulin and rosiglitazone is not food-compatible. Here, we investigate the necessity of these four classic adipogenesis inducers in a serum-containing and an in-house developed serum-free medium (DMAD). Using a full-factorial design, we show that only two of these four inducers, insulin and rosiglitazone, are necessary for adipogenic differentiation, as measured by gene expression changes and lipid accumulation. Additionally, two glucocorticoid receptor binding molecules, progesterone and hydrocortisone, found in DMAD and FBS, are also required. Importantly, this protocol also leads to mature adipocytes in 3D, edible hydrogels. This was demonstrated in both media types and in four species; ruminant and monogastric. We therefore propose this as an alternative protocol for adipogenesis, which, given the replacement of rosiglitazone by a food-compatible PPARγ agonist, can be suitable for human consumption.

2023-01-18 | GSE206990 | GEO

food metagenome

Project description:goat meat Metagenome

| PRJNA347408 | ENA

food metagenome

Project description:Yao meat Metagenome

| PRJNA408222 | ENA

Metabolomics2018_demo_data

Project description:Example metabolite analysis of food and stool samples. Samples were extracted in ethanol using FoodOmics protocols. Data were acquired using a Bruker Daltonics maXis Impact and C18 RP-UHPLC. Positive polarity acquisition of LC-MS and LC-MS/MS.

2018-06-11 | MSV000082453 | MassIVE

food metagenome

Project description:miCROgame - microbiota of game meat sausage

| PRJNA428753 | ENA