MWDB Major Upgrade: 20,000 plant metabolites
MWDB (Metware Database) can now detect 20000 types of plant metabolites
Since 2014, Metware Biotechnology has been pushing the boundaries of metabolite detection. Our featured product Widely-Targeted Metabolomics for Plants has been undergoing a major upgrade this year where our identifiable plant endogenous metabolites rose to 20,000, a doubling from our previous plant metabolite database of 10,000!
Average identified metabolites: 1,300 widely targeted metabolite detection in real samples
Applying this metabolome database to the detection of different species or tissue types, the average number of substances detected in a sample can be as much as 1300. Below, we present real outputs using Oryza sativa samples.
Unvealing the data:
The graph below shows different tissues types from O. sativa averages to 1300 identified metabolites.
The data reveals that we can detect over 800 secondary metabolites and over 400 primary metabolites. Our observations here is in concordance with published literature where primary metabolites in plants are relatively conserved ranging around 1000 types, whereas secondary metabolites vary greatly between species and can range from 0.2 ~ 1 million. This is a significant improvement in identifying secondary metabolites in plants.
Analysis of detected metabolites: wide-coverage
Analyzing the metabolomics database in various tissues, we find that flavonoids and phenolic acids stands out whereas other metabolites show large differences between tissue types. Due to these differences, it is best to cover all types of metabolites in a
metabolomics study.
Comprehensive analysis in final report: 12 analyses and 22 figures
In addition to the upgrading of the database, we also updated our analysis reports to include 12 analyses and 22 figures.
Reference:
1. A multi-omic study uncovers a bZIP23-PER1A–mediated detoxification pathway to enhance seed vigor in rice.
2. Rice metabolic regulatory network spanning its entire life cycle.
3. A molecular switch in sulfur metabolism to reduce arsenic and enrich selenium in rice grain.
4. Loss function of SL (Sekiguchi lesion) in the rice cultivar Minghui 86 leads to enhanced resistance to (hemi)biotrophic pathogens.
5. Transcriptomic and Metabolomic Responses of Rice Plants to Cnaphalocrocis medinalis Caterpillar Infestation.
6. Dynamic transcriptome and metabolome analyses of two types of rice during the seed germination and young seedling growth stages.
7. Analysis of Global Methylome and Gene Expression during Carbon Reserve Mobilization in Stems under Soil Drying.
8. UDP-glucosyltransferase regulates grain size and abiotic stress tolerance associated with metabolic flux redirection in rice.
For more information about metabolome project, please feel free to contact us!
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