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Large Curated Database
Collected ultra-high sensitivity data of over 30,000 metabolites from over 1000 plant species. Each sample can typically identify 1000-2000 metabolites.
Widely-Targeted Metabolomics for Plants is an innovative metabolomics method that combines the benefits of untargeted metabolomics and targeted metabolomics to achieve high-throughput identification and quantification of a wide variety of metabolites associated with plants. As part of our continual R&D, Metware's metabolite database (MWDB) now houses over 30,000 plant-associated metabolites data to allow more extensive annotation and quantification from plant samples.
This methodology is especially useful in plant metabolism research where the number of metabolites far exceeds those in animals. Metware's patented Widely-Targeted Metabolomics approach stands out from many others with features such as:
Using high-resolution mass spectrometers to allow the unbiased collection of MS/MS spectrum data;
Highly curated in-house metabolomics database (MWDB) that provides accurate metabolite identification;
Using MRM analysis from QQQ to accurately quantify metabolites in each sample.
Collected ultra-high sensitivity data of over 30,000 metabolites from over 1000 plant species. Each sample can typically identify 1000-2000 metabolites.
A mature quality control system monitoring all aspects of experimentation from sample preparation to data collection.
Stable and tested sample preparation protocol stemming from processing over 1 million samples a year. Over 10 different plant tissues from 1000 plant species has been processed through our lab.
Combining AB SCIEX QTOF 6600+ ultra-high resolution mass specltrum with our in-house curated database to achieve accurate metabolite identification.
Using MRM mode from AB SCIEX Triple Quad 6500+ to achieve accurate relative quantification of metabolites.
Results of our services have been cited in over 500 publications with a combined lF over 3000.
Applicable for identifying metabolic changes in different stages of plant growth such as seed germination, stem elongation, flower development, pollination, and fruit development.
Article Spotlight: MicroTom Metabolic Network: Rewiring Tomato Metabolic Regulatory Network throughout the Growth Cycle
This study integrated high-resolution Spatio-temporal metabolome and transcriptome data to systematically explore the metabolic landscape across 20 major tomato tissues and growth stages. Based on their MicroTom Metabolic Network, they divided 540 detected metabolites and their co-expressed genes into 10 distinct clusters based on their biological functions. This enabled them to construct a global map of the major metabolic changes that occur throughout the tomato growth cycle and dissected the underlying regulatory network. Furthermore, they identified novel transcription factors that regulate the biosynthesis of important secondary metabolites such as steroidal glycoalkaloids and flavonoids.
Applicable for research in plant response to:
Abiotic stress: light (UV), water (drought, waterlogging), heavy metals (cadmium, lead, etc.), temperature (high temperature, low temperature), mechanical damage and other external factors bring reversible or irreversible effects on plants.
Biological stress: the influence of insects, bacteria, fungi, and viruses on the growth and development of plants.
Article Spotlight: Analysis of Global Methylome and Gene Expression during Carbon Reserve Mobilization in Stems under Soil Drying
In this study, the researchers looked at high-resolution DNA methylome in rice (Oryza sativa) during moderate soil drying (MD) conditions. They found a hypermethylated/up-regulated transcription factor of MYBS2 inhibited MYB30 expression and possibly enhanced β-Amylase5 expression, promoting subsequent starch degradation in rice stems under MD treatment. In addition, a hypermethylated/down-regulated transcription factor of ERF24 was predicted to interact with, and thereby decrease the expression of, abscisic acid 8'-hydroxylase1, thus increasing abscisic acid concentration under MD treatment.
Applicable for examining metabolites associated with crop phenotypes such as yield, grain width, grain color, nutrient composition, plant height, lodging resistance, fruit size, fruit color, taste, and many selected traits.
Article Spotlight: UDP-glucosyltransferase regulates grain size and abiotic stress tolerance associated with metabolic flux redirection in rice
Researchers characterized GSA1, a gene that regulates grain size and abiotic stress tolerance associated with metabolic flux redirection by exhibiting glucosyltransferase activity toward flavonoids and monolignols. GSA1 regulates grain size by modulating cell proliferation and expansion, which are regulated by flavonoid-mediated auxin levels and related gene expression. GSA1 is required for the redirection of metabolic flux from lignin biosynthesis to flavonoid biosynthesis under abiotic stress and the accumulation of flavonoid glycosides, which protect rice against abiotic stress. GSA1 overexpression results in larger grains and enhanced abiotic stress tolerance.
Article Spotlight: Identification of key taste components in loquat using widely targeted metabolomics
The researchers tackle the question of why white-fleshed loquats taste better by performing LC-MS/MS-based widely targeted metabolome analysis. A total of 536 metabolites were identified, 193 of which (including 7 carbohydrates, 12 organic acids, and 8 amino acids) were different between the cultivars. Pathway enrichment analysis also identified significant differences in phenolic pathways between the cultivars. Our results suggest that taste differences between the cultivars can be explained by variations in composition and abundance of carbohydrates, organic acids, amino acids, and phenolics.
Our curated in-house database contains over 30,000 metabolites, which includes over 1800 primary metabolites and over 28.000 secondary metabolites. Primary metabolites include sugars, amino acids, lipids, and nuclear acids. Secondary metabolites include flavonoids, polyphenol, steroidal saponins, anthraquinone, naphthoquinone, indole alkaloids, isoquin- oline alkaloids, triterpenoid saponin, tetraterpene, coumarin, lignan.
| Number Of Metabolites In Different Classes | |||
| Carbohydrates | 340 | Phenolic acids | 2100 |
| Alkaloids | 7000 | Quinones | 700 |
| Amino acid | 540 | Steroids | 1300 |
| Coumarins | 800 | Tannins | 240 |
| Flavonoids | 3700 | Terpenes | 8000 |
| Lignans | 1000 | Vitamins | 50 |
| Lipids | 500 | Glucosinolates | 150 |
| Nucleotides | 120 | Others | 3200 |
| Organic acids | 270 | ||
Please submit a detailed description of your project. We will provide you with a customized project plan metabolomics services to meet your research requests. You can also send emails directly to support-global@metwarebio.com for inquiries.
