Different from genomics and proteomics, the unique challenges of metabolomics lie in the following:
1. The various physical and chemical properties of different small metabolite molecules, limitation in mass spectrometry methods and the low abundance of small molecules altogether limit the detection coverage of metabolites;
Characteristic differences between current standard techniques and clinical mass spectrometry tests
2. The amount of unknown metabolites and the absence of unified reference database has rendered current quantitative annotation and analysis extremely challenging.
By thoroughly and systematically recording thousands of natural small molecules (as standard references), the company devotes itself to establish a unique, world-class metabolite standard database. Until now more than 8,000 entries have been included. We have also established databases consisting of isotope biological markers for different species, tissues under different developmental stages. Each database contains over 5000 metabolite entries and each metabolite entry has been determined with unique chemical sum formula. The combination of these approaches has granted us the great potential to integrate more and more metabolomics information into the multi-omics data pool.
3. Different factors such as detection environment, detection method during data acquisition may cause retention time shifts, influence on detection sensitivity, which may subsequently lead to difficulties in repeatability and standardization during data collection, and difficulties in standardization and automation during data analysis process.
To maximumly optimize the experimental design from biological and statistic aspects and the perspective of data application;
to develop and continuously improve our standard operation process and quality control system from sample collection, pretreatment, extraction, detection to data acquisition, processing and analysis in order to render our mass spectrometry data following characteristics: adapts to experimental designs reflecting metabolomic molecules changes, great biological and statistical significance, excellent quality control system and strict standard operating process to maximize signal-to-noise ratio, high data comparability of metabolomic and lipid molecules from same samples, high repeatability derived from internal R&D mass spectrometry data processing and algorithm.
4. Differences in the magnitudes of different omics data and the difference in molecular spatio-temporal changes have brought challenges to multi-omics data integration and analysis.
In addition to our strength in generating reliable and meaningful metabolomic data based on our highly standardized platform and solid biological and clinical design, we have profound understanding in multiple omics data integration (e.g. genomic, proteomic, phenotypic data) and algorithm development for specific application. We provide integrated solutions for revealing underlying biological and physiologic mechanisms, identification of markers associated with variable traits or diseases.
Multi-omics data integration and analysis pathway
Combining its rich experience in omics data analysis with its powerful equipment platform, Metanotitia has devoted its unique technology into the discovery and determination of disease-related biological markers for applications in early stage disease diagnosis, benign & malignant tumor diagnosis, clinical effect and prognosis monitoring.
As the ultimate executors in life activities, the changes in metabolite level directly reflect disease occurrence and development within organism. In fact, the majority of disease markers are metabolites and its great potentials in disease diagnosis has been well recognized. Current known disease markers, especially tumor markers have low sensitivity and specificity, these characteristics have made early, effective and accurate disease (especially cancer) detection and diagnosis rather difficult and challenging.
The discovery and application of disease markers can be divided into three
stages: high-throughput discovery (discover numerous potential markers from
small scale samples); to preliminary verification (obtain reliable markers from
medium scale samples); and to large scale validation (identify and confirm the
most reliable markers) before clinical applications. Metanotitia utilizes ThermoFisher's
Orbitrap Ultra High Resolution Mass Spectrometry Platform to highly efficiently
conduct the entire process of disease markers from discovery to application
Discover the quantitative changes between the proteome of a healthy population and a population with specific disease state through blood, urine or biopsy sample analysis, screen and identify disease-related potential marker or marker panel.
2. Verification and validation
Through large scale sample examinations and analysis, individual differences and experimental differences can be excluded and biological markers with high specificity can be screened and identified. Medium scale verification and large scale validation to confirm biological marker’s validness in distinguishing between healthy people and disease patients, the key of which lies in the standardized analytical process.
To apply the biological makers discovered and identified on mass spectrometry based detection and quantification in clinical detection, early diagnosis, benign and malignant tumors determination, clinical efficacy testing.