Untargeted
Metabolomics

Untargeted metabolomics is a powerful hypothesis-generating approach designed to survey a broad range of metabolites in biological samples. The aim is to capture as comprehensive a view of the metabolome as possible, which is challenging due to the diverse nature of metabolites in terms of their chemical properties, concentrations, and biological roles. A significant challenge in untargeted metabolomics lies in the data processing and metabolite annotation stages, which are time-consuming and complex, often yielding redundant features such as in-source fragments, adducts, and isotopes.Metabolon's untargeted metabolomics platform addresses these challenges by offering extensive coverage, with a reference library containing over 5,400 metabolites across 70 major biochemical pathways. Our advanced data processing pipeline efficiently manages redundant features, ensuring accurate metabolite identification. This breadth and precision enable the capture of both known and unknown metabolites, providing researchers with a more complete metabolic snapshot and the potential to uncover novel insights into biological processes. Our approach enables the detection of a wide array of compounds, from common metabolites to rare or previously uncharacterized molecules, maximizing the potential for new discoveries and hypothesis generation in metabolomics research.

Confidence levels in metabolite identification are crucial for ensuring the reliability and reproducibility of metabolomics research. These levels, established by the Metabolomics Standards Initiative, range from Level 1 (highest confidence) to Level 5 (lowest confidence), reflecting the degree of certainty in identifying a metabolite based on various analytical parameters. Higher confidence levels are essential for drawing accurate conclusions, particularly in complex studies where misidentification could lead to erroneous interpretations of biological processes or disease mechanisms.

Metabolon addresses this critical need by employing a robust approach to metabolite identification, utilizing the largest Level 1 library in the metabolomics industry. Our proprietary library, built and curated over 20 years, contains over 5,400 entries, with approximately 85% (~4,600) being high-confidence Level 1 annotations. This is in stark contrast to other providers who often advertise large library sizes but rely on indexing to external databases rather than maintaining an internal, validated library. Such practices can lead to increased false positives and negatives, affecting reproducibility. Metabolon's approach, combining our extensive internal library with carefully selected external databases for Level 2 annotations, significantly enhances the reliability and interpretability of results. This multi-tiered identification strategy ensures that researchers receive accurate, highly actionable insights for their scientific or clinical inquiries.

Data analysis and interpretation are crucial in metabolomics due to the complexity and volume of data generated. Metabolomics experiments often produce vast datasets containing information on thousands of metabolites, making it challenging to extract meaningful biological insights without sophisticated analytical tools. Traditional approaches often require researchers to use multiple software packages, possess coding skills, or rely on static reports that most service providers deliver, which can be time-consuming and limit the depth of analysis.

Metabolon addresses these challenges with its Integrated Bioinformatics Platform, offering a comprehensive, all-in-one solution for metabolomics data analysis and interpretation. The platform seamlessly integrates advanced statistical techniques with powerful visualization tools, allowing users to effortlessly transition between principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), volcano plots, and pathway mapping within a single environment. This integrated approach streamlines the analysis process and enhances the ability to derive meaningful biological insights. The platform's intuitive interface and cloud-based architecture enable researchers to handle large datasets without the need for powerful computing hardware, making complex metabolomics data accessible and actionable for a wide range of users. By providing this unified, user-friendly solution, Metabolon empowers researchers to focus on understanding the biology driving their data, accelerating discovery and facilitating more comprehensive metabolomics research.