Email:
support-global@metwarebio.com
Aug 23, 2023
Metabolomic methodologies are broadly categorized into two primary approaches: untargeted and targeted metabolomics. Untargeted metabolomics involves a comprehensive analysis, capturing all metabolites within a sample, even those yet to be identified. Conversely, targeted metabolomics focuses on quantifying a specific, well-defined set of biochemically annotated analytes. Each approach, whether untargeted or targeted, possesses distinct advantages and drawbacks, often showcasing trade-offs between the two in metabolomic analyses.
Distinguishing between targeted and untargeted metabolomics hinges on their scope. Targeted metabolomics concentrates on a known set of metabolites, often validating hypotheses by precisely measuring around 20 metabolites with absolute quantification. On the other hand, untargeted metabolomics explores all metabolites in a sample, offering qualitative identification and relative quantification of thousands of metabolites, fostering discovery and hypothesis generation.
Procedurally, targeted metabolomics involves specific extraction procedures, while untargeted metabolomics necessitates global metabolite extraction. Both methods utilize techniques like NMR, GC-MS, or LC-MS for data acquisition. However, due to the intricacies of untargeted metabolomics, additional data processing steps become essential. Both approaches employ diverse data analysis methods, including bioinformatics, enrichment analysis, pathway analysis, and the creation of metabolic networks. The selection between these methods relies on the researcher's objectives and the study's specific characteristics.
Targeted metabolomics offers distinct advantages by focusing on identifying and characterizing known metabolites, leveraging established knowledge of metabolic processes and molecular pathways. It utilizes isotopically labeled standards and defined parameters, minimizing false positives and analytical artifacts. Absolute quantification enhances precision compared to untargeted metabolomics, and optimized sample preparation reduces the impact of high-abundance molecules. However, its limitations include dependency on prior knowledge, a restricted number of measured metabolites (usually around 20), and an increased risk of overlooking relevant ones. Researchers should carefully evaluate the alignment of targeted metabolomics with their research questions before implementation, considering its designed focus on known metabolites.
The strengths of untargeted metabolomics complement the limitations of targeted approaches. Geared towards discovery and hypothesis generation, untargeted methods don't require extensive prior knowledge of identified metabolites. This allows for the measurement of thousands of metabolites in a single sample, enabling comprehensive analyses for metabolite identification and metabolic profiling. Key advantages include flexible biological sample preparation, systematic measurement of numerous metabolites in an unbiased manner, generation of extensive quantitative data without internal standards, and the potential to uncover both known and unknown metabolites, leading to discoveries of previously unidentified or unexpected changes.
Despite providing valuable insights into novel processes, untargeted metabolomics method comes with several limitations. The extensive data generated requires complex statistical analyses, and identifying unknown metabolites without reference standards poses challenges. Other drawbacks encompass unpredictable or uninformative fragmentation patterns, difficulty interpreting false discovery rates, decreased precision due to relative quantification, and the need for additional time and resources for statistical analysis and method selection. Additionally, there's a bias toward detecting higher abundance metabolites.
Researchers are strategically combining multiple analytical methods to address the limitations of individual metabolomics techniques. For instance, in exploring the metabolome linked to hyperuricemia, a study used untargeted metabolomics for initial biomarker screening, followed by targeted metabolomics for validation. This integrative approach has unveiled insights into hyperuricemia and shed light on diseases like cardiovascular disease, neurodegenerative conditions, diabetes, and cancer. This widely-targeted metabolomics technology is a process that combines DDA and MRM data acquisition modes based on Q-TOF and QQQ (triple quadrupole) mass spectrometers. First, untargeted metabolomics using high-resolution mass spectrometers is performed to collect primary and secondary mass spectrometry data from various samples. These data are compared against databases for high throughput metabolite identification. After that, targeted metabolomics using low-resolution QQQ mass spectrometers in MRM mode is performed to collect mass spectrometry data and metabolite quantity from each sample based on the metabolites detected from the high-resolution mass spectrometer.
Scientists are now embracing "semi-targeted" analyses involving larger predefined lists of targets (e.g., hundreds of metabolites) without specific hypotheses. This approach has been instrumental in advancing our understanding of physiology and disease, notably identifying key metabolites associated with an increased risk of future pancreatic cancer. Additionally, integrating metabolomics with genome-wide association studies (mGWAS) has revealed genetic associations with changing metabolite levels, providing deeper insights into the causal mechanisms behind physiology and disease.
.png "Targeted_vs_Untargeted_vs_Widely-targeted_Metabolomics_workflow")
Metware Biotechnology Inc. (MetwareBio) is a metabolomics CRO focusing on developing and applying innovative metabolome technologies to life science and health research. Based on the high-throughput, ultra-sensitive and patented 'widely targeted metabolomics' technology, as well as large-curated metabolic database, MetwareBio offers 'one-stop metabolomics and multi-omics research and analysis services' for research institutes, hospitals and pharmaceutical companies.
