Dual MSTUS™ Normalization
A next-generation normalization algorithm that dramatically improves quantitative accuracy, precision, and reproducibility in untargeted metabolomics.
Traditional vs. Dual MSTUS™ Workflow
See how Dual MSTUS™ eliminates analytical variability to produce more accurate and biologically meaningful metabolomics data.
Traditional Workflow
Conventional metabolomics workflows are affected by analytical variability.
Ion Suppression
Matrix effects reduce signal intensity and affect metabolite quantification.
Instrument Variability
Instrument drift introduces unwanted analytical variation.
False Biological Differences
Technical artefacts may be interpreted as genuine biological changes.
Dual MSTUS™ Workflow
By using appropriate internal standards analytical variability is corrected before biological interpretation.
Ion Suppression Corrected
Matrix effects are compensated for improved quantitative accuracy.
Dual MSTUS™ Normalization
Corrects run-to-run and batch-to-batch analytical variation.
Reliable Biological Insights
Results reflect true biological differences with greater confidence.
The Problem With Conventional Normalization
Conventional normalization methods often fail to account for ion suppression, sample variability, and instrument drift. As a result, technical variation can mask true biological differences and reduce confidence in metabolomics data.
Variable Sample Input
Different extraction amounts and injection volume create inconsistent analytical signals.
Ion Suppression
Matrix effects reduce metabolite intensity and compromise quantitative accuracy.
Instrument Variability
Instrument drift and batch effects reduce reproducibility across analytical runs.
Loss of Biological Confidence
Technical variability obscures genuine biological differences and reduces confidence.
Introducing Dual MSTUS™
Built on isotope-based internal standards, Dual MSTUS™ uses suppression-corrected data to remove analytical bias and enable accurate sample normalization for more reliable metabolomic comparisons.
Raw Data
LC-MS detects thousands of metabolites.
IROA Internal Standard
Isotope-labelled standards added to every sample.
Ion Suppression Correction
Correct each metabolite for matrix effects and other ion signal losses.
Dual MSTUS™
Compare totals of 12C and 13C signals.
Normalization Factor
Generate a sample-specific normalization factor.
Normalized Metabolome
Apply factor to all metabolites consistently.
Biological Insights
Accurate, precise, and reproducible results.
Proven Across Platforms and Matrices
Dual MSTUS™ delivers consistent normalization across multiple analytical platforms and biological sample types, ensuring reliable metabolomics data regardless of matrix complexity.
- 1% median CV achieved across platforms
- 11% → >90% ion suppression accurately corrected
- Validated using multiple biological matrices and cell models
- Compatible with LC-MS, HILIC, RPLC, and IC-MS workflows
- Thousands of metabolites normalized with high precision
Everything You Need to Know About Dual MSTUS™
Explore answers to the most common questions about Dual MSTUS™, including how it works, why it outperforms conventional normalization methods, and how it improves the accuracy, reproducibility, and reliability of LC-MS metabolomics data.
Dual MSTUS™ (Mass Spectrometry Total Useful Signal) is IROA's proprietary normalization technology that uses paired 12C and 13C isotopic signals to calculate a sample-specific normalization factor. By correcting analytical variation at the metabolite level, it improves quantitative accuracy while preserving genuine biological differences between samples.
Traditional normalization methods often assume that total metabolite abundance remains constant across samples or rely on a limited number of reference compounds. Dual MSTUS™ instead uses isotope-labelled internal standards to directly measure technical variability, enabling more reliable normalization regardless of sample complexity or biological variation.
LC-MS metabolomics data can be influenced by ion suppression, matrix effects, extraction efficiency, injection variability, and instrument drift. Normalization reduces these unwanted sources of technical variation, allowing researchers to distinguish meaningful biological changes with greater confidence.
Dual MSTUS™ compares the total useful signals generated by naturally occurring 12C metabolites and their corresponding 13C-labelled internal standards. These paired measurements are used to generate a sample-specific normalization factor that is consistently applied across the metabolome.
Dual MSTUS™ is designed to compensate for common sources of analytical variability, including ion suppression, matrix effects, sample preparation inconsistencies, extraction variability, injection differences, and instrument drift. Correcting these factors improves both precision and reproducibility.
Yes. Because the normalization process is based on isotope-labelled internal standards rather than assumptions about the biological composition of samples, Dual MSTUS™ reduces technical variability while maintaining authentic biological differences that are essential for accurate interpretation.
Dual MSTUS™ has been successfully applied to a wide range of biological matrices, including plasma, serum, urine, cultured cells, tissue extracts, and other sample types commonly analysed by LC-MS metabolomics workflows.
Yes. Dual MSTUS™ is compatible with multiple chromatographic approaches, including HILIC, reversed-phase liquid chromatography (RPLC), ion chromatography-mass spectrometry (IC-MS), as well as both positive and negative ionisation modes.
By calculating a normalization factor for every individual sample, Dual MSTUS™ reduces run-to-run variability and minimizes the effects of technical inconsistencies. This produces more consistent quantitative measurements across experiments, instruments, and laboratories.
Yes. Ion suppression is a major challenge in LC-MS metabolomics because it affects the measured intensity of metabolites. Dual MSTUS™ uses isotope-labelled internal standards to detect and compensate for these suppression effects, resulting in more accurate metabolite quantification.
Yes. The scientific principles behind Dual MSTUS™ have been described in peer-reviewed publications, including research published in Nature portfolio journals and other leading metabolomics journals. These studies demonstrate the value of isotope-based normalization for improving quantitative accuracy and reproducibility.
Dual MSTUS™ is designed for researchers performing quantitative metabolomics in academic institutions, pharmaceutical research, biotechnology, clinical studies, biomarker discovery, systems biology, and precision medicine. It is particularly valuable for studies where accurate normalization and reproducible metabolite quantification are critical.