The lack of reproducible data due to matrix effects in untargeted metabolomics has been an on-going major concern. Ion suppression, interference from coeluted chemical components (sample matrix, solvent or LC-MS system components), is often observed as the loss of analyte ionization response and negatively affects precision, accuracy, and reproducibility (over- or underestimation of analyte levels). The optimization and validation of quantitative LC-MS methods relies on the assessment and correction of ion suppression.
We conducted a simple experimental to understand the level of suppression of compounds in a common human plasma sample that had been serially diluted. Once the impact of ion suppression was assessed and quantified, we developed a workflow to minimize variability and to correct the ion suppressed data which then could be effectively normalized to achieve reproducible measurements. Why work up bad data?
IROA is an isotopic methodology in which all biological molecules are uniformly and randomly labeled to create informative isotopic patterns that are readily discriminated from artifacts. The IROA protocol generates an IROA Internal Standard providing specific molecular information so that the small biochemical molecules within biological samples may be easily and more accurately identified. Because of the uniform nature of the labeling, these patterns are revealed not only in the MS, but also in all fragments in any subsequent MS/MS. SWATH® acquisition, a data independent acquisition (DIA) workflow is well adopted in quantitative discovery proteomics, but still not commonly used in discovery metabolomics.
SWATH acquisition allows a user to collect MS and MS/MS of every detectable metabolite in their sample, thus creating a digital map of the metabolome. Variable Window SWATH acquisition (an enhanced way of collecting MS/MS, using targeted mass windows in denser regions of the MS spectrum) allows for targeted specificity. The use of IROA with a SWATH variable window acquisition has allowed us to collect extremely advanced information for the biological components of a mixture, with significantly enhanced accurate identification and quantitation, clearly differentiating MS/MS IROA-SWATH peaks from artifacts. The MS/MS IROA pattern can be observed by varying the mass window overlap during SWATH acquisition which is unique for any data independent acquisition (DIA) approach. IROA can correctly assign formulae to all IROA peaks in both the MS and MS/MS scans. This is the first example whereby the correct formula is routinely found not only for the parent peak but also all fragments. Quantitation of any compound may be done at either the MS or MS/MS level.
Where it is not possible to label the biological sample, the “Phenotypic” IROA Protocol is applied. Here the experimental sample is collected at natural abundance and mixed with a fully predefined “Standard” that has been isotopically labeled using IROA media in which all of the carbon components are randomly labeled at 95% U-13C. An ideal Standard would be one that represented the entire metabolome of the sample under study. This Application Note describes the labeling and cell growth of HepG2 for use as an internal Standard.
The IROA protocol has been applied in a phenotypic analysis of field grown maize (Zea mays) to understand the biochemical differences across selected genotypes when exposed to drought conditions. In this IROA phenotypic analysis, field-grown leaves containing carbon at natural abundance were compared to a standard maize leaf that was grown to contain universally-distributed ~97% 13C; resulting in a targeted analysis using a biologically-relevant internal standard. At 97% 13C the IROA patterns were sufficient to find isotopically labeled peaks, identify their 12C isotopomers, and remove artifacts, noise and extraneous peaks using the IROA ClusterFinder software. With accurate mass and IROA, the identification of observed component peaks to chemical formula is unambiguous. The benefit of IROA is it takes into account variances introduced during sample-preparation and analysis, including ion suppression.
Myxobacteria represent an important source of novel natural products exhibiting a wide range of biological activities. In this Application Note, the IROA tools coupled with the Bruker Daltonik UHR- Q-TOF instrument (maXis 4G) were employed to analyze the secondary metabolome of myxobacteria to detect changes triggered by differential iron supply.