![]() ![]() Finally, the analysis of more complex samples by LC-MS can produce thousands of features, represented as pairs of a retention time (RT) and a mass/charge value ( m/ z), that in fact correspond to a much smaller number of actual analytes. Reproducibility, method development, and transfer may also be affected if the observed species change in unpredictable, compound-dependent ways. Furthermore, targeted multiple reaction monitoring (MRM) quantitation may seem immune to these effects, but sensitivity can suffer if the signal is distributed between many species. Data acquisition can be impacted, for example in data-dependent analysis (DDA) where species selected for fragmentation may be redundant and/or refractory, so valuable time is spent collecting useless data. Spectral interpretation is more complicated since the “true” molecular ions, i.e., +, may be hard to determine or even absent. The presence of numerous related species has many consequences. Although analyte ions are frequently formed by the addition or removal of protons to generate + ions in positive mode and − ions in negative mode, many other ionization processes are known, so even the spectrum of a single analyte may contain many different species. Ionization of the sample molecules is a critical step and is often achieved using electrospray ionization (ESI) since it is sensitive, straightforward, and amenable to polar molecules. Mass spectrometry (MS) and hyphenated liquid chromatography-mass spectrometry (LC-MS) are widely used for qualitative and quantitative analyses in many applications, including metabolomics, pharmaceutical development, forensics, doping control, and proteomics. Detection of low-intensity ions and correct grouping were found to be essential for annotation performance. The results were benchmarked against three other annotation tools, CAMERA, findMAIN, and CliqueMS: findMAIN and mzAdan consistently produced higher numbers of + candidates compared with CliqueMS and CAMERA, especially with co-eluting metabolites. MzAdan was then integrated in a workflow with XCMS for the untargeted LC-MS data analysis of a 52 metabolite standard mix and a human urine sample. False positives were monitored with mass accuracy and bias as well as chromatographic behavior which led to the identification of adducts with calcium instead of the expected potassium. This resulted in 402 correct + identifications and, with combinations of sodium, ammonium, and potassium adducts and water and ammonia losses within a tolerance of 10 mmu, explained close to 50% of the total ion current. MzAdan was first tested with a collection of 408 analytes acquired with flow injection analysis. The tool annotates single or multiple accurate mass spectra using a customizable adduct annotation list and outputs a list of + candidates. We introduce mzAdan, a nonchromatography-based multipurpose standalone application that was developed for the annotation and exploration of convolved high-resolution ESI-MS spectra. In many cases, annotation is integrated in metabolomics workflows and is based on specific chromatographic peak-picking tools. This diversity challenges automatic annotation and is often poorly addressed by current annotation tools. Not only protonated, deprotonated, and neutral loss ions but also sodium, potassium, and ammonium adducts as well as oligomers are frequently observed. ![]() Annotation and interpretation of full scan electrospray mass spectra of metabolites is complicated by the presence of a wide variety of ions.
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