Domingo-Almenara, X.; J. R. Montenegro-Burke, C. Guijas, E. L.-W. Majumder, H. P. Benton and G. Siuzdak (2019) Autonomous METLIN-guided in-source fragmentation detection increases annotation confidence in untargeted metabolomics. ACS Analytical Chemistry. [doi]:1021/acs.analchem.8b03126
A clever adaptation of METLIN to turn an annotation problem into an identification advantage by Xavi Domingo and Scripps Research Institute team has enabled high throughput metabolomics analysis; aligning metabolites with genomics data, a significant advantage for ENIGMA’s efforts. As of August 2019, METLIN has over 500,000 molecular standards with experimental tandem MS data. METLIN technology platform is now routinely used for both the identification of known metabolites and other chemical entities. More interesting though is that it can also be used to identify unknowns specifically through similarity searching. These applications are particularly prominent in the field of microbial sciences, in particular, it has supported numerous studies within our ENIGMA program. For example, METLIN is currently in use in collaborations between team members Baliga, Fields, and Adams labs in the Active Fraction and Environmental Simulation and Monitoring Campaigns. Specifically, METLIN has been used to facilitate 1) the metabolomic profiling of field communities grown in reactors over time 2) Stable isotope probing for nitrogen cycling 3) Contributing data to metabolic models 4) Systems biology analysis by incorporating metabolite data with transcriptomic
profiling 5) Monitoring and discovery of novel sulfur-containing metabolites and 6) Determination of active metabolites from the active fraction of microbes from Oak Ridge Research site field communities.