Reverse Spectral Search Reimagined: A Simple but Overlooked Solution for Chimeric Spectral Annotation

The exponential growth of untargeted metabolomics data, now reaching billions of mass spectra in public repositories, benefits from reannotation strategies for data reuse. While tandem mass spectrometry (MS/MS) library matching remains the gold standard, annotation workflows face a critical bottleneck: chimeric spectra. These composite spectra, arising from simultaneous fragmentation of multiple precursor ions, compromise the ability to annotate MS/MS spectra against nonchimeric reference spectra. Here, we demonstrate that an enhanced version of reverse spectral search, a principle first introduced in 1975 but largely overlooked, provides a simple, computationally efficient solution, rescuing up to 62% more metabolite annotations in benchmark data sets while maintaining stringent quality control. The enhanced reverse spectral search is now added to the GNPS ecosystem. Source codes can be accessed at https://github.com/Philipbear/reverse_search.