A significant bottleneck in metabolomics data interpretation is the effective use of domain knowledge to assign structural information based on fragmentation patterns. The mass spectrometry query lang...

In/post-source fragments (ISFs) arise during electrospray ionization or ion transfer in mass spectrometry when molecular bonds break, generating ions that can complicate data interpretation. Although ISFs have been recognized for decades, their contribution to untargeted metabolomics - particularly in the context of the so-called “dark matter” (unannotated MS or MS/MS spectra) and the “dark metabolome” (unannotated molecules) - remains unsettled. This ongoing debate reflects a central tension: while some caution against overinterpreting unidentified signals lacking biological evidence, others argue that dismissing them too quickly risks overlooking genuine molecular discoveries. These discussions also raise a deeper question: what exactly should be considered part of the metabolome? As metabolomics advances toward large-scale data mining and high-throughput computational analysis, resolving these conceptual and methodological ambiguities has become essential. In this perspective, we propose a refined definition of the “dark metabolome” and present a systematic overview of ISFs and related ion forms, including adducts and multimers. We examine their impact on metabolite annotation, experimental design, statistical analysis, computational workflows, and repository-scale data mining. Finally, we provide practical recommendations - including a set of dos and don’ts for researchers and reviewers - and discuss the broader implications of ISFs for how the field explores unknown molecular space. By embracing a more nuanced understanding of ISFs, metabolomics can achieve greater rigor, reduce misinterpretation, and unlock new opportunities for discovery.

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 spectromet...

Physiologically relevant omega-positions of double bonds in fatty acyls in complex lipids can now only be identified with specialized instrumentation. Here, the authors present a computational approac...

With the exception of molecules acquired through the lungs, skin absorption, or part of a medication regime, nearly all molecules in our bodies origin…

To improve annotation in non-targeted metabolomics studies, authors develop a Multiplexed Chemical Metabolomics (MCheM) platform, combining post-column derivatization with integrated data processing. ...

Background Untargeted tandem mass spectrometry serves as a scalable solution for the organization of small molecules. One of the most prevalent techniques for analyzing the acquired tandem mass spectr...

Interfacing R's Spectra package with the Python world. - rformassspectrometry/SpectriPy

Mass spectrometry data mining tools enabled the creation of an MS/MS spectral library containing hundreds of N-acyl lipids, including conjugates with short-chain fatty acids. This resource enabled the...

Background The supramolecular structure and composition of milk fat globules in breast milk is complex. Lipid droplets in formula milk are typically smaller compared to human milk and differ in their ...

Bile acids have important roles in human metabolism and immune regulation. In this Perspective, Dorrestein and colleagues discuss the technologies and data science-related approaches that are improvin...

The etiology of Alzheimer’s Disease (AD) remains largely unclear but is likely driven by gene-environment interactions. Here, we present a multi-organ untargeted metabolomics dataset (2,271 samples) g...