{'fraction_non_alphanumeric': 0.02496016994158258, 'fraction_numerical': 0.015932023366967606, 'mean_word_length': 5.9010989010989015, 'pattern_counts': {'":': 0, '<': 1, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
The detection of bacterial exometabolites in marine dissolved organic matter through ultrahigh‐resolution mass spectrometry

Bacteria play a key role in sustaining the chemodiversity of marine dissolved organic matter (DOM), yet there is limited direct evidence of a major contribution of bacterial exometabolites to the DOM pool. This study tests whether molecular formulae of intact exometabolites can be detected in natural DOM via untargeted Fourier‐transform ion cyclotron resonance mass spectrometry (FT‐ICR‐MS). We analyzed a series of quantitative mixtures of solid‐phase extracted DOM from the deep ocean, of a natural microbial community and selected model strains of marine bacteria. Under standard instrument settings (200 broadband scans, mass range 92–1000 Da), 77% of molecular formulae were shared between the mesocosm and marine DOM. However, there was < 10% overlap between pure bacterial exometabolome with marine DOM, and in mixing ratios closest to mimicking natural environments (1% bacterial DOM, 99% marine DOM), only 4% of the unique bacterial exometabolites remained detectable. Further experiments with the bacterial exometabolome DOM mixtures using enhanced instrument settings resulted in increased detection of the exometabolites at low concentrations. At 1000 and 10,000 accumulated scans, 23% and 29% of the unique molecular formulae were detectable at low concentrations, respectively. Moreover, windowing a specific mass range encompassing a representative fraction of exometabolites tripled the number of unique detected formulae at low concentrations. Routine FT‐ICR‐MS settings are thus not always sufficient to distinguish bacterial exometabolome patterns from a seawater DOM background. To observe these patterns at higher sensitivity, we recommend a high scan number coupled with windowing a characteristic region of the molecular fingerprint.