The Molecular Fingerprint of Fluorescent Natural Organic Matter Offers Insight into Biogeochemical Sources and Diagenetic State

Abstract

Investigating the biogeochemistry of dissolved organic matter (DOM) requires the synthesis of data from several complementary analytical techniques. The traditional approach to data synthesis is to search for correlations between measurements made on the same sample using different instruments. In contrast, data fusion simultaneously decomposes data from multiple instruments into the underlying shared and unshared components. Here, Advanced Coupled Matrix and Tensor Factorization (ACMTF) was used to identify the molecular fingerprint of DOM fluorescence fractions in Arctic fjords. ACMTF explained 99.84% of the variability with six fully shared components. Individual molecular formulas were linked to multiple fluorescence components and vice versa. Molecular fingerprints differed in diversity and oceanographic patterns, suggesting a link to the biogeochemical sources and diagenetic state of DOM. The fingerprints obtained through ACMTF were more specific compared to traditional correlation analysis and yielded greater compositional insight. Multivariate data fusion aligns extremely complex, heterogeneous DOM data sets and thus facilitates a more holistic understanding of DOM biogeochemistry.

Complexity of dissolved organic matter in the molecular size dimension: insights from coupled size exclusion chromatography electrospray ionisation mass spectrometry

“…The size range difference between optically active and ionisable DOM probably explains why solid phase extraction, which is poor at extracting high molecular weight components, 53,54 has a minimal effect on ESI-MS results, 54 but a large effect on absorption and uorescence spectroscopy. 55 Great care should therefore be taken in studies that aim to link the optical and MS character of terrestrial DOM [56][57][58][59][60] or the concentration of DOC and MS signal, 61 as the results being compared are not necessarily representing the same pools of carbon, 47,48,62 and relationships are likely to be coincidental, albeit related. This larger molecular weight pool, which we refer to as phenolic compounds (Fig.…”

“…The analytical window and inherent biases of any chosen method must be considered in any study of complex mixtures, and the best tools moving forward will include various analytical windows in order to validate assumptions and to thoroughly explore correlations and dependencies within the data. 48,60 Pitfalls to be aware of include limited analytical windows in ionisation and detection methods, interactions between DOM and the stationary phase during chromatography and other separations/extractions, and molecules occurring as aggregates and other intermolecular effects, either naturally or during chromatography and analysis. Considering the diversity of DOM and the different rates at which different fractions of it react in natural waters, 75,76 a full coverage of the molecular diversity of DOM is needed in order to understand its biogeochemistry.…”

Mathematical chromatography deciphers the molecular fingerprints of dissolved organic matter

“…Moreover, PCA components are orthogonal and may thus have loadings that do not necessarily follow the natural structure of the underlying data. 53 Many HRMS studies of DOM have employed some type of data reduction method that involves calculating pairwise sample distances followed by multidimensional scaling into principle coordinates. These methods usually require peak intensities to be scaled to a normalised total value and also force trends into orthogonal components, which may not be realistic in environmental data.…”

“…62,63 Recent advances in multivariate data fusion provide the flexible mathematical framework necessary to jointly analyse the composition of DOM with different analytical tools. 53 However, further work is required to determine the extent to which DOM samples are ionised by techniques such as ESI, as well as the extent to which DOM absorbs and fluoresces light, in order to properly investigate the overlap and molecular nature of these pools.…”

High Anthropogenic Organic Matter Inputs during a Festival Increase River Heterotrophy and Refractory Carbon Load

“…Our results confirm that PARAFAC is a remarkably sensitive method to detect DOM sources not previously present in a system, 36 , 72 even if they are masked inside a complex matrix. 73 In turn, our findings also demonstrate new challenges for monitoring DOM in aquatic environments. Fluorescence indices 74 might lead to wrong conclusions as they were not developed nor tested to capture contributions of synthetic DOM ( Supplementary Text 6 ).…”