A community resource for paired genomic and metabolomic data mining

Genomics and metabolomics are widely used to explore specialized metabolite diversity. The Paired Omics Data Platform is a community initiative to systematically document links between metabolome and (meta)genome data, aiding identification of natural product biosynthetic origins and metabolite structures.Peer reviewe

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. The 'omics' approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n = 20) and confirmed viral infection (n = 20). We show for the first time that bacterial and viral infection produces distinct profile in the host lipidome. Some species of glycerophosphoinositol, sphingomyelin, lysophosphatidylcholine and cholesterol sulfate were higher in the confirmed virus infected group, while some species of fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were lower in the confirmed virus infected group when compared with confirmed bacterial infected group. A combination of three lipids achieved an area under the receiver operating characteristic (ROC) curve of 0.911 (95% CI 0.81 to 0.98). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics

Short-term dynamics of dissolved organic matter and bacterial communities in the open North Sea off Helgoland Island

Dissolved organic matter (DOM) in the ocean is one of the largest active carbon pools on earth, similar in size to atmospheric CO2 or all land plant biomass. Due to its richness in energy and nutrients it is fundamental for microbial life and for marine food webs. The microbial loop is an essential compartment in the global carbon cycle and is important for the transformation and recycling of organic matter and nutrients in the oceans. Microbial communities shape the molecular composition of DOM and vice versa. Earlier long-term studies have shown that seasonal dynamics in DOM composition and microbial communities exists. The aim of this study was to explore and characterize variations in composition of bacterial communities and DOM over short periods of time, ranging from hours to days. We hypothesize that variations in DOM composition are directly related to variations in the bacterial community and/ or environmental conditions. To test these hypotheses, water samples were taken daily over a time period of 20 days and hourly (over 24 hours) in the open North Sea off Helgoland Island. Sea water was analyzed for environmental variables, molecular DOM composition and the bacterial community structure. DOM was isolated from seawater by solid phase extraction and analyzed via ultrahigh resolution mass spectrometry (FT-ICR-MS, Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry). To investigate bacterial community structure, Automated Ribosomal Intergenic Spacer Analysis (ARISA) fingerprinting was used. The current study did not reveal a direct relation between a bacterial community structure changes and variation in the composition of DOM, neither within daily sampling nor the 24 h time series. However both, bacterial community and DOM composition undergo a characteristic shift during the daily sampling, mainly driven by salinity. The 24 h sampling during this time captured much of the variation in salinity and the microbial community, accordingly. High variations of salinity during the sampling period indicate the presence of changes in different water masses that carry distinct molecular and microbial signatures. For the first time, these changes have been documented in such high temporal and analytical resolution

Exploring Dissolved Organic Matter Dynamics in Vulnerable Marine Environments using Untargeted Metabolomics

Dissolved organic matter (DOM) sustains microbial activity and structures ecological interactions. The composition of DOM, in terms of quality and quantity, shapes microbial communities, subsequently affecting global biogeochemical cycles. Beyond contributing nutrient, organic molecules can also function as communication signals and, in certain scenarios, engage in chemical warfare. Therefore, a molecular-level study of DOM is necessary for a more thorough understanding of its role in aquatic environments. However, DOM exists as a very complex mixture in seawater, and its individual components' concentrations are extremely small relative to salts. This complicates the analysis of DOM and as a result, the true chemical diversity within DOM has remained elusive. To address this, innovative analytical and data processing techniques are essential. Chapter 2 introduces the analytical framework developed in this thesis. By employing untargeted metabolomics—specifically, liquid chromatography paired with high-resolution tandem mass spectrometry—and utilizing cutting-edge cheminformatic tools, I was able to illuminate the chemical dark matter of DOM. Using molecular networking and in silico annotation tools, I assigned molecular formulas and predicted structures and compound class affiliations for thousands of chemical features, representing most detectable compounds. I then used this established methodological workflow to explore the role of DOM in ecosystems vulnerable to global change, such as harmful algal blooms, coral reefs, and oxygen-deficient zones. Toxin-producing marine microalgae, Pseudo-nitzschia sp. thrive in upwelling coastal ecosystems, and their harmful blooms are increasing in frequency and intensity in the face of ecosystem changes due to global warming and eutrophication. In Chapter 3, I showed that these algae have species-specific microbiomes that appear to be interacting with unique metabolites, particularly compounds containing diverse nitrogen functional groups. This research provides an in-depth cataloging of chemical classes in algal culture, enhancing our understanding of microbial interactions. Oxygen-deficient zones (ODZs) occur naturally in coastal upwelling regions, but studies suggest they may expand due to climate change. In Chapter 4, I examined DOM in the ODZ of the Eastern Tropical North Pacific. I used specific compounds to trace organic matter inputs to the ODZ and highlighted potential reasons for DOM accumulation in these low-oxygen waters. The results suggest selective preservation of DOM, which could lead to carbon sequestration, altering the local carbon cycle. Coral reefs are among the world's most impacted ecosystems, threatened by global warming, ocean acidification, and pollution. In Chapter 5, I investigated the dynamics of DOM, which is critical to coral reefs' health, productivity, and function. Using a Lagrangian sampling approach and following the biogeochemical changes in water flowing over a rapidly flushed reef in Mo'orea, French Polynesia, I was able to provide new insights into nutrient recycling, metabolite production by benthic primary producers, and DOM removal processes over the reef. Together, the chapters of this dissertation establish a robust methodological foundation for molecular-level DOM analysis. By applying this approach to specific environments, I demonstrated the profound impact of DOM on ecosystems vulnerable to global change, underscoring its broader implications for marine biogeochemistry in a changing world

A thicker Antarctic ice stream during the mid-Pliocene warm period

This work is supported by Stockholm University (APS), Norwegian Polar Institute/NARE under Grant “MAGIC-DML” (OF), the US National Science Foundation under Grant No. OPP-1542930 (NAL and JMH), Swedish Research Council under Grant No. 2016-04422 (JMH and APS), and the German Research Foundation Priority Programme 1158 “Antarctic Research” under Grant No. 365737614 (IR and Matthias Prange). R.S.J. is supported by the Australian Research Council under grants DE210101923 and SR200100005 (Securing Antarctica’s Environmental Future). The computations and data handling were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC), partially funded by the Swedish Research Council through grant agreement No. 2018-05973.Ice streams regulate most ice mass loss in Antarctica. Determining ice stream response to warmer conditions during the Pliocene could provide insights into their future behaviour, but this is hindered by a poor representation of subglacial topography in ice-sheet models. We address this limitation using a high-resolution model for Dronning Maud Land (East Antarctica). We show that contrary to dynamic thinning of the region’s ice streams following ice-shelf collapse, the largest ice stream, Jutulstraumen, thickens by 700 m despite lying on a retrograde bed slope. We attribute this counterintuitive thickening to a shallower Pliocene subglacial topography and inherent high lateral stresses at its flux gate. These conditions constrict ice drainage and, combined with increased snowfall, allow ice accumulation upstream. Similar stress balances and increased precipitation projections occur across 27% of present-day East Antarctica, and understanding how lateral stresses regulate ice-stream discharge is necessary for accurately assessing Antarctica’s future sea-level rise contribution.Publisher PDFPeer reviewe

ConCISE: Consensus Annotation Propagation of Ion Features in Untargeted Tandem Mass Spectrometry Combining Molecular Networking and In Silico Metabolite Structure Prediction

Recent developments in molecular networking have expanded our ability to characterize the metabolome of diverse samples that contain a significant proportion of ion features with no mass spectral match to known compounds. Manual and tool-assisted natural annotation propagation is readily used to classify molecular networks; however, currently no annotation propagation tools leverage consensus confidence strategies enabled by hierarchical chemical ontologies or enable the use of new in silico tools without significant modification. Herein we present ConCISE (Consensus Classifications of In Silico Elucidations) which is the first tool to fuse molecular networking, spectral library matching and in silico class predictions to establish accurate putative classifications for entire subnetworks. By limiting annotation propagation to only structural classes which are identical for the majority of ion features within a subnetwork, ConCISE maintains a true positive rate greater than 95% across all levels of the ChemOnt hierarchical ontology used by the ClassyFire annotation software (superclass, class, subclass). The ConCISE framework expanded the proportion of reliable and consistent ion feature annotation up to 76%, allowing for improved assessment of the chemo-diversity of dissolved organic matter pools from three complex marine metabolomics datasets comprising dominant reef primary producers, five species of the diatom genus Pseudo-nitzchia, and stromatolite sediment samples

Two-Dimensional Liquid Chromatography Tandem-Mass Spectrometry Untangles the Deep Metabolome of Marine Dissolved Organic Matter

Dissolved organic matter (DOM) is one of the most complex chemical mixtures and plays a central role in biogeochemical cycles across our ecosphere. Despite its importance, DOM remains poorly understood at the molecular level. Over the last decades, significant efforts have been made to decipher the chemical composition of DOM by high-resolution mass spectrometry (HRMS) and liquid chromatography (LC) coupled with tandem mass spectrometry (MS/MS). Yet, the complexity and high degree of non-resolved isomers still hamper the full structural analysis of DOM. To overcome this challenge, we adapted a two-dimensional (2D) LC approach consisting of two reversed-phase dimensions with orthogonal pH, followed by MS/MS data acquisition and molecular networking. The 2D chromatography approach mitigates the complexity of DOM, enhancing both the quality of MS/MS spectra and spectral annotation rates. Applying our approach to analyze coastal surface DOM from Southern California (USA), we annotated in total more than 600 structures via MS/MS spectrum matching, which was up to 90% more than in iterative 1D LC-MS/MS analysis with the same total run time. Our data provide an unprecedented view into the molecular composition of coastal DOM, highlighting the potential of 2D LC-MS/MS approaches to decipher ultra-complex mixtures