Tailored Mass Spectral Data Exploration Using the SpecXplore Interactive Dashboard.

Untargeted metabolomics promises comprehensive characterization of small molecules in biological samples. However, the field is hampered by low annotation rates and abstract spectral data. Despite recent advances in computational metabolomics, manual annotations and manual confirmation of in-silico annotations remain important in the field. Here, exploratory data analysis methods for mass spectral data provide overviews, prioritization, and structural hypothesis starting points to researchers facing large quantities of spectral data. In this research, we propose a fluid means of dealing with mass spectral data using specXplore, an interactive Python dashboard providing interactive and complementary visualizations facilitating mass spectral similarity matrix exploration. Specifically, specXplore provides a two-dimensional t-distributed stochastic neighbor embedding embedding as a jumping board for local connectivity exploration using complementary interactive visualizations in the form of partial network drawings, similarity heatmaps, and fragmentation overview maps. SpecXplore makes use of state-of-the-art ms2deepscore pairwise spectral similarities as a quantitative backbone while allowing fast changes of threshold and connectivity limitation settings, providing flexibility in adjusting settings to suit the localized node environment being explored. We believe that specXplore can become an integral part of mass spectral data exploration efforts and assist users in the generation of structural hypotheses for compounds of interest.

Neuroactive metabolites and bile acids are altered in extremely premature infants with brain injury.

The gut microbiome is associated with pathological neurophysiological evolvement in extremely premature infants suffering from brain injury. The exact underlying mechanism and its associated metabolic signatures in infants are not fully understood. To decipher metabolite profiles linked to neonatal brain injury, we investigate the fecal and plasma metabolome of samples obtained from a cohort of 51 extremely premature infants at several time points, using liquid chromatography (LC)-high-resolution mass spectrometry (MS)-based untargeted metabolomics and LC-MS/MS-based targeted analysis for investigating bile acids and amidated bile acid conjugates. The data are integrated with 16S rRNA gene amplicon gut microbiome profiles as well as patient cytokine, growth factor, and T cell profiles. We find an early onset of differentiation in neuroactive metabolites between infants with and without brain injury. We detect several bacterially derived bile acid amino acid conjugates in plasma and feces. These results provide insights into the early-life metabolome of extremely premature infants.

Ecophysiology and interactions of a taurine-respiring bacterium in the mouse gut.

Taurine-respiring gut bacteria produce H2S with ambivalent impact on host health. We report the isolation and ecophysiological characterization of a taurine-respiring mouse gut bacterium. Taurinivorans muris strain LT0009 represents a new widespread species that differs from the human gut sulfidogen Bilophila wadsworthia in its sulfur metabolism pathways and host distribution. T. muris specializes in taurine respiration in vivo, seemingly unaffected by mouse diet and genotype, but is dependent on other bacteria for release of taurine from bile acids. Colonization of T. muris in gnotobiotic mice increased deconjugation of taurine-conjugated bile acids and transcriptional activity of a sulfur metabolism gene-encoding prophage in other commensals, and slightly decreased the abundance of Salmonella enterica, which showed reduced expression of galactonate catabolism genes. Re-analysis of metagenome data from a previous study further suggested that T. muris can contribute to protection against pathogens by the commensal mouse gut microbiota. Together, we show the realized physiological niche of a key murine gut sulfidogen and its interactions with selected gut microbiota members.

Exposomic Biomonitoring of Polyphenols by Non-Targeted Analysis and Suspect Screening.

Polyphenols, prevalent in plants and fungi, are investigated intensively in nutritional and clinical settings because of their beneficial bioactive properties. Due to their complexity, analysis with untargeted approaches is favorable, which typically use high-resolution mass spectrometry (HRMS) rather than low-resolution mass spectrometry (LRMS). Here, the advantages of HRMS were evaluated by thoroughly testing untargeted techniques and available online resources. By applying data-dependent acquisition on real-life urine samples, 27 features were annotated with spectral libraries, 88 with in silico fragmentation, and 113 by MS1 matching with PhytoHub, an online database containing >2000 polyphenols. Moreover, other exogenous and endogenous molecules were screened to measure chemical exposure and potential metabolic effects using the Exposome-Explorer database, further annotating 144 features. Additional polyphenol-related features were explored using various non-targeted analysis techniques including MassQL for glucuronide and sulfate neutral losses, and MetaboAnalyst for statistical analysis. As HRMS typically suffers a sensitivity loss compared to state-of-the-art LRMS used in targeted workflows, the gap between the two instrumental approaches was quantified in three spiked human matrices (urine, serum, plasma) as well as real-life urine samples. Both instruments showed feasible sensitivity, with median limits of detection in the spiked samples being 10-18 ng/mL for HRMS and 4.8-5.8 ng/mL for LRMS. The results demonstrate that, despite its intrinsic limitations, HRMS can readily be used for comprehensively investigating human polyphenol exposure. In the future, this work is expected to allow for linking human health effects with exposure patterns and toxicological mixture effects with other xenobiotics.

Nontargeted Analysis Study Reporting Tool: A Framework to Improve Research Transparency and Reproducibility.

Non-targeted analysis (NTA) workflows using mass spectrometry are gaining popularity in many disciplines, but universally accepted reporting standards are nonexistent. Current guidance addresses limited elements of NTA reporting-most notably, identification confidence-and is insufficient to ensure scientific transparency and reproducibility given the complexity of these methods. This lack of reporting standards hinders researchers' development of thorough study protocols and reviewers' ability to efficiently assess grant and manuscript submissions. To overcome these challenges, we developed the NTA Study Reporting Tool (SRT), an easy-to-use, interdisciplinary framework for comprehensive NTA methods and results reporting. Eleven NTA practitioners reviewed eight published articles covering environmental, food, and health-based exposomic applications with the SRT. Overall, our analysis demonstrated that the SRT provides a valid structure to guide study design and manuscript writing, as well as to evaluate NTA reporting quality. Scores self-assigned by authors fell within the range of peer-reviewer scores, indicating that SRT use for self-evaluation will strengthen reporting practices. The results also highlighted NTA reporting areas that need immediate improvement, such as analytical sequence and quality assurance/quality control information. Although scores intentionally do not correspond to data/results quality, widespread implementation of the SRT could improve study design and standardize reporting practices, ultimately leading to broader use and acceptance of NTA data.

Drug-Exposome Interactions: The Next Frontier in Precision Medicine.

Drug-drug interactions are a known concern during medical treatment. However, in addition to therapeutic drugs, humans are exposed to thousands of environment- and food-related chemicals on a daily basis. The exposome (i.e.,the total measure of environmental factors on the human body) is an emerging concept in the field of environmental health. Many chemicals have the potential to interact with drugs and subsequently influence health outcomes. To date, this concept has not been systematicallyinvestigated. Nevertheless, adverse effects have been observed betweenenvironmental, dietary, and microbiome-derived xenobiotics and a number of drugs, including chemotherapeutics. Recent technological advances in mass spectrometry-based metabolomics and the establishment of omic-scale exposure assessment will enable a broader and systemic investigation of these interactions. As a complement to pharmacogenomics and pharmacometabolomics, research ondrug-exposome interactions holds immense potential to elevate precision medicineto an unprecedented level.