Studying Plant Specialized Metabolites Using Computational Metabolomics Strategies.

Plant specialized metabolites have diversified vastly over the course of plant evolution, and they are considered key players in complex interactions between plants and their environment. The chemical diversity of these metabolites has been widely explored and utilized in agriculture and crop enhancement, the food industry, and drug development, among other areas. However, the immensity of the plant metabolome can make its exploration challenging. Here we describe a protocol for exploring plant specialized metabolites that combines high-resolution mass spectrometry and computational metabolomics strategies, including molecular networking, identification of structural motifs, as well as prediction of chemical structures and metabolite classes.

The underappreciated diversity of bile acid modifications.

The repertoire of modifications to bile acids and related steroidal lipids by host and microbial metabolism remains incompletely characterized. To address this knowledge gap, we created a reusable resource of tandem mass spectrometry (MS/MS) spectra by filtering 1.2 billion publicly available MS/MS spectra for bile-acid-selective ion patterns. Thousands of modifications are distributed throughout animal and human bodies as well as microbial cultures. We employed this MS/MS library to identify polyamine bile amidates, prevalent in carnivores. They are present in humans, and their levels alter with a diet change from a Mediterranean to a typical American diet. This work highlights the existence of many more bile acid modifications than previously recognized and the value of leveraging public large-scale untargeted metabolomics data to discover metabolites. The availability of a modification-centric bile acid MS/MS library will inform future studies investigating bile acid roles in health and disease.

microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data.

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

Functional metabolomics of the human scalp: a metabolic niche for Staphylococcus epidermidis.

Although metabolomics data acquisition and analysis technologies have become increasingly sophisticated over the past 5-10 years, deciphering a metabolite's function from a description of its structure and its abundance in a given experimental setting is still a major scientific and intellectual challenge. To point out ways to address this "data to knowledge" challenge, we developed a functional metabolomics strategy that combines state-of-the-art data analysis tools and applied it to a human scalp metabolomics data set: skin swabs from healthy volunteers with normal or oily scalp (Sebumeter score 60-120, n = 33; Sebumeter score > 120, n = 41) were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), yielding four metabolomics data sets for reversed phase chromatography (C18) or hydrophilic interaction chromatography (HILIC) separation in electrospray ionization (ESI) + or - ionization mode. Following our data analysis strategy, we were able to obtain increasingly comprehensive structural and functional annotations, by applying the Global Natural Product Social Networking (M. Wang, J. J. Carver, V. V. Phelan, L. M. Sanchez, et al., Nat Biotechnol 34:828-837, 2016, https://doi.org/10.1038/nbt.3597), SIRIUS (K. Dührkop, M. Fleischauer, M. Ludwig, A. A. Aksenov, et al., Nat Methods 16:299-302, 2019, https://doi.org/10.1038/s41592-019-0344-8), and MicrobeMASST (S. ZuffaS, R. Schmid, A. Bauermeister, P. W, P. Gomes, et al., bioRxiv:rs.3.rs-3189768, 2023, https://doi.org/10.21203/rs.3.rs-3189768/v1) tools. We finally combined the metabolomics data with a corresponding metagenomic sequencing data set using MMvec (J. T. Morton, A. A. Aksenov, L. F. Nothias, J. R. Foulds, et. al., Nat Methods 16:1306-1314, 2019, https://doi.org/10.1038/s41592-019-0616-3), gaining insights into the metabolic niche of one of the most prominent microbes on the human skin, Staphylococcus epidermidis.IMPORTANCESystems biology research on host-associated microbiota focuses on two fundamental questions: which microbes are present and how do they interact with each other, their host, and the broader host environment? Metagenomics provides us with a direct answer to the first part of the question: it unveils the microbial inhabitants, e.g., on our skin, and can provide insight into their functional potential. Yet, it falls short in revealing their active role. Metabolomics shows us the chemical composition of the environment in which microbes thrive and the transformation products they produce. In particular, untargeted metabolomics has the potential to observe a diverse set of metabolites and is thus an ideal complement to metagenomics. However, this potential often remains underexplored due to the low annotation rates in MS-based metabolomics and the necessity for multiple experimental chromatographic and mass spectrometric conditions. Beyond detection, prospecting metabolites' functional role in the host/microbiome metabolome requires identifying the biological processes and entities involved in their production and biotransformations. In the present study of the human scalp, we developed a strategy to achieve comprehensive structural and functional annotation of the metabolites in the human scalp environment, thus diving one step deeper into the interpretation of "omics" data. Leveraging a collection of openly accessible software tools and integrating microbiome data as a source of functional metabolite annotations, we finally identified the specific metabolic niche of Staphylococcus epidermidis, one of the key players of the human skin microbiome.

Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics.

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or "suspects," were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer's brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

On-tissue dataset-dependent MALDI-TIMS-MS2 bioimaging.

Trapped ion mobility spectrometry (TIMS) adds an additional separation dimension to mass spectrometry (MS) imaging, however, the lack of fragmentation spectra (MS2) impedes confident compound annotation in spatial metabolomics. Here, we describe spatial ion mobility-scheduled exhaustive fragmentation (SIMSEF), a dataset-dependent acquisition strategy that augments TIMS-MS imaging datasets with MS2 spectra. The fragmentation experiments are systematically distributed across the sample and scheduled for multiple collision energies per precursor ion. Extendable data processing and evaluation workflows are implemented into the open source software MZmine. The workflow and annotation capabilities are demonstrated on rat brain tissue thin sections, measured by matrix-assisted laser desorption/ionisation (MALDI)-TIMS-MS, where SIMSEF enables on-tissue compound annotation through spectral library matching and rule-based lipid annotation within MZmine and maps the (un)known chemical space by molecular networking. The SIMSEF algorithm and data analysis pipelines are open source and modular to provide a community resource.

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data.

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms' role in ecology and human health.

Evaluation of Data-Dependent MS/MS Acquisition Parameters for Non-Targeted Metabolomics and Molecular Networking of Environmental Samples: Focus on the Q Exactive Platform.

Non-targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely used tool for metabolomics analysis, enabling the detection and annotation of small molecules in complex environmental samples. Data-dependent acquisition (DDA) of product ion spectra is thereby currently one of the most frequently applied data acquisition strategies. The optimization of DDA parameters is central to ensuring high spectral quality, coverage, and number of compound annotations. Here, we evaluated the influence of 10 central DDA settings of the Q Exactive mass spectrometer on natural organic matter samples from ocean, river, and soil environments. After data analysis with classical and feature-based molecular networking using MZmine and GNPS, we compared the total number of network nodes, multivariate clustering, and spectrum quality-related metrics such as annotation and singleton rates, MS/MS placement, and coverage. Our results show that automatic gain control, microscans, mass resolving power, and dynamic exclusion are the most critical parameters, whereas collision energy, TopN, and isolation width had moderate and apex trigger, monoisotopic selection, and isotopic exclusion minor effects. The insights into the data acquisition ergonomics of the Q Exactive platform presented here can guide new users and provide them with initial method parameters, some of which may also be transferable to other sample types and MS platforms.

Comparison of Cosine, Modified Cosine, and Neutral Loss Based Spectrum Alignment For Discovery of Structurally Related Molecules.

Spectrum alignment of tandem mass spectrometry (MS/MS) data using the modified cosine similarity and subsequent visualization as molecular networks have been demonstrated to be a useful strategy to discover analogs of molecules from untargeted MS/MS-based metabolomics experiments. Recently, a neutral loss matching approach has been introduced as an alternative to MS/MS-based molecular networking with an implied performance advantage in finding analogs that cannot be discovered using existing MS/MS spectrum alignment strategies. To comprehensively evaluate the scoring properties of neutral loss matching, the cosine similarity, and the modified cosine similarity, similarity measures of 955 228 peptide MS/MS spectrum pairs and 10 million small molecule MS/MS spectrum pairs were compared. This comparative analysis revealed that the modified cosine similarity outperformed neutral loss matching and the cosine similarity in all cases. The data further indicated that the performance of MS/MS spectrum alignment depends on the location and type of the modification, as well as the chemical compound class of fragmented molecules.

Field Validation of a Non-carcinogenic and Eco-Friendly Disinfectant in a Stand-In Footbath for Treatment of Footrot Associated With aprV2-Positive Strains of Dichelobacter nodosus in Swiss Sheep Flocks.

A national control program for virulent footrot is currently planned in Switzerland. Since commonly used disinfectants either contain heavy metals or are carcinogenic, the aim of this study was to verify the effectiveness of an eco-friendly and non-carcinogenic candidate disinfectant against aprV2-positive strains of Dichelobacter nodosus. Additionally, the effect of the selective use of long-acting oxytetracyclines was evaluated. A total of 18 farms with confirmed footrot infection, randomly allocated to two treatment groups: (1) with antibiotics (AB; n = 9) and, (2) no antibiotics (NAB; n = 9), were included. Claws were carefully trimmed and scored using a scale from 0 (clinically healthy) to 5 (complete loss of the horn capsule) and a prewash waterbath was implemented on 11 farms. Twice-weekly, repeated whole-flock stand-in footbaths with the candidate disinfectant (6%) were performed. Additionally, animals of group AB with a score ≥ 3 were administered oxytetracyclines by injection. On all farms, 10 days after last treatment, aprV2-positive strains could not be detected by risk-based sampling for real-time PCR analysis after 7-21 (median = 12) footbaths with a minimal culling rate of non-responders on nine farms. Farms without contact to other sheep remained without clinical signs of footrot for a minimum of 245 days (mean ± standard deviation: 293.6 ± 23.6). Antibiotic treatment did not reduce the number of footbaths needed. In contrast, a mean of 3.3 disinfecting footbaths could be saved by implementing a prewash waterbath. At animal level, individual and selective use of oxytetracyclines lead to a higher chance (odds ratio = 9.95; 95% CI: 3.54-27.95; p < 0.001) for a lesion score ≥ 3 to improve to a lesion score < 3 within 2 weeks compared to treatment without antibiotics. The test disinfectant is an effective and eco-friendly alternative for the planned Swiss footrot control program and selective use of oxytetracycline has a beneficial impact on the recovery of animals with lesion scores ≥ 3.

foodMASST a mass spectrometry search tool for foods and beverages.

There is a growing interest in unraveling the chemical complexity of our diets. To help the scientific community gain insight into the molecules present in foods and beverages that we ingest, we created foodMASST, a search tool for MS/MS spectra (of both known and unknown molecules) against a growing metabolomics food and beverage reference database. We envision foodMASST will become valuable for nutrition research and to assess the potential uniqueness of dietary biomarkers to represent specific foods or food classes.

Tattoo Pigment Identification in Inks and Skin Biopsies of Adverse Reactions by Complementary Elemental and Molecular Bioimaging with Mass Spectral Library Matching.

Tattooing has become increasingly popular throughout society. Despite the recognized issue of adverse reactions in tattoos, regulations remain challenging with limited data available and a missing positive list. The diverse chemical properties of mostly insoluble inorganic and organic pigments pose an outstanding analytical challenge, which typically requires extensive sample preparation. Here, we present a multimodal bioimaging approach combining micro X-ray fluorescence (µXRF) and laser desorption ionization-mass spectrometry (LDI-MS) to detect the elemental and molecular composition in the same sample. The pigment structures directly absorb the laser energy, eliminating the need for matrix application. A computational data processing workflow clusters spatially resolved LDI-MS scans to merge redundant information into consensus spectra, which are then matched against new open mass spectral libraries of tattoo pigments. When applied to 13 tattoo inks and 68 skin samples from skin biopsies in adverse tattoo reactions, characteristic signal patterns of isotopes, ion adducts, and in-source fragments in LDI-MS1 scans yielded confident compound annotations across various pigment classes. Combined with µXRF, pigment annotations were achieved for all skin samples with 14 unique structures and 2 inorganic pigments, emphasizing the applicability to larger studies. The tattoo-specific spectral libraries and further information are available on the tattoo-analysis.github.io website.

Native mass spectrometry-based metabolomics identifies metal-binding compounds.

Although metals are essential for the molecular machineries of life, systematic methods for discovering metal-small molecule complexes from biological samples are limited. Here, we describe a two-step native electrospray ionization-mass spectrometry method, in which post-column pH adjustment and metal infusion are combined with ion identity molecular networking, a rule-based data analysis workflow. This method enabled the identification of metal-binding compounds in complex samples based on defined mass (m/z) offsets of ion species with the same chromatographic profiles. As this native electrospray metabolomics approach is suited to the use of any liquid chromatography-mass spectrometry system to explore the binding of any metal, this method has the potential to become an essential strategy for elucidating metal-binding molecules in biology.

First description of interdigital hyperplasia associated with contagious ovine digital dermatitis in two sheep.

Interdigital hyperplasia (IH) is a fold of fibrous tissue protruding into the interdigital space that rarely occurs in sheep. Interdigital hyperplasia secondary infected with bovine digital dermatitis (BDD) treponemes has been reported in cattle in the course of the increasing spread of classical BDD lesions. In this report, we describe proliferative/ulcerative interdigital lesions associated with contagious ovine digital dermatitis (CODD) treponemes and clinically scored as (IH+CODD), occurring in both hind limbs of a ram and the left hindlimb of a ewe. Both cases exhibited epidermal hyperplasia, parakeratosis and focal-extensive areas of epidermal necrosis with numerous infiltrating neutrophils. Treponema PCR and fluorescence in situ hybridization (FISH) were positive for Treponema phylotype 1 (PT1). In addition, Dichelobacter (D.) nodosus and Porphyromonas (P.) levii were detected in the biopsy by PCR. In three slaughter sheep, without claw lesions, which were kept together with both affected sheep, Treponema spp. were detected neither with PCR nor FISH; the PCRs for D. nodosus and P. levii were also negative. Complete clinical healing occurred in the ewe within 6 weeks after three local applications of a chlortetracycline spray in 2 weeks intervals. This report is the first description of IH+CODD in sheep as demonstrated by a combination of histopathological and molecular analyses.

Feature-based molecular networking for identification of organic micropollutants including metabolites by non-target analysis applied to riverbank filtration.

Due to growing concern about organic micropollutants and their transformation products (TP) in surface and drinking water, reliable identification of unknowns is required. Here, we demonstrate how non-target liquid chromatography (LC)-high-resolution tandem mass spectrometry (MS/MS) and the feature-based molecular networking (FBMN) workflow provide insight into water samples from four riverbank filtration sites with different redox conditions. First, FBMN prioritized and connected drinking water relevant and seasonally dependent compounds based on a modification-aware MS/MS cosine similarity. Within the resulting molecular networks, forty-three compounds were annotated. Here, carbamazepine, sartans, and their respective TP were investigated exemplarily. With chromatographic information and spectral similarity, four additional TP (dealkylated valsartan, dealkylated irbesartan, two oxygenated irbesartan isomers) and olmesartan were identified and partly verified with an authentic standard. In this study, sartans and TP were investigated and grouped regarding their removal behavior under different redox conditions and seasons for the first time. Antihypertensives were grouped into compounds being well removed during riverbank filtration, those primarily removed under anoxic conditions, and rather persistent compounds. Observed seasonal variations were mainly limited to varying river water concentrations. FBMN is a powerful tool for identifying previously unknown or unexpected compounds and their TP in water samples by non-target analysis.

Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment.

Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.

Spatially and size-resolved analysis of gold nanoparticles in rat spleen after intratracheal instillation by laser ablation-inductively coupled plasma-mass spectrometry.

In a dual approach, laser ablation-inductively coupled plasma-mass spectrometry was applied to investigate spleen samples of rats after intratracheal instillation of polyvinylpyrrolidone-coated gold nanoparticles. First, spatially resolved imaging analysis was deployed to investigate gold translocation from the lungs to the spleen and to investigate the distribution pattern of gold in the spleen parenchyma itself. Using the same instrumental setup, laser ablation-inductively coupled plasma-mass spectrometry in single particle mode was applied to determine the species of translocated gold. Single particle analysis allows the determination of particle size distributions and therefore to distinguish between ionic species, intact nanoparticles, and agglomerates. A translocation of instilled gold from the lungs to the spleen was demonstrated for gold nanoparticles of 30 and 50 nm diameter. Furthermore single particle analysis revealed the translocation of intact gold nanoparticles in a non-agglomerated state.

Feature-based molecular networking in the GNPS analysis environment.

Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.