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.

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.

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.

Effects of a ketogenic and low-fat diet on the human metabolome, microbiome, and foodome in adults at risk for Alzheimer's disease.

INTRODUCTION: The ketogenic diet (KD) is an intriguing therapeutic candidate for Alzheimer's disease (AD) given its protective effects against metabolic dysregulation and seizures. Gut microbiota are essential for KD-mediated neuroprotection against seizures as well as modulation of bile acids, which play a major role in cholesterol metabolism. These relationships motivated our analysis of gut microbiota and metabolites related to cognitive status following a controlled KD intervention compared with a low-fat-diet intervention. METHODS: Prediabetic adults, either with mild cognitive impairment (MCI) or cognitively normal (CN), were placed on either a low-fat American Heart Association diet or high-fat modified Mediterranean KD (MMKD) for 6 weeks; then, after a 6-week washout period, they crossed over to the alternate diet. We collected stool samples for shotgun metagenomics and untargeted metabolomics at five time points to investigate individuals' microbiome and metabolome throughout the dietary interventions. RESULTS: Participants with MCI on the MMKD had lower levels of GABA-producing microbes Alistipes sp. CAG:514 and GABA, and higher levels of GABA-regulating microbes Akkermansia muciniphila. MCI individuals with curcumin in their diet had lower levels of bile salt hydrolase-containing microbes and an altered bile acid pool, suggesting reduced gut motility. DISCUSSION: Our results suggest that the MMKD may benefit adults with MCI through modulation of GABA levels and gut-transit time.

Enhancing untargeted metabolomics using metadata-based source annotation.

Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.

ReDU: a framework to find and reanalyze public mass spectrometry data.

We present ReDU ( https://redu.ucsd.edu/ ), a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one's own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking.

Global chemical effects of the microbiome include new bile-acid conjugations.

A mosaic of cross-phylum chemical interactions occurs between all metazoans and their microbiomes. A number of molecular families that are known to be produced by the microbiome have a marked effect on the balance between health and disease1-9. Considering the diversity of the human microbiome (which numbers over 40,000 operational taxonomic units10), the effect of the microbiome on the chemistry of an entire animal remains underexplored. Here we use mass spectrometry informatics and data visualization approaches11-13 to provide an assessment of the effects of the microbiome on the chemistry of an entire mammal by comparing metabolomics data from germ-free and specific-pathogen-free mice. We found that the microbiota affects the chemistry of all organs. This included the amino acid conjugations of host bile acids that were used to produce phenylalanocholic acid, tyrosocholic acid and leucocholic acid, which have not previously been characterized despite extensive research on bile-acid chemistry14. These bile-acid conjugates were also found in humans, and were enriched in patients with inflammatory bowel disease or cystic fibrosis. These compounds agonized the farnesoid X receptor in vitro, and mice gavaged with the compounds showed reduced expression of bile-acid synthesis genes in vivo. Further studies are required to confirm whether these compounds have a physiological role in the host, and whether they contribute to gut diseases that are associated with microbiome dysbiosis.

Intermittent Hypoxia and Hypercapnia Reproducibly Change the Gut Microbiome and Metabolome across Rodent Model Systems.

Studying perturbations in the gut ecosystem using animal models of disease continues to provide valuable insights into the role of the microbiome in various pathological conditions. However, understanding whether these changes are consistent across animal models of different genetic backgrounds, and hence potentially translatable to human populations, remains a major unmet challenge in the field. Nonetheless, in relatively limited cases have the same interventions been studied in two animal models in the same laboratory. Moreover, such studies typically examine a single data layer and time point. Here, we show the power of utilizing time series microbiome (16S rRNA amplicon profiling) and metabolome (untargeted liquid chromatography-tandem mass spectrometry [LC-MS/MS]) data to relate two different mouse models of atherosclerosis-ApoE-/- (n = 24) and Ldlr-/- (n = 16)-that are exposed to intermittent hypoxia and hypercapnia (IHH) longitudinally (for 10 and 6 weeks, respectively) to model chronic obstructive sleep apnea. Using random forest classifiers trained on each data layer, we show excellent accuracy in predicting IHH exposure within ApoE-/- and Ldlr-/- knockout models and in cross-applying predictive features found in one animal model to the other. The key microbes and metabolites that reproducibly predicted IHH exposure included bacterial species from the families Mogibacteriaceae, Clostridiaceae, bile acids, and fatty acids, providing a refined set of biomarkers associated with IHH. The results highlight that time series multiomics data can be used to relate different animal models of disease using supervised machine learning techniques and can provide a pathway toward identifying robust microbiome and metabolome features that underpin translation from animal models to human disease. IMPORTANCE Reproducibility of microbiome research is a major topic of contemporary interest. Although it is often possible to distinguish individuals with specific diseases within a study, the differences are often inconsistent across cohorts, often due to systematic variation in analytical conditions. Here we study the same intervention in two different mouse models of cardiovascular disease (atherosclerosis) by profiling the microbiome and metabolome in stool specimens over time. We demonstrate that shared microbial and metabolic changes are involved in both models with the intervention. We then introduce a pipeline for finding similar results in other studies. This work will help find common features identified across different model systems that are most likely to apply in humans.

Intermittent Hypoxia and Hypercapnia, a Hallmark of Obstructive Sleep Apnea, Alters the Gut Microbiome and Metabolome.

Obstructive sleep apnea (OSA) is a common disorder characterized by episodic obstruction to breathing due to upper airway collapse during sleep. Because of the episodic airway obstruction, intermittently low O2 (hypoxia) and high CO2 (hypercapnia) ensue. OSA has been associated with adverse cardiovascular and metabolic outcomes, although data regarding potential causal pathways are still evolving. As changes in inspired O2 and CO2 can affect the ecology of the gut microbiota and the microbiota has been shown to contribute to various cardiometabolic disorders, we hypothesized that OSA alters the gut ecosystem, which, in turn, exacerbates the downstream physiological consequences. Here, we model human OSA and its cardiovascular consequence using Ldlr-/- mice fed a high-fat diet and exposed to intermittent hypoxia and hypercapnia (IHH). The gut microbiome and metabolome were characterized longitudinally (using 16S rRNA amplicon sequencing and untargeted liquid chromatography-tandem mass spectrometry [LC-MS/MS]) and seen to covary during IHH. Joint analysis of microbiome and metabolome data revealed marked compositional changes in both microbial (>10%, most remarkably in Clostridia) and molecular (>22%) species in the gut. Moreover, molecules that altered in abundance included microbe-dependent bile acids, enterolignans, and fatty acids, highlighting the impact of IHH on host-commensal organism cometabolism in the gut. Thus, we present the first evidence that IHH perturbs the gut microbiome functionally, setting the stage for understanding its involvement in cardiometabolic disorders. IMPORTANCE Intestinal dysbiosis mediates various cardiovascular diseases comorbid with OSA. To understand the role of dysbiosis in cardiovascular and metabolic disease caused by OSA, we systematically study the effect of intermittent hypoxic/hypercapnic stress (IHH, mimicking OSA) on gut microbes in an animal model. We take advantage of a longitudinal study design and paired omics to investigate the microbial and molecular dynamics in the gut to ascertain the contribution of microbes on intestinal metabolism in IHH. We observe microbe-dependent changes in the gut metabolome that will guide future research on unrecognized mechanistic links between gut microbes and comorbidities of OSA. Additionally, we highlight novel and noninvasive biomarkers for OSA-linked cardiovascular and metabolic disorders.

Top-Down Atmospheric Ionization Mass Spectrometry Microscopy Combined With Proteogenomics.

Mass spectrometry-based protein analysis has become an important methodology for proteogenomic mapping by providing evidence for the existence of proteins predicted at the genomic level. However, screening and identification of proteins directly on tissue samples, where histological information is preserved, remain challenging. Here we demonstrate that the ambient ionization source, nanospray desorption electrospray ionization (nanoDESI), interfaced with light microscopy allows for protein profiling directly on animal tissues at the microscopic scale. Peptide fragments for mass spectrometry analysis were obtained directly on ganglia of the medicinal leech (Hirudo medicinalis) without in-gel digestion. We found that a hypothetical protein, which is predicted by the leech genome, is highly expressed on the specialized neural cells that are uniquely found in adult sex segmental ganglia. Via this top-down analysis, a post-translational modification (PTM) of tyrosine sulfation to this neuropeptide was resolved. This three-in-one platform, including mass spectrometry, microscopy, and genome mining, provides an effective way for mappings of proteomes under the lens of a light microscope.

Mass Spectrometry-Based Visualization of Molecules Associated with Human Habitats.

The cars we drive, the homes we live in, the restaurants we visit, and the laboratories and offices we work in are all a part of the modern human habitat. Remarkably, little is known about the diversity of chemicals present in these environments and to what degree molecules from our bodies influence the built environment that surrounds us and vice versa. We therefore set out to visualize the chemical diversity of five built human habitats together with their occupants, to provide a snapshot of the various molecules to which humans are exposed on a daily basis. The molecular inventory was obtained through untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of samples from each human habitat and from the people that occupy those habitats. Mapping MS-derived data onto 3D models of the environments showed that frequently touched surfaces, such as handles (e.g., door, bicycle), resemble the molecular fingerprint of the human skin more closely than other surfaces that are less frequently in direct contact with humans (e.g., wall, bicycle frame). Approximately 50% of the MS/MS spectra detected were shared between people and the environment. Personal care products, plasticizers, cleaning supplies, food, food additives, and even medications that were found to be a part of the human habitat. The annotations indicate that significant transfer of chemicals takes place between us and our built environment. The workflows applied here will lay the foundation for future studies of molecular distributions in medical, forensic, architectural, space exploration, and environmental applications.

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Biochemical Establishment and Characterization of EncM's Flavin-N5-oxide Cofactor.

The ubiquitous flavin-dependent monooxygenases commonly catalyze oxygenation reactions by means of a transient C4a-peroxyflavin. A recent study, however, suggested an unprecedented flavin-oxygenating species, proposed as the flavin-N5-oxide (Fl(N5[O])), as key to an oxidative Favorskii-type rearrangement in the biosynthesis of the bacterial polyketide antibiotic enterocin. This stable superoxidized flavin is covalently tethered to the enzyme EncM and converted into FADH2 (Fl(red)) during substrate turnover. Subsequent reaction of Fl(red) with molecular oxygen restores the postulated Fl(N5[O]) via an unknown pathway. Here, we provide direct evidence for the Fl(N5[O]) species via isotope labeling, proteolytic digestion, and high-resolution tandem mass spectrometry of EncM. We propose that formation of this species occurs by hydrogen-transfer from Fl(red) to molecular oxygen, allowing radical coupling of the formed protonated superoxide and anionic flavin semiquinone at N5, before elimination of water affords the Fl(N5[O]) cofactor. Further biochemical and spectroscopic investigations reveal important features of the Fl(N5[O]) species and the EncM catalytic mechanism. We speculate that flavin-N5-oxides may be intermediates or catalytically active species in other flavoproteins that form the anionic semiquinone and promote access of oxygen to N5.

Phenotyping drug polypharmacology via eicosanoid profiling of blood.

It is widely accepted that small-molecule drugs, despite their selectivity at primary targets, exert pharmacological effects (and safety liabilities) through a multiplicity of pathways. As such, it has proved extremely difficult to experimentally assess polypharmacology in an agnostic fashion. Profiling of metabolites produced as part of physiological responses to pharmacological stimuli provides a unique opportunity to explore drug pharmacology. A total of 122 eicosanoid lipids in human whole blood were monitored from 10 different donors upon stimulation with several inducers of immunological responses and treatment with modulators of prostaglandin (PG) and leukotriene biosynthesis, including clinical and investigational molecules. Such analysis revealed differentiation between drugs nominally targeting different eicosanoid biosynthetic enzymes, or even those designed to target the same enzyme. Profiled agents, some of them marketed products, affect eicosanoid biosynthesis in ways that cannot be predicted from information on their intended targets. As an example, we used this platform to discriminate drugs based on their ability to silence PG biosynthesis in response to bacterial lipopolysaccharide, resulting in differential pharmacological activity in an in vivo model of endotoxemia. Some of the observed effects are subject to variability among individuals, indicating a potential application of this methodology to the patient stratification, based on their responses to benchmark drugs and experimental compounds read on the eicosanome via a simple blood test.

Molecular cartography of the human skin surface in 3D.

The human skin is an organ with a surface area of 1.5-2 m(2) that provides our interface with the environment. The molecular composition of this organ is derived from host cells, microbiota, and external molecules. The chemical makeup of the skin surface is largely undefined. Here we advance the technologies needed to explore the topographical distribution of skin molecules, using 3D mapping of mass spectrometry data and microbial 16S rRNA amplicon sequences. Our 3D maps reveal that the molecular composition of skin has diverse distributions and that the composition is defined not only by skin cells and microbes but also by our daily routines, including the application of hygiene products. The technological development of these maps lays a foundation for studying the spatial relationships of human skin with hygiene, the microbiota, and environment, with potential for developing predictive models of skin phenotypes tailored to individual health.

Direct detection of fungal siderophores on bats with white-nose syndrome via fluorescence microscopy-guided ambient ionization mass spectrometry.

White-nose syndrome (WNS) caused by the pathogenic fungus Pseudogymnoascus destructans is decimating the populations of several hibernating North American bat species. Little is known about the molecular interplay between pathogen and host in this disease. Fluorescence microscopy ambient ionization mass spectrometry was used to generate metabolic profiles from the wings of both healthy and diseased bats of the genus Myotis. Fungal siderophores, molecules that scavenge iron from the environment, were detected on the wings of bats with WNS, but not on healthy bats. This work is among the first examples in which microbial molecules are directly detected from an infected host and highlights the ability of atmospheric ionization methodologies to provide direct molecular insight into infection.

Mechanism of action of thalassospiramides, a new class of calpain inhibitors.

Thalassospiramides comprise a large family of lipopeptide natural products produced by Thalassospira and Tistrella marine bacteria. Here we provide further evidence of their nanomolar inhibitory activity against the human calpain 1 protease. Analysis of structure-activity relationship data supported our hypothesis that the rigid 12-membered ring containing an α,ß-unsaturated carbonyl moiety is the pharmacologically active functional group, in contrast to classic electrophilic "warheads" in known calpain inhibitors. Using a combination of chemical modifications, mass spectrometric techniques, site-directed mutagenesis, and molecular modeling, we show the covalent binding of thalassospiramide's α,ß-unsaturated carbonyl moiety to the thiol group of calpain's catalytic Cys115 residue by a Michael 1,4-addition reaction. As nanomolar calpain inhibitors with promising selectivity and low toxicity from natural sources are rare, we consider thalassospiramides as promising drug leads.

A highly efficient, high-throughput lipidomics platform for the quantitative detection of eicosanoids in human whole blood.

We have developed an ultra-performance liquid chromatography-multiple reaction monitoring/mass spectrometry (UPLC-MRM/MS)-based, high-content, high-throughput platform that enables simultaneous profiling of multiple lipids produced ex vivo in human whole blood (HWB) on treatment with calcium ionophore and its modulation with pharmacological agents. HWB samples were processed in a 96-well plate format compatible with high-throughput sample processing instrumentation. We employed a scheduled MRM (sMRM) method, with a triple-quadrupole mass spectrometer coupled to a UPLC system, to measure absolute amounts of 122 distinct eicosanoids using deuterated internal standards. In a 6.5-min run, we resolved and detected with high sensitivity (lower limit of quantification in the range of 0.4-460 pg) all targeted analytes from a very small HWB sample (2.5 µl). Approximately 90% of the analytes exhibited a dynamic range exceeding 1000. We also developed a tailored software package that dramatically sped up the overall data quantification and analysis process with superior consistency and accuracy. Matrix effects from HWB and precision of the calibration curve were evaluated using this newly developed automation tool. This platform was successfully applied to the global quantification of changes on all 122 eicosanoids in HWB samples from healthy donors in response to calcium ionophore stimulation.

Analysis of the ketosynthase-chain length factor heterodimer from the fredericamycin polyketide synthase.

The pentadecaketide fredericamycin has the longest carbon chain backbone among polycyclic aromatic polyketide antibiotics whose biosynthetic genes have been sequenced. This backbone is synthesized by the bimodular fdm polyketide synthase (PKS). Here, we demonstrate that the bimodular fdm PKS as well as its elongation module alone synthesize undecaketides and dodecaketides. Thus, unlike other homologs, the fdm ketosynthase-chain length factor (KS-CLF) heterodimer does not exclusively control the backbone length of its natural product. Using sequence- and structure-based approaches, 48 CLF multiple mutants were engineered and analyzed. Unexpectedly, the I134F mutant was unable to turn over but could initiate and partially elongate the polyketide chain. This unprecedented mutant suggests that the KS-CLF heterodimer harbors an as yet uncharacterized chain termination mechanism. Together, our findings reveal fundamental mechanistic differences between the fdm PKS and its well-studied homologs.