Increasing appreciation of the gut microbiome’s role in health motivates understanding the molecular composition of human feces. To analyze such complex samples, we developed a platform coupling targeted and untargeted metabolomics. The approach is facilitated through split flow from one UPLC, joint timing triggered by contact closure relays, and a script to retrieve the data. It is designed to detect specific metabolites of interest with high sensitivity, allows for correction of targeted information, enables better quantitation thus providing an advanced analytical tool for exploratory studies. Procrustes analysis revealed that untargeted approach provides a better correlation to microbiome data, associating specific metabolites with microbes that produce or process them. With the subset of over one hundred human fecal samples from the American Gut project, the implementation of the described coupled workflow revealed that targeted analysis using combination of single transition per compound with retention time misidentifies 30% of the targeted data and could lead to incorrect interpretations. At the same time, the targeted analysis extends detection limits and dynamic range, depending on the compounds, by orders of magnitude. A software application has been developed as a part of the workflow to allows for quantitative assessments based on calibration curves. Using this approach, we detect expected microbially modified molecules such as secondary bile acids and unexpected microbial molecules including Pseudomonas-associated quinolones and rhamnolipids in feces, setting the stage for metabolome-microbiome-wide association studies (MMWAS).

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.

Covering: up to 2016 Humans are walking microbial ecosystems, each harboring a complex microbiome with the genetic potential to produce a vast array of natural products. Recent sequencing data suggest that our microbial inhabitants are critical for maintaining overall health. Shifts in microbial communities have been correlated to a number of diseases including infections, inflammation, cancer, and neurological disorders. Some of these clinically and diagnostically relevant phenotypes are a result of the presence of small molecules, yet we know remarkably little about their contributions to the health of individuals. Here, we review microbe-derived natural products as mediators of human disease.

•CT scan images used to generate 3D models of human lungs for mapping omics data•Microbiome and metabolome data obtained from a CF lung•Omics data plotted on 3D lung model to visualize spatial interactions and variations•Region-specific metabolism of medications placed in the context of microbial distributionOur understanding of the spatial variation in the chemical and microbial makeup of an entire human organ remains limited, in part due to the size and heterogeneity of human organs and the complexity of the associated metabolome and microbiome. To address this challenge, we developed a workflow to enable the cartography of metabolomic and microbiome data onto a three-dimensional (3D) organ reconstruction built off radiological images. This enabled the direct visualization of the microbial and chemical makeup of a human lung from a cystic fibrosis patient. We detected host-derived molecules, microbial metabolites, medications, and region-specific metabolism of medications and placed it in the context of microbial distributions in the lung. Our tool further created browsable maps of a 3D microbiome/metabolome reconstruction map on a radiological image of a human lung and forms an interactive resource for the scientific community.Download high-res image (233KB)Download full-size image

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.

Imagine a scenario where personal belongings such as pens, keys, phones, or handbags are found at an investigative site. It is often valuable to the investigative team that is trying to trace back the belongings to an individual to understand their personal habits, even when DNA evidence is also available. Here, we develop an approach to translate chemistries recovered from personal objects such as phones into a lifestyle sketch of the owner, using mass spectrometry and informatics approaches. Our results show that phones’ chemistries reflect a personalized lifestyle profile. The collective repertoire of molecules found on these objects provides a sketch of the lifestyle of an individual by highlighting the type of hygiene/beauty products the person uses, diet, medical status, and even the location where this person may have been. These findings introduce an additional form of trace evidence from skin-associated lifestyle chemicals found on personal belongings. Such information could help a criminal investigator narrowing down the owner of an object found at a crime scene, such as a suspect or missing person.

•Pattern-based genome mining was applied to 35 Salinispora strains•Molecular networking facilitated new compound discovery•The quinomycin-type depsipeptide retimycin A was characterizedGenome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. Here we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated the identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. These efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.Figure optionsDownload full-size imageDownload high-quality image (218 K)Download as PowerPoint slide

Since the time Van Leeuwenhoek was able to observe microbes through a microscope, an innovation that led to the birth of the field of microbiology, we have aimed to understand how microorganisms function, interact and communicate. The exciting progress in the development of analytical technologies and workflows has demonstrated that mass spectrometry is a very powerful technique for the interrogation of microbiology at the molecular level. In this review, we aim to highlight the available and emerging tools in mass spectrometry for microbial analysis by overviewing the methods and workflow advances for taxonomic identification, microbial interaction, dereplication and drug discovery. We emphasize their potential for future development and point out unsolved problems and future directions that would aid in the analysis of the chemistry produced by microbes.

•MS/MS molecular networking was used to analyze complex mixtures.•Data from in-house drug libraries, NIST, METLIN was used for rapid identification.•Lyso-PAF was identified in coral samples using lung data set and NIST database.While in nucleotide sequencing, the analysis of DNA from complex mixtures of organisms is common, this is not yet true for mass spectrometric data analysis of complex mixtures. The comparative analyses of mass spectrometry data of microbial communities at the molecular level is difficult to perform, especially in the context of a host. The challenge does not lie in generating the mass spectrometry data, rather much of the difficulty falls in the realm of how to derive relevant information from this data. The informatics based techniques to visualize and organize datasets are well established for metagenome sequencing; however, due to the scarcity of informatics strategies in mass spectrometry, it is currently difficult to cross correlate two very different mass spectrometry data sets from microbial communities and their hosts. We highlight that molecular networking can be used as an organizational tool of tandem mass spectrometry data, automated database search for rapid identification of metabolites, and as a workflow to manage and compare mass spectrometry data from complex mixtures of organisms. To demonstrate this platform, we show data analysis from hard corals and a human lung associated with cystic fibrosis.

The human skin is an organ with a surface area of 1.5–2 m2 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.

Ribosomally synthesized and posttranslationally modified peptides (RiPPs), especially from microbial sources, are a large group of bioactive natural products that are a promising source of new (bio)chemistry and bioactivity.1 In light of exponentially increasing microbial genome databases and improved mass spectrometry (MS)-based metabolomic platforms, there is a need for computational tools that connect natural product genotypes predicted from microbial genome sequences with their corresponding chemotypes from metabolomic data sets. Here, we introduce RiPPquest, a tandem mass spectrometry database search tool for identification of microbial RiPPs, and apply it to lanthipeptide discovery. RiPPquest uses genomics to limit search space to the vicinity of RiPP biosynthetic genes and proteomics to analyze extensive peptide modifications and compute p-values of peptide-spectrum matches (PSMs). We highlight RiPPquest by connecting multiple RiPPs from extracts of Streptomyces to their gene clusters and by the discovery of a new class III lanthipeptide, informatipeptin, from Streptomyces viridochromogenes DSM 40736 to reflect that it is a natural product that was discovered by mass spectrometry based genome mining using algorithmic tools rather than manual inspection of mass spectrometry data and genetic information. The presented tool is available at cyclo.ucsd.edu.

Coral reefs are intricate ecosystems that harbor diverse organisms, including 25% of all marine fish. Healthy corals exhibit a complex symbiosis between coral polyps, endosymbiotic alga, and an array of microorganisms, called the coral holobiont. Secretion of specialized metabolites by coral microbiota is thought to contribute to the defense of this sessile organism against harmful biotic and abiotic factors. While few causative agents of coral diseases have been unequivocally identified, fungi have been implicated in the massive destruction of some soft corals worldwide. Because corals are nocturnal feeders, they may be more vulnerable to fungal infection at night, and we hypothesized that the coral microbiota would have the capability to enhance their defenses against fungi in the dark. A Pseudoalteromonas sp. isolated from a healthy octocoral displayed light-dependent antifungal properties when grown adjacent to Penicillium citrinum (P. citrinum) isolated from a diseased Gorgonian octocoral. Microbial MALDI-imaging mass spectrometry (IMS) coupled with molecular network analyses revealed that Pseudoalteromonas produced higher levels of antifungal polyketide alteramides in the dark than in the light. The alteramides were inactivated by light through a photoinduced intramolecular cyclization. Further NMR studies led to a revision of the stereochemical structure of the alteramides. Alteramide A exhibited antifungal properties and elicited changes in fungal metabolite distributions of mycotoxin citrinin and citrinadins. These data support the hypothesis that coral microbiota use abiotic factors such as light to regulate the production of metabolites with specialized functions to combat opportunistic pathogens at night.

Most (75%) of the anti-infectives that save countless lives and enormously improve quality of life originate from microbes found in nature. Herein, we described a global visualization of the detectable molecules produced from a single microorganism, which we define as the ‘molecular network’ of that organism, followed by studies to characterize the cellular effects of antibacterial molecules. We demonstrate that Streptomyces roseosporus produces at least four non-ribosomal peptide synthetase-derived molecular families and their gene subnetworks (daptomycin, arylomycin, napsamycin and stenothricin) were identified with different modes of action. A number of previously unreported analogs involving truncation, glycosylation, hydrolysis and biosynthetic intermediates and/or shunt products were also captured and visualized by creation of a map through MS/MS networking. The diversity of antibacterial compounds produced by S. roseosporus highlights the importance of developing new approaches to characterize the molecular capacity of an organism in a more global manner. This allows one to more deeply interrogate the biosynthetic capacities of microorganisms with the goal to streamline the discovery pipeline for biotechnological applications in agriculture and medicine. This is a contribution to a special issue to honor Chris Walsh’s amazing career.

Microorganisms such as bacteria and fungi produce a variety of specialized metabolites that are invaluable for agriculture, biological research, and drug discovery. However, the screening of microbial metabolic output is usually a time-intensive task. Here, we utilize a liquid microjunction surface sampling probe for electrospray ionization-mass spectrometry to extract and ionize metabolite mixtures directly from living microbial colonies grown on soft nutrient agar in Petri-dishes without any sample pretreatment. To demonstrate the robustness of the method, this technique was applied to observe the metabolic output of more than 30 microorganisms, including yeast, filamentous fungi, pathogens, and marine-derived bacteria, that were collected worldwide. Diverse natural products produced from different microbes, including Streptomyces coelicolor, Bacillus subtilis, and Pseudomonas aeruginosa are further characterized.

Understanding molecular interaction pathways in complex biological systems constitutes a treasure trove of knowledge that might facilitate the specific, chemical manipulation of the countless microbiological systems that occur throughout our world. However, there is a lack of methodologies that allow the direct investigation of chemical gradients and interactions in living biological systems, in real time. Here, we report the use of nanospray desorption electrospray ionization (nanoDESI) imaging mass spectrometry for in vivo metabolic profiling of living bacterial colonies directly from the Petri dish with absolutely no sample preparation needed. Using this technique, we investigated single colonies of Shewanella oneidensis MR-1, Bacillus subtilis 3610, and Streptomyces coelicolor A3(2) as well as a mixed biofilm of S. oneidensis MR-1 and B. subtilis 3610. Data from B. subtilis 3610 and S. coelicolor A3(2) provided a means of validation for the method while data from S. oneidensis MR-1 and the mixed biofilm showed a wide range of compounds that this bacterium uses for the dissimilatory reduction of extracellular metal oxides, including riboflavin, iron-bound heme and heme biosynthetic intermediates, and the siderophore putrebactin.

A major goal in natural product discovery programs is to rapidly dereplicate known entities from complex biological extracts. We demonstrate here that molecular networking, an approach that organizes MS/MS data based on chemical similarity, is a powerful complement to traditional dereplication strategies. Successful dereplication with molecular networks requires MS/MS spectra of the natural product mixture along with MS/MS spectra of known standards, synthetic compounds, or well-characterized organisms, preferably organized into robust databases. This approach can accommodate different ionization platforms, enabling cross correlations of MS/MS data from ambient ionization, direct infusion, and LC-based methods. Molecular networking not only dereplicates known molecules from complex mixtures, it also captures related analogues, a challenge for many other dereplication strategies. To illustrate its utility as a dereplication tool, we apply mass spectrometry-based molecular networking to a diverse array of marine and terrestrial microbial samples, illustrating the dereplication of 58 molecules including analogues.

Atmospheric ionization methods are ideally suited for prolonged MS/MS analysis. Data-independent MS/MS is a complementary technique for analysis of biological samples as compared to data-dependent analysis. Here, we pair data-independent MS/MS with the ambient ionization method nanospray desorption electrospray ionization (nanoDESI) for untargeted analysis of bacterial metabolites. Proof-of-principle data and analysis are illustrated by sampling Bacillus subtilis and Pseudomonas aeruginosa directly from Petri dishes. We found that this technique enables facile comparisons between strains via MS and MS/MS plots which can be translated to chemically informative molecular maps through MS/MS networking. The development of novel techniques to characterize microbial metabolites allows rapid and efficient analysis of metabolic exchange factors. This is motivated by our desire to develop novel techniques to explore the role of interspecies interactions in the environment, health, and disease. This is a contribution to honor Professor Catherine C. Fenselau in receiving the prestigious ASMS Award for a Distinguished Contribution in Mass Spectrometry for her pioneering work on microbial mass spectrometry.

There is immense cellular and molecular heterogeneity in biological systems. Here, we demonstrate the utility of integrating an inverted light microscope with an ambient ionization source, nanospray electrospray desorption ionization, attached to a high-resolution mass spectrometer to characterize the molecular composition of mouse spinal cords. We detected a broad range of molecules, including peptides and proteins, as well as metabolites such as lipids, sugars, and other small molecules, including S-adenosyl methionine and glutathione, through top-down MS. Top-down analysis revealed variation in the expression of Hb, including the transition from fetal to adult Hb and heterogeneity in Hb subunits consistent with the genetic diversity of the mouse models. Similarly, temporal changes to actin-sequestering proteins β-thymosins during development were observed. These results demonstrate that interfacing microscopy with ambient ionization provides the means to perform targeted in situ ambient top-down mass spectral analysis to study the pattern of proteins, lipids, and sugars in biologically heterogeneous samples.

The ability to correlate the production of specialized metabolites to the genetic capacity of the organism that produces such molecules has become an invaluable tool in aiding the discovery of biotechnologically applicable molecules. Here, we accomplish this task by matching molecular families with gene cluster families, making these correlations to 60 microbes at one time instead of connecting one molecule to one organism at a time, such as how it is traditionally done. We can correlate these families through the use of nanospray desorption electrospray ionization MS/MS, an ambient pressure MS technique, in conjunction with MS/MS networking and peptidogenomics. We matched the molecular families of peptide natural products produced by 42 bacilli and 18 pseudomonads through the generation of amino acid sequence tags from MS/MS data of specific clusters found in the MS/MS network. These sequence tags were then linked to biosynthetic gene clusters in publicly accessible genomes, providing us with the ability to link particular molecules with the genes that produced them. As an example of its use, this approach was applied to two unsequenced Pseudoalteromonas species, leading to the discovery of the gene cluster for a molecular family, the bromoalterochromides, in the previously sequenced strain P. piscicida JCM 20779T. The approach itself is not limited to 60 related strains, because spectral networking can be readily adopted to look at molecular family–gene cluster families of hundreds or more diverse organisms in one single MS/MS network.

Glycosyl groups are an essential mediator of molecular interactions in cells and on cellular surfaces. There are very few methods that directly relate sugar-containing molecules to their biosynthetic machineries. Here, we introduce glycogenomics as an experiment-guided genome-mining approach for fast characterization of glycosylated natural products (GNPs) and their biosynthetic pathways from genome-sequenced microbes by targeting glycosyl groups in microbial metabolomes. Microbial GNPs consist of aglycone and glycosyl structure groups in which the sugar unit(s) are often critical for the GNP’s bioactivity, e.g., by promoting binding to a target biomolecule. GNPs are a structurally diverse class of molecules with important pharmaceutical and agrochemical applications. Herein, O- and N-glycosyl groups are characterized in their sugar monomers by tandem mass spectrometry (MS) and matched to corresponding glycosylation genes in secondary metabolic pathways by a MS-glycogenetic code. The associated aglycone biosynthetic genes of the GNP genotype then classify the natural product to further guide structure elucidation. We highlight the glycogenomic strategy by the characterization of several bioactive glycosylated molecules and their gene clusters, including the anticancer agent cinerubin B from Streptomyces sp. SPB74 and an antibiotic, arenimycin B, from Salinispora arenicola CNB-527.

Glycosyl groups are an essential mediator of molecular interactions in cells and on cellular surfaces. There are very few methods that directly relate sugar-containing molecules to their biosynthetic machineries. Here, we introduce glycogenomics as an experiment-guided genome-mining approach for fast characterization of glycosylated natural products (GNPs) and their biosynthetic pathways from genome-sequenced microbes by targeting glycosyl groups in microbial metabolomes. Microbial GNPs consist of aglycone and glycosyl structure groups in which the sugar unit(s) are often critical for the GNP’s bioactivity, e.g., by promoting binding to a target biomolecule. GNPs are a structurally diverse class of molecules with important pharmaceutical and agrochemical applications. Herein, O- and N-glycosyl groups are characterized in their sugar monomers by tandem mass spectrometry (MS) and matched to corresponding glycosylation genes in secondary metabolic pathways by a MS-glycogenetic code. The associated aglycone biosynthetic genes of the GNP genotype then classify the natural product to further guide structure elucidation. We highlight the glycogenomic strategy by the characterization of several bioactive glycosylated molecules and their gene clusters, including the anticancer agent cinerubin B from Streptomyces sp. SPB74 and an antibiotic, arenimycin B, from Salinispora arenicola CNB-527.

Mono- and multispecies microbial populations alter the chemistry of their surrounding environments during colony development thereby influencing multicellular behavior and interspecies interactions of neighboring microbes. Here we present a methodology that enables the creation of three-dimensional (3D) models of a microbial chemotype that can be correlated to the colony phenotype through multimodal imaging analysis. These models are generated by performing matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) imaging mass spectrometry (IMS) on serial cross-sections of microbial colonies grown on 8 mm deep agar, registering data sets of each serial section in MATLAB to create a model, and then superimposing the model with a photograph of the colonies themselves. As proof-of-principle, 3D models were used to visualize metabolic exchange during microbial interactions between Bacillus subtilis and Streptomyces coelicolor, as well as, Candida albicans and Pseudomonas aeruginosa. The resulting models were able to capture the depth profile of secreted metabolites within the agar medium and revealed properties of certain mass signals that were previously not observable using two-dimensional MALDI-TOF IMS. Most significantly, the 3D models were capable of mapping previously unobserved chemical distributions within the array of sub-surface hyphae of C. albicans and how this chemistry is altered by the presence of P. aeruginosa, an opportunistic pathogen known to alter virulence of C. albicans. It was determined that the presence of C. albicans triggered increased rhamnolipid production by P. aeruginosa, which in turn was capable of inhibiting embedded hyphal growth produced beneath the C. albicans colony at ambient temperature.

The communities constituting our microbiotas are emerging as mediators of the health-disease continuum. However, deciphering the functional impact of microbial communities on host pathophysiology represents a formidable challenge, due to the heterogeneous distribution of chemical and microbial species within the gastrointestinal (GI) tract. Herein, we apply imaging mass spectrometry (IMS) to localize metabolites from the interaction between the host and colonizing microbiota. This approach complements other molecular imaging methodologies in that analytes need not be known a priori, offering the possibility of untargeted analysis. Localized molecules within the GI tract were then identified in situ by surface sampling with nanodesorption electrospray ionization Fourier transform ion cyclotron resonance-mass spectrometry (nanoDESI FTICR-MS). Products from diverse structural classes were identified including cholesterol-derived lipids, glycans, and polar metabolites. Specific chemical transformations performed by the microbiota were validated with bacteria in culture. This study illustrates how untargeted spatial characterization of metabolites can be applied to the molecular dissection of complex biology in situ.

Many microbes can be cultured as single-species communities. Often, these colonies are controlled and maintained via the secretion of metabolites. Such metabolites have been an invaluable resource for the discovery of therapeutics (e.g. penicillin, taxol, rapamycin, epothilone). In this article, written for a special issue on imaging mass spectrometry, we show that MALDI-imaging mass spectrometry can be adapted to observe, in a spatial manner, the metabolic exchange patterns of a diverse array of microbes, including thermophilic and mesophilic fungi, cyanobacteria, marine and terrestrial actinobacteria, and pathogenic bacteria. Dependent on media conditions, on average and based on manual analysis, we observed 11.3 molecules associated with each microbial IMS experiment, which was split nearly 50:50 between secreted and colony-associated molecules. The spatial distributions of these metabolic exchange factors are related to the biological and ecological functions of the organisms. This work establishes that MALDI-based IMS can be used as a general tool to study a diverse array of microbes. Furthermore the article forwards the notion of the IMS platform as a window to discover previously unreported molecules by monitoring the metabolic exchange patterns of organisms when grown on agar substrates.This article is part of a Special Issue entitled: Imaging Mass Spectrometry: A User’s Guide to a New Technique for Biological and Biomedical Research.Highlights► Imaging mass spectrometry can be performed on a large number of microbes. ► An avg. of 11.3 metabolic exchange factors were observed from a microbial IMS experiment. ► Complex microbial samples can be characterized at the molecular level using IMS. ► IMS can be used to discover therapeutic leads from microbes.

In polymicrobial infections, microbes can interact with both the host immune system and one another through direct contact or the secretion of metabolites, affecting disease progression and treatment options. The thick mucus in the lungs of patients with cystic fibrosis is highly susceptible to polymicrobial infections by opportunistic pathogens, including the bacterium Pseudomonas aeruginosa and the fungus Aspergillus fumigatus. Unravelling the hidden molecular interactions within such polymicrobial communities and their metabolic exchange processes will require effective enabling technologies applied to model systems. In the present study, MALDI-TOF and MALDI-FT-ICR imaging mass spectrometry (MALDI-IMS) combined with MS/MS networking were used to provide insight into the interkingdom interaction between P. aeruginosa and A. fumigatus at the molecular level. The combination of these technologies enabled the visualization and identification of metabolites secreted by these microorganisms grown on agar. A complex molecular interplay was revealed involving suppression, increased production, and biotransformation of a range of metabolites. Of particular interest is the observation that P. aeruginosa phenazine metabolites were converted by A. fumigatus into other chemical entities with alternative properties, including enhanced toxicities and the ability to induce fungal siderophores. This work highlights the capabilities of MALDI-IMS and MS/MS network analysis to study interkingdom interactions and provides insight into the complex nature of polymicrobial metabolic exchange and biotransformations.

Integrating the governing chemistry with the genomics and phenotypes of microbial colonies has been a “holy grail” in microbiology. This work describes a highly sensitive, broadly applicable, and cost-effective approach that allows metabolic profiling of live microbial colonies directly from a Petri dish without any sample preparation. Nanospray desorption electrospray ionization mass spectrometry (MS), combined with alignment of MS data and molecular networking, enabled monitoring of metabolite production from live microbial colonies from diverse bacterial genera, including Bacillus subtilis, Streptomyces coelicolor, Mycobacterium smegmatis, and Pseudomonas aeruginosa. This work demonstrates that, by using these tools to visualize small molecular changes within bacterial interactions, insights can be gained into bacterial developmental processes as a result of the improved organization of MS/MS data. To validate this experimental platform, metabolic profiling was performed on Pseudomonas sp. SH-C52, which protects sugar beet plants from infections by specific soil-borne fungi [R. Mendes et al. (2011) Science 332:1097–1100]. The antifungal effect of strain SH-C52 was attributed to thanamycin, a predicted lipopeptide encoded by a nonribosomal peptide synthetase gene cluster. Our technology, in combination with our recently developed peptidogenomics strategy, enabled the detection and partial characterization of thanamycin and showed that it is a monochlorinated lipopeptide that belongs to the syringomycin family of antifungal agents. In conclusion, the platform presented here provides a significant advancement in our ability to understand the spatiotemporal dynamics of metabolite production in live microbial colonies and communities.

Imaging mass spectrometry tools allow the two-dimensional visualization of the distribution of trace metals, metabolites, surface lipids, peptides and proteins directly from biological samples without the need for chemical tagging or antibodies, and are becoming increasingly useful for microbiology applications. These tools, comprising different imaging mass spectrometry techniques, are ushering in an exciting new era of discovery by enabling the generation of chemical hypotheses based on the spatial mapping of atoms and molecules that can correlate to or transcend observed phenotypes. In this Innovation article, we explore the wide range of imaging mass spectrometry techniques that is available to microbiologists and describe the unique applications of these tools to microbiology with respect to the types of samples to be investigated.

The microbiome is an abundance of microorganisms within a host (e.g. human microbiome). These microorganisms produce small molecules and metabolites that have been shown to affect and dictate the physiology of an individual. Functional knowledge of these molecules, often produced for communication or defense, will reveal the interplay between microbes and host in health and disease. The vast diversity in structure and function of microbiome-associated small molecules necessitate tools that will utilize multiple ‘-omics’ strategies to understand the interactions within the human microbiome. This review discusses the importance of these investigations and the integration of current ‘-omics’ technologies with tools established in natural product discovery in order to identify and characterize uncharacterized small molecules in the effort towards diagnostic modeling of the human microbiome.

There are very few fungal polyketide synthases that have been characterized by mass spectrometry. In this paper we describe the in vitro reconstitution and FT-ICR-MS verification of the full activity of an intact 277 kDa fungal polyketide synthase LovF of the lovastatin biosynthetic pathway. We report here both the verification of the reconstitution of fully functional holo-LovF by using 13C-labeled malonyl-CoA to form α-methylbutyrate functionality and also detection of five predicted intermediates covalently bound to the 4′-phosphopantetheine at the acyl carrier protein (ACP) active site utilizing the phosphopantetheine ejection assay and high-resolution mass spectrometry. Under in vitro conditions, the diketide acetoacetyl intermediate did not accumulate on the ACP active site of holo-LovF following incubation with malonyl-CoA substrate. We found that incubation of holo-LovF with acetoacetyl-CoA served as an effective means of loading the diketide intermediate onto the ACP active site of LovF. Our results demonstrate that subsequent α-methylation of the acetoacetyl intermediate stabilizes the intermediate onto the ACP active site and facilitates the formation and mass spectrometric detection of additional intermediates en route to the formation of α-methylbutyrate.

Direct observation of halogenated natural products produced by different strains of marine cyanobacteria was accomplished by electrospray ionization and matrix assisted laser desorption ionization and gas phase separation via ion mobility mass spectrometry of extracts as well as intact organisms.

Selective degradation of cellular proteins offers an important mechanism to coordinate cellular processes including cell differentiation, defense, metabolic control, signal transduction and proliferation. While much is known about eukaryotic ubiquitination, we know little about the recently discovered ubiquitin-like protein in prokaryotes (PUP). Through expression of His7 tagged PUP and exploitation of the characteristic +243 Da mass shift attributed to trypsinized PUPylated peptides, a global pull-down of protein targets for PUPylation in Mycobacterium smegmatis revealed 103 candidate PUPylation targets and 52 confirmed targets. Similar to eukaryotic ubiquitination, further analysis of these targets revealed neither primary sequence nor secondary structure homology at the point of attachment. Pathways containing PUPylated proteins include many central to rapid cell growth, such as glycolysis, gluconeogenesis, amino acid and mycolic acidmetabolism and biosynthesis, as well as translation. Seventeen of the 29 nitrosylated protein targets previously identified in Mycobacterium tuberculosis were also identified as PUPylation candidates indicating a connection between PUP-mediated remodeling of critical metabolic pathways and the mycobacterial response to exogenous stress.

Covering: up to June 2009

Natural and non-natural cyclic peptides are a crucial component in drug discovery programs because of their considerable pharmaceutical properties. Cyclosporin, microcystins, and nodularins are all notable pharmacologically important cyclic peptides. Because these biologically active peptides are often biosynthesized nonribosomally, they often contain nonstandard amino acids, thus increasing the complexity of the resulting tandem mass spectrometry data. In addition, because of the cyclic nature, the fragmentation patterns of many of these peptides showed much higher complexity when compared to related counterparts. Therefore, at the present time it is still difficult to annotate cyclic peptides MS/MS spectra. In this current work, an annotation program was developed for the annotation and characterization of tandem mass spectra obtained from cyclic peptides. This program, which we call MS-CPA is available as a web tool (http://lol.ucsd.edu/ms-cpa_v1/Input.py). Using this program, we have successfully annotated the sequence of representative cyclic peptides, such as seglitide, tyrothricin, desmethoxymajusculamide C, dudawalamide A, and cyclomarins, in a rapid manner and also were able to provide the first-pass structure evidence of a newly discovered natural product based on predicted sequence. This compound is not available in sufficient quantities for structural elucidation by other means such as NMR.1 In addition to the development of this cyclic annotation program, it was observed that some cyclic peptides fragmented in unexpected ways resulting in the scrambling of sequences. In summary, MS-CPA not only provides a platform for rapid confirmation and annotation of tandem mass spectrometry data obtained with cyclic peptides but also enables quantitative analysis of the ion intensities. This program facilitates cyclic peptide analysis, sequencing, and also acts as a useful tool to investigate the uncommon fragmentation phenomena of cyclic peptides and aids the characterization of newly discovered cyclic peptides encountered in drug discovery programs.

A global LC–MS metabolite analysis of wild-type Pseudomonas auerigunosa and mutants targeting the natural product pyochelin revealed the production of previously unknown metabolites, the 2-alkyl-4,5-dihydrothiazole-4-carboxylates.

Marine cyanobacteria and sponges are prolific sources of natural products with therapeutic applications. In this paper we introduce a mass spectrometry based approach to characterize the spatial distribution of these natural products from intact organisms of differing complexities. The natural product MALDI-TOF-imaging (npMALDI-I) approach readily identified a number of metabolites from the cyanobacteria Lyngbya majuscula 3L and JHB, Oscillatoria nigro-viridis, Lyngbya bouillonii, and a Phormidium species, even when they were present as mixtures. For example, jamaicamide B, a well established natural product from the cyanobacterium Lyngbya majuscula JHB, was readily detected as were the ions that correspond to the natural products curacin A and curazole from Lyngbya majuscula 3L. In addition to these known natural products, a large number of unknown ions co-localized with the different cyanobacteria, providing an indication that this method can be used for dereplication and drug discovery strategies. Finally, npMALDI-I was used to observe the secondary metabolites found within the sponge Dysidea herbacea. From these sponge data, more than 40 ions were shown to be co-localized, many of which were halogenated. The npMALDI-I data on the sponge indicates that, based on the differential distribution of secondary metabolites, sponges have differential chemical micro-environments within their tissues. Our data demonstrate that npMALDI-I can be used to provide spatial distribution of natural products, from single strands of cyanobacteria to the very complex marine assemblage of a sponge.

Molecular networking is a tandem mass spectrometry (MS/MS) data organizational approach that has been recently introduced in the drug discovery, metabolomics, and medical fields. The chemistry of molecules dictates how they will be fragmented by MS/MS in the gas phase and, therefore, two related molecules are likely to display similar fragment ion spectra. Molecular networking organizes the MS/MS data as a relational spectral network thereby mapping the chemistry that was detected in an MS/MS-based metabolomics experiment. Although the wider utility of molecular networking is just beginning to be recognized, in this review we highlight the principles behind molecular networking and its use for the discovery of therapeutic leads, monitoring drug metabolism, clinical diagnostics, and emerging applications in precision medicine.