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.

Impact of Artificial Sputum Medium Formulation on Pseudomonas aeruginosa Secondary Metabolite Production.

In vitro culture media are being developed to understand how host site-specific nutrient profiles influence microbial pathogenicity and ecology. To mimic the cystic fibrosis (CF) lung environment, a variety of artificial sputum media (ASM) have been created. However, the composition of these ASM vary in the concentration of key nutrients, including amino acids, lipids, DNA, and mucin. In this work, we used feature-based molecular networking (FBMN) to perform comparative metabolomics of Pseudomonas aeruginosa, the predominant opportunistic pathogen infecting the lungs of people with CF, cultured in nine different ASM. We found that the concentration of aromatic amino acids and iron from mucin added to the media contributes to differences in the production of P. aeruginosa virulence-associated secondary metabolites. IMPORTANCE Different media formulations aiming to replicate in vivo infection environments contain different nutrients, which affects interpretation of experimental results. Inclusion of undefined components, such as commercial porcine gastric mucin (PGM), in an otherwise chemically defined medium can alter the nutrient content of the medium in unexpected ways and influence experimental outcomes.

Exogenous Alginate Protects Staphylococcus aureus from Killing by Pseudomonas aeruginosa.

Cystic fibrosis (CF) patients chronically infected with both Pseudomonas aeruginosa and Staphylococcus aureus have worse health outcomes than patients who are monoinfected with either P. aeruginosa or S. aureus We showed previously that mucoid strains of P. aeruginosa can coexist with S. aureusin vitro due to the transcriptional downregulation of several toxic exoproducts typically produced by P. aeruginosa, including siderophores, rhamnolipids, and HQNO (2-heptyl-4-hydroxyquinoline N-oxide). Here, we demonstrate that exogenous alginate protects S. aureus from P. aeruginosa in both planktonic and biofilm coculture models under a variety of nutritional conditions. S. aureus protection in the presence of exogenous alginate is due to the transcriptional downregulation of pvdA, a gene required for the production of the iron-scavenging siderophore pyoverdine as well as the downregulation of the PQS (Pseudomonas quinolone signal) (2-heptyl-3,4-dihydroxyquinoline) quorum sensing system. The impact of exogenous alginate is independent of endogenous alginate production. We further demonstrate that coculture of mucoid P. aeruginosa with nonmucoid P. aeruginosa strains can mitigate the killing of S. aureus by the nonmucoid strain of P. aeruginosa, indicating that the mechanism that we describe here may function in vivo in the context of mixed infections. Finally, we investigated a panel of mucoid clinical isolates that retain the ability to kill S. aureus at late time points and show that each strain has a unique expression profile, indicating that mucoid isolates can overcome the S. aureus-protective effects of mucoidy in a strain-specific manner.IMPORTANCE CF patients are chronically infected by polymicrobial communities. The two dominant bacterial pathogens that infect the lungs of CF patients are P. aeruginosa and S. aureus, with ∼30% of patients coinfected by both species. Such coinfected individuals have worse outcomes than monoinfected patients, and both species persist within the same physical space. A variety of host and environmental factors have been demonstrated to promote P. aeruginosa-S. aureus coexistence, despite evidence that P. aeruginosa kills S. aureus when these organisms are cocultured in vitro Thus, a better understanding of P. aeruginosa-S. aureus interactions, particularly mechanisms by which these microorganisms are able to coexist in proximal physical space, will lead to better-informed treatments for chronic polymicrobial infections.

Natural products as mediators of disease.

Covering: up to 2016Humans 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.

MS/MS networking guided analysis of molecule and gene cluster families.

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 20779(T). 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.

Interkingdom metabolic transformations captured by microbial imaging mass spectrometry.

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.

Impact of a transposon insertion in phzF2 on the specialized metabolite production and interkingdom interactions of Pseudomonas aeruginosa.

In microbiology, gene disruption and subsequent experiments often center on phenotypic changes caused by one class of specialized metabolites (quorum sensors, virulence factors, or natural products), disregarding global downstream metabolic effects. With the recent development of mass spectrometry-based methods and technologies for microbial metabolomics investigations, it is now possible to visualize global production of diverse classes of microbial specialized metabolites simultaneously. Using imaging mass spectrometry (IMS) applied to the analysis of microbiology experiments, we can observe the effects of mutations, knockouts, insertions, and complementation on the interactive metabolome. In this study, a combination of IMS and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to visualize the impact on specialized metabolite production of a transposon insertion into a Pseudomonas aeruginosa phenazine biosynthetic gene, phzF2. The disruption of phenazine biosynthesis led to broad changes in specialized metabolite production, including loss of pyoverdine production. This shift in specialized metabolite production significantly alters the metabolic outcome of an interaction with Aspergillus fumigatus by influencing triacetylfusarinine production.

Iron content of commercial mucin contributes to compositional stability of a cystic fibrosis airway synthetic microbiota community.

In vitro culture models of mucosal environments are used to elucidate the mechanistic roles of the microbiota in human health. These models often include commercial mucins to reflect the in-situ role of mucins as an attachment site and nutrient source for the microbiota. Two types of mucins are commercially available: porcine gastric mucin (PGM) and bovine submaxillary mucin (BSM). These commercial mucins have been shown to contain iron, an essential element required by the microbiota as a co-factor for a variety of metabolic functions. In these mucin preparations, the concentration of available iron can exceed physiological concentrations present in the native environment. This unexpected source of iron influences experimental outcomes, including shaping the interactions between co-existing microbes in synthetic microbial communities used to elucidate the multispecies interactions within native microbiota. In this work, we leveraged the well-characterized iron-dependent production of secondary metabolites by the opportunistic pathogen Pseudomonas aeruginosa to aid in the development of a simple, low-cost, reproducible workflow to remove iron from commercial mucins. Using the mucosal environment of the cystic fibrosis (CF) airway as a model system, we show that P. aeruginosa is canonically responsive to iron concentration in the chemically defined synthetic CF medium complemented with semi-purified PGM, and community composition of a clinically relevant, synthetic CF airway microbial community is modulated, in part, by iron concentration in PGM.

Secondary metabolite profiling of Pseudomonas aeruginosa isolates reveals rare genomic traits.

Pseudomonas aeruginosa is a ubiquitous Gram-negative opportunistic pathogen with remarkable phylogenetic and phenotypic variabilities. In this work, we applied classical molecular networking analysis to secondary metabolite profiling data from seven Pseudomonas aeruginosa strains, including five clinical isolates from the lung secretions of people with cystic fibrosis (CF). We provide three vignettes illustrating how secondary metabolite profiling aids in the identification of rare genomics traits in P. aeruginosa. First, we describe the identification of a previously unreported class of acyl putrescines produced by isolate mFLRO1. Secondary analysis of publicly available metabolomics data revealed that acyl putrescines are produced by <5% of P. aeruginosa strains. Second, we show that isolate SH3A does not produce di-rhamnolipids. Whole-genome sequencing and comparative genomics revealed that SH3A cannot produce di-rhamnolipids because its genome belongs to clade 5 of the P. aeruginosa phylogenetic tree. Previous phylogenetic analysis of thousands of P. aeruginosa strains concluded that <1% of publicly available genome sequences contribute to this clade. Last, we show that isolate SH1B does not produce the phenazine pyocyanin or rhamnolipids because it has a one-base insertion frameshift mutation (678insC) in the gene rhlR, which disrupts rhl-driven quorum sensing. Secondary analysis of the tens of thousands of publicly available genomes in the National Center for Biotechnology Information (NCBI) and the Pseudomonas Genome Database revealed that this mutation was present in only four P. aeruginosa genomes. Taken together, this study highlights that secondary metabolite profiling combined with genomic analysis can identify rare genetic traits of P. aeruginosa isolates.IMPORTANCESecondary metabolite profiling of five Pseudomonas aeruginosa isolates from cystic fibrosis sputum captured three traits present in <1%-5% of publicly available data, pointing to how our current library of P. aeruginosa strains may not represent the diversity within this species or the genetic variance that occurs in the CF lung.

Network Topology Evaluation and Transitive Alignments for Molecular Networking.

Untargeted tandem mass spectrometry (MS/MS) is an essential technique in modern analytical chemistry, providing a comprehensive snapshot of chemical entities in complex samples and identifying unknowns through their fragmentation patterns. This high-throughput approach generates large data sets that can be challenging to interpret. Molecular Networks (MNs) have been developed as a computational tool to aid in the organization and visualization of complex chemical space in untargeted mass spectrometry data, thereby supporting comprehensive data analysis and interpretation. MNs group related compounds with potentially similar structures from MS/MS data by calculating all pairwise MS/MS similarities and filtering these connections to produce a MN. Such networks are instrumental in metabolomics for identifying novel metabolites, elucidating metabolic pathways, and even discovering biomarkers for disease. While MS/MS similarity metrics have been explored in the literature, the influence of network topology approaches on MN construction remains unexplored. This manuscript introduces metrics for evaluating MN construction, benchmarks state-of-the-art approaches, and proposes the Transitive Alignments approach to improve MN construction. The Transitive Alignment technique leverages the MN topology to realign MS/MS spectra of related compounds that differ by multiple structural modifications. Combining this Transitive Alignments approach with pseudoclique finding, a method for identifying highly connected groups of nodes in a network, resulted in more complete and higher-quality molecular families. Finally, we also introduce a targeted network construction technique called induced transitive alignments where we demonstrate effectiveness on a real world natural product discovery application. We release this transitive alignment technique as a high-throughput workflow that can be used by the wider research community.

ModiFinder: Tandem Mass Spectral Alignment Enables Structural Modification Site Localization.

Untargeted tandem mass spectrometry (MS/MS) has become a high-throughput method to measure small molecules in complex samples. One key goal is the transformation of these MS/MS spectra into chemical structures. Computational techniques such as MS/MS library search have enabled the reidentification of known compounds. Analog library search and molecular networking extend this identification to unknown compounds. While there have been advancements in metrics for the similarity of MS/MS spectra of structurally similar compounds, there is still a lack of automated methods to provide site specific information about structural modifications. Here we introduce ModiFinder which leverages the alignment of peaks in MS/MS spectra between structurally related known and unknown small molecules. Specifically, ModiFinder focuses on shifted MS/MS fragment peaks in the MS/MS alignment. These shifted peaks putatively represent substructures of the known molecule that contain the site of the modification. ModiFinder synthesizes this information together and scores the likelihood for each atom in the known molecule to be the modification site. We demonstrate in this manuscript how ModiFinder can effectively localize modifications which extends the capabilities of MS/MS analog searching and molecular networking to accelerate the discovery of novel compounds.

Microbial metabolic exchange--the chemotype-to-phenotype link.

The function of microbial interactions is to enable microorganisms to survive by establishing a homeostasis between microbial neighbors and local environments. A microorganism can respond to environmental stimuli using metabolic exchange-the transfer of molecular factors, including small molecules and proteins. Microbial interactions not only influence the survival of the microbes but also have roles in morphological and developmental processes of the organisms themselves and their neighbors. This, in turn, shapes the entire habitat of these organisms. Here we highlight our current understanding of metabolic exchange as well as the emergence of new technologies that are allowing us to eavesdrop on microbial conversations comprising dozens to hundreds of secreted metabolites that control the behavior, survival and differentiation of members of the community. The goal of the rapidly advancing field studying multifactorial metabolic exchange is to devise a microbial 'Rosetta stone' in order to understand the language by which microbial interactions are negotiated and, ultimately, to control the outcome of these conversations.

MBRA-2: a Modified Chemostat System to Culture Biofilms.

Culture-dependent approaches for investigating microbial ecology aim to model the nutrient content of specific environments by simplifying the system for high-resolution molecular analysis. These in vitro systems are enticing due to their increased throughput compared to animal models, flexibility in modulating nutrient content and community composition, scaling of culture volume to isolate biological molecules, and control of environmental parameters, such as temperature, humidity, and nutrient flow. However, different devices are used to investigate homogenous, planktonic microbial communities and heterogeneous biofilms. Here, we present the minibioreactor array 2 (MBRA-2) with media rails, a benchtop multireactor system derived from the MBRA system that enables researchers to use the same system to grow planktonic and biofilm cultures. We simplified flow through the system and reduced contamination, leakage, and time required for array assembly by designing and implementing a reusable media rail to replace the branched tubing traditionally used to convey media through chemostat arrays. Additionally, we altered the structure of the six-bioreactor strip to incorporate a removable lid to provide easy access to the bioreactor wells, enabling biofilm recovery and thorough cleaning for reuse. Using Pseudomonas aeruginosa, a model biofilm-producing organism, we show that the technical improvements of the MBRA-2 for biofilms growth does not disrupt the function of the bioreactor array. IMPORTANCE The MBRA-2 with media rails provides an accessible system for investigators to culture heterogenous, suspended biofilms under constant flow.

Pyochelin biotransformation by Staphylococcus aureus shapes bacterial competition with Pseudomonas aeruginosa in polymicrobial infections.

Pseudomonas aeruginosa and Staphylococcus aureus are among the most frequently isolated bacterial species from polymicrobial infections of patients with cystic fibrosis and chronic wounds. We apply mass spectrometry guided interaction studies to determine how chemical interaction shapes the fitness and community structure during co-infection of these two pathogens. We demonstrate that S. aureus is equipped with an elegant mechanism to inactivate pyochelin via the yet uncharacterized methyltransferase Spm (staphylococcal pyochelin methyltransferase). Methylation of pyochelin abolishes the siderophore activity of pyochelin and significantly lowers pyochelin-mediated intracellular reactive oxygen species (ROS) production in S. aureus. In a murine wound co-infection model, an S. aureus mutant unable to methylate pyochelin shows significantly lower fitness compared with its parental strain. Thus, Spm-mediated pyochelin methylation is a mechanism to increase S. aureus survival during in vivo competition with P. aeruginosa.

Primer on agar-based microbial imaging mass spectrometry.

Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) imaging mass spectrometry (IMS) applied directly to microbes on agar-based medium captures global information about microbial molecules, allowing for direct correlation of chemotypes to phenotypes. This tool was developed to investigate metabolic exchange factors of intraspecies, interspecies, and polymicrobial interactions. Based on our experience of the thousands of images we have generated in the laboratory, we present five steps of microbial IMS: culturing, matrix application, dehydration of the sample, data acquisition, and data analysis/interpretation. We also address the common challenges encountered during sample preparation, matrix selection and application, and sample adherence to the MALDI target plate. With the practical guidelines described herein, microbial IMS use can be extended to bio-based agricultural, biofuel, diagnostic, and therapeutic discovery applications.

Bacillus cereus phosphopentomutase is an alkaline phosphatase family member that exhibits an altered entry point into the catalytic cycle.

Bacterial phosphopentomutases (PPMs) are alkaline phosphatase superfamily members that interconvert α-D-ribose 5-phosphate (ribose 5-phosphate) and α-D-ribose 1-phosphate (ribose 1-phosphate). We investigated the reaction mechanism of Bacillus cereus PPM using a combination of structural and biochemical studies. Four high resolution crystal structures of B. cereus PPM revealed the active site architecture, identified binding sites for the substrate ribose 5-phosphate and the activator α-D-glucose 1,6-bisphosphate (glucose 1,6-bisphosphate), and demonstrated that glucose 1,6-bisphosphate increased phosphorylation of the active site residue Thr-85. The phosphorylation of Thr-85 was confirmed by Western and mass spectroscopic analyses. Biochemical assays identified Mn(2+)-dependent enzyme turnover and demonstrated that glucose 1,6-bisphosphate treatment increases enzyme activity. These results suggest that protein phosphorylation activates the enzyme, which supports an intermolecular transferase mechanism. We confirmed intermolecular phosphoryl transfer using an isotope relay assay in which PPM reactions containing mixtures of ribose 5-[(18)O(3)]phosphate and [U-(13)C(5)]ribose 5-phosphate were analyzed by mass spectrometry. This intermolecular phosphoryl transfer is seemingly counter to what is anticipated from phosphomutases employing a general alkaline phosphatase reaction mechanism, which are reported to catalyze intramolecular phosphoryl transfer. However, the two mechanisms may be reconciled if substrate encounters the enzyme at a different point in the catalytic cycle.

Spray-Based Application of Matrix to Agar-Based Microbial Samples for Reproducible Sample Adherence in MALDI MSI.

Microbial mass spectrometry imaging (MSI) is a powerful tool used to generate biological hypotheses about the roles of metabolites in microbial competition based upon their two-dimensional spatial distribution. The most commonly used ionization method for microbial MSI is matrix-assisted laser desorption ionization (MALDI). However, medium components and microbial metabolites influence the adhesion of agar samples to the MALDI target, limiting the applicability of MALDI MSI to microbes grown on specific media. Here, we describe a three-step process using a robotic sprayer for a matrix application that improves the adherence of agar samples to the MALDI target, enabling the use of different media for microbial growth and an MSI analysis of larger sample surface areas.

Model Systems to Study the Chronic, Polymicrobial Infections in Cystic Fibrosis: Current Approaches and Exploring Future Directions.

A recent workshop titled "Developing Models to Study Polymicrobial Infections," sponsored by the Dartmouth Cystic Fibrosis Center (DartCF), explored the development of new models to study the polymicrobial infections associated with the airways of persons with cystic fibrosis (CF). The workshop gathered 35+ investigators over two virtual sessions. Here, we present the findings of this workshop, summarize some of the challenges involved with developing such models, and suggest three frameworks to tackle this complex problem. The frameworks proposed here, we believe, could be generally useful in developing new model systems for other infectious diseases. Developing and validating new approaches to study the complex polymicrobial communities in the CF airway could open windows to new therapeutics to treat these recalcitrant infections, as well as uncovering organizing principles applicable to chronic polymicrobial infections more generally.

Feature-Based Molecular Networking for Metabolite Annotation.

The Global Natural Product Social Molecular Networking (GNPS) platform leverages tandem mass spectrometry (MS/MS) data for annotation of compounds. Molecular networks aid in the visualization of the chemical space within a metabolomics experiment. Recently, molecular networking has been combined with feature detection methods to yield Feature-Based Molecular Networking (FBMN). FBMN allows for the discrimination of isomers within the molecular network, incorporation of quantitative information generated by the feature detection tools into visualization of the molecular network, and compatibility with forthcoming in silico annotation tools. This chapter provides step-by-step methods for generating a molecular network to annotate microbial natural products using the Global Natural Product Social Molecular Networking (GNPS) Feature-Based Molecular Networking (FBMN) workflow.