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.

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.

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.

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.

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.

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.

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.

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.

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.

Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads.

As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing.

Microbiome and metabolome data integration provides insight into health and disease.

For much of our history, the most basic information about the microbial world has evaded characterization. Next-generation sequencing has led to a rapid increase in understanding of the structure and function of host-associated microbial communities in diverse diseases ranging from obesity to autism. Through experimental systems such as gnotobiotic mice only colonized with known microbes, a causal relationship between microbial communities and disease phenotypes has been supported. Now, microbiome research must move beyond correlations and general demonstration of causality to develop mechanistic understandings of microbial influence, including through their metabolic activities. Similar to the microbiome field, advances in technologies for cataloguing small molecules have broadened our understanding of the metabolites that populate our bodies. Integration of microbial and metabolomics data paired with experimental validation has promise for identifying microbial influence on host physiology through production, modification, or degradation of bioactive metabolites. Realization of microbial metabolic activities that affect health is hampered by gaps in our understanding of (1) biological properties of microbes and metabolites, (2) which microbial enzymes/pathways produce which metabolites, and (3) the effects of metabolites on hosts. Capitalizing on known mechanistic relationships and filling gaps in our understanding has the potential to enable translational microbiome research across disease contexts.

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.

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.

Microbial, host and xenobiotic diversity in the cystic fibrosis sputum metabolome.

Cystic fibrosis (CF) lungs are filled with thick mucus that obstructs airways and facilitates chronic infections. Pseudomonas aeruginosa is a significant pathogen of this disease that produces a variety of toxic small molecules. We used molecular networking-based metabolomics to investigate the chemistry of CF sputa and assess how the microbial molecules detected reflect the microbiome and clinical culture history of the patients. Metabolites detected included xenobiotics, P. aeruginosa specialized metabolites and host sphingolipids. The clinical culture and microbiome profiles did not correspond to the detection of P. aeruginosa metabolites in the same samples. The P. aeruginosa molecules that were detected in sputum did not match those from laboratory cultures. The pseudomonas quinolone signal (PQS) was readily detectable from cultured strains, but absent from sputum, even when its precursor molecules were present. The lack of PQS production in vivo is potentially due to the chemical nature of the CF lung environment, indicating that culture-based studies of this pathogen may not explain its behavior in the lung. The most differentially abundant molecules between CF and non-CF sputum were sphingolipids, including sphingomyelins, ceramides and lactosylceramide. As these highly abundant molecules contain the inflammatory mediator ceramide, they may have a significant role in CF hyperinflammation. This study demonstrates that the chemical makeup of CF sputum is a complex milieu of microbial, host and xenobiotic molecules. Detection of a bacterium by clinical culturing and 16S rRNA gene profiling do not necessarily reflect the active production of metabolites from that bacterium in a sputum sample.

Mass Spectrometry Analysis of Pseudomonas aeruginosa Treated with Azithromycin.

In microbiology, changes in specialized metabolite production (cell-to-cell signaling metabolites, virulence factors, and natural products) are measured using phenotypic assays. However, advances in mass spectrometry-based techniques including imaging mass spectrometry (IMS) now allow researchers to directly visualize the production of specialized metabolites from microbial colony biofilms. In this study, a combination of IMS and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to visualize the effect of the macrolide antibiotic azithromycin (AZM) on colony biofilms of Pseudomonas aeruginosa. Although previous research suggested that AZM may inhibit cell-to-cell signaling of P. aeruginosa and thereby reduce pathogenicity, we observed no clear decrease in specialized metabolite production.

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.

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.

Microbial metabolic exchange in 3D.

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.