Mining Public Mass Spectrometry Data to Characterize the Diversity and Ubiquity of P. aeruginosa Specialized Metabolites

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.

Fast mass spectrometry search and clustering of untargeted metabolomics data

The throughput of mass spectrometers and the amount of publicly available metabolomics data are growing rapidly, but analysis tools such as molecular networking and Mass Spectrometry Search Tool do not scale to searching and clustering billions of mass spectral data in metabolomics repositories. To address this limitation, we designed MASST+ and Networking+, which can process datasets that are up to three orders of magnitude larger than those processed by state-of-the-art tools.

Biosynthetic gene cluster signature profiles of pathogenic Gram-negative bacteria isolated from Egyptian clinical settings

Biosynthetic gene clusters (BGCs) are a subset of consecutive genes present within a variety of organisms to produce specialized metabolites (SMs). These SMs are becoming a cornerstone to produce multiple medications including antibacterial and anticancer agents. Natural products (NPs) also play a pivotal role in enhancing the virulence of ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.), which represent a global health threat. We aimed to sequence and computationally analyze the BGCs present in 66 strains pertaining to three different ESKAPE pathogenic species: 21 A. baumannii, 28 K. pneumoniae, and 17 P. aeruginosa strains recovered from clinical settings in Egypt. DNA was extracted using QIAamp DNA Mini kit and Illumina NextSeq 550 was used for whole-genome sequencing. The sequences were quality-filtered by fastp and assembled by Unicycler. BGCs were detected by antiSMASH, BAGEL, GECCO, and PRISM, and aligned using Clinker. The highest abundance of BGCs was detected in P. aeruginosa (590), then K. pneumoniae (146) and the least in A. baumannii strains (133). P. aeruginosa isolates shared mostly the non-ribosomal peptide synthase (NRPS) type, K. pneumoniae isolates shared the ribosomally synthesized and post-translationally modified peptide-like (RiPP-like) type, while A. baumannii isolates shared the siderophore type. Most of the isolates harbored non-ribosomal peptide (NRP) BGCs with few K. pneumoniae isolates encoding polyketide BGCs. Sactipeptides and bottromycin BGCs were the most frequently detected RiPP clusters. We hypothesize that each species' BGC signature confers its virulence. Future experiments will link the detected clusters with their species and determine whether the encoded SMs are produced and cause their virulence. IMPORTANCE Our study analyzes the biosynthetic gene clusters (BGCs) present in 66 assemblies from clinical ESKAPE pathogen isolates pertaining to Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa strains. We report their sequencing and assembly followed by the analysis of their BGCs using several bioinformatics tools. We then focused on the most abundant BGC type in each species and we discussed their potential roles in the virulence of each species. This study is pivotal to further build on its experimental work that deciphers the role in virulence, possible antibacterial effects, and characterization of the encoded specialized metabolites (SMs). The study highlights the importance of studying the "harmful" BGCs and understanding the pathogenicity and virulence of those species, as well as possible benefits if the SMs were used as antibacterial agents. This could be the first study of its kind from Egypt and would shed light on BGCs from ESKAPE pathogens from Egypt.

Metabolomic Analysis of Polymicrobial Wound Infections and an Associated Adhesive Bandage

Concerns about ion suppression, spectral contamination, or interference have led to avoidance of polymers in mass spectrometry (MS)-based metabolomics. This avoidance, however, has left many biochemical fields underexplored, including wounds, which are often treated with adhesive bandages. Here, we found that despite previous concerns, the addition of an adhesive bandage can still result in biologically informative MS data. Initially, a test LC-MS analysis was performed on a mixture of known chemical standards and a polymer bandage extract. Results demonstrated successful removal of many polymer-associated features through a data processing step. Furthermore, the bandage presence did not interfere with metabolite annotation. This method was then implemented in the context of murine surgical wound infections covered with an adhesive bandage and inoculated with Staphylococcus aureus, Pseudomonas aeruginosa, or a 1:1 mix of these pathogens. Metabolites were extracted and analyzed by LC-MS. On the bandage side, we observed a greater impact of infection on the metabolome. Distance analysis showed significant differences between all conditions and demonstrated that coinfected samples were more similar to S. aureus-infected samples compared to P. aeruginosa-infected samples. We also found that coinfection was not merely a summative effect of each monoinfection. Overall, these results represent an expansion of LC-MS-based metabolomics to a novel, previously under-investigated class of samples, leading to actionable biological information.

Construction of a Bacterial Lipidomics Analytical Platform: Pilot Validation with Bovine Paratuberculosis Serum

Lipidomics analyses of bacteria offer the potential to detect and monitor infections in a host since many bacterial lipids are not present in mammals. To evaluate this omics approach, we first built a database of bacterial lipids for representative Gram-positive and Gram-negative bacteria. Our lipidomics analysis of the reference bacteria involved high-resolution mass spectrometry and electrospray ionization with less than a 1.0 ppm mass error. The lipidomics profiles of bacterial cultures clearly distinguished between Gram-positive and Gram-negative bacteria. In the case of bovine paratuberculosis (PTB) serum, we monitored two unique bacterial lipids that we also monitored in Mycobacterium avian subspecies PTB. These were PDIM-B C82, a phthiodiolone dimycocerosate, and the trehalose monomycolate hTMM 28:1, constituents of the bacterial cell envelope in mycolic-containing bacteria. The next step will be to determine if lipidomics can detect subclinical PTB infections which can last 2-to-4 years in bovine PTB. Our data further suggest that it will be worthwhile to continue building our bacterial lipidomics database and investigate the further utility of this approach in other infections of veterinary and human clinical interest.

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.

Advancements in capturing and mining mass spectrometry data are transforming natural products research

Covering: 2016 up to 2021Mass spectrometry (MS) is an essential technology in natural products research with MS fragmentation (MS/MS) approaches becoming a key tool. Recent advancements in MS yield dense metabolomics datasets which have been, conventionally, used by individual labs for individual projects; however, a shift is brewing. The movement towards open MS data (and other structural characterization data) and accessible data mining tools is emerging in natural products research. Over the past 5 years, this movement has rapidly expanded and evolved with no slowdown in sight; the capabilities of today vastly exceed those of 5 years ago. Herein, we address the analysis of individual datasets, a situation we are calling the '2021 status quo', and the emergent framework to systematically capture sample information (metadata) and perform repository-scale analyses. We evaluate public data deposition, discuss the challenges of working in the repository scale, highlight the challenges of metadata capture and provide illustrative examples of the power of utilizing repository data and the tools that enable it. We conclude that the advancements in MS data collection must be met with advancements in how we utilize data; therefore, we argue that open data and data mining is the next evolution in obtaining the maximum potential in natural products research.

Metabolomic profiling of Burkholderia cenocepacia in synthetic cystic fibrosis sputum medium reveals nutrient environment-specific production of virulence factors

Infections by Burkholderia cenocepacia lead to life-threatening disease in immunocompromised individuals, including those living with cystic fibrosis (CF). While genetic variation in various B. cenocepacia strains has been reported, it remains unclear how the chemical environment of CF lung influences the production of small molecule virulence factors by these strains. Here we compare metabolomes of three clinical B. cenocepacia strains in synthetic CF sputum medium (SCFM2) and in a routine laboratory medium (LB), in the presence and absence of the antibiotic trimethoprim. Using a mass spectrometry-based untargeted metabolomics approach, we identify several compound classes which are differentially produced in SCFM2 compared to LB media, including siderophores, antimicrobials, quorum sensing signals, and various lipids. Furthermore, we describe that specific metabolites are induced in the presence of the antibiotic trimethoprim only in SCFM2 when compared to LB. Herein, C13-acyl-homoserine lactone, a quorum sensing signal previously not known to be produced by B. cenocepacia as well as pyochelin-type siderophores were exclusively detected during growth in SCFM2 in the presence of trimethoprim. The comparative metabolomics approach described in this study provides insight into environment-dependent production of secondary metabolites by B. cenocepacia strains and suggests future work which could identify personalized strain-specific regulatory mechanisms involved in production of secondary metabolites. Investigations into whether antibiotics with different mechanisms of action induce similar metabolic alterations will inform development of combination treatments aimed at effective clearance of Burkholderia spp. pathogens.

Metabolic Footprints of Burkholderia Sensu Lato Rhizosphere Bacteria Active against Maize Fusarium Pathogens

Consistent with their reported abundance in soils, several Burkholderia sensu lato strains were isolated from the rhizosphere of maize plants cultivated at different sites in central México. Comparative analysis of their 16S rRNA gene sequences permitted their separation into three distinctive clades, which were further subdivided into six other clusters by their close resemblance to (1) Trinickia dinghuensis; (2) Paraburkholderia kirstenboschensis, P. graminis, P. dilworthii and P. rhynchosiae; (3) B. gladioli; (4) B. arboris; (5) B. contaminans, or (6) B. metallica representative species. Direct confrontation assays revealed that these strains inhibited the growth of pathogenic Fusarium oxysporum f. sp. radicis-lycopersici, and F. verticillioides within a roughly 3-55% inhibition range. The use of a DIESI-based non-targeted mass spectroscopy experimental strategy further indicated that this method is an option for rapid determination of the pathogen inhibitory capacity of Burkholderia sensu lato strains based solely on the analysis of their exometabolome. Furthermore, it showed that the highest anti-fungal activity observed in B. contaminans and B. arboris was associated with a distinctive abundance of certain m/z ions, some of which were identified as components of the ornbactin and pyochelin siderophores. These results highlight the chemical diversity of Burkholderia sensu lato bacteria and suggest that their capacity to inhibit the Fusarium-related infection of maize in suppressive soils is associated with siderophore synthesis.

Characterization of Pseudomonas aeruginosa Quorum Sensing Inhibitors from the Endophyte Lasiodiplodia venezuelensis and Evaluation of Their Antivirulence Effects by Metabolomics

The opportunistic pathogen Pseudomonas aeruginosa is one of the "critical priority pathogens" due to its multidrug resistance to a wide range of antibiotics. Its ability to invade and damage host tissues is due to the use of quorum sensing (QS) to collectively produce a plethora of virulence factors. Inhibition of QS is an attractive strategy for new antimicrobial agents because it disrupts the initial events of infection without killing the pathogen. Highly diverse microorganisms as endophytes represent an under-explored source of bioactive natural products, offering opportunities for the discovery of novel QS inhibitors (QSI). In the present work, the objective was to explore selective QSIs within a unique collection of fungal endophytes isolated from the tropical palm Astrocaryum sciophilum. The fungi were cultured, extracted, and screened for their antibacterial and specific anti-QS activities against P. aeruginosa. The endophytic strain Lasiodiplodia venezuelensis was prioritized for scaled-up fractionation for its selective activity, leading to the isolation of eight compounds in a single step. Among them, two pyran-derivatives were found to be responsible for the QSI activity, with an effect on some QS-regulated virulence factors. Additional non-targeted metabolomic studies on P. aeruginosa documented their effects on the production of various virulence-related metabolites.

The bacterial quorum sensing molecule, 2-heptyl-3-hydroxy-4-quinolone (PQS), inhibits signal transduction mechanisms in brain tissue and is behaviorally active in mice

Interkingdom communication between bacteria and host organisms is one of the most interesting research topics in biology. Quorum sensing molecules produced by Gram-negative bacteria, such as acylated homoserine lactones and quinolones, have been shown to interact with host cell receptors, stimulating innate immunity and bacterial clearance. To our knowledge, there is no evidence that these molecules influence CNS function. Here, we have found that low micromolar concentrations of the Pseudomonas aeruginosa quorum sensing autoinducer, 2-heptyl-3-hydroxy-4-quinolone (PQS), inhibited polyphosphoinositide hydrolysis in mouse brain slices, whereas four selected acylated homoserine lactones were inactive. PQS also inhibited forskolin-stimulated cAMP formation in brain slices. We therefore focused on PQS in our study. Biochemical effects of PQS were not mediated by the bitter taste receptors, T2R4 and T2R16. Interestingly, submicromolar concentrations of PQS could be detected in the serum and brain tissue of adult mice under normal conditions. Levels increased in five selected brain regions after single i.p. injection of PQS (10 mg/kg), peaked after 15 min, and returned back to normal between 1 and 4 h. Systemically administered PQS reduced spontaneous locomotor activity, increased the immobility time in the forced swim test, and largely attenuated motor response to the psychostimulant, methamphetamine. These findings offer the first demonstration that a quorum sensing molecule specifically produced by Pseudomonas aeruginosa is centrally active and influences cell signaling and behavior. Quorum sensing autoinducers might represent new interkingdom signaling molecules between ecological communities of commensal, symbiotic, and pathogenic microorganisms and the host CNS.