Facilitating Imaging Mass Spectrometry of Microbial Specialized Metabolites with METASPACE.
Ontology highlight
ABSTRACT:
SUBMITTER: Nguyen DD
PROVIDER: S-EPMC8401310 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Lichens are slow-growing organisms supposed to synthetize specialized metabolites to protect themselves against diverse grazers. As predicted by the optimal defense theory (ODT), lichens are expected to invest specialized metabolites in higher levels in reproductive tissues compared to thallus. We investigated whether Laser Desorption Ionization coupled to Mass Spectrometry Imaging (LDI-MSI) could be a relevant tool for chemical ecology issues such as ODT. In the present study, this method was applied to cross-sections of thalli and reproductive tissues of the lichen Pseudocyphellaria crocata. Spatial mapping revealed phenolic families of metabolites. A quantification of these metabolites was carried out in addition to spatial imaging. By this method, accumulation of specialized metabolites was observed in both reproductive parts (apothecia and soralia) of P. crocata, but their nature depended on the lichen organs: apothecia concentrated norstictic acid, tenuiorin, and pulvinic acid derivatives, whereas soralia mainly contained tenuiorin and pulvinic acid. Stictic acid, tenuiorin and calycin, tested in no-choices feeding experiments, were deterrent for N. hookeri while entire thalli were consumed by the snail. To improve better knowledge in relationships between grazed and grazing organisms, LDI-MSI appears to be a complementary tool in ecological studies.
| S-EPMC7020473 | biostudies-literature
Project description: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.
| S-EPMC3427086 | biostudies-other
Project description: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.
| S-EPMC3486372 | biostudies-literature
Project description:Glandular secreting trichomes of cultivated tomato (Solanum lycopersicum) and close relatives produce a variety of structurally diverse volatile and non-volatile specialized ('secondary') metabolites, including terpenes, flavonoids and acyl sugars. A genetic screen is described here to profile leaf trichome and surface metabolite extracts of nearly isogenic chromosomal substitution lines covering the tomato genome. These lines contain specific regions of the Solanum pennellii LA0716 genome in an otherwise 'wild-type' M82 tomato genetic background. Regions that have an impact on the total amount of extractable mono- and sesquiterpenes (IL2-2) or only sesquiterpenes (IL10-3) or specifically influence accumulation of the monoterpene alpha-thujene (IL1-3 and IL1-4) were identified using GC-MS. A rapid LC-TOF-MS method was developed and used to identify changes in non-volatile metabolites through non-targeted analysis. Metabolite profiles generated using this approach led to the discovery of introgression lines producing different acyl chain substitutions on acyl sugar metabolites (IL1-3/1-4 and IL8-1/8-1-1), as well as two regions that influence the quantity of acyl sugars (IL5-3 and IL11-3). Chromosomal region 1-1/1-1-3 was found to influence the types of glycoalkaloids that are detected in leaf surface extracts. These results show that direct chemical screening is a powerful way to characterize genetic diversity in trichome specialized metabolism.
| S-EPMC2881305 | biostudies-literature
Project description:Retinoblastoma (RB) is an intraocular childhood tumor which, if left untreated, leads to blindness and mortality. Nucleolin (NCL) protein which is differentially expressed on the tumor cell surface, binds ligands and regulates carcinogenesis and angiogenesis. We found that NCL is over expressed in RB tumor tissues and cell lines compared to normal retina. We studied the effect of nucleolin-aptamer (NCL-APT) to reduce proliferation in RB tumor cells. Aptamer treatment on the RB cell lines (Y79 and WERI-Rb1) led to significant inhibition of cell proliferation. Locked nucleic acid (LNA) modified NCL-APT administered subcutaneously (s.c.) near tumor or intraperitoneally (i.p.) in Y79 xenografted nude mice resulted in 26 and 65% of tumor growth inhibition, respectively. Downregulation of inhibitor of apoptosis proteins, tumor miRNA-18a, altered serum cytokines, and serum miRNA-18a levels were observed upon NCL-APT treatment. Desorption electrospray ionization mass spectrometry (DESI MS)-based imaging of cell lines and tumor tissues revealed changes in phosphatidylcholines levels upon treatment. Thus, our study provides proof of concept illustrating NCL-APT-based targeted therapeutic strategy and use of DESI MS-based lipid imaging in monitoring therapeutic responses in RB.
2016-11-15 | GSE89818 | GEO
Project description:Ambient ionization methods for MS enable direct, high-throughput measurements of samples in the open air. Here, we report on one such method, desorption electrospray ionization (DESI), which is coupled to a linear ion trap mass spectrometer and used to record the spatial intensity distribution of a drug directly from histological sections of brain, lung, kidney, and testis without prior chemical treatment. DESI imaging provided identification and distribution of clozapine after an oral dose of 50 mg/kg by: i) measuring the abundance of the intact ion at m/z 327.1, and ii) monitoring the dissociation of the protonated drug compound at m/z 327.1 to its dominant product ion at m/z 270.1. In lung tissues, DESI imaging was performed in the full-scan mode over an m/z range of 200-1100, providing an opportunity for relative quantitation by using an endogenous lipid to normalize the signal response of clozapine. The presence of clozapine was detected in all tissue types, whereas the presence of the N-desmethyl metabolite was detected only in the lung sections. Quantitation of clozapine from the brain, lung, kidney, and testis, by using LC-MS/MS, revealed concentrations ranging from 0.05 microg/g (brain) to a high of 10.6 microg/g (lung). Comparisons of the results recorded by DESI with those by LC-MS/MS show good agreement and are favorable for the use of DESI imaging in drug and metabolite detection directly from biological tissues.
| S-EPMC2587601 | biostudies-literature
Project description:Mass spectrometry imaging (MSI) provides insight into the molecular distribution of a broad range of compounds and, therefore, is frequently applied in the pharmaceutical industry. Pharmacokinetic and toxicological studies deploy MSI to localize potential drugs and their metabolites in biological tissues but currently require other analytical tools to quantify these pharmaceutical compounds in the same tissues. Quantitative mass spectrometry imaging (Q-MSI) is a field with challenges due to the high biological variability in samples combined with the limited sample cleanup and separation strategies available prior to MSI. In consequence, more selectivity in MSI instruments is required. This can be provided by multiple reaction monitoring (MRM) which uses specific precursor ion-product ion transitions. This targeted approach is in particular suitable for pharmaceutical compounds because their molecular identity is known prior to analysis. In this work, we compared different analytical platforms to assess the performance of MRM detection compared to other MS instruments/MS modes used in a Q-MSI workflow for two drug candidates (A and B). Limit of detection (LOD), linearity, and precision and accuracy of high and low quality control (QC) samples were compared between MS instruments/modes. MRM mode on a triple quadrupole mass spectrometer (QqQ) provided the best overall performance with the following results for compounds A and B: LOD 35.5 and 2.5 μg/g tissue, R2 0.97 and 0.98 linearity, relative standard deviation QC <13.6%, and 97-112% accuracy. Other MS modes resulted in LOD 6.7-569.4 and 2.6-119.1 μg/g tissue, R2 0.86-0.98 and 0.86-0.98 linearity, relative standard deviation QC < 19.4 and < 37.5%, and 70-356% and 64-398% accuracy for drug candidates A and B, respectively. In addition, we propose an optimized 3D printed mimetic tissue model to increase the overall analytical throughput of our approach for large animal studies. The MRM imaging platform was applied as proof-of-principle for quantitative detection of drug candidates A and B in four dog livers and compared to LC-MS. The Q-MSI concentrations differed <3.5 times with the concentrations observed by LC-MS. Our presented MRM-based Q-MSI approach provides a more selective and high-throughput analytical platform due to MRM specificity combined with an optimized 3D printed mimetic tissue model.
| S-EPMC8007509 | biostudies-literature
Project description:Studying microbial interactions by MALDI mass spectrometry imaging (MSI) directly from growing media is a difficult task if high sensitivity is demanded. We present a quick and robust sample preparation strategy for growing fungi (Trichoderma atroviride, Rhizoctonia solani) on glass slides to establish a miniaturized confrontation assay. By this we were able to visualize metabolite distributions by MALDI MSI after matrix deposition with a home-built sublimation device and thorough recrystallization. We present for the first time MALDI MSI data for secondary metabolite release during active mycoparasitism.
| S-EPMC4982067 | biostudies-literature
Project description:Pseudomonas aeruginosa is a ubiquitous environmental bacterium that causes chronic infections of burn wounds and in the lungs of cystic fibrosis (CF) patients. Vital to its infection is a myriad of specialized metabolites that serve a variety of biological roles including quorum sensing, metal chelation and inhibition of other competing bacteria. This study employed newly available algorithms for searching individual tandem mass (MS/MS) spectra against the publicly available Global Natural Product Social Molecular Networking (GNPS) database to identify the chemical diversity of these compounds and their presence in environmental, laboratory and clinical samples. For initial characterization, the metabolomes of eight clinical isolates of P. aeruginosa were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and uploaded to GNPS for spectral searching. Quinolones, rhamnolipids, phenazines and siderophores were identified and characterized; including the discovery of modified forms of the iron chelator pyochelin. Quinolones were highly diverse with the three base forms Pseudomonas quinolone signal 2-heptyl-3-hydroxy-4(1H)-quinolone (PQS), 4-heptyl-4(1H)-quinolone (HHQ) and 2-heptyl-4-quinolone-N-oxide (HQNO) having extensive variation in the length of their acyl chain from as small as 3 carbons to as large as 17. Rhamnolipids were limited to either one or two sugars with a limited set of fatty acyl chains, but the base lipid form without the rhamnose was also detected. These specialized metabolites were identified from diverse sources including ant-fungal mutualist dens, soil, plants, human teeth, feces, various lung mucus samples and cultured laboratory isolates. Their prevalence in fecal samples was particularly notable as P. aeruginosa is not known as a common colonizer of the human gut. The chemical diversity of the compounds identified, particularly the quinolones, demonstrates a broad spectrum of chemical properties within these the metabolite groups with likely significant impacts on their biological functions. Mining public data with GNPS enables a new approach to characterize the chemical diversity of biological organisms, which includes enabling the discovery of new chemistry from pathogenic bacteria.
| S-EPMC7694397 | biostudies-literature
Project description:High mass resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a suitable method for biomarker detection for several tumor entities. Renal cell carcinoma (RCC) is the seventh most common cancer type and accounts for more than 80% of all renal tumors. Prognostic biomarkers for RCC are still missing. Therefore, we analyzed a large, multicenter cohort including the three most common RCC subtypes (clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC)) by MALDI for prognostic biomarker detection. MALDI-Fourier-transform ion cyclotron resonance (FT-ICR)-MSI analysis was performed for renal carcinoma tissue sections from 782 patients. SPACiAL pipeline was integrated for automated co-registration of histological and molecular features. Kaplan-Meier analyses with overall survival as endpoint were executed to determine the metabolic features associated with clinical outcome. We detected several pathways and metabolites with prognostic power for RCC in general and also for different RCC subtypes.
| S-EPMC8996951 | biostudies-literature