Browse
Submit Data
Databases
API
Help

Dataset Information

8 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Streamlined Analysis of Cardiolipins in Prokaryotic and Eukaryotic Samples Using a Norharmane Matrix by MALDI-MSI.

ABSTRACT: Cardiolipins (CLs) are an important, regulated lipid class both in prokaryotic and eukaryotic cells, yet they remain largely unexplored by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) in tissues. To date, no in-depth optimization studies of label-free visualization of CLs in complex biological samples have been reported. Here we report a streamlined modification to our previously reported MALDI-MSI method for detection of endogenous CLs in prokaryotic and eukaryotic cells based on preparation with norharmane (NRM) matrix. Notably, the use of NRM matrix permitted sensitive detection (4.7 pg/mm²) of spotted CL synthetic standards. By contrast, four other MALDI matrices commonly used for lipid analysis failed to generate CL ions. Using this NRM-based method, endogenous CLs were detected from two types of complex biological samples: dried bacterial arrays and mouse tissue sections. In both cases, using NRM resulted in a better signal/noise for CL ions than the other matrices. Furthermore, inclusion of a washing step improved CL detection from tissue and this combined tissue preparation method (washing and NRM matrix) was used to profile normal mouse lung. Mouse lung yielded 26 unique CLs that were mapped and identified. Consistent with previous findings, CLs containing polyunsaturated fatty acids (PUFAs) were found in abundance in the airway and vascular features of the lung. This work represents a comprehensive investigation of detection conditions for CL using MALDI-MSI in complex biological samples that resulted in a streamlined method that enables future studies of the biological role(s) of CL in tissue.

SUBMITTER: Yang H

PROVIDER: S-EPMC8681877 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Cosmetic Analysis Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI).

Project description:A new "omic" platform-Cosmetomics-that proves to be extremely simple and effective in terms of sample preparation and readiness for data acquisition/interpretation is presented. This novel approach employing Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) for cosmetic analysis has proven to readily identify and quantify compounds of interest. It also allows full control of all the production phases, as well as of the final product, by integration of both analytical and statistical data. This work has focused on products of daily use, namely nail polish, lipsticks and eyeliners of multiple brands sold in the worldwide market.

| S-EPMC5512960 | biostudies-other

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

Project description: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.

| S-EPMC9341124 | biostudies-literature

Viral Biomarker Detection and Validation Using MALDI Mass Spectrometry Imaging (MSI).

Project description:(1) Background: MALDI imaging is a technique that still largely depends on time of flight (TOF)-based instrument such as the Bruker UltrafleXtreme. While capable of performing targeted MS/MS, these instruments are unable to perform fragmentation while imaging a tissue section necessitating the reliance of MS1 values for peptide level identifications. With this premise in mind, we have developed a hybrid bioinformatic/image-based method for the identification and validation of viral biomarkers. (2) Methods: Formalin-Fixed Paraffin-Embedded (FFPE) mouse samples were sectioned, mounted and prepared for mass spectrometry imaging using our well-established methods. Peptide identification was achieved by first extracting confident images corresponding to theoretical viral peptides. Next, those masses were used to perform a Peptide Mmass Fingerprint (PMF) searched against known viral FASTA sequences against a background mouse FASTA database. Finally, a correlational analysis was performed with imaging data to confirm pixel-by-pixel colocalization and intensity of viral peptides. (3) Results: 14 viral peptides were successfully identified with significant PMF Scores and a correlational result of >0.79 confirming the presence of the virus and distinguishing it from the background mouse proteins. (4) Conclusions: this novel approach leverages the power of mass spectrometry imaging and provides confident identifications for viral proteins without requiring MS/MS using simple MALDI Time Of Flight/Time Of Flight (TOF/TOF) instrumentation.

| S-EPMC9506211 | biostudies-literature

High-throughput MALDI-MSI metabolite analysis of plant tissue microarrays.

Project description:A novel metabolomics analysis technique, termed matrix-assisted laser desorption/ionization mass spectrometry imaging-based plant tissue microarray (MALDI-MSI-PTMA), was successfully developed for high-throughput metabolite detection and imaging from plant tissues. This technique completely overcomes the disadvantage that metabolites cannot be accessible on an intact plant tissue due to the limitations of the special structures of plant cells (e.g. epicuticular wax, cuticle and cell wall) through homogenization of plant tissues, preparation of PTMA moulds and matrix spraying of PTMA sections. Our study shows several properties of MALDI-MSI-PTMA, including no need of sample separation and enrichment, high-throughput metabolite detection and imaging (>1000 samples per day), high-stability mass spectrometry data acquisition and imaging reconstruction and high reproducibility of data. This novel technique was successfully used to quickly evaluate the effects of two plant growth regulator treatments (i.e. 6-benzylaminopurine and N-phenyl-N'-1,2,3-thiadiazol-5-ylurea) on endogenous metabolite expression in plant tissue culture specimens of Dracocephalum rupestre Hance (D. rupestre). Intra-day and inter-day evaluations indicated that the metabolite data detected on PTMA sections had good reproducibility and stability. A total of 312 metabolite ion signals in leaves tissues of D. rupestre were detected, of which 228 metabolite ion signals were identified, they were composed of 122 primary metabolites, 90 secondary metabolites and 16 identified metabolites of unknown classification. The results demonstrated the advantages of MALDI-MSI-PTMA technique for enhancing the overall detection ability of metabolites in plant tissues, indicating that MALDI-MSI-PTMA has the potential to become a powerful routine practice for high-throughput metabolite study in plant science.

| S-EPMC10651148 | biostudies-literature

Comparative analysis of prokaryotic and eukaryotic transcription factors using machine-learning techniques.

Project description:The DNA-protein interactions play vital roles in the central dogma of molecular biology. Proper interactions between DNA and protein would lead to the onset of various biological phenomena like transcription, translation, and replication. However, the mechanisms of these well-known processes vary between prokaryotic and eukaryotic organisms. The exact molecular mechanisms of these processes are unknown. Therefore, it is of interest to report the comparative estimate of the different properties of the DNA binding proteins from prokaryotic and eukaryotic organisms. We analyzed the different sequence-based features such as the frequency of amino acids and amino acid groups in the proteins of prokaryotes and eukaryotes by statistical measures. The general pattern of differences between the various DNA binding proteins for the development of a prediction system to discriminate between these proteins between prokaryotes and eukaryotes is documented.

| S-EPMC6137564 | biostudies-literature

Electrospray deposition device used to precisely control the matrix crystal to improve the performance of MALDI MSI.

Project description:MALDI MSI has been recently applied as an innovative tool for detection of molecular distribution within a specific tissue. MALDI MSI requires deposition of an organic compound, known as matrix, on the tissue of interest to assist analyte desorption and ionization, in which the matrix crystal homogeneity and size greatly influence the imaging reproducibility and spatial resolution in MALDI MSI. In this work, a homemade electrospray deposition device was developed for deposition of matrix in MALDI MSI. The device could be used to achieve 1??m homogeneous matrix crystals in MALDI MSI analysis. Moreover, it was found, for the first time, that the electrospray deposition device could be used to precisely control the matrix crystal size, and the imaging spatial resolution was increased greatly as the matrix crystals size becoming smaller. In addition, the easily-built electrospray deposition device was durable for acid, base or organic solvent, and even could be used for deposition of nanoparticles matrix, which made it unparalleled for MALDI MSI analysis. The feasibility of the electrospray deposition device was investigated by combination with MALDI FTICR MSI to analyze the distributions of lipids in mouse brain and liver cancer tissue section.

| S-EPMC5122855 | biostudies-other

Spatial Multimodal Analysis: MALDI-MSI and Spatial Transcriptomics within the same tissue section

Project description:We present a spatial omics approach that merges and expands the capabilities of independently performedin situassays on a single tissue section. Our spatial multimodal analysis combines histology, mass spectrometry imaging, and spatial transcriptomics to facilitate precise measurements of mRNA transcripts and low-molecular weight metabolites across tissue regions. We demonstrate the potential of our method using murine and human brain samples in the context of dopamine and Parkinson’s disease.

2023-05-21 | GSE232910 | GEO

On-Tissue Derivatization of Lipopolysaccharide for Detection of Lipid A Using MALDI-MSI.

Project description:We developed a method to directly detect and map the Gram-negative bacterial virulence factor lipid A derived from lipopolysaccharide (LPS) by coupling acid hydrolysis with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). As the structure of lipid A (endotoxin) determines the innate immune outcome during infection, the ability to map its location within an infected organ or animal is needed to understand localized inflammatory responses that results during host-pathogen interactions. We previously demonstrated detection of free lipid A from infected tissue; however detection of lipid A derived from intact (smooth) LPS from host-pathogen MSI studies, proved elusive. Here, we detected LPS-derived lipid A from the Gram-negative pathogens, Escherichia coli (Ec, m/z 1797) and Pseudomonas aeruginosa (Pa, m/z 1446) using on-tissue acid hydrolysis to cleave the glycosidic linkage between the polysaccharide (core and O-antigen) and lipid A moieties of LPS. Using accurate mass methods, the ion corresponding to the major Ec and Pa lipid A species (m/z 1797 and 1446, respectively) were unambiguously discriminated from complex tissue substrates. Further, we evaluated potential delocalization and signal loss of other tissue lipids and found no evidence for either, making this LPS-to-Lipid A-MSI (LLA-MSI) method, compatible with simultaneous host-pathogen lipid imaging following acid hydrolysis. This spatially sensitive technique is the first step in mapping host-influenced de novo lipid A modifications, such as those associated with antimicrobial resistance phenotypes, during Gram-negative bacterial infection and will advance our understanding of the host-pathogen interface.

| S-EPMC8717242 | biostudies-literature

MSI analysis using blood-derived MSI markers

Project description:MSI analysis using blood-derived MSI markers

| PRJEB53321 | ENA

Site-to-Site Reproducibility and Spatial Resolution in MALDI-MSI of Peptides from Formalin-Fixed Paraffin-Embedded Samples.

Project description:PurposeTo facilitate the transition of MALDI-MS Imaging (MALDI-MSI) from basic science to clinical application, it is necessary to analyze formalin-fixed paraffin-embedded (FFPE) tissues. The aim is to improve in situ tryptic digestion for MALDI-MSI of FFPE samples and determine if similar results would be reproducible if obtained from different sites.Experimental designFFPE tissues (mouse intestine, human ovarian teratoma, tissue microarray of tumor entities sampled from three different sites) are prepared for MALDI-MSI. Samples are coated with trypsin using an automated sprayer then incubated using deliquescence to maintain a stable humid environment. After digestion, samples are sprayed with CHCA using the same spraying device and analyzed with a rapifleX MALDI Tissuetyper at 50 µm spatial resolution. Data are analyzed using flexImaging, SCiLS, and R.ResultsTrypsin application and digestion are identified as sources of variation and loss of spatial resolution in the MALDI-MSI of FFPE samples. Using the described workflow, it is possible to discriminate discrete histological features in different tissues and enabled different sites to generate images of similar quality when assessed by spatial segmentation and PCA.Conclusions and clinical relevanceSpatial resolution and site-to-site reproducibility can be maintained by adhering to a standardized MALDI-MSI workflow.

| S-EPMC6590241 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data