Hari Krishnan R, SRM Institute of Science and Technology
Ion Identity Molecular Networking (IIMN) connects and collapses ion species of the same molecule. Ionization by mass spectrometry causes molecules to form multiple ion species expressing different fragmentation patterns, this causes the formation of redundant and disconnected sub-networks of the same compound species. IIMN is a newly devised technique designed to use chromatographic peak analysis to analyze molecular networks to connect different ion species of the same molecules. This method is used to improve molecular network connectivity, enhance annotation within molecular networks, find novel ion-ligand complexes, and generation of spectral libraries.
The IIMN starts from feature grouping, followed by feature shape correlation, and identification of ion species using a variety of open-source software tools, such as MZmine, XCMS, and MS-DIAL which identifies various ion adducts using different algorithms.
What is GNPS?
Global Natural Products Social molecular networking (GNPS) is an open-access web-based organization for sharing fragmentation mass spectrometry data, starting from raw data to processed data. GNPS is used for molecular networking where non-targeted mass spectrometry data are analyzed. Molecular networking comprises a spectral network formed by the fragmentation pattern of various structures. Molecular networking using GNPS can help in identifying new analogs of known molecules by mapping the chemical space of molecules.
Tools available for Grouping and Annotation of Ion species in LC-MS
- Tools like CAMERA and CliqueMS add pairwise correlation and allows for the annotation of a single spectrum
- RAMClust simultaneously processes LC-MS data with a fragmentation spectrum through Data-independent Acquisition (DIA). DIA predicts the molecular structure by selecting the ions within a specific m/z range and fragmenting them and analyzing them in the second stage of MS.
- MZmine, MS-DIAL, and XCMS are open-source MS processing tools
- MS-FLO processes exported feature lists from MZmine17, MS-DIAL18, and XCMS.
Steps to Create Ion Identity Molecular Networking (IIMN)
- Convert the data files to open-source format (mzML)
- Import the data into any of the open-source tools (MZmine/MS-DIAL/XCMS)
- Data processing and creating a feature list
- Performing MS-based annotation and feature grouping
- Export feature list as 1. Feature quantification table in “.csv” format, 2. Summary format (.mgf) and supplementary edges files like IIN files, .csv.
- Grouping of samples by creating a metadata file. This is optional
- Uploading all files to GNPS and initiating feature-based MN.
- Visualizing the results in analysis software like Cytoscape.
- Download Cytoscape data to get the IIMN network and its collapsed version.
Some applications of Ion Identity Molecular Networking (IIMN)
- The IIMN methodology performs annotation and connects related ion species in feature-based molecular networks in GNPS. The two-layered feature connectivity network generated by IIMN helps in better interpretation of MS data.
- IIMN can also be used to generate spectral libraries by processing datasets and spectral annotations to create entries of connected ion species. It is found to increase the annotation density of molecular networks (MN) by connecting compound annotations from a variety of compound classes and analytical platforms.
- IIMN can identify ion adducts that can reveal biologically significant novel ionophores.
Also read: Influence of Tau proteins on Parkinson’s disease
Source:
Schmid, R., Petras, D., Nothias, LF. et al. Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment. Nat Commun 12, 3832 (2021). https://doi.org/10.1038/s41467-021-23953-9
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About the Author:
Hari Krishnan is a research enthusiast in Cell biology and Cell signalling. He is currently a final year Biotechnology Engineering student. He is a prolific Scientific writer with vast knowledge in diverse backgrounds of biotechnology. He is constantly focused on improving his knowledge and laboratory skills through various internships. A Chennai native, Hari is a spicy food lover and passionate about music and sports.
Publications-
- Krishnan, H. (2021). COMPARISON OF THE DRUG ENTRAPMENT EFFICIENCY OF ALMOND GUM (Badam Pisin) TO SPAN-60 NIOSOMES BY FOLIN- CIOCALTEU ASSAY. BioRxiv. https://doi.org/10.1101/2021.04.03.438312
- Krishnan, H. (2020). TELOMERASE TARGETING IN CANCER. International Research Journal of Modernization in Engineering Technology and Science. https://doi.org/10.3390/cancers12082260
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