Ion Mobility Spectrometry: Fundamental Concepts, Instrumentation, Applications, and the Road Ahead

Journal of the American Society for Mass Spectrometry, Journal Year: 2019, Volume and Issue: 30(11), P. 2185 - 2195

Published: Sept. 6, 2019

Ion mobility spectrometry (IMS) is a rapid separation technique that has experienced exponential growth as field of study. Interfacing IMS with mass (IMS-MS) provides additional analytical power complementary separations from each enable multidimensional characterization detected analytes. occur on millisecond timescale, and therefore can be readily nested into traditional GC LC/MS workflows. However, the continual development novel methods generated some level confusion regarding advantages disadvantages each. In this critical insight, we aim to clarify common misconceptions for new users in community pertaining fundamental concepts various instrumental platforms (i.e., DTIMS, TWIMS, TIMS, FAIMS, DMA), while addressing strengths shortcomings associated Common IMS-MS applications are also discussed review, such separating isomeric species, performing signal filtering MS, incorporating collision cross-section (CCS) values both targeted untargeted omics-based workflows ion descriptors chemical annotation. Although many challenges must addressed by before information collected routine fashion, future bright possibilities.

Language: Английский

---

Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics

Nature Communications, Journal Year: 2020, Volume and Issue: 11(1)

Published: Aug. 28, 2020

Abstract The metabolome includes not just known but also unknown metabolites; however, metabolite annotation remains the bottleneck in untargeted metabolomics. Ion mobility – mass spectrometry (IM-MS) has emerged as a promising technology by providing multi-dimensional characterizations of metabolites. Here, we curate an ion CCS atlas, namely AllCCS, and develop integrated strategy for using or chemical structures. AllCCS atlas covers vast structures with >5000 experimental records ~12 million calculated values >1.6 small molecules. We demonstrate high accuracy wide applicability medium relative errors 0.5–2% broad spectrum combined silico MS/MS spectra facilitates match substantially improves coverage both from biological samples. Together, is versatile resource that enables confident annotation, revealing comprehensive metabolic insights towards processes.

Language: Английский

---

Trapped ion mobility spectrometry and PASEF enable in-depth lipidomics from minimal sample amounts

Nature Communications, Journal Year: 2020, Volume and Issue: 11(1)

Published: Jan. 16, 2020

Abstract A comprehensive characterization of the lipidome from limited starting material remains very challenging. Here we report a high-sensitivity lipidomics workflow based on nanoflow liquid chromatography and trapped ion mobility spectrometry (TIMS). Taking advantage parallel accumulation–serial fragmentation (PASEF), fragment average 15 precursors in each 100 ms TIMS scans, while maintaining full resolution co-eluting isomers. The acquisition speed over Hz allows us to obtain MS/MS spectra vast majority isotope patterns. Analyzing 1 µL human plasma, PASEF increases number identified lipids more than three times standard TIMS-MS/MS, achieving attomole sensitivity. Building high intra- inter-laboratory precision accuracy collisional cross sections (CCS), compile 1856 lipid CCS values liver cancer cells. Our study establishes analysis paves way for sensitive, mobility-enhanced four dimensions.

Language: Английский

---

Ion mobility conformational lipid atlas for high confidence lipidomics

Nature Communications, Journal Year: 2019, Volume and Issue: 10(1)

Published: Feb. 28, 2019

Abstract Lipids are highly structurally diverse molecules involved in a wide variety of biological processes. Here, we use high precision ion mobility-mass spectrometry to compile structural database 456 mass-resolved collision cross sections (CCS) sphingolipid and glycerophospholipid species. Our CCS comprises sphingomyelin, cerebroside, ceramide, phosphatidylethanolamine, phosphatidylcholine, phosphatidylserine, phosphatidic acid classes. Primary differences observed between lipid categories, with sphingolipids exhibiting 2–6% larger CCSs than glycerophospholipids similar mass, likely result the sphingosine backbone’s restriction sn1 tail length, limiting gas-phase packing efficiency. Acyl length degree unsaturation found be primary descriptors determining magnitude, being four times as influential per mass unit. The empirical values previously unmapped quantitative trends detailed this work expected facilitate prediction broadscale lipidomics research.

Language: Английский

---

Ion Mobility Spectrometry in Food Analysis: Principles, Current Applications and Future Trends

Molecules, Journal Year: 2019, Volume and Issue: 24(15), P. 2706 - 2706

Published: July 25, 2019

In the last decade, ion mobility spectrometry (IMS) has reemerged as an analytical separation technique, especially due to commercialization of mass spectrometers. Its applicability been extended beyond classical applications such determination chemical warfare agents and nowadays it is widely used for characterization biomolecules (e.g., proteins, glycans, lipids, etc.) and, more recently, small molecules metabolites, xenobiotics, etc.). Following this trend, interest in technique growing among researchers from different fields including food science. Several advantages are attributed IMS when integrated traditional liquid chromatography (LC) gas (GC) (MS) workflows: (1) improves method selectivity by providing additional dimension that allows isobaric isomeric compounds; (2) increases sensitivity isolating compounds background noise; (3) provides complementary information spectra retention time, so-called collision cross section (CCS), so can be identified with confidence, either targeted or non-targeted approaches. context, number focused on analysis increased exponentially few years. This review overview current status technology its areas (i.e., composition, process control, authentication, adulteration safety).

Language: Английский

---

Predicting Ion Mobility Collision Cross-Sections Using a Deep Neural Network: DeepCCS

Analytical Chemistry, Journal Year: 2019, Volume and Issue: 91(8), P. 5191 - 5199

Published: April 1, 2019

Untargeted metabolomic measurements using mass spectrometry are a powerful tool for uncovering new small molecules with environmental and biological importance. The molecule identification step, however, still remains an enormous challenge due to fragmentation difficulties or unspecific fragment ion information. Current methods address this often dependent on databases require the use of nuclear magnetic resonance (NMR), which have their own difficulties. gas-phase collision cross section (CCS) values obtained from mobility (IMS) were recently demonstrated reduce number false positive metabolite identifications. While promising, amount empirical CCS information currently available is limited, thus predictive need be developed. In article, we expand upon current experimental IMS capabilities by predicting deep learning algorithm. We successfully developed trained prediction model requiring only about compound's SMILES notation type. data five different laboratories instruments allowed algorithm tested more than 2400 molecules. resulting predictions found achieve coefficient determination 0.97 median relative error 2.7% wide range Furthermore, method requires processing power predict values. Considering performance, time, resources necessary, as well its applicability variety molecules, was able outperform all algorithms.

Language: Английский

---

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

Mass Spectrometry Reviews, Journal Year: 2021, Volume and Issue: 41(5), P. 722 - 765

Published: Feb. 1, 2021

Abstract Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM‐MS), for metabolomics and lipidomics applications in a variety fields including life, biomedical, food sciences. IM‐MS provides three main technical advantages over traditional LC‐MS workflows. Firstly, addition to mass, allows collision cross‐section values be measured metabolites lipids, physicochemical identifier related the chemical shape an analyte that increases confidence identification. Second, peak capacity signal‐to‐noise, improving fingerprinting well quantification, better defining spatial localization lipids biological samples. Third, can coupled with various fragmentation modes, adding new tools improve structural characterization molecular annotation. Here, we review state‐of‐the‐art technologies approaches utilized support assess challenges opportunities this growing field.

Language: Английский

---

Deep learning the collisional cross sections of the peptide universe from a million experimental values

Nature Communications, Journal Year: 2021, Volume and Issue: 12(1)

Published: Feb. 19, 2021

The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate nature utility collisional cross section (CCS) space, we measure more than a million data points from whole-proteome digests five organisms with trapped ion mobility spectrometry (TIMS) parallel accumulation-serial fragmentation (PASEF). scale precision (CV < 1%) our is sufficient to train deep recurrent neural network that accurately predicts CCS values solely based on sequence. Cross predictions synthetic ProteomeTools peptides validate model within 1.4% median relative error (R > 0.99). Hydrophobicity, proportion prolines position histidines main determinants sections addition sequence-specific interactions. can now be predicted any organism, forming basis advanced proteomics workflows make full use additional information.

Language: Английский

---

Ion Mobility Mass Spectrometry (IM-MS) for Structural Biology: Insights Gained by Measuring Mass, Charge, and Collision Cross Section

Chemical Reviews, Journal Year: 2023, Volume and Issue: 123(6), P. 2902 - 2949

Published: Feb. 24, 2023

The investigation of macromolecular biomolecules with ion mobility mass spectrometry (IM-MS) techniques has provided substantial insights into the field structural biology over past two decades. An IM-MS workflow applied to a given target analyte provides mass, charge, and conformation, all three these can be used discern information. While charge are determined in (MS), it is addition that enables separation isomeric isobaric ions direct elucidation which reaped huge benefits for biology. In this review, where we focus on analysis proteins their complexes, outline typical features an experiment from preparation samples, creation ions, different spectrometers. We describe interpretation data terms protein conformation how compared other sources use computational tools. benefit coupling activation via collisions gas or surfaces photons photoactivation detailed reference recent examples. And finally, afforded by experiments when study conformationally dynamic intrinsically disordered proteins.

Language: Английский

---

The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Environmental Sciences Europe, Journal Year: 2022, Volume and Issue: 34(1)

Published: Oct. 21, 2022

Abstract Background The NORMAN Association ( https://www.norman-network.com/ ) initiated the Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/ in 2015, following collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange information chemicals that are expected to occur environment, along with accompanying expert knowledge and references, has become a valuable base for “suspect screening” lists. NORMAN-SLE now serves as FAIR (Findable, Accessible, Interoperable, Reusable) chemical resource worldwide. Results contains 99 separate suspect list collections (as May 2022) from over 70 contributors around world, totalling 100,000 unique substances. substance classes include per- polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume covered under European REACH regulation (EC: 1272/2008), priority contaminants emerging concern (CECs) regulatory lists partners. Several focus transformation products (TPs) complex features detected environment various levels provenance structural information. Each is available download. merged, curated collection also Substance Database (NORMAN SusDat). Both SusDat integrated within System (NDS). individual receive digital object identifiers (DOIs) traceable versioning via Zenodo community https://zenodo.org/communities/norman-sle ), total > 40,000 views, 50,000 downloads 40 citations (May 2022). content progressively into large open databases such PubChem https://pubchem.ncbi.nlm.nih.gov/ US EPA’s CompTox Chemicals Dashboard https://comptox.epa.gov/dashboard/ enabling further access these lists, additional functionality calculated properties resources offer. significant annotation NORMAN-SLE, including classification browser https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101 ). Conclusions offers specialized service hosting relevance an open, manner allows integration other major resources. These efforts foster between scientists regulators, supporting paradigm shift “one substance, one assessment” approach. New submissions welcome contacts provided website

Language: Английский

---