Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge

May, Jody C.; McLean, John A.

doi:10.1146/annurev-anchem-071015-041734

Cited by 76 publications

(81 citation statements)

References 142 publications

(148 reference statements)

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“…Hence, the utility of IM-MS is evident in the analysis of complex samples that require identification of both distinct molecules (MS) and potential isomers, conformers or multimeric species of these compounds (IM), illustrating the well-known advantages of hyphenated separations. 64,65 …”

Section: Resultsmentioning

confidence: 99%

Correlating Resolving Power, Resolution, and Collision Cross Section: Unifying Cross-Platform Assessment of Separation Efficiency in Ion Mobility Spectrometry

2017

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Here we examine the relationship between resolving power (Rp), resolution (Rpp), and collision cross section (CCS) for compounds analyzed in previous ion mobility (IM) experiments representing a wide variety of instrument platforms and IM techniques. Our previous work indicated these three variables effectively describe and predict separation efficiency for drift tube ion mobility spectrometry (DTIMS) experiments. In this work we seek to determine if our previous findings are a general reflection of IM behavior applicable to various instrument platforms and mobility techniques. Results suggest IM distributions are well characterized by a Gaussian model and separation efficiency can be predicted based on empirical difference in the gas-phase CCS and a CCS-based resolving power definition (CCS/ΔCCS). Notably traveling wave (TWIMS) was found to operate at substantially higher resolutions than a single-peak resolving power suggested. When a CCS-based Rp definition was utilized, TWIMS was found to operate at a resolving power of between 40 and 50, confirming the previous observations by Giles and coworkers. After converting the separation axis (and corresponding resolving power) to cross section space it is possible to effectively predict separation behavior for all mobility techniques evaluated (i.e. uniform field, trapped ion mobility, traveling wave, cyclic and overtone instruments) using the equations described in this work. Finally, we are able to establish for the first time that the current state-of-the-art ion mobility separations benchmark at a CCS-based resolving powers above 300 which is sufficient to differentiate analyte ions with CCS differences as small as 0.5%.

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Section: Resultsmentioning

confidence: 99%

Correlating Resolving Power, Resolution, and Collision Cross Section: Unifying Cross-Platform Assessment of Separation Efficiency in Ion Mobility Spectrometry

2017

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“…The annotated human metabolome is considered to be less complex than the proteome [2,3], yet the diverse chemical structures exhibit a wide range of concentration, solubility, polarity, and volatility [4]. Proteomics samples often require a multi-step preparation that may involve cell lysis, purification, enzymatic digestion, and solid phase extraction [5].…”

Section: Lc-ms Based Metabolomics: Strengths and Challengesmentioning

confidence: 99%

Untargeted Metabolomics Strategies—Challenges and Emerging Directions

Schrimpe‐Rutledge

Codreanu

Sherrod

et al. 2016

J. Am. Soc. Mass Spectrom.

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Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes, and as such the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating, workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS based untargeted metabolomics studies – specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

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“…A final observation to make from Figure 6A is that the bimodal distribution observed over the past five years (2011–2015) closely mimics the analytical trend observed within the largest chemical database, PubChem, 160,161 where chemical entries have, over time, shifted to focusing on lower mass analytes while the total number of entries in PubChem currently exhibits a bimodal mass distribution. 11 …”

Section: Ccs Coverage Over Timementioning

confidence: 99%

“…14–19 Many of the contemporary challenges being addressed by IM-MS are grand challenges of our era of humanity. 11 …”

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confidence: 99%

Ion Mobility Collision Cross Section Compendium

2016

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In this review, we focus on an important aspect of ion mobility (IM) research, namely the reporting of quantitative ion mobility measurements in the form of the gas-phase collision cross section (CCS), which has provided a common basis for comparison across different instrument platforms and offers a unique form of structural information, namely size and shape preferences of analytes in the absence of bulk solvent. This review surveys the over 24,000 CCS values reported from IM methods spanning the era between 1975 to 2015, which provides both a historical and analytical context for the contributions made thus far, as well as insight into the future directions that quantitative ion mobility measurements will have in the analytical sciences. The analysis was conducted in 2016, so CCS values reported in that year are purposely omitted. In another few years, a review of this scope will be intractable, as the number of CCS values which will be reported in the next three to five years is expected to exceed the total amount currently published in the literature.

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Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge

Cited by 76 publications

References 142 publications

Correlating Resolving Power, Resolution, and Collision Cross Section: Unifying Cross-Platform Assessment of Separation Efficiency in Ion Mobility Spectrometry

Correlating Resolving Power, Resolution, and Collision Cross Section: Unifying Cross-Platform Assessment of Separation Efficiency in Ion Mobility Spectrometry

Untargeted Metabolomics Strategies—Challenges and Emerging Directions

Ion Mobility Collision Cross Section Compendium

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