IMS–MS studies based on coupling a differential mobility analyzer (DMA) to commercial API–MS systems

Rus, Juan; Moro, David; Sillero, Juan A.; Royuela, Javier; Casado, Alejandro; Estevez-Molinero, Francisco; Mora, Juan Fernández de la

doi:10.1016/j.ijms.2010.05.008

Cited by 110 publications

(99 citation statements)

References 18 publications

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“…In the low field limit, DMA can potentially provide collision cross sections as defined in Eqn (3), [29,30] whereas highfield phenomena in FAIMS are much more complicated. [31] (3) In trapping IMS devices (TIMS), ions face a counter-current gas flow and are trapped, depending on the electric field.…”

Section: Experimental Collision Cross Section Determinationmentioning

confidence: 99%

“…They are the mobility analogues of quadrupole or sector-type mass analyzers. Filters can operate in the low field limit (like differential mobility analyzers or 'DMA') or involve high fields (like field asymmetric waveform ion mobility spectrometry or 'FAIMS').In the low field limit, DMA can potentially provide collision cross sections as defined in Eqn (3), [29,30] whereas highfield phenomena in FAIMS are much more complicated. [31] (3) In trapping IMS devices (TIMS), ions face a counter-current gas flow and are trapped, depending on the electric field.…”

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Linking molecular models with ion mobility experiments. Illustration with a rigid nucleic acid structure

D’Atri¹,

Porrini²,

Rosu³

et al. 2015

J. Mass Spectrom.

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Ion mobility spectrometry experiments allow the mass spectrometrist to determine an ion's rotationally averaged collision cross section Ω EXP . Molecular modelling is used to visualize what ion three-dimensional structure(s) is(are) compatible with the experiment. The collision cross sections of candidate molecular models have to be calculated, and the resulting Ω CALC are compared with the experimental data. Researchers who want to apply this strategy to a new type of molecule face many questions: (1) What experimental error is associated with Ω EXP determination, and how to estimate it (in particular when using a calibration for traveling wave ion guides)? (2) How to generate plausible 3D models in the gas phase? (3) Different collision cross section calculation models exist, which have been developed for other analytes than mine. Which one(s) can I apply to my systems? To apply ion mobility spectrometry to nucleic acid structural characterization, we explored each of these questions using a rigid structure which we know is preserved in the gas phase: the tetramolecular G-quadruplex [dTGGGGT] 4 , and we will present these detailed investigation in this tutorial. Additional supporting information may be found in the online version of this article at the publisher's web site.Keywords: ion mobility spectrometry; collision cross section; structure; nucleic acids; simulations; molecular modeling; gas-phase ion structure IntroductionElectrospray mass spectrometry (ESI-MS) in native conditions can preserve the structures of biomolecules and separate them according to their mass-to-charge ratios. [1,2] Ion mobility spectrometry (IMS) separates ions according to their size-to-charge ratios in the gas-phase. [3][4][5][6] Size is related to the mass (or number of atoms) and to the three-dimensional shape of a molecule. Therefore, by hyphenating IMS to mass spectrometry (IM-MS), one can sort ions according to both mass and shape. The challenge is to decipher structural information from ion mobility experiments. [7][8][9] The physical quantity characterizing the shape is the collision cross section (CCS), [10] which will be introduced in more detail in the Section on Ion mobility and collision cross sections. The present tutorial clarifies how to interpret CCS measurements in terms of three-dimensional structure for ions larger than 100 atoms extracted from the solution by electrospray ionization (ESI). The gold standard is to match CCSs experimentally obtained from IMS with CCSs calculated for modelling three-dimensional structures of the ion of interest. We will discuss the factors that can affect the precision (reproducibility) and accuracy in both the measurements and the calculations. Understanding each of these factors is crucial to interpret quantitative matches confidently and assess the meaningfulness of structural assignments.On the experimental side, we will describe the determination of CCS from traveling wave ion mobility spectrometers and from drift tube ion mobility spectrometers, with example data recorde...

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Section: Experimental Collision Cross Section Determinationmentioning

confidence: 99%

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confidence: 99%

Linking molecular models with ion mobility experiments. Illustration with a rigid nucleic acid structure

D’Atri¹,

Porrini²,

Rosu³

et al. 2015

J. Mass Spectrom.

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“…This allows for DMAs to be readily coupled as front-end devices to almost any mass spectrometer with an atmospheric pressure ion source, without any modification in the operation of the MS [21]. Recently, hightransmission parallel-plate DMAs have been constructed with resolving powers in excess of 50 [22,23], which are well suited to DMA-MS integration. In tandem DMA-MS with a parallel-plate DMA, the DMA operates at atmospheric pressure, and, unlike most other IMS-MS instruments, it can be used to measure the mobility of electrosprayed ions immediately following the evaporation of electrospray drops, without the need to subject the ions to RF fields, declustering collisions, energetic injection stages, or even vacuum interfaces.…”

Section: Introductionmentioning

confidence: 99%

Ion Mobility Measurements of Nondenatured 12–150 kDa Proteins and Protein Multimers by Tandem Differential Mobility Analysis–Mass Spectrometry (DMA-MS)

Hogan

Mora

2011

J. Am. Soc. Mass Spectrom.

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The mobilities of electrosprayed proteins and protein multimers with molecular weights ranging from 12.4 kDa (cytochrome C monomers) to 154 kDa (nonspecific concanavalin A hexamers) were measured in dry air by a planar differential mobility analyzer (DMA) coupled to a time-offlight mass spectrometer (TOF-MS). The DMA determines true mobility at atmospheric pressure, without perturbing ion structure from that delivered by the electrospray. A nondenaturing aqueous 20 mM triethylammonium formate buffer yields compact ions with low charge states, moderating polarization effects on ion mobility. Conversion of mobilities into cross-sections involves a reduction factor ξ for the actual mobility relative to that associated with elastic specular collisions with smooth surfaces. ξ is known to be 1.36 in air from Millikan's oil drop experiments. A similar enhancement effect ascribed to atomic-scale surface roughness has been found in numerical simulations. Adopting Millikan's value ξ=1.36 and assuming a spherical geometry yields a gas-phase protein density ρ p =0.949±0.053 g cm −3 for all our protein data. This is substantially higher than the 0.67 g cm −3 found in recent low-resolution DMA measurements of singly charged proteins. DMA-MS can distinguish nonspecific protein aggregates formed during the electrospray process from those formed preferentially in solution.The observed charge versus diameter relation is compatible with a protein charge reduction mechanism based on the evaporation of triethylammonium ions from electrosprayed drops.

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“…To achieve this resolution, these DMAs operate at Reynolds numbers well beyond that typically associated with the onset of turbulence. Although the exceptionally high flow rates required for these supercritical, laminar-flow, high-resolution DMAs (100 to 1000 liters per minute (lpm) or more) limit their applicability, these instruments have enabled a number of important studies, especially when used as a front-end to a mass spectrometer (Hogan and de la Mora 2010;Rus et al 2010;Hogan and de la Mora 2011;Oberreit et al 2015).…”

Section: Advancing Nanometer Particle Classificationmentioning

confidence: 99%

Design, simulation, and characterization of a radial opposed migration ion and aerosol classifier (ROMIAC)

Mui

Mai

Downard

et al. 2017

Aerosol Science and Technology

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We present the design, simulation, and characterization of the radial opposed migration ion and aerosol classifier (ROMIAC), a compact differential electrical mobility classifier. We evaluate the performance of the ROMIAC using a combination of finite element modeling and experimental validation of two nearly identical instruments using tetra-alkyl ammonium halide mass standards and sodium chloride particles. Mobility and efficiency calibrations were performed over a wide range of particle diameters and flow rates to characterize ROMIAC performance under the range of anticipated operating conditions. The ROMIAC performs as designed, though performance deviates from that predicted using simplistic models of the instrument. The underlying causes of this nonideal behavior are found through finite element simulations that predict the performance of the ROMIAC with greater accuracy than the simplistic models. It is concluded that analytical performance models based on idealized geometries, flows, and fields should not be relied on to make accurate a priori predictions about instrumental behavior if the actual geometry or fields deviate from the ideal assumptions. However, if such deviations are accurately captured, finite element simulations have the potential to predict instrumental performance. The present prototype of the ROMIAC maintains its resolution over nearly three orders of magnitude in particle mobility, obtaining sub-20 nm particle size distributions in a compact package with relatively low flow rate operation requirements.

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IMS–MS studies based on coupling a differential mobility analyzer (DMA) to commercial API–MS systems

Cited by 110 publications

References 18 publications

Linking molecular models with ion mobility experiments. Illustration with a rigid nucleic acid structure

Linking molecular models with ion mobility experiments. Illustration with a rigid nucleic acid structure

Ion Mobility Measurements of Nondenatured 12–150 kDa Proteins and Protein Multimers by Tandem Differential Mobility Analysis–Mass Spectrometry (DMA-MS)

Design, simulation, and characterization of a radial opposed migration ion and aerosol classifier (ROMIAC)

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