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Record W2327376952 · doi:10.1021/ac5044016

Exploring the Mechanism of Salt-Induced Signal Suppression in Protein Electrospray Mass Spectrometry Using Experiments and Molecular Dynamics Simulations

2015· article· en· W2327376952 on OpenAlexafffund
Haidy Metwally, Robert G. McAllister, Lars Konermann

Bibliographic record

VenueAnalytical Chemistry · 2015
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryIonElectrospray ionizationAdductMolecular dynamicsMass spectrometryElectrospraySalt (chemistry)Analytical Chemistry (journal)TetramethylammoniumChromatographyComputational chemistryPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Protein analyses by electrospray ionization (ESI) mass spectrometry can suffer from interferences caused by nonvolatile salts. The mechanistic basis of this effect remains to be fully investigated. In the current work we explore the behavior of proteins under native and denaturing conditions in the presence of NaCl, CsCl, and tetrabutyl ammonium chloride (NBu4Cl). All three salts interfere with the formation of "clean" [M + zH](z+) protein ions by progressively deteriorating spectral S/N ratios. We propose that salt interferences can be dissected into two independent aspects, i.e., (i) peak splitting by adduct formation and (ii) protein ion suppression. NaCl degrades the spectral quality by forming heterogeneous [M + zH + n(Na - H) + m(Cl + H)](z+) ions, while the integrated protein ion intensity remains surprisingly robust. Conversely, NBu4Cl does not cause any adduction, while dramatically reducing the protein ion yield. These findings demonstrate that adduct formation and protein ion suppression are indeed unrelated effects that may occur independently of one another. Other salts, such as CsCl, can give rise to a combination of the two scenarios. Molecular dynamics simulations of water droplets charged with either Na(+) or NBu4(+) provide insights into the mechanism underlying the observed effects. Na(+) containing droplets evolve relatively close to the Rayleigh limit (z/z(R) ≈ 0.74), whereas the z/z(R) values of NBu4(+) charged droplets are considerably lower (∼0.59). This difference is due to the high surface affinity of NBu4(+), which facilitates charge ejection from the droplet. We propose that the low z/z(R) values encountered in the presence of NBu4(+) suppress the Rayleigh fission of parent droplets in the ESI plume, thereby reducing the yield of progeny droplets that represent the precursors of gaseous protein ions. In addition, the rate of solvent evaporation is reduced in the presence of NBu4(+). Both of these factors lower the protein signal intensity. NaCl does not interfere with droplet fission, such that protein ions continue to form with high yield—albeit in heavily adducted form. Our findings expand on earlier proposals of charge competition as a key factor during the ESI process for salt-contaminated solutions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059
GPT teacher head0.306
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations87
Published2015
Admission routes2
Has abstractyes

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