A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer’s disease

Merrihew, Gennifer E.; Park, Jea; Plubell, Deanna; Searle, Brian C.; Keene, C. Dirk; Larsen, Eric; Bateman, Randall J.; Perrin, Richard J.; Chhatwal, Jasmeer P.; Farlow, Martin R.; McLean, Catriona; Ghetti, Bernardino; Newell, Kathy L.; Frosch, Matthew P.; Montine, Thomas J.; MacCoss, Michael J.

doi:10.1101/2022.11.04.515203

Cited by 8 publications

(10 citation statements)

References 29 publications

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“…54,43,39,32 Furthermore, the three data sets that we analyzed all had relatively simple experimental designs. For the DIA 35 and TMT 41 data sets, each analyzed sample came from a different individual, and serial biopsies and time series data were excluded from our analysis. For the label-free DDA data set, 39 biological replicates from two Brucella species were compared.…”

Section: Discussionmentioning

confidence: 99%

“…For differential expression analysis we obtained data from PXD034525, a DIA study of Alzheimer's disease. 35 Clinical samples had previously been assigned to experimental groups based on several genetic, histopathological, and cognitive criteria. We compared differentially expressed peptides between (i) autosomal dominant Alzheimer's disease dementia and (ii) high cognitive function and low Alzheimer's disease neuropathologic change.…”

Section: Differential Expressionmentioning

confidence: 99%

“…We obtained peptide-level quantifications from a DIA-based clinical study of Alzheimer's disease. 35 Patient-derived brain samples had been assigned to experimental groups based on several genetic, histopathological, and cognitive criteria. We compared samples belonging to two experimental groups: (i) autosomal dominant dementia and (ii) high cognitive function and low Alzheimer's disease neuropathologic change.…”

Section: Differential Expressionmentioning

confidence: 99%

“…Data were obtained from PXD034525, a DIA study of Alzheimer's disease. Differentially expressed peptides were identified between two clinically annotated Alzheimer's disease groups 35. The areas under the precision-recall curves (AUCs) for the MCAR and MNAR are indicated.…”

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confidence: 99%

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Evaluating Proteomics Imputation Methods with Improved Criteria

Harris,

Fondrie,

et al. 2023

J. Proteome Res.

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Quantitative measurements produced by tandem mass spectrometry proteomics experiments typically contain a large proportion of missing values. Missing values hinder reproducibility, reduce statistical power, and make it difficult to compare across samples or experiments. Although many methods exist for imputing missing values, in practice, the most commonly used methods are among the worst performing. Furthermore, previous benchmarking studies have focused on relatively simple measurements of error such as the mean-squared error between imputed and held-out values. Here we evaluate the performance of commonly used imputation methods using three practical, “downstream-centric” criteria. These criteria measure the ability to identify differentially expressed peptides, generate new quantitative peptides, and improve the peptide lower limit of quantification. Our evaluation comprises several experiment types and acquisition strategies, including data-dependent and data-independent acquisition. We find that imputation does not necessarily improve the ability to identify differentially expressed peptides but that it can identify new quantitative peptides and improve the peptide lower limit of quantification. We find that MissForest is generally the best performing method per our downstream-centric criteria. We also argue that existing imputation methods do not properly account for the variance of peptide quantifications and highlight the need for methods that do.

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Section: Discussionmentioning

confidence: 99%

Section: Differential Expressionmentioning

confidence: 99%

Section: Differential Expressionmentioning

confidence: 99%

mentioning

confidence: 99%

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Evaluating Proteomics Imputation Methods with Improved Criteria

Harris,

Fondrie,

et al. 2023

J. Proteome Res.

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“…The two instruments examined different pooled human brain tissue samples with slightly different LC setups and gradients. Sample preparation has been described in detail previously, 16 and the nanoLC conditions can be found in the Supporting Information. Experiments without FAIMS used a 240,000 resolving power MS1 survey scan, Standard AGC Target, and Auto Maximum Injection Time, followed by MS/MS of the most intense precursors for 1 second.…”

Section: Methodsmentioning

confidence: 99%

Comparing peptide identifications by FAIMS versus quadrupole gas-phase fractionation

Faivre,

McGann,

Merrihew

et al. 2023

Preprint

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High-field asymmetric waveform ion mobility spectrometry (FAIMS) coupled to liquid chromatography-mass spectrometry (LC-MS) has been shown to increase peptide and protein detections compared to LC-MS/MS alone. However, FAIMS has not been compared to other methods of gas-phase fractionation, such as quadrupole gas-phase fractionation, which could increase our understanding of the mechanisms of improvement. The goal of this work was to assess whether FAIMS improves peptide identifications because 1) gas-phase fractionation enables the analysis of less abundant signals by excluding more abundant precursors from filling the ion trap, 2) the use of FAIMS reduces co-isolation of peptides during the MS/MS process resulting in a reduction of chimeric spectra, or 3) a combination of both. To investigate these hypotheses, pooled human brain tissue samples were measured in triplicate using FAIMS gas-phase fractionation, quadrupole gas-phase fractionation, or no gas-phase fractionation on two Thermo Eclipse Tribrid Mass Spectrometers. On both instruments, our data confirmed prior observations that FAIMS increased the number of peptides identified. We further demonstrated that the main benefit of FAIMS is due to the reduced co-isolation of persistent peptide precursor ions, which results in a decrease in chimeric spectra.

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Combining FAIMS based glycoproteomics and DIA proteomics reveals widespread proteome alterations in response to glycosylation occupancy changes in Neisseria gonorrhoeae

Hadjineophytou,

Loh,

Koomey

et al. 2024

Proteomics

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Protein glycosylation is increasingly recognized as a common protein modification across bacterial species. Within the Neisseria genus O‐linked protein glycosylation is conserved yet closely related Neisseria species express O‐oligosaccharyltransferases (PglOs) with distinct targeting activities. Within this work, we explore the targeting capacity of different PglOs using Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) fractionation and Data‐Independent Acquisition (DIA) to allow the characterization of the impact of changes in glycosylation on the proteome of Neisseria gonorrhoeae. We demonstrate FAIMS expands the known glycoproteome of wild type N. gonorrhoeae MS11 and enables differences in glycosylation to be assessed across strains expressing different pglO allelic chimeras with unique substrate targeting activities. Combining glycoproteomic insights with DIA proteomics, we demonstrate that alterations within pglO alleles have widespread impacts on the proteome of N. gonorrhoeae. Examination of peptides known to be targeted by glycosylation using DIA analysis supports alterations in glycosylation occupancy occurs independently of changes in protein levels and that the occupancy of glycosylation is generally low on most glycoproteins. This work thus expands our understanding of the N. gonorrhoeae glycoproteome and the roles that pglO allelic variation may play in governing genus‐level protein glycosylation.

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A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer’s disease

Cited by 8 publications

References 29 publications

Evaluating Proteomics Imputation Methods with Improved Criteria

Evaluating Proteomics Imputation Methods with Improved Criteria

Comparing peptide identifications by FAIMS versus quadrupole gas-phase fractionation

Combining FAIMS based glycoproteomics and DIA proteomics reveals widespread proteome alterations in response to glycosylation occupancy changes in Neisseria gonorrhoeae

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