Mass Spectrometry for Neurobiomarker Discovery: The Relevance of Post-Translational Modifications

Azevedo, Rita; Jacquemin, Chloé; Villain, Nicolas; Fenaille, François; Lamari, Foudil; Bécher, François

doi:10.3390/cells11081279

Cited by 18 publications

(14 citation statements)

References 151 publications

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“…Our work independently discovered AD-specific, HMW-tau oligomers, and we further identified several site-specific phospho-tau-detectable HMW-tau aggregates as potential AD biomarkers. Given that hyperphosphorylation is a common theme of PTM implicated in disease pathogenesis and progression in multiple amyloidogenic proteins including tau, α-synuclein, and TDP-43 in neurodegenerative diseases, ,,,− we envision that our approach of biomarker discovery may be readily extended more broadly to other neurodegenerative disease diagnoses and translational detection applications.…”

Section: Discussionmentioning

confidence: 99%

Site-Specific Phospho-Tau Aggregation-Based Biomarker Discovery for AD Diagnosis and Differentiation

Gilyazova

Ervin

et al. 2022

ACS Chem. Neurosci.

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Tau aggregates are present in multiple neurodegenerative diseases known as "tauopathies," including Alzheimer's disease (AD), Pick's disease (PiD), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD). Such misfolded tau aggregates are therefore potential sources for tauopathy biomarker discovery. Using the tau antibody screening approach targeting high-molecular-weight misfolded tau aggregates, we tested several tau antibodies and a comprehensive set of site-specific phospho-tau (p-tau) antibodies targeting tau phosphorylation sites showing high frequencies in AD subjects. Our screens revealed that site-specific p-tau antibodies can not only differentiate AD from non-AD brains, but also discriminate AD from rare tauopathies PiD, PSP, and CBD brains. Differential detection of tau aggregates identified several novel p-tau sites as potential new biomarkers. As a proof-of-principle example, we showed that p-tau198 is a novel promising AD biomarker with sensitivity and specificity comparable with the existing biomarkers p-tau181 and p-tau217. Our results demonstrated that p-tau198 detection can not only differentiate AD from non-AD controls, but also diagnose AD from related 4R tauopathies PSP and CBD with AUCs of 0.96−0.99 (95% CI ranges from 0.90 to 1.00). Promisingly, p-tau198 was able to discriminate mild cognitive impairment from cognitively normal brains with an AUC of 0.75 (95% CI = 0.58−0.92). Our work provides a new avenue for developing diagnosis and differentiation tools for AD and related tauopathies.

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Section: Discussionmentioning

confidence: 99%

Site-Specific Phospho-Tau Aggregation-Based Biomarker Discovery for AD Diagnosis and Differentiation

Gilyazova

Ervin

et al. 2022

ACS Chem. Neurosci.

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“…2 Antibody-free extraction protocols represent a good complement or alternative in the objective of unbiased analyses of the variety of proteoforms described for tau. 9 Top-down or intact protein analysis, which delivers the most comprehensive information on the protein sequence, 10 would benefit in the future from such extraction protocols.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of SP3 for antibody-free quantification of tau in CSF mimic and brain by mass spectrometry

Jacquemin,

Villain,

Azevedo

et al. 2024

Eur J Mass Spectrom (Chichester)

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Tubulin-associated unit (tau) has an important role in the pathogenesis and the diagnosis of Alzheimer's disease (AD) and other tauopathies. In view of the diversity of tau proteoforms, antibody-free methods represent a good approach for unbiased quantification. We adapted and evaluated the single-pot, solid-phase-enhanced sample-preparation (SP3) protocol for antibody-free extraction of the tau protein in cerebro-spinal fluid (CSF) mimic and in human brain. A total of 13 non-modified peptides were quantified by high-resolution mass spectrometry (HRMS) after digestion of tau by trypsin. We significantly improved the basic SP3 protocol by carefully optimizing the organic solvents and incubation time for tau binding, as well as the digestion step for the release directly from the SP3 beads of the 13 tau peptides. These optimizations proved to be primarily beneficial for the most hydrophilic tau peptides, increasing the sequence coverage of recombinant tau. Mean recovery in CSF mimic of the 13 non-modified peptides was of 53%, with LODs ranging from 0.75 to 10 ng/mL. Next, we tested the optimized SP3 protocol on pathological tau extracted from the soluble fraction from an AD brain sample (middle frontal gyrus). We could successfully identify and quantify biologically relevant tau peptides including representative peptides of two isoforms and two phospho-peptides (pTau217 and pTau181).

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“…Tandem mass spectrometry (MS/MS)-based proteomics enables high-throughput characterization and quantification of tens of thousands of peptides in a single experiment. , Despite the remarkable advancements in mass spectrometers over the past decade, automated data analysis software tools still struggle to keep pace with the increasingly complex field of proteomics research. , Usually, this process involves predicting theoretical spectra from known protein sequences present in complete proteome databases and then comparing these predictions with observed spectra. Such in-silico spectra provide broad coverage of peptide–spectrum matches (PSMs) but may lack more distinctive features, such as fragment intensities or noncanonical fragment ions, , that can help mitigate inevitable false positive matches.…”

Section: Introductionmentioning

confidence: 99%

UniSpec: Deep Learning for Predicting the Full Range of Peptide Fragment Ion Series to Enhance the Proteomics Data Analysis Workflow

Lapin,

Yan,

Dong

2024

Anal. Chem.

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We present UniSpec, an attention-driven deep neural network designed to predict comprehensive collisioninduced fragmentation spectra, thereby improving peptide identification in shotgun proteomics. Utilizing a training data set of 1.8 million unique high-quality tandem mass spectra (MS2) from 0.8 million unique peptide ions, UniSpec learned with a peptide fragmentation dictionary encompassing 7919 fragment peaks. Among these, 5712 are neutral loss peaks, with 2310 corresponding to modification-specific neutral losses. Remarkably, UniSpec can predict 73%−77% of fragment intensities based on our NIST reference library spectra, a significant leap from the 35%−45% coverage of only b and y ions. Comparative studies with Prosit elucidate that while both models are strong at predicting their respective fragment ion series, UniSpec particularly shines in generating more complex MS2 spectra with diverse ion annotations. The integration of UniSpec's predictions into shotgun proteomics data analysis boosts the identification rate of tryptic peptides by 48% at a 1% false discovery rate (FDR) and 60% at a more confident 0.1% FDR. Using UniSpec's predicted in-silico spectral library, the search results closely matched those from search engines and experimental spectral libraries used in peptide identification, highlighting its potential as a stand-alone identification tool. The source code and Python scripts are available on GitHub (https://github.com/usnistgov/UniSpec) and Zenodo (https:// zenodo.org/records/10452792), and all data sets and analysis results generated in this work were deposited in Zenodo (https:// zenodo.org/records/10052268).

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Mass Spectrometry for Neurobiomarker Discovery: The Relevance of Post-Translational Modifications

Cited by 18 publications

References 151 publications

Site-Specific Phospho-Tau Aggregation-Based Biomarker Discovery for AD Diagnosis and Differentiation

Site-Specific Phospho-Tau Aggregation-Based Biomarker Discovery for AD Diagnosis and Differentiation

Evaluation of SP3 for antibody-free quantification of tau in CSF mimic and brain by mass spectrometry

UniSpec: Deep Learning for Predicting the Full Range of Peptide Fragment Ion Series to Enhance the Proteomics Data Analysis Workflow

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