TMTpro reagents: a set of isobaric labeling mass tags enables simultaneous proteome-wide measurements across 16 samples

Li, Jiaming; Vranken, Jonathan G. Van; Vaites, Laura Pontano; Schweppe, Devin K.; Huttlin, Edward L; Etienne, Chris; Nandhikonda, Premchendar; Viner, Rosa; Robitaille, Aaron M.; Thompson, Andrew; Kuhn, Karsten; Pike, Ian; Bomgarden, Ryan; Rogers, John C.; Gygi, Steven P.; Paulo, João A.

doi:10.1038/s41592-020-0781-4

Cited by 319 publications

(360 citation statements)

References 40 publications

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“…Multiplex TMT labeling of the remaining replication samples was performed as previously described ( 17 ). For each replication analysis, all CSF samples, including the GIS and boost samples, were labeled using an 11-plex (CSF replications 1 and 2) or 16-plex (CSF replication 4) TMT kit (Thermo Fisher Scientific) ( 70 ). See the “Data and materials availability” section for sample to batch arrangement.…”

Section: Methodsmentioning

confidence: 99%

Integrated proteomics reveals brain-based cerebrospinal fluid biomarkers in asymptomatic and symptomatic Alzheimer’s disease

et al. 2020

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Alzheimer’s disease (AD) lacks protein biomarkers reflective of its diverse underlying pathophysiology, hindering diagnostic and therapeutic advancements. Here, we used integrative proteomics to identify cerebrospinal fluid (CSF) biomarkers representing a wide spectrum of AD pathophysiology. Multiplex mass spectrometry identified ~3500 and ~12,000 proteins in AD CSF and brain, respectively. Network analysis of the brain proteome resolved 44 biologically diverse modules, 15 of which overlapped with the CSF proteome. CSF AD markers in these overlapping modules were collapsed into five protein panels representing distinct pathophysiological processes. Synaptic and metabolic panels were decreased in AD brain but increased in CSF, while glial-enriched myelination and immunity panels were increased in brain and CSF. The consistency and disease specificity of panel changes were confirmed in >500 additional CSF samples. These panels also identified biological subpopulations within asymptomatic AD. Overall, these results are a promising step toward a network-based biomarker tool for AD clinical applications.

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Section: Methodsmentioning

confidence: 99%

Integrated proteomics reveals brain-based cerebrospinal fluid biomarkers in asymptomatic and symptomatic Alzheimer’s disease

et al. 2020

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“…with TMT [76,77]. This strategy, when coupled to off-line fractionation, can result in the quantification of thousands of additional proteins and has permitted remarkably deep proteomic analysis of AD brain tissue [74,75,78,79].…”

Section: Strategies For Mass Spectrometry-based Quantificationmentioning

confidence: 99%

Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau

Rayaprolu

Higginbotham

Bagchi

et al. 2020

Neuropsychopharmacol.

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The repeated failures of amyloid-targeting therapies have challenged our narrow understanding of Alzheimer’s disease (AD) pathogenesis and inspired wide-ranging investigations into the underlying mechanisms of disease. Increasing evidence indicates that AD develops from an intricate web of biochemical and cellular processes that extend far beyond amyloid and tau accumulation. This growing recognition surrounding the diversity of AD pathophysiology underscores the need for holistic systems-based approaches to explore AD pathogenesis. Here we describe how network-based proteomics has emerged as a powerful tool and how its application to the AD brain has provided an informative framework for the complex protein pathophysiology underlying the disease. Furthermore, we outline how the AD brain network proteome can be leveraged to advance additional scientific and translational efforts, including the discovery of novel protein biomarkers of disease.

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“…We used stable isotope labeled proteomics strategy TMTpro (16plex) (Li et al, 2020a) were identified with authentic compound library searching. For metabolomic analysis, both hydrophilic and hydrophobic molecules were analyzed using both positive and negative ionization to cover various endogenous biochemical classes.…”

Section: Proteomic and Metabolomic Profiling Of Covid-19 Seramentioning

confidence: 99%

Proteomic and Metabolomic Characterization of COVID-19 Patient Sera

Shen

Sun

et al. 2020

Preprint

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24Severe COVID-19 patients account for most of the mortality of this disease. 25 Early detection and effective treatment of severe patients remain major 26 challenges. Here, we performed proteomic and metabolomic profiling of sera 27 from 46 COVID-19 and 53 control individuals. We then trained a machine 28 learning model using proteomic and metabolomic measurements from a 29 training cohort of 18 non-severe and 13 severe patients. The model correctly 30 classified severe patients with an accuracy of 93.5%, and was further 31 validated using ten independent patients, seven of which were correctly 32 classified. We identified molecular changes in the sera of COVID-19 patients 33 implicating dysregulation of macrophage, platelet degranulation and 34 complement system pathways, and massive metabolic suppression. This 35 study shows that it is possible to predict progression to severe COVID-19 36 disease using serum protein and metabolite biomarkers. Our data also 37 uncovered molecular pathophysiology of COVID-19 with potential for 38 developing anti-viral therapies.

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TMTpro reagents: a set of isobaric labeling mass tags enables simultaneous proteome-wide measurements across 16 samples

Cited by 319 publications

References 40 publications

Integrated proteomics reveals brain-based cerebrospinal fluid biomarkers in asymptomatic and symptomatic Alzheimer’s disease

Integrated proteomics reveals brain-based cerebrospinal fluid biomarkers in asymptomatic and symptomatic Alzheimer’s disease

Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau

Proteomic and Metabolomic Characterization of COVID-19 Patient Sera

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