TMT‐Based Quantitative Proteomic Analysis Reveals Proteomic Changes Involved in Longevity

Wang, Zongkui; Zhang, Rong; Liu, Fengjuan; Jiang, Peng; Xu, Jun; Cao, Haijun; Du, Xi; Ma, Li; Lin, Fen; Cheng, Lu; Zhou, Xuefeng; Shi, Zhihui; Liu, Yeheng; Huang, Yaojing; Ye, Shengliang; Li, Changqing

doi:10.1002/prca.201800024

Cited by 20 publications

(27 citation statements)

References 41 publications

(36 reference statements)

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“…Inclusion criteria for a manuscript included healthy individuals, proteomics results published on or after 2010, publications/authors provided list of significant/all proteins. Thirty three manuscripts met the inclusion criteria, including 12 that covered human plasma (Enroth et al, 2015; Lehallier et al, 2019; Lind et al, 2019; Menni et al, 2015; Ngo et al, 2016; Orwoll et al, 2018; Santos‐Lozano et al, 2020; Sun et al, 2018; Tanaka et al, 2018; Wang, Zhu, et al, 2019; Wang, Zhang, et al, 2019; Ye et al, 2019), 9 from 14 different matrices in humans (Baird et al, 2012; Bakun et al, 2014; Bell‐Temin et al, 2019; Gueugneau et al, 2014; Heinze et al, 2018; Hennrich et al, 2018; Ubaida‐Mohien et al, 2019; Waldera‐Lupa et al, 2014; Wang, Wang, et al, 2018), and 12 publications covering 21 different species/matrices (Amin et al, 2020; Angelidis et al, 2019; Braun et al, 2016; Cutler et al, 2017; Drulis‐Fajdasz et al, 2018; Gebert et al, 2020; Heinze et al, 2018; Kelley et al, 2018; Meng et al, 2020; Stauch et al, 2015; Wang, Zhu, et al, 2019; Yu et al, 2020). The age range of participants included in these studies spanned from 14 to 103 years, and measures were carried out using multiple platforms including but not limited to liquid chromatography–mass spectrometry (LC‐MS)‐based proteomics, multiplexed proteomic assay using modified aptamers (SOMAscan) and Proximity Extension Assay (PEA, O‐Link) (Gold et al, 2010; Lundberg et al, 2011).…”

Section: Methodsmentioning

confidence: 99%

Proteomics in aging research: A roadmap to clinical, translational research

et al. 2021

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The identification of plasma proteins that systematically change with age and, independent of chronological age, predict accelerated decline of health is an expanding area of research. Circulating proteins are ideal translational “omics” since they are final effectors of physiological pathways and because physicians are accustomed to use information of plasma proteins as biomarkers for diagnosis, prognosis, and tracking the effectiveness of treatments. Recent technological advancements, including mass spectrometry (MS)‐based proteomics, multiplexed proteomic assay using modified aptamers (SOMAscan), and Proximity Extension Assay (PEA, O‐Link), have allowed for the assessment of thousands of proteins in plasma or other biological matrices, which are potentially translatable into new clinical biomarkers and provide new clues about the mechanisms by which aging is associated with health deterioration and functional decline. We carried out a detailed literature search for proteomic studies performed in different matrices (plasma, serum, urine, saliva, tissues) and species using multiple platforms. Herein, we identified 232 proteins that were age‐associated across studies. Enrichment analysis of the 232 age‐associated proteins revealed metabolic pathways previously connected with biological aging both in animal models and in humans, most remarkably insulin‐like growth factor (IGF) signaling, mitogen‐activated protein kinases (MAPK), hypoxia‐inducible factor 1 (HIF1), cytokine signaling, Forkhead Box O (FOXO) metabolic pathways, folate metabolism, advance glycation end products (AGE), and receptor AGE (RAGE) metabolic pathway. Information on these age‐relevant proteins, likely expanded and validated in longitudinal studies and examined in mechanistic studies, will be essential for patient stratification and the development of new treatments aimed at improving health expectancy.

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Section: Methodsmentioning

confidence: 99%

Proteomics in aging research: A roadmap to clinical, translational research

et al. 2021

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“…We used 8 M urea to redissolve the proteins, and the protein concentration was determined by a BCA kit (Thermo Fisher Scientific, Waltham, MA, United States). Trypsin digestion and TMT labeling were conducted according to a previously published method ( Wang et al, 2019 ). Briefly, the same amount of protein from each sample was used for digestion.…”

Section: Methodsmentioning

confidence: 99%

Quantitative Transcriptomic and Proteomic Analysis of Fruit Development and Ripening in Watermelon (Citrullus lanatus)

Guo

Ren

et al. 2022

Front. Plant Sci.

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Fruit ripening is a highly complicated process, which is modulated by phytohormones, signal regulators and environmental factors playing in an intricate network that regulates ripening-related genes expression. Although transcriptomics is an effective tool to predict protein levels, protein abundances are also extensively affected by post-transcriptional and post-translational regulations. Here, we used RNA sequencing (RNA-seq) and tandem mass tag (TMT)-based quantitative proteomics to study the comprehensive mRNA and protein expression changes during fruit development and ripening in watermelon, a non-climacteric fruit. A total of 6,226 proteins were quantified, and the large number of quantitative proteins is comparable to proteomic studies in model organisms such as Oryza sativa L. and Arabidopsis. Base on our proteome methodology, integrative analysis of the transcriptome and proteome showed that the mRNA and protein levels were poorly correlated, and the correlation coefficients decreased during fruit ripening. Proteomic results showed that proteins involved in alternative splicing and the ubiquitin proteasome pathway were dynamically expressed during ripening. Furthermore, the spliceosome and proteasome were significantly enriched by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, suggesting that post-transcriptional and post-translational mechanisms might play important roles in regulation of fruit ripening-associated genes expression, which might account for the poor correlation between mRNAs and proteins during fruit ripening. Our comprehensive transcriptomic and proteomic data offer a valuable resource for watermelon research, and provide new insights into the molecular mechanisms underlying the complex regulatory networks of fruit ripening.

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“…The lowland controls were enrolled from Chengdu (∼400 m) with no visits to high-altitude areas in at least 3 years prior to this study. Individuals who had history of thrombus or hemorrhage, usage of oral anticoagulation therapy, HBV/HCV/HIV infection, acute infection, pregnancy, diabetes, cardiopathy, hepatic disease, renal insufficiency, and others were excluded from the present study by standardized questionnaire as we previously described. , According to our previous study, ,,, two tubes of blood sample of each subject (5 mL) were collected by venipuncture. One tube of blood sample was immediately for routine tests of ABO types, red blood cell count (RBC), hematocrit (Hct), hemoglobin (Hb), and platelet count (PLT).…”

Section: Methodsmentioning

confidence: 99%

Alterations of Human Plasma Proteome Profile on Adaptation to High-Altitude Hypobaric Hypoxia

Zhang

et al. 2019

J. Proteome Res.

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For individuals migrating to or residing permanently in high-altitude regions, environmental hypobaric hypoxia is a primary challenge that induces several physiological or pathological responses. It is well documented that human beings adapt to hypobaric hypoxia via some protective mechanisms, such as erythropoiesis and overproduction of hemoglobin; however, little is known on the alterations of plasma proteome profiles in accommodation to highaltitude hypobaric hypoxia. In the present study, we investigated differential plasma proteomes of high altitude natives and lowland normal controls by a TMT-based proteomic approach. A total of 818 proteins were identified, of which 137 were differentially altered. Bioinformatics (including GO, KEGG, protein−protein interactions, etc.) analysis showed that the differentially altered proteins were basically involved in complement and coagulation cascades, antioxidative stress, and glycolysis. Validation results demonstrated that CCL18, C9, PF4, MPO, and S100A9 were notably up-regulated, and HRG and F11 were down-regulated in high altitude natives, which were consistent with TMT-based proteomic results. Our findings highlight the contributions of complement and coagulation cascades, antioxidative stress, and glycolysis in acclimatization to hypobaric hypoxia and provide a foundation for developing potential diagnostic or/and therapeutic biomarkers for high altitude hypobaric hypoxia-induced diseases.

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TMT‐Based Quantitative Proteomic Analysis Reveals Proteomic Changes Involved in Longevity

Cited by 20 publications

References 41 publications

Proteomics in aging research: A roadmap to clinical, translational research

Proteomics in aging research: A roadmap to clinical, translational research

Quantitative Transcriptomic and Proteomic Analysis of Fruit Development and Ripening in Watermelon (Citrullus lanatus)

Alterations of Human Plasma Proteome Profile on Adaptation to High-Altitude Hypobaric Hypoxia

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