Analysis of the plasma proteome using iTRAQ and TMT‐based Isobaric labeling

Moulder, Robert; Bhosale, Santosh D.; Goodlett, David R.; Lahesmaa, Riitta

doi:10.1002/mas.21550

Cited by 122 publications

(90 citation statements)

References 231 publications

(503 reference statements)

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“…These tags permit multiplexing of several samples per LC-MS run, commonly 4, 6, 8, or 10 samples, but more are possible 91 . To learn more about the use of isobaric labeling for plasma proteomics, see review by Moulder et al, 92 and recent applications 37,93,94 . Multiplexing methods compensate for throughput concerns associated with large sample numbers and some plasma processing workflows (e.g., fractionation), enabling the combination of several samples 95,96 .…”

Section: Quantification Workflowsmentioning

confidence: 99%

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

et al. 2019

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The proteomic analyses of human blood and blood-derived products (e.g. plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g. inter-individual variability), analysis of biospecimen (e.g. sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest whilst enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.

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Section: Quantification Workflowsmentioning

confidence: 99%

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

et al. 2019

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“…The uterine fluid proteome was qualitatively very similar to serum, with highly abundant proteins including serum albumin, complement proteins, serotransferrin and alpha‐2‐macroglobulin (Wiktorowicz & Soman ; Moulder et al . ; Kuscuoglu et al . ).…”

Section: Resultsmentioning

confidence: 99%

Pre‐ and post‐puberty expression of genes and proteins in the uterus of Bos indicus heifers: the luteal phase effect post‐puberty

et al. 2018

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Progesterone signaling and uterine function are crucial in terms of pregnancy establishment. To investigate how the uterine tissue and its secretion changes in relation to puberty, we sampled tissue and uterine fluid from six pre- and six post-pubertal Brahman heifers. Post-pubertal heifers were sampled in the luteal phase. Gene expression of the uterine tissue was investigated with RNA-sequencing, whereas the uterine fluid was used for protein profiling with mass spectrometry. A total of 4034 genes were differentially expressed (DE) at a nominal P-value of 0.05, and 26 genes were significantly DE after Bonferroni correction (P < 3.1 × 10 ). We also identified 79 proteins (out of 230 proteins) that were DE (P < 1 × 10 ) in the uterine fluid. When we compared proteomics and transcriptome results, four DE proteins were identified as being encoded by DE genes: OVGP1, GRP, CAP1 and HBA. Except for CAP1, the other three had lower expression post-puberty. The function of these four genes hypothetically related to preparation of the uterus for a potential pregnancy is discussed in the context of puberty. All DE genes and proteins were also used in pathway and ontology enrichment analyses to investigate overall function. The DE genes were enriched for terms related to ribosomal activity. Transcription factors that were deemed key regulators of DE genes are also reported. Transcription factors ZNF567, ZNF775, RELA, PIAS2, LHX4, SOX2, MEF2C, ZNF354C, HMG20A, TCF7L2, ZNF420, HIC1, GTF3A and two novel genes had the highest regulatory impact factor scores. These data can help to understand how puberty influences uterine function.

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“…Proteomics, the study pertaining to protein products encoded and expressed by genes, is the way of understanding the interactions of protein molecules in the human body. Proteomics can, thus, reflect the dynamic changes in the physiological and pathological activities in the bodies [36]. The technology is currently being applied to understand several life phenomena that are unable to be explained at the genetic level.…”

Section: Discussionmentioning

confidence: 99%

Quantitative proteomics analysis of differentially expressed proteins induced by astragaloside IV in cervical cancer cell invasion

Xia

Cai

2020

Cell Mol Biol Lett

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Background: Cervical cancer remains the second leading cause of mortality in women in developing countries. While surgery, chemotherapy, radiotherapy, and vaccine therapy are being applied for its treatment, individually or in combination, the survival rate in advanced cervical cancer patients is still very low. Traditional Chinese medicine has been found to be effective in the treatment of cervical cancer. Astragaloside IV (AS-IV), a compound belonging to Astragalus polysaccharides, shows anticancer activity through several cell signaling pathways. However, the detailed molecular mechanism governing the anticancer activity of AS-IV remains unknown. Material and methods: In our study, we performed tumor xenograft analysis, transwell cell migration and invasion assay, Western blot analysis, and iTRAQ combination by parallel reaction monitoring (PRM) analysis to study the molecular mechanism of AS-IV in the suppression of cervical cancer cell invasion. Results: Our results showed that AS-IV suppressed cervical cancer cell invasion and induced autophagy in them, with the tumor growth curve increasing slowly. We also identified 32 proteins that were differentially expressed in the SiHa cells when treated with AS-IV, with 16 of them involved in the upregulation and 16 in the downregulation of these cells. These differentially expressed proteins, which were predominantly actinmyosin complexes, controlled cell proliferation and cell development by steroid binding and altering the composition of the cell cytoskeleton. DCP1A and TMSB4X, the two proteins regulating autophagy, increased in cervical cancer cells when treated with AS-IV. Conclusions: We conclude that AS-IV could inhibit cervical cancer invasion by inducing autophagy in cervical cancer cells. Since iTRAQ combination by PRM has been observed to be useful in identifying macromolecular target compounds, it may be considered as a novel strategy in the screening of anticancer compounds used in the treatment of cervical cancer.

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Analysis of the plasma proteome using iTRAQ and TMT‐based Isobaric labeling

Cited by 122 publications

References 231 publications

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

Pre‐ and post‐puberty expression of genes and proteins in the uterus of Bos indicus heifers: the luteal phase effect post‐puberty

Quantitative proteomics analysis of differentially expressed proteins induced by astragaloside IV in cervical cancer cell invasion

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