Type 1 diabetes cadaveric human pancreata exhibit a unique exocrine tissue proteomic profile

Li, Youfu; Atkinson, Mark A.; Zhang, Qibin

doi:10.1002/pmic.201500333

Cited by 21 publications

(21 citation statements)

References 78 publications

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“…Mobile phases A and B consisted of 10 mM ammonium formate in water (pH 10) and 90% ACN (pH 10), respectively. Ninety six fractions were collected and concatenated into 24 fractions [17, 18]. Peptide solutions were dried, stored at −80 °C, and reconstituted in 0.1% FA until LC-MS/MS analysis.…”

Section: Methodsmentioning

confidence: 99%

Temporal profiles of plasma proteome during childhood development

Bramer

Webb-Robertson

et al. 2017

Journal of Proteomics

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Human blood plasma proteome reflects physiological changes associated with a child’s development as well as development of disease states. While age-specific normative values are available for proteins routinely measured in clinical practice, there is paucity of comprehensive longitudinal data regarding changes in human plasma proteome during childhood. We applied TMT-10plex isobaric labeling-based quantitative proteomics to longitudinally profile the plasma proteome in 10 healthy children during their development, each with 9 serial time points from 9 months to 15 years of age. In total, 1828 protein groups were identified at peptide and protein level false discovery rate of 1% and with at least two razor and unique peptides. The longitudinal expression profiles of 1747 protein groups were statistically modeled and their temporal changes were categorized into 7 different patterns. The patterns and relative abundance of proteins obtained by LC-MS were also verified with ELISA. To our knowledge, this study represents the most comprehensive longitudinal profiling of human plasma proteome to date. The temporal profiles of plasma proteome obtained in this study provide a comprehensive resource and reference for biomarker studies in childhood diseases.

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Section: Methodsmentioning

confidence: 99%

Temporal profiles of plasma proteome during childhood development

Bramer

Webb-Robertson

et al. 2017

Journal of Proteomics

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“…In fact, the workflow used has generated one of the largest datasets to date with the Q-Exactive Plus. As a comparison, in a study delineating the proteomes of pancreatic tissue specimens from controls and Type 1 diabetic patients, approximately 5500 unique proteins were identified using a similar workflow on the Q-Exactive Plus ( Liu et al , 2016). …”

Section: Discussionmentioning

confidence: 99%

Unraveling endometriosis-associated ovarian carcinomas using integrative proteomics

et al. 2018

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Background: To elucidate potential markers of endometriosis and endometriosis-associated endometrioid and clear cell ovarian carcinomas using mass spectrometry-based proteomics. Methods: A total of 21 fresh, frozen tissues from patients diagnosed with clear cell carcinoma, endometrioid carcinoma, endometriosis and benign endometrium were subjected to an in-depth liquid chromatography-tandem mass spectrometry analysis on the Q-Exactive Plus. Protein identification and quantification were performed using MaxQuant, while downstream analyses were performed using Perseus and various bioinformatics databases. Results: Approximately 9000 proteins were identified in total, representing the first in-depth proteomic investigation of endometriosis and its associated cancers. This proteomic data was shown to be biologically sound, with minimal variation within patient cohorts and recapitulation of known markers. While moderate concordance with genomic data was observed, it was shown that such data are limited in their abilities to represent tumours on the protein level and to distinguish tumours from their benign precursors. Conclusions: The proteomic data suggests that distinct markers may differentiate endometrioid and clear cell carcinoma from endometriosis. These markers may be indicators of pathobiology but will need to be further investigated. Ultimately, this dataset may serve as a basis to unravel the underlying biology of the endometrioid and clear cell cancers with respect to their endometriotic origins.

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“…This method could be applied to study the in situ islet proteome and to “take a snapshot” of the pathophysiological mechanism underlying islet and β-cell dysfunction in Type 1 Diabetes. In addition, the exocrine pancreas was reported to be involved in the pathogenesis of T1D [43, 44] and the method we propose enables proteomic analysis of purified pancreatic acinar tissue without enzymatic isolation. Previous studies on the cellular function of the pancreas were typically performed in vitro on two enzymatically isolated and separated functional units: the endocrine islets of Langerhans and the exocrine pancreatic acinar tissue [11, 45, 46].…”

Section: Discussionmentioning

confidence: 99%

Proteomic profiling of human islets collected from frozen pancreata using laser capture microdissection

Zhang

Lanzoni

Battarra

et al. 2017

Journal of Proteomics

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The etiology of Type 1 Diabetes (T1D) remains elusive. Enzymatically isolated and cultured (EIC) islets cannot fully reflect the natural protein composition and disease process of in vivo islets, because of the stress from isolation procedures. In order to study islet protein composition in conditions close to the natural environment, we performed proteomic analysis of EIC islets, and laser capture microdissected (LCM) human islets and acinar tissue from fresh-frozen pancreas sections of three cadaveric donors. 1104 and 706 proteins were identified from 6 islets equivalents (IEQ) of LCM islets and acinar tissue, respectively. The proteomic profiles of LCM islets were reproducible within and among cadaveric donors. The endocrine hormones were only detected in LCM islets, whereas catalytic enzymes were significantly enriched in acinar tissue. Furthermore, high overlap (984 proteins) and similar function distribution were found between LCM and EIC islets proteomes, except that EIC islets had more acinar contaminants and stress-related signal transducer activity proteins. The comparison among LCM islets, LCM acinar tissue and EIC islets proteomes indicates that LCM combined with proteomic methods enables accurate and unbiased profiling of islet proteome from frozen pancreata. This paves the way for proteomic studies on human islets during the progression of T1D.

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Type 1 diabetes cadaveric human pancreata exhibit a unique exocrine tissue proteomic profile

Cited by 21 publications

References 78 publications

Temporal profiles of plasma proteome during childhood development

Temporal profiles of plasma proteome during childhood development

Unraveling endometriosis-associated ovarian carcinomas using integrative proteomics

Proteomic profiling of human islets collected from frozen pancreata using laser capture microdissection

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