Dataset Information

Large-scale identification of membrane proteins with properties favorable for crystallization.

ABSTRACT: Membrane protein crystallography is notoriously difficult due to challenges in protein expression and issues of degradation and structural stability. We have developed a novel method for large-scale screening of native sources for integral membrane proteins that have intrinsic biochemical properties favorable for crystallization. Highly expressed membrane proteins that are thermally stable and nonaggregating in detergent solutions were identified by mass spectrometry from Escherichia coli, Saccharomyces cerevisiae, and Sus scrofa cerebrum. Many of the membrane proteins identified had been crystallized previously, supporting the promise of the approach. Most identified proteins have known functions and include high-value targets such as transporters and ATPases. To validate the method, we recombinantly expressed and purified the yeast protein, Yop1, which is responsible for endoplasmic reticulum curvature. We demonstrate that Yop1 can be purified with the detergent dodecylmaltoside without aggregating.

SUBMITTER: Kim J

PROVIDER: S-EPMC4622209 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Large-scale identification of membrane proteins with properties favorable for crystallization.

Kim Jared J Kagawa Allison A Kurasaki Kellie K Ataie Niloufar N Cho Il Kyu IK Li Qing X QX Ng Ho Leung HL

Protein science : a publication of the Protein Society 20150827 11

Membrane protein crystallography is notoriously difficult due to challenges in protein expression and issues of degradation and structural stability. We have developed a novel method for large-scale screening of native sources for integral membrane proteins that have intrinsic biochemical properties favorable for crystallization. Highly expressed membrane proteins that are thermally stable and nonaggregating in detergent solutions were identified by mass spectrometry from Escherichia coli, Sacch ...[more]

PMID: 26257393

Similar Datasets

Project description:BACKGROUND: Attempts to reduce morbidity and mortality in breast cancer is based on efforts to identify novel biomarkers to support prognosis and therapeutic choices. The present study has focussed on S100 proteins as a potentially promising group of markers in cancer development and progression. One reason of interest in this family of proteins is because the majority of the S100 genes are clustered on a region of human chromosome 1q21 that is prone to genomic rearrangements. Moreover, there is increasing evidence that S100 proteins are often up-regulated in many cancers, including breast, and this is frequently associated with tumour progression. METHODS: Samples of breast cancer tissues were obtained during surgical intervention, according to the bioethical recommendations, and cryo-preserved until used. Tissue extracts were submitted to proteomic preparations for 2D-IPG. Protein identification was performed by N-terminal sequencing and/or peptide mass finger printing. RESULTS: The majority of the detected S100 proteins were absent, or present at very low levels, in the non-tumoral tissues adjacent to the primary tumor. This finding strengthens the role of S100 proteins as putative biomarkers. The proteomic screening of 100 cryo-preserved breast cancer tissues showed that some proteins were ubiquitously expressed in almost all patients while others appeared more sporadic. Most, if not all, of the detected S100 members appeared reciprocally correlated. Finally, from the perspective of biomarkers establishment, a promising finding was the observation that patients which developed distant metastases after a three year follow-up showed a general tendency of higher S100 protein expression, compared to the disease-free group. CONCLUSIONS: This article reports for the first time the comparative proteomic screening of several S100 protein members among a large group of breast cancer patients. The results obtained strongly support the hypothesis that a significant deregulation of multiple S100 protein members is associated with breast cancer progression, and suggest that these proteins might act as potential prognostic factors for patient stratification. We propose that this may offer a significant contribution to the knowledge and clinical applications of the S100 protein family to breast cancer.

Dataset Information

Large-scale identification of membrane proteins with properties favorable for crystallization.

Publications

Large-scale identification of membrane proteins with properties favorable for crystallization.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets