Dataset Information

Molecular profiling of the human nasal epithelium: A proteomics approach.

ABSTRACT: A comprehensive proteomic profiling of nasal epithelium (NE) is described. This study relies on simple subcellular fractionation used to obtain soluble- and membrane-enriched fractions followed by 2-dimensional liquid chromatography (2D-LC) separation and tandem mass spectrometry (MS/MS). The cells were collected using a brushing technique applied on NE of clinically evaluated volunteers. Subsequently, the soluble- and the membrane-protein enriched fractions were prepared and analyzed in parallel using 2D-LC-MS/MS. In a set of 1482 identified proteins, 947 (63.9%) proteins were found to be associated to membrane fraction. Grand average hydropathy value index (GRAVY) analysis, the transmembrane protein mapping and annotations of primary location deposited in the Human Protein Reference Database (HPRD) confirmed an enrichment of hydrophobic proteins on this dataset. Ingenuity Pathway Analysis (IPA) of soluble fraction revealed an enrichment of molecular and cellular functions associated with cell death, protein folding and drug metabolism while in membrane fraction showed an enrichment of functions associated with molecular transport, protein trafficking and cell-to-cell signaling and interaction. The IPA showed similar enrichment of functions associated with cellular growth and proliferation in both soluble and membrane subproteomes. This finding was in agreement with protein content analysis using exponentially modified protein abundance index (emPAI). A comparison of our data with previously published studies focusing on respiratory tract epithelium revealed similarities related to identification of proteins associated with physical barrier function and immunological defence. In summary, we extended the NE molecular profile by identifying and characterizing proteins associated to pivotal functions of a respiratory epithelium, including the control of fluid volume and ionic composition at the airways' surface, physical barrier maintenance, detoxification and immunological defence. The extent of similarities supports the applicability of a less invasive analysis of NE to assess prognosis and treatment response of lung diseases such as asthma, cystic fibrosis and chronic obstructive pulmonary disease.

SUBMITTER: Simoes T

PROVIDER: S-EPMC7185466 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular profiling of the human nasal epithelium: A proteomics approach.

Simões Tânia T Charro Nuno N Blonder Josip J Faria Daniel D Couto Francisco M FM Chan King C KC Waybright Timothy T Isaaq Haleem J HJ Veenstra Timothy D TD Penque Deborah D

Journal of proteomics 20110518 1

A comprehensive proteomic profiling of nasal epithelium (NE) is described. This study relies on simple subcellular fractionation used to obtain soluble- and membrane-enriched fractions followed by 2-dimensional liquid chromatography (2D-LC) separation and tandem mass spectrometry (MS/MS). The cells were collected using a brushing technique applied on NE of clinically evaluated volunteers. Subsequently, the soluble- and the membrane-protein enriched fractions were prepared and analyzed in paralle ...[more]

PMID: 21621024

Similar Datasets

Project description:Dogs have an exquisite sense of olfaction. In many instances this ability has been utilized by humans for a wide range of important situations including detecting explosives and illegal drugs. It is accepted that some breeds have better senses of smell than others. Dogs can detect many volatile compounds at extremely low concentrations in air. To achieve such high levels of detection, the canine olfactory system is both complex and highly developed requiring a high density of olfactory receptors capable of detecting volatiles. Consequently the dog genome encodes a large number of olfactory receptor (OR) genes. However, it remains unclear as to what extent are all of these OR genes expressed on the cell surface. To facilitate such studies, a nasal brushing method was developed to recover dog nasal epithelial cell samples from which total RNA could be extracted and used to prepare high quality cDNA libraries. After capture by hybridization with an extensive set of oligonucleotides, the level of expression of each transcript was measured following next generation sequencing (NGS). The reproducibility of this sampling approach was checked by analyzing replicate samples from the same animal (up to 6 per each naris). The quality of the hybridization capture was also checked by analyzing two DNA libraries; this offered an advantage over RNA libraries by having an equal presence for each gene. Finally, we compared this brushing method performed on living dogs to a nasal epithelium biopsy approach applied to two euthanized terminally ill dogs, following consent from their owners.Comparison the expression levels of each transcript indicate that the ratios of expression between the highest and the least expressed OR in each sample are greater than 10,000 (paralog variation). Furthermore, it was clear that a number of OR genes are not expressed.The method developed and described here will allow researchers to further address whether variations observed in the OR transcriptome relate to dog 'life experiences' and whether any differences observed between samples are dog-specific or breed-specific.

Project description:Traditional proteomics analysis is plagued by the use of arbitrary thresholds resulting in large loss of information. We propose here a novel method in proteomics that utilizes all detected proteins. We demonstrate its efficacy in a proteomics screen of 5 and 7 liver cancer patients in the moderate and late stage, respectively. Utilizing biological complexes as a cluster vector, and augmenting it with submodules obtained from partitioning an integrated and cleaned protein-protein interaction network, we calculate a Proteomics Signature Profile (PSP) for each patient based on the hit rates of their reported proteins, in the absence of fold change thresholds, against the cluster vector. Using this, we demonstrated that moderate- and late-stage patients segregate with high confidence. We also discovered a moderate-stage patient who displayed a proteomics profile similar to other poor-stage patients. We identified significant clusters using a modified version of the SNet approach. Comparing our results against the Proteomics Expansion Pipeline (PEP) on which the same patient data was analyzed, we found good correlation. Building on this finding, we report significantly more clusters (176 clusters here compared to 70 in PEP), demonstrating the sensitivity of this approach. Gene Ontology (GO) terms analysis also reveals that the significant clusters are functionally congruent with the liver cancer phenotype. PSP is a powerful and sensitive method for analyzing proteomics profiles even when sample sizes are small. It does not rely on the ratio scores but, rather, whether a protein is detected or not. Although consistency of individual proteins between patients is low, we found the reported proteins tend to hit clusters in a meaningful and informative manner. By extracting this information in the form of a Proteomics Signature Profile, we confirm that this information is conserved and can be used for (1) clustering of patient samples, (2) identification of significant clusters based on real biological complexes, and (3) overcoming consistency and coverage issues prevalent in proteomics data sets.

Dataset Information

Molecular profiling of the human nasal epithelium: A proteomics approach.

Publications

Molecular profiling of the human nasal epithelium: A proteomics approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets