Dataset Information

Data set for the mass spectrometry based exoproteome analysis of Aspergillus flavus isolates.

ABSTRACT: Aspergillus flavus is one of the predominant causative organisms of mycotic keratitis in tropical parts of the world. Extracellular proteins are the earliest proteins that come in contact with the host and have a role in the infection process. Exoproteins of A. flavus isolated from infected cornea, sputum and a saprophyte were pooled and identified using high resolution mass spectrometry in order to get the total exoproteome from cultures isolated from different sources. A total of 637 proteins was identified from the pooled A. flavus exoproteome. Analysis based on GO annotations of the 637 identified proteins revealed that hydrolases form the predominant class of proteins in the exoproteome. Interestingly, a greater proportion of the exoproteins seem to be secreted through the non-classical pathways. This data represent the first in-depth analysis of the representative A. flavus exoproteome of a large set of isolates from distinct sources. This data have been deposited to the ProteomeXchange with identifier PXD001296.

SUBMITTER: Muthu Selvam R

PROVIDER: S-EPMC4459775 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Data set for the mass spectrometry based exoproteome analysis of Aspergillus flavus isolates.

Muthu Selvam Ramu R Nithya Rathnavel R Narmatha Devi Palraj P Bhuvana Shree R S RS Valar Nila Murugesan M Demonte Naveen Luke NL Thangavel Chitra C Jeya Maheshwari Jayapal J Lalitha Prajna P Venkatesh Prajna Namperumalsamy N Dharmalingam Kuppamuthu K

Data in brief 20141215

Aspergillus flavus is one of the predominant causative organisms of mycotic keratitis in tropical parts of the world. Extracellular proteins are the earliest proteins that come in contact with the host and have a role in the infection process. Exoproteins of A. flavus isolated from infected cornea, sputum and a saprophyte were pooled and identified using high resolution mass spectrometry in order to get the total exoproteome from cultures isolated from different sources. A total of 637 proteins ...[more]

PMID: 26217704

Similar Datasets

Project description:BackgroundAssessing the reproducibility of measurements is an important first step for improving the reliability of downstream analyses of high-throughput metabolomics experiments. We define a metabolite to be reproducible when it demonstrates consistency across replicate experiments. Similarly, metabolites which are not consistent across replicates can be labeled as irreproducible. In this work, we introduce and evaluate the use (Ma)ximum (R)ank (R)eproducibility (MaRR) to examine reproducibility in mass spectrometry-based metabolomics experiments. We examine reproducibility across technical or biological samples in three different mass spectrometry metabolomics (MS-Metabolomics) data sets.ResultsWe apply MaRR, a nonparametric approach that detects the change from reproducible to irreproducible signals using a maximal rank statistic. The advantage of using MaRR over model-based methods that it does not make parametric assumptions on the underlying distributions or dependence structures of reproducible metabolites. Using three MS Metabolomics data sets generated in the multi-center Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPD) study, we applied the MaRR procedure after data processing to explore reproducibility across technical or biological samples. Under realistic settings of MS-Metabolomics data, the MaRR procedure effectively controls the False Discovery Rate (FDR) when there was a gradual reduction in correlation between replicate pairs for less highly ranked signals. Simulation studies also show that the MaRR procedure tends to have high power for detecting reproducible metabolites in most situations except for smaller values of proportion of reproducible metabolites. Bias (i.e., the difference between the estimated and the true value of reproducible signal proportions) values for simulations are also close to zero. The results reported from the real data show a higher level of reproducibility for technical replicates compared to biological replicates across all the three different datasets. In summary, we demonstrate that the MaRR procedure application can be adapted to various experimental designs, and that the nonparametric approach performs consistently well.ConclusionsThis research was motivated by reproducibility, which has proven to be a major obstacle in the use of genomic findings to advance clinical practice. In this paper, we developed a data-driven approach to assess the reproducibility of MS-Metabolomics data sets. The methods described in this paper are implemented in the open-source R package marr, which is freely available from Bioconductor at http://bioconductor.org/packages/marr .

Dataset Information

Data set for the mass spectrometry based exoproteome analysis of Aspergillus flavus isolates.

Publications

Data set for the mass spectrometry based exoproteome analysis of Aspergillus flavus isolates.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets