Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses.
10.3346/jkms.2012.27.10.1129
- Author:
Yu Rang PARK
1
;
Tae Su CHUNG
;
Young Joo LEE
;
Yeong Wook SONG
;
Eun Young LEE
;
Yeo Won SOHN
;
Sukgil SONG
;
Woong Yang PARK
;
Ju Han KIM
Author Information
1. Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, Korea. juhan@snu.ac.kr
- Publication Type:Original Article ; Research Support, Non-U.S. Gov't
- Keywords:
Prediction Model;
Microbial Infection;
DNA Microarray;
Mycoplasma
- MeSH:
Algorithms;
Cell Line;
Chondrocytes/cytology/metabolism/microbiology;
Databases, Genetic;
Gene Expression Profiling;
Host-Pathogen Interactions;
Humans;
Keratinocytes/cytology/metabolism/microbiology;
*Models, Genetic;
Mycoplasma/genetics/metabolism;
Oligonucleotide Array Sequence Analysis
- From:Journal of Korean Medical Science
2012;27(10):1129-1136
- CountryRepublic of Korea
- Language:English
-
Abstract:
Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI).
