Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses
Journal of Korean Medical Science
;
: 1129-1136, 2012.
Artigo
em Inglês
| WPRIM
| ID: wpr-161072
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).
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Algoritmos
/
Queratinócitos
/
Linhagem Celular
/
Condrócitos
/
Análise de Sequência com Séries de Oligonucleotídeos
/
Perfilação da Expressão Gênica
/
Bases de Dados Genéticas
/
Interações Hospedeiro-Patógeno
/
Modelos Genéticos
/
Mycoplasma
Tipo de estudo:
Estudo prognóstico
Limite:
Humanos
Idioma:
Inglês
Revista:
Journal of Korean Medical Science
Ano de publicação:
2012
Tipo de documento:
Artigo
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