Two-dimensional gel electrophoresis (2D-GE) image analysis based on CellProfiler: Pseudomonas aeruginosa AG1 as model
artículo original
Fecha
2020Autor
Molina Mora, José Arturo
Chinchilla Montero, Diana
Castro Peña, Carolina
García Santamaría, Fernando
Metadatos
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Two-dimensional gel electrophoresis (2D-GE) is an indispensable technique for the study of proteomes of biological systems,
providing an assessment of changes in protein abundance under various experimental conditions. However, due to the complexity of
2D-GE gels, there is no systematic, automatic, and reproducible protocol for image analysis and specific implementations are
required for each context. In addition, practically all available solutions are commercial, which implies high cost and little flexibility to
modulate the parameters of the algorithms. Using the bacterial strain, Pseudomonas aeruginosaAG1 as a model, we obtained
images from 2D-GE of periplasmic protein profiles when the strain was exposed to multiple conditions, including antibiotics. Then, we
proceeded to implement and evaluate an image analysis protocol with open-source software, CellProfiler. First, a preprocessing step
included a bUnwarpJ-Image pipeline for aligning 2D-GE images. Then, using CellProfiler, we standardized two pipelines for spots
identification. Total spots recognition was achieved using segmentation by intensity, whose performance was evaluated when
compared with a reference protocol. In a second pipeline with the same program, differential identification of spots was addressed
when comparing pairs of protein profiles. Due to the characteristics of the programs used, our workflow can automatically analyze a
large number of images and it is parallelizable, which is an advantage with respect to other implementations. Finally, we compared six
experimental conditions of bacterial strain in the presence or absence of antibiotics, determining protein profiles relationships by
applying clustering algorithms PCA (Principal Components Analysis) and HC (Hierarchical Clustering).
External link to the item
10.1097/MD.0000000000023373Colecciones
- Microbiología [1171]