Document Detail


Spot identification and quality control in cell-based microarrays.
MedLine Citation:
PMID:  22850537     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Cell-based microarrays are being increasingly used as a tool for combinatorial and high throughput screening of cellular microenvironments. Analysis of microarrays requires several steps, including microarray imaging, identification of cell spots, quality control, and data exploration. While high content image analysis, cell counting, and cell pattern recognition methods are established, there is a need for new postprocessing and quality control methods for cell-based microarrays used to investigate combinatorial microenvironments. Previously, microarrayed cell spot identification and quality control were performed manually, leading to excessive processing time and potentially resulting in human bias. This work introduces an automated approach to identify cell-based microarray spots and spot quality control. The approach was used to analyze the adhesion of murine cardiac side population cells on combinatorial arrays of extracellular matrix proteins. Microarrays were imaged by automated fluorescence microscopy and cells were identified using open-source image analysis software (CellProfiler). From these images, clusters of cells making up single cell spots were reliably identified by analyzing the distances between cells using a density-based clustering algorithm (OPTICS). Naïve Bayesian classifiers trained on manually scored training sets identified good and poor quality spots using spot size, number of cells per spot, and cell location as quality control criteria. Combined, the approach identified 78% of high quality spots and 87% of poor quality spots. Full factorial analysis of the resulting microarray data revealed that collagen IV exhibited the highest positive effect on cell attachment. This data processing approach allows for fast and unbiased analysis of cell-based microarray data.
Authors:
Michael Bauer; Keekyoung Kim; Yiling Qiu; Blaise Calpe; Ali Khademhosseini; Ronglih Liao; Ian Wheeldon
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't     Date:  2012-08-01
Journal Detail:
Title:  ACS combinatorial science     Volume:  14     ISSN:  2156-8944     ISO Abbreviation:  ACS Comb Sci     Publication Date:  2012 Aug 
Date Detail:
Created Date:  2012-08-13     Completed Date:  2012-12-12     Revised Date:  2013-08-15    
Medline Journal Info:
Nlm Unique ID:  101540531     Medline TA:  ACS Comb Sci     Country:  United States    
Other Details:
Languages:  eng     Pagination:  471-7     Citation Subset:  IM    
Affiliation:
Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, United States. mihi@tentacleriot.eu
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MeSH Terms
Descriptor/Qualifier:
Animals
Cell Adhesion
Cell Separation
Combinatorial Chemistry Techniques
Extracellular Matrix / chemistry*
Humans
Mice
Quality Control
Tissue Array Analysis / methods*,  standards*
Grant Support
ID/Acronym/Agency:
HL099073/HL/NHLBI NIH HHS; R01 HL099073/HL/NHLBI NIH HHS
Comments/Corrections

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