Protein microarray

Résumé

A protein microarray (or protein chip) is a high-throughput method used to track the interactions and activities of proteins, and to determine their function, and determining function on a large scale. Its main advantage lies in the fact that large numbers of proteins can be tracked in parallel. The chip consists of a support surface such as a glass slide, nitrocellulose membrane, bead, or microtitre plate, to which an array of capture proteins is bound. Probe molecules, typically labeled with a fluorescent dye, are added to the array. Any reaction between the probe and the immobilised protein emits a fluorescent signal that is read by a laser scanner. Protein microarrays are rapid, automated, economical, and highly sensitive, consuming small quantities of samples and reagents. The concept and methodology of protein microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) in 1983 in a scientific publication and a series of patents.

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https://en.wikipedia.org/wiki/Protein_microarray

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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). Naive 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.

Amer Chemical Soc2012

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In the developing heart, a subset of endothelial cells (ECs) undergo a process of endothelial to mesenchymal transformation (EMT) that leads to the remodeling of the cardiac cushions and the formation of the cardiac valves. Understanding how microenvironmental cues regulate EMT has important implication for the treatment of congenital heart valve diseases and for heart valve tissue engineering. Here a set of extracellular matrix (ECM) proteins and growth factors (GF) were tested to determine the extent of regulation of EMT in adult ovine mitral valve endothelial cells (MVECs). Traditional cell culture dishes present limitations on large scale screening of cells-microenvironments interactions. To address this problem, a high throughput cellular microarray platform was developed. Using a contact printer, 84 different combinations of ECM proteins and GF were microarrayed on a modified glass slide. The slides were seeded with MVECs and immunostained against EMT maker alpha smooth muscle actin ([alpha]-SMA). Fluorescence images of each spot of the microarray were taken with a microscope equipped with an automated stage. These images were analyzed with a custom image processing routine developed with CellProfiler to assess the percentage of cells expressing [alpha]-SMA on each ECM combination.

2011

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Protein-binding microarrays: probing disease markers at the interface of proteomics and genomics

Tanja Egener-Kuhn, Jan Kerschgens, Nicolas Mermod

DNA-binding proteins mediate a variety of crucial molecular functions, such as transcriptional regulation and chromosome maintenance, replication and repair, which in turn control cell division and differentiation. The roles of these proteins in disease are currently being investigated using microarray-based approaches. However, these assays can be difficult to adapt to routine diagnosis of complex diseases such as cancer. Here, we review promising alternative approaches involving protein-binding microarrays (PBMs) that probe the interaction of proteins from crude cell or tissue extracts with large collections of synthetic or natural DNA sequences. Recent studies have demonstrated the use of these novel PBM approaches to provide rapid and unbiased characterization of DNA-binding proteins as molecular markers of disease, for example cancer progression or infectious diseases.

2009

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