Literature DB >> 21401847

Graph-based deconvolution analysis of multiplex sandwich microarray immunoassays: applications for environmental monitoring.

Luis A Rivas1, Jacobo Aguirre, Yolanda Blanco, Elena González-Toril, Víctor Parro.   

Abstract

The sandwich microarray immunoassay (SMI) is a powerful technique for the analysis and characterization of environmental samples, from the identification of microorganisms to specific bioanalytes. As the number of antibodies increases, however, unspecific binding and cross-reactivity can become a problem. To cope with such difficulties, we present here the concept of antibody graph associated to a sandwich antibody microarray. Antibody graphs give valuable information about the antibody cross-reactivity network and all the players involved in the sandwich format: capturing and tracer antibodies, the antigenic sample and the degree of cross-reactivity between antibodies. Making use of the information contained in the antibody graph, we have developed a deconvolution method that disentangles the antibody cross-reactivity events and gives qualitative information about the composition of the experimental sample under study. We have validated the method by using a 66 antibody-containing microarray to describe known antigenic mixtures as well as natural environmental samples characterized by 16S-RNA gene phylogenetic analysis. The application of our antibody graph and deconvolution method allowed us to discriminate between true specific antigen-antibody reactions and spurious signals on a microarray designed for environmental monitoring.
© 2011 Society for Applied Microbiology and Blackwell Publishing Ltd.

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Year:  2011        PMID: 21401847     DOI: 10.1111/j.1462-2920.2011.02442.x

Source DB:  PubMed          Journal:  Environ Microbiol        ISSN: 1462-2912            Impact factor:   5.491


  13 in total

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3.  Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip.

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Journal:  Astrobiology       Date:  2018-08-02       Impact factor: 4.335

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Journal:  PLoS One       Date:  2014-12-22       Impact factor: 3.240

8.  Simulating Mars Drilling Mission for Searching for Life: Ground-Truthing Lipids and Other Complex Microbial Biomarkers in the Iron-Sulfur Rich Río Tinto Analog.

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Journal:  Astrobiology       Date:  2020-01-09       Impact factor: 4.335

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10.  Microbial Markers Profile in Anaerobic Mars Analogue Environments Using the LDChip (Life Detector Chip) Antibody Microarray Core of the SOLID (Signs of Life Detector) Platform.

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Journal:  Microorganisms       Date:  2019-09-18
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