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1921 KiB

Open AccessArticle

Serology in the Digital Age: Using Long Synthetic Peptides Created from Nucleic Acid Sequences as Antigens in Microarrays

by Muhammad Rizwan, Bengt Rönnberg, Maksims Cistjakovs, Åke Lundkvist, Rudiger Pipkorn and Jonas Blomberg

Microarrays 2016, 5(3), 22; https://doi.org/10.3390/microarrays5030022 - 10 Aug 2016

Cited by 6 | Viewed by 4948

Abstract

Background: Antibodies to microbes, or to autoantigens, are important markers of disease. Antibody detection (serology) can reveal both past and recent infections. There is a great need for development of rational ways of detecting and quantifying antibodies, both for humans and animals. Traditionally, [...] Read more.

Background: Antibodies to microbes, or to autoantigens, are important markers of disease. Antibody detection (serology) can reveal both past and recent infections. There is a great need for development of rational ways of detecting and quantifying antibodies, both for humans and animals. Traditionally, serology using synthetic antigens covers linear epitopes using up to 30 amino acid peptides. Methods: We here report that peptides of 100 amino acids or longer (“megapeptides”), designed and synthesized for optimal serological performance, can successfully be used as detection antigens in a suspension multiplex immunoassay (SMIA). Megapeptides can quickly be created just from pathogen sequences. A combination of rational sequencing and bioinformatic routines for definition of diagnostically-relevant antigens can, thus, rapidly yield efficient serological diagnostic tools for an emerging infectious pathogen. Results: We designed megapeptides using bioinformatics and viral genome sequences. These long peptides were tested as antigens for the presence of antibodies in human serum to the filo-, herpes-, and polyoma virus families in a multiplex microarray system. All of these virus families contain recently discovered or emerging infectious viruses. Conclusion: Long synthetic peptides can be useful as serological diagnostic antigens, serving as biomarkers, in suspension microarrays. Full article

(This article belongs to the Special Issue High-Throughput Microarray for Protein Biomarker Discovery)

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Review

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363 KiB

Open AccessReview

Aptamer-Based Screens of Human Body Fluids for Biomarkers

by Dania Albaba, Sanam Soomro and Chandra Mohan

Microarrays 2015, 4(3), 424-431; https://doi.org/10.3390/microarrays4030424 - 22 Sep 2015

Cited by 8 | Viewed by 4969

Abstract

In recent years, aptamers have come to replace antibodies in high throughput multiplexed experiments. The aptamer-based biomarker screening technology, which kicked off in 2010, is capable of interrogating thousands of proteins in a very small sample volume. With this new technology, researchers hope [...] Read more.

In recent years, aptamers have come to replace antibodies in high throughput multiplexed experiments. The aptamer-based biomarker screening technology, which kicked off in 2010, is capable of interrogating thousands of proteins in a very small sample volume. With this new technology, researchers hope to find clinically appropriate biomarkers for a myriad of illnesses by screening human body fluids. In this work, we have reviewed a total of eight studies utilizing aptamer-based biomarker screens of human body fluids, and have highlighted novel protein biomarkers discovered. Full article

(This article belongs to the Special Issue High-Throughput Microarray for Protein Biomarker Discovery)

1263 KiB

Open AccessReview

Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

by Christopher J. Walsh, Pingzhao Hu, Jane Batt and Claudia C. Dos Santos

Microarrays 2015, 4(3), 389-406; https://doi.org/10.3390/microarrays4030389 - 21 Aug 2015

Cited by 67 | Viewed by 11673

Abstract

The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature [...] Read more.

The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers. Full article

(This article belongs to the Special Issue High-Throughput Microarray for Protein Biomarker Discovery)

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