Dataset Information

Data mining strategies to improve multiplex microbead immunoassay tolerance in a mouse model of infectious diseases.

ABSTRACT: Multiplex methodologies, especially those with high-throughput capabilities generate large volumes of data. Accumulation of such data (e.g., genomics, proteomics, metabolomics etc.) is fast becoming more common and thus requires the development and implementation of effective data mining strategies designed for biological and clinical applications. Multiplex microbead immunoassay (MMIA), on xMAP or MagPix platform (Luminex), which is amenable to automation, offers a major advantage over conventional methods such as Western blot or ELISA, for increasing the efficiencies in serodiagnosis of infectious diseases. MMIA allows detection of antibodies and/or antigens efficiently for a wide range of infectious agents simultaneously in host blood samples, in one reaction vessel. In the process, MMIA generates large volumes of data. In this report we demonstrate the application of data mining tools on how the inherent large volume data can improve the assay tolerance (measured in terms of sensitivity and specificity) by analysis of experimental data accumulated over a span of two years. The combination of prior knowledge with machine learning tools provides an efficient approach to improve the diagnostic power of the assay in a continuous basis. Furthermore, this study provides an in-depth knowledge base to study pathological trends of infectious agents in mouse colonies on a multivariate scale. Data mining techniques using serodetection of infections in mice, developed in this study, can be used as a general model for more complex applications in epidemiology and clinical translational research.

SUBMITTER: Mani A

PROVIDER: S-EPMC4304816 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Data mining strategies to improve multiplex microbead immunoassay tolerance in a mouse model of infectious diseases.

Mani Akshay A Ravindran Resmi R Mannepalli Soujanya S Vang Daniel D Luciw Paul A PA Hogarth Michael M Khan Imran H IH Krishnan Viswanathan V VV

PloS one 20150123 1

Multiplex methodologies, especially those with high-throughput capabilities generate large volumes of data. Accumulation of such data (e.g., genomics, proteomics, metabolomics etc.) is fast becoming more common and thus requires the development and implementation of effective data mining strategies designed for biological and clinical applications. Multiplex microbead immunoassay (MMIA), on xMAP or MagPix platform (Luminex), which is amenable to automation, offers a major advantage over conventi ...[more]

PMID: 25614982

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Project description:Precise monitoring of the rapidly changing immune status during the course of a disease requires multiplex analysis of cytokines from frequently sampled human blood. However, the current lack of rapid, multiplex, and low volume assays makes immune monitoring for clinical decision-making (e.g., critically ill patients) impractical. Without such assays, immune monitoring is even virtually impossible for infants and neonates with infectious diseases and/or immune mediated disorders as access to their blood in large quantities is prohibited. Localized surface plasmon resonance (LSPR)-based microfluidic optical biosensing is a promising approach to fill this technical gap as it could potentially permit real-time refractometric detection of biomolecular binding on a metallic nanoparticle surface and sensor miniaturization, both leading to rapid and sample-sparing analyte analysis. Despite this promise, practical implementation of such a microfluidic assay for cytokine biomarker detection in serum samples has not been established primarily due to the limited sensitivity of LSPR biosensing. Here, we developed a high-throughput, label-free, multiarrayed LSPR optical biosensor device with 480 nanoplasmonic sensing spots in microfluidic channel arrays and demonstrated parallel multiplex immunoassays of six cytokines in a complex serum matrix on a single device chip while overcoming technical limitations. The device was fabricated using easy-to-implement, one-step microfluidic patterning and antibody conjugation of gold nanorods (AuNRs). When scanning the scattering light intensity across the microarrays of AuNR ensembles with dark-field imaging optics, our LSPR biosensing technique allowed for high-sensitivity quantitative cytokine measurements at concentrations down to 5-20 pg/mL from a 1 μL serum sample. Using the nanoplasmonic biosensor microarray device, we demonstrated the ability to monitor the inflammatory responses of infants following cardiopulmonary bypass (CPB) surgery through tracking the time-course variations of their serum cytokines. The whole parallel on-chip assays, which involved the loading, incubation, and washing of samples and reagents, and 10-fold replicated multianalyte detection for each sample using the entire biosensor arrays, were completed within 40 min.

Dataset Information

Data mining strategies to improve multiplex microbead immunoassay tolerance in a mouse model of infectious diseases.

Publications

Data mining strategies to improve multiplex microbead immunoassay tolerance in a mouse model of infectious diseases.

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