Magnetic Silica‐Coated Fluorescent Microspheres (MagSiGlow) for Simultaneous Detection of Tumor‐Associated Proteins

Author:

Halabi Elias A.1ORCID,Gessner Isabel1ORCID,Yang Katherine S.1ORCID,Kim Jae‐Jun1ORCID,Jana Rupsa12ORCID,Peterson Hannah M.1ORCID,Spitzberg Joshua D.1ORCID,Weissleder Ralph13ORCID

Affiliation:

1. Center for Systems Biology Massachusetts General Hospital Harvard Medial School 185 Cambridge Street, CPZN 5206 02114 Boston MA USA

2. CaNCURE Cancer Nanomedicine Research Program Mugar Life Sciences Bldg Department of Biochemistry Northeastern University 330 Huntington Ave #203 02115 Boston MA USA

3. Department of Systems Biology Harvard Medical School 200 Longwood Ave 02115 Boston MA USA

Abstract

AbstractMultiplexed bead assays for solution‐phase biosensing often encounter cross‐over reactions during signal amplification steps, leading to unwanted false positive and high background signals. Current solutions involve complex custom‐designed and costly equipment, limiting their application in simple laboratory setup. In this study, we introduce a straightforward protocol to adapt a multiplexed single‐bead assay to standard fluorescence imaging plates, enabling the simultaneous analysis of thousands of reactions per plate. This approach focuses on the design and synthesis of bright fluorescent and magnetic microspheres (MagSiGlow) with multiple fluorescent wavelengths serving as unique detection markers. The imaging‐based, single‐bead assay, combined with a scripted algorithm, allows the detection, segmentation, and co‐localization on average of 7500 microspheres per field of view across five imaging channels in less than one second. We demonstrate the effectiveness of this method with remarkable sensitivity at low protein detection limits (100 pg/mL). This technique showed over 85 % reduction in signal cross‐over to the solution‐based method after the concurrent detection of tumor‐associated protein biomarkers. This approach holds the promise of substantially enhancing high throughput biosensing for multiple targets, seamlessly integrating with rapid image analysis algorithms.

Funder

National Cancer Institute

National Science Foundation

Deutsche Forschungsgemeinschaft

Publisher

Wiley

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