Quantum sensing of Lanthandie binding tags with relaxometer of NV center in diamond
Zibo Gao (1,2,3), Zhengzhi Jiang (4), Qiyu Liang (1,5), Ruihua He (1,5), Van Cuong Mai (6), Yingwei Tang (6), Qirong Xiong (6), Wenting Zhao (6), Hongwei Duan (6), Hongliang Sun (7), Mo Li (2,3), Yansong Miao (5,8), Weibo Gao (1,9,10) ((1) Division of Physics, Applied Physics

TL;DR
This paper demonstrates a novel magnetic detection method using NV centers in diamond to identify lanthanide binding tags and their interactions with biological targets, achieving high sensitivity at femtomole and picomole levels.
Contribution
It introduces a relaxometry-based detection scheme for LBTs with NV centers, enabling sensitive magnetic detection of biomolecular interactions.
Findings
Detection limit of 25 fmol for LBTs.
Detection threshold of ~1 pmol for LBT-RBD interaction.
Potential for biomarker detection at picomole concentrations.
Abstract
Lanthanide binding tags (LBTs) stand out as a prominent group of fluorescent probes that are extensively utilized in biological detection. However, research on LBTs has predominantly emphasized their fluorescence properties, which frequently compromised by background fluorescence noise. Investigating magnetic properties could optimize detection methodologies that offer enhanced sensitivity and specificity. In this study, we measured the response of a relaxometer based on ensemble nitrogen-vacancy (NV) centers in diamond to various amounts of LBTs with gadolinium ions, determining the detection limit of LBTs to be 25 fmol. We then proposed and demonstrated a detection scheme employing the NV relaxometer to detect specific binding between LBTs and target. Specifically, we assessed the relaxometer's response to various concentrations of the interaction between the modified LBTs and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
