Single-point mutated lanmodulin as a high-performance MRI contrast agent for vascular and kidney imaging

Yuxia Liu, Duyang Gao, Yuanyuan He, Jing Ma, Suet Yen Chong, Xinyi Qi, Hui Jun Ting, Zichao Luo, Zhigao Yi, Jingyu Tang, Chao Chang, Jiongwei Wang, Zonghai Sheng (), Hairong Zheng () and Xiaogang Liu ()
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Yuxia Liu: National University of Singapore
Duyang Gao: Chinese Academy of Sciences
Yuanyuan He: Peking University
Jing Ma: Peking University
Suet Yen Chong: National University of Singapore
Xinyi Qi: National University of Singapore
Hui Jun Ting: National University of Singapore
Zichao Luo: National University of Singapore
Zhigao Yi: National University of Singapore
Jingyu Tang: National University of Singapore
Chao Chang: Peking University
Jiongwei Wang: National University of Singapore
Zonghai Sheng: Chinese Academy of Sciences
Hairong Zheng: Chinese Academy of Sciences
Xiaogang Liu: National University of Singapore

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: Abstract Magnetic resonance imaging contrast agents can enhance diagnostic precision but often face limitations such as short imaging windows, low tissue specificity, suboptimal contrast enhancement, or potential toxicity, which affect resolution and long-term monitoring. Here, we present a protein contrast agent based on lanmodulin, engineered with a single-point mutation at position 108 from N to D to yield maximum gadolinium binding sites. After loading with Gd3+ ions, the resulting protein complex, LanND-Gd, exhibits efficient renal clearance, high relaxivity, and prolonged renal retention compared to commercial agents. LanND-Gd enables high-performance visualization of whole-body structures and brain vasculature in male mice at a resolution finer than one hundred micrometers. In male ischemia mouse models, LanND-Gd also improves kidney dysfunction monitoring while minimizing risks of neural toxicity or immunogenic reactions. This protein-based contrast agent offers superior image quality, improved biocompatibility, and extended imaging timeframes, promising significant advancements in magnetic resonance-based diagnostics and patient outcomes.

Date: 2024
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DOI: 10.1038/s41467-024-54167-4

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