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基于聚集的微生物全细胞传感器分布式算法。

An Allee-based distributed algorithm for microbial whole-cell sensors.

机构信息

LMF, Université Paris-Saclay, CNRS, ENS Paris-Saclay, Gif-sur-Yvette, France.

LISN, Université Paris-Saclay, CNRS, Gif-sur-Yvette, France.

出版信息

NPJ Syst Biol Appl. 2024 Apr 22;10(1):43. doi: 10.1038/s41540-024-00363-3.

Abstract

Reliable detection of substances present at potentially low concentrations is a problem common to many biomedical applications. Complementary to well-established enzyme-, antibody-antigen-, and sequencing-based approaches, so-called microbial whole-cell sensors, i.e., synthetically engineered microbial cells that sense and report substances, have been proposed as alternatives. Typically these cells operate independently: a cell reports an analyte upon local detection.In this work, we analyze a distributed algorithm for microbial whole-cell sensors, where cells communicate to coordinate if an analyte has been detected. The algorithm, inspired by the Allee effect in biological populations, causes cells to alternate between a logical 0 and 1 state in response to reacting with the particle of interest. When the cells in the logical 1 state exceed a threshold, the algorithm converts the remaining cells to the logical 1 state, representing an easily-detectable output signal. We validate the algorithm through mathematical analysis and simulations, demonstrating that it works correctly even in noisy cellular environments.

摘要

可靠地检测潜在低浓度物质是许多生物医学应用中共同面临的问题。除了成熟的酶、抗体-抗原和测序方法外,所谓的微生物全细胞传感器(即合成工程微生物细胞,能够感知和报告物质)也被提出来作为替代方法。通常这些细胞独立运作:细胞在局部检测到分析物后报告。在这项工作中,我们分析了一种微生物全细胞传感器的分布式算法,其中细胞通过通信来协调是否检测到了分析物。该算法受到生物种群中的阿利效应的启发,导致细胞在与感兴趣的粒子反应时在逻辑 0 和 1 状态之间交替。当逻辑 1 状态的细胞超过阈值时,算法将其余细胞转换为逻辑 1 状态,代表一个易于检测的输出信号。我们通过数学分析和模拟验证了该算法,表明即使在嘈杂的细胞环境中它也能正常工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f19b/11035582/b5e2bd2d01c9/41540_2024_363_Fig1_HTML.jpg

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