美国哈佛大学医学院Johan Paulsson、Scott Luro等研究人员合作开发出高通量、长时间、延时显微镜下的活细胞分离技术。相关论文于2019年11月25日在线发表在《自然—方法学》杂志上。

研究人员表示，单细胞遗传筛选功能十分强大，但是当前的高通量平台无法追踪动态过程，即使对于非动态特性，它们也难以将感兴趣的突变体与野生型群体的表型异常区分开。

研究人员开发了一个名为SIFT的技术，以解决这些限制。在严格控制的生长条件下连续数十代对单个细菌进行成像和跟踪后，将目标细胞分离并繁殖以进行下游分析，无污染且无遗传或生理扰动。该平台每天可表征成千上万个细胞谱系，从而无需条形码或遗传修饰即可准确筛选复杂的表型。

研究人员使用SIFT来识别一组超精密合成基因振荡，其回路变体跨越了平均周期的30倍范围。这揭示了合成生物学中新颖的设计原理，并证明了SIFT能够可靠地筛选各种动态表型的功能。

附：英文原文

Title: Isolating live cells after high-throughput, long-term, time-lapse microscopy

Author: Scott Luro, Laurent Potvin-Trottier, Burak Okumus, Johan Paulsson

Issue&Volume: 2019-11-25

Abstract: Single-cell genetic screens can be incredibly powerful, but current high-throughput platforms do not track dynamic processes, and even for non-dynamic properties they struggle to separate mutants of interest from phenotypic outliers of the wild-type population. Here we introduce SIFT, single-cell isolation following time-lapse imaging, to address these limitations. After imaging and tracking individual bacteria for tens of consecutive generations under tightly controlled growth conditions, cells of interest are isolated and propagated for downstream analysis, free of contamination and without genetic or physiological perturbations. This platform can characterize tens of thousands of cell lineages per day, making it possible to accurately screen complex phenotypes without the need for barcoding or genetic modifications. We applied SIFT to identify a set of ultraprecise synthetic gene oscillators, with circuit variants spanning a 30-fold range of average periods. This revealed novel design principles in synthetic biology and demonstrated the power of SIFT to reliably screen diverse dynamic phenotypes.

DOI: 10.1038/s41592-019-0620-7

Source: https://www.nature.com/articles/s41592-019-0620-7