Dynamics of Drosophila endoderm specification.
Dynamics of Drosophila endoderm specification.
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DOI：
10.1073/pnas.2112892119
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发表时间：
2022-04-12
影响因子：
11.1
通讯作者：
中科院分区：
文献类型：
--
作者：
为了了解生物体的发育模式，有必要准确测量基因调控网络的状态如何随时间变化。提取网络动态的一种方式涉及同时对固定组织内的几个报告子进行成像。从这样的数据重建动态需要随着时间的推移分期许多样本，往往导致低的时间分辨率。荧光转录报告的延时显微镜技术彻底改变了单细胞水平上的生物动力学研究。然而，这种方法受到一次可以成像的报告子数量的限制。我们提出了一种计算方法来解决这个问题，并通过建模果蝇后部图案化的基因调控网络和重建其发育动力学来展示其应用。在早期果蝇胚胎发育过程中，基因调控相互作用网络协调了末端模式，在随后的肠道形成中发挥了关键作用。我们利用内源基因座的CRISPR基因编辑来创建转录的活报告基因，并利用光片显微镜来监测原肠胚形成前90分钟内后肠模式网络的各个组成部分。我们开发了一种计算方法，用于将各个组件的成像数据集融合到一个共同的多变量轨迹中。数据融合揭示了野生型胚胎后图案化和细胞命运规范的低内在维度。我们发现的简单结构使我们能够在后模式调控网络中构建一个相互作用模型，并在蛋白质水平上对其动态进行可测试的预测。所提出的数据融合策略是朝着建立一个统一的框架，将探讨如何随机时空信号产生高度可重复的形态发生的结果。
To understand developmental patterning of an organism, it is necessary to accurately measure how the state of a gene regulatory network is changing over time. One way of extracting dynamics of a network involves simultaneously imaging several reporters within fixed tissue. Reconstructing dynamics from such data requires staging many samples over time and often leads to low temporal resolution. Time-lapse microscopy of fluorescent transcriptional reporters has revolutionized studies of biological dynamics at the single-cell level. However, this method is limited by the number of reporters that can be imaged at one time. We present a computational method for addressing this problem and demonstrate its application by modeling the gene regulatory network underlying Drosophila posterior patterning and reconstructing its developmental dynamics. During early Drosophila embryogenesis, a network of gene regulatory interactions orchestrates terminal patterning, playing a critical role in the subsequent formation of the gut. We utilized CRISPR gene editing at endogenous loci to create live reporters of transcription and light-sheet microscopy to monitor the individual components of the posterior gut patterning network across 90 min prior to gastrulation. We developed a computational approach for fusing imaging datasets of the individual components into a common multivariable trajectory. Data fusion revealed low intrinsic dimensionality of posterior patterning and cell fate specification in wild-type embryos. The simple structure that we uncovered allowed us to construct a model of interactions within the posterior patterning regulatory network and make testable predictions about its dynamics at the protein level. The presented data fusion strategy is a step toward establishing a unified framework that would explore how stochastic spatiotemporal signals give rise to highly reproducible morphogenetic outcomes.
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Llamatags：在活胚胎中图像转录因子动力学的多功能工具。
影响因子：
64.5
作者：
Bothma JP;Norstad MR;Alamos S;Garcia HG
通讯作者：
Garcia HG
影响因子：
4.5
作者：
Harder MJ;Hix J;Reeves WM;Veeman MT
通讯作者：
Veeman MT
DOI：
10.1109/34.121791
发表时间：
1992-02-01
影响因子：
23.6
作者：
BESL, PJ;MCKAY, ND
通讯作者：
MCKAY, ND
影响因子：
4.6
作者：
Ajuria, Leiore;Nieva, Claudia;Jimenez, Gerardo
通讯作者：
Jimenez, Gerardo
DOI：
10.1073/pnas.0401654101
发表时间：
2004-05-18
影响因子：
11.1
作者：
Chawengsaksophak, K;de Graaff, W;Beck, F
通讯作者：
Beck, F