Simons Center for the Study of Living Machines, National Center for Biological Sciences - TIFR, Bangalore, India.
National Center for Biological Sciences - TIFR, Bangalore, India.
Elife. 2023 Mar 6;12:e79257. doi: 10.7554/eLife.79257.
Precise spatial patterning of cell fate during morphogenesis requires accurate inference of cellular position. In making such inferences from morphogen profiles, cells must contend with inherent stochasticity in morphogen production, transport, sensing and signalling. Motivated by the multitude of signalling mechanisms in various developmental contexts, we show how cells may utilise multiple tiers of processing (compartmentalisation) and parallel branches (multiple receptor types), together with feedback control, to bring about fidelity in morphogenetic decoding of their positions within a developing tissue. By simultaneously deploying specific and nonspecific receptors, cells achieve a more accurate and robust inference. We explore these ideas in the patterning of wing imaginal disc by Wingless morphogen signalling, where multiple endocytic pathways participate in decoding the morphogen gradient. The geometry of the inference landscape in the high dimensional space of parameters provides a measure for robustness and delineates and directions. This distributed information processing at the scale of the cell highlights how local cell autonomous control facilitates global tissue scale design.
形态发生过程中细胞命运的精确空间模式需要对细胞位置进行准确推断。在根据形态发生素图谱进行此类推断时,细胞必须应对形态发生素产生、运输、感应和信号传递中的固有随机性。受各种发育背景中众多信号机制的启发,我们展示了细胞如何利用多个处理层次(区室化)和并行分支(多种受体类型),以及反馈控制,在其在发育组织中的位置的形态发生解码中实现保真度。通过同时部署特异性和非特异性受体,细胞实现了更准确和稳健的推断。我们在 Wingless 形态发生素信号对翅膀图像盘的模式形成中探索了这些想法,其中多个内吞途径参与解码形态发生素梯度。在参数的高维空间中的推断景观的几何形状提供了稳健性的度量,并描绘了 和 方向。这种在细胞尺度上的分布式信息处理突出了局部细胞自主控制如何促进全局组织尺度设计。