Neurite outgrowth is an integrated whole cell response triggered by the cannabinoid-1 receptor. We sought to identify the many different biochemical pathways that contribute to this whole cell response. To understand underlying mechanisms, we identified subcellular processes (SCPs) composed of one or more biochemical pathways and their interactions required for this response. Differentially expressed genes and proteins were obtained from bulk transcriptomics and proteomic analysis of extracts from cells stimulated with a cannabinoid-1 receptor agonist. We used these differentially expressed genes and proteins to build networks of interacting SCPs by combining the expression data with prior pathway knowledge. From these SCP networks, we identified additional genes that when ablated, experimentally validated the SCP involvement in neurite outgrowth. Our experiments and informatics modeling allowed us to identify diverse SCPs such as those involved in pyrimidine metabolism, lipid biosynthesis, and mRNA splicing and stability, along with more predictable SCPs such as membrane vesicle transport and microtubule dynamics. We find that SCPs required for neurite outgrowth are widely distributed among many biochemical pathways required for constitutive cellular functions, several of which are termed ‘deep’, since they are distal to signaling pathways and the key SCPs directly involved in extension of the neurite. In contrast, ‘proximal’ SCPs are involved in microtubule growth and membrane vesicle transport dynamics required for neurite outgrowth. From these bioinformatics and dynamical models based on experimental data, we conclude that receptor-mediated regulation of subcellular functions for neurite outgrowth is both distributed, that is, involves many different biochemical pathways, and deep.

神经突生长是由大麻素-1 受体触发的综合全细胞反应。我们试图确定有助于这种全细胞反应的许多不同的生化途径。为了解潜在机制，我们确定了由一种或多种生化途径组成的亚细胞过程 (SCP) 及其响应所需的相互作用。从用大麻素-1 受体激动剂刺激的细胞提取物的大量转录组学和蛋白质组学分析中获得差异表达的基因和蛋白质。我们使用这些差异表达的基因和蛋白质，通过将表达数据与先前的通路知识相结合来构建相互作用的 SCP 网络。从这些 SCP 网络中，我们发现了额外的基因，当这些基因被消融时，通过实验验证了 SCP 参与了神经突的生长。我们的实验和信息学建模使我们能够识别各种 SCP，例如涉及嘧啶代谢、脂质生物合成、mRNA 剪接和稳定性的 SCP，以及更可预测的 SCP，例如膜囊泡运输和微管动力学。我们发现神经突长出所需的 SCP 广泛分布在构成细胞功能所需的许多生化途径中，其中一些被称为“深层”，因为它们远离信号通路和直接参与神经突延伸的关键 SCP。相反，“近端”SCP 参与微管生长和神经突长出所需的膜囊泡运输动力学。从这些基于实验数据的生物信息学和动力学模型，