Unifying Transcriptome Regulation and Cellular Operational Efficiency: Application of the Locality and Caching Principles via a Cell-to-Computer Analogy

Gene expression is time-consuming, and the delay from transcription activation to produced proteins is sequentially longer from bacteria to yeast and to humans. How human cells overcome the delay and attain operational efficiency, i.e., quick proteomic response to signals, is not well understood. The computer has endured the same system latency issue due to much slower information retrieval (hard drive (HD) to memory and to central processing unit (CPU)) than CPU execution, and mitigated it via efficient memory management, namely, the spatiotemporal locality principles that control specialized user programs and the permanent caching of core system functions – the operating system (OS) kernel. In this study, we unified gene expression and HD-memory-CPU information flow as instances of the Shannon information theory, that support the respective system operations and both consist of three components: information storage, the execution/decoding step, and the channel for the dynamic storage-to-execution information flow; the gene expression machinery and their regulators, and the OS kernel, were deemed as the respective channels. This abstraction prompted a multi-omic comparative analysis, leading to three observations. First, the temporal locality principle explains the mRNA stabilization-by-translation regulatory mechanism and controls specialized cellular functions. Second, the caching principle explains cytoplasmic mRNA sequestration and the defiance of the locality principle by highly sequestered mRNAs. Third, strikingly, in both systems, the caching principle controls the information channels; similar to permanent caching of OS kernel, basic gene expression machinery and their regulators are the top most sequestered mRNAs. In short, the locality and the caching principles act in the cells to control specialized and core cellular functions, respectively. The results close the knowledge gap between, and thus unify, transcriptome regulation and cellular operational latency mitigation.