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Unifying Gene Expression Complexity and Cellular Operational Efficiency: Application of the Locality and Caching Principles via a Cell-to-Computer Analogy

Wen Jiang, Denis Feliers, W. Jim Zheng, Fangyuan Zhang, View ORCID ProfileDegeng Wang
doi: https://doi.org/10.1101/2022.01.11.475967
Wen Jiang
aDepartment of Environmental Toxicology, Texas Tech University, Lubbock, TX 79409
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Denis Feliers
dGenomics Institute of the Novartis Research Foundation, 10675 John Jay Hopkins Drive, San Diego, CA 92121
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W. Jim Zheng
eSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, TX 77030
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Fangyuan Zhang
cDepartment of Mathematics & Statistics, Texas Tech University, Lubbock, TX 79409
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Degeng Wang
aDepartment of Environmental Toxicology, Texas Tech University, Lubbock, TX 79409
bThe Institute of Environmental and Human Health (TIEHH), Texas Tech University, Lubbock, TX 79409
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  • ORCID record for Degeng Wang
  • For correspondence: degeng.wang@ttu.edu
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Abstract

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 bypass 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 CPU) than CPU execution, and mitigated it via efficient memory management, namely, the spatiotemporal locality principles that control specialized user functions and the permanent caching of core system functions – the operating system (OS) kernel. Thus, in this study, we unified gene expression and HD-memory-CPU information flow as instances of the Shannon information theory, both supporting the respective system operations and consisting 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, generating experimental evidence that transcriptome regulation shares the computer memory management principles. 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 translation/transcription machinery and their regulators are the top most sequestered mRNAs. Summarily, the locality and the caching principles differentially regulate specialized functions and core system functions, respectively, integrating the complexity of transcriptome regulation with cellular operational latency mitigation.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 13, 2022.
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Unifying Gene Expression Complexity and Cellular Operational Efficiency: Application of the Locality and Caching Principles via a Cell-to-Computer Analogy
Wen Jiang, Denis Feliers, W. Jim Zheng, Fangyuan Zhang, Degeng Wang
bioRxiv 2022.01.11.475967; doi: https://doi.org/10.1101/2022.01.11.475967
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Unifying Gene Expression Complexity and Cellular Operational Efficiency: Application of the Locality and Caching Principles via a Cell-to-Computer Analogy
Wen Jiang, Denis Feliers, W. Jim Zheng, Fangyuan Zhang, Degeng Wang
bioRxiv 2022.01.11.475967; doi: https://doi.org/10.1101/2022.01.11.475967

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