Memory in repetitive protein-protein interaction series

Aaron M. Rosado, Yan Zhang, Hyun Kyu Choi, Yunfeng Chen, Samuel M. Ehrlich, Fengzhi Jin, Arash Grakoui, Brian D. Evavold, Cheng Zhu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Interactions between proteins coordinate biological processes in an organism and may impact its responses to changing environments and diseases through feedback systems. Feedback systems function by using changes in the past to influence behaviors in the future, which we refer to here as memory. Here, we summarized several observations made, ideas conceptualized, and mathematical models developed for quantitatively analyzing memory effects in repetitive protein-protein interactions (PPIs). Specifically, we consider how proteins on the cell or in isolation retain information about prior interactions to impact current interactions. The micropipette, biomembrane force probe, and atomic force microscopic techniques were used to repeatedly assay PPIs. The resulting time series were analyzed by a previous and two new models to extract three memory indices of short (seconds), intermediate (minutes), and long (hours) timescales. We found that interactions of cell membrane, but not soluble, T cell receptor (TCR) with peptide-major histocompatibility complex (pMHC) exhibits short-term memory that impacts on-rate, but not off-rate of the binding kinetics. Peptide dissociation from MHC resulted in intermediate- and long-term memories in TCR-pMHC interactions. However, we observed no changes in kinetic parameters by repetitive measurements on living cells over intermediate timescales using stable pMHCs. Parameters quantifying memory effects in PPIs could provide additional information regarding biological mechanisms. The methods developed herein also provide tools for future research.

Original languageEnglish (US)
Article number016102
JournalAPL Bioengineering
Volume7
Issue number1
DOIs
StatePublished - Mar 1 2023
Externally publishedYes

ASJC Scopus subject areas

  • Bioengineering
  • Biophysics
  • Biomaterials
  • Biomedical Engineering

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