Substrates elicit different patterns of intracellular signaling which in turn cause differences in cell adhesion

Venkat Shankarraman, Miti M. Shah, Michael Caplan

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Although intracellular signal transduction is relatively well understood, how the cells can distinguish among thousands of micro-environments is not. This study proposes that a systems level view of intracellular signaling is necessary to interpret differences in cell interactions with different substrates. Human umbilical vein endothelial cells were exposed to 10 substrates (9 adsorbed extracellular matrix proteins and uncoated polystyrene), and the activities of 4 intracellular signaling kinases were quantified for cells on each substrate as a function of time. Principal component analysis demonstrates that each substrate elicits a different pattern of signaling. Mean activity of the 4 kinases can distinguish 44 of 45 possible pair-wise comparisons among the substrates. Partial Least Squares Regression Analysis is used to hypothesize causal relationships between signaling activity and cell adhesion or β1-integrin expression. Inhibition studies generally confirm that ERK (extracellular signalrelated kinase) and JNK (c-Jun N-terminal kinase) cause increased adhesion and β1-integrin expression. Inhibition of IKK (IκB kinase), on the other hand, showed no statistically significant effect on β1-integrin expression and led to significant decreases in cell adhesion-confirming a causal link but opposite of the hypothesized relationship (that inhibition of IKK would increase adhesion).

Original languageEnglish (US)
Pages (from-to)229-246
Number of pages18
JournalCellular and Molecular Bioengineering
Volume3
Issue number3
DOIs
StatePublished - Sep 2010

Keywords

  • Biocompatible materials
  • Endothelial cells
  • Extracellular matrix
  • Least-squares analysis
  • Principal component analysis
  • Signal transduction
  • Systems biology

ASJC Scopus subject areas

  • Modeling and Simulation
  • General Biochemistry, Genetics and Molecular Biology

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