An information theoretic approach to insulin sensing by human kidney podocytes

Abstract

Podocytes are key components of the glomerular filtration barrier (GFB). They are insulin-responsive but can become insulin-resistant, causing features of the leading global cause of kidney failure, diabetic nephropathy. Insulin acts via insulin receptors to control activities fundamental to GFB integrity, but the amount of information transferred is unknown. Here we measure this in human podocytes, using information theory-derived statistics that take into account cell-cell variability. High content imaging was used to measure insulin effects on Akt, FOXO and ERK. Mutual Information (MI) and Channel Capacity (CC) were calculated as measures of information transfer. We find that insulin acts via noisy communication channels with more information flow to Akt than to ERK. Information flow estimates were increased by consideration of joint sensing (ERK and Akt) and response trajectory (live cell imaging of FOXO1-clover translocation). Nevertheless, MI values were always <1Bit as most information was lost through signaling. Constitutive PI3K activity is a predominant feature of the system that restricts the proportion of CC engaged by insulin. Negative feedback from Akt supressed this activity and thereby improved insulin sensing, whereas sensing was robust to manipulation of feedforward signaling by inhibiting PI3K, PTEN or PTP1B. The decisions made by individual podocytes dictate GFB integrity, so we suggest that understanding the information on which the decisions are based will improve understanding of diabetic kidney disease and its treatment.