Molecular Memory in Voltage-Gated Lysenin Channels
Additional Funding Sources
The project described was supported by the Center of Excellence in Biomedical Research through the Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under Grant Nos. P20GM109095 and P20GM103408 and the National Science Foundation S-STEM Gateway Scholarships in Biological Sciences under Grant Award No. DUE-1644233. The project received additional support from the Center of Excellence in Biomedical Research through the Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under Grant Nos. P20GM109095 and P20GM103408 and the National Science Foundation S-STEM Gateway Scholarships in Biological Sciences under Grant Award No. DUE-1644233, and the National Science Foundation CAREER Grant No. 1551146.
Abstract
Memory in physical systems is often viewed as a property of electronic components and computers. However, any system dependent on past events can display memory, whether electronic or biophysical. One such system is that formed by lysenin, a pore-forming toxin with many unusual properties. Lysenin typically displays hysteresis at positive voltages; however, when exposed to copper, this effect becomes significantly more prominent. In this situation, the conductance of lysenin channels at zero applied voltage is dependent not only on outside stimuli, but also on their recent history. We measured this effect within an artificial planar bilayer lipid membrane by applying small AC voltages to channels at various voltage levels and states. Furthermore, we designed a Python script to analyze the resulting data, making it simpler to distinguish between the different memory states of our channels. Ultimately, we intend to create a full mathematical model based on differential memory equations to describe the behavior of lysenin channels.
Molecular Memory in Voltage-Gated Lysenin Channels
Memory in physical systems is often viewed as a property of electronic components and computers. However, any system dependent on past events can display memory, whether electronic or biophysical. One such system is that formed by lysenin, a pore-forming toxin with many unusual properties. Lysenin typically displays hysteresis at positive voltages; however, when exposed to copper, this effect becomes significantly more prominent. In this situation, the conductance of lysenin channels at zero applied voltage is dependent not only on outside stimuli, but also on their recent history. We measured this effect within an artificial planar bilayer lipid membrane by applying small AC voltages to channels at various voltage levels and states. Furthermore, we designed a Python script to analyze the resulting data, making it simpler to distinguish between the different memory states of our channels. Ultimately, we intend to create a full mathematical model based on differential memory equations to describe the behavior of lysenin channels.