Source abstract
Abstract
Anionic and cationic lipids are key molecules involved in many cellular processes; their distribution in biomembranes is highly asymmetric, and their concentration is well-controlled. Graphene solution-gated field-effect transistors (SGFETs) exhibit high sensitivity toward the presence of surface charges. Here, we establish conditions that allow the observation of the formation of charged lipid layers on solution-gated field-effect transistors in real time. We quantify the electrostatic screening of electrolyte ions and derive a model that explains the influence of charged lipids on the ion sensitivity of graphene SGFETs. The electrostatic model is validated using structural information from X-ray reflectometry measurements, which show that the lipid monolayer forms on graphene. We demonstrate that SGFETs can be used to detect cationic lipids by self-exchange of lipids. Furthermore, SGFETs allow measuring the kinetics of layer formation induced by vesicle fusion or spreading from a reservoir. Because of the high transconductance and low noise of the electrical readout, we can observe characteristic conductance spikes that we attribute to bouncing-off events of lipid aggregates from the SGFET surface, suggesting a great potential of graphene SGFETs to measure the on-off kinetics of small aggregates interacting with supported layers.
Source: openalex_inverted_index · Quality: baseline
Affiliations
Walter Schottky Institut und Physik-Department, Technische Universität München, Am Coulombwall 4, 85748 Garching, Germany
Fakultät für Physik and Center for NanoScience, Ludwig-Maximilians-Universität, Geschwister-Scholl-Platz 1, 80539 München, Germany
Nanosystems Initiative Munich, Schellingstraße 4, 80799 München, Germany
Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and The Barcelona Institute of Science and Technology, Campus UAB, Bellaterra, 08193 Barcelona, Spain
ICREA, Pg. Lluís Companys 23, 08010 Barcelona, Spain
Funding
Bundesministerium f?r Bildung und Forschung · Deutsche Forschungsgemeinschaft · Horizon 2020 Framework Programme