With a range of desirable mechanical and optical properties, single wall carbon nanotubes (SWCNTs) are a promising material for nanobiotechnologies. SWCNTs also have potential as biomaterials for modulation of cellular structures. Previously, we showed that highly purified, dispersed SWCNTs grossly alter F-actin inside cells. F-actin plays critical roles in the maintenance of cell structure, force transduction, transport and cytokinesis. Thus, quantification of SWCNT-actin interactions ranging from molecular, sub-cellular and cellular levels with both structure and function is critical for developing SWCNT-based biotechnologies. Further, this interaction can be exploited, using SWCNTs as a unique actin-altering material. Here, we utilized molecular dynamics simulations to explore the interactions of SWCNTs with actin filaments. Fluorescence lifetime imaging microscopy confirmed that SWCNTs were located within ~5 nm of F-actin in cells but did not interact with G-actin. SWCNTs did not alter myosin II sub-cellular localization, and SWCNT treatment in cells led to significantly shorter actin filaments. Functionally, cells with internalized SWCNTs had greatly reduced cell traction force. Combined, these results demonstrate direct, specific SWCNT alteration of F-actin structures which can be exploited for SWCNT-based biotechnologies and utilized as a new method to probe fundamental actin-related cellular processes and biophysics.
In the biotechnology industry, a visual assessment is the most commonly used method for color characterization, batch release, and stability testing of liquid protein drug solutions. Using this method, an analyst visually determines the color of the sample by choosing the closest match to a standard color series. This visual method can be subjective because it requires an analyst to make a judgment of the best match of color of the sample to the standard color series, and it does not capture data on hue and chroma that would allow for improved product characterization and the ability to detect subtle differences between samples. To overcome these challenges, we developed a quantitative spectral method for color determination that greatly reduces the variability in measuring color and allows for a more precise understanding of color differences. The details of the spectral quantitative method are described. A comparison between the visual assessment method and spectral quantitative method is presented. This study supports the transition to a quantitative spectral method from the visual assessment method for quality testing of protein solutions.
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