Spectroscopic characterization of protein-wrapped single-wall carbon nanotubes and quantification of their cellular uptake in multiple cell generations

We study the spectral characteristics of bovine serum albumin (BSA) protein conjugated single-wall carbon nanotubes (SWNTs), and quantify their uptake by macrophages. The binding of BSA onto the SWNT surface is found to change the protein structure and to increase the doping of the nanotubes. The G-band Raman intensity follows a well-defined power law for SWNT concentrations of up to 33 μg ml-1 in aqueous solutions. Subsequently, in vitro experiments demonstrate that incubation of BSA-SWNT complexes with macrophages affects neither the cellular growth nor the cellular viability over multiple cell generations. Using wide spot Raman spectroscopy as a fast, non-destructive method for statistical quantification, we observe that macrophages effectively uptake BSA-SWNT complexes, with the average number of nanotubes internalized per cell remaining relatively constant over consecutive cell generations. The number of internalized SWNTs is found to be ∼30 × 106 SWNTs/cell for a 60 mm-2 seeding density and ∼100 × 10 6 SWNTs/cell for a 200 mm-2 seeding density. Our results show that BSA-functionalized SWNTs are an efficient molecular transport system with low cytotoxicity maintained over multiple cell generations. © 2013 IOP Publishing Ltd.

Fundamental limits on the suppression of molecular fluctuations.

Negative feedback is common in biological processes and can increase a system's stability to internal and external perturbations. But at the molecular level, control loops always involve signalling steps with finite rates for random births and deaths of individual molecules. Here we show, by developing mathematical tools that merge control and information theory with physical chemistry, that seemingly mild constraints on these rates place severe limits on the ability to suppress molecular fluctuations. Specifically, the minimum standard deviation in abundances decreases with the quartic root of the number of signalling events, making it extremely expensive to increase accuracy. Our results are formulated in terms of experimental observables, and existing data show that cells use brute force when noise suppression is essential; for example, regulatory genes are transcribed tens of thousands of times per cell cycle. The theory challenges conventional beliefs about biochemical accuracy and presents an approach to the rigorous analysis of poorly characterized biological systems.