27 research outputs found

    Preparation and characterization of protein-nanotube conjugates

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    This chapter describes methods of immobilizing proteins on carbon nanotubes, using two different routes—physical adsorption and covalent attachment. We also provide an overview on how such conjugates can be characterized with the help of various techniques, such as Raman, Fourier transform infrared (FT-IR), circular dichroism (CD), and fluorescence spectroscopies, in addition to the standard enzyme kinetic analyses of activity and stability. Both the attachment routes—covalent and noncovalent—could be used to prepare protein conjugates that retained a significant fraction of their native structure and function; furthermore, the protein conjugates were operationally stable, reusable, and functional even under harsh denaturing conditions. These studies therefore corroborate the use of these immobilization methods to engineer functional carbon nanotube-protein hybrids that are highly active and stable

    The protein–nanomaterial interface

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    Developments in the past few years have illustrated the potentially revolutionizing impact of nanomaterials, especially in biomedical imaging, drug delivery, biosensing and the design of functional nanocomposites. Methods to effectively interface proteins with nanomaterials for realizing these applications continue to evolve. Proteins are being used to control both the synthesis and assembly of nanomaterials. There has also been an increasing interest in understanding the influence of nanomaterials on the structure and function of proteins. Understanding and controlling the protein–nanomaterial interface will be crucial for designing functional protein–nanomaterial conjugates and assemblies

    Structure, Function, and Stability of Enzymes Covalently Attached to Single-Walled Carbon Nanotubes

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    We describe the structure, activity, and stability of enzymes covalently attached to single-walled carbon nanotubes (SWNTs). Conjugates of SWNTs with three functionally unrelated enzymeshorseradish peroxidase, subtilisin Carlsberg, and chicken egg white lysozymewere found to be soluble in aqueous solutions. Furthermore, characterization of the secondary and tertiary structure of the immobilized proteins by circular dichroism and fluorescence spectroscopies, respectively, and determination of enzyme kinetics revealed that the enzymes retained a high fraction of their native structure and activity upon attachment to SWNTs. The SWNT−enzyme conjugates were also more stable in guanidine hydrochloride (GdnHCl) and at elevated temperatures relative to their solution counterparts. Thus, these protein conjugates represent novel preparations that possess the attributes of both soluble enzymeshigh activity and low diffusional resistanceand immobilized enzymeshigh stabilitymaking them attractive choices for applications ranging from diagnostics and sensing to drug delivery

    Protein-Carbon Nanotube Conjugates

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    Proteins have been conjugated to carbon nanotubes for applications in biosensing, biorecognition, delivery, and functional composites. Despite the growing interest in these carbon nanotube-protein hybrids, very little is known about how carbon nanotubes affect the structure and function of bound proteins. Here we provide an overview of our recent efforts to gain a more fundamental understanding of how proteins interact with carbon nanotubes. We also discuss recent results from our laboratories which suggest several new opportunities for protein-carbon nanotube conjugates to address problems in materials science and biotechnology

    Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics

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    Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses
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