Genetically-tunable morphology and mechanical properties of bacterial functional amyloid nanofibers

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2017-05

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Baykara, Mehmet Zeyyad

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Bilkent University

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English

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Abstract

The highly dynamic behavior of material systems exploited by nature results in research efforts to employ them as next generation biomaterials exhibiting sustainability and resistance against harsh environmental conditions. In recent years, functional protein-based structures started to be investigated heavily. Among these, bacterial biofilms present themselves as highly organized, hierarchical, dynamic material systems comprising cells, various carbohydrates, and extracellular proteins. They are known to be resistant against different kinds of disruptions by chemical, physical, and biological agents. These fascinating qualities make them potential candidates for next generation biomaterials. Motivated as above, we present in this M.S. thesis a comprehensive study of the morphological and mechanical properties (in terms of Young’s modulus) of biofilm structures assembled from bacterial amyloid nanofibers of Escherichia coli (E. coli) via imaging and force spectroscopy performed by the atomic force microscope (AFM). We used techniques adopted from genetic engineering to employ different E. coli mutants, allowing comparisons of Young’s modulus and morphology of different biofilm nanofibers based on genetic composition. In particular, we tuned the genetic expression of the major (CsgA) and minor (CsgB) proteins constituting bacterial amyloid nanofibers, with the optional addition of certain amino acid tags in order to have multiple controlled versions of biofilm nanofibers. After sample preparation, we calibrated a single AFM probe to be used for all experiments, and performed contact-mode imaging measurements to probe the morphological differences among these genetically-different biofilm amyloid nanofibers. In addition, we conducted nanoindentation experiments to obtain force spectroscopy curves. A precise processing routine was developed to extract the mechanical stiffness from acquired data. Furthermore, we statistically contrasted the stiffness values to reveal the genetic dependence of the mechanical properties of the final protein assembly. The processing routine was also able to detect the effect of the substrate on mechanical stiffness measurements. The experimental results presented in this thesis pave the road for the use of genetic engineering to rationally tune the mechanical as well as the morphological properties of bacterial amyloid nanofibers, and thereby underline the critical role that they may play as new generation biomaterials.

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