Tunable erosion of polymeric materials is an important aspect of tissue engineering for reasons that include cell infiltration, controlled release of therapeutic agents, and ultimately to tissue healing. In general, the biological response to proteinaceous polymeric hydrogels is favorable (e.g., minimal inflammatory response). However, unlike synthetic polymers, achieving tunable erosion with natural materials is a challenge. Keratins are a class of intermediate filament proteins that can be obtained from several sources including human hair and have gained increasing levels of use in tissue engineering applications. An important characteristic of keratin proteins is the presence of a large number of cysteine residues. Two classes of keratins with different chemical properties can be obtained by varying the extraction techniques: (1) keratose by oxidative extraction and (2) kerateine by reductive extraction. Cysteine residues of keratose are “capped” by sulfonic acid and are unable to form covalent crosslinks upon hydration, whereas cysteine residues of kerateine remain as sulfhydryl groups and spontaneously form covalent disulfide crosslinks. Here, we describe a straightforward approach to fabricate keratin hydrogels with tunable rates of erosion by mixing keratose and kerateine. SEM imaging and mechanical testing of freeze-dried materials showed similar pore diameters and compressive moduli, respectively, for each keratose-kerateine mixture formulation (~1200 kPa for freeze-dried materials and ~1.5 kPa for hydrogels). However, the elastic modulus (G’) determined by rheology varied in proportion with the keratose-kerateine ratios, as did the rate of hydrogel erosion and the release rate of thiol from the hydrogels. The variation in keratose-kerateine ratios also led to tunable control over release rates of recombinant human insulin-like growth factor 1.
A membrane alignment technique has been used to measure the distance between two TOAC nitroxide spin labels on the membrane-spanning M2δ, peptide of the nicotinic acetylcholine receptor (AChR), via CW-EPR spectroscopy. The TOAC-labeled M2δ peptides were mechanically aligned using DMPC lipids on a planar quartz support, and CW-EPR spectra were recorded at specific orientations. Global analysis in combination with rigorous spectral simulation was used to simultaneously analyze data from two different sample orientations for both single- and double-labeled peptides. We measured an internitroxide distance of 14.6 Å from a dual TOAC-labeled AChR M2δ peptide at positions 7 and 13 that closely matches with the 14.5 Å distance obtained from a model of the labeled AChR M2δ peptide. In addition, the angles determining the relative orientation of the two nitroxides have been determined, and the results compare favorably with molecular modeling. The global analysis of the data from the aligned samples gives much more precise estimates of the parameters defining the geometry of the two labels than can be obtained from a randomly dispersed sample.
Wild-type Phospholamban (WT-PLB), a Ca2+-ATPase (SERCA) regulator in the sarcoplasmic reticulum membrane, was studied using TOAC nitroxide spin labeling, magnetically aligned bicelles, and electron paramagnetic resonance (EPR) spectroscopy to ascertain structural and dynamic information. Different structural domains of PLB (transmembrane segment: positions 42 and 45, loop region: position 20, and cytoplasmic domain: position 10) were probed with rigid TOAC spin labels to extract the transmembrane helical tilt and structural dynamic information, which is crucial for understanding the regulatory function of PLB in modulating Ca2+-ATPase activity. Aligned experiments indicate that the transmembrane domain of wild-type PLB has a helical tilt of 13° ± 4° in DMPC/DHPC bicelles. TOAC spin labels placed on the WT-PLB transmembrane domain showed highly restricted motion with more than 100 ns rotational correlation time (τc); whereas the loop, and the cytoplasmic regions each consists of two distinct motional dynamics: one fast component in the sub-nanosecond scale and the other component is slower dynamics in the nanosecond range.
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