Immunogenicity of decellularized porcine liver for bioengineered hepatic tissue.

Liver disease affects millions of patients each year. The field of regenerative medicine promises alternative therapeutic approaches, including the potential to bioengineer replacement hepatic tissue. One approach combines cells with acellular scaffolds derived from animal tissue. The goal of this study was to scale up our rodent liver decellularization method to livers of a clinically relevant size. Porcine livers were cannulated via the hepatic artery, then perfused with PBS, followed by successive Triton X-100 and SDS solutions in saline buffer. After several days of rinsing, decellularized liver samples were histologically analyzed. In addition, biopsy specimens of decellularized scaffolds were seeded with hepatoblastoma cells for cytotoxicity testing or implanted s.c. into rodents to investigate scaffold immunogenicity. Histological staining confirmed cellular clearance from pig livers, with removal of nuclei and cytoskeletal components and widespread preservation of structural extracellular molecules. Scanning electron microscopy confirmed preservation of an intact liver capsule, a porous acellular lattice structure with intact vessels and striated basement membrane. Liver scaffolds supported cells over 21 days, and no increased immune response was seen with either allogeneic (rat-into-rat) or xenogeneic (pig-into-rat) transplants over 28 days, compared with sham-operated on controls. These studies demonstrate that successful decellularization of the porcine liver could be achieved with protocols developed for rat livers, yielding nonimmunogenic scaffolds for future hepatic bioengineering studies.

Production and implantation of renal extracellular matrix scaffolds from porcine kidneys as a platform for renal bioengineering investigations.

BACKGROUND: It is important to identify new sources of transplantable organs because of the critical shortage of donor organs. Tissue engineering holds the potential to address this issue through the implementation of decellularization-recellularization technology. OBJECTIVE: To produce and examine acellular renal extracellular matrix (ECM) scaffolds as a platform for kidney bioengineering. METHODS: Porcine kidneys were decellularized with distilled water and sodium dodecyl sulfate-based solution. After rinsing with buffer solution to remove the sodium dodecyl sulfate, the so-obtained renal ECM scaffolds were processed for vascular imaging, histology, and cell seeding to investigate the vascular patency, degree of decellularization, and scaffold biocompatibility in vitro. Four whole renal scaffolds were implanted in pigs to assess whether these constructs would sustain normal blood pressure and to determine their biocompatibility in vivo. Pigs were sacrificed after 2 weeks and the explanted scaffolds were processed for histology. RESULTS: Renal ECM scaffolds were successfully produced from porcine kidneys. Scaffolds retained their essential ECM architecture and an intact vascular tree and allowed cell growth. On implantation, unseeded scaffolds were easily reperfused, sustained blood pressure, and were tolerated throughout the study period. No blood extravasation occurred. Pathology of explanted scaffolds showed maintenance of renal ultrastructure. Presence of inflammatory cells in the pericapsular region and complete thrombosis of the vascular tree were evident. CONCLUSIONS: Our investigations show that pig kidneys can be successfully decellularized to produce renal ECM scaffolds. These scaffolds maintain their basic components, are biocompatible, and show intact, though thrombosed, vasculature.

Quantifying polypeptide conformational space: sensitivity to conformation and ensemble definition.

Quantifying the density of conformations over phase space (the conformational distribution) is needed to model important macromolecular processes such as protein folding. In this work, we quantify the conformational distribution for a simple polypeptide (N-mer polyalanine) using the cumulative distribution function (CDF), which gives the probability that two randomly selected conformations are separated by less than a "conformational" distance and whose inverse gives conformation counts as a function of conformational radius. An important finding is that the conformation counts obtained by the CDF inverse depend critically on the assignment of a conformation's distance span and the ensemble (e.g., unfolded state model): varying ensemble and conformation definition (1 --> 2 A) varies the CDF-based conformation counts for Ala(50) from 10(11) to 10(69). In particular, relatively short molecular dynamics (MD) relaxation of Ala(50)'s random-walk ensemble reduces the number of conformers from 10(55) to 10(14) (using a 1 A root-mean-square-deviation radius conformation definition) pointing to potential disconnections in comparing the results from simplified models of unfolded proteins with those from all-atom MD simulations. Explicit waters are found to roughen the landscape considerably. Under some common conformation definitions, the results herein provide (i) an upper limit to the number of accessible conformations that compose unfolded states of proteins, (ii) the optimal clustering radius/conformation radius for counting conformations for a given energy and solvent model, (iii) a means of comparing various studies, and (iv) an assessment of the applicability of random search in protein folding.

Information content of molecular structures.

For a completely enumerated set of conformers of a macromolecule or for exhaustive lattice walks of model polymers it is straightforward to use Shannon information theory to deduce the information content of the ensemble. It is also practicable to develop numerical measures of the information content of sets of exact distance constraints applied to specific conformational ensembles. We examine the effects of experimental uncertainties by considering "noisy" constraints. The introduction of noise requires additional assumptions about noise distribution and conformational clustering protocols that make the problem of measuring information content more complex. We make use of a standard concept in communication theory, the "noise sphere," to link uncertainty in measurements to information loss. Most of our numerical results are derived from two-dimensional lattice ensembles. Expressing results in terms of information per degree of freedom removes almost all of the chain length dependence. We also explore off-lattice polyalanine chains that yield surprisingly similar results.