Sortase as a Tool in Biotechnology and Medicine

We have harnessed two reactions catalyzed by the enzyme sortase A and applied them to generate new methods for the purification and site-selective modification of recombinant protein therapeutics.

We utilized native peptide ligation —a well-known function of sortase A— to attach a small molecule drug specifically to the carboxy-terminus of a recombinant protein. By combining this reaction with the unique phase behavior of elastin-like polypeptides, we developed a protocol that produces homogenously-labeled protein-small molecule conjugates using only centrifugation. The same reaction can be used to produce unmodified therapeutic proteins simply by substituting a single reactant. The isolated proteins or protein-small molecule conjugates do not have any exogenous purification tags, eliminating the potential influence of these tags on bioactivity. Because both unmodified and modified proteins are produced by a general process that is the same for any protein of interest and does not require any chromatography, the time, effort, and cost associated with protein purification and modification is greatly reduced.

We also developed an innovative and unique method that attaches a tunable number of drug molecules to any recombinant protein of interest in a site-specific manner. Although the ability of sortase A to carry out native peptide ligation is widely used, we demonstrated that Sortase A is also capable of attaching small molecules to proteins through an isopeptide bond at lysine side chains within a unique amino acid sequence. This reaction —isopeptide ligation— is a new site-specific conjugation method that is orthogonal to all available protein-small conjugation technologies and is the first site-specific conjugation method that attaches the payload to lysine residues. We show that isopeptide ligation can be applied broadly to peptides, proteins, and antibodies using a variety of small molecule cargoes to efficiently generate stable conjugates. We thoroughly assessed the site-selectivity of this reaction using a variety of analytical methods and showed that in many cases the reaction is site-specific for lysines in flexible, disordered regions of the substrate proteins. Finally, we showed that isopeptide ligation can be used to create clinically-relevant antibody-drug conjugates that have potent cytotoxicity towards cancerous cells

Combined Gene Therapy and Functional Tissue Engineering for the Treatment of Osteoarthritis

The pathogenesis of osteoarthritis is mediated in part by inflammatory cytokines including interleukin-1 (IL-1), which promote degradation of articular cartilage and prevent human mesenchymal stem cell (hMSC) chondrogenesis. We combined gene therapy and functional tissue engineering to develop engineered cartilage with immunomodulatory properties that allow chondrogenesis in the presence of pathologic levels of IL-1 by inducing overexpression of IL-1 receptor antagonist (IL-1Ra) in hMSCs via scaffold-mediated lentiviral gene delivery. A doxycycline-inducible vector was used to transduce hMSCs in monolayer or within 3D woven PCL scaffolds to enable tunable IL-1Ra production. In the presence of IL-1, IL-1Ra-expressing engineered cartilage produced cartilage-specific extracellular matrix, while resisting IL-1-induced upregulation of matrix metalloproteinases and maintaining mechanical properties similar to native articular cartilage. The ability of functional engineered cartilage to deliver tunable anti-inflammatory cytokines to the joint may enhance the long-term success of therapies for cartilage injuries or osteoarthritis.

Following this, we modified this anti-inflammatory engineered cartilage to incorporate rabbit MSCs and evaluated this therapeutic strategy in a pilot study in vivo in rabbit osteochondral defects. Rabbits were fed a custom doxycycline diet to induce gene expression in engineered cartilage implanted in the joint. Serum and synovial fluid were collected and the levels of doxycycline and inflammatory mediators were measured. Rabbits were euthanized 3 weeks following surgery and tissues were harvested for analysis. We found that doxycycline levels in serum and synovial fluid were too low to induce strong overexpression of hIL-1Ra in the joint and hIL-1Ra was undetectable in synovial fluid via ELISA. Although hIL-1Ra expression in the first few days local to the site of injury may have had a beneficial effect, overall a higher doxycycline dose and more readily transduced cell population would improve application of this therapy.

In addition to the 3D woven PCL scaffold, cartilage-derived matrix scaffolds have recently emerged as a promising option for cartilage tissue engineering. Spatially-defined, biomaterial-mediated lentiviral gene delivery of tunable and inducible morphogenetic transgenes may enable guided differentiation of hMSCs into both cartilage and bone within CDM scaffolds, enhancing the ability of the CDM scaffold to provide chondrogenic cues to hMSCs. In addition to controlled production of anti-inflammatory proteins within the joint, in situ production of chondro- and osteo-inductive factors within tissue-engineered cartilage, bone, or osteochondral tissue may be highly advantageous as it could eliminate the need for extensive in vitro differentiation involving supplementation of culture media with exogenous growth factors. To this end, we have utilized controlled overexpression of transforming growth factor-beta 3 (TGF-β3), bone morphogenetic protein-2 (BMP-2) or a combination of both factors, to induce chondrogenesis, osteogenesis, or both, within CDM hemispheres. We found that TGF-β3 overexpression led to robust chondrogenesis in vitro and BMP-2 overexpression led to mineralization but not accumulation of type I collagen. We also showed the development of a single osteochondral construct by combining tissues overexpressing BMP-2 (hemisphere insert) and TGF-β3 (hollow hemisphere shell) and culturing them together in the same media. Chondrogenic ECM was localized in the TGF-β3-expressing portion and osteogenic ECM was localized in the BMP-2-expressing region. Tissue also formed in the interface between the two pieces, integrating them into a single construct.

Since CDM scaffolds can be enzymatically degraded just like native cartilage, we hypothesized that IL-1 may have an even larger influence on CDM than PCL tissue-engineered constructs. Additionally, anti-inflammatory engineered cartilage implanted in vivo will likely affect cartilage and the underlying bone. There is some evidence that osteogenesis may be enhanced by IL-1 treatment rather than inhibited. To investigate the effects of an inflammatory environment on osteogenesis and chondrogenesis within CDM hemispheres, we evaluated the ability of IL-1Ra-expressing or control constructs to undergo chondrogenesis and osteogenesis in the prescence of IL-1. We found that IL-1 prevented chondrogenesis in CDM hemispheres but did not did not produce discernable effects on osteogenesis in CDM hemispheres. IL-1Ra-expressing CDM hemispheres produced robust cartilage-like ECM and did not upregulate inflammatory mediators during chondrogenic culture in the presence of IL-1.

Pathogen-Specific Adaptations to Conserved Signaling Pathways in Cryptococcus neoformans

Cryptococcus neoformans is an opportunistic fungal pathogen that causes significant disease worldwide. Even though this fungus has not evolved specifically to cause human disease, it has a remarkable ability to adapt to many different environments within its infected host. C. neoformans adapts by utilizing conserved eukaryotic and fungal-specific signaling pathways to sense and respond to stresses within the host. Upon infection, two of the most significant environmental changes this organism experiences are elevated temperature and high pH.

Conserved Rho and Ras family GTPases are central regulators of thermotolerance in C. neoformans. Many GTPases require prenylation to associate with cellular membranes and function properly. Using molecular genetic techniques, microscopy, and infection models, I demonstrated that the prenyltransferase, geranylgeranyl transferase I (GGTase I) is required for thermotolerance and pathogenesis. Using fluorescence microscopy, I found that only a subset of conserved GGTase I substrates requires this enzyme for membrane localization. Therefore, the C. neoformans GGTase I may recognize its substrate in a slightly different manner than other eukaryotic organisms.

The alkaline response transcription factor, Rim101, is a central regulator of stress-response genes important for adapting to the host environment. In particular, Rim101 regulates cell surface alterations involved in immune avoidance. In other fungi, Rim101 is activated by alkaline pH through a conserved signaling pathway, but this pathway had yet been characterized in C. neoformans. Using molecular genetic techniques, I identified and analyzed the conserved members of the Rim pathway. I found that it was only partially conserved in C. neoformans, missing the components that sense pH and initiate pathway activation. Using a genetic screen, I identified a novel Rim pathway component named Rra1. Structural prediction and genetic epistasis experiments suggest that Rra1 may serve as the Rim pathway pH sensor in C. neoformans and other related basidiomycete fungi.

To explore the relevance of Rim pathway signaling in the interaction of C neoformans with its host, I characterized the Rim101-regulated cell wall changes that prevent immune detection. Using HPLC, enzymatic degradation, and cell wall stains, I found that the rim101Δ mutation resulted in increased cell wall chitin exposure. In vitro co-culture assays demonstrated that increased chitin exposure is associated with enhanced activation of macrophages and dendritic cells. To further test this association, I demonstrated that other mutant strains with increased chitin exposure induce macrophage and dendritic cell responses similar to rim101Δ. We used primary macrophages from mutant mouse lines to demonstrate that members of both the Toll-like receptor and C-type lectin receptor families are involved in detecting strains with increased chitin exposure. Finally, in vivo immunological experiments demonstrated that the rim101Δ strain induced a global inflammatory immune response in infected mouse lungs, expanding upon our previous in vivo rim101Δ studies. These results demonstrate that cell wall organization largely determines how fungal cells are detected by the immune system.

Combining Information from Multiple Sources in Bayesian Modeling

Surveys can collect important data that inform policy decisions and drive social science research. Large government surveys collect information from the U.S. population on a wide range of topics, including demographics, education, employment, and lifestyle. Analysis of survey data presents unique challenges. In particular, one needs to account for missing data, for complex sampling designs, and for measurement error. Conceptually, a survey organization could spend lots of resources getting high-quality responses from a simple random sample, resulting in survey data that are easy to analyze. However, this scenario often is not realistic. To address these practical issues, survey organizations can leverage the information available from other sources of data. For example, in longitudinal studies that suffer from attrition, they can use the information from refreshment samples to correct for potential attrition bias. They can use information from known marginal distributions or survey design to improve inferences. They can use information from gold standard sources to correct for measurement error.

This thesis presents novel approaches to combining information from multiple sources that address the three problems described above.

The first method addresses nonignorable unit nonresponse and attrition in a panel survey with a refreshment sample. Panel surveys typically suffer from attrition, which can lead to biased inference when basing analysis only on cases that complete all waves of the panel. Unfortunately, the panel data alone cannot inform the extent of the bias due to attrition, so analysts must make strong and untestable assumptions about the missing data mechanism. Many panel studies also include refreshment samples, which are data collected from a random sample of new

individuals during some later wave of the panel. Refreshment samples offer information that can be utilized to correct for biases induced by nonignorable attrition while reducing reliance on strong assumptions about the attrition process. To date, these bias correction methods have not dealt with two key practical issues in panel studies: unit nonresponse in the initial wave of the panel and in the

refreshment sample itself. As we illustrate, nonignorable unit nonresponse

can significantly compromise the analyst's ability to use the refreshment samples for attrition bias correction. Thus, it is crucial for analysts to assess how sensitive their inferences---corrected for panel attrition---are to different assumptions about the nature of the unit nonresponse. We present an approach that facilitates such sensitivity analyses, both for suspected nonignorable unit nonresponse

in the initial wave and in the refreshment sample. We illustrate the approach using simulation studies and an analysis of data from the 2007-2008 Associated Press/Yahoo News election panel study.

The second method incorporates informative prior beliefs about

marginal probabilities into Bayesian latent class models for categorical data.

The basic idea is to append synthetic observations to the original data such that

(i) the empirical distributions of the desired margins match those of the prior beliefs, and (ii) the values of the remaining variables are left missing. The degree of prior uncertainty is controlled by the number of augmented records. Posterior inferences can be obtained via typical MCMC algorithms for latent class models, tailored to deal efficiently with the missing values in the concatenated data.

We illustrate the approach using a variety of simulations based on data from the American Community Survey, including an example of how augmented records can be used to fit latent class models to data from stratified samples.

The third method leverages the information from a gold standard survey to model reporting error. Survey data are subject to reporting error when respondents misunderstand the question or accidentally select the wrong response. Sometimes survey respondents knowingly select the wrong response, for example, by reporting a higher level of education than they actually have attained. We present an approach that allows an analyst to model reporting error by incorporating information from a gold standard survey. The analyst can specify various reporting error models and assess how sensitive their conclusions are to different assumptions about the reporting error process. We illustrate the approach using simulations based on data from the 1993 National Survey of College Graduates. We use the method to impute error-corrected educational attainments in the 2010 American Community Survey using the 2010 National Survey of College Graduates as the gold standard survey.