Distinct intron DNA structures in simian virus 40 T-antigen and adenovirus 2 E1A genes

Distinct structures delineating the introns of Simian Virus 40 T-antigen and Adenovirus 2 E1A genes have been discovered. The structures, which are centered around the branch points of the genes inserted in supercoiled double-stranded plasmids, are specifically targeted through photoactivated strand cleavage by the metal complex tris(4,7-diphenyl-1,10-phenanthroline)rhodium(III). The DNA sites that are recognized lack sequence homology but are similar in demarcating functionally important sites on the RNA level. The single-stranded DNA fragments corresponding to the coding strands of the genes were also found to fold into a structure apparently identical to that in the supercoiled genes based on the recognition by the metal complex. Further investigation of different single-stranded DNA fragments with other structural probes, such as another metal complex bis(1,10-phenanthroline)(phenanthrenequinone diimine)rhodium(III), AMT (4'aminomethyl-4,5',8 trimethylpsoralen), restriction enzyme Mse I, and mung bean nuclease, showed that the structures require the sequ ences at both ends of the intron plus the flanking sequences but not the middle of the intron. The two ends form independent helices which interact with each other to form the global tertiary structures. Both of the intron structures share similarities to the structure of the Holliday junction, which is also known to be specifically targeted by the former metal complex. These structures may have arisen from early RNA intron structures and may have been used to facilitate the evolution of genes through exon shuffling by acting as target sites for recombinase enzymes.

Signal transduction with hybridization chain reactions

Some of the most exciting developments in the field of nucleic acid engineering include the utilization of synthetic nucleic acid molecular devices as gene regulators, as disease marker detectors, and most recently, as therapeutic agents. The common thread between these technologies is their reliance on the detection of specific nucleic acid input markers to generate some desirable output, such as a change in the copy number of an mRNA (for gene regulation), a change in the emitted light intensity (for some diagnostics), and a change in cell state within an organism (for therapeutics). The research presented in this thesis likewise focuses on engineering molecular tools that detect specific nucleic acid inputs, and respond with useful outputs.

Four contributions to the field of nucleic acid engineering are presented: (1) the construction of a single nucleotide polymorphism (SNP) detector based on the mechanism of hybridization chain reaction (HCR); (2) the utilization of a single-stranded oligonucleotide molecular Scavenger as a means of enhancing HCR selectivity; (3) the implementation of Quenched HCR, a technique that facilitates transduction of a nucleic acid chemical input into an optical (light) output, and (4) the engineering of conditional probes that function as sequence transducers, receiving target signal as input and providing a sequence of choice as output. These programmable molecular systems are conceptually well-suited for performing wash-free, highly selective rapid genotyping and expression profiling in vitro, in situ, and potentially in living cells.

Structure-Guided Design and Biophysical Characterization of Novel Anti-HIV Reagents

Despite over 30 years of effort, an HIV-1 vaccine that elicits protective antibodies still does not exist. Recent clinical studies have identified that during natural infection about 20% of the population is capable of mounting a potent and protective antibody response. Closer inspection of these individuals reveal that a subset of these antibodies, recently termed potent VRC01-like (PVL), derive exclusively from a single human germline heavy chain gene. Induced clonal expansion of the B cell encoding this gene is the first step through which PVL antibodies may be elicited. Unfortunately, naturally occurring HIV gp120s fail to bind to this germline, and as a result cannot be used as the initial prime for a vaccine regimen. We have determined the crystal structure of an important germline antibody that is a promising target for vaccine design efforts, and have set out to engineer a more likely candidate using computationally-guided rational design.

In addition to prevention efforts on the side of vaccine design, recently characterized broadly neutralizing anti-HIV antibodies have excellent potential for use in gene therapy and passive immunotherapy. The separation distance between functional Fabs on an antibody is important due to the sparse distribution of envelop spikes on HIV compared to other viruses. We set out to build and characterize novel antibody architectures by incorporating structured linkers into the hinge region of an anti-HIV antibody b12. The goal was to observe whether these linkers increased the arm-span of the IgG dimer. When incorporated, flexible Gly4Ser repeats did not result in detectable extensions of the IgG antigen binding domains, by contrast to linkers including more rigid domains such as β2-microglobulin, Zn-α2-glycoprotein, and tetratricopeptide repeats (TPRs). This study adds an additional set of linkers with varying lengths and rigidities to the available linker repertoire, which may be useful for the modification and construction of antibodies and other fusion proteins.

Technology for Single Cell Protein Analysis in Immunology and Cancer Prognostics

The first chapter of this thesis deals with automating data gathering for single cell microfluidic tests. The programs developed saved significant amounts of time with no loss in accuracy. The technology from this chapter was applied to experiments in both Chapters 4 and 5.

The second chapter describes the use of statistical learning to prognose if an anti-angiogenic drug (Bevacizumab) would successfully treat a glioblastoma multiforme tumor. This was conducted by first measuring protein levels from 92 blood samples using the DNA-encoded antibody library platform. This allowed the measure of 35 different proteins per sample, with comparable sensitivity to ELISA. Two statistical learning models were developed in order to predict whether the treatment would succeed. The first, logistic regression, predicted with 85% accuracy and an AUC of 0.901 using a five protein panel. These five proteins were statistically significant predictors and gave insight into the mechanism behind anti-angiogenic success/failure. The second model, an ensemble model of logistic regression, kNN, and random forest, predicted with a slightly higher accuracy of 87%.

The third chapter details the development of a photocleavable conjugate that multiplexed cell surface detection in microfluidic devices. The method successfully detected streptavidin on coated beads with 92% positive predictive rate. Furthermore, chambers with 0, 1, 2, and 3+ beads were statistically distinguishable. The method was then used to detect CD3 on Jurkat T cells, yielding a positive predictive rate of 49% and false positive rate of 0%.

The fourth chapter talks about the use of measuring T cell polyfunctionality in order to predict whether a patient will succeed an adoptive T cells transfer therapy. In 15 patients, we measured 10 proteins from individual T cells (~300 cells per patient). The polyfunctional strength index was calculated, which was then correlated with the patient's progress free survival (PFS) time. 52 other parameters measured in the single cell test were correlated with the PFS. No statistical correlator has been determined, however, and more data is necessary to reach a conclusion.

Finally, the fifth chapter talks about the interactions between T cells and how that affects their protein secretion. It was observed that T cells in direct contact selectively enhance their protein secretion, in some cases by over 5 fold. This occurred for Granzyme B, Perforin, CCL4, TNFa, and IFNg. IL- 10 was shown to decrease slightly upon contact. This phenomenon held true for T cells from all patients tested (n=8). Using single cell data, the theoretical protein secretion frequency was calculated for two cells and then compared to the observed rate of secretion for both two cells not in contact, and two cells in contact. In over 90% of cases, the theoretical protein secretion rate matched that of two cells not in contact.

Towards in situ Single Cell Systems Biology

Systems-level studies of biological systems rely on observations taken at a resolution lower than the essential unit of biology, the cell. Recent technical advances in DNA sequencing have enabled measurements of the transcriptomes in single cells excised from their environment, but it remains a daunting technical problem to reconstruct in situ gene expression patterns from sequencing data. In this thesis I develop methods for the routine, quantitative in situ measurement of gene expression using fluorescence microscopy.

The number of molecular species that can be measured simultaneously by fluorescence microscopy is limited by the pallet of spectrally distinct fluorophores. Thus, fluorescence microscopy is traditionally limited to the simultaneous measurement of only five labeled biomolecules at a time. The two methods described in this thesis, super-resolution barcoding and temporal barcoding, represent strategies for overcoming this limitation to monitor expression of many genes in a single cell. Super-resolution barcoding employs optical super-resolution microscopy (SRM) and combinatorial labeling via-smFISH (single molecule fluorescence in situ hybridization) to uniquely label individual mRNA species with distinct barcodes resolvable at nanometer resolution. This method dramatically increases the optical space in a cell, allowing a large numbers of barcodes to be visualized simultaneously. As a proof of principle this technology was used to study the S. cerevisiae calcium stress response. The second method, sequential barcoding, reads out a temporal barcode through multiple rounds of oligonucleotide hybridization to the same mRNA. The multiplexing capacity of sequential barcoding increases exponentially with the number of rounds of hybridization, allowing over a hundred genes to be profiled in only a few rounds of hybridization.

The utility of sequential barcoding was further demonstrated by adapting this method to study gene expression in mammalian tissues. Mammalian tissues suffer both from a large amount of auto-fluorescence and light scattering, making detection of smFISH probes on mRNA difficult. An amplified single molecule detection technology, smHCR (single molecule hairpin chain reaction), was developed to allow for the quantification of mRNA in tissue. This technology is demonstrated in combination with light sheet microscopy and background reducing tissue clearing technology, enabling whole-organ sequential barcoding to monitor in situ gene expression directly in intact mammalian tissue.

The methods presented in this thesis, specifically sequential barcoding and smHCR, enable multiplexed transcriptional observations in any tissue of interest. These technologies will serve as a general platform for future transcriptomic studies of complex tissues.

Microfluidics-based single-cell functional proteomics microchip for portraying protein signal transduction networks within the framework of physicochemical principles, with applications in fundamental and translational cancer research

Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.

The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.

The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).

The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.

The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.

In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.