Design, Synthesis, and Photophysical Investigation of Porphyrin-containing Polymer-wrapped Single-walled Carbon Nanotubes

Significant advances in understanding the fundamental photophysical behavior of single-walled carbon nanotubes (SWNTs) have been made possible by the development of ionic, conjugated aryleneethynylene polymers that helically wrap SWNTs with well-defined morphology. My contribution to this work was the design and synthesis of porphyrin-containing polymers and the photophysical investigation of the corresponding polymer-wrapped SWNTs. For these new constructs, the polymer acts as more than just a solubilization scaffold; such assemblies can provide benchmark data for evaluating spectroscopic signatures of energy and charge transfer events and lay the groundwork for further, rational development of polymers with precisely tuned redox properties and electronic coupling with the underlying SWNT. The first design to incorporate a zinc porphyrin into the polymer backbone, PNES-PZn, suffered from severe aggregation in solution and was redesigned to produce the porphyrin-containing polymer S-PBN-PZn. This polymer was utilized to helically wrap chirality-enriched (6,5) SWNTs, which resulted in significant quenching of the porphyrin-based fluorescence. Time-resolved spectroscopy revealed a simultaneous rise and decay of the porphyrin radical cation and SWNT electron polaron spectroscopic signatures indicative of photoinduced electron transfer. A new polymer, S-PBN(b)-Ph2PZn3, was then synthesized which incorporated a meso-ethyne linked zinc porphyrin trimer. By changing the absorption profile and electrochemical redox potentials of the polymer, the photophysical behavior of the corresponding polymer-wrapped (6,5)-SWNTs was dramatically changed, and the polymer-wrapped SWNTs no longer showed evidence for photoinduced electron transfer.

Characterization of a Full-Length TTP Family Member Association with RNA Sequence Elements

Post-transcriptional regulation of cytoplasmic mRNAs is an efficient mechanism of regulating the amounts of active protein within a eukaryotic cell. RNA sequence elements located in the untranslated regions of mRNAs can influence transcript degradation or translation through associations with RNA-binding proteins. Tristetraprolin (TTP) is the best known member of a family of CCCH zinc finger proteins that targets adenosine-uridine rich element (ARE) binding sites in the 3’ untranslated regions (UTRs) of mRNAs, promoting transcript deadenylation through the recruitment of deadenylases. More specifically, TTP has been shown to bind AREs located in the 3’-UTRs of transcripts with known roles in the inflammatory response. The mRNA-binding region of the protein is the highly conserved CCCH tandem zinc finger (TZF) domain. The synthetic TTP TZF domain has been shown to bind with high affinity to the 13-mer sequence of UUUUAUUUAUUUU. However, the binding affinities of full-length TTP family members to the same sequence and its variants are unknown. Furthermore, the distance needed between two overlapping or neighboring UUAUUUAUU 9-mers for tandem binding events of a full-length TTP family member to a target transcript has not been explored. To address these questions, we recombinantly expressed and purified the full-length C. albicans TTP family member Zfs1. Using full-length Zfs1, tagged at the N-terminus with maltose binding protein (MBP), we determined the binding affinities of the protein to the optimal TTP binding sequence, UUAUUUAUU. Fluorescence anisotropy experiments determined that the binding affinities of MBP-Zfs1 to non-canonical AREs were influenced by ionic buffer strength, suggesting that transcript selectivity may be affected by intracellular conditions. Furthermore, electrophoretic mobility shift assays (EMSAs) revealed that separation of two core AUUUA sequences by two uridines is sufficient for tandem binding of MBP-Zfs1. Finally, we found evidence for tandem binding of MBP-Zfs1 to a 27-base RNA oligonucleotide containing only a single ARE-binding site, and showed that this was concentration and RNA length dependent; this phenomenon had not been seen previously. These data suggest that the association of the TTP TZF domain and the TZF domains of other species, to ARE-binding sites is highly conserved. Domains outside of the TZF domain may mediate transcript selectivity in changing cellular conditions, and promote protein-RNA interactions not associated with the ARE-binding TZF domain.

In summary, the evidence presented here suggests that Zfs1-mediated decay of mRNA targets may require additional interactions, in addition to ARE-TZF domain associations, to promote transcript destabilization and degradation. These studies further our understanding of post-transcriptional steps in gene regulation.

Mechanisms of CD8+ T Cell Mediated Virus Inhibition in HIV-1 Virus Controllers

CD8+ T cells are associated with long term control of virus replication to low or undetectable levels in a population of HIV+ therapy-naïve individuals known as virus controllers (VCs; <5000 RNA copies/ml and CD4+ lymphocyte counts >400 cells/µl). These subjects' ability to control viremia in the absence of therapy makes them the gold standard for the type of CD8+ T-cell response that should be induced with a vaccine. Studying the regulation of CD8+ T cells responses in these VCs provides the opportunity to discover mechanisms of durable control of HIV-1. Previous research has shown that the CD8+ T cell population in VCs is heterogeneous in its ability to inhibit virus replication and distinct T cells are responsible for virus inhibition. Further defining both the functional properties and regulation of the specific features of the select CD8+ T cells responsible for potent control of viremia the in VCs would enable better evaluation of T cell-directed vaccine strategies and may inform the design of new therapies.

Here we discuss the progress made in elucidating the features and regulation of CD8+ T cell response in virus controllers. We first detail the development of assays to quantify CD8+ T cells' ability to inhibit virus replication. This includes the use of a multi-clade HIV-1 panel which can subsequently be used as a tool for evaluation of T cell directed vaccines. We used these assays to evaluate the CD8+ response among cohorts of HIV-1 seronegative, HIV-1 acutely infected, and HIV-1 chronically infected (both VC and chronic viremic) patients. Contact and soluble CD8+ T cell virus inhibition assays (VIAs) are able to distinguish these patient groups based on the presence and magnitude of the responses. When employed in conjunction with peptide stimulation, the soluble assay reveals peptide stimulation induces CD8+ T cell responses with a prevalence of Gag p24 and Nef specificity among the virus controllers tested. Given this prevalence, we aimed to determine the gene expression profile of Gag p24-, Nef-, and unstimulated CD8+ T cells. RNA was isolated from CD8+ T-cells from two virus controllers with strong virus inhibition and one seronegative donor after a 5.5 hour stimulation period then analyzed using the Illumina Human BeadChip platform (Duke Center for Human Genome Variation). Analysis revealed that 565 (242 Nef and 323 Gag) genes were differentially expressed in CD8+ T-cells that were able to inhibit virus replication compared to those that could not. We compared the differentially expressed genes to published data sets from other CD8+ T-cell effector function experiments focusing our analysis on the most recurring genes with immunological, gene regulatory, apoptotic or unknown functions. The most commonly identified gene in these studies was TNFRSF9. Using PCR in a larger cohort of virus controllers we confirmed the up-regulation of TNFRSF9 in Gag p24 and Nef-specific CD8+ T cell mediated virus inhibition. We also observed increase in the mRNA encoding antiviral cytokines macrophage inflammatory proteins (MIP-1α, MIP-1αP, MIP-1β), interferon gamma (IFN-γ), granulocyte-macrophage colony-stimulating factor (GM-CSF), and recently identified lymphotactin (XCL1).

Our previous work suggests the CD8+ T-cell response to HIV-1 can be regulated at the level of gene regulation. Because RNA abundance is modulated by transcription of new mRNAs and decay of new and existing RNA we aimed to evaluate the net rate of transcription and mRNA decay for the cytokines we identified as differentially regulated. To estimate rate of mRNA synthesis and decay, we stimulated isolated CD8+ T-cells with Gag p24 and Nef peptides adding 4-thiouridine (4SU) during the final hour of stimulation, allowing for separation of RNA made during the final hour of stimulation. Subsequent PCR of RNA isolated from these cells, allowed us to determine how much mRNA was made for our genes of interest during the final hour which we used to calculate rate of transcription. To assess if stimulation caused a change in RNA stability, we calculated the decay rates of these mRNA over time. In Gag p24 and Nef stimulated T cells , the abundance of the mRNA of many of the cytokines examined was dependent on changes in both transcription and mRNA decay with evidence for potential differences in the regulation of mRNA between Nef and Gag specific CD8+ T cells. The results were highly reproducible in that in one subject that was measured in three independent experiments the results were concordant.

This data suggests that mRNA stability, in addition to transcription, is key in regulating the direct anti-HIV-1 function of antigen-specific memory CD8+ T cells by enabling rapid recall of anti-HIV-1 effector functions, namely the production and increased stability of antiviral cytokines. We have started to uncover the mechanisms employed by CD8+ T cell subsets with antigen-specific anti-HIV-1 activity, in turn, enhancing our ability to inhibit virus replication by informing both cure strategies and HIV-1 vaccine designs that aim to reduce transmission and can aid in blocking HIV-1 acquisition.

Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.