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The adaptive immune system provides protection against disease and maintains memory of past exposures. Randomly rearranged antigen receptors can recognize virtually any pathogen. T cells recognize processed peptides that originate from protein fragments and are presented on major histocompatibility complex molecules. Human T cell receptor (TCR) function is mostly studied in the context of model antigens. TCRs against the majority of presented epitopes are not defined. Single cell sequencing allowed for paired TCRα/β sequencing at a scale not previously imaginable, which increased interest in identification of antigen specific TCRs. Antigen specific TCR discovery efforts are challenging because of the repertoire diversity. Up to 10^19 possible TCRs can be randomly generated in the thymus. Antigen specific T cells can be selected by a range of techniques based on either physical staining of the TCR or selection of cells activated with specific antigen. Antigen specific T cell rarity and abundance of weakly reactive cells leads to selection of large numbers of false positive clones. The TCRα/β needs to be sequenced and genetically reconstructed in allogeneic T cells to confirm antigen recognition. The qualities of an antigen specific TCR include the ability to direct the killing of target cell lines, stimulating the production of multiple cytokines, and driving cell division. Such data can then be used to rank TCRs and identify highly functional clones. More sensitive and specific selection prior to sequencing can reduce the amount of labor involved when profiling TCRs.This thesis work describes a new technology for sequencing antigen specific TCRs, which is used to study T cell responses against SARS-CoV-2. We developed a protocol that allows for TCR sequencing in cells that have been identified as functional based on cytokine production in response to stimulation with specific antigens. TCR engagement drives cytokine production which is one of the fundamental properties of a T cell. For this reason, intracellular cytokine staining is one of the most commonly used techniques to quantify antigen specific T cells. We then identified SARS-CoV-2 polymerase specific TCRs in unexposed human donors. Polymerase specific TCRs are able to recognize multiple human coronaviruses, indicating the potential to provide immunity regardless of the SARS-CoV-2 variant. Broadly reactive T cells provide heterosubtypic immunity against Influenza, another respiratory virus. Based on this work our laboratory, in collaboration with other laboratories at UCLA, is developing a novel COVID-19 vaccine strategy. Our SARS-CoV-2 work illustrates the utility of studying single TCRs to discover immune responses, but another approach is to use TCRs directly as therapeutics. TCR engineered T cells are effective in the clinic and cure late-stage tumors. Projects described in this thesis are helping drive other efforts in our laboratory that are directed at identifying TCRs against novel prostate cancer antigens.

Viruses have plagued humanity for thousands of years, but it is only in the last few centuries that we have even begun to develop vaccines and therapeutics to manage them. While we now have myriad vaccines that reduce death and suffering hugely compared to even half a century ago, millions of people still die every year from viral infections—some of which are preventable given current vaccines. Part of this is attributable to inequities that persist globally, but many deaths still result from diseases that we have been unable to control adequately. The main issues in producing effective vaccines derive from two factors: inability to induce an adequate immune response, and the ability of the pathogen to avoid an immune response. In many cases, such as HIV-1, certain flu strains, and hepatitis C virus, both are an issue. In HIV-1, a high tolerance for mutations allows for rapid escape from antibodies, which are adequate to prevent infection for many other pathogens. Conversely, we do not have methods to reliably generate T cell responses capable of broad recognition, and it is unknown whether doing so would even suffice. However, to approach more mechanistic explanations of how particular conditions affect an immune response, it is valuable to study the results of all vaccine trials, failed or otherwise. To this end, I characterize the antiviral capabilities of CD8+ cytotoxic T lymphocyte (CTL) clones that were elicited by the Mrk/Ad5 vaccine, a recombinant adenoviral vector that introduced single variants of the HIV-1 gag, pol, and nef genes. By testing their ability to kill and suppress virus-infected cells, I found that most clones were able to efficiently target the sequence used in the vaccine, but each exhibited very limited antiviral functions when tested against common epitope variants. The most recent pandemic, caused by SARS-CoV-2, has killed millions in a span of a few years, despite public health measures and rapid development of vaccines. A common issue seen in both SARS-CoV-2 vaccination and after infection is an apparent rapid waning of immune responses. As T cells are very important in containing and clearing most viral infections, it is crucial to characterize their responses in these contexts. By testing responses against SARS-CoV-2 structural proteins, I characterize the distribution of CTL targeting, the immunodominance of this targeting, and the persistence of different T cell responses elicited in either natural infection or SARS-CoV-2 mRNA vaccination.

The attached compressed file package supplements our research article. It comprises SARS-CoV-2 variant timemaps SVG files for 2020 and 2021, updated with data submitted to GISAID as of February 10th 2021 (inclusive). It is a snapshot of the webpage hosting these maps (https://bcgsc.github.io/SARS2) on that day and includes the script and single nucleotide variation (SNV) report files used to generate these and could be used by anyone to generate additional and custom interactive SVG maps. The frequently updated and comprehensive SARS-CoV-2 genome SNV reports (https://www.bcgsc.ca/downloads/btl/SARS-CoV-2/mutations) represent a wealth of variant information that could be mined to gain further insights into the rapid SARS-CoV-2 coronavirus evolution in human hosts.

As the year 2020 came to a close, several new strains have been reported for the SARS-CoV-2 coronavirus, the agent responsible for the COVID-19 pandemic that has afflicted us all this past year. However, it is difficult to comprehend the scale, in sequence space, geographical location and time, at which SARS-CoV-2 mutates and evolves in its human hosts. To get an appreciation for the rapid evolution of the coronavirus, we built interactive scalable vector graphics (SVG) maps that show daily nucleotide variations in genomes from the six most populated continents compared to that of the initial, ground-zero SARS-CoV-2 isolate sequenced at the beginning of the year. The attached compressed file package comprises SARS-CoV-2 mutation timemaps SVG files for 2020 and 2021, updated with data submitted to GISAID as of February 5th 2021 (inclusive). It is a snapshot of the webpage hosting these maps (https://bcgsc.github.io/SARS2) on that day and includes the script and single nucleotide variation (SNV) report files used to generate these and could be used by anyone to generate additional and custom interactive SVG maps. It supplements our F1000research article. The frequently updated and comprehensive SARS-CoV-2 genome SNV reports (https://www.bcgsc.ca/downloads/btl/SARS-CoV-2/mutations) represent a wealth of information that could be mined to gain further insights into the rapid SARS-CoV-2 coronavirus evolution in human hosts.

As year 2020 came to a close, several new strains have been reported for the SARS-CoV-2 coronavirus, the agent responsible for the COVID-19 pandemic that has afflicted us all this past year. However, it is difficult to comprehend the scale, in sequence space, geographical location and time, at which SARS-CoV-2 mutates and evolves in its human hosts. To get an appreciation for the rapid evolution of the coronavirus, we built interactive scalable vector graphics (SVG) maps that show daily nucleotide variations in genomes from the six most populated continents compared to that of the initial, ground-zero SARS-CoV-2 isolate sequenced at the beginning of the year. The attached compressed file package comprises SARS-CoV-2 mutation timemaps for 2020 and 2021, updated with data submitted to GISAID (gisaid.org) as of January 25th 2021 (inclusive). It is a snapshot of the webpage hosting these maps (https://bcgsc.github.io/SARS2) on that day.

Background: Nearly 30,000 patients with coronavirus disease-2019 (COVID-19) have been hospitalized in New York City as of April 14th, 2020. Data on the epidemiology, clinical course, and outcomes of critically ill patients with COVID-19 in this setting are needed. Methods: We prospectively collected clinical, biomarker, and treatment data on critically ill adults with laboratory-confirmed-COVID-19 admitted to two hospitals in northern Manhattan between March 2nd and April 1st, 2020. The primary outcome was in-hospital mortality. Secondary outcomes included frequency and duration of invasive mechanical ventilation, frequency of vasopressor use and renal-replacement-therapy, and time to clinical deterioration following hospital admission. The relationship between clinical risk factors, biomarkers, and in-hospital mortality was modeled using Cox-proportional-hazards regression. Each patient had at least 14 days of observation. Results: Of 1,150 adults hospitalized with COVID-19 during the study period, 257 (22%) were critically ill. The median age was 62 years (interquartile range [IQR] 51-72); 170 (66%) were male. Two-hundred twelve (82%) had at least one chronic illness, the most common of which were hypertension (63%; 162/257) and diabetes mellitus (36%; 92/257). One-hundred-thirty-eight patients (54%) were obese, and 13 (5%) were healthcare workers. As of April 14th, 2020, in-hospital mortality was 33% (86/257); 47% (122/257) of patients remained hospitalized. Two-hundred-one (79%) patients received invasive mechanical ventilation (median 13 days [IQR 9-17]), and 54% (138/257) and 29% (75/257) required vasopressors and renal-replacement-therapy, respectively. The median time to clinical deterioration following hospital admission was 3 days (IQR 1-6). Older age, hypertension, chronic lung disease, and higher concentrations of interleukin-6 and d-dimer at admission were independently associated with in-hospital mortality. Conclusions: Critical illness among patients hospitalized with COVID-19 in New York City is common and associated with a high frequency of invasive mechanical ventilation, extra-pulmonary organ dysfunction, and substantial in-hospital mortality.