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Mycobacterium tuberculosis continues to cause devastating levels of mortality due to tuberculosis (TB). The failure to control TB stems from an incomplete understanding of the highly specialized strategies that M. tuberculosis utilizes to modulate host immunity and thereby persist in host lungs. Here, we show that M. tuberculosis induced the expression of indoleamine 2,3-dioxygenase (IDO), an enzyme involved in tryptophan catabolism, in macrophages and in the lungs of animals (mice and macaque) with active disease. In a macaque model of inhalation TB, suppression of IDO activity reduced bacterial burden, pathology, and clinical signs of TB disease, leading to increased host survival. This increased protection was accompanied by increased lung T cell proliferation, induction of inducible bronchus-associated lymphoid tissue and correlates of bacterial killing, reduced checkpoint signaling, and the relocation of effector T cells to the center of the granulomata. The enhanced killing of M. tuberculosis in macrophages in vivo by CD4⁺ T cells was also replicated in vitro, in cocultures of macaque macrophages and CD4⁺ T cells. Collectively, these results suggest that there exists a potential for using IDO inhibition as an effective and clinically relevant host-directed therapy for TB.

Background Early in the pandemic, we designed a SARS-CoV-2 peptide vaccine containing epitope regions optimized for concurrent B cell, CD4 + T cell, and CD8 + T cell stimulation. The rationale for this design was to drive both humoral and cellular immunity with high specificity while avoiding undesired effects such as antibody-dependent enhancement (ADE). Methods We explored the set of computationally predicted SARS-CoV-2 HLA-I and HLA-II ligands, examining protein source, concurrent human/murine coverage, and population coverage. Beyond MHC affinity, T cell vaccine candidates were further refined by predicted immunogenicity, sequence conservation, source protein abundance, and coverage of high frequency HLA alleles. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering for surface accessibility, sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. Results From 58 initial candidates, three B cell epitope regions were identified. From 3730 (MHC-I) and 5045 (MHC-II) candidate ligands, 292 CD8 + and 284 CD4 + T cell epitopes were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we proposed a set of 22 SARS-CoV-2 vaccine peptides for use in subsequent murine studies. We curated a dataset of ~ 1000 observed T cell epitopes from convalescent COVID-19 patients across eight studies, showing 8/15 recurrent epitope regions to overlap with at least one of our candidate peptides. Of the 22 candidate vaccine peptides, 16 (n = 10 T cell epitope optimized; n = 6 B cell epitope optimized) were manually selected to decrease their degree of sequence overlap and then synthesized. The immunogenicity of the synthesized vaccine peptides was validated using ELISpot and ELISA following murine vaccination. Strong T cell responses were observed in 7/10 T cell epitope optimized peptides following vaccination. Humoral responses were deficient, likely due to the unrestricted conformational space inhabited by linear vaccine peptides. Conclusions Overall, we find our selection process and vaccine formulation to be appropriate for identifying T cell epitopes and eliciting T cell responses against those epitopes. Further studies are needed to optimize prediction and induction of B cell responses, as well as study the protective capacity of predicted T and B cell epitopes.

Although it is accepted that the environment within the granuloma profoundly affects Mycobacterium tuberculosis (Mtb) and infection outcome, our ability to understand Mtb gene expression in these niches has been limited. We determined intragranulomatous gene expression in human-like lung lesions derived from nonhuman primates with both active tuberculosis (ATB) and latent TB infection (LTBI). We employed a non-laser-based approach to microdissect individual lung lesions and interrogate the global transcriptome of Mtb within granulomas. Mtb genes expressed in classical granulomas with central, caseous necrosis, as well as within the caseum itself, were identified and compared with other Mtb lesions in animals with ATB (n = 7) or LTBI (n = 7). Results were validated using both an oligonucleotide approach and RT-PCR on macaque samples and by using human TB samples. We detected approximately 2,900 and 1,850 statistically significant genes in ATB and LTBI lesions, respectively (linear models for microarray analysis, Bonferroni corrected, P < 0.05). Of these genes, the expression of approximately 1,300 (ATB) and 900 (LTBI) was positively induced. We identified the induction of key regulons and compared our results to genes previously determined to be required for Mtb growth. Our results indicate pathways that Mtb uses to ensure its survival in a highly stressful environment in vivo. A large number of genes is commonly expressed in granulomas with ATB and LTBI. In addition, the enhanced expression of the dormancy survival regulon was a key feature of lesions in animals with LTBI, stressing its importance in the persistence of Mtb during the chronic phase of infection.

BackgroundThere is an urgent need for a vaccine with efficacy against SARS-CoV-2. We hypothesize that peptide vaccines containing epitope regions optimized for concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation would drive both humoral and cellular immunity with high specificity, potentially avoiding undesired effects such as antibody-dependent enhancement (ADE) (figure 1). Leveraging methods initially developed for prediction of tumor-specific antigen targets, we combine computational prediction of T cell epitopes, recently published B cell epitope mapping studies, and epitope accessibility to select candidate peptide vaccines for SARS-CoV-2 (figure 2).MethodsSARS-CoV-2 HLA-I and HLA-II ligands were predicted using multiple MHC binding prediction software. T cell vaccine candidates were further refined by predicted immunogenicity, viral source protein abundance, sequence conservation, coverage of high frequency HLA alleles, and co-localization of CD4+/CD8+ T cell epitopes. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, filtering to select regions with surface accessibility, high sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. Using murine compatible T/B cell epitopes, vaccine studies were performed with downstream ELISA/ELISpot to monitor immunogenicity.ResultsWe observed distribution of HLA-I (n = 2486) and -II (n = 3138) ligands evenly across the SARS-CoV-2 proteome, with significant overlap between predicted human and murine ligands (figure 3). Applying a multivariable immunogenicity model trained from IEDB viral tetramer data (AUC 0.7 and 0.9 for HLA-I and -II, respectively), alongside filters for entropy and protein expression resulted in 292 CD8+ and 616 CD4+ epitopes (figure 4). From an initial pool of 58 B cell epitope candidates, three epitope regions were identified (figure 5). Combining B cell and T cell analyses, alongside manufacturability heuristic, we propose a set of SARS-CoV-2 vaccine peptides for use in subsequent murine studies and clinical trials (figure 6). Preliminary murine studies demonstrate evidence of T and B cell activation (figure 7).Abstract 478 Figure 1Summary of combination CD4+/CD8+ T cell and B cell SARS-CoV-2 peptide vaccine. Humoral immunity (blue dashed box) is targeted through B cell and HLA-II epitopes, aimed at viral neutralization while avoiding non-neutralizing and ADE promoting targets. Cellular immunity (red dashed box) is targeted through HLA-I and HLA-II epitopes, aimed to clear virally infected cellsAbstract 478 Figure 2Summary of B cell and CD4+/CD8+ epitope prediction workflows. Pathways are colored by B cell (blue), human T cell (black), and murine T cell (red) epitope prediction workflows. Color bars represent proportions of epitopes derived from internal proteins (ORF), nucleocapsid phosphoprotein, and surface-exposed proteins (spike, membrane, envelope)Abstract 478 Figure 3Landscape of SARS-CoV-2 MHC ligands. (A&B) Selection criteria for (A) HLA-I and (B) HLA-II SARS-CoV-2 HLA ligand candidates. Scatterplot (bottom) shows predicted (x-axis) versus IEDB (y-axis) binding affinity, with horizontal line representing 500 nM IEDB binding affinity and vertical line representing corresponding predicted binding affinity for 90% specificity in binding prediction. Histogram (top) shows all predicted SARS-CoV-2 HLA ligand candidates. (C) Landscape of predicted HLA ligands, showing nested HLA ligands comprising HLA-I and -II ligands with complete overlap (top), and LOESS fitted curve (span = 0.1) for HLA-I/II ligands by location along the SARS-CoV2 proteome (bottom). Red track represents SARS epitopes identified in literature review with sequence identity in SARS-CoV-2. Predicted HLA ligands with conserved sequences to this literature set are represented in the lollipop plot with a red stick. (D) Summary of total number of predicted HLA-I/II ligands and nested HLA ligands. (E) Summary of nested HLA ligand coverage by protein, with raw counts (left) or counts normalized by protein length (right). (F) Summary of murine/human MHC ligand overlap. (G) Distribution of population frequencies among predicted HLA-I, -II, and nested HLA ligandsAbstract 478 Figure 4Prediction of SARS-CoV-2 T cell epitopes. (Top) Summary of predicted (left) and IEDB-defined (right) SARS-CoV-2 HLA ligands, showing proportions of each derivative protein. (Middle) Funnel plot representing counts of HLA-I (red text), HLA-II (blue text), and nested HLA (violet text) ligands along with proportions of HLA-I (top bar) and HLA-II (bottom bar) alleles at each filtering step. (Bottom) Summary of CD8+ (red, top), CD4+ (blue, bottom), and nested T cell epitopes (middle) after filtering criteria in S, M, and N proteins. Y-axis and size represent the population frequency of each CD8+ and CD4+ epitopes by circles. Middle track of diamonds represents overlaps between CD8+ and CD4+ epitopes, showing the overlap with greatest population frequency (size) for each region of overlap. Color of diamonds represents the proportion of overlap between CD4+ and CD8+ epitope sequences.Abstract 478 Figure 5Selection of SARS-CoV-2 B cell epitope regions. (A) SARS-CoV-2 linear B cell epitopes curated from epitope mapping studies. X-axis represents amino acid position along the SARS-CoV-2 spike protein, with labeled start sites. (B) Schematic for filtering criteria of B cell epitope candidates. (C) Spike protein amino acid sequence, with overlay of selection features prior to filtering. Polymorphic residues are red, glycosites are blue, accessible regions highlighted in yellow. The receptor binding domain (RBD), fusion peptide (FP), and HR1/HR2 regions are outlined. (D) Spike protein functional regions (RBD, FP, HR1/2) amino acid sequences, with residues colored by how many times they occur in identified epitopes. Selected accessible sub-sequences of known antibody epitopes highlighted in purple outline. (E) S protein trimer crystal structure with glycosylation, with final linear epitope regions highlighted by colorAbstract 478 Figure 6T cell and B cell vaccine candidates. (A) 27mer vaccine peptide sets selecting for best CD4+, CD8+, CD4+/CD8+, and B cell epitopes with HLA-I, HLA-II, and total population coverage. (B) Unified list of all selected 27mer vaccine peptides. Vaccine peptides containing predicted ligands for murine MHC alleles (H2-b and H2-d haplotypes) are indicated in their respective columnsAbstract 478 Figure 7Immunogenicity of murine-compatible peptide vaccines. (A) ELISA result: peptides derived from three B cell vaccine candidate regions were coated on peptide capture plates, either in combination by overlapping core epitopes (1+2 and 3+4) or alone (5). (B) ELISpot results: splenocytes from animals vaccinated against predicted B cell epitopes (1–5) or measles peptide control (M; adapted from Obeid et al. 1995). Each point represents the average of technical triplicates, background subtracted against no-peptide control. (A&B) Colors represent adjuvant used for vaccination. P-values shown above each graph represent pair-wise Mann-Whitney u-testConclusionsA peptide vaccine targeting B cells, CD4+ T cells, and CD8+ T cells in parallel may prove an important part of a multifaceted response to the COVID-19 pandemic. Adapting methods for predicting tumor-specific antigens, we presented a set of peptide candidates with high overlap for T and B cell epitopes and broad haplotype population coverage, with validation of immunogenicity in murine vaccine studies.AcknowledgementsThe authors appreciate funding support from University of North Carolina University Cancer Research Fund (AR and BGV), the Susan G. Komen Foundation (BGV), the V Foundation for Cancer Research (BGV), and the National Institutes of Health (CCS, 1F30CA225136). We would like to thank members of the #DownWithTheCrown Slack channel for helpful discussion and feedback.

This thesis examines the use of defensive strategies in relation to territories year round in the northern cardinal (Cardinalis cardinalis). Responses to recorded neighbor song and stranger song playback from the middle of a focal male’s territory were measured. This allowed for an estimation of aggression in both the winter and spring seasons. Each focal male was subjected to both treatments (stranger song and neighbor song). Males were more responsive over-all to neighbor song playback, however in the winter months, persistence of response to neighbor song playback increased. It was also shown that southeastern United States cardinals show year-round territory occupancy and more importantly the tendency to defend that territory during the entire year. Blood collected from a small number of birds during a neighbor STI trial shows that circulating testosterone does not significantly change from baselines or birds being challenged with a strange song playback.

Neural activity is increasingly recognized as a critical regulator of cancer growth. In the brain, neuronal activity robustly influences glioma growth both through paracrine mechanisms and through electrochemical integration of malignant cells into neural circuitry via neuron-to-glioma synapses, while perisynaptic neurotransmitter signaling drives breast cancer brain metastasis growth. Outside of the CNS, innervation of tumors such as prostate, breast, pancreatic and gastrointestinal cancers by peripheral nerves similarly regulates cancer progression. However, the extent to which the nervous system regulates lung cancer progression, either in the lung or when metastatic to brain, is largely unexplored. Small cell lung cancer (SCLC) is a lethal high-grade neuroendocrine tumor that exhibits a strong propensity to metastasize to the brain. Here we demonstrate that, similar to glioma, metastatic SCLC cells in the brain co-opt neuronal activity-regulated mechanisms to stimulate growth and progression. Optogenetic stimulation of cortical neuronal activity drives proliferation and invasion of SCLC brain metastases. In the brain, SCLC cells exhibit electrical currents and consequent calcium transients in response to neuronal activity, and direct SCLC cell membrane depolarization is sufficient to promote the growth of SCLC tumors. In the lung, vagus nerve transection markedly inhibits primary lung tumor formation, progression and metastasis, highlighting a critical role for innervation in overall SCLC initiation and progression. Taken together, these studies illustrate that neuronal activity plays a crucial role in dictating SCLC pathogenesis in both primary and metastatic sites.

We vaccinated BALB/c mice with peptides derived from the SARS-CoV-2 proteome selected in silico to elicit T-cell responses and/or B-cell responses against linear epitopes. These peptides were administered in combination with either of two adjuvants, poly(I:C) and the STING agonist BI-1387466. Antibody responses against predicted linear epitopes were not observed but both adjuvants consistently elicited T-cell responses to the same peptides, which were primarily from the set chosen for predicted T-cell immunogenicity. The magnitude of T-cell responses was significantly higher with BI-1387466 compared with poly(I:C). Neither adjuvant group, however, provided any protection against infection with the murine adapted virus SARS-CoV-2-MA10 or from disease following infection. In light of more recent evidence for protection from severe disease mediated by CD8+ T-cells, we suspect that the epitopes selected for vaccination were not presented by infected murine cells.

There is significant interest in T-cell mediated immunity against SARS-CoV-2. Both vaccination and infection have been observed to elicit durable T-cell responses against the virus. The classical role of CD4+ T-cell responses in coordinating humoral immunity is well understood but it is less clear to what degree, if any, T-cell responses play a direct protective role against infection In this study we vaccinated BALB/c mice with peptides derived from the SARS-CoV-2 proteome designed to either elicit T-cell responses or B-cell responses against linear epitopes. These peptides were administered in combination with either of two adjuvants, poly(I:C) and the STING agonist BI-1387466. Both adjuvants consistently elicited responses against the same peptides, preferentially from the group selected for predicted T-cell immunogenicity. The magnitude of T-cell responses was, however, significantly higher with BI-1387466 compared with poly(I:C). Neither adjuvant group, however, provided any protection against infection with the murine adapted virus SARS-CoV-2-MA10 or from disease following infection. Competing Interest Statement The authors have declared no competing interest.