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In vertebrates, the RNA-binding protein (RBP) dead end 1 (DND1) is essential for primordial germ cell (PGC) survival and maintenance of cell identity. In multiple species, Dnd1 loss or mutation leads to severe PGC loss soon after specification or, in some species, germ cell transformation to somatic lineages. Our investigations into the role of DND1 in PGC specification and differentiation have been limited by the absence of an available antibody. To address this problem, we used CRISPR/Cas9 gene editing to establish a transgenic mouse line carrying a DND1GFP fusion allele. We present imaging analysis of DND1GFP expression showing that DND1GFP expression is heterogeneous among male germ cells (MGCs) and female germ cells (FGCs). DND1GFP was detected in MGCs throughout fetal life but lost from FGCs at meiotic entry. In postnatal and adult testes, DND1GFP expression correlated with classic markers for the premeiotic spermatogonial population. Utilizing the GFP tag for RNA immunoprecipitation (RIP) analysis in MGCs validated this transgenic as a tool for identifying in vivo transcript targets of DND1. The DND1GFP mouse line is a novel tool for isolation and analysis of embryonic and fetal germ cells, and the spermatogonial population of the postnatal and adult testis. Summary sentence Characterization of this novel transgenic mouse showed that DND1GFP is expressed throughout the pre-meiotic germline, supports growing evidence in the field of germ cell heterogeneity, and demonstrated the tagged allele can be used for identification of DND1 targets.

In vertebrates, the RNA-binding protein (RBP) dead end 1 (DND1) is essential for primordial germ cell (PGC) survival and maintenance of cell identity. In multiple species, Dnd1 loss or mutation leads to severe PGC loss soon after specification or, in some species, germ cell transformation to somatic lineages. Our investigations into the role of DND1 in PGC specification and differentiation have been limited by the absence of an available antibody. To address this problem, we used CRISPR/Cas9 gene editing to establish a transgenic mouse line carrying a DND1 (GFP) fusion allele. We present imaging analysis of DND1 (GFP) expression showing that DND1 (GFP) expression is heterogeneous among male germ cells (MGCs) and female germ cells (FGCs). DND1 (GFP) was detected in MGCs throughout fetal life but lost from FGCs at meiotic entry. In postnatal and adult testes, DND1 (GFP) expression correlated with classic markers for the premeiotic spermatogonial population. Utilizing the GFP tag for RNA immunoprecipitation (RIP) analysis in MGCs validated this transgenic as a tool for identifying in vivo transcript targets of DND1. The DND1 (GFP) mouse line is a novel tool for isolation and analysis of embryonic and fetal germ cells, and the spermatogonial population of the postnatal and adult testis. Characterization of this novel transgenic mouse showed that DND1GFP is expressed throughout the pre-meiotic germline, supports growing evidence in the field of germ cell heterogeneity, and demonstrated the tagged allele can be used for identification of DND1 targets.

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.

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.

BackgroundImmune checkpoint inhibition (ICI) has led to improved response rates in metastatic cancer, however only a subset of patients respond. The exact reason(s) for lack of response are an active area of research, and environmental exposures that alter systemic immunity might impact ICI efficacy. Alcohol exposure is a common lifestyle factor with known detrimental effects on adaptive immune cell function. Therefore, we hypothesized that alcohol intake would negatively impact ICI efficacy.MethodsWe performed a retrospective study of 238 patients treated with ICI therapy for lung, bladder, melanoma, or head and neck cancer, associating survival with drinking history and tumor transcriptomic features. To better understand the immunomodulatory effects of alcohol exposure, we established murine models of lung (LN4K1) and bladder (MB49) tumors in which mice received either 2.5g/kg (moderate dose) or 5g/kg (binge dose) of ethanol pre-treatment for 5 weeks (5 days/week, i.g.) prior to tumor injection. At day 8, 11, and 14 mice were treated with anti-PD1 (10 ug/kg), and tumor size was monitored. Additionally, we performed flow cytometry to evaluate leukocyte phenotypes in the tumor microenvironment and spleen on day 11 post-tumor. We also used RNA sequencing and functional assays (MTT and EliSPOT) of OT-1 T cells to better understand ethanol’s impact on T cell function.ResultsAlcohol exposure was associated with reduced survival in human cancer patients treated with anti-PD-1 therapy (Lung HR: 1.7, Bladder HR: 2.27). In the murine lung model, ethanol significantly reduced the efficacy of the ICI regimen, worsening survival from 58 days to 86 days. In the bladder model, both moderate and binge alcohol decreased survival post-immunotherapy from 89% to near 30%. In murine bladder tumors, we found significant decreases in the number of CD4+ and CD8+ T cells. We also found that CD4+ differentiation was altered away from a Th1 phenotype in favor of Th2 and Th17 phenotypes. In the spleen, FoxP3 and IL10 expression were significantly increased in both CD4+ and CD8+ T cells, suggesting that alcohol induced regulatory T cell phenotypes. In addition, CD8 T cells exposed to ethanol showed reduced capacity for IFN stimulation (via EliSPOT) and cytotoxicity (via MTT assay).ConclusionsAlcohol exposure was associated with decreased efficacy of ICI therapy. These studies implicate alcohol-induced T cell dysfunction through loss of T cells in the tumoral space, impaired effector T cell differentiation, and loss of CD8+ T cell cytotoxicity.Ethics ApprovalAll animal studies were approved by University of North Carolina IUCAC under protocol #23-230. Human data usage was approved by University of North Carolina IRB under protocol LCCC1727.

The adult spermatogonial stem cell population arises from pluripotent primordial germ cells (PGCs) that enter the fetal testis around embryonic day 10.5 (E10.5). These cells undergo rapid mitotic proliferation, then enter a prolonged period of cell cycle arrest (G1/G0) during which they transition to pro-spermatogonia. In mice homozygous for the Ter mutation in the RNA-binding protein Dnd1 (Dnd1Ter/Ter), many germ cells fail to enter G1/G0, and give rise to teratomas, tumors in which many embryonic cell types are represented. To investigate the origin of these tumors, we sequenced the transcriptome of male germ cells in Dnd1Ter/Ter mutants at E12.5, E13.5, and E14.5, just prior to the formation of teratomas, and correlated this information with direct targets of DND1 identified by DO-RIP-Seq. Consistent with previous results, we found that DND1 controls the down regulation of many genes associated with pluripotency and active cell cycle, including elements of the mTor, Hippo and Bmp/Nodal signaling pathways. However, DND1 targets also include genes associated with male differentiation including a large group of chromatin regulators activated in wild type but not mutant germ cells during the transition between E13.5 and E14.5. These results suggest multiple functions of DND1, and link DND1 to the initiation of epigenetic modifications in male germ cells.

Immune checkpoint inhibition (ICI) has improved clinical outcomes for certain patients with cancer. However, only a minority of patients have durable responses with underlying causes of differential immune responses across individuals often being unknown. Lifestyle exposures impact immune function and may subsequently alter the response to ICI. Alcohol use is common among cancer patients with known detrimental effects on adaptive immune function. However, its impact on ICI efficacy remains unknown. To determine if alcohol impacts ICI therapies, we performed a retrospective assessment of outcomes for patients receiving anti-PD1 ICI across tumor types and employed preclinical mouse models of ICI for lung and bladder cancer. Alcohol use reduced ICI efficacy in human patients treated with anti-PD1 for lung and bladder cancer (HR ~2.0) as well as in murine models ICI in lung (LN4K1) and bladder (MB49) cancer. Alcohol reduced tumoral T cell numbers, promoting less productive Th2 and Th17 CD4+ phenotypes intratumorally and regulatory phenotypes in the periphery. In both rodent and human T cells, alcohol disrupted T cell activation and effector functions. Thus, alcohol use negatively impacts ICI efficacy warranting alcohol cessation for this patient population.

There 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). Additionally, such vaccines can be rapidly manufactured in a distributed manner. In this study, 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. We begin with an exploration of the space of possible T cell epitopes in SARS-CoV-2 with interrogation of predicted HLA-I and HLA-II ligands, overlap between predicted ligands, protein source, as well as concurrent human/murine coverage. Beyond MHC affinity, 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 and CD8 T cell epitopes. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering to select regions with surface accessibility, high sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. From 58 initial candidates, three B cell epitope regions were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we propose a set of SARS-CoV-2 vaccine peptides for use in subsequent murine studies and clinical trials.

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.