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In Caenorhabditis elegans, mutations in WDR-5 and other components of the COMPASS H3K4 methyltransferase complex extend lifespan and enable its inheritance. Here, we show that wdr-5 mutant longevity is itself a transgenerational trait that corresponds with a global enrichment of the heterochromatin factor H3K9me2 over twenty generations. In addition, we find that the transgenerational aspects of wdr-5 mutant longevity require the H3K9me2 methyltransferase MET-2, and can be recapitulated by removal of the putative H3K9me2 demethylase JHDM-1. Finally, we show that the transgenerational acquisition of longevity in jhdm-1 mutants is associated with accumulating genomic H3K9me2 that is inherited by their long-lived wild-type descendants at a subset of loci. These results suggest that heterochromatin facilitates the transgenerational establishment and inheritance of a complex trait. Based on these results, we propose that transcription-coupled H3K4me via COMPASS limits lifespan by encroaching upon domains of heterochromatin in the genome.

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.

The Hedgehog signaling pathway is part of the ancient developmental-evolutionary animal toolkit. Frequently co-opted to pattern new structures, the pathway is conserved among eumetazoans yet flexible and pleiotropic in its effects. The Hedgehog receptor, Patched, is transcriptionally activated by Hedgehog, providing essential negative feedback in all tissues. Our locus-wide dissections of the cis-regulatory landscapes of fly patched and mouse Ptch1 reveal abundant, diverse enhancers with stage- and tissue-specific expression patterns. The seemingly simple, constitutive Hedgehog response of patched/Ptch1 is driven by a complex regulatory architecture, with batteries of context-specific enhancers engaged in promoter-specific interactions to tune signaling individually in each tissue, without disturbing patterning elsewhere. This structure—one of the oldest cis-regulatory features discovered in animal genomes—explains how patched/Ptch1 can drive dramatic adaptations in animal morphology while maintaining its essential core function. It may also suggest a general model for the evolutionary flexibility of conserved regulators and pathways.

Biochar, a carbon-rich material derived from the pyrolysis of organic matter, exhibits beneficial chemical and physical properties when added to a soilless medium. Research on the use of biochar to improve plant productivity and growth has increased over the past decade, and has focused on using biochar as an alternative to sphagnum peatmoss. However, little work has been done to determine whether biochar can be used to partially replace commercially available sphagnum peatmoss–based greenhouse medium in vegetable transplant production. This study investigated the potential for supplementing a greenhouse growing medium with biochar for ‘Paladin’ pepper ( Capsicum annuum ) transplant production. Biochar was added to a soilless mix at rates of 0%, 20%, 40%, 60%, or 80% (by weight). Pepper seedlings were grown for 56 days in 50-, 72-, or 98-cell transplant trays at each of the five levels of biochar concentration. Germination increased in the 50- and 72- cell trays with 20%, 40%, and 60% biochar; however, biochar had no effect on germination in the 98-cell tray. Seedling height and dry weight decreased as biochar concentration and cell number increased. Seedling stem diameter also decreased with increasing cell number and biochar concentration. Leaf SPAD readings (indirect measurement of chlorophyll) decreased with increasing biochar rate. Medium pH increased with increasing biochar application rates. Higher rates of biochar (60% and 80%) increased pH well beyond 7.0 and negatively affected transplant growth. Overall results indicate positive effect of biochar in sphagnum peatmoss–based growing mix on seedling growth characteristics; although higher biochar concentrations could negatively affect seedling growth. Biochar can successfully replace up to 40% of sphagnum peatmoss–based growing medium and serve as a sustainable alternative medium in vegetable transplant production.

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.

The proper coordination of transcription factors, ATP dependent chromatin remodelers and histone modifications is essential for tissue specific gene expression, but how gene expression is regulated at these different levels is not well understood. In , H3K4 methylation that is acquired in the germline is reprorgammed at fertilization by the H3K4me1/2 demethlyase SPR-5/LSD1/KDM1A and the H3K9 methyltransferase MET2/SETDB1/KMT2E. SPR-5/MET-2 maternal reprogramming is required to help establish the germline-soma distinction and prevent developmental delay by preventing inherited H3K4 methylation from inappropriately maintaining germline gene expression in somatic tissues. To determine if the DREAM transcriptional repressor complex and the MEC NuRD ATP dependent nucleosome remodeling and histone deacetylase complex function to reinforce SPR-5/MET-2 maternal reprogamming, we asked if loss of these complexes affects the ectopic germline transcription and developmental delay in double mutants. We find that knocking down the DREAM or MEC NuRD complexes specifically exacerbates the developmental delay and ectopic expression of germline genes in the soma caused by loss of SPR-5 and MET-2. In addition, the DREAM and MEC NuRD complexes bind together at SPR-5/MET-2 reprogramming targets. These data suggest that the transcriptional repression of DREAM and the ATP dependent chromatin remodeling and deactylation activities of the MEC NuRD complex are required somatically to reinforce maternal histone reporgamming by SPR-5/MET-2. Thus, these data provide a novel example of how gene regulation is coordinated at multiple levels to maintain the germlinesoma distinction and ensure proper development.

While the kinesin-2 motors KIF3A and KIF3B have essential roles in ciliogenesis and Hedgehog (HH) signal transduction, potential role(s) for another kinesin-2 motor, KIF17, in HH signaling have yet to be explored. Here, we investigated the contribution of KIF17 to HH-dependent cerebellar development, where Kif17 is expressed in both HH-producing Purkinje cells and HH-responding cerebellar granule neuron progenitors (CGNPs). Germline Kif17 deletion in mice results in cerebellar hypoplasia due to reduced CGNP proliferation, a consequence of decreased HH pathway activity mediated through decreased Sonic HH (SHH) protein. Notably, Purkinje cell-specific Kif17 deletion phenocopies Kif17 germline mutants. Surprisingly, CGNP-specific Kif17 deletion results in the opposite phenotype— increased CGNP proliferation and HH target gene expression due to altered GLI transcription factor processing. Together these data identify KIF17 as a key regulator of HH-dependent cerebellar development, with dual and opposing roles in HH-producing Purkinje cells and HH-responding CGNPS. Competing Interest Statement The authors have declared no competing interest.

Embryos undergo extensive reprogramming at fertilization to prevent the inappropriate inheritance of histone methylation. In C. elegans, this reprogramming is mediated by the H3K4me2 demethylase, SPR-5, and the H3K9 methyltransferase, MET-2. In contrast to this reprogramming, the H3K36 methyltransferase, MES-4, maintains H3K36me2/3 at germline genes between generations to help re-establish the germline. To determine whether the MES-4 germline inheritance system antagonizes spr-5; met-2 reprogramming, we examined the interaction between these two systems. We find that the developmental delay of spr-5; met-2 mutant progeny is associated with ectopic H3K36me2/3 and the ectopic expression of MES-4 targeted germline genes in somatic tissues. Furthermore, the developmental delay is dependent upon MES-4 and the H3K4 methyltransferase, SET-2. We propose that the MES-4 inheritance system prevents critical germline genes from being repressed by maternal spr-5; met-2 reprogramming. Thus, the balance of inherited histone modifications is necessary to distinguish germline versus soma and prevent developmental delay. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE143839

Hedgehog (HH) signaling is an evolutionary conserved pathway that is indispensable for embryonic development and adult tissue homeostasis. GLI proteins are the transcriptional effector molecules of the HH signaling pathway that act in the nucleus to both activate and repress HH target gene expression. GLI proteins traffic between multiple subcellular compartments including the nucleus, cytoplasm, and primary cilium. Disruption in GLI trafficking results in defects in GLI protein activity, yet the mechanisms regulating these trafficking events are unclear. Kinesin-2 motor complexes, namely the heterotrimeric KIF3A/KIF3B/KAP3 complex and the homodimeric KIF17 complex, regulate both ciliary and non-ciliary transport of protein cargo, but whether these motor complexes regulate GLI proteins directly has not been tested. To examine a role for the heterotrimeric KIF3A/KIF3B/KAP3 kinesin-2 motor complex in regulating GLI activity, I performed a series of structure-function analyses using biochemical, cell signaling and in vivo approaches that define novel, specific interactions between GLI proteins and two components of this complex, KAP3 and KIF3A. I find that all three mammalian GLI proteins interact with KAP3 and map specific interaction sites in both proteins. Further, I find that GLI proteins interact selectively with KIF3A, but not KIF3B and that GLI interacts synergistically with KAP3 and KIF3A. Using a combination of cell signaling assays and chicken in ovo electroporations, I demonstrate that KAP3 interactions restrict GLI activator, but not GLI repressor function. These data suggest that GLI interactions with KIF3A/KIF3B/KAP3 complexes are essential for proper GLI transcriptional activity. Further, I provide evidence that homodimeric KIF17 interacts with all mammalian GLI proteins and that GLI1 protein expression is decreased in cells stably expressing a dominant-negative version of KIF17. Finally, I show that KIF17 and GLI proteins are expressed in overlapping cell layers in the developing cerebellum, and that Kif17-/- mice display smaller cerebella. These data suggest a model in which KIF17 is playing a tissue-specific role in regulating HH signaling through interactions with GLI proteins. Together, my findings define novel interactions between GLI proteins and two distinct kinesin-2 motor complexes and further demonstrate that these interactions are required for proper GLI transcriptional activity.

During active transcription, the COMPASS complex methylates histone H3 at lysine 4 (H3K4me). In Caenorhabditis elegans, mutations in COMPASS subunits, including WDR-5, extend lifespan and enable the inheritance of increased lifespan in wild-type descendants. Here we show that the increased lifespan of wdr-5 mutants is itself a transgenerational trait that manifests after eighteen generations and correlates with changes in the heterochromatin factor H3K9me2. Additionally, we find that wdr-5 mutant longevity and its inheritance requires the H3K9me2 methyltransferase MET-2 and can be recapitulated by a mutation in the putative H3K9me2 demethylase JHDM-1. These data suggest that lifespan is constrained by reduced H3K9me2 due to transcription-coupled H3K4me. wdr-5 mutants alleviate this burden, extending lifespan and enabling the inheritance of increased lifespan. Thus, H3K9me2 functions in the epigenetic establishment and inheritance of a complex trait. Based on this model, we propose that lifespan is limited by the germline in part because germline transcription reduces heterochromatin. Footnotes * https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE129928