STING-induced regulatory B cells compromise NK function in cancer immunity.

An immunosuppressive tumour microenvironment is a major obstacle in the control of pancreatic and other solid cancers1-3. Agonists of the stimulator of interferon genes (STING) protein trigger inflammatory innate immune responses to potentially overcome tumour immunosuppression4. Although these agonists hold promise as potential cancer therapies5, tumour resistance to STING monotherapy has emerged in clinical trials and the mechanism(s) is unclear5-7. Here we show that the administration of five distinct STING agonists, including cGAMP, results in an expansion of human and mouse interleukin (IL)-35+ regulatory B cells in pancreatic cancer. Mechanistically, cGAMP drives expression of IL-35 by B cells in an IRF3-dependent but type I interferon-independent manner. In several preclinical cancer models, the loss of STING signalling in B cells increases tumour control. Furthermore, anti-IL-35 blockade or genetic ablation of IL-35 in B cells also reduces tumour growth. Unexpectedly, the STING-IL-35 axis in B cells reduces proliferation of natural killer (NK) cells and attenuates the NK-driven anti-tumour response. These findings reveal an intrinsic barrier to systemic STING agonist monotherapy and provide a combinatorial strategy to overcome immunosuppression in tumours.

Balance between immunoregulatory B cells and plasma cells drives pancreatic tumor immunity.

Plasma cell responses are associated with anti-tumor immunity and favorable response to immunotherapy. B cells can amplify anti-tumor immune responses through antibody production; yet B cells in patients and tumor-bearing mice often fail to support this effector function. We identify dysregulated transcriptional program in B cells that disrupts differentiation of naive B cells into anti-tumor plasma cells. The signaling network contributing to this dysfunction is driven by interleukin (IL) 35 stimulation of a STAT3-PAX5 complex that upregulates the transcriptional regulator BCL6 in naive B cells. Transient inhibition of BCL6 in tumor-educated naive B cells is sufficient to reverse the dysfunction in B cell differentiation, stimulating the intra-tumoral accumulation of plasma cells and effector T cells and rendering pancreatic tumors sensitive to anti-programmed cell death protein 1 (PD-1) blockade. Our findings argue that B cell effector dysfunction in cancer can be due to an active systemic suppression program that can be targeted to synergize with T cell-directed immunotherapy.

Landscape and selection of vaccine epitopes in SARS-CoV-2.

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.

Landscape and Selection of Vaccine Epitopes in SARS-CoV-2.

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.

rmtA-Dependent Transcriptome and Its Role in Secondary Metabolism, Environmental Stress, and Virulence in Aspergillus flavus.

Aspergillus flavus colonizes numerous oil seed crops such as maize, peanuts, treenuts and cottonseed worldwide, contaminating them with aflatoxins and other harmful toxins. Previously our lab characterized the gene rmtA, which encodes an arginine methyltransferase in A. flavus, and demonstrated its role governing the expression of regulators in the aflatoxin gene cluster and subsequent synthesis of toxin. Furthermore, our studies revealed that rmtA also controls conidial and sclerotial development implicating it as an epigenetic regulator in A. flavus To confirm this, we performed a RNA sequencing analysis to ascertain the extent of rmtA's influence on the transcriptome of A. flavus In this analysis we identified over 2000 genes that were rmtA-dependent, including over 200 transcription factor genes, as well as an uncharacterized secondary metabolite gene cluster possibly responsible for the synthesis of an epidithiodiketopiperazine-like compound. Our results also revealed rmtA-dependent genes involved in multiple types of abiotic stress response in A. flavus Importantly, hundreds of genes active during maize infection were also regulated by rmtA In addition, in the animal infection model, rmtA was dispensable for virulence, however forced overexpression of rmtA increased mortality with respect to the wild type.

Bioinformatics Identification of Anti-CRISPR Loci by Using Homology, Guilt-by-Association, and CRISPR Self-Targeting Spacer Approaches.

Anti-CRISPR (Acr) loci/operons encode Acr proteins and Acr-associated (Aca) proteins. Forty-five Acr families have been experimentally characterized inhibiting seven subtypes of CRISPR-Cas systems. We have developed a bioinformatics pipeline to identify genomic loci containing Acr homologs and/or Aca homologs by combining three computational approaches: homology, guilt-by-association, and self-targeting spacers. Homology search found thousands of Acr homologs in bacterial and viral genomes, but most are homologous to AcrIIA7 and AcrIIA9. Investigating the gene neighborhood of these Acr homologs revealed that only a small percentage (23.0% in bacteria and 8.2% in viruses) of them have neighboring Aca homologs and thus form Acr-Aca operons. Surprisingly, although a self-targeting spacer is a strong indicator of the presence of Acr genes in a genome, a large percentage of Acr-Aca loci are found in bacterial genomes without self-targeting spacers or even without complete CRISPR-Cas systems. Additionally, for Acr homologs from genomes with self-targeting spacers, homology-based Acr family assignments do not always agree with the self-targeting CRISPR-Cas subtypes. Last, by investigating Acr genomic loci coexisting with self-targeting spacers in the same genomes, five known subtypes (I-C, I-E, I-F, II-A, and II-C) and five new subtypes (I-B, III-A, III-B, IV-A, and V-U4) of Acrs were inferred. Based on these findings, we conclude that the discovery of new anti-CRISPRs should not be restricted to genomes with self-targeting spacers and loci with Acr homologs. The evolutionary arms race of CRISPR-Cas systems and anti-CRISPR systems may have driven the adaptive and rapid gain and loss of these elements in closely related genomes.IMPORTANCE As a naturally occurring adaptive immune system, CRISPR-Cas (clustered regularly interspersed short palindromic repeats-CRISPR-associated genes) systems are widely found in bacteria and archaea to defend against viruses. Since 2013, the application of various bacterial CRISPR-Cas systems has become very popular due to their development into targeted and programmable genome engineering tools with the ability to edit almost any genome. As the natural off-switch of CRISPR-Cas systems, anti-CRISPRs have a great potential to serve as regulators of CRISPR-Cas tools and enable safer and more controllable genome editing. This study will help understand the relative usefulness of the three bioinformatics approaches for new Acr discovery, as well as guide the future development of new bioinformatics tools to facilitate anti-CRISPR research. The thousands of Acr homologs and hundreds of new anti-CRISPR loci identified in this study will be a valuable data resource for genome engineers to search for new CRISPR-Cas regulators.

Cell Wall Enzymes in Zygnema circumcarinatum UTEX 1559 Respond to Osmotic Stress in a Plant-Like Fashion.

Previous analysis of charophyte green algal (CGA) genomes and transcriptomes for specific protein families revealed that numerous land plant characteristics had already evolved in CGA. In this study, we have sequenced and assembled the transcriptome of Zygnema circumcarinatum UTEX 1559, and combined its predicted protein sequences with those of 13 additional species [five embryophytes (Emb), eight charophytes (Cha), and two chlorophytes (Chl) as the outgroup] for a comprehensive comparative genomics analysis. In total 25,485 orthologous gene clusters (OGCs, equivalent to protein families) of the 14 species were classified into nine OGC groups. For example, the Cha+Emb group contains 4,174 OGCs found in both Cha and Emb but not Chl species, representing protein families that have evolved in the common ancestor of Cha and Emb. Different OGC groups were subjected to a Gene Ontology (GO) enrichment analysis with the Chl+Cha+Emb group (including 5,031 OGCs found in Chl and Cha and Emb) as the control. Interestingly, nine of the 20 top enriched GO terms in the Cha+Emb group are cell wall-related, such as biological processes involving celluloses, pectins, lignins, and xyloglucans. Furthermore, three glycosyltransferase families (GT2, 8, 43) were selected for in-depth phylogenetic analyses, which confirmed their presence in UTEX 1559. More importantly, of different CGA groups, only Zygnematophyceae has land plant cellulose synthase (CesA) orthologs, while other charophyte CesAs form a CGA-specific CesA-like (Csl) subfamily (likely also carries cellulose synthesis activity). Quantitative real-time-PCR experiments were performed on selected GT family genes in UTEX 1559. After osmotic stress treatment, significantly elevated expression was found for GT2 family genes ZcCesA, ZcCslC and ZcCslA-like (possibly mannan and xyloglucan synthases, respectively), as well as for GT8 family genes (possibly pectin synthases). All these suggest that the UTEX 1559 cell wall polysaccharide synthesis-related genes respond to osmotic stress in a manner that is similar to land plants.

Orphan Genes Shared by Pathogenic Genomes Are More Associated with Bacterial Pathogenicity.

Orphan genes (also known as ORFans [i.e., orphan open reading frames]) are new genes that enable an organism to adapt to its specific living environment. Our focus in this study is to compare ORFans between pathogens (P) and nonpathogens (NP) of the same genus. Using the pangenome idea, we have identified 130,169 ORFans in nine bacterial genera (505 genomes) and classified these ORFans into four groups: (i) SS-ORFans (P), which are only found in a single pathogenic genome; (ii) SS-ORFans (NP), which are only found in a single nonpathogenic genome; (iii) PS-ORFans (P), which are found in multiple pathogenic genomes; and (iv) NS-ORFans (NP), which are found in multiple nonpathogenic genomes. Within the same genus, pathogens do not always have more genes, more ORFans, or more pathogenicity-related genes (PRGs)-including prophages, pathogenicity islands (PAIs), virulence factors (VFs), and horizontal gene transfers (HGTs)-than nonpathogens. Interestingly, in pathogens of the nine genera, the percentages of PS-ORFans are consistently higher than those of SS-ORFans, which is not true in nonpathogens. Similarly, in pathogens of the nine genera, the percentages of PS-ORFans matching the four types of PRGs are also always higher than those of SS-ORFans, but this is not true in nonpathogens. All of these findings suggest the greater importance of PS-ORFans for bacterial pathogenicity. IMPORTANCE Recent pangenome analyses of numerous bacterial species have suggested that each genome of a single species may have a significant fraction of its gene content unique or shared by a very few genomes (i.e., ORFans). We selected nine bacterial genera, each containing at least five pathogenic and five nonpathogenic genomes, to compare their ORFans in relation to pathogenicity-related genes. Pathogens in these genera are known to cause a number of common and devastating human diseases such as pneumonia, diphtheria, melioidosis, and tuberculosis. Thus, they are worthy of in-depth systems microbiology investigations, including the comparative study of ORFans between pathogens and nonpathogens. We provide direct evidence to suggest that ORFans shared by more pathogens are more associated with pathogenicity-related genes and thus are more important targets for development of new diagnostic markers or therapeutic drugs for bacterial infectious diseases.

The Transcriptional Regulator Hbx1 Affects the Expression of Thousands of Genes in the Aflatoxin-Producing Fungus Aspergillus flavus.

In filamentous fungi, homeobox proteins are conserved transcriptional regulators described to control conidiogenesis and fruiting body formation. Eight homeobox (hbx) genes are found in the genome of the aflatoxin-producing ascomycete, Aspergillus flavus While loss-of-function of seven of the eight genes had little to no effect on fungal growth and development, disruption of hbx1, resulted in aconidial colonies and lack of sclerotial production. Furthermore, the hbx1 mutant was unable to produce aflatoxins B1 and B2, cyclopiazonic acid and aflatrem. In the present study, hbx1 transcriptome analysis revealed that hbx1 has a broad effect on A. flavus gene expression, and the effect of hbx1 increases overtime, impacting more than five thousand protein-coding genes. Among the affected genes, those in the category of secondary metabolism (SM), followed by that of cellular transport, were the most affected. Specifically, regarding the effect of hbx1 on SM, we found that genes in 44 SM gene clusters where upregulated while 49 were downregulated in the absence of hbx1, including genes in the SM clusters responsible for the synthesis of asparasone, piperazine and aflavarin, all known to be associated with sclerotia. In addition, our study revealed that hbx1 affects the expression of other transcription factor genes involved in development, including the conidiation central regulatory pathway and flb genes.

dbCAN-seq: a database of carbohydrate-active enzyme (CAZyme) sequence and annotation.

Carbohydrate-active enzyme (CAZymes) are not only the most important enzymes for bioenergy and agricultural industries, but also very important for human health, in that human gut microbiota encode hundreds of CAZyme genes in their genomes for degrading various dietary and host carbohydrates. We have built an online database dbCAN-seq (http://cys.bios.niu.edu/dbCAN_seq) to provide pre-computed CAZyme sequence and annotation data for 5,349 bacterial genomes. Compared to the other CAZyme resources, dbCAN-seq has the following new features: (i) a convenient download page to allow batch download of all the sequence and annotation data; (ii) an annotation page for every CAZyme to provide the most comprehensive annotation data; (iii) a metadata page to organize the bacterial genomes according to species metadata such as disease, habitat, oxygen requirement, temperature, metabolism; (iv) a very fast tool to identify physically linked CAZyme gene clusters (CGCs) and (v) a powerful search function to allow fast and efficient data query. With these unique utilities, dbCAN-seq will become a valuable web resource for CAZyme research, with a focus complementary to dbCAN (automated CAZyme annotation server) and CAZy (CAZyme family classification and reference database).

dbCAN2: a meta server for automated carbohydrate-active enzyme annotation.

Complex carbohydrates of plants are the main food sources of animals and microbes, and serve as promising renewable feedstock for biofuel and biomaterial production. Carbohydrate active enzymes (CAZymes) are the most important enzymes for complex carbohydrate metabolism. With an increasing number of plant and plant-associated microbial genomes and metagenomes being sequenced, there is an urgent need of automatic tools for genomic data mining of CAZymes. We developed the dbCAN web server in 2012 to provide a public service for automated CAZyme annotation for newly sequenced genomes. Here, dbCAN2 (http://cys.bios.niu.edu/dbCAN2) is presented as an updated meta server, which integrates three state-of-the-art tools for CAZome (all CAZymes of a genome) annotation: (i) HMMER search against the dbCAN HMM (hidden Markov model) database; (ii) DIAMOND search against the CAZy pre-annotated CAZyme sequence database and (iii) Hotpep search against the conserved CAZyme short peptide database. Combining the three outputs and removing CAZymes found by only one tool can significantly improve the CAZome annotation accuracy. In addition, dbCAN2 now also accepts nucleotide sequence submission, and offers the service to predict physically linked CAZyme gene clusters (CGCs), which will be a very useful online tool for identifying putative polysaccharide utilization loci (PULs) in microbial genomes or metagenomes.