Outer Membrane Vesicles From The Gut Microbiome Contribute to Tumor Immunity by Eliciting Cross-Reactive T Cells.

A growing body of evidence supports the notion that the gut microbiome plays an important role in cancer immunity. However, the underpinning mechanisms remain to be fully elucidated. One attractive hypothesis envisages that among the T cells elicited by the plethora of microbiome proteins a few exist that incidentally recognize neo-epitopes arising from cancer mutations ("molecular mimicry (MM)" hypothesis). To support MM, the human probiotic Escherichia coli Nissle was engineered with the SIINFEKL epitope (OVA-E.coli Nissle) and orally administered to C57BL/6 mice. The treatment with OVA-E.coli Nissle, but not with wild type E. coli Nissle, induced OVA-specific CD8+ T cells and inhibited the growth of tumors in mice challenged with B16F10 melanoma cells expressing OVA. The microbiome shotgun sequencing and the sequencing of TCRs from T cells recovered from both lamina propria and tumors provide evidence that the main mechanism of tumor inhibition is mediated by the elicitation at the intestinal site of cross-reacting T cells, which subsequently reach the tumor environment. Importantly, the administration of Outer Membrane Vesicles (OMVs) from engineered E. coli Nissle, as well as from E. coli BL21(DE3)ΔompA, carrying cancer-specific T cell epitopes also elicited epitope-specific T cells in the intestine and inhibited tumor growth. Overall, our data strengthen the important role of MM in tumor immunity and assign a novel function of OMVs in host-pathogen interaction. Moreover, our results pave the way to the exploitation of probiotics and OMVs engineered with tumor specific-antigens as personalized mucosal cancer vaccines.

Polycomb group ring finger protein 6 suppresses Myc-induced lymphomagenesis.

Max is an obligate dimerization partner for the Myc transcription factors and for several repressors, such as Mnt, Mxd1-4, and Mga, collectively thought to antagonize Myc function in transcription and oncogenesis. Mga, in particular, is part of the variant Polycomb group repressive complex PRC1.6. Here, we show that ablation of the distinct PRC1.6 subunit Pcgf6-but not Mga-accelerates Myc-induced lymphomagenesis in Eµ-myc transgenic mice. Unexpectedly, however, Pcgf6 loss shows no significant impact on transcriptional profiles, in neither pre-tumoral B-cells, nor lymphomas. Altogether, these data unravel an unforeseen, Mga- and PRC1.6-independent tumor suppressor activity of Pcgf6.

Commensal Bifidobacterium Strains Enhance the Efficacy of Neo-Epitope Based Cancer Vaccines.

A large body of data both in animals and humans demonstrates that the gut microbiome plays a fundamental role in cancer immunity and in determining the efficacy of cancer immunotherapy. In this work, we have investigated whether and to what extent the gut microbiome can influence the antitumor activity of neo-epitope-based cancer vaccines in a BALB/c-CT26 cancer mouse model. Similarly to that observed in the C57BL/6-B16 model, Bifidobacterium administration per se has a beneficial effect on CT26 tumor inhibition. Furthermore, the combination of Bifidobacterium administration and vaccination resulted in a protection which was superior to vaccination alone and to Bifidobacterium administration alone, and correlated with an increase in the frequency of vaccine-specific T cells. The gut microbiome analysis by 16S rRNA gene sequencing and shotgun metagenomics showed that tumor challenge rapidly altered the microbiome population, with Muribaculaceae being enriched and Lachnospiraceae being reduced. Over time, the population of Muribaculaceae progressively reduced while the Lachnospiraceae population increased-a trend that appeared to be retarded by the oral administration of Bifidobacterium. Interestingly, in some Bacteroidales, Prevotella and Muribaculacee species we identified sequences highly homologous to immunogenic neo-epitopes of CT26 cells, supporting the possible role of "molecular mimicry" in anticancer immunity. Our data strengthen the importance of the microbiome in cancer immunity and suggests a microbiome-based strategy to potentiate neo-epitope-based cancer vaccines.

Integrated requirement of non-specific and sequence-specific DNA binding in Myc-driven transcription.

Eukaryotic transcription factors recognize specific DNA sequence motifs, but are also endowed with generic, non-specific DNA-binding activity. How these binding modes are integrated to determine select transcriptional outputs remains unresolved. We addressed this question by site-directed mutagenesis of the Myc transcription factor. Impairment of non-specific DNA backbone contacts caused pervasive loss of genome interactions and gene regulation, associated with increased intra-nuclear mobility of the Myc protein in murine cells. In contrast, a mutant lacking base-specific contacts retained DNA-binding and mobility profiles comparable to those of the wild-type protein, but failed to recognize its consensus binding motif (E-box) and could not activate Myc-target genes. Incidentally, this mutant gained weak affinity for an alternative motif, driving aberrant activation of different genes. Altogether, our data show that non-specific DNA binding is required to engage onto genomic regulatory regions; sequence recognition in turn contributes to transcriptional activation, acting at distinct levels: stabilization and positioning of Myc onto DNA, and-unexpectedly-promotion of its transcriptional activity. Hence, seemingly pervasive genome interaction profiles, as detected by ChIP-seq, actually encompass diverse DNA-binding modalities, driving defined, sequence-dependent transcriptional responses.

STRAIN: an R package for multi-locus sequence typing from whole genome sequencing data.

BACKGROUND: Multi-locus sequence typing (MLST) is a standard typing technique used to associate a sequence type (ST) to a bacterial isolate. When the output of whole genome sequencing (WGS) of a sample is available the ST can be assigned directly processing the read-set. Current approaches employ reads mapping (SRST2) against the MLST loci, k-mer distribution (stringMLST), selective assembly (GRAbB) or whole genome assembly (BIGSdb) followed by BLASTn sequence query. Here we present STRAIN (ST Reduced Assembly IdentificatioN), an R package that implements a hybrid strategy between assembly and mapping of the reads to assign the ST to an isolate starting from its read-sets. RESULTS: Analysis of 540 publicly accessible Illumina read sets showed STRAIN to be more accurate at correct allele assignment and new alleles identification compared to SRTS2, stringMLST and GRAbB. STRAIN assigned correctly 3666 out of 3780 alleles (capability to identify correct alleles 97%) and, when presented with samples containing new alleles, identified them in 3730 out of 3780 STs (capability to identify new alleles 98.7%) of the cases. On the same dataset the other tested tools achieved lower capability to identify correct alleles (from 28.5 to 96.9%) and lower capability to identify new alleles (from 1.1 to 97.1%). CONCLUSIONS: STRAIN is a new accurate method to assign the alleles and ST to an isolate by processing the raw reads output of WGS. STRAIN is also able to retrieve new allele sequences if present. Capability to identify correct and new STs/alleles, evaluated on a benchmark dataset, are higher than other existing methods. STRAIN is designed for single allele typing as well as MLST. Its implementation in R makes allele and ST assignment simple, direct and prompt to be integrated in wider pipeline of downstream bioinformatics analyses.

Comparison of Open-Source Reverse Vaccinology Programs for Bacterial Vaccine Antigen Discovery.

Reverse Vaccinology (RV) is a widely used approach to identify potential vaccine candidates (PVCs) by screening the proteome of a pathogen through computational analyses. Since its first application in Group B meningococcus (MenB) vaccine in early 1990's, several software programs have been developed implementing different flavors of the first RV protocol. However, there has been no comprehensive review to date on these different RV tools. We have compared six of these applications designed for bacterial vaccines (NERVE, Vaxign, VaxiJen, Jenner-predict, Bowman-Heinson, and VacSol) against a set of 11 pathogens for which a curated list of known bacterial protective antigens (BPAs) was available. We present results on: (1) the comparison of criteria and programs used for the selection of PVCs (2) computational runtime and (3) performances in terms of fraction of proteome identified as PVC, fraction and enrichment of BPA identified in the set of PVCs. This review demonstrates that none of the programs was able to recall 100% of the tested set of BPAs and that the output lists of proteins are in poor agreement suggesting in the process of prioritize vaccine candidates not to rely on a single RV tool response. Singularly the best balance in terms of fraction of a proteome predicted as good candidate and recall of BPAs has been observed by the machine-learning approach proposed by Bowman (1) and enhanced by Heinson (2). Even though more performing than the other approaches it shows the disadvantage of limited accessibility to non-experts users and strong dependence between results and a-priori training dataset composition. In conclusion we believe that to significantly enhance the performances of next RV methods further studies should focus on the enhancement of accuracy of the existing protein annotation tools and should leverage on the assets of machine-learning techniques applied to biological datasets expanded also through the incorporation and curation of bacterial proteins characterized by negative experimental results.

Retrospective Identification of a Broad IgG Repertoire Differentiating Patients With S. aureus Skin and Soft Tissue Infections From Controls.

Background: Although the relevance of humoral immunity for protection against S. aureus skin and soft tissue infections (SSTIs) has been suggested by several animal and human studies, the question of which human antibodies may be protective has so far impeded the development of a safe and effective vaccine. Because most adults have developed certain anti-S. aureus antibodies due to S. aureus colonization or infection, we hypothesized that the titers of antibodies to S. aureus in uninfected controls would differ from those in infected patients and would also differ in infected patients from the time of acute infection to a 40-day convalescent serum. Methods: To test these hypotheses, we measured human antibody levels against a panel of 134 unique antigens comprising the S. aureus surfome and secretome in subjects with active culture-confirmed S. aureus SSTIs (cases) and in controls with no infection, using a novel S. aureus protein microarray. Results: Most S. aureus SSTI patients (n = 60) and controls (n = 142) had antibodies to many of the tested S. aureus antigens. Univariate analysis showed statistically weak differences in the IgG levels to some antigens in the SSTI patient (case) sera compared with controls. Antibody levels to most tested antigens did not increase comparing acute with 40-day serum. Multiple logistic regression identified a rich subset of antigens that, by their antibody levels, together correctly differentiated all cases from all controls. Conclusions: Antibodies directed against S. aureus antigens were present both in patients with S. aureus SSTIs and in uninfected control patients. We found that SSTI patients and controls could be distinguished only based on differences in antibody levels to many staphylococcal surface and secreted antigens. Our results demonstrate that in the studied population, the levels of anti-S. aureus antibodies appear largely fixed, suggesting that there may be some level of unresponsiveness to natural infection.

Genome-Based Approach Delivers Vaccine Candidates Against Pseudomonas aeruginosa.

High incidence, severity and increasing antibiotic resistance characterize Pseudomonas aeruginosa infections, highlighting the need for new therapeutic options. Vaccination strategies to prevent or limit P. aeruginosa infections represent a rational approach to positively impact the clinical outcome of risk patients; nevertheless this bacterium remains a challenging vaccine target. To identify novel vaccine candidates, we started from the genome sequence analysis of the P. aeruginosa reference strain PAO1 exploring the reverse vaccinology approach integrated with additional bioinformatic tools. The bioinformatic approaches resulted in the selection of 52 potential antigens. These vaccine candidates were conserved in P. aeruginosa genomes from different origin and among strains isolated longitudinally from cystic fibrosis patients. To assess the immune-protection of single or antigens combination against P. aeruginosa infection, a vaccination protocol was established in murine model of acute respiratory infection. Combinations of selected candidates, rather than single antigens, effectively controlled P. aeruginosa infection in the in vivo model of murine pneumonia. Five combinations were capable of significantly increase survival rate among challenged mice and all included PA5340, a hypothetical protein exclusively present in P. aeruginosa. PA5340 combined with PA3526-MotY gave the maximum protection. Both proteins were surface exposed by immunofluorescence and triggered a specific immune response. Combination of these two protein antigens could represent a potential vaccine to prevent P. aeruginosa infection.