Background. Complete Genomics provides an open-source suite of command-line tools for the analysis of their CG-formatted mapped sequencing files. Deter

Illumina and nanopore sequencing technologies are powerful tools that can be used to determine the bacterial composition of complex microbial communities. In this study, we compared nasal microbiota results at genus level using both Illumina and nanopore 16S rRNA gene sequencing. We also monitored the progression of nanopore sequencing in the accurate identification of species, using pure, single species cultures, and evaluated the performance of the nanopore EPI2ME 16S data analysis pipeline. Fifty-nine nasal swabs were sequenced using Illumina MiSeq and Oxford Nanopore 16S rRNA gene sequencing technologies. In addition, five pure cultures of relevant bacterial species were sequenced with the nanopore sequencing technology. The Illumina MiSeq sequence data were processed using bioinformatics modules present in the Mothur software package. Albacore and Guppy base calling, a workflow in nanopore EPI2ME (Oxford Nanopore Technologies—ONT, Oxford, UK) and an in-house developed bioinformatics script were used to analyze the nanopore data. At genus level, similar bacterial diversity profiles were found, and five main and established genera were identified by both platforms. However, probably due to mismatching of the nanopore sequence primers, the nanopore sequencing platform identified Corynebacterium in much lower abundance compared to Illumina sequencing. Further, when using default settings in the EPI2ME workflow, almost all sequence reads that seem to belong to the bacterial genus Dolosigranulum and a considerable part to the genus Haemophilus were only identified at family level. Nanopore sequencing of single species cultures demonstrated at least 88% accurate identification of the species at genus and species level for 4/5 strains tested, including improvements in accurate sequence read identification when the basecaller Guppy and Albacore, and when flowcell versions R9.4 (Oxford Nanopore Technologies—ONT, Oxford, UK) and R9.2 (Oxford Nanopore Technologies—ONT, Oxford, UK) were compared. In conclusion, the current study shows that the nanopore sequencing platform is comparable with the Illumina platform in detection bacterial genera of the nasal microbiota, but the nanopore platform does have problems in detecting bacteria within the genus Corynebacterium. Although advances are being made, thorough validation of the nanopore platform is still recommendable.

Preeclampsia (PE) carries increased risks of cardiovascular- and metabolic diseases in mothers and offspring during the life course. While the severe early-onset PE (EOPE) phenotype originates from impaired placentation in early pregnancy, late-onset PE (LOPE) is in particular associated with pre-existing maternal cardiovascular- and metabolic risk factors. We hypothesize that PE is associated with altered epigenetic programming of placental and fetal tissues and that these epigenetic changes might elucidate the increased cardiovascular- and metabolic disease susceptibility in PE offspring. A nested case-control study was conducted in The Rotterdam Periconceptional Cohort comprising 13 EOPE, 16 LOPE, and three control groups of 36 uncomplicated pregnancies, 27 normotensive fetal growth restricted and 20 normotensive preterm birth (PTB) complicated pregnancies. Placental tissue, newborn umbilical cord white blood cells (UC-WBC) and umbilical vein endothelial cells were collected and DNA methylation of cytosine-guanine dinucleotides was measured by the Illumina HumanMethylation450K BeadChip. An epigenome-wide analysis was performed by using multiple linear regression models. Epigenome-wide tissue-specific analysis between EOPE and PTB controls revealed 5001 mostly hypermethylated differentially methylated positions (DMPs) in UC-WBC and 869 mostly hypomethylated DMPs in placental tissue, situated in or close to genes associated with cardiovascular-metabolic developmental pathways. This study shows differential methylation in UC-WBC and placental tissue in EOPE as compared to PTB, identifying DMPs that are associated with cardiovascular system pathways. Future studies should examine these loci and pathways in more detail to elucidate the associations between prenatal PE exposure and the cardiovascular disease risk in offspring.

Long-read sequencing can be applied to generate very long contigs and even completely assembled genomes at relatively low cost and with minimal sample preparation. As a result, long-read sequencing platforms are becoming more popular. In this respect, the Oxford Nanopore Technologies–based long-read sequencing “nanopore" platform is becoming a widely used tool with a broad range of applications and end-users. However, the need to explore and manipulate the complex data generated by long-read sequencing platforms necessitates accompanying specialized bioinformatics platforms and tools to process the long-read data correctly. Importantly, such tools should additionally help democratize bioinformatics analysis by enabling easy access and ease-of-use solutions for researchers. The Galaxy platform provides a user-friendly interface to computational command line–based tools, handles the software dependencies, and provides refined workflows. The users do not have to possess programming experience or extended computer skills. The interface enables researchers to perform powerful bioinformatics analysis, including the assembly and analysis of short- or long-read sequence data. The newly developed “NanoGalaxy" is a Galaxy-based toolkit for analysing long-read sequencing data, which is suitable for diverse applications, including de novo genome assembly from genomic, metagenomic, and plasmid sequence reads. A range of best-practice tools and workflows for long-read sequence genome assembly has been integrated into a NanoGalaxy platform to facilitate easy access and use of bioinformatics tools for researchers. NanoGalaxy is freely available at the European Galaxy server https://nanopore.usegalaxy.eu with supporting self-learning training material available at https://training.galaxyproject.org.

Background Pancreatic ductal adenocarcinoma (PDAC) is notoriously resistant to treatment including checkpoint-blockade immunotherapy. We hypothesized that a bimodal treatment approach consisting of dendritic cell (DC) vaccination to prime tumor-specific T cells, and a strategy to reprogram the desmoplastic tumor microenvironment (TME) would be needed to break tolerance to these pancreatic cancers. As a proof-of-concept, we investigated the efficacy of combined DC vaccination with CD40-agonistic antibodies in a poorly immunogenic murine model of PDAC. Based on the rationale that mesothelioma and pancreatic cancer share a number of tumor associated antigens, the DCs were loaded with either pancreatic or mesothelioma tumor lysates. Methods Immune-competent mice with subcutaneously or orthotopically growing KrasG12D/+;Trp53R172H/+;Pdx-1-Cre (KPC) PDAC tumors were vaccinated with syngeneic bone marrow-derived DCs loaded with either pancreatic cancer (KPC) or mesothelioma (AE17) lysate and consequently treated with FGK45 (CD40 agonist). Tumor progression was monitored and immune responses in TME and lymphoid organs were analyzed using multicolor flow cytometry and NanoString analyzes. Results Mesothelioma-lysate loaded DCs generated cross-reactive tumor-antigen-specific T-cell responses to pancreatic cancer and induced delayed tumor outgrowth when provided as prophylactic vaccine. In established disease, combination with stimulating CD40 antibody was necessary to improve survival, while anti-CD40 alone was ineffective. Extensive analysis of the TME showed that anti-CD40 monotherapy did improve CD8 +T cell infiltration, but these essential effector cells displayed hallmarks of exhaustion, including PD-1, TIM-3 and NKG2A. Combination therapy induced a strong change in tumor transcriptome and mitigated the expression of inhibitory markers on CD8 +T cells. Conclusion These results demonstrate the potency of DC therapy in combination with CD40-stimulation for the treatment of pancreatic cancer and provide directions for near future clinical trials.

Antigen Receptor Galaxy (ARGalaxy) is a Web-based tool for analyses and visualization of TCR and BCR sequencing data of 13 species. ARGalaxy consists of four parts: the demultiplex tool, the international ImMunoGeneTics information system (IMGT) concatenate tool, the immune repertoire pipeline, and the somatic hypermutation (SHM) and class switch recombination (CSR) pipeline. Together they allow the analysis of all different aspects of the immune repertoire. All pipelines can be run independently or combined, depending on the available data and the question of interest. The demultiplex tool allows data trimming and demultiplexing, whereas with the concatenate tool multiple IMGT/HighV-QUEST output files can be merged into a single file. The immune repertoire pipeline is an extended version of our previously published ImmunoGlobulin Galaxy (IGGalaxy) virtual machine that was developed to visualize V(D)J gene usage. It allows analysis of both BCR and TCR rearrangements, visualizes CDR3 characteristics (length and amino acid usage) and junction characteristics, and calculates the diversity of the immune repertoire. Finally, ARGalaxy includes the newly developed SHM and CSR pipeline to analyze SHM and/or CSR in BCR rearrangements. It analyzes the frequency and patterns of SHM, Ag selection (including BASELINe), clonality (Change-O), and CSR. The functionality of the ARGalaxy tool is illustrated in several clinical examples of patients with primary immunodeficiencies. In conclusion, ARGalaxy is a novel tool for the analysis of the complete immune repertoire, which is applicable to many patient groups with disturbances in the immune repertoire such as autoimmune diseases, allergy, and leukemia, but it can also be used to address basic research questions in repertoire formation and selection.