Differential ATAC-seq and ChIP-seq peak detection using ROTS

Changes in cellular chromatin states fine-tune transcriptional output and ultimately lead to phenotypic changes. Here we propose a novel application of our reproducibility-optimized test statistics (ROTS) to detect differential chromatin states (ATAC-seq) or differential chromatin modification states (ChIP-seq) between conditions. We compare the performance of ROTS to existing and widely used methods for ATAC-seq and ChIP-seq data using both synthetic and real datasets. Our results show that ROTS outperformed other commonly used methods when analyzing ATAC-seq data. ROTS also displayed the most accurate detection of small differences when modeling with synthetic data. We observed that two-step methods that require the use of a separate peak caller often more accurately called enrichment borders, whereas one-step methods without a separate peak calling step were more versatile in calling sub-peaks. The top ranked differential regions detected by the methods had marked correlation with transcriptional differences of the closest genes. Overall, our study provides evidence that ROTS is a useful addition to the available differential peak detection methods to study chromatin and performs especially well when applied to study differential chromatin states in ATAC-seq data. </p

Long Intergenic Noncoding RNA MIAT as a Regulator of Human Th17 Cell Differentiation

T helper 17 (Th17) cells protect against fungal and bacterial infections and are implicated in autoimmunity. Several long intergenic noncoding RNAs (lincRNA) are induced during Th17 differentiation, however, their contribution to Th17 differentiation is poorly understood. We aimed to characterize the function of the lincRNA Myocardial Infarction Associated Transcript (MIAT) during early human Th17 cell differentiation. We found MIAT to be upregulated early after induction of human Th17 cell differentiation along with an increase in the chromatin accessibility at the gene locus. STAT3, a key regulator of Th17 differentiation, directly bound to the MIAT promoter and induced its expression during the early stages of Th17 cell differentiation. MIAT resides in the nucleus and regulates the expression of several key Th17 genes, including IL17A, IL17F, CCR6 and CXCL13, possibly by altering the chromatin accessibility of key loci, including IL17A locus. Further, MIAT regulates the expression of protein kinase C alpha (PKC alpha), an upstream regulator of IL17A. A reanalysis of published single-cell RNA-seq data showed that MIAT was expressed in T cells from the synovium of RA patients. Our results demonstrate that MIAT contributes to human Th17 differentiation by upregulating several genes implicated in Th17 differentiation. High MIAT expression in T cells of RA patient synovia suggests a possible role of MIAT in Th17 mediated autoimmune pathologies

The Glanville fritillary genome retains ancient karyotype and reveals selective chromosomal fusions in Lepidoptera

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Comparison of de novo metagenomic assembly tools

The field of metagenomics involves studying the composition and function of microbial communities via isolated DNA from a variety of environments like soil, water and the human gut. Since the current generation sequencing instruments produce millions of short read fragments (75-300 bp), while bacterial genomes typically range from 1 to 7 Mbp, an issue of recovering meaningful information from the fragments arises. To help overcome the issue, a number of de novo sequence assembly software have been published, which assembles the short fragments into contigs. This thesis aims to provide a comprehensive evaluation of five different assemblers (DISCO, Faucet, IDBA-UD, MEGAHIT and metaSPAdes) using a previously published benchmarking dataset and an assembly evaluation tool (metaQUAST). The resulting metaQUAST report together with some practical insights like assembly time and documentation was evaluated, determining the strengths and limitations of each tool. The best performers were MEGAHIT and metaSPAdes, having the fastest assembly times and longest contigs, while Faucet had the worst performance in almost every evaluation category. IDBA-UD and DISCO were unable to finish the assembly of the dataset due to technical difficulties. In conclusion, MEGAHIT would be the first recommendation for an assembler to use due to the fast assembly times. metaSPAdes is worth using if contig length is of importance, while Faucet is only recommended for the storage space deprived

Phylogeny of the Rhizobium-Allorhizobium-Agrobacterium clade supports the delineation of Neorhizobium gen. nov.

Supplementary dataInternational audienceThe genera Agrobacterium, Allorhizobium, and Rhizobium belong to the family Rhizobiaceae. However, the placement of a phytopathogenic group of bacteria, the genus Agrobacterium, among the nitrogen-fixing bacteria and the unclear position of Rhizobium galegae have caused controversy in previous taxonomic studies. To resolve uncertainties in the taxonomy and nomenclature within this family, the phylogenetic relationships of generic members of Rhizobiaceae were studied, but with particular emphasis on the taxa included in Agrobacterium and the "R. galegae complex" (R. galegae and related taxa), using multilocus sequence analysis (MLSA) of six protein-coding housekeeping genes among 114 rhizobial and agrobacterial taxa. The results showed that R. galegae, R. vignae, R. huautlense, and R. alkalisoli formed a separate clade that clearly represented a new genus, for which the name Neorhizobium is proposed. Agrobacterium was shown to represent a separate cluster of mainly pathogenic taxa of the family Rhizobiaceae. A. vitis grouped with Allorhizobium, distinct from Agrobacterium, and should be reclassified as Allorhizobium vitis, whereas Rhizobium rhizogenes was considered to be the proper name for former Agrobacterium rhizogenes. This phylogenetic study further indicated that the taxonomic status of several taxa could be resolved by the creation of more novel genera

Targeted plasma metabolomics in resuscitated comatose out-of-hospital cardiac arrest patients

Background: Out-of-hospital cardiac arrest (OHCA) is a leading cause of death. Even if successfully resuscitated, mortality remains high due to ischemic and reperfusion injury (I/R). The oxygen deprivation leads to a metabolic derangement amplified upon reperfusion resulting in an uncontrolled generation of reactive oxygen species in the mitochondria triggering cell death mechanisms. The understanding of I/R injury in humans following OHCA remains sparse, with no existing treatment to attenuate the reperfusion injury. Aim: To describe metabolic derangement in patients following resuscitated OHCA. Methods: Plasma from consecutive resuscitated unconscious OHCA patients drawn at hospital admission were analyzed using ultra-performance-liquid-mass-spectrometry. Sixty-one metabolites were prespecified for quantification and studied. Results: In total, 163 patients were included, of which 143 (88%) were men, and the median age was 62 years (53–68). All measured metabolites from the tricarboxylic acid (TCA) cycle were significantly higher in non-survivors vs. survivors (180-days survival). Hierarchical clustering identified four clusters (A-D) of patients with distinct metabolic profiles. Cluster A and B had higher levels of TCA metabolites, amino acids and acylcarnitine species compared to C and D. The mortality was significantly higher in cluster A and B (A:62% and B:59% vs. C:21 % and D:24%, p < 0.001). Cluster A and B had longer time to return of spontaneous circulation (A:33 min (21–43), B:27 min (24–35), C:18 min (13–28), and D:18 min (12–25), p < 0.001). Conclusion: Circulating levels of metabolites from the TCA cycle best described the variance between survivors and non-survivors. Four different metabolic phenotypes with significantly different mortality were identified

Swedish Chronic Pain Biobank: protocol for a multicentre registry and biomarker project

INTRODUCTION: About 20% of the adult population have chronic pain, often associated with psychological distress, sick leave and poor health. There are large variations in the clinical picture. A biopsychosocial approach is used in investigation and treatment. The concept of personalised medicine, that is, optimising medication types and dosages for individual patients based on biomarkers and other patient-related factors, has received increasing attention in different diseases but used less in chronic pain. This cooperative project from all Swedish University Hospitals will investigate whether there are changes in inflammation and metabolism patterns in saliva and blood in chronic pain patients and whether the changes correlate with clinical characteristics and rehabilitation outcomes. METHODS AND ANALYSIS: Patients at multidisciplinary pain centres at University Hospitals in Sweden who have chosen to participate in the Swedish Quality Registry for Pain Rehabilitation and healthy sex-matched and age-matched individuals will be included in the study. Saliva and blood samples will be collected in addition to questionnaire data obtained from the register. From the samples, proteins, lipids, metabolites and micro-RNA will be analysed in relation to, for example, diagnosis, pain characteristics, psychological distress, body weight, pharmacological treatment and clinical rehabilitation results using advanced multivariate data analysis and bioinformatics. ETHICS AND DISSEMINATION: The study is approved by the Swedish Ethical Review Authority (Dnr 2021-04929) and will be conducted in accordance with the declaration of Helsinki.The results will be published in open access scientific journals and in popular scientific relevant journals such as those from patient organisations. Data will be also presented in scientific meetings, meeting with healthcare organisations and disseminated in different lecturers at the clinics and universities