Project description:Multiomics of faecal samples collected from individuals in families with multiple cases of type 1 diabetes mellitus (T1DM) over 3 or 4 months. Metagenomic and metatranscriptomic sequencing and metaproteomics were carried out, as well as whole human genome sequencing. Phenotypic data is available.
Project description:Primary objectives: The primary objective is to investigate circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Primary endpoints: circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Project description:Purpose: The goal of this study is to compare colonic transcriptional responses following ex-vivo colonization with fecal samples collected from multiple sclerosis patients, before and after Propionic acid treatment and between the patients that responded or not to the therapy. Methods: Bulk whole-tissue mRNA profiles of 13-day-old wild-type mice colons were generated by deep sequencing, in triplicate, using Illumina NextSeq platform.
Project description:Members of the Mycobacterium (M.) abscessus complex (MABC) are rapidly growing mycobacteria showing smooth and/or rough colony morphotype. While not as virulent as M. tuberculosis, they can cause soft tissue infection and fatal pulmonary disease, especially in patients with cystic fibrosis. Diagnosing MABC pulmonary disease is challenging since the isolation of M. abscessus from respiratory samples is in itself not diagnostic and the clinical features are often non-specific. Immunologic assays, which could aid in the understanding and diagnosis of the disease, are not available. In this study eight rough and six smooth colony morphotype isolates were collected from seven clinical MABC strains and the M. abscessus reference strain ATCC19977, as six strains showed both morphotypes simultaneously and two strains only showed a rough morphotype. Clinical isolates were submitted to whole genome sequencing. Quantitative proteomic analysis was performed on bacterial lysates and the culture supernatant of all 14 isolates. Supernatant proteins present in all isolates were compared in a BLAST search against other clinically significant mycobacterial species to determine species-specific proteins of MABC. In silico B- and T-cell epitope prediction was performed for species-specific proteins. All clinical strains were found to be M. abscessus ssp. abscessus. Six of seven rough colony clinical isolates contained genetic changes in the MAB_4099c gene, which is a likely genetic basis for the rough morphotype. Proteomic analysis detected 3 137 different proteins in total of which 79 proteins were found in the culture supernatants of all isolates. BLAST analyses of these 79 proteins identified 12 of those exclusively encoded by all members of MABC plus M. immunogenum. In silico prediction of epitopes predicted B- and T-cell epitopes in all these 12 species-specific proteins, rendering them promising candidates for future studies on immune pathogenesis and immune diagnostic tools for MABC disease.
Project description:Multiomics of faecal samples collected from individuals in families with multiple cases of type 1 diabetes mellitus (T1DM) over 3 or 4 months. Metagenomic and metatranscriptomic sequencing and metaproteomics were carried out, as well as whole human genome sequencing. Phenotypic data is available.
Project description:High throughput sequencing is performed on mRNA isolated from whole blood of adult Covid-19 patients, bacterial coinfection with Covid-19 and healthy controls in a South Indian cohort. Samples were collected from individuals at the time of hospitalization or visit to clinic. The Covid-19 samples are categorized by severeity.
Project description:Hypermutable P. aeruginosa isolates are prevalent in cystic fibrosis and associated with acute exacerbations of chronic lung infections leading to early death and increased resistance emergence. Achievable epithelial lining fluid concentration-time profiles of meropenem and tobramycin in monotherapy and combination regimens were simulated against two clinical hypermutable P. aeruginosa isolates; CW8 (MICmeropenem=8mg/L, MICtobramycin=8mg/L) and CW44 (MICmeropenem=4mg/L, MICtobramycin=2mg/L) in an 8-day hollow fiber infection model (HFIM). Both isolates were previously characterised with genotypes resembling those of carbapenem- and aminoglycoside-resistant strains. Meropenem at 1 or 2g every 8h (3h infusion) and tobramycin at 5 or 10mg/kg body weight every 24h (0.5h infusion) were studied. Total and resistant bacterial counts were determined. Whole genome sequencing was performed on mutants and whole population samples at 191h, and transcriptomics at 1 and 191h. Mechanism-based modelling of total and resistant populations was informed by the multi-omics analysis. While all regimens against both isolates produced regrowth, the high dose combination synergistically suppressed resistant regrowth against CW8 up to ~96h. The high dose combination provided some killing against CW44, however failed to prevent resistant regrowth. In CW8, mutations emerged during treatment in pmrB, ampR, and multiple efflux pump regulators; in CW44, mutations in pmrB and PBP2 were observed. In CW8, resistance genes mexB and oprM were downregulated by the combination at 1h and coincided with synergistic killing, with differential expression of outer membrane norspermidine and lipopolysaccharide genes at 191h. Mechanism-based modelling incorporating subpopulation and mechanistic synergy successfully characterized the bacterial response of CW8, while mechanistic synergy was not required for CW44. Incorporating information from the multi-omics analyses was instrumental in building the mechanism-based model to describe the bacterial response of the hypermutable isolates, whereas MICs and traditional PK/PD indices could not predict the outcomes of the HFIM.