Project description:Early detection of spoilage microorganisms and food pathogens is of major importance in preventing food recalls and foodborne outbreaks. Although constant effort is invested in developing sensitive methods for rapid microbial detection, none of the current methods enables the detection of food pathogens within a few hours; therefore, development of innovative early-warning food-testing strategies are needed. Herein, we assessed a novel strategy that harnesses the microbiome signature of a food product to determine deviations in the abundance of particular community members and detect production defects. Employing the production process of barbecued (BarBQ) pastrami as a model, we characterized the microbiome profiles of the product along the production line using next-generation sequencing of the 16S rRNA gene, concentrating on the live microbiota. Following the establishment of a microbiome dataset representing a properly produced product, we were able to identify shifts in the microbiome profile of a defective batch produced under potassium lactate deficiency. With the identification of Vibrio and Lactobacillus as potential indicator bacteria for potassium lactate deficiency, rapid qPCR assays were designed for their quantification. Aligned with the microbiome profiling results, these qPCR assays were effective for rapid identification of a defective production event. This implies the use of rapid quantification targeting microbiome profile-derived indicator bacteria for in-house detection of defective batches and identification of food-safety and quality events with results obtained on the same day. The suggested strategy should pave the way toward safer and more efficient food-production systems.
Project description:Detection of causal variant for thrombocytopenia and second hit causing malignant disease onset by next-generation sequencing. The sample was taken at MDS diagnosis, the illness later developed into AML.
Project description:Primary human monocytes were isolated from four healthy donors. Monocytes were differentiated into macrophages, infected with virulent Mycobacterium tuberculosis (Mtb), strain H37Rv, for 24 or 48 hours, at a multiplicity of infection of 5 or 10. Following infection, infected cells and time-matched uninfected controls were harvested, total RNA including small RNAs was isolated and used for next-generation small RNA sequencing. Small RNA sequencing data was processed using miRge2.0, including a novel miRge2.0-based tRF detection tool. Processed data was used to determine differential expression of microRNAs and differential production of tRNA-derived fragments (tRFs) during infection with Mtb.
Project description:To evaluate targeted MinION next generation sequencing as a diagnostic method for detection of pathogens in human blood and plasma, human blood or plasma samples were spiked with measured amounts of viruses, bacteria, protozoan parasites or tested pathogen-free as negative controls. Nucleic acid was extracted from samples and PCR amplification performed in multiplex primer pools with a procedure described in ArrayExpress experiment submission ID 18379. The PCR products were used for library preparation. The libraries sequenced on an Oxford Nanopore MinION. The passed reads aligned with a custom reference file to determine the identity of the pathogen in the sample.
Project description:Whole genome sequencing (WGS) from snap-frozen oesophageal tumour tissue and germline nucleic acids isolated from peripheral blood mononuclear cells (PBMC) was performed as part of the International Cancer Genome Consortium project and OCCAMS consortium (1,2). Filtered read sequences were mapped to the human reference genome (GRCh37) using Burrows-Wheeler Alignment (BWA). In the matched tumour/germline samples, somatic acquired mutation identification was performed using a Bayesian algorithm implemented in the tool Seurat (3). Functional annotation of identified somatic mutations was performed with the tool SnpEff (4). CNV detection was performed with the tool Control-FREEC (5) 1) Weaver, J. M. et al. Ordering of mutations in preinvasive disease stages of esophageal carcinogenesis. Nat.Genet. 46, 837-843 (2014). 2) Weaver, J. M., Ross-Innes, C. S. & Fitzgerald, R. C. The '-omics' revolution and oesophageal adenocarcinoma. Nature reviews. Gastroenterology & hepatology 11, 19-27 (2014) 3) Christoforides, A. et al. Identification of somatic mutations in cancer through Bayesian-based analysis of sequenced genome pairs. BMC.Genomics 14, 302 (2013). 4) Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly.(Austin.) 6, 80-92 (2012). 5) Boeva V, Popova T, Bleakley K, Chiche P, Cappo J, Schleiermacher G, Janoueix-Lerosey I, Delattre O, Barillot E. (2011) Control-FREEC: a tool for assessing copy number and allelic content using next generation sequencing data. Bioinformatics. 2011 Dec 6
Project description:One of the cornerstones of an effective biodefense strategy is the ability to detect infectious agents with a high degree of sensitivity and specificity in the context of a complex sample background. The nature of the B. anthracis genome, however, renders specific detection difficult, due to close homology with B. cereus and B. thuringiensis. We therefore elected to determine the efficacy of next-generation sequencing analysis and microarrays for detection of B. anthracis in an environmental background. We applied next-generation sequencing to titrated genome copy numbers of B. anthracis in the presence of background nucleic acid extracted from aerosol and soil samples. We found next-generation sequencing to be capable of detecting as few as 10 genomic equivalents of B. anthracis DNA per nanogram of background nucleic acid. Detection was accomplished by mapping reads to either a defined subset of reference genomes or to the full GenBank database. Moreover, sequence data obtained from B. anthracis could be reliably distinguished from sequence data mapping to either B. cereus or B. thuringiensis. We also demonstrated the efficacy of a microbial census microarray in detecting B. anthracis in the same samples, representing a cost-effective and high-throughput approach, complementary to next-generation sequencing. This Series contains the NimbleGen array data only (no next-generation sequencing data). B. anthracis DNA was spiked at 6 different concentrations (1, 10, 100, 1000, 10000 and 100000 genome copies) into 1 ng of background nucleic acids extracted either from a soil sample or from an aerosol (air filter) sample. Two replicates of each combination of B. anthracis copy number and background sample were analyzed.
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.