Blood metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA693402 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The Blood Borne Pathogen Resequencing Microarray Expanded (BBP-RMAv.2) is a platform that allows multiplex detection and identification of 80 different blood-borne pathogens in one single test, comprising 60 virus, 5 bacteria and 15 parasites. The objective is to evaluate the lowest concentration detected in blood or plasma, species discrimination and applicability of the microarray platform for testing blood donors. Human blood or plasma spiked with selected pathogens (10,000, 1,000 or 100 cells or copies/ml), including 6 viral, 2 bacterial and 5 protozoan pathogens were each tested on this platform. The nucleic acids were extracted, amplified using multiplexed sets of pooled specific primers, fragmented, labeled, and hybridized to a microarray. Finally, the detected sequences were identified using an automated genomic database alignment algorithm. The performance of the BBP-RMAv.2 demonstrated detection for most spiked protozoan pathogens at 1,000 cells/ml, 10,000 cells/ml for bacterial pathogens and as low as 100 copies/ml for viral pathogens. Coded specimens, including spiked and negative controls, were identified correctly for one blood specimen and for two plasma specimens. One negative plasma resulted in a false positive detection of a virus demonstrating the effectiveness of the platform.
2024-06-08 | E-MTAB-13972 | biostudies-arrayexpress
Project description:Sepsis is a clinical syndrome that can be caused by bacteria or fungi. Early knowledge on the nature of the causative agent is a prerequisite for targeted anti-microbial therapy. Besides currently used detection methods like blood culture and PCR-based assays, the analysis of the transcriptional response of the host to infecting organisms holds great promise. In this study, we aim to examine the transcriptional footprint of infections caused by the bacterial pathogens Staphylococcus aureus and Escherichia coli and the fungal pathogens Candida albicans and Aspergillus fumigatus in a human whole-blood model. Moreover, we use the expression information to build a random forest classifier to determine if the pathogen is bacterial, fungal or neither of the two. After normalizing the transcription intensities using stably expressed reference genes, we filtered the gene set for biomarkers of bacterial or fungal blood infections. This selection is based on differential expression and an additional gene relevance measure. In this way, we identified 38 biomarker genes, including IL6, SOCS3, and IRG1 which were already associated to sepsis by other studies. Using these genes, we trained the classifier and assessed its performance. It yielded a 96% accuracy (sensitivities >93%, specificities >97%) for a 10-fold stratified cross-validation and a 92% accuracy (sensitivities and specificities >83%) for an additional dataset comprising Cryptococcus neoformans infections. Furthermore, the noise-robustness of the classifier suggests high rates of correct class predictions on datasets of new species. In conclusion, this genome-wide approach demonstrates an effective feature selection process in combination with the construction of a well-performing classification model. Further analyses of genes with pathogen-dependent expression patterns can provide insights into the systemic host responses, which may lead to new anti-microbial therapeutic advances. Analysis of innate immune activation on the basis of gene expression of whole blood cells during ex vivo whole blood infection with bacterial (Staphylococcus aureus, Escherichia coli) and fungal pathogens (Candida albicans, Aspergillus fumigatus) in comparison to mock-treated blood.
2015-03-11 | E-GEOD-65088 | biostudies-arrayexpress
Project description:Bloodstream infections (BSIs), the presence of microorganisms in blood, are potentially serious conditions that can quickly develop into sepsis and life-threatening situations. When assessing proper treatment, rapid diagnosis is the key; besides clinical judgement performed by attending physicians, supporting microbiological tests typically are performed, often requiring microbial isolation and culturing steps, which increases the time required for confirming positive cases of BSI. The additional waiting time forces physicians to prescribe broad-spectrum antibiotics and empiric treatment, before determining the precise cause of the disease. Thus, alternative and more rapid cultivation-independent methods are needed to improve clinical diagnostics, supporting prompt and accurate treatment and reducing the development of antibiotic resistance. In this study, a culture-independent workflow for pathogen detection and identification in blood samples was developed, using peptide biomarkers and applying bottom-up proteomics analyses, i.e., so-called ”proteotyping”. To demonstrate the feasibility of detection of blood infectious pathogens using proteotyping, Escherichia coli and Staphylococcus aureus were included in the study, as the most prominent bacterial causes of bacteremia and sepsis, as well as Candida albicans, one of the most prominent causes of fungemia. Model systems including spiked negative blood samples, as well as positive blood cultures, without further culturing steps, were investigated. Furthermore, an experiment designed to study the incubation time needed for correct identification of the infectious pathogens in blood cultures was performed. Compared to the MALDI-TOF MS-based approaches, shotgun proteotyping demonstrated higher sensitivity and accuracy, and required shorter incubation time before detection and identification of the correct pathogen could be accomplished.
2021-07-20 | PXD023033 | Pride
Project description:A Comparison of Blood Pathogens Detection Among Droplet Digital PCR, Metagenomic Next Generation Sequencing, and Blood Culture in Critically ill Patients With Suspected Bloodstream Infections
| PRJEB42541 | ENA
Project description:Objective:To identify an accurate blood-based gene signature for early detection of Kashin-Beck disease (KBD). Methods: Gene expression analysis was conducted of peripheral blood samples from 100 patients with KBD and 100 controls randomly chosen from two KBD-endemic areas
2014-07-16 | GSE59446 | GEO
Project description:Objective:To identify an accurate blood-based gene signature for early detection of Kashin-Beck disease (KBD). Methods: Gene expression analysis was conducted of peripheral blood samples from 100 patients with KBD and 100 controls randomly chosen from two KBD-endemic areas Two-condition experiment, Control vs. KBD PBM cells. Biological replicates: 100 control replicates, 100 KBD replicates.
2014-07-16 | E-GEOD-59446 | biostudies-arrayexpress
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.
2024-06-08 | E-MTAB-14011 | biostudies-arrayexpress
Project description:The health state of an individual is closely linked to the glycosylation patterns of their blood plasma proteins. However, obtaining this information requires cost- and time-efficient analytical methods. We put forward infrared spectroscopy, which allows label-free analysis of protein glycosylation, but so far has only been applied to analyses of individual proteins. Although spectral information does not directly provide the molecular structure of the glycans, it is sensitive to changes therein and covers all types of glycosidic linkages. Combining single-step ion exchange chromatography with infrared spectroscopy, we developed a workflow that enables separation and analysis of major protein classes in blood plasma. Our results demonstrate that infrared spectroscopy can identify different patterns and global levels of glycosylation of intact plasma proteins. To showcase the strengths and limitations of the proposed approach, we compare the glycoforms of human and bovine alpha-1-acid glycoproteins, which exhibit highly variable global levels of glycosylation. To further independently evaluate our conclusions, the glycan moieties of human alpha-1-acid glycoprotein were further analyzed using established glycomics workflow. Importantly, the chromatographic separation of blood plasma improves the detection of aberrant glycoforms of a given protein, as compared to infrared spectroscopy of bulk plasma. The presented approach allows time-efficient comparison of glycosylation patterns of multiple plasma proteins, opening new avenues for biomedical probing.
2024-02-26 | PXD046796 | Pride