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ABSTRACT:
PROVIDER: PRJNA723730 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Analysis of COVID-19 hospitalized patients, with different kind of symptoms, by human rectal swabs collection and 16S sequencing approach.
2022-09-22 | E-MTAB-12236 | biostudies-arrayexpress
Project description:Clostridioides difficile strain:Hospitalized patients | isolate:Hospitalized patients Genome sequencing and assembly
| PRJNA732612 | ENA
Project description:Background: Distinguishing between bacterial and viral lower respiratory tract infections (LRTI) in hospitalized patients remains challenging. Transcriptional profiling is a promising tool for improving diagnosis in LRTI. Methods: We performed whole blood transcriptional analysis in a cohort of 118 adult patients (median [IQR] age, 61 [50-76] years) hospitalized with bacterial, viral or viral-bacterial LRTI, and 40 age-matched healthy controls (60 [46-70] years). We applied class comparisons, modular analysis and class prediction algorithms to identify distinct biosignatures for bacterial and viral LRTI, which were validated in an independent group of patients. Results: Patients were classified as bacterial (B, n=22), viral (V, n=71) and bacterial-viral LRTI (BV, n=25) based on comprehensive microbiologic testing. Compared with healthy controls statistical group comparisons (p<0.01; with multiple test corrections) identified 3,376 differentially expressed genes in patients with B-LRTI; 2,391 in V-LRTI, and 2,628 in BV-LRTI. Independent of etiologic pathogen, patients with LRTI demonstrated overexpression of innate immunity and underexpression of adaptive immunity genes. Patients with B-LRTI showed significant overexpression of inflammation (B>BV>V) and neutrophils (B>BV>V) while those with V-LRTI displayed significantly greater overexpression of interferon genes (V>BV>B). The K-Nearest Neighbors (K-NN) algorithm identified 10 classifier genes that discriminated patients with bacterial vs viral LRTI with 97% [95%CI: 84-100] sensitivity and 92% [77-98] specificity. In comparison, procalcitonin classified bacterial vs viral LRTI with 38% [18-62] sensitivity and 91% [76-98] specificity. Conclusions: Transcriptional profiling can be used as a helpful tool for the diagnosis of adults hospitalized with LRTI. 158 samples, no replicates; bacterial LRTI n=22, viral LRTI n=71, bacterial-viral coinfections n=25, and healthy controls n=40
2015-09-14 | E-GEOD-60244 | biostudies-arrayexpress
Project description:The goal of this study is the discovery of (a) meaningful phylogenomic relationships among members of this B. cereus/B. anthracis group, and (b) reliable gene-phenotype associations, e.g. recognition of links between genomic traits and the ability of certain strains to cause various forms of disease. We also tried to elucidate genome evolution aspects that may lead to the emergence of variants that are capable (or have the potential) of causing anthrax-like disease. This large-scale comparative genomics approach is unprecedented for this taxonomic group. Dr. A. Hoffmaster (CDC) provided the PFGRC with 73 B. cereus and B. anthracis isolates from the CDC culture collection. Of these, 27 were isolated from patients with severe or systemic disease; ten isolates of this group were obtained from patients (welding factory workers) with anthrax-like disease or from the environment near their workplace. Another set of 26 represented isolates from food-born illnesses. Of the 26 gastrointestinal disease isolates (GIDI), 10 were obtained from patients with diarrhea, whereas another set of 10 had been shown to harbor the emetic (vomit) toxin gene by PCR. The rest of the group consisted of 20 isolates with various phenotypes. All strains were screened for their genomic content using the B. cereus/B. anthracis species microarray.
2009-11-25 | GSE19125 | GEO
Project description:The lack of available biomarkers for diagnosing and predicting different stages of coronavirus disease 2019 (COVID-19) is currently one of the main challenges that clinicians are facing. Recent evidence indicates that the plasma levels of specific miRNAs may be significantly modified in COVID-19 patients. Large-scale deep sequencing analysis of small RNA expression was performed on plasma samples from 40 patients hospitalized for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (between March and May 2020) (median 13.50 [IQR 9–24] days since symptoms initiation) and 21 healthy noninfected individuals. Patients were categorized as hospitalized not requiring oxygen therapy (n = 6), hospitalized requiring low-flow oxygen (n = 23), and hospitalized requiring high-flow oxygen support (n = 11). A total of 1218 different micro(mi)RNAs were identified. When compared with healthy noninfected donors, SARS-CoV-2 infected patients showed significantly (fold change [FC] >1.2 and adjusted p [padj] <0.05) altered expression of 190 miRNAs. The top 10 differentially expressed (DE) miRNAs were miR-122-5p, let-7b-5p, miR-146a-5p, miR-342-3p, miR-146b-5p, miR-629-5p, miR-24-3p, miR-12136, let-7a-5p, and miR-191-5p, which displayed FC and padj values ranging from 153 to 5 and 2.51 × 10-32 to 2.21 × 10-21, respectively, which unequivocally diagnosed SARS-CoV-2 infection. No differences in blood cell counts and biochemical plasma parameters, including interleukin 6, ferritin and D-dimer, were observed between COVID-19 patients on high-flow oxygen therapy, low-flow oxygen therapy, or not requiring oxygen therapy. Notably, 31 significantly deregulated miRNAs were found when patients on high- and low-flow oxygen therapy were compared. Similarly, 6 DE miRNAs were identified between patients on high flow and those not requiring oxygen therapy. SARS-CoV-2 infection generates a specific miRNA signature in hospitalized patients. Furthermore, specific miRNA profiles are associated with COVID-19 prognosis in severe patients.
2024-04-03 | GSE230092 | GEO
Project description:Transcriptome profiling of pyrethroid resistant field populations of Anopheles funestus across Uganda and neighboring Kenya from Uganda and Kenya compared to a susceptible lab strain FANG
2020-10-19 | E-MTAB-9529 | biostudies-arrayexpress
Project description:The study aimed to define transcriptional signatures for detection of active TB (TB) compared to latent TB infection (LTBI) as well as to other diseases (OD) with similar clinical phenotypes in patients with and without HIV in a paediatric cohort from Kenya Transcriptional signatures were identified that distinguished active TB from LTBI, active TB from other diseases, and active TB from both LTBI and other diseases in HIV+/- patients. Children were recruited from 2 hospitals in Coast Province, Kenya (n=157) who were either HIV+ or HIV - with either active TB (culture confirmed), active TB (culture negative), LTBI or OD. Blood was collected into PAX gene tubes (PreAnalytiX). Total RNA integrity was assessed using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA). Labeled cRNA was hybridized to Illumina Human HT-12 Beadchips. Data were analysed in R.
2014-05-01 | E-GEOD-39939 | biostudies-arrayexpress
Project description:Genomic variation is an inherent phenomena observed among members of same species belonging to different geographical locations. In case of P. falciparum, an apicomplexan protozoan parasite, its 22.8 MB nuclear genome is known to display vast genetic diversity in the subtelomeric compartments having but not exclusively variant gene families like var, rifins and stevors and examples in other elements of the genome have recently been documented. Microarrays, relies solely on the genomic sequence information to capture the relevant transcript abundance and needs to consider these variations into account for revealing true transcriptional variation.Here, we describe the designing strategy of a custom P. falciparum 15K array using Agilent platform to study the transcriptome of Indian field isolates for which genome sequence information is limited. Array contains probes representing genome sequence of two distinct geographical isolates (i.e 3D7 and HB3) and subtelomeric var gene sequence of a third isolate (IT4) known to adhere in culture condition. Probes in the array have been selected based on their efficiency to detect transcripts by performing a 244K array experiment representing multiple probes per gene/transcript. Array performance was evaluated and validated using RNA materials from P. falciparum clinical isolates obtained directly from patients with differing clinical conditions due to malaria infection.Due to pre probe screening large percentage (91 %) of the represented transcripts could be detected from Indian P. falciparum isolates. Replicated probes and multiple probes representing the same gene showed perfect correlation between them suggesting good probe performance. Additional transcripts could be detected due to inclusion of unique probes representing HB3 strain transcripts. Variant surface antigen (VSA) transcripts were detected by optimized probes representing the VSA genes of three geographically distinct strains. Plasmodium falciparum isolates were collected from patients (n=13) with differing clinical conditions. The patients exhibited symptoms categorized as uncomplicated (n=6) or complicated malaria (n=7). Criteria for determination of complicated disease were based on World Health Organization year 2000 guidelines. Microarray array based transcriptional profiling was carried out to evaluate the performance of the array.
2016-01-17 | E-GEOD-54253 | biostudies-arrayexpress