Project description:In this study, we performed a comparative analysis of gut microbiota composition and gut microbiome-derived bacterial extracellular vesicles (bEVs) isolated from patients with solid tumours and healthy controls. After isolating bEVs from the faeces of solid tumour patients and healthy controls, we performed spectrometry analysis of their proteomes and next-generation sequencing (NGS) of the 16S gene. We also investigated the gut microbiomes of faeces from patientsand controls using 16S rRNA sequencing. Machine learning was used to classify the samples into patients and controls based on their bEVs and faecal microbiomes.
Project description:Azithromycin (AZM) reduces pulmonary inflammation and exacerbations in chronic obstructive pulmonary disease patients with emphysema. The antimicrobial effects of AZM on the lung microbiome are not known and may contribute to its beneficial effects. Methods. Twenty smokers with emphysema were randomized to receive AZM 250 mg or placebo daily for 8 weeks. Bronchoalveolar lavage (BAL) was performed at baseline and after treatment. Measurements included: rDNA gene quantity and sequence. Results. Compared with placebo, AZM did not alter bacterial burden but reduced α-diversity, decreasing 11 low abundance taxa, none of which are classical pulmonary pathogens. Conclusions. AZM treatment the lung microbiome Randomized trial comparing azithromycin (AZM) treatment with placebo for eight weeks. Bronchoalveolar lavage (BAL) samples were obtained before and after treatment to explore the effects of AZM on microbiome, in the lower airways. 16S rRNA was quantified and sequenced (MiSeq) The amplicons from total 39 samples are barcoded and the barcode is provided in the metadata_complete.txt file.
Project description:This repository contains human sample derived microbiome full-length 16S rRNA sequencing data for sputum samples in COPD patients. The project goal is to understand the association of the lung microbiome with accelerated lung function decline in COPD patients.
Project description:In previous study, patients with Diabetes Mellitus (DM) have high risk of active TB and LTBI. Here we report and compare 16S rRNA data of DM-LTBI and DM-nonLTBI in gut microbiota to identify differential candidates between the two groups. The results showed the differential genera have potential to predict the LTBI status in patients.
Project description:One unmet challenge in current lung cancer diagnosis is to accurately differentiate lung cancer patients from those with other lung diseases with similar clinical symptoms and radiological features. Previous studies have reported cases of misdiagnosis for patients with lung cancer mimicking pulmonary tuberculosis (TB) or for TB patients with multiple lung nodules mimicking lung cancer progression, which is concerning for clinical practice in TB-endemic countries/regions. Here, we develop a molecular signature composed of non-canonical small non-coding RNAs in human peripheral blood mononuclear cells (PBMCs), including tRNA-derived small RNAs (tsRNAs), rRNA-derived small RNAs (rsRNAs), and YRNA-derived small RNAs (ysRNAs). This signature consists of i) the tsRNAs derived from tRNA-Ala, tRNA-Asn, tRNA-Leu, tRNA-Lys, and tRNA-Tyr that are upregulated in the lung cancer patients relative to the healthy controls and patients with pulmonary TB, ii) the rsRNAs derived from rRNA-5S that are upregulated in the lung cancer patients but downregulated in TB patients relative to the controls, and iii) the ysRNAs originating from YRNA-RNY1 that are downregulated in the lung cancer patients but upregulated in the TB patients compared with the controls. This diagnostic signature discriminates between healthy controls, lung cancer patients, and pulmonary TB subjects with high accuracy in both the discovery and validation cohorts. We conclude that the PBMC tsRNAs, rsRNAs, and ysRNAs are informative for both screening for and discriminating between lung cancer and pulmonary TB.
Project description:One unmet challenge in current lung cancer diagnosis is to accurately differentiate lung cancer patients from those with other lung diseases with similar clinical symptoms and radiological features. Previous studies have reported cases of misdiagnosis for patients with lung cancer mimicking pulmonary tuberculosis (TB) or for TB patients with multiple lung nodules mimicking lung cancer progression, which is concerning for clinical practice in TB-endemic countries/regions. Here, we develop a molecular signature composed of non-canonical small non-coding RNAs in human peripheral blood mononuclear cells (PBMCs), including tRNA-derived small RNAs (tsRNAs), rRNA-derived small RNAs (rsRNAs), and YRNA-derived small RNAs (ysRNAs). This signature consists of i) the tsRNAs derived from tRNA-Ala, tRNA-Asn, tRNA-Leu, tRNA-Lys, and tRNA-Tyr that are upregulated in the lung cancer patients relative to the healthy controls and patients with pulmonary TB, ii) the rsRNAs derived from rRNA-5S that are upregulated in the lung cancer patients but downregulated in TB patients relative to the controls, and iii) the ysRNAs originating from YRNA-RNY1 that are downregulated in the lung cancer patients but upregulated in the TB patients compared with the controls. This diagnostic signature discriminates between healthy controls, lung cancer patients, and pulmonary TB subjects with high accuracy in both the discovery and validation cohorts. We conclude that the PBMC tsRNAs, rsRNAs, and ysRNAs are informative for both screening for and discriminating between lung cancer and pulmonary TB.
Project description:Gut microbial profiling of uterine fibroids (UFs) patients comparing control subjects. The gut microbiota was examined by 16S rRNA quantitative arrays and bioinformatics analysis. The goal was to reveal alterations in the gut microbiome of uterine fibroids patients.
Project description:The impact of mono-chronic S. stercoralis infection on the gut microbiome and microbial activities in infected participants was explored. The 16S rRNA gene sequencing of a longitudinal study with 2 sets of human fecal was investigated. Set A, 42 samples were matched, and divided equally into positive (Pos) and negative (Neg) for S. stercoralis diagnoses. Set B, 20 samples of the same participant in before (Ss+PreT) and after (Ss+PostT) treatment was subjected for 16S rRNA sequences and LC-MS/MS to explore the effect of anti-helminthic treatment on microbiome proteomes.
Project description:The human gut is colonized by trillions of microorganisms that influence human health and disease through the metabolism of xenobiotics, including therapeutic drugs and antibiotics. The diversity and metabolic potential of the human gut microbiome have been extensively characterized, but it remains unclear which microorganisms are active and which perturbations can influence this activity. Here, we use flow cytometry, 16S rRNA gene sequencing, and metatranscriptomics to demonstrate that the human gut contains distinctive subsets of active and damaged microorganisms, primarily composed of Firmicutes, which display marked temporal variation. Short-term exposure to a panel of xenobiotics resulted in significant changes in the physiology and gene expression of this active microbiome. Xenobiotic-responsive genes were found across multiple bacterial phyla, encoding novel candidate proteins for antibiotic resistance, drug metabolism, and stress response. These results demonstrate the power of moving beyond DNA-based measurements of microbial communities to better understand their physiology and metabolism. RNA-Seq analysis of the human gut microbiome during exposure to antibiotics and therapeutic drugs.