Characterization of Fecal Microbiota with Clinical Specimen Using Long-Read and Short-Read Sequencing Platform

Wei, Po Li; Hung, Ching-Sheng; Kao, Yi Wei; Lin, Ying; Lee, Cheng Yang; Chang, Tzu Hao; Shia, Ben‐Chang; Lin, Ji-Ping

doi:10.3390/ijms21197110

Cited by 17 publications

(21 citation statements)

References 25 publications

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“…These results delineated differences in the composition rather than the richness or numerical abundance of the gut microbial communities between the CKD patients and healthy participants. The long-read sequencing approach has been demonstrated to exhibit a higher efficiency than that of short-read sequencing for taxonomic classification of the gut microbiota at the species level [21,22]. In this study, around 350-400 OTUs at the species level were classified in individual groups using MinION sequencing-coupled with the EPI2ME algorithm, and the top 20 classified OTUs at the species level in all groups are shown in Figure 3.…”

Section: Statistical Results Of Gut Microbial Communities In Enrolled Subjected Assessed With Long-read Sequencing Resultsmentioning

confidence: 82%

Gut Microbiota Composition and Its Metabolites in Different Stages of Chronic Kidney Disease

Chen

Liu

et al. 2021

JCM

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A growing body of study have documented the association of gut dysbiosis or fecal metabolites with chronic kidney disease (CKD). However, it is not clear whether the phenomenon simply reflects the microenvironment changes correlated with the CKD severity or contributes to the progression of CKD. In this study, we identified the gut microbiota and metabolite in feces samples correlated with CKD severity using the Nanopore long-read sequencing platform and UPLC-coupled MS/MS approach. A cross-sectional cohort study was performed from 1 June 2020 to 31 December 2020. One hundred and fifty-six clinical participants, including 60 healthy enrollees and 96 Stage 1–5 CKD patients, were enrolled in this study. The ROC curve generated with the relative abundance of Klebsiella pneumonia or S-Adenosylhomocysteine showed a gradual increase with the CKD severity. Our results further revealed the positive correlation of increased K. pneumonia and S-Adenosylhomocysteine in gut environment, which may be of etiological importance to the deterioration of a CKD patient. In that sense, the microbiota or metabolite changes constitute potential candidates for evaluating the progression of CKD.

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Section: Statistical Results Of Gut Microbial Communities In Enrolled Subjected Assessed With Long-read Sequencing Resultsmentioning

confidence: 82%

Gut Microbiota Composition and Its Metabolites in Different Stages of Chronic Kidney Disease

Chen

Liu

et al. 2021

JCM

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“…The functional assignment of metagenomic data, particularly the presence and abundance of BSH (EC 3.5.1.24), 7α‐HSDH, 7β‐HSDH and bai genes, were explored using CLC Genomic 15 workbench version 20.0.4 (CLC, Bio‐Qiagen). An average of 11 million reads per sample were trimmed and assembled using the ‘De Novo Assemble Metagenomic’ tool.…”

Section: Methodsmentioning

confidence: 99%

Decreased secondary faecal bile acids in children with ulcerative colitis and Clostridioides difficile infection

Rotondo-Trivette

Wang

Gayer

et al. 2021

Aliment Pharmacol Ther

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Summary Background Patients with ulcerative colitis (UC) have an increased risk of Clostridioides difficile infection (CDI). There is a well‐documented relationship between bile acids and CDI. Aims To evaluate faecal bile acid profiles and gut microbial changes associated with CDI in children with UC. Methods This study was conducted at Children's Hospital Los Angeles. Faecal bile acids and gut microbial genes related to bile acid metabolism were measured in 29 healthy children, 23 children with mild to moderate UC without prior CDI (UC group), 16 children with mild to moderate UC with prior CDI (UC+CDI group) and 10 children without UC with prior CDI (CDI group). Results Secondary faecal bile acids, especially lithocholic acid (3.296 vs 10.793, P ≤ 0.001) and ursodeoxycholic acid (7.414 vs 10.617, P ≤ 0.0001), were significantly lower in children with UC+CDI when compared to UC alone. Secondary faecal bile acids can predict disease status between these groups with 84.6% accuracy. Additionally, gut microbial genes coding for bile salt hydrolase, 7α‐hydroxysteroid dehydrogenase and 7α/β‐dehydroxylation were all diminished in children with UC+CDI compared to children with UC alone. Conclusions Bile acids can distinguish between children with UC based on their prior CDI status. Bile acid profile changes can be explained by gut microbial genes encoding for bile salt hydrolase, 7α‐hydroxysteroid dehydrogenase and 7α/β‐dehydroxylation. Bile acid profiles may be helpful as biomarkers to identify UC children who have had CDI and may serve as future therapeutic targets.

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“…Oxford Nanopore Technologies (Oxford, UK; ONT) has developed a third-generation platform for long-read and direct sequencing of individual strands of DNA [ 26 , 27 ], and the ability to provide a full-length sequence of 16S rRNA genes leads to more accurate identification of microorganisms at the species level [ 28 , 29 ]. Within the last five years, the sequence accuracy of ONT nanopore sequencing has been improved from 60% to >90%, and researchers have begun to use it to characterize the composition of the microbial community in clinical samples, such as human respiratory samples [ 30 ], fecal samples [ 31 ], and colorectal cancer tumor tissues [ 32 ].…”

Section: Introductionmentioning

confidence: 99%

Species-Level Characterization of the Microbiome in Breast Tissues with Different Malignancy and Hormone-Receptor Statuses Using Nanopore Sequencing

Luo

Shi

et al. 2023

JPM

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Unambiguous evidence indicates that microbes are closely linked to various human diseases, including cancer. Most prior work investigating the microbiome of breast tissue describes an association between compositional differences of microbial species in benign and malignant tissues, but few studies have examined the relative abundance of microbial communities within human breast tissue at the species level. In this work, a total of 44 breast tissue samples including benign and malignant tissues with adjacent normal breast tissue pairs were collected, and Oxford Nanopore long-read sequencing was employed to assess breast tissue microbial signatures. Nearly 900 bacterial species were detected from the four dominant phyla: Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. The bacteria with the highest abundance in all breast tissues was Ralstonia pickettii, and its relative abundance increased with decreasing malignancy. We further examined the breast-tissue microbiome composition with different hormone-receptor statuses, and the relative abundance of the genus Pseudomonas increased most significantly in breast tissues. Our study provides a rationale for exploring microbiomes associated with breast carcinogenesis and cancer development. Further large-cohort investigation of the breast microbiome is necessary to characterize a microbial risk signature and develop potential microbial-based prevention therapies.

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Characterization of Fecal Microbiota with Clinical Specimen Using Long-Read and Short-Read Sequencing Platform

Cited by 17 publications

References 25 publications

Gut Microbiota Composition and Its Metabolites in Different Stages of Chronic Kidney Disease

Gut Microbiota Composition and Its Metabolites in Different Stages of Chronic Kidney Disease

Decreased secondary faecal bile acids in children with ulcerative colitis and Clostridioides difficile infection

Species-Level Characterization of the Microbiome in Breast Tissues with Different Malignancy and Hormone-Receptor Statuses Using Nanopore Sequencing

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