Asad ul-Haq , Kyung-Ann Lee , Hoonhee Seo , Sukyung Kim , Sujin Jo , Kyung Min Ko , Su-Jin Moon , Yun Sung Kim , Jung Ran Choi , Ho-Yeon Song , Hyun-Sook Kim
J. Microbiol. 2022;60(12):1178-1190. Published online November 24, 2022
Microbiome research has been on the rise recently for a more
in-depth understanding of gout. Meanwhile, there is a need to
understand the gut microbiome related to uric acid-lowering
drug resistance. In this study, 16S rRNA gene-based microbiota
analysis was performed for a total of 65 stool samples
from 17 healthy controls and 48 febuxostat-treated gout patients
(including 28 controlled subjects with decreased uric
acid levels and 20 uncontrolled subjects with non-reduced
uric acid levels). Alpha diversity of bacterial community decreased
in the healthy control, controlled, and uncontrolled
groups. In the case of beta diversity, the bacterial community
was significantly different among groups (healthy control, controlled,
and uncontrolled groups). Taxonomic biomarker analysis
revealed the increased population of g-Bifidobacterium
in healthy controls and g-Prevotella in uncontrolled patients.
PCR further confirmed this result at the species level. Additionally,
functional metagenomics predictions led to the exploration
of various functional biomarkers, including purine
metabolism. The results of this study can serve as a basis
for developing potential new strategies for diagnosing and
treating gout from microbiome prospects.
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Microbial communities present in diverse environments from
deep seas to human body niches play significant roles in the
complex ecosystem and human health. Characterizing their
structural and functional diversities is indispensable, and
many approaches, such as microscopic observation, DNA
fingerprinting, and PCR-based marker gene analysis, have
been successfully applied to identify microorganisms. Since
the revolutionary improvement of DNA sequencing technologies,
direct and high-throughput analysis of genomic
DNA from a whole environmental community without prior
cultivation has become the mainstream approach, overcoming
the constraints of the classical approaches. Here, we first
briefly review the history of environmental DNA analysis
applications with a focus on profiling the taxonomic composition
and functional potentials of microbial communities.
To this end, we aim to introduce the shotgun metagenomic
sequencing (SMS) approach, which is used for the untargeted
(“shotgun”) sequencing of all (“meta”) microbial genomes
(“genomic”) present in a sample. SMS data analyses are performed
in silico using various software programs; however,
in silico analysis is typically regarded as a burden on wet-lab
experimental microbiologists. Therefore, in this review, we
present microbiologists who are unfamiliar with in silico analyses
with a basic and practical SMS data analysis protocol.
This protocol covers all the bioinformatics processes of the
SMS analysis in terms of data preprocessing, taxonomic profiling,
functional annotation, and visualization.
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