Journal of Microbiology

Meta-Analysis

Exploring COVID-19 Pandemic Disparities with Transcriptomic Meta-analysis from the Perspective of Personalized Medicine: Medi Kori, Ceyda Kasavi, Kazim Yalcin Arga; J. Microbiol. 2024;62(9):785-798. Published online July 9, 2024; DOI: https://doi.org/10.1007/s12275-024-00154-9

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Abstract: Infection with SARS-CoV2, which is responsible for COVID-19, can lead to differences in disease development, severity and mortality rates depending on gender, age or the presence of certain diseases. Considering that existing studies ignore these differences, this study aims to uncover potential differences attributable to gender, age and source of sampling as well as viral load using bioinformatics and multi-omics approaches. Differential gene expression analyses were used to analyse the phenotypic differences between SARS-CoV-2 patients and controls at the mRNA level. Pathway enrichment analyses were performed at the gene set level to identify the activated pathways corresponding to the differences in the samples. Drug repurposing analysis was performed at the protein level, focusing on host-mediated drug candidates to uncover potential therapeutic differences. Significant differences (i.e. the number of differentially expressed genes and their characteristics) were observed for COVID-19 at the mRNA level depending on the sample source, gender and age of the samples. The results of the pathway enrichment show that SARS-CoV-2 can be combated more effectively in the respiratory tract than in the blood samples. Taking into account the different sample sources and their characteristics, different drug candidates were identified. Evaluating disease prediction, prevention and/or treatment strategies from a personalised perspective is crucial. In this study, we not only evaluated the differences in COVID-19 from a personalised perspective, but also provided valuable data for further experimental and clinical efforts. Our findings could shed light on potential pandemics.

Journal Article

Characteristic alterations of gut microbiota in uncontrolled gout: 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; DOI: https://doi.org/10.1007/s12275-022-2416-1

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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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Different Prostatic Tissue Microbiomes between High- and Low-Grade Prostate Cancer Pathogenesis
Jae Heon Kim, Hoonhee Seo, Sukyung Kim, Md Abdur Rahim, Sujin Jo, Indrajeet Barman, Hanieh Tajdozian, Faezeh Sarafraz, Ho-Yeon Song, Yun Seob Song
International Journal of Molecular Sciences.2024; 25(16): 8943. CrossRef
Reassessing Gout Management through the Lens of Gut Microbiota
Jean Demarquoy, Oumaima Dehmej
Applied Microbiology.2024; 4(2): 824. CrossRef
Changes in gut microbiota structure and function in gout patients
Feiyan Zhao, Zhixin Zhao, Dafu Man, Zhihong Sun, Ning Tie, Hongbin Li, Heping Zhang
Food Bioscience.2023; 54: 102912. CrossRef
Effect of a Novel Handheld Photobiomodulation Therapy Device in the Management of Chemoradiation Therapy-Induced Oral Mucositis in Head and Neck Cancer Patients: A Case Series Study
In-Young Jo, Hyung-Kwon Byeon, Myung-Jin Ban, Jae-Hong Park, Sang-Cheol Lee, Yong Kyun Won, Yun-Su Eun, Jae-Yun Kim, Na-Gyeong Yang, Sul-Hee Lee, Pyeongan Lee, Nam-Hun Heo, Sujin Jo, Hoonhee Seo, Sukyung Kim, Ho-Yeon Song, Jung-Eun Kim
Photonics.2023; 10(3): 241. CrossRef
New drug targets for the treatment of gout arthritis: what’s new?
Tiago H. Zaninelli, Geovana Martelossi-Cebinelli, Telma Saraiva-Santos, Sergio M. Borghi, Victor Fattori, Rubia Casagrande, Waldiceu A. Verri
Expert Opinion on Therapeutic Targets.2023; 27(8): 679. CrossRef
A dynamics association study of gut barrier and microbiota in hyperuricemia
Qiulan Lv, Jun Zhou, Changyao Wang, Xiaomin Yang, Yafei Han, Quan Zhou, Ruyong Yao, Aihua Sui
Frontiers in Microbiology.2023;[Epub] CrossRef
Biochemical Recurrence in Prostate Cancer Is Associated with the Composition of Lactobacillus: Microbiome Analysis of Prostatic Tissue
Jae Heon Kim, Hoonhee Seo, Sukyung Kim, Asad Ul-Haq, Md Abdur Rahim, Sujin Jo, Ho-Yeon Song, Yun Seob Song
International Journal of Molecular Sciences.2023; 24(13): 10423. CrossRef
Remote effects of kidney drug transporter OAT1 on gut microbiome composition and urate homeostasis
Vladimir S. Ermakov, Jeffry C. Granados, Sanjay K. Nigam
JCI Insight.2023;[Epub] CrossRef
Causal Relationship between Gut Microbiota and Gout: A Two-Sample Mendelian Randomization Study
Mengna Wang, Jiayao Fan, Zhaohui Huang, Dan Zhou, Xue Wang
Nutrients.2023; 15(19): 4260. CrossRef
Emerging Urate-Lowering Drugs and Pharmacologic Treatment Strategies for Gout: A Narrative Review
Robert Terkeltaub
Drugs.2023; 83(16): 1501. CrossRef
Characterization of Fecal Microbiomes of Osteoporotic Patients in Korea
Asad Ul-Haq, Hoonhee Seo, Sujin Jo, Hyuna Park, Sukyung Kim, Youngkyoung Lee, Saebim Lee, Je Hoon Jeong, Ho‑Yeon Song
Polish Journal of Microbiology.2022; 71(4): 601. CrossRef

Randomized Controlled Trial

Ulmus macrocarpa Hance extract modulates intestinal microbiota in healthy adults: a randomized, placebo-controlled clinical trial: Kwangmin Kim , Karpagam Veerappan , Nahyun Woo , Bohyeon Park , Sathishkumar Natarajan , Hoyong Chung , Cheolmin Kim , Junhyung Park; J. Microbiol. 2021;59(12):1150-1156. Published online October 26, 2021; DOI: https://doi.org/10.1007/s12275-021-1329-8

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Abstract

The stem and root bark of Ulmus macrocarpa Hance has been used as traditional pharmacological agent against inflammation related disorders. The objective of this study was to explore the impact of Ulmus macrocarpa Hance extract (UME) on human gut microbiota. A randomized placebo-controlled clinical study was conducted in healthy adults. The study subjects were given 500 mg/day of UME or placebo orally for 4 weeks. Eighty fecal samples were collected at baseline and 4 weeks of UME or placebo intervention. The gut microbiota variation was evaluated by 16S rRNA profiling. The microbial response was highly personalized, and no statistically significant differences was observed in both species richness and abundance. The number of bacterial species identified in study subjects ranged from 86 to 182 species. The analysis for taxonomical changes revealed an increase in Eubacterium ventriosum, Blautia faecis, Ruminococcus gnavus in the UME group. Functional enrichment of bacterial genes showed an increase in primary and secondary bile acid biosynthesis in UME group. Having known from previous studies Eubacterium regulated bile acid homeostasis in protecting gut microbial architecture and immunity, we suggest that UME supplementation might enhance host immunity by modulating gut microbiota. This is the first stage study and forthcoming clinical studies with larger participants are needed to confirm these findings.

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Catechin and flavonoid glycosides from the Ulmus genus: Exploring their nutritional pharmacology and therapeutic potential in osteoporosis and inflammatory conditions
Chanhyeok Jeong, Chang Hyung Lee, Jiwon Seo, Jung Han Yoon Park, Ki Won Lee
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Comparative transcriptomes of four Elm species provide insights into the genetic features and adaptive evolution of Ulmus spp.
Shijie Wang, Lihui Zuo, Yichao Liu, Lianxiang Long, Jianghao Wu, Mengting Yuan, Jinmao Wang, Minsheng Yang
Forest Ecology and Management.2024; 553: 121560. CrossRef
Dietary Supplementation with Popped Amaranth Modulates the Gut Microbiota in Low Height-for-Age Children: A Nonrandomized Pilot Trial
Oscar de Jesús Calva-Cruz, Cesaré Ovando-Vázquez, Antonio De León-Rodríguez, Fabiola Veana, Eduardo Espitia-Rangel, Samuel Treviño, Ana Paulina Barba-de la Rosa
Foods.2023; 12(14): 2760. CrossRef
Potential lipid-lowering effects of Ulmus macrocarpa Hance extract in adults with untreated high low-density lipoprotein cholesterol concentrations: A randomized double-blind placebo-controlled trial
Ye Li Lee, Sang Yeoup Lee
Frontiers in Medicine.2022;[Epub] CrossRef
Research progress on the relationship between intestinal microecology and intestinal bowel disease
Qianhui Fu, Tianyuan Song, Xiaoqin Ma, Jian Cui
Animal Models and Experimental Medicine.2022; 5(4): 297. CrossRef
The current status of old traditional medicine introduced from Persia to China
Jinmin Shi, Yifan Yang, Xinxin Zhou, Lijun Zhao, Xiaohua Li, Abdullah Yusuf, Mohaddeseh S. M. Z. Hosseini, Fatemeh Sefidkon, Xuebo Hu
Frontiers in Pharmacology.2022;[Epub] CrossRef

Journal Articles

Instruction of microbiome taxonomic profiling based on 16S rRNA sequencing: Hyojung Kim , Sora Kim , Sungwon Jung; J. Microbiol. 2020;58(3):193-205. Published online February 27, 2020; DOI: https://doi.org/10.1007/s12275-020-9556-y

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Abstract

Recent studies on microbiome highlighted their importance in various environments including human, where they are involved in multiple biological contexts such as immune mechanism, drug response, and metabolism. The rapid increase of new findings in microbiome research is partly due to the technological advances in microbiome identification, including the next-generation sequencing technologies. Several applications of different next-generation sequencing platforms exist for microbiome identification, but the most popular method is using short-read sequencing technology to profile targeted regions of 16S rRNA genes of microbiome because of its low-cost and generally reliable performance of identifying overall microbiome compositions. The analysis of targeted 16S rRNA sequencing data requires multiple steps of data processing and systematic analysis, and many software tools have been proposed for such procedures. However, properly organizing and using such software tools still require certain level of expertise with computational environments. The purpose of this article is introducing the concept of computational analysis of 16S rRNA sequencing data to microbiologists and providing easy-to-follow and step-by-step instructions of using recent software tools of microbiome analysis. This instruction may be used as a quick guideline for general next-generation sequencing-based microbiome studies or a template of constructing own software pipelines for customized analysis.

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逸欣王
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Microbial community analysis using high-throughput sequencing technology: a beginner’s guide for microbiologists: Jihoon Jo , Jooseong Oh , Chungoo Park; J. Microbiol. 2020;58(3):176-192. Published online February 27, 2020; DOI: https://doi.org/10.1007/s12275-020-9525-5

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Abstract

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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Reviews

[MINIREVIEW] Progress of analytical tools and techniques for human gut microbiome research: Eun-Ji Song , Eun-Sook Lee , Young-Do Nam; J. Microbiol. 2018;56(10):693-705. Published online September 28, 2018; DOI: https://doi.org/10.1007/s12275-018-8238-5

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Abstract

Massive DNA sequencing studies have expanded our insights and understanding of the ecological and functional characteristics of the gut microbiome. Advanced sequencing technologies allow us to understand the close association of the gut microbiome with human health and critical illnesses. In the future, analyses of the gut microbiome will provide key information associating with human individual health, which will help provide personalized health care for diseases. Numerous molecular biological analysis tools have been rapidly developed and employed for the gut microbiome researches; however, methodological differences among researchers lead to inconsistent data, limiting extensive share of data. It is therefore very essential to standardize the current
method
ologies and establish appropriate pipelines for human gut microbiome research. Herein, we review the methods and procedures currently available for studying the human gut microbiome, including fecal sample collection, metagenomic DNA extraction, massive DNA sequencing, and data analyses with bioinformatics. We believe that this review will contribute to the progress of gut microbiome research in the clinical and practical aspects of human health.

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MINIREVIEW] On the study of microbial transcriptomes using second- and third-generation sequencing technologies: Sang Chul Choi; J. Microbiol. 2016;54(8):527-536. Published online August 2, 2016; DOI: https://doi.org/10.1007/s12275-016-6233-2

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Abstract

Second-generation sequencing technologies transformed the study of microbial transcriptomes. They helped reveal the transcription start sites and antisense transcripts of microbial species, improving the microbial genome annotation. Quantification of genome-wide gene expression levels allowed for functional studies of microbial research. Ever-evolving sequencing technologies are reshaping approaches to studying microbial transcriptomes. Recently, Oxford Nanopore Technologies delivered a sequencing platform called MinION, a third-generation sequencing technology, to the research community. We expect it to be the next sequencing technology that enables breakthroughs in life science fields. The studies of microbial transcriptomes will be no exception. In this paper, we review microbial transcriptomics studies using second- generation sequencing technology. We also discuss the prospect of microbial transcriptomics studies with thirdgeneration sequencing.

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Research Support, Non-U.S. Gov'ts

Prediction of Bacterial microRNAs and Possible Targets in Human Cell Transcriptome: Amir Shmaryahu , Margarita Carrasco , Pablo D.T. Valenzuela; J. Microbiol. 2014;52(6):482-489. Published online May 29, 2014; DOI: https://doi.org/10.1007/s12275-014-3658-3

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Abstract

Recent studies have examined gene transfer from bacteria to humans that would result in vertical inheritance. Bacterial DNA appears to integrate into the human somatic genome through an RNA intermediate, and such integrations are detected more frequently in tumors than normal samples and in RNA than DNA samples. Also, vertebrate viruses encode products that interfere with the RNA silencing machinery, suggesting that RNA silencing may indeed be important for antiviral responses in vertebrates. RNA silencing in response to virus infection could be due to microRNAs encoded by either the virus or the host. We hypothesized that bacterial expression of RNA molecules with secondary structures is potentially able to generate miRNA molecules that can interact with the human host mRNA during bacterial infection. To test this hypothesis, we developed a pipelinebased bioinformatics approach to identify putative micro-RNAs derived from bacterial RNAs that may have the potential to regulate gene expression of the human host cell. Our results suggest that 68 bacterial RNAs predicted from 37 different bacterial genomes have predicted secondary structures potentially able to generate putative microRNAs that may interact with messenger RNAs of genes involved in 47 different human diseases. As an example, we examined the effect of transfecting three putative microRNAs into human embryonic kidney 293 (HEK293) cells. The results show that the bacterially derived microRNA sequence can significantly regulate the expression of the respective target human gene. We suggest that the study of these predicted microRNAs may yield important clues as to how the human host cell processes involved in human diseases like cancer, diabetes, rheumatoid arthritis, and others may respond to a particular bacterial environment.

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A Method for Comparing Multiple Bacterial Community Structures from 16S rDNA Clone Library Sequences: Inae Hur , Jongsik Chun; J. Microbiol. 2004;42(1):9-13.; DOI: https://doi.org/2008 [pii]

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Abstract: Culture-independent approaches, based on 16S rDNA sequences, are extensively used in modern microbial ecology. Sequencing of the clone library generated from environmental DNA has advantages over fingerprint-based methods, such as denaturing gradient gel electrophoresis, as it provides precise identification and quantification of the phylotypes present in samples. However, to date, no method exists for comparing multiple bacterial community structures using clone library sequences. In this study, an automated method to achieve this has been developed, by applying pair wise alignment, hierarchical clustering and principle component analysis. The method has been demonstrated to be successful in comparing samples from various environments. The program, named CommCluster, was written in JAVA, and is now freely available, at http://chunlab.snu.ac.kr/commcluster/.

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