Journal of Microbiology

Volume 59(3); March 2021

Introductory Journal Article

[Editorial]Omics-based microbiome analysis in microbial ecology: from sequences to information: Jang-Cheon Cho; J. Microbiol. 2021;59(3):229-232.; DOI: https://doi.org/10.1007/s12275-021-0698-3

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Abstract: Microbial ecology is the study of microorganisms present in nature. It particularly focuses on microbial interactions with any biota and with surrounding environments. Microbial ecology is entering its golden age with innovative multi-omics
methods
triggered by next-generation sequencing technologies. However, the extraction of ecologically relevant information from ever-increasing omics data remains one of the most challenging tasks in microbial ecology. This special issue includes 11 review articles that provide an overview of the state of the art of omics-based approaches in the field of microbial ecology, with particular emphasis on the interpretation of omics data, environmental pollution tracking, interactions in microbiomes, and viral ecology.

Reviews

Application of computational approaches to analyze metagenomic data: Ho-Jin Gwak , Seung Jae Lee , Mina Rho; J. Microbiol. 2021;59(3):233-241. Published online February 10, 2021; DOI: https://doi.org/10.1007/s12275-021-0632-8

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11 Citations

Abstract: Microorganisms play a vital role in living systems in numerous ways. In the soil or ocean environment, microbes are involved in diverse processes, such as carbon and nitrogen cycle, nutrient recycling, and energy acquisition. The relation between microbial dysbiosis and disease developments has been extensively studied. In particular, microbial communities in the human gut are associated with the pathophysiology of several chronic diseases such as inflammatory bowel disease and diabetes. Therefore, analyzing the distribution of microorganisms and their associations with the environment is a key step in understanding nature. With the advent of nextgeneration sequencing technology, a vast amount of metagenomic data on unculturable microbes in addition to culturable microbes has been produced. To reconstruct microbial genomes, several assembly algorithms have been developed by incorporating metagenomic features, such as uneven depth. Since it is difficult to reconstruct complete microbial genomes from metagenomic reads, contig binning approaches were suggested to collect contigs that originate from the same genome. To estimate the microbial composition in the environment, various methods have been developed to classify individual reads or contigs and profile bacterial proportions. Since microbial communities affect their hosts and environments through metabolites, metabolic profiles from metagenomic or metatranscriptomic data have been estimated. Here, we provide a comprehensive review of computational
methods
that can be applied to investigate microbiomes using metagenomic and metatranscriptomic sequencing data. The limitations of metagenomic studies and the key approaches to overcome such problems are discussed.

Prokaryotic DNA methylation and its functional roles: Hoon Je Seong , Sang-Wook Han , Woo Jun Sul; J. Microbiol. 2021;59(3):242-248. Published online February 23, 2021; DOI: https://doi.org/10.1007/s12275-021-0674-y

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29 Citations

Abstract: DNA methylation is known as a universal mechanism of epigenetic regulation in all kingdoms of life. Particularly, given that prokaryotes lack key elements such as histones and nucleosomes that can structurally modify DNA, DNA methylation is considered a major epigenetic regulator in these organisms. However, because DNA methylation studies have focused primarily on eukaryotes, the mechanism of prokaryotic DNA methylation has been less studied than in eukaryotes. DNA methylation in prokaryotes plays an important role in regulating not only the host defense system, but also the cell cycle, gene expression, and virulence that can respond directly to the environment. Recent advances in sequencing techniques capable of detecting methylation signals have allowed for the characterization of prokaryotic genome-wide epigenetic regulation. In this review, we describe representative examples of cellular events regulated by DNA methylation in prokaryotes, from early studies to current applications.

Microbial phenomics linking the phenotype to function: The potential of Raman spectroscopy: Jin-Kyung Hong , Soo Bin Kim , Eun Sun Lyou , Tae Kwon Lee; J. Microbiol. 2021;59(3):249-258. Published online January 26, 2021; DOI: https://doi.org/10.1007/s12275-021-0590-1

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20 Citations

Abstract: Raman spectroscopy is a promising tool for identifying microbial phenotypes based on single cell Raman spectra reflecting cellular biochemical biomolecules. Recent studies using Raman spectroscopy have mainly analyzed phenotypic changes caused by microbial interactions or stress responses (e.g., antibiotics) and evaluated the microbial activity or substrate specificity under a given experimental condition using stable isotopes. Lack of labelling and the nondestructive pretreatment and measurement process of Raman spectroscopy have also aided in the sorting of microbial cells with interesting phenotypes for subsequently conducting physiology experiments through cultivation or genome analysis. In this review, we provide an overview of the principles, advantages, and status of utilization of Raman spectroscopy for studies linking microbial phenotypes and functions. We expect Raman spectroscopy to become a next-generation phenotyping tool that will greatly contribute in enhancing our understanding of microbial functions in natural and engineered systems.

Microbial source tracking using metagenomics and other new technologies: Shahbaz Raza , Jungman Kim , Michael J. Sadowsky , Tatsuya Unno; J. Microbiol. 2021;59(3):259-269. Published online February 10, 2021; DOI: https://doi.org/10.1007/s12275-021-0668-9

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9 Citations

Abstract: The environment is under siege from a variety of pollution sources. Fecal pollution is especially harmful as it disperses pathogenic bacteria into waterways. Unraveling origins of mixed sources of fecal bacteria is difficult and microbial source tracking (MST) in complex environments is still a daunting task. Despite the challenges, the need for answers far outweighs the difficulties experienced. Advancements in qPCR and next generation sequencing (NGS) technologies have shifted the traditional culture-based MST approaches towards culture independent technologies, where communitybased MST is becoming a method of choice. Metagenomic tools may be useful to overcome some of the limitations of community-based MST methods as they can give deep insight into identifying host specific fecal markers and their association with different environments. Adoption of machine learning (ML) algorithms, along with the metagenomic based MST approaches, will also provide a statistically robust and automated platform. To compliment that, ML-based approaches provide accurate optimization of resources. With the successful application of ML based models in disease prediction, outbreak investigation and medicine prescription, it would be possible that these methods would serve as a better surrogate of traditional MST approaches in future.

Overview of bioinformatic methods for analysis of antibiotic resistome from genome and metagenome data: Kihyun Lee , Dae-Wi Kim , Chang-Jun Cha; J. Microbiol. 2021;59(3):270-280. Published online February 23, 2021; DOI: https://doi.org/10.1007/s12275-021-0652-4

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16 Citations

Abstract: Whole genome and metagenome sequencing are powerful approaches that enable comprehensive cataloging and profiling of antibiotic resistance genes at scales ranging from a single clinical isolate to ecosystems. Recent studies deal with genomic and metagenomic data sets at larger scales; therefore, designing computational workflows that provide high efficiency and accuracy is becoming more important. In this review, we summarize the computational workflows used in the research field of antibiotic resistome based on genome or metagenome sequencing. We introduce workflows, software tools, and data resources that have been successfully employed in this rapidly developing field. The workflow described in this review can be used to list the known antibiotic resistance genes from genomes and metagenomes, quantitatively profile them, and investigate the epidemiological and evolutionary contexts behind their emergence and transmission. We also discuss how novel antibiotic resistance genes can be discovered and how the association between the resistome and mobilome can be explored.

Dissection of plant microbiota and plant-microbiome interactions: Kihyuck Choi , Raees Khan , Seon-Woo Lee; J. Microbiol. 2021;59(3):281-291. Published online February 23, 2021; DOI: https://doi.org/10.1007/s12275-021-0619-5

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36 Citations

Abstract: Plants rooted in soil have intimate associations with a diverse array of soil microorganisms. While the microbial diversity of soil is enormous, the predominant bacterial phyla associated with plants include Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, and Verrucomicrobia. Plants supply nutrient niches for microbes, and microbes support plant functions such as plant growth, development, and stress tolerance. The interdependent interaction between the host plant and its microbes sculpts the plant microbiota. Plant and microbiome interactions are a good model system for understanding the traits in eukaryotic organisms from a holobiont perspective. The holobiont concept of plants, as a consequence of co-evolution of plant host and microbiota, treats plants as a discrete ecological unit assembled with their microbiota. Dissection of plant-microbiome interactions is highly complicated; however, some reductionist approaches are useful, such as the synthetic community method in a gnotobiotic system. Deciphering the interactions between plant and microbiome by this reductionist approach could lead to better elucidation of the functions of microbiota in plants. In addition, analysis of microbial communities’ interactions would further enhance our understanding of coordinated plant microbiota functions. Ultimately, better understanding of plantmicrobiome interactions could be translated to improvements in plant productivity.

Omics in gut microbiome analysis: Tae Woong Whon , Na-Ri Shin , Joon Yong Kim , Seong Woon Roh; J. Microbiol. 2021;59(3):292-297. Published online February 23, 2021; DOI: https://doi.org/10.1007/s12275-021-1004-0

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39 Citations

Abstract: Our understanding of the interactions between microbial communities and their niche in the host gut has improved owing to recent advances in environmental microbial genomics. Integration of metagenomic and metataxonomic sequencing data with other omics data to study the gut microbiome has become increasingly common, but downstream analysis after data integration and interpretation of complex omics data remain challenging. Here, we review studies that have explored the gut microbiome signature using omics approaches, including metagenomics, metataxonomics, metatranscriptomics, and metabolomics. We further discuss recent analytics programs to analyze and integrate multi-omics datasets and further utilization of omics data with other advanced techniques, such as adaptive immune receptor repertoire sequencing, microbial culturomics, and machine learning, to evaluate important microbiome characteristics in the gut.

Ammonia-oxidizing archaea in biological interactions: Jong-Geol Kim , Khaled S. Gazi , Samuel Imisi Awala , Man-Young Jung , Sung-Keun Rhee; J. Microbiol. 2021;59(3):298-310. Published online February 23, 2021; DOI: https://doi.org/10.1007/s12275-021-1005-z

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18 Citations

Abstract: The third domain Archaea was known to thrive in extreme or anoxic environments based on cultivation studies. Recent metagenomics- based approaches revealed a widespread abundance of archaea, including ammonia-oxidizing archaea (AOA) of Thaumarchaeota in non-extreme and oxic environments. AOA alter nitrogen species availability by mediating the first step of chemolithoautotrophic nitrification, ammonia oxidation to nitrite, and are important primary producers in ecosystems, which affects the distribution and activity of other organisms in ecosystems. Thus, information on the interactions of AOA with other cohabiting organisms is a crucial element in understanding nitrogen and carbon cycles in ecosystems as well as the functioning of whole ecosystems. AOA are self-nourishing, and thus interactions of AOA with other organisms can often be indirect and broad. Besides, there are possibilities of specific and obligate interactions. Mechanisms of interaction are often not clearly identified but only inferred due to limited knowledge on the interaction factors analyzed by current technologies. Here, we overviewed different types of AOA interactions with other cohabiting organisms, which contribute to understanding AOA functions in ecosystems.

Metaviromics coupled with phage-host identification to open the viral ‘black box’: Kira Moon , Jang-Cheon Cho; J. Microbiol. 2021;59(3):311-323. Published online February 23, 2021; DOI: https://doi.org/10.1007/s12275-021-1016-9

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10 Citations

Abstract: Viruses are found in almost all biomes on Earth, with bacteriophages (phages) accounting for the majority of viral particles in most ecosystems. Phages have been isolated from natural environments using the plaque assay and liquid medium- based dilution culturing. However, phage cultivation is restricted by the current limitations in the number of culturable bacterial strains. Unlike prokaryotes, which possess universally conserved 16S rRNA genes, phages lack universal marker genes for viral taxonomy, thus restricting cultureindependent analyses of viral diversity. To circumvent these limitations, shotgun viral metagenome sequencing (i.e., metaviromics) has been developed to enable the extensive sequencing of a variety of viral particles present in the environment and is now widely used. Using metaviromics, numerous studies on viral communities have been conducted in oceans, lakes, rivers, and soils, resulting in many novel phage sequences. Furthermore, auxiliary metabolic genes such as ammonic monooxygenase C and β-lactamase have been discovered in viral contigs assembled from viral metagenomes. Current attempts to identify putative bacterial hosts of viral metagenome sequences based on sequence homology have been limited due to viral sequence variations. Therefore, culture- independent approaches have been developed to predict bacterial hosts using single-cell genomics and fluorescentlabeling. This review focuses on recent viral metagenome studies conducted in natural environments, especially in aquatic ecosystems, and their contributions to phage ecology. Here, we concluded that although metaviromics is a key tool for the study of viral ecology, this approach must be supplemented with phage-host identification, which in turn requires the cultivation of phage-bacteria systems.

Minor and major circRNAs in virus and host genomes: Zhihao Lou , Rui Zhou , Yinghua Su , Chun Liu , Wenting Ruan , Che Ok Jeon , Xiao Han , Chun Lin , Baolei Jia; J. Microbiol. 2021;59(3):324-331. Published online February 23, 2021; DOI: https://doi.org/10.1007/s12275-021-1021-z

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5 Citations

Abstract: As a special type of noncoding RNA, circular RNAs (circRNAs) are prevalent in many organisms. They can serve as sponges for microRNAs and protein scaffolds, or templates for protein translation, making them linked to cellular homeostasis and disease progression. In recent years, circRNAs have been found to be abnormally expressed during the processes of viral infection and pathogenesis, and can help a virus escape the immune response of a host. Thus, they are now considered to play important functions in the invasion and development of viruses. Moreover, the potential application of circRNAs as biomarkers of viral infection or candidates for therapeutic targeting deserves consideration. This review summarizes circRNAs in the transcriptome, including their classification, production, functions, and value as biomarkers. This review paper also describes research progress on circRNAs in viral infection (mainly hepatitis B virus, HIV, and some human herpes viruses) and aims to provide new ideas for antiviral therapies targeting circRNAs.

A comprehensive review of SARS-CoV-2 genetic mutations and lessons from animal coronavirus recombination in one health perspective: Woonsung Na , Hyoungjoon Moon , Daesub Song; J. Microbiol. 2021;59(3):332-340. Published online February 23, 2021; DOI: https://doi.org/10.1007/s12275-021-0660-4

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15 Citations

Abstract: SARS-CoV-2 was originated from zoonotic coronaviruses and confirmed as a novel beta-coronavirus, which causes serious respiratory illness such as pneumonia and lung failure, COVID-19. In this review, we describe the genetic characteristics of SARS-CoV-2, including types of mutation, and molecular epidemiology, highlighting its key difference from animal coronaviruses. We further summarized the current knowledge on clinical, genetic, and pathological features of several animal coronaviruses and compared them with SARSCoV- 2, as well as recent evidences of interspecies transmission and recombination of animal coronaviruses to provide a better understanding of SARS-CoV-2 infection in One Health perspectives. We also discuss the potential wildlife hosts and zoonotic origin of this emerging virus in detail, that may help mitigate the spread and damages caused by the disease.

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