• Genomics & Informatics
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• v.11 no.3
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• pp.102-113
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• 2013

Metagenomics has become one of the indispensable tools in microbial ecology for the last few decades, and a new revolution in metagenomic studies is now about to begin, with the help of recent advances of sequencing techniques. The massive data production and substantial cost reduction in next-generation sequencing have led to the rapid growth of metagenomic research both quantitatively and qualitatively. It is evident that metagenomics will be a standard tool for studying the diversity and function of microbes in the near future, as fingerprinting methods did previously. As the speed of data accumulation is accelerating, bioinformatic tools and associated databases for handling those datasets have become more urgent and necessary. To facilitate the bioinformatics analysis of metagenomic data, we review some recent tools and databases that are used widely in this field and give insights into the current challenges and future of metagenomics from a bioinformatics perspective.

• Genomics & Informatics
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• v.21 no.4
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• pp.49.1-49.11
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• 2023

Recent advances in sequencing technologies and platforms have enabled to generate metagenomics sequences using different sequencing platforms. In this study, we analyzed and compared shotgun metagenomic sequences generated by HiSeq3000 and BGISEQ-500 platforms from 12 sediment samples collected across the Norwegian coast. Metagenomics DNA sequences were normalized to an equal number of bases for both platforms and further evaluated by using different taxonomic classifiers, reference databases, and assemblers. Normalized BGISEQ-500 sequences retained more reads and base counts after preprocessing, while a slightly higher fraction of HiSeq3000 sequences were taxonomically classified. Kaiju classified a higher percentage of reads relative to Kraken2 for both platforms, and comparison of reference database for taxonomic classification showed that MAR database outperformed RefSeq. Assembly using MEGAHIT produced longer assemblies and higher total contigs count in majority of HiSeq3000 samples than using metaSPAdes, but the assembly statistics notably improved with unprocessed or normalized reads. Our results indicate that both platforms perform comparably in terms of the percentage of taxonomically classified reads and assembled contig statistics for metagenomics samples. This study provides valuable insights for researchers in selecting an appropriate sequencing platform and bioinformatics pipeline for their metagenomics studies.

• Journal of Periodontal and Implant Science
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• v.52 no.4
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• pp.282-297
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• 2022

Purpose: To explore differences in the subgingival microbiome according to the presence of periodontitis and/or type 2 diabetes mellitus (T2D), a metagenomic sequencing analysis of the subgingival microbiome was performed. Methods: Twelve participants were divided into 4 groups based on their health conditions (periodontitis, T2D, T2D complicated with periodontitis, and generally healthy). Subgingival plaque was collected for metagenomic sequencing, and gingival crevicular fluids were collected to analyze the concentrations of short-chain fatty acids. Results: The shifts in the subgingival flora from the healthy to periodontitis states were less prominent in T2D subjects than in subjects without T2D. The pentose and glucuronate interconversion, fructose and mannose metabolism, and galactose metabolism pathways were enriched in the periodontitis state, while the phosphotransferase system, lipopolysaccharide (LPS) and peptidoglycan biosynthesis, bacterial secretion system, sulfur metabolism, and glycolysis pathways were enriched in the T2D state. Multiple genes whose expression was upregulated from the red and orange complex bacterial genomes were associated with bacterial biofilm formation and pathogenicity. The concentrations of propionic acid and butyric acid were significantly higher in subjects with periodontitis, with or without T2D, than in healthy subjects. Conclusions: T2D patients are more susceptible to the presence of periodontal pathogens and have a higher risk of developing periodontitis. The pentose and glucuronate interconversion, fructose and mannose metabolism, galactose metabolism, and glycolysis pathways may represent the potential microbial functional association between periodontitis and T2D, and butyric acid may play an important role in the interaction between these 2 diseases. The enrichment of the LPS and peptidoglycan biosynthesis, bacterial secretion system, and sulfur metabolism pathways may cause T2D patients to be more susceptible to periodontitis.

• Food Science of Animal Resources
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• v.44 no.2
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• pp.390-407
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• 2024

Kuflu cheese, a popular variety of traditional Turkish mold-ripened cheeses, is characterized by its semi-hard texture and blue-green color. It is important to elucidate the microbiota of Kuflu cheese produced from raw milk to standardize and sustain its sensory properties. This study aimed to examine the bacteria, yeasts, and filamentous mold communities in Kuflu cheese using high-throughput amplicon sequencing based on 16S and ITS2 regions. Lactococcus, Streptococcus, and Staphylococcus were the most dominant bacterial genera while Bifidobacterium genus was found to be remarkably high in some Kuflu cheese samples. Penicillium genus dominated the filamentous mold biota while the yeasts with the highest relative abundances were detected as Debaryomyces, Pichia, and Candida. The genera Virgibacillus and Paraliobacillus, which were not previously reported for mold-ripened cheeses, were detected at high relative abundances in some Kuflu cheese samples. None of the genera that include important food pathogens like Salmonella, Campylobacter, Listeria were detected in the samples. This is the first experiment in which the microbiota of Kuflu cheeses were evaluated with a metagenomic approach. This study provided an opportunity to evaluate Kuflu cheese, which was previously examined for fungal composition, in terms of both pathogenic and beneficial bacteria.

• Environmental Engineering Research
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• v.12 no.5
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• pp.231-237
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• 2007

The microbial eco-physiology has been the vital key of microbial ecological research. Unfortunately, available methods for direct identity of microorganisms and for the investigation of their activity in complicated community dynamics are limited. In this study, metagenomics was considered as a promising functional genomics tool for improving our understanding of microbial eco-physiology. Its potential applications and challenges were also reviewed. Because of tremendous diversity in microbial populations in environment, sequence analysis for whole metagenomic libraries from environmental samples seems to be unrealistic to most of environmental engineering researchers. When a target function is of interest, however, sequence analysis for whole metagenomic libraries would not be necessary. For this case, nucleic acids of active populations of interest can be selectively gained using another cutting-edge functional genomic tool, SIP (stable isotope probing) technique. If functional genomes isolated by SIP can be transferred into metagenomic library, sequence analysis for such selected functional genomes would be feasible because the reduced size of clone library may become adequate for sequencing analysis. Herein, integration of metagenomics with SIP was suggested as a novel functional genomics approach to study microbial eco-physiology in environment.

• Journal of Microbiology and Biotechnology
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• v.24 no.6
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• pp.812-822
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• 2014

Metagenomic analysis of the human intestinal microbiota has extended our understanding of the role of these bacteria in improving human intestinal health; however, a number of reports have shown that current total fecal DNA extraction methods and 16S rRNA universal primer sets could affect the species coverage and resolution of these analyses. Here, we improved the extraction method for total DNA from human fecal samples by optimization of the lysis buffer, boiling time (10 min), and bead-beating time (0 min). In addition, we developed a new long-range 16S rRNA universal PCR primer set targeting the V6 to V9 regions with a 580 bp DNA product length. This new 16S rRNA primer set was evaluated by comparison with two previously developed 16S rRNA universal primer sets and showed high species coverage and resolution. The optimized total fecal DNA extraction method and newly designed long-range 16S rRNA universal primer set will be useful for the highly accurate metagenomic analysis of adult and infant intestinal microbiota with minimization of any bias.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.7
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• pp.957-966
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• 2017

Objective: To understand the dynamic structure, function, and influence on nutrient metabolism in hosts, it was crucial to assess the genetic potential of gut microbial community in yaks of different ages. Methods: The denaturing gradient gel electrophoresis (DGGE) profiles and Illumina-based metagenomic sequencing on colon contents of 15 semi-domestic yaks were investigated. Unweighted pairwise grouping method with mathematical averages (UPGMA) clustering and principal component analysis (PCA) were used to analyze the DGGE fingerprint. The Illumina sequences were assembled, predicted to genes and functionally annotated, and then classified by querying protein sequences of the genes against the Kyoto encyclopedia of genes and genomes (KEGG) database. Results: Metagenomic sequencing showed that more than 85% of ribosomal RNA (rRNA) gene sequences belonged to the phylum Firmicutes and Bacteroidetes, indicating that the family Ruminococcaceae (46.5%), Rikenellaceae (11.3%), Lachnospiraceae (10.0%), and Bacteroidaceae (6.3%) were dominant gut microbes. Over 50% of non-rRNA gene sequences represented the metabolic pathways of amino acids (14.4%), proteins (12.3%), sugars (11.9%), nucleotides (6.8%), lipids (1.7%), xenobiotics (1.4%), coenzymes, and vitamins (3.6%). Gene functional classification showed that most of enzyme-coding genes were related to cellulose digestion and amino acids metabolic pathways. Conclusion: Yaks' age had a substantial effect on gut microbial composition. Comparative metagenomics of gut microbiota in 0.5-, 1.5-, and 2.5-year-old yaks revealed that the abundance of the class Clostridia, Bacteroidia, and Lentisphaeria, as well as the phylum Firmicutes, Bacteroidetes, Lentisphaerae, Tenericutes, and Cyanobacteria, varied more greatly during yaks' growth, especially in young animals (0.5 and 1.5 years old). Gut microbes, including Bacteroides, Clostridium, and Lentisphaeria, make a contribution to the energy metabolism and synthesis of amino acid, which are essential to the normal growth of yaks.

• BMB Reports
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• v.49 no.12
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• pp.662-670
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• 2016

The human oral cavity contains a highly personalized microbiome essential to maintaining health, but capable of causing oral and systemic diseases. Thus, an in-depth definition of "healthy oral microbiome" is critical to understanding variations in disease states from preclinical conditions, and disease onset through progressive states of disease. With rapid advances in DNA sequencing and analytical technologies, population-based studies have documented the range and diversity of both taxonomic compositions and functional potentials observed in the oral microbiome in healthy individuals. Besides factors specific to the host, such as age and race/ethnicity, environmental factors also appear to contribute to the variability of the healthy oral microbiome. Here, we review bioinformatic techniques for metagenomic datasets, including their strengths and limitations. In addition, we summarize the interpersonal and intrapersonal diversity of the oral microbiome, taking into consideration the recent large-scale and longitudinal studies, including the Human Microbiome Project.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.8
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• pp.1144-1151
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• 2013

In this study, protein domains with cellulase activity in goat rumen microbes were investigated using metagenomic and bioinformatic analyses. After the complete genome of goat rumen microbes was obtained using a shotgun sequencing method, 217,892,109 pair reads were filtered, including only those with 70% identity, 100-bp matches, and thresholds below $E^{-10}$ using METAIDBA. These filtered contigs were assembled and annotated using blastN against the NCBI nucleotide database. As a result, a microbial community structure with 1431 species was analyzed, among which Prevotella ruminicola 23 bacteria and Butyrivibrio proteoclasticus B316 were the dominant groups. In parallel, 201 sequences related with cellulase activities (EC.3.2.1.4) were obtained through blast searches using the enzyme.dat file provided by the NCBI database. After translating the nucleotide sequence into a protein sequence using Interproscan, 28 protein domains with cellulase activity were identified using the HMMER package with threshold E values below $10^{-5}$. Cellulase activity protein domain profiling showed that the major protein domains such as lipase GDSL, cellulase, and Glyco hydro 10 were present in bacterial species with strong cellulase activities. Furthermore, correlation plots clearly displayed the strong positive correlation between some protein domain groups, which was indicative of microbial adaption in the goat rumen based on feeding habits. This is the first metagenomic analysis of cellulase activity protein domains using bioinformatics from the goat rumen.

• Journal of Periodontal and Implant Science
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• v.52 no.5
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• pp.394-410
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• 2022

Purpose: The purpose of this study was to compare the microbial composition of 3 types of oral samples through 16S metagenomic sequencing to determine how to resolve some sampling issues that occur during the collection of sub-gingival plaque samples. Methods: In total, 20 subjects were recruited. In both the healthy and periodontitis groups, samples of saliva and supra-gingival plaque were collected. Additionally, in the periodontitis group, sub-gingival plaque samples were collected from the deepest periodontal pocket. After DNA extraction from each sample, polymerase chain reaction amplification was performed on the V3-V4 hypervariable region on the 16S rRNA gene, followed by metagenomic sequencing and a bioinformatics analysis. Results: When comparing the healthy and periodontitis groups in terms of alpha-diversity, the saliva samples demonstrated much more substantial differences in bacterial diversity than the supra-gingival plaque samples. Moreover, in a comparison between the samples in the case group, the diversity score of the saliva samples was higher than that of the supra-gingival plaque samples, and it was similar to that of the sub-gingival plaque samples. In the beta-diversity analysis, the sub-gingival plaque samples exhibited a clustering pattern similar to that of the periodontitis group. Bacterial relative abundance analysis at the species level indicated lower relative frequencies of bacteria in the healthy group than in the periodontitis group. A statistically significant difference in frequency was observed in the saliva samples for specific pathogenic species (Porphyromonas gingivalis, Treponema denticola, and Prevotella intermedia). The saliva samples exhibited a similar relative richness of bacterial communities to that of sub-gingival plaque samples. Conclusions: In this 16S oral microbiome study, we confirmed that saliva samples had a microbial composition that was more similar to that of sub-gingival plaque samples than to that of supra-gingival plaque samples within the periodontitis group.