• Food Science of Animal Resources
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• v.37 no.4
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• pp.535-541
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• 2017

This study investigated the psychrotrophic bacteria isolated from chicken meat to characterize their microbial composition during refrigerated storage. The bacterial community was identified by the Illumina MiSeq method based on bacterial DNA extracted from spoiled chicken meat. Molecular identification of the isolated psychrotrophic bacteria was carried out using 16S rDNA sequencing and their putrefactive potential was investigated by the growth at low temperature as well as their proteolytic activities in chicken meat. From the Illumina sequencing, a total of 187,671 reads were obtained from 12 chicken samples. Regardless of the type of chicken meat (i.e., whole meat and chicken breast) and storage temperatures ($4^{\circ}C$ and $10^{\circ}C$), Pseudomonas weihenstephanensis and Pseudomonas congelans were the most prominent bacterial species. Serratia spp. and Acinetobacter spp. were prominent in chicken breast and whole chicken meat, respectively. The 118 isolated strains of psychrotrophic bacteria comprised Pseudomonas spp. (58.48%), Serratia spp. (10.17%), and Morganella spp. (6.78%). All isolates grew well at $10^{\circ}C$ and they induced different proteolytic activities depending on the species and strains. Parallel analysis of the next generation sequencing and culture dependent approach provides in-depth information on the biodiversity of the spoilage microbiota in chicken meat. Further study is needed to develop better preservation methods against these spoilage bacteria.

• Journal of Microbiology and Biotechnology
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• v.28 no.8
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• pp.1318-1331
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• 2018

Lettuce (Lactuca sativa L.) is a major ingredient used in many food recipes in South Korea. Lettuce samples were collected during their maximum production period between April and July in order to investigate the microbiota of lettuce during different seasons. 16S rRNA gene-based sequencing was conducted using Illumina MiSeq, and real-time PCR was performed for quantification. The number of total bacterial was greater in lettuce collected in July than in that collected in April, albeit with reduced diversity. The bacterial compositions varied according to the site and season of sample collection. Potential pathogenic species such as Bacillus spp., Enterococcus casseliflavus, Klebsiella pneumoniae, and Pseudomonas aeruginosa showed season-specific differences. Results of the network co-occurrence analysis with core genera correlations showed characteristics of bacterial species in lettuce, and provided clues regarding the role of different microbes, including potential pathogens, in this microbiota. Although further studies are needed to determine the specific effects of regional and seasonal characteristics on the lettuce microbiota, our results imply that the 16S rRNA gene-based sequencing approach can be used to detect pathogenic bacteria in lettuce.

• Journal of Microbiology and Biotechnology
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• v.28 no.8
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• pp.1247-1259
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• 2018

Raspberries are polyphenol-rich fruits with the potential to reduce the severity of the clinical signs associated with obesity, a phenomenon that may be related to changes in the gut microbiota. The aim of this study was to investigate the effect of raspberry supplementation on the fecal microbiota using an in vivo model of obesity. Obese diabetic db/db mice were used in this study and assigned to two experimental groups (with and without raspberry supplementation). Fecal samples were collected at the end of the supplementation period (8 weeks) and used for bacterial 16S rRNA gene profiling using a MiSeq instrument (Illumina). QIIME 1.8 was used to analyze the 16S data. Raspberry supplementation was associated with an increased abundance of Lachnospiraceae (p = 0.009), a very important group for gut health, and decreased abundances of Lactobacillus, Odoribacter, and the fiber degrader S24-7 family as well as unknown groups of Bacteroidales and Enterobacteriaceae (p < 0.05). These changes were enough to clearly differentiate bacterial communities accordingly to treatment, based on the analysis of UniFrac distance metrics. However, a predictive approach of functional profiles showed no difference between the treatment groups. Fecal metabolomic analysis provided critical information regarding the raspberry-supplemented group, whose relatively higher phytosterol concentrations may be relevant for the host health, considering the proven health benefits of these phytochemicals. Further studies are needed to investigate whether the observed differences in microbial communities (e.g., Lachnospiraceae) or metabolites relate to clinically significant differences that can prompt the use of raspberry extracts to help patients with obesity.

• Journal of Microbiology and Biotechnology
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• v.30 no.11
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• pp.1697-1705
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• 2020

Meju, a type of fermented soybean paste, is used as a starter in the preparation of various Korean traditional soybean-based foods. In this study, we performed Illumina-MiSeq paired-end sequencing for microbial communities and mass spectrometry analysis for metabolite profiling to investigate the differences between 11 traditional meju products from different regions across Korea. Even though the bacterial and fungal communities showed remarkable variety, major genera including Bacillus, Enterococcus, Variovorax, Pediococcus, Weissella, and Aspergillus were detected in every sample of meju. The metabolite profile patterns of the 11 samples were clustered into two main groups: group I (M1-5) and group II (M6-11). The metabolite analysis indicated a relatively higher amino acid content in group I, while group II exhibited higher isoflavone, soyasaponin, and lysophospholipid contents. The bioactivity analysis proved that the ABTS (2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid)) radical-scavenging activity was higher in group II and the FRAP (ferric reducing antioxidant power) activity was higher in group I. The correlation analysis revealed that the ABTS activity was isoflavonoid, lipid, and soyasaponin related, whereas the FRAP activity was amino acid and flavonoid related. These results suggest that the antioxidant activities of meju are critically influenced by the microbiome and metabolite dynamics.

• Journal of Microbiology and Biotechnology
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• v.30 no.11
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• pp.1688-1696
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• 2020

Soil physical and chemical characteristics, soil potential denitrification rates (PDR), community composition and nirK-, nirS- and nosZ-encoding denitrifiers were studied by using MiSeq sequencing, quantitative polymerase chain reaction (qPCR), and terminal restriction fragment polymorphism (T-RFLP) technologies base on short-term (5-year) tillage field experiment. The experiment included four tillage treatments: conventional tillage with crop residue incorporation (CT), rotary tillage with crop residue incorporation (RT), no-tillage with crop residue retention (NT), and rotary tillage with crop residue removed as control (RTO). The results indicated that soil organic carbon, total nitrogen and NH₄⁺-N contents were increased with CT, RT and NT treatments. Compared with RTO treatment, the copies number of nirK, nirS and nosZ in paddy soil with CT, RT and NT treatments were significantly increased. The principal coordinate analysis indicated that tillage management and crop residue returning management were the most and the second important factors for the change of denitrifying bacteria community, respectively. Meanwhile, this study indicated that activity and community composition of denitrifiers with CT, RT and NT treatments were increased, compared with RTO treatment. This result showed that nirK, nirS and nosZ-type denitrifiers communities in crop residue applied soil had higher species diversity compared with crop residue removed soil, and denitrifying bacteria community composition were dominated by Gammaproteobacteria, Deltaproteobacteria, and Betaproteobacteria. Therefore, it is a beneficial practice to increase soil PDR level, abundance and community composition of nitrogen-functional soil microorganism by combined application of tillage with crop residue management.

• Genomics & Informatics
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• v.13 no.3
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• pp.81-85
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• 2015

Molecular characterization technology in genetically modified organisms, in addition to how transgenic biotechnologies are developed now require full transparency to assess the risk to living modified and non-modified organisms. Next generation sequencing (NGS) methodology is suggested as an effective means in genome characterization and detection of transgenic insertion locations. In the present study, we applied NGS to insert transgenic loci, specifically the epidermal growth factor (EGF) in genetically modified rice cells. A total of 29.3 Gb (${\sim}72{\times}coverage$) was sequenced with a $2{\times}150bp$ paired end method by Illumina HiSeq2500, which was consecutively mapped to the rice genome and T-vector sequence. The compatible pairs of reads were successfully mapped to 10 loci on the rice chromosome and vector sequences were validated to the insertion location by polymerase chain reaction (PCR) amplification. The EGF transgenic site was confirmed only on chromosome 4 by PCR. Results of this study demonstrated the success of NGS data to characterize the rice genome. Bioinformatics analyses must be developed in association with NGS data to identify highly accurate transgenic sites.

• Journal of Microbiology and Biotechnology
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• v.30 no.9
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• pp.1355-1366
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• 2020

Sediment bacterial communities are critical to the biogeochemical cycle in river ecosystems, but our understanding of the relationship between sediment bacterial communities and their specific input streams in rivers remains insufficient. In this study, we analyzed the sediment bacterial community structure in a local river receiving discharge of urban domestic sewage by applying Illumina MiSeq high-throughput sequencing. The results showed that the bacterial communities of sediments samples of different pollution types had similar dominant phyla, mainly Proteobacteria, Actinobacteria, Chloroflexi and Firmicutes, but their relative abundances were different. Moreover, there were great differences at the genus level. For example, the genus Bacillus showed statistically significant differences in the hotel site. The clustering of bacterial communities at various sites and the dominant families (i.e., Nocardioidaceae, and Sphingomonadaceae) observed in the residential quarter differed from other sites. This result suggested that environmentally induced species sorting greatly influenced the sediment bacterial community composition. The bacterial co-occurrence patterns showed that the river bacteria had a nonrandom modular structure. Microbial taxonomy from the same module had strong ecological links (such as the nitrogenium cycle and degradation of organic pollutants). Additionally, PICRUSt metabolic inference analysis showed the most important function of river bacterial communities under the influence of different types of domestic sewage was metabolism (e.g., genes related to xenobiotic degradation predominated in residential quarter samples). In general, our results emphasize that the adaptive changes and interactions in the bacterial community structure of river sediment represent responses to different exogenous pollution sources.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.1-7
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• 2019

Recently, various approaches to detect network attacks using machine learning have been studied and are being applied to detect new attacks and to increase precision. However, the machine learning method is dependent on feature extraction and takes a long time and complexity. It also has limitation of performace due to learning data imbalance. In this study, we propose a method to solve the degradation of classification performance due to imbalance of learning data among the limit points of detection system. To do this, we generate data using Generative Adversarial Networks (GANs) and propose a classification method using Convolutional Neural Networks (CNNs). Through this approach, we can confirm that the accuracy is improved when applied to the NSL-KDD and UNSW-NB15 datasets.

• Journal of Veterinary Science
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• v.22 no.3
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• pp.37.1-37.14
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• 2021

Background: Ticks are one of the most common external parasites in dogs, and are associated with the transmission of a number of major zoonoses, which result in serious harm to human health and even death. Also, the increasing number of pet dogs and pet owners in China has caused concern regarding human tick-borne illnesses. Accordingly, studies are needed to gain a complete understanding of the bacterial composition and diversity of the ticks that parasitize dogs. Objectives: To date, there have been relatively few reports on the analysis of the bacterial community structure and diversity in ticks that parasitize dogs. The objective of this study was to investigate the microbial composition and diversity of parasitic ticks of dogs, and assessed the effect of tick sex and geographical region on the bacterial composition in two tick genera collected from dogs in China. Methods: A total of 178 whole ticks were subjected to a 16S ribosomal RNA (rRNA) next generation sequencing analysis. The Illumina MiSeq platform targeting the V3-V4 region of the 16S rRNA gene was used to characterize the bacterial communities of the collected ticks. Sequence analysis and taxonomic assignment were performed using QIIME 2 and the GreenGene database, respectively. After clustering the sequences into taxonomic units, the sequences were quality-filtered and rarefied. Results: After pooling 24 tick samples, we identified a total of 2,081 operational taxonomic units, which were assigned to 23 phyla and 328 genera, revealing a diverse bacterial community profile. The high, moderate and low prevalent taxa include 46, 101, and 182 genera, respectively. Among them, dominant taxa include environmental bacterial genera, such as Psychrobacter and Burkholderia. Additionally, some known tick-associated endosymbionts were also detected, including Coxiella, Rickettsia, and Ricketssiella. Also, the potentially pathogenic genera Staphylococcus and Pseudomonas were detected in the tick pools. Moreover, our preliminary study found that the differences in microbial communities are more dependent on the sampling location than tick sex in the tick specimens collected from dogs. Conclusions: The findings of this study support the need for future research on the microbial population present in ticks collected from dogs in China.

• Journal of Microbiology and Biotechnology
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• v.29 no.9
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• pp.1391-1400
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• 2019

Canine parvoviral enteritis (PVE) is an important intestinal disease of the puppies; however, the potential impact of the canine parvovirus (CPV) on the gut microbiota has not been investigated. Therefore, the aim of this study was to evaluate the gut microbial shifts in puppies naturally infected with CPV. Fecal samples were collected from healthy dogs and those diagnosed with PVE at 4, 6, 8, and 12 weeks of age. The distal gut microbiota of dogs was characterized using Illumina MiSeq sequencing of the bacterial 16S rRNA genes. The sequence data were analyzed using QIIME with an Operational Taxonomic Unit definition at a similarity cutoff of 97%. Our results showed that the CPV was associated with significant microbial dysbiosis of the intestinal microbiota. Alpha diversity and species richness and evenness in dogs with PVE decreased compared to those of healthy dogs. At the phylum level, the proportion of Proteobacteria was significantly enriched in dogs with PVE while Bacteroidetes was significantly more abundant in healthy dogs (p < 0.05). In dogs with PVE, Enterobacteriaceae was the most abundant bacterial family accounting for 36.44% of the total bacterial population compared to only 0.21% in healthy puppies. The two most abundant genera in healthy dogs were Prevotella and Lactobacillus and their abundance was significantly higher compared to that of dogs with PVE (p < 0.05). These observations suggest that disturbances of gut microbial communities were associated with PVE in young dogs. Evaluation of the roles of these bacterial groups in the pathophysiology of PVE warrants further studies.