• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.167-172
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• 2012

In biology the advent of the high-throughput technology for sequencing, probing, or screening has produced huge volume of data which could not be manually handled. Biologists have resorted to software tools in order to effectively handle them. This paper introduces a bioinformatics tool to help biologists find potentially interesting pathway maps from a transcriptome data set in which the expression levels of genes are described for both case and control samples. The tool accepts a transcriptome data set, and then selects and categorizes some of genes into four classes using a fuzzy filtering technique where classes are defined by membership functions. It collects and edits the pathway maps related to those selected genes without analyst' intervention. It invokes a sequence of web service functions from KEGG, which an online pathway database system, in order to retrieve related information, locate pathway maps, and manipulate them. It maintains all retrieved pathway maps in a local database and presents them to the analysts with graphical user interface. The tool has been successfully used in identifying target genes for further analysis in transcriptome study of human cytomegalovirous. The tool is very helpful in that it can considerably save analysts' time and efforts by collecting and presenting the pathway maps that contain some interesting genes, once a transcriptome data set is just given.

• Genomics & Informatics
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• v.11 no.4
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• pp.174-179
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• 2013

The large amount of data on cancer genome research has contributed to our understanding of cancer biology. Indeed, the genomics approach has a strong advantage for analyzing multi-factorial and complicated problems, such as cancer. It is time to think about the actual usage of cancer genomics in the clinical field. The clinical cancer field has lots of unmet needs in the management of cancer patients, which has been defined in the pre-genomic era. Unmet clinical needs are not well known to bioinformaticians and even non-clinician cancer scientists. A personalized approach in the clinical field will bring potential additional challenges to cancer genomics, because most data to now have been population-based rather than individualbased. We can maximize the use of cancer genomics in the clinical field if cancer scientists, bioinformaticians, and clinicians think and work together in solving unmet clinical needs. In this review, we present one imaginary case of a cancer patient, with which we can think about unmet clinical needs to solve with cancer genomics in the diagnosis, prediction of prognosis, monitoring the status of cancer, and personalized treatment decision.

• Journal of Microbiology and Biotechnology
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• v.22 no.2
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• pp.159-165
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• 2012

The rhizobacterial composition varies according to the soil properties. To test if the effect of herbicides on the rhizobacterial communities of genetically modified NK603 glyphosate-tolerant maize varies according to different soil locations, a comparison was made between the effects of glyphosate (Roundup Plus), a post-emergence applied herbicide, and a pre-emergence applied herbicide (GTZ) versus untreated soil. The potential effect was monitored by direct amplification, cloning, and sequencing of the soil DNA encoding 16S rRNA, and high-throughput DNA pyrosequencing of the bacterial DNA coding for the 16S rRNA hypervariable V6 region. The results obtained using three different methods to analyze the herbicide effect on the rhizobacterial communities of genetically modified NK603 maize were comparable to those previously obtained when glyphosate-tolerant maize was grown in soil with different characteristics. Both herbicides decreased the bacterial diversity in the rhizosphere, with Actinobacteria being the taxonomic group most affected. The results suggest that both herbicides affected the structure of the maize rhizobacterial community, but glyphosate was environmentally less aggressive.

• Journal of Microbiology
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• v.43 no.5
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• pp.411-416
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• 2005

The high-throughput sequencing of microbial genomes has resulted in the relatively rapid accumulation of an enormous amount of genomic sequence data. In this context, the problem posed by the detection of promoters in genomic DNA sequences via computational methods has attracted considerable research attention in recent years. This paper addresses the development of a predictive model, known as the dependence decomposition weight matrix model (DDWMM), which was designed to detect the core promoter region, including the -10 region and the transcription start sites (TSSs), in prokaryotic genomic DNA sequences. This is an issue of some importance with regard to genome annotation efforts. Our predictive model captures the most significant dependencies between positions (allowing for non­adjacent as well as adjacent dependencies) via the maximal dependence decomposition (MDD) procedure, which iteratively decomposes data sets into subsets, based on the significant dependence between positions in the promoter region to be modeled. Such dependencies may be intimately related to biological and structural concerns, since promoter elements are present in a variety of combinations, which are separated by various distances. In this respect, the DDWMM may prove to be appropriate with regard to the detection of core promoter regions and TSSs in long microbial genomic contigs. In order to demonstrate the effectiveness of our predictive model, we applied 10-fold cross-validation experiments on the 607 experimentally-verified promoter sequences, which evidenced good performance in terms of sensitivity.

• Journal of Microbiology and Biotechnology
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• v.31 no.7
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• pp.978-989
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• 2021

Allyl isothiocyanate (AITC), as a fumigant, plays an important role in soil control of nematodes, soil-borne pathogens, and weeds, but its effects on soil microorganisms are unclear. In this study, the effects of AITC on microbial diversity and community composition of Capsicum annuum L. soil were investigated through Illumina high-throughput sequencing. The results showed that microbial diversity and community structure were significantly influenced by AITC. AITC reduced the diversity of soil bacteria, stimulated the diversity of the soil fungal community, and significantly changed the structure of fungal community. AITC decreased the relative abundance of dominant bacteria Planctomycetes, Acinetobacter, Pseudodeganella, and RB41, but increased that of Lysobacter, Sphingomonas, Pseudomonas, Luteimonas, Pseudoxanthomonas, and Bacillus at the genera level, while for fungi, Trichoderma, Neurospora, and Lasiodiplodia decreased significantly and Aspergillus, Cladosporium, Fusarium, Penicillium, and Saccharomyces were higher than the control. The correlation analysis suggested cellulase had a significant correlation with fungal operational taxonomic units and there was a significant correlation between cellulase and fungal diversity, while catalase, cellulose, sucrase, and urease were the major contributors in the shift of the community structure. Our results will provide useful information for the use of AITC in the assessment of environmental and ecological security.

• Journal of Environmental Science International
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• v.30 no.12
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• pp.1093-1100
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• 2021

The present study investigated the effect of ammonia load on microbial communities in mesophilic anaerobic digestion of propionic acid. A laboratory-scale continuous anaerobic digester treating propionic acid as a sole organic substrate was operated under non-inhibitory condition and inhibitory conditions with ammonia (1.5 g and 3.5 g ammonia-N/L, respectively), and bacterial and archaeal communities in the steady states of each ammonia condition were analyzed using high-throughput sequencing. Thirteen bacterial families were detected as abundant bacterial groups in mesophilic anaerobic digestion of propionic acid. Increase in ammonia concentration resulted in significant shifts in microbial community structures. Syntorophobacter, Pelotomaculum, and Thermovigra were determined as the dominant groups of (potential) propionate oxidizing bacteria in the non-inhibitory condition, whereas Cryptanaerobacter and Aminobacterium were the dominant groups of (potential) propionate oxidizing bacteria in the ammonia-inhibitory condition. Methanoculleus and Methanosaeta were the dominant methanogens. Acetate-oxidation coupled with hydrogenotrophic methanogenesis might be enhanced with increases in the relative abundances of Methanoculleus and Tepidanaerobacter acetatoxydans under the ammonia-inhibitory condition. The results of the present study could be a valuable reference for microbial management of anaerobic digestion systems that are exposed to ammonia inhibition and propionic acid accumulation.

• The Korean Journal of Physiology and Pharmacology
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• v.25 no.4
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• pp.261-272
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• 2021

Doxorubicin (Dox) is widely used to the treatment of cancer, however, it could cause damage to gastric mucosa. To investigate the protective effects and related mechanisms of coenzyme Q10 (CoQ10) and vitamin C (VC) on Dox-induced gastric mucosal injury, we presented the survey of the 4 groups of the rats with different conditions. The results showed Dox treatment significantly induced GES-1 apoptosis, but preconditioning in GES-1 cells with VC or CoQ10 significantly inhibited the Dox-induced decrease and other harm effects, including the expression and of IκKβ, IκBα, NF-κB/p65 and tumor necrosis factor (TNF-α) in GES-1 cells. Moreover, high-throughput sequencing results showed Dox treatment increased the number of harmful gut microbes, and CoQ10 and VC treatment inhibited this effect. CoQ10 and VC treatment inhibits Dox-induced gastric mucosal injury by inhibiting the activation of the IkKB/IκBα/NF-κB/p65/TNF-α pathway, promoting anti-inflammatory effects of gastric tissue and regulating the composition of the intestinal flora.

• Mycobiology
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• v.50 no.1
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• pp.55-65
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• 2022

Lichen is a symbiotic mutualism of mycobiont and photobiont that harbors diverse organisms including endolichenic fungi (ELF). Despite the taxonomic and ecological significance of ELF, no comparative investigation of an ELF community involving isolation of a pure culture and high-throughput sequencing has been conducted. Thus, we analyzed the ELF community in Parmotrema tinctorum by culture and metabarcoding. Alpha diversity of the ELF community was notably greater in metabarcoding than in culture-based analysis. Taxonomic proportions of the ELF community estimated by metabarcoding and by culture analyses showed remarkable differences: Sordariomycetes was the most dominant fungal class in culture-based analysis, while Dothideomycetes was the most abundant in metabarcoding analysis. Thirty-seven operational taxonomic units (OTUs) were commonly observed by culture-and metabarcoding-based analyses but relative abundances differed: most of common OTUs were underrepresented in metabarcoding. The ELF community differed in lichen segments and thalli in metabarcoding analysis. Dissimilarity of ELF community intra lichen thallus increased with thallus segment distance; inter-thallus ELF community dissimilarity was significantly greater than intra-thallus ELF community dissimilarity. Finally, we tested how many fungal sequence reads would be needed to ELF diversity with relationship assays between numbers of lichen segments and saturation patterns of OTU richness and sample coverage. At least 6000 sequence reads per lichen thallus were sufficient for prediction of overall ELF community diversity and 50,000 reads per thallus were enough to observe rare taxa of ELF.

• Mass Spectrometry Letters
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• v.13 no.4
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• pp.106-114
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• 2022

A rapid and reliable approach to the identification of microorganisms is a critical requirement for large-scale culturomics analysis. MALDI-TOF MS is a suitable technique that can be a better alternative to conventional biochemical and gene sequencing methods as it is economical both in terms of cost and labor. In this review, the applications of MALDI-TOF MS for the comprehensive identification of microorganisms and bacterial strain typing for culturomics-based approaches for various environmental studies including bioremediation, plant sciences, agriculture and food microbiology have been widely explored. However, the restriction of this technique is attributed to insufficient coverage of the mass spectral database. To improve the applications of this technique for the identification of novel isolates, the spectral database should be updated with the peptide mass fingerprint (PMF) of type strains with not only microbes with clinical relevance but also from various environmental sources. Further, the development of enhanced sample processing methods and new algorithms for automation and de-replication of isolates will increase its application in microbial ecology studies.

• Journal of Genetic Medicine
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• v.19 no.1
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• pp.27-31
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• 2022

X-linked dominant hypophosphatemic rickets are the most common form of familial hypophosphatemic rickets resulting from hypophosphatemia caused by renal phosphate wasting, which in turn is a result of loss-of-function mutations in PHEX. Herein, we report a 39-year-old female with short stature and skeletal deformities and 12-month-old asymptomatic daughter. The female has a history of multiple surgical treatments because of lower limb deformities. Her biochemical findings revealed low serum phosphorus levels with elevated serum alkaline phosphatase activity and normal serum calcium levels, suggesting presence of hypophosphatemic rickets. To identify the molecular causes, we used a multigene testing panel and found a mutation, c.667dup (p.Asp223GlyfsTer15), in PHEX gene. To the best of our knowledge, this is a novel mutation. A heterozygous form of the same variant was detected in daughter, who showed no typical symptoms such as bow legs, frontal bossing, or waddling gate, but presented early signs of impaired mineralization in both X-ray and biochemical findings. The daughter was initiated onto early medical treatment with oral phosphate supplementation and an active vitamin D analog. Because the daughter was genetically diagnosed based on a family history before the onset of symptoms, appropriate medical management was possible from early infancy.