17 research outputs found

    ์ „๊ธฐ ์˜๋™์— ์˜ํ•œ Leishmania major์˜ ๋‹จ๋ฐฑ์งˆ ์„ฑ๋ถ„ ๋ถ„์„

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜ํ•™๊ณผ ๊ธฐ์ƒ์ถฉํ•™์ „๊ณต,1995.Maste

    Flowcytometric quantification of toxoplasma gondii tachyzoite infection in mice and in vitro lymphocyte cultures

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜ํ•™๊ณผ ๊ธฐ์ƒ์ถฉํ•™์ „๊ณต,2001.Docto

    ๋น„๋งŒ์ด ์œ ๋„๋œ ์ƒ์ฅ์—์„œ ์œ ์‚ฐ๊ท ์˜ ๊ฒฝ๊ตฌํˆฌ์—ฌ๊ฐ€ ๋ฏธ์น˜๋Š” ํ•ญ ๋น„๋งŒํšจ๊ณผ์™€ ์žฅ๋‚ด ์„ธ๊ท ์ด์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) --์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ƒ๋ช…๊ณผํ•™๋ถ€,2008.2.Maste

    ๊ธฐ์ฃผ ๋ฉด์—ญ์„ ์กฐ์ ˆํ•˜๋Š” ๋ฒผ ๋„์—ด๋ณ‘๊ท ์˜ ํ•ต ์ดํŽ™ํ„ฐ ๊ธฐ๋Šฅ ๊ตฌ๋ช…

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋†์—…์ƒ๋ช…๊ณผํ•™๋Œ€ํ•™ ๋†์ƒ๋ช…๊ณตํ•™๋ถ€, 2021. 2. ์ด์šฉํ™˜.Plant pathogens threat human being for devastating crop loss in worldwide. Two-layered plant immune systems, PAMP- and effector-triggered immunity, eliminate most of invaders. Despite of robust immune systems of plants, compatible pathogen effectors neutralize hostile environment during infection via versatile strategies. Spatial compartments emerged during the plant infection classify the effectors such as apoplastic effector and cytoplasmic effector. Translocated cytoplasmic effectors move to specific organelles and modify immune responses. A group of effectors located in host nuclei are classified as nuclear effector, facilitating efficient colonization of plant tissues. Numerous nuclear effectors are discovered in bacterial and oomycete pathogens, and some of them target the same immune responses in terms of biological processes such as transcriptional regulation, hormonal signaling, programmed cell death. However, functional mechanism of fungal nuclear effectors remains to be revealed. Magnaporthe oryze, rice blast pathogen, causes serious yield loss for rice production. Rice-M. oryzae pathosystem is used for model of plant-microbe interaction owing to plenty of genome/transcriptome information and robustness of experimental system. M. oryzae penetrates rice cell wall using appressoria, and invaginates plant plasma membrane using invasive hyphae. Apoplastic effectors are secreted into extracellular matrix, interfering host defense responses. Cytoplasmic effectors are translocated via a specialized secretory structure, biotrophic interfacial complex (BIC), and moved to cellular organelles. In this study, two nuclear effectors of rice blast fungus named as MoHTR1 and MoHTR2 are characterized. Both nuclear effectors are translocated via BIC, and transferred into the nuclei of initially penetrated and surrounding cells. Theses effectors bind effector binding elements in target gene promoters and reprogram the expression of immunity-associated genes in rice. Transgenic rice expressing each MoHTR showed ambivalent response to pathogens with different lifestyles: increased susceptibility to M. oryzae and Xanthomonas oryzae pv. oryzae, hemibiotrophic pathogens, but enhanced resistance to Cochliobolus miyabeanus, a necrotrophic pathogen. The opposite effect of the transcriptional reprogramming by these effectors on defense against hemibiotrophic pathogen vs. necrotrophic pathogens, a phenomenon defined as ambivalent immunity, suggest that they target genes and processes involved in defense against all types of pathogens, not just M. oryzae. Findings in this study help understanding functional role of DNA-targeting nuclear effectors in fungal pathogen, and solve the question underlying how pathogens manipulate plant immunity.CHAPTER I. Nuclear effectors of plant pathogens Crop plants provides essential foods to mankind, but numerous plant pathogens destroy substantial amount of the products worldwide. Among the microbial pathogens, bacteria, oomycete, and fungi are major causal agent. They invade different strategies according to their lifestyle such as biotrophy, necrotrophy, and hemibiotrophy. Host plants protect themselves via two-layered immune systems. PAMP- and effector-triggered immunity efficiently block the offense of the pathogens, but compatible pathogens evade the immune systems using effectors. Effectors, molecular weapons of pathogens, are secreted and change the infection environment. According to the effector localization, they classified as apoplastic effectors and cytoplasmic effectors. Some effectors are transferred to host nuclei, essential organelle for immunity regulation, interrupting host defense responses. This type of effectors is called nuclear effector, and several effectors are discovered in the bacteria, oomycete, and fungi. In this review, nuclear effectors that have been discovered in the plant microbial pathogens are described. How these effectors modulate plant immunity is also highlighted in terms of biological processes and molecular functions.CHAPTER II. Two nuclear effectors of the rice blast fungus modulate host immunity via transcriptional reprogramming Pathogens utilize multiple types of effectors to modulate plant immunity. Although many apoplastic and cytoplasmic effectors have been reported, nuclear effectors have not been well characterized in fungal pathogens. Here, two nuclear effectors are characterized in the rice blast pathogen Magnaporthe oryzae. Both nuclear effectors are secreted via the biotrophic interfacial complex, translocated into the nuclei of initially penetrated and surrounding cells, and reprogram the expression of immunity-associated genes by binding on effector binding elements in rice. Their expression in transgenic rice caused ambivalent immunity: increased susceptibility to M. oryzae and Xanthomonas oryzae pv. oryzae, hemibiotrophic pathogens, but enhanced resistance to Cochliobolus miyabeanus, a necrotrophic pathogen. Findings in this study help remedy a significant knowledge deficiency in the mechanism of M. oryzae-rice interactions and underscore how effector-mediated manipulation of plant immunity by one pathogen may also affect the disease severity by other pathogens.์‹๋ฌผ ๋ณ‘์›์ฒด๋Š” ์ „์„ธ๊ณ„ ๊ณก๋ฌผ ์ƒ์‚ฐ์— ํฐ ์†์‹ค์„ ์ผ์œผ์ผœ ์‹๋Ÿ‰ ๋ฌธ์ œ๋ฅผ ์ผ์œผํ‚จ๋‹ค. ์‹๋ฌผ์˜ ๋ฉด์—ญ์ฒด๊ณ„๋Š” ๋Œ€๋ถ€๋ถ„์˜ ์™ธ๋ถ€ ์นจ์ž…์„ ๋ง‰์•„๋‚ด์ง€๋งŒ ๋ณ‘์›์ฒด๋Š” ๋‹ค์–‘ํ•œ ์ข…๋ฅ˜์˜ ์ดํŽ™ํ„ฐ(effector)๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๊ธฐ์ฃผ์˜ ๋ฐฉ์–ด๋ฐ˜์‘์„ ๋ฌด๋ ฅํ™”ํ•œ๋‹ค. ๋ณ‘์›์ฒด๊ฐ€ ์‹๋ฌผ์— ์ ‘์ด‰ํ•œ ํ›„ ์‹๋ฌผ์นจ์ž…์ด ์ด๋ฃจ์–ด์ง€๋Š” ๊ณผ์ •์—์„œ ๊ณต๊ฐ„์  ๋ถ„๋ฆฌ๊ฐ€ ์ผ์–ด๋‚˜๋Š”๋ฐ, ์ด๋Ÿฌํ•œ ๊ณต๊ฐ„์  ๋ถ„๋ฆฌ์— ๋”ฐ๋ผ ๋ณ‘์›์ฒด ์ดํŽ™ํ„ฐ๋Š” ์„ธํฌ ๊ฐ„๊ทน ์ดํŽ™ํ„ฐ(apoplastic effector)์™€ ์„ธํฌ์งˆ ์ดํŽ™ํ„ฐ(cytoplasmic effector)๋กœ ๋‚˜๋ˆ„์–ด์ง„๋‹ค. ์‹๋ฌผ ์นจ์ž…๊ณผ์ •์—์„œ ๊ธฐ์ฃผ์˜ ํ•ต์œผ๋กœ ์ด๋™ํ•˜์—ฌ ์ž‘๋™ํ•˜๋Š” ์ดํŽ™ํ„ฐ๋ฅผ ํ•ต ์ดํŽ™ํ„ฐ(nuclear effector)๋กœ ๋ถ„๋ฅ˜ํ•˜๋ฉฐ, ๋ณ‘์›์ฒด๊ฐ€ ๋ณ‘ ๋ฐœ์ƒํ™˜๊ฒฝ์„ ํšจ๊ณผ์ ์œผ๋กœ ์กฐ์ž‘ํ•˜๋Š”๋ฐ ํฐ ์˜ํ–ฅ์„ ์ค€๋‹ค. ํ•ต ์ดํŽ™ํ„ฐ๋Š” ์ฃผ๋กœ ์‹๋ฌผ๋ณ‘์›์„ฑ ์„ธ๊ท ๊ณผ ๋‚œ๊ท ์—์„œ ๊ธฐ๋Šฅ์ด ๋ถ„์„๋˜์—ˆ์œผ๋ฉฐ ๊ณตํ†ต์ ์œผ๋กœ ๋ฐฉ์–ด ์œ ์ „์ž ๋ฐœํ˜„, ํ˜ธ๋ฅด๋ชฌ ์‹ ํ˜ธ์ „๋‹ฌ์ฒด๊ณ„, ์„ธํฌ์‚ฌ๋ฉธ ๋“ฑ์„ ์กฐ์ ˆํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ์‹๋ฌผ๋ณ‘์›์„ฑ ๊ณฐํŒก์ด์˜ ํ•ต ์ดํŽ™ํ„ฐ์— ๋Œ€ํ•œ ๊ธฐ๋Šฅ๋ถ„์„์€ ์ƒ๋Œ€์ ์œผ๋กœ ๋ถ€์กฑํ•œ ์ƒํ™ฉ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ฒผ ์ˆ˜ํ™•๋Ÿ‰์— ํฐ ์†์‹ค์„ ์ผ์œผํ‚ค๋Š” ๋ฒผ ๋„์—ด๋ณ‘๊ท  (Magnaporthe oryzae)์˜ ํ•ต ์ดํŽ™ํ„ฐ ๊ธฐ๋Šฅ์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ฒผ ๋„์—ด๋ณ‘๊ท ์˜ ์นจ์ž…๊ณผ์ •์„ ์‚ดํŽด๋ณด๋ฉด, ํฌ์ž๊ฐ€ ๋ฒผ ํ‘œ๋ฉด์— ๋ถ€์ฐฉ, ๋ฐœ์•„ํ•œ ํ›„ ๋ถ€์ฐฉ๊ธฐ๋ฅผ ํ†ตํ•ด ๋ฌผ๋ฆฌ์ ์œผ๋กœ ์‹๋ฌผ ์„ธํฌ๋ฅผ ์นจ์ž…ํ•œ๋‹ค. ์นจ์ž… ํ›„ ๋ฒผ ๋„์—ด๋ณ‘๊ท ์€ ๊ธฐ์ฃผ ๋ฉด์—ญ์„ ์กฐ์ ˆํ•˜๊ธฐ ์œ„ํ•ด ์ดํŽ™ํ„ฐ๋ฅผ ๋ถ„๋น„ํ•˜๋Š”๋ฐ, ์„ธํฌ ๊ฐ„๊ทน ์ดํŽ™ํ„ฐ๋Š” ์„ธํฌ ์™ธ ๊ธฐ์งˆ(extracellular matrix)๋กœ ๋ถ„๋น„๋˜์–ด ๊ธฐ์ฃผ ๋ฐฉ์–ด๋ฐ˜์‘์„ ๋ฐฉํ•ดํ•œ๋‹ค. ์„ธํฌ์งˆ ์ดํŽ™ํ„ฐ๋Š” ํ™œ๋ฌผ๊ธฐ์ƒ ๊ณ„๋ฉด ๋ณตํ•ฉ์ฒด(biotrophic interfacial complex)๋ฅผ ํ†ตํ•ด ๊ธฐ์ฃผ ์„ธํฌ ๋‚ด๋ถ€๋กœ ์ด๋™ํ•˜๋ฉฐ ํŠน์ • ์†Œ๊ธฐ๊ด€์—์„œ ์ž‘๋™ํ•œ๋‹ค. ๋ฒผ ๋„์—ด๋ณ‘๊ท ์˜ ํ•ต ์ดํŽ™ํ„ฐ๋กœ ๋™์ •๋œ ์œ ์ „์ž๋“ค ์ค‘ MoHTR1๊ณผ MoHTR2๋Š” ์นจ์ž…๊ท ์‚ฌ๋กœ๋ถ€ํ„ฐ ๋ถ„๋น„๋œ ํ›„ ์‹๋ฌผ ์„ธํฌ ๋‚ด๋ถ€๋กœ ์ด๋™ํ•˜๊ณ , ํ•ต์— ๋„๋‹ฌํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ดํŽ™ํ„ฐ ๊ฒฐํ•ฉ ์ธ์ž(effector binding element)๋ฅผ ์ง€๋‹ˆ๊ณ  ์žˆ๋Š” ๋ฒผ ์œ ์ „์ž์˜ ํ”„๋กœ๋ชจํ„ฐ(promoter)์— ๊ฒฐํ•ฉํ•˜์—ฌ ๋ชฉํ‘œ ์œ ์ „์ž ๋ฐœํ˜„์„ ์–ต์ œํ•˜๊ณ , ๊ฐ„์ ‘์ ์ธ ํšจ๊ณผ๋กœ ์‹๋ฌผ ๋ฉด์—ญ ์œ ์ „์ž์˜ ๋ฐœํ˜„์„ ์žฌ ํ”„๋กœ๊ทธ๋ž˜๋ฐํ•œ๋‹ค. MoHTR1๊ณผ MoHTR2๋ฅผ ๋ฐœํ˜„ํ•˜๋„๋ก ์„ค๊ณ„ํ•œ ์œ ์ „์ž ๋„์ž… ์‹๋ฌผ์ฒด๋Š” ๋ฐ˜ํ™œ๋ฌผ๊ธฐ์ƒ ๋ณ‘์›์ฒด์ธ ๋ฒผ ๋„์—ด๋ณ‘๊ท ๊ณผ ๋ฒผ ํฐ์žŽ๋งˆ๋ฆ„๋ณ‘๊ท (Xanthomonas oryzae pv. oryzae)์— ๋Œ€ํ•œ ๊ฐ์ˆ˜์„ฑ์ด ์ฆ๊ฐ€ํ•˜๋ฉฐ, ๋ฐ˜๋Œ€๋กœ ์‚ฌ๋ฌผ๊ธฐ์ƒ ๋ณ‘์›์ฒด์ธ ๋ฒผ ๊นจ์”จ๋ฌด๋Šฌ๋ณ‘๊ท (Cochliobolus miyabeanus)์— ๋Œ€ํ•œ ์ €ํ•ญ์„ฑ์ด ์ฆ๊ฐ€ํ•œ๋‹ค. ๋ณ‘์›์ฒด์˜ ์ƒํ™œ์‚ฌ์— ๋”ฐ๋ผ ๋‹ค๋ฅด๊ฒŒ ๋‚˜ํƒ€๋‚˜๋Š” ๋ณ‘ ์ €ํ•ญ์„ฑ์€ ์–‘๊ฐ€ ๋ฉด์—ญ์˜ ํ•œ ์‚ฌ๋ก€๋กœ ๋ณผ ์ˆ˜ ์žˆ์œผ๋ฉฐ, MoHTR์˜ ๋ชฉํ‘œ ์œ ์ „์ž๋“ค์ด ๋ฒผ ๋„์—ด๋ณ‘ ์ €ํ•ญ์„ฑ์— ๊ด€์—ฌํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‹ค๋ฅธ ๋ณ‘์›์ฒด์˜ ์ €ํ•ญ์„ฑ์—๋„ ๊ด€์—ฌํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋‚˜ํƒ€๋‚ธ๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ๋ฒผ์™€ ๋ฒผ ๋„์—ด๋ณ‘๊ท  ์ƒํ˜ธ ์ž‘์šฉ ๊ธฐ์ž‘์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ์ •๋ณด๋ฅผ ์ œ๊ณตํ•˜๋ฉฐ, ๋ณ‘์›์ฒด ํ•ต ์ดํŽ™ํ„ฐ์— ์˜ํ•œ ์‹๋ฌผ ๋ฉด์—ญ ์กฐ์ ˆ์ด ๋‹ค๋ฅธ ๋ณ‘์›์ฒด์— ๋Œ€ํ•œ ์ €ํ•ญ์„ฑ์— ์–ด๋–ป๊ฒŒ ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ๋Š”์ง€๋ฅผ ์ œ์‹œํ•œ๋‹ค.CHAPTER I. Nuclear effectors of plant pathogens 1 ABSTRACT 2 INTRODUCTION 3 I. Nuclear effectors of plant pathogenic bacteria 7 II. Nuclear effectors of plant pathogenic oomycetes 14 III. Nuclear effectors of plant pathogenic nematodes 15 IV. Nuclear effectors of plant pathogenic fungi 16 V. Multiple nuclear effectors target the same biological processes 18 VI. Molecular mechanisms of nuclear effectors 20 VII. Effects of nuclear effectors on multiple microbe interactions 21 PERSPECTIVES 23 LITERATURE CITED 25 CHAPTER II. Two nuclear effectors of the rice blast fungus modulate host immunity via transcriptional reprogramming 45 ABSTRACT 46 INTRODUCTION 47 MATERIALS AND METHODS 50 I. Genome mining to identify nuclear effector candidates and identification of their target genes in rice 50 II. Assays for subcellular location of MoHTR proteins 51 III. Protein binding microarray to identify MoHTR-binding DNA sequences 52 IV. Validation of MoHTR-DNA interaction in vivo 53 V. Transcriptional activity assay in rice protoplasts 55 VI. Genetic manipulation of M. oryzae 56 VII. Production of transgenic rice plants expressing each MoHTR gene without the signal peptide 57 VIII. Gene expression analysis via quantitative RT-PCR and RNA-Seq 58 IX. Growth and developmental characteristics of MoHTR mutants 59 X. Infection assays for fungal and bacterial pathogens 60 RESULTS 66 I. Identification of nuclear effectors of M. oryzae 66 II. Expression patterns of MoHTRs, their distribution, and structural features 70 III. In planta localization of MoHTR1 and MoHTR2 77 IV. Identification of effector binding elements (EBEs) for MoHTR1 and MoHTR2 84 V. Identification of the rice genes targeted by MoHTR1 and MoHTR2 91 VI. MoHTR1 and MoHTR2 regulate transcription in rice protoplasts 110 VII. MoHTR1 and MoHTR2 reprogram the expression of many immunity-associated genes in rice 114 VIII. Effect of MoHTR deletion on fungal development and virulence 124 IX. Expression of MoHTR1 and MoHTR2 in rice affects susceptibility to multiple pathogens 129 DISCUSSION 132 LITERATURE CITED 139 ABSTRACT IN KOREAN 149Docto

    Digital Twin for Prediction of the Steady State Temperature Field of a Natural Gas Boiler

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    In this study, a simulation-based digital twin is developed for large-scale industrial natural gas boiler. The digital twin can predict temperature distribution under unexplored operating conditions by a regression model and a limited number of sensor data. The former is generally known as a surrogate model and the latter is known as sparse reconstruction. Proper orthogonal decomposition method is employed together with a kriging regression model for the surrogate model and gappy proper orthogonal decomposition for sparse reconstruction. Three-dimensional simulation data of the natural gas boiler are collected in the parameter space, which consists of excess air rate and swirl vane angle of the device. The surrogate model provides prediction performance within 5% least squared error. With sparse reconstruction, more than 32 measuring points provides prediction performance within 10% least squared error. The results show that the proper orthogonal decomposition has high potential as an analysis method for digital twin and prediction of reacting scalars in industrial combustion devices.22Nkc
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