우리는 재정 지원을 위해 중국 과학 기술부 (2016YDF0600803)에 감사드립니다.

1. 샘플 준비 <ol><li> 식물 샘플 ( 예 : 포플러 줄기)에서 작은 조직 블록 (약 3mm x 3mm x 5mm)을 자릅니다. </li><li> 조직을 끓는 탈 이온수에 30 분간 담근다. 즉시 실온 (RT)에서 30 분 동안 탈 이온수로 옮긴다. 티슈가 용기 바닥에 가라 앉을 때까지이 단계를 반복하여 조직의 공기가 제거되었고 조직이 부드럽게되었다는 것을 나타냅니다. 참고 :이 단계 이전에 바닥에 가라 앉은 샘플의 경우 일반적으로이주기를 3-5 번 반복하십시오. </li><li> 순수한 PEG뿐만 아니라 탈 이온수에 폴리에틸렌 글리콜 (PEG)의 20, 50, 70, 90 % (v / v) 분취 량을 준비하고 65 ° C에서 용액을 유지하십시오. </li><li> 수분을 치환하고 PEG가 침투하도록 일련의 등급이 매겨진 PEG 조에 조직을 배양합니다. 참고 : 일반적으로 분자량 2,000 (PEG2000) 인 PEG가 삽입에 사용됩니다. <ol><li> 조직을 g로 처리하십시오.(a) 1 시간 동안 20 % PEG, (b) 1.5 시간 동안 50 % PEG, (c) 2 시간 동안 70 % PEG, (d) 2 시간 동안 90 % PEG, 및 (e) 10 시간 동안 100 % PEG. </li></ol></li><li> 카세트를 오븐에서 65 ° C로 예열하십시오. 블록이 들어있는 PEG를 카세트에 넣은 다음 예열 된 핀셋 또는 바늘을 사용하여 조직 블록을 원하는 위치에 놓습니다. </li><li> 천천히 카세트를 식히고 사용할 때까지 실온에 티슈를 보관하십시오. </li><li> 날카로운 면도날을 사용하여 작은 블록 (약 1cm x 1cm x 2cm)에 표적 조직이 들어있는 PEG 블록을 해부하고 그것을 마이크로톰에 올려 놓습니다. </li><li> PEG 블록 (일반적으로 3-10 μm)에서 얇은 절편을 잘라냅니다. </li><li> 시계에서 10 번 탈 이온수로 섹션을 씻어 조직에서 PEG를 제거합니다. </li><li> 추출물을 제거하기 위해 6 시간 동안 톨루엔 / 에탄올 (2 : 1, v / v)로 섹션을 담그십시오. 탈 이온수 65 mL, 아세트산 0.5 mL 및 나트륨 클로라이드 0.6 g을 혼합하여 반응 액을 조제한다.비커에 의식. 5 mL 바이알에 한 개의 섹션과 3 mL의 반응 액을 첨가한다. 유리 병의 상단에 나사를 조이십시오. </li><li> 유리 병을 75oC에서 2 시간 가열하여 조직의 리그닌을 제거한다. 시계 유리에있는 탈 이온수로 섹션을 10 번 헹굽니다. </li><li> 미처리 / 탈 리그닌 부분을 유리 현미경 슬라이드로 옮긴다. 브러시 또는 바늘을 사용하여 조심스럽게 섹션을 펼칩니다. 티슈 페이퍼로 여분의 탈 이온수를 제거하십시오. </li><li> 섹션을 D 2 O에 담그십시오. 샘플을 유리 커버 슬립으로 덮으십시오. D 2 O의 증발을 막기 위해 매니큐어로 커버 슬립을 밀봉하십시오. </li></ol> 2. 스펙트럼 획득 <ol><li> 공 촛점 라만 현미경의 장비 운영 소프트웨어를 엽니 다. 레이저 (파장 = 532 nm)를 켜고 100 배 현미경 대물 렌즈를 사용하여 결정 실리콘 표면에 초점을 맞추고 보정 버튼을 클릭하여 장비를 보정합니다. </li><li> 계기 스위치광학 현미경 모드로 설정하고 현미경 램프를 켭니다. 커버 슬립이 목표를 향하도록 스테이지에 현미경 슬라이드를 장착하십시오. </li><li> 20X 현미경 대물 렌즈로 샘플을보고 관심 영역을 찾습니다. 커버 슬립에 침지 오일을 바르고 액침 현미경 대물 렌즈 (60X, 개구 수 NA = 1.35)로 전환합니다. 샘플 표면에 초점을 맞 춥니 다. </li><li> 장비를 라만 테스트 모드로 전환하고 현미경 램프를 끕니다. </li><li> 직사각형 도구를 사용하여 매핑 영역을 선택하십시오. 단계 크기를 변경하여 얻은 스펙트럼의 수를 결정합니다. 주 : 스텝 크기 (일반적으로 대물 렌즈의 개구 수에 의해 계산 된 스폿 직경보다 큰, 이론적으로는 1.22λ / NA)보다 유의하십시오. 이 크기보다 작은 경우 오버 샘플링이 발생합니다. </li><li> 최적의 스펙트럼 파라미터를 설정하여 적절한 획득 시간 (일반적으로 8 시간 미만)에서 최적의 신호 대 잡음비 (SNR) 및 스펙트럼 품질을 얻고,샘플 적합성에 관한 정보. 일반적으로 레이저 (532 nm), 필터 (100 %), 구멍 (300), 슬릿 (100), 분광계 (1,840 cm -1 ), 홈 (1200 t), 대물 렌즈 60X 오일) 및 수집 시간 (2 초). </li><li> 데이터 처리 전에 스펙트럼 데이터를 저장하고 범용 형식 ( 예 : TXT 파일)으로 변환하십시오. </li></ol> 3. 데이터 분석 <ol><li> 스펙트럼 데이터 (TXT 파일)를 데이터 분석 소프트웨어 ( 예 : Matlab)에로드하십시오. 데이터 세트에 노이즈 감소 기술을 적용하여 SNR을 향상시킵니다 ( 예 : Savitzsky-Golay 알고리즘 또는 웨이블릿 알고리즘) </li><li> 미처리 샘플을 사용하여 리그닌과 다당류의 이미지를 생성하십시오. 리그닌 영상의 경우, 방향족 링 대칭 스트레칭 진동 때문에 1,600 cm -1 부근의 스펙트럼 피크를 고려하십시오. 다당류 이미징 (셀룰로오스 및 헤미 셀룰로오스 포함)의 경우 스펙트럼 피크 aCH와 CH 2 뻗기 때문에 2,889 cm -1 라운드. </li><li> delignified 샘플을 사용하여 셀룰로오스와 헤미 셀룰로스의 이미지를 생성합니다. 획득 된 스펙트럼에서 자기 모델링 곡선 분해능 (SMCR)을 수행하여 셀룰로오스와 헤미 셀룰로스의 스펙트럼을 구별하고 그 분포를 영상화하십시오. </li><li> 획득 한 데이터에 대해 주성분 분석 (PCA) 및 클러스터링 분석을 수행하여 다른 셀 벽 레이어의 라만 스펙트럼을 구별합니다. </li></ol>

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M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+2.">Chapter 2.</a> Ionic Liquids in the Biorefinery Concept: Challenges and Perspectives. , 38-64 (2016).</li><li>Sun, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Understanding+tissue+specific+compositions+of+bioenergy+feedstocks+Through+hyperspectral+Raman+imaging.">Understanding tissue specific compositions of bioenergy feedstocks Through hyperspectral Raman imaging.</a> Bio. 108 (2), 286-295 (2009).</li><li>Tolstik, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Classification+and+prediction+of+HCC+tissues+by+Raman+imaging+with+identification+of+fatty+acids+as+potential+lipid+biomarkers.">Classification and prediction of HCC tissues by Raman imaging with identification of fatty acids as potential lipid biomarkers.</a> J. Cancer. Res. Clin. Oncol. 141 (3), 407-418 (2015).</li><li>Schrader, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Infrared and Raman spectroscopy: methods and applications. , (2008).</li><li>Gierlinger, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+of+plant+cell+walls+by+confocal+Raman+microscopy.">Imaging of plant cell walls by confocal Raman microscopy.</a> Nat. Protoc. 7 (9), 1694-1708 (2012).</li><li>Luca, A. C. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Online+fluorescence+suppression+in+modulated+Raman+spectroscopy.">Online fluorescence suppression in modulated Raman spectroscopy.</a> Anal. 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저자는 공개 할 것이 없습니다.

식물 세포 벽은 세포 모서리 (CC), 2 차벽 (S1, S2 및 S3 층을 갖는 SW) 및 복합 중간 엽 줄기 (CML, 중층 및 인접한 주 엽산)를 포함하는 여러 층으로 조직화 된 복합체이다. 벽), 이는 샘플 준비 동안 평평한 표면을 얻는 것을 어렵게 만듭니다. 따라서 나무보다 복잡한 구조를 가진 식물 샘플, 특히 잔디는 미세 절단을 위해 응고 될 필요가 있습니다. PEG는 물에 녹기 때문에 절단 및 라만 조사를위한 이상적...

Plant biomass is the most abundant renewable resource on Earth; is mainly composed of lignin, cellulose, and hemicellulose; and is considered an attractive source of bioenergy and bio-based chemicals1. Unfortunately, it can resist degradation and confer hydrolytic stability or structural robustness to the plant cell wall. Such resistance is attributable to the accessible surface area, biomass particle size, degree of polymerization, cellulose crystallinity, and protective lignin2. A comprehensive understanding of the structural and chemical nature of the plant cell wall is thus significant from the viewpoint of plant biology and chemistry, as well as from that of commercial utilization. Commonly used wet chemistry analyses, such as chromatography, mass spectrometry, and nuclear magnetic resonance spectroscopy, only provide average compositional data of the measured sample. Furthermore, these methods are invasive and destroy the original structure of the plant tissue3. 
The Raman imaging technique is a powerful tool for the nondestructive visualization of spatially resolved chemical information4. It uses a laser light to cause inelastic scattering with a photon and relies on changes in polarizability arising from the molecular vibrations. In this case, water causes weak Raman scattering, which makes this approach suitable for in situ investigations of biological samples5. The application of the Raman imaging technique to the plant cell wall can elucidate the structure and composition of plant cell walls in their native state, with the resolution on the scale of the single cell and even of the cell wall layers6. A typical Raman imaging analysis of a plant cell wall generally consists of three steps: 1) sample preparation, 2) spectral acquisition, and 3) data processing. 
Although one of the major advantages of Raman imaging is the ability to achieve label-free and non-destructive spectra with minimal sample preparation, physical sample sectioning is still necessary to expose the surface of interest. This process should be performed carefully to obtain a flat surface, since the technique depends on maintaining optical focus7. Spectral acquisition requires a balance between image quality and extensive acquisition times8. Data processing aims to effectively extract the chemical information from the image data, especially for the components with similar chemical structures, such as cellulose and hemicellulose. Due to the strong spectral overlap, the exact spectra are difficult to discern. In this case, multivariate analysis is a straightforward approach to effectively uncover the hiding structural and chemical information9. This work presents a general protocol describing the use of Raman imaging to visualize the main components in plant cell walls, including lignin, cellulose, and hemicellulose.

<table border="0" cellpadding="0" cellspacing="0" width="597">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:199px;">Microtome</td>
			<td style="width:136px;">Thermo Scientific</td>
			<td style="width:199px;">Microm HM430</td>
			<td style="width:64px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Confocal Raman microscope</td>
			<td>Horiba Jobin Yvon</td>
			<td>Xplora</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Oven</td>
			<td>Shanghai ZHICHENG</td>
			<td>ZXFD-A5040</td>
			<td></td>
		</tr>
	</tbody>
</table>

combining raman imaging and multivariate analysis to visualize lignin, cellulose, and hemicellulose in the plant cell wall

식물체 바이오 매스에 라만 이미징을 적용하는 것은 수용액에 대한 공간적 및 조성 정보를 제공 할 수 있기 때문에 증가하고 있습니다. 분석은 일반적으로 광범위한 샘플 준비가 필요하지 않습니다. 라벨을 붙이지 않고도 구조적 및 화학적 정보를 얻을 수 있습니다. 그러나 각 라만 이미지에는 수천 개의 스펙트럼이 포함되어 있습니다. 이것은 숨겨진 정보를 추출 할 때 어려움을 낳습니다. 특히 비슷한 화학 구조를 가진 구성 요소의 경우. 이 연구는이 문제를 해결하기 위해 다변량 분석을 도입합니다. 이 프로토콜은 식물 세포벽 내에서 리그닌, 셀룰로오스 및 헤미 셀룰로스를 비롯한 주성분을 시각화하는 일반적인 방법을 수립합니다. 이 프로토콜에서는 시료 준비, 스펙트럼 획득 및 데이터 처리 절차가 설명됩니다. 이는 시료 준비 및 데이터 분석시 운영자의 기술에 크게 의존합니다. 이 접근법을 사용함으로써 비전문 사용자가 라만 조사를 수행하여 high 품질 데이터 및 식물 세포벽 분석에 대한 의미있는 결과.

그림 1 은 식물 세포벽의 라만 이미징을위한 전형적인 마이크로 라만 시스템의 개요를 나타냅니다. 예를 들어, 포플라 ( Populus nigra L.)의 원래 라만 스펙트럼은 상당한 기준선 드리프트와 스파이크를 가지고 있습니다 ( 그림 2a ). 라만 이미징 데이터 세트 (APRI)에 대한 자동 사전 처리 방법을 수행 한 후,이 두 스펙트럼 오?...

Watch this Scientific Journal Video about Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall at JoVE.com

Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall

이 프로토콜은 라만 이미징 및 다 변수 분석을 사용하여 식물 세포 벽에서 리그닌, 셀룰로오스 및 헤미 셀룰로오스를 시각화하는 일반적인 방법을 제시합니다.

라만 이미징과 다변량 분석을 결합하여 식물 세포벽에서 리그닌, 셀룰로오스 및 헤미 셀룰로스를 시각화합니다.

The application of Raman imaging to plant biomass is increasing because it can offer spatial and compositional information on aqueous solutions. The ...

combining-raman-imaging-multivariate-analysis-to-visualize-lignin

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JoVE Journal

Biochemistry

11.8K 조회수.  Beijing Forestry University.  이 프로토콜은 라만 이미징 및 다 변수 분석을 사용하여 식물 세포 벽에서 리그닌, 셀룰로오스 및 헤미 셀룰로오스를 시각화하는 일반적인 방법을 제시합니다. 

비디오: Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall

Determination of the Glycogen Content in Cyanobacteria

Cyanobacteria accumulate glycogen as a major intracellular carbon and energy storage&#160;during photosynthesis. Recent developments in research have highlighted complex mechanisms of glycogen metabolism, including the diel cycle of biosynthesis and catabolism, redox regulation, and the involvement of non-coding RNA. At the same time, efforts are being made to redirect carbon from glycogen to desirable products in genetically engineered cyanobacteria to enhance product yields. Several methods are used to determine the glycogen contents in cyanobacteria, with variable accuracies and technical complexities. Here, we provide a detailed protocol for the reliable determination of the glycogen content in cyanobacteria that can be performed in a standard life science laboratory. The protocol entails the selective precipitation of glycogen from the cell lysate and the enzymatic depolymerization of glycogen to generate glucose monomers, which are detected by a glucose oxidase-peroxidase (GOD-POD) enzyme coupled assay. The method has been applied to Synechocystis sp. PCC 6803 and Synechococcus sp. PCC 7002, two model cyanobacterial species that are widely used in metabolic engineering. Moreover, the method successfully showed differences in the glycogen contents between the wildtype and mutants defective in regulatory elements or glycogen biosynthetic genes.

Here, we present a reliable and easy assay to measure the glycogen content in cyanobacterial cells. The procedure entails precipitation, selectable depolymerization, and the detection of glucose residues. This method is suitable for both wildtype and genetically engineered strains and can facilitate the metabolic engineering of cyanobacteria.

시아 노 박테리아의 글리코겐 함량 측정

Cyanobacteria accumulate glycogen as a major intracellular carbon and energy storage&#160;during photosynthesis. Recent developments in research have ...

연구

생화학

Structural Characterization of Mannan Cell Wall Polysaccharides in Plants Using PACE

Plant cell wall polysaccharides are notoriously difficult to analyze, and most methods require expensive equipment, skilled operators, and large amounts of purified material. Here, we describe a simple method for gaining detailed polysaccharide structural information, including resolution of structural isomers. For polysaccharide analysis by gel electrophoresis (PACE), plant cell wall material is hydrolyzed with glycosyl hydrolases specific to the polysaccharide of interest (e.g., mannanases for mannan). Large format polyacrylamide gels are then used to separate the released oligosaccharides, which have been fluorescently labeled. Gels can be visualized with a modified gel imaging system (see Table of Materials). The resulting oligosaccharide fingerprint can either be compared qualitatively or, with replication, quantitatively. Linkage and branching information can be established using additional glycosyl hydrolases (e.g., mannosidases and galactosidases). Whilst this protocol describes a method for analyzing glucomannan structure, it can be applied to any polysaccharide for which characterized glycosyl hydrolases exist. Alternatively, it can be used to characterize novel glycosyl hydrolases using defined polysaccharide substrates.

A protocol for the structural analysis of polysaccharides by gel electrophoresis (PACE), using mannan as an example, is described.

속도 사용 하 여 식물에 Mannan 세포 벽 다 당 류 구조 특성

Plant cell wall polysaccharides are notoriously difficult to analyze, and most methods require expensive equipment, skilled operators, and large amounts ...

Isolation and Respiratory Measurements of Mitochondria from Arabidopsis thaliana

Mitochondria are essential organelles involved in numerous metabolic pathways in plants, most notably the production of adenosine triphosphate (ATP) from the oxidation of reduced compounds such as nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FADH2). The complete annotation of the Arabidopsis thaliana genome has established it as the most widely used plant model system, and thus the need to purify mitochondria from a variety of organs (leaf, root, or flower) is necessary to fully utilize the tools that are now available for Arabidopsis to study mitochondrial biology. Mitochondria are isolated by homogenization of the tissue using a variety of approaches, followed by a series of differential centrifugation steps producing a crude mitochondrial pellet that is further purified using continuous colloidal density gradient centrifugation. The colloidal density material is subsequently removed by multiple centrifugation steps. Starting from 100 g of fresh leaf tissue, 2 - 3 mg of mitochondria can be routinely obtained. Respiratory experiments on these mitochondria display typical rates of 100 - 250 nmol O2 min-1 mg total mitochondrial protein-1 (NADH-dependent rate) with the ability to use various substrates and inhibitors to determine which substrates are being oxidized and the capacity of the alternative and cytochrome terminal oxidases. This protocol describes an isolation method of mitochondria from Arabidopsis thaliana leaves using continuous colloidal density gradients and an efficient respiratory measurements of purified plant mitochondria.

Isolation and Respiratory Measurements of Mitochondria from Arabidopsis thaliana

As mitochondria are only a small percentage of the plant cell, they need to be purified for a range of studies. Mitochondria can be isolated from a variety of plant organs by homogenization, followed by differential and density gradient centrifugation to obtain a highly purified mitochondrial fraction.

절연 및 호흡 측정의 미토 콘 드리 아 애기 thaliana 에서

Mitochondria are essential organelles involved in numerous metabolic pathways in plants, most notably the production of adenosine triphosphate (ATP) from ...

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes

Cellular processes are regulated by interactions between biological molecules such as proteins, metabolites, and nucleic acids. While the investigation of protein-protein interactions (PPI) is no novelty, experimental approaches aiming to characterize endogenous protein-metabolite interactions (PMI) constitute a rather recent development. Herein, we present a protocol that allows simultaneous characterization of the PPI and PMI of a protein of choice, referred to as bait. Our protocol was optimized for Arabidopsis cell cultures and combines affinity purification (AP) with mass spectrometry (MS)-based protein and metabolite detection. In short, transgenic Arabidopsis lines, expressing bait protein fused to an affinity tag, are first lysed to obtain a native cellular extract. Anti-tag antibodies are used to pull down protein and metabolite partners of the bait protein. The affinity-purified complexes are extracted using a one-step methyl tert-butyl ether (MTBE)/methanol/water method. Whilst metabolites separate into either the polar or the hydrophobic phase, proteins can be found in the pellet. Both metabolites and proteins are then analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS or UPLC-MS/MS). Empty-vector (EV) control lines are used to exclude false positives. The major advantage of our protocol is that it enables identification of protein and metabolite partners of a target protein in parallel in near-physiological conditions (cellular lysate). The presented method is straightforward, fast, and can be easily adapted to biological systems other than plant cell cultures.

Protein-protein and protein-metabolite interactions are crucial for all cellular functions. Herein, we describe a protocol that allows parallel analysis of these interactions with a protein of choice. Our protocol was optimized for plant cell cultures and combines affinity purification with mass spectrometry-based protein and metabolite detection.

2 1: 원스텝 단백질 단백질과 단백질 대사 산물 단지의 병렬 분석에 대 한 친 화력 정화

Cellular processes are regulated by interactions between biological molecules such as proteins, metabolites, and nucleic acids. While the investigation of ...

Using In Vitro Fluorescence Resonance Energy Transfer to Study the Dynamics Of Protein Complexes at a Millisecond Time Scale

Proteins are the primary operators of biological systems, and they usually interact with other macro- or small molecules to carry out their biological functions. Such interactions can be highly dynamic, meaning the interacting subunits are constantly associated and dissociated at certain rates. While measuring the binding affinity using techniques such as quantitative pull-down reveals the strength of the interaction, studying the binding kinetics provides insights on how fast the interaction occurs and how long each complex can exist. Furthermore, measuring the kinetics of an interaction in the presence of an additional factor, such as a protein exchange factor or a drug, helps reveal the mechanism by which the interaction is regulated by the other factor, providing important knowledge for the advancement of biological and medical research. Here, we describe a protocol for measuring the binding kinetics of a protein complex that has a high intrinsic association rate and can be dissociated quickly by another protein. The method uses fluorescence resonance energy transfer to report the formation of the protein complex in vitro, and it enables monitoring the fast association and dissociation of the complex in real time on a stopped-flow fluorimeter. Using this assay, the association and dissociation rate constants of the protein complex are quantified.

Protein-protein interactions are critical for biological systems, and studies of the binding kinetics provide insights into the dynamics and function of protein complexes. We describe a method that quantifies the kinetic parameters of a protein complex using fluorescence resonance energy transfer and the stopped-flow technique. &#160;

체 외 형광 공명 에너지 전달에 밀리초 시간 규모에서 단백질 복합물의 역학을 공부 하는 사용 하 여

Proteins are the primary operators of biological systems, and they usually interact with other macro- or small molecules to carry out their biological ...

In Vivo Calcium Imaging in C. elegans Body Wall Muscles

The model organism C. elegans provides an excellent system to perform in vivo calcium imaging. Its transparent body and genetic manipulability allow for the targeted expression of genetically encoded calcium sensors. This protocol outlines the use of these sensors for the in vivo imaging of calcium dynamics in targeted cells, specifically the body wall muscles of the worms. By utilizing the co-expression of presynaptic channelrhodopsin, stimulation of acetylcholine release from excitatory motor neurons can be induced using blue light pulses, resulting in muscle depolarization and reproducible changes in cytoplasmic calcium levels. Two worm immobilization techniques are discussed with varying levels of difficulty. Comparison of these techniques demonstrates that both approaches preserve the physiology of the neuromuscular junction and allow for the reproducible quantification of calcium transients. By pairing optogenetics and functional calcium imaging, changes in postsynaptic calcium handling and homeostasis can be evaluated in a variety of mutant backgrounds. Data presented validates both immobilization techniques and specifically examines the roles of the C. elegans sarco(endo)plasmic reticular calcium ATPase and the calcium-activated BK potassium channel in the body wall muscle calcium regulation.

In Vivo Calcium Imaging in C. elegans Body Wall Muscles

This method provides a way to couple optogenetics and genetically encoded calcium sensors to image baseline cytosolic calcium levels and changes in evoked calcium transients in the body wall muscles of the model organism C. elegans.

C. 예쁜꼬마선충의 생체내 칼슘 이미징

The model organism C. elegans provides an excellent system to perform in vivo calcium imaging. Its transparent body and genetic manipulability allow for ...

Study on the Metabolism of Six Systemic Insecticides in a Newly Established Cell Suspension Culture Derived from Tea (Camellia Sinensis L.) Leaves

A platform for studying insecticide metabolism using in vitro tissues of tea plant was developed. Leaves from sterile tea plantlets were induced to form loose callus on Murashige and Skoog (MS) basal media with the plant hormones 2,4-dichlorophenoxyacetic acid (2,4-D, 1.0 mg L-1) and kinetin (KT, 0.1 mg L-1). Callus formed after 3 or 4 rounds of subculturing, each lasting 28 days. Loose callus (about 3 g) was then inoculated into B5 liquid media containing the same plant hormones and was cultured in a shaking incubator (120 rpm) in the dark at 25 &#177; 1 &#176;C. After 3&#8722;4 subcultures, a cell suspension derived from tea leaf was established at a subculture ratio ranging between 1:1 and 1:2 (suspension mother liquid: fresh medium). Using this platform, six insecticides (5 &#181;g mL-1 each thiamethoxam, imidacloprid, acetamiprid, imidaclothiz, dimethoate, and omethoate) were added into the tea leaf-derived cell suspension culture. The metabolism of the insecticides was tracked using liquid chromatography and gas chromatography. To validate the usefulness of the tea cell suspension culture, the metabolites of thiamethoxan and dimethoate present in treated cell cultures and intact plants were compared using mass spectrometry. In treated tea cell cultures, seven metabolites of thiamethoxan and two metabolites of dimethoate were found, while in treated intact plants, only two metabolites of thiamethoxam and one of dimethoate were found. The use of a cell suspension simplified the metabolic analysis compared to the use of intact tea plants, especially for a difficult matrix such as tea.

Study on the Metabolism of Six Systemic Insecticides in a Newly Established Cell Suspension Culture Derived from Tea Camellia Sinensis L. Leaves

This work presents a protocol for establishing a cell suspension culture derived from tea (Camellia sinensis L.) leaves that can be used to study the metabolism of external compounds that can be taken up by the whole plant, such as insecticides.

차에서 파생된 새로 설립된 세포 현탁액 배양에서 6개의 전신 살충제의 물질대사에 관한 연구(동백나무시넨시스 L.) 잎

A platform for studying insecticide metabolism using in vitro tissues of tea plant was developed. Leaves from sterile tea plantlets were induced to form ...

Measuring Interactions between Fluorescent Probes and Lignin in Plant Sections by sFLIM Based on Native Autofluorescence

In lignocellulosic biomass (LB), the activity of enzymes is limited by the appearance of non-specific interactions with lignin during the hydrolysis process, which maintains enzymes far from their substrate. Characterization of these complex interactions is thus a challenge in complex substrates such as LB. The method here measures molecular interactions between fluorophore-tagged molecules and native autofluorescent lignin, to be revealed by F&#246;rster resonance energy transfer (FRET). Contrary to FRET measurements in living cells using two exogenous fluorophores, FRET measurements in plants using lignin is not trivial due to its complex autofluorescence. We have developed an original acquisition and analysis pipeline with correlated observation of two complementary properties of fluorescence: fluorescence emission and lifetime. sFLIM (spectral and fluorescent lifetime imaging microscopy) provides the quantification of these interactions with high sensitivity, revealing different interaction levels between biomolecules and lignin.

This protocol describes an original setup combining spectral and fluorescence lifetime measurements to evaluate F&#246;rster resonance energy transfer (FRET) between rhodamine-based fluorescent probes and lignin polymer directly in thick plant sections.

네이티브 오토플루임션을 기반으로 sFLIM에 의한 식물 섹션의 형광 프로브와 리그닌 간의 상호 작용 측정

In lignocellulosic biomass (LB), the activity of enzymes is limited by the appearance of non-specific interactions with lignin during the hydrolysis ...

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects

Cells are known to be inherently heterogeneous in their responses to drugs. Therefore, it is essential that single-cell heterogeneity is accounted for in drug discovery studies. This can be achieved by accurately measuring the plethora of cellular interactions between a cell and drug at the single-cell level (i.e., drug uptake, metabolism, and effect). This paper describes a single-cell Raman spectroscopy and mass spectrometry (MS) platform to monitor metabolic changes of cells in response to drugs. Using this platform, metabolic changes in response to the drug can be measured by Raman spectroscopy, while the drug and its metabolite can be quantified using mass spectrometry in the same cell. The results suggest that it is possible to access information about drug uptake, metabolism, and response at a single-cell level.

This protocol presents an integrated Raman spectroscopy-mass spectrometry (MS) platform that is capable of achieving single-cell resolution. Raman spectroscopy can be used to study cellular response to drugs, while MS can be used for targeted and quantitative analysis of drug uptake and metabolism.

단일 세포 약물 섭취, 신진 대사 및 효과를 연구하기 위한 통합 라만 분광법 및 질량 분광법 플랫폼

Cells are known to be inherently heterogeneous in their responses to drugs. Therefore, it is essential that single-cell heterogeneity is accounted for in ...

RNA Blot Analysis for the Detection and Quantification of Plant MicroRNAs

MicroRNAs (miRNAs) are a class of endogenously expressed non-coding, ~21 nt small RNAs involved in the regulation of gene expression in both plants and animals. Most miRNAs act as negative switches of gene expression targeting key genes. In plants, primary miRNAs (pri-miRNAs) transcripts are generated by RNA polymerase II, and they form varying lengths of stable stem-loop structures called pre-miRNAs. An endonuclease, Dicer-like1, processes the pre-miRNAs into miRNA-miRNA* duplexes. One of the strands from miRNA-miRNA* duplex is selected and loaded onto Argonaute 1 protein or its homologs to mediate the cleavage of target mRNAs. Although miRNAs are key signaling molecules, their detection is often carried out by less than optimal PCR-based methods instead of a sensitive northern blot analysis. We describe a simple, reliable, and extremely sensitive northern method that is ideal for the quantification of miRNA levels with very high sensitivity, literally from any plant tissue. Additionally, this method can be used to confirm the size, stability and the abundance of miRNAs and their precursors.

This method demonstrates use of the northern hybridization technique to detect miRNAs from total RNA extract.

식물 MicroRNAs의 검출 및 정량화를 위한 RNA 블롯 분석

MicroRNAs (miRNAs) are a class of endogenously expressed non-coding, ~21 nt small RNAs involved in the regulation of gene expression in both plants and ...