Name: evaluation of the impact of protein aggregation on cellular oxidative stress in yeast
Uploaded: 2018-06-23T13:00:00.000+00:00
Duration: 11 min 4 s
Description: Watch this Scientific Journal Video about Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast at JoVE.com

1. S. cerevisiae 문화와 단백질 표정
참고: Aβ 변종 전시 Aβ42 펩 티 드 (그림 1A)의 위치 19 (Phe19)에서 단일 잔류물에 돌연변이 인해 다른 상대 집계 경향. 이 펩 티 드 이체는 녹색 형광 단백질 (GFP), 집계 기자 (그림 1)29역할으로 태그 됩니다.
<ol><li>플라스 미드 BY4741 부모의 배경 (타 그의3Δ1 레이2Δ0 만난15Δ0 ura3Δ0)30효 모 세포로 20 Aβ42-GFP 변종에 대 한 인코딩 변환. 각 플라스 미드 GSSGSSG 링커에 의해 GFP를 융합 하는 Aβ42 돌연변이 인코딩합니다. 플라스 미드는 pESC(-URA) 이며 선택 가능한 마커 URA329를 포함.<ol>
<li>다음 구성 요소와 uracil (사우스 캐롤라이나-우 라) 없이 합성 완전 한 매체 준비: 1.9 g/L 효 질소 uracil, 5 g/L 황산 암모늄과 900 mL ddH2O의 기본 20% (w/v) 포도 당 100ml와 결합.</li>
		<li>2% 포도 당을 포함 하는 SC-우 라 중간의 20 mL로 변형 된 효 모 세포에의 한 식민지를 넣고 하룻밤 동요 210 rpm에서 30 ° C에서 문화를 성장.</li>
	</ol>
</li>
	<li>다음 날, 신선한 SC-우 라 중간의 5 mL에 접종 100 µ L의 숙박 문화에 의해 새로운 효 모 세포 배양 성장.</li>
	<li>에는 OD590 0.5, 원심 4 분 3000 x g에서 문화, 상쾌한, 삭제 고 resuspend 동일한 양의 신선한 SC-우 라 중 2% 유를 포함 하는 셀.</li>
	<li>30 분 동안 210 rpm 동요에서 30 ° C에서 품 어. 그리고 4 분 3000 x g에서 세포를 원심는 상쾌한을 삭제 합니다. 재조합 형 단백질 표정 유도 2% 갈 락 토스를 포함 하는 신선한 SC-우 라 매체에 셀 resuspend</li>
	<li>단백질 표정 2% 갈 락 토스를 포함 하는 사우스 캐롤라이나-우 라 중간에 유도의 16 h 후 4 분 3000 x g에서 원심 분리 하 여 살 균 microcentrifuge 관에 유도 세포의 1 mL를 수확. 참고: 가장 관련성이 높은 차이 발생 후 Aβ42 GFP 변종 표현 16 h. 유도 효 모 세포의 유도 기간 형광 현미경 검사 법 (그림 2B) 셀 안에 재조합 단백질 분포를 결정 하 여 구상 될 수 있다.</li>
</ol>2. 세포 얼룩
참고: 신선한 비 유발 세포는 FC 분석 동안 형광 임계값을 설정 하는 부정적인 컨트롤으로 구성 해야 합니다.
<ol><li>16 h 유발 효 모 세포를가지고 고 590에서 그들의 광학 밀도 결정 nm (OD590). 0.1의 OD590 를 버퍼링 하는 멸 균 인산 염 분 (PBS)에 그들을 희석.<ol>
<li>버퍼링 인산 염 분 x 1을 다음과 같이 준비: NaCl, KCl, 나2HPO4, 1.44 g의 0.2 g의 8 g을 추가 하 고 KH2포4 ddH2오의 800 mL의 0.24 g pH 7.4에 조정 후 1 L ddH2O의 솔루션 작성 HCl. 버퍼 0.2 µ m 필터를 통해 필터링.</li>
	</ol>
</li>
	<li>레이블이 표시 된 튜브 (12 × 75 m m 라운드 하단 폴리스 티 렌)을 표현 하는 세포 정지를 전송 하 고 빛에서 그들을 보호. 그들은 비 유도 및 비-얼룩진 셀 함께 분석에 대 한 교류 cytometer에 로드할 준비가 다는 것을 확인 하십시오.</li>
	<li>5 µ M의 최종 농도에 각 샘플을 (예를 들어, CellROX 딥 레드) 산화 스트레스 프로브를 추가 하 고 어둠 속에서 30 분 동안 30 ° C에 세포를 품 어.</li>
	<li>부 화, 후 셀 1 x PBS로 3 회 세척 하 고 FC 그들의 분석 전에 버퍼의 동일한 볼륨에 그들을 resuspend.</li>
</ol>3. 교류 Cytometry 분석
참고: 적절 한 레이저와 필터는 FC 설치를 사용 하 여 GFP와 산화 스트레스 프로브 형광 신호를 감지. 교류 cytometer GFP의 발견을 위한 488 nm 청색 레이저와 산화 스트레스 프로브 형광의 탐지를 위한 635 nm 빨간 레이저를 사용할 수 있습니다. GFP와 산화 스트레스 프로브 방출 형광의 인수는 각각 530/30 nm BP 필터와 660/20 BP 필터 수행 (표 1).
<ol><li>새 워크시트 패널 열기 에 클릭 하 고 다음 인수 점 플롯을 만들.<ol>
<li>도구 모음에서 분산형 플롯 도구 를 선택 하 고 A를 만들기 음모 쪽 분산형-지역 변수 (SSC-)는 y 축 대 앞으로 피해 지역에 (FSC-A)는 x 축에 선형 눈금에.</li>
		<li>도구 모음에서 분산형 플롯 도구 를 클릭 하 고 x 축 대에 변수 FL1 지역 (FITC)와 음모를 만들. FL3 지역 (APC)는 y 축에 로그 눈금.</li>
	</ol>
</li>
	<li>악기 설정 아이콘을 클릭 합니다. 보상 탭을 클릭 하 고 모든 보상 수준을 설정 합니다. 인수 탭에서 클릭 하 고 기록 20000 이벤트의 총 수를 선택 합니다.</li>
	<li>유량 아이콘 낮은흐름 속도 전환 하려면 클릭 합니다.</li>
	<li>취득 탭 비 유도, 흠 없는 세포 실행 시작을 클릭 하 고 인구 중간 왼쪽 사분면에 배포 될 때까지 측면 분산형 및 앞으로의 악기 설정 에서 전압을 조정 합니다.<ol>
<li>다각형 아이콘 세포 인구 세포 파편을 제외 하 고 주변 지역 R1 설정을 클릭 하 고이 문이 인구 p 1을 사용 하 여 모든 형광 점 플롯과 히스토그램 표시 (그림 3)에 대 한 R1 =.</li>
	</ol>
</li>
	<li>형광 신호의 PMT 전압을 조정 하려면 셀 낮은 왼쪽된 사분면에 배포 될 때까지 튜닝 악기 설정 탭에서 이득 FL1 FL3 점 플롯에 흠 없는 셀을 실행 합니다.</li>
	<li>GFP 형광을 측정 하는 유도 셀에 샘플을 변경 합니다. 악기 설정 탭에서 인구 오른쪽 아래 사분면에 배포 될 때에는 FSC-A 대 FL1 (FITC) 이득을 설정 합니다. 게이트 (게이트 P2) 긍정적인 세포 인구를 정의 합니다.</li>
	<li>변경 샘플 비 유발 산화 스트레스는 FSC-A 대 FL3 (APC) 도트 음모에 형광으로 표시 하려면 셀 스테인드. 튜닝 이득 셀 인구는 왼쪽 위 사분면에서 배 부 될 때까지. P3에 긍정적인 세포 인구 게이트입니다.</li>
	<li>확인을 셀 형광을 나타내는 히스토그램 아이콘 두 히스토그램 플롯 합니다. 형광 강도 나타내는 FL1 (FITC) GFP 형광을 나타내는 x 축, 이며 FL3 (APC) 형광을 나타내는 y에 로그 눈금에 P2 및 P3 인구를 각각 적용 있는지 확인 합니다. 참고: 막대 그래프 오버레이 다른 Aβ 이체를 표현 하는 셀의 형광 프로필 간의 차이 설명 하기 위해 좋은 방법입니다.</li>
</ol>4. 재조합 단백질 Immunodetection
<ol><li>단백질 표정 수준 결정, 16 h에 대 일 분, 4000 x g에서 원심 분리에 의해 유도 된 효 모 배양 수확을-80 ° c.에 셀 펠 릿 저장<ol>
<li>PBS에 16 h에 대 한 재조합 단백질을 표현 하는 수집 된 셀 resuspend 20의 OD590 를 각 Aβ42 GFP 돌연변이의 200 µ L 셀 정지를 준비 합니다.</li>
	</ol>
</li>
	<li>총 단백질 분수 분석에 대 일 분 14000 x g에서 원심 분리 하 여 각 돌연변이의 100 µ L를 수확 하 고 효 모 세포의 용 해 버퍼 Y의 동일한 볼륨에 셀 펠 릿 resuspend-(50 mM Tris HCl pH 8.0, 1 %DMSO, 200 mM NaCl, 1 mM EDTA 10 mg/mL SB3-14 (myr 포함 된 당 istyl sulfobetaine) 보충 1 m m phenylmethylsulfonyl 불 (PMSF)).<ol>
<li>온화한 동요에서 실 온에서 20 분에 대 한 샘플을 품 어.</li>
	</ol>
</li>
	<li>Bradford 분석 실험을 사용 하 여 단백질 추출 농도 결정 합니다. 15% 아크릴 SDS 페이지 젤 전기 이동 법에 60 분 100 V에서 polyvinylidene difluoride (PVDF) 막에 오 각 샘플의 단백질 추출의 최대 5 µ g를 로드 합니다.<ol>
<li>브래드 퍼 드 Coomassie 화려한 블루 G-250의 100 밀리 그램으로 시 약 50ml 95% 에탄올에에서 용 해 하 고 85% (w/v) 인산의 100ml를 추가 준비. 다음, 염료 해산 완전히 ddH2O 1 l 혼합물을 희석 하 고 그냥 사용 하기 전에 셀 루 로스 필터 종이 통해 필터링. 참고: 브래드 퍼 드 시 해야 될 빛 갈색.</li>
		<li>소 혈 청 알 부 민 (BSA)의 브래드포드 시 약 1000 µ L에서 단백질의 5-100 µ g에서 배열의 표준 준비.</li>
		<li>1-10 µ L 단백질의 브래드포드 시의 1 mL에 추출 하 고 품 어 5 분 동안 실내 온도에 혼합물을 추가 합니다.</li>
		<li>표준과 마약595에서 단백질 추출 물 샘플의 흡 광도 측정 한다.</li>
		<li>분석을 위해 표준 대에 대 한 얻은 흡 광도 값으로 음모를 확인 합니다. 단백질의 µ g입니다. 표준 곡선에 따라 달라 집니다, 있는 경우 볼륨 및 희석, 고려는 양의 단백질에서 원래 샘플의 농도 결정 합니다.</li>
	</ol>
</li>
	<li>린스 Tris 버퍼 염 분 (TBS), x 1 막 0.1% Tween 20 (TTBS), 1 x TTBS의 5% (w/v) 무 지방 건조 우유를 사용 하 여 차단 하 고.<ol>
<li>10 x TBS의 1 리터를 준비 하려면 기본 트리 스의 24 g와 H2Odd 900 mL에 NaCl의 88 g을 녹이 고 pH 7.6 조정. DdH2O l. 1의 최종 볼륨을 추가 10 x 재고 1 일부 ddH2o.의 9 부분 혼합 1 x 솔루션에 대 한</li>
	</ol>
</li>
	<li>기본 β 아 밀 로이드 항 체 희석 6E10 1:1,000와 함께 1 시간에 대 한 막 품 어 그리고 이차 항 체 염소와 실 온에서 1 h에 대 한 반대로 마우스 IgG HRP 공액 희석 1:10, 000.</li>
	<li>막 Luminata 형광 시 약의 1 mL를 사용 하 여 개발 및 단계 5.2에서에서 설명한 densitometric 분석 하 여 밴드를 계량 합니다.</li>
</ol>5. 데이터 분석
<ol><li>FC에서 얻은 데이터를 분석 하려면 표시 의미 형광 강도 (MFI) 테이블을 만듭니다와 그 해당 표준 오류 또는 GFP 형광 및 산화 스트레스 수준에 대 한 차이 (CV)의 계수 중간 형광.<ol>
<li>관리자 탭 및 통계 아이콘 각 채널에 필요한 통계 데이터를 사용자 지정을 클릭 합니다. 참고: 비교할 때 단백질 이체, 접이식 배경 또는 해상도 통계 (RD)에 형광 값 데이터 변환: <img alt="Equation 1" src="/files/ftp_upload/57470/57470eq1.jpg"> 이 통계에서 평균 샘플 문제 샘플의 평균 형광, 평균 컨트롤은 컨트롤을 사용 하는 셀의 평균 형광 이며 SD는 평균 형광의 표준 편차. RD 요소 MFI 값 보다 더 정확한 인덱스는 그것 뿐만 아니라 샘플 뿐만 아니라 데이터의 확산을 위한 계정 사이의 차이 계산 합니다. 이 계산은 시간이 지남에 수행 다른 실험 데이터를 비교 하는 때 특히 적합 합니다. 일단는 RDs를 계산 통계 시험의 사용은 단백질 이체의 관찰 된 차이점의 중요성을 확인 하는 것이 좋습니다.</li>
	</ol>
</li>
	<li>단백질 immunodetection에 대 한 재조합 단백질 수준 서쪽 오 점 ImageJ 소프트웨어를 사용 하 여 계량.<ol>
<li>Densitometry 분석 하기 전에 개발 된 막의 원래 raw 이미지를 JPEG 파일 형식와 회색조 모드 변환.</li>
		<li>회색값 의미 분석 메뉴의 설정 측정 섹션을 조정 합니다.</li>
		<li>ImageJ에서 사각형 도구를 클릭 하 고 밴드 densitometry 분석에 대 한 일관 된 크기와 관심 (ROI)의 영역을 정의. 만든된 사각형 프레임 안에 막 이미지에 각 밴드 센터 고 측정 Ctrl + M (측정 명령)를 사용 하 여 하나 하나를 기록 합니다.</li>
		<li>동일한 투자 수익 영역을 적용 하는 각 밴드에 인접 한 로컬 백그라운드를 측정 합니다. 측정 후 각각의 개별 밴드에서 해당 로컬 백그라운드를 뺍니다.</li>
	</ol>
</li>
</ol>

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다양 한 질병 세포 예금6,,78,33으로 misfolded 단백질의 축적에 연결 된다. 많은 노력 계정 단백질 농도를 고려 하지 않습니다, 계산 방법을 사용 하 여 이러한 질병의 발병을 트리거하는 분자 메커니즘을 해명 되었습니다 또는 생체 외에서 접근, 어떤 단백질 농도 반응 동안 상수 남아 있습니다. 그...

Proteostasis 셀 체력과 노화 프로세스의 근본적인 결정 이다. 셀, 네트워크는 올바른 refolding misfolded 단백질 conformers의 보호자 또는 그들의 타겟된 베이스로 몇 가지 잘 보존 메커니즘1 보장 하기 위한 정교한 단백질 품질 관리에 의해 단백질 항상성 유지 ,2,3,,45. 연구의 많은 발병과 인간의 질병의 광범위 한 범위와 proteostasis, 단백질 misfolding 및 집계의 실패의 진행 사이의 링크에 지원을 제공 합니다. 예를 들어, 단백질 예금의 존재는 많은 신경 퇴행 성 질환, 알츠하이머병, 파 킨 슨 병, 등, 헌팅턴의 질병6,7,8의 병 적인 특징을 간주 됩니다. prionogenic 질병, 고 퇴행 성 비 amyloidoses9. 그것은 집계 반응에서 초기 oligomeric 및 protofibrillar 어셈블리 붐비는 셀룰러 환경10다른 단백질 들과 탈 선 상호 작용을 설정 하는 세포 독성의 주요 elicitors는 건의 되었다. 또한, 전파 하는 그들의 독성 효과11,12셀 사이의 단백질 포함 (PI)를 전송할 수 있습니다. 따라서, PI의 대형 셀, 어디 처리 될 수 있다 또는 주요 부작용 없이 축적에서 특정 위치에 위험한 집계 된 종의 존재를 제한 하는 해독 메커니즘 구성 실제로 수 있습니다. 수 있습니다. 13 , 14.
표준 체 외에서 생 화 확 적인 접근 집계 반응와 그들의 속성15,16종에 대 한 중요 한 통찰력을 제공 했다. 그러나, 이러한 분석 실험에서 사용 하는 조건 셀 내에 발생 하는 명확 하 게 다른 있으며, 따라서 그들의 생리 적인 관련성 질문. 세포질 통로 단백질 품질 관리, autophagy, 진핵생물19,20,21 중 세포질 산화 환 원 상태17,18 의 규제 등의 주목할 만한 절약 때문에 ,,2223, 신진 효 모 Saccharomyces cerevisiae (S. cerevisiae) 단백질 집단의 분자 결정 요인 연구 특권 간단한 세포 모델 나왔다 그리고 생물학으로 관련 환경24,,2526에 관련 된 세포 독성 영향.
단백질 집계 성향 본질적으로 기본 순서로 인코딩 기능입니다. 따라서, 아 밀 로이드 같은 구조의 형성 예측할 수 있습니다 식별 및 집계 추진의 힘의 평가에 따라 지역 polypeptides27에. 그러나, 예측 단백질 시퀀스의 생체 외에서 집계 속성 bioinformatic 알고리즘의 성공에도 불구 하 고 그들은 여전히 이러한 경향 vivo에서 세포 독성 영향으로 번역 하는 어떻게 예측까지 있습니다. 체계적인 방식으로 주어진된 단백질의 집계 상태 및 그것의 관련 된 세포 손상을 사이 연결 하는 연구는 전산이 한계를 우회 하는 데 도움이 있습니다. 이 연결은 현재 연구, 아 밀 로이드 β 펩 티 드 Aβ42 단일 잔류물에만 서로 다른 하지만 집계 경향 vivo에서28의 연속 범위 표시의 이체의 큰 세트의 활용에서 해결 됩니다. 특히, 구조적 종 효 모 세포에서 집계 하기 쉬운 단백질에 의해 elicited 산화 손상에 대 한 회계를 식별 하는 FC 기반 접근 방식을 설명 합니다. 방법론에는 단순, 높은 처리 능력, 그리고 정확한 양적 측정 등 많은 이점을 제공합니다. 이 방법은 PI 놀이 산화 스트레스에 대 한 보호 역할을 확인 가능 합니다.

<table><tbody><tr><td>Yeast cells BY4741&amp;nbsp;</td><td>ATCC</td><td>201388</td><td>Genotype: MATa his3&amp;Delta;1 leu2&amp;Delta;0 met15&amp;Delta;0 ura3&amp;Delta;0</td></tr><tr><td>pESC(-Ura) plasmid&amp;nbsp;</td><td>Agilent Genomics</td><td>217454</td><td>Yeast expression plasmid with a Gal promotor. Selectable marker URA3</td></tr><tr><td>Yeast Synthetic Drop-out Medium Supplements</td><td>Sigma</td><td>Y1501</td><td>Powder</td></tr><tr><td>Yeast Nitrogen Base Without Amino Acids</td><td>Sigma</td><td>Y0626</td><td>Powder</td></tr><tr><td>Raffinose</td><td>Sigma</td><td>R7630</td><td>Powder</td></tr><tr><td>Glucose</td><td>Sigma</td><td>G7021</td><td>Powder</td></tr><tr><td>Galactose</td><td>Sigma</td><td>G0750</td><td>Powder</td></tr><tr><td>Phosphate Buffered Saline (PBS)</td><td>Fisher Scientific</td><td>BP3991&amp;nbsp;</td><td>Solution 10X</td></tr><tr><td>CellROX Deep Red Reagent&amp;nbsp;</td><td>Life Technologies</td><td>C10422</td><td>Free radical cell-permeant fluorescent sensor, non-fluorescent while in a reduced state, and exhibits bright fluorescence upon oxidation by reactive oxygen species (ROS), with absorption/emission maxima at 644/665 nm.&amp;nbsp;</td></tr><tr><td>Y-PER protein extraction reagent&amp;nbsp;</td><td>Thermo Scientific</td><td>78990</td><td>Liquid cell lysis buffer</td></tr><tr><td>Acrylamide/Bis-acrylamide</td><td>Sigma</td><td>A6050</td><td>Solution</td></tr><tr><td>Bradford dye reagent</td><td>Bio-Rad&amp;nbsp;</td><td>5000205</td><td>Dye reagent for one-step determination of protein concentration</td></tr><tr><td>&amp;beta;-amyloid antibody 6E10&amp;nbsp;</td><td>BioLegend</td><td>803001</td><td>Mouse IgG1. The epitope lies within amino acids 3-8 of beta amyloid (EFRHDS).</td></tr><tr><td>Goat anti-mouse IgG-HRP conjugate&amp;nbsp;</td><td>Bio-Rad</td><td>1721011</td><td></td></tr><tr><td>Membrane Immobilon-P, PVDF</td><td>Millipore</td><td>IPVH00010</td><td></td></tr><tr><td>Luminata forte</td><td>Merk</td><td>WBLUF0100</td><td>Premixed, ready to use chemiluminescent HRP detection reagent</td></tr><tr><td>Phenylmethanesulfonyl fluoride solution (PMSF)</td><td>Sigma</td><td>93482</td><td>Protease inhibitor. Dissolved at 0.1 M in ethanol</td></tr><tr><td>FACSCanto flow cytometer&amp;nbsp;</td><td>BD Biosciences</td><td>657338</td><td>Equipped with a 488&amp;nbsp;nm blue laser for the detection of GFP, and 635&amp;nbsp;nm red laser / 530/30 nm BP filter and 660/20 BP filter</td></tr><tr><td>Mini Trans-Blot Electrophoresis Transfer cell</td><td>Bio-Rad</td><td>1703930</td><td>Protein transference system</td></tr><tr><td>Mini-PROTEAN Tetra Handcast Systems</td><td>Bio-Rad</td><td>1658000FC</td><td>Electrophoresis system</td></tr></tbody></table>

evaluation of the impact of protein aggregation on cellular oxidative stress in yeast

단백질 misfolding 및 녹말 체 conformations로 집계 발병 및 여러 신경 퇴행 성 질환의 진행에 관련 되어있다. 그러나, 여전히 약간의 정보는 어떻게 불용 성 단백질에 대 한 집계는 그들의 독성 효과 비보를 발휘. 단순 간결한 및 진 핵 모형 유기 체, 박테리아와 효 모, 등 세포내 녹말 체 형성, 집계 전파 및 독성 뒤에 있는 메커니즘의 우리의 현재 이해에 크게 기여 했다. 이 프로토콜에서 효를 사용 하 여 단백질의 형성 및 세포질 산화 스트레스에 미치는 영향 관계를 해 부 모델로 설명 합니다. 메서드는 amyloidogenic 단백질의 세포내 수용 성/집계 상태 감지 세포 산화 손상 cytometry (FC)을 사용 하 여 식에서 결과의 정량화 결합 합니다. 이 방법은 간단 하 고 빠르며, 양적입니다. 연구는 그들의 각각 고유한 집계 경향으로 아 밀 로이드 β 펩 티 드 이체의 큰 세트에 기인한 세포질 산화 스트레스를 연관 하 여 기법을 보여 줍니다.

이 프로토콜 어디 Phe19은 모든 자연 proteinogenic 아미노산28변경 되었습니다 Aβ42 펩 티 드의 20 이체의 컬렉션을 사용 하는 방법을 설명 합니다. 이 단백질의 이론적인 집계 경향 두 다른 bioinformatic 알고리즘 (AGGRESCAN와 탱고31,32)를 사용 하 여 분석할 수 있습니다. 두 경우 모두에서이 분석 집계 추세, ascribing, 일반?...

Watch this Scientific Journal Video about Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast at JoVE.com

Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast

효 모 세포 산화 스트레스에 단백질 집단의 영향 평가

단백질 집계 세포 산화 스트레스 elicits. 이 프로토콜 amyloidogenic 단백질의 세포내 주와 관련 된, cytometry 사용 하 여 산화 스트레스 모니터링 하는 방법을 설명 합니다. 접근은 아 밀 로이드 β 펩 티 드의 가용성과 집계 경향이 이체의 동작을 연구 하는 데 사용 됩니다.

Protein misfolding and aggregation into amyloid conformations have been related to the onset and progression of several neurodegenerative diseases. ...

evaluation-impact-protein-aggregation-on-cellular-oxidative-stress

Research

JoVE Journal

Biochemistry

7.2K 조회수.  Universitat Autònoma de Barcelona. 단백질 집계 세포 산화 스트레스 elicits. 이 프로토콜 amyloidogenic 단백질의 세포내 주와 관련 된, cytometry 사용 하 여 산화 스트레스 모니터링 하는 방법을 설명 합니다. 접근은 아 밀 로이드 β 펩 티 드의 가용성과 집계 경향이 이체의 동작을 연구 하는 데 사용 됩니다.

비디오: Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast

Defining Hsp33's Redox-regulated Chaperone Activity and Mapping Conformational Changes on Hsp33 Using Hydrogen-deuterium Exchange Mass Spectrometry

Living organisms regularly need to cope with fluctuating environments during their life cycle, including changes in temperature, pH, the accumulation of reactive oxygen species, and more. These fluctuations can lead to a widespread protein unfolding, aggregation, and cell death. Therefore, cells have evolved a dynamic and stress-specific network of molecular chaperones, which maintain a "healthy" proteome during stress conditions. ATP-independent chaperones constitute one major class of molecular chaperones, which serve as first-line defense molecules, protecting against protein aggregation in a stress-dependent manner. One feature these chaperones have in common is their ability to utilize structural plasticity for their stress-specific activation, recognition, and release of the misfolded client. 
In this paper, we focus on the functional and structural analysis of one such intrinsically disordered chaperone, the bacterial redox-regulated Hsp33, which protects proteins against aggregation during oxidative stress. Here, we present a toolbox of diverse techniques for studying redox-regulated chaperone activity, as well as for mapping conformational changes of the chaperone, underlying its activity. Specifically, we describe a workflow which includes the preparation of fully reduced and fully oxidized proteins, followed by an analysis of the chaperone anti-aggregation activity in vitro using light-scattering, focusing on the degree of the anti-aggregation activity and its kinetics. To overcome frequent outliers accumulated during aggregation assays, we describe the usage of Kfits, a novel graphical tool which allows easy processing of kinetic measurements. This tool can be easily applied to other types of kinetic measurements for removing outliers and fitting kinetic parameters. To correlate the function with the protein structure, we describe the setup and workflow of a structural mass spectrometry technique, hydrogen-deuterium exchange mass spectrometry, that allows the mapping of conformational changes on the chaperone and substrate during different stages of Hsp33 activity. The same methodology can be applied to other protein-protein and protein-ligand interactions.

One of the most challenging stress conditions that organisms encounter during their lifetime involves the accumulation of oxidants. During oxidative stress, cells heavily rely on molecular chaperones. Here, we present methods used to investigate the redox-regulated anti-aggregation activity, as well as to monitor structural changes governing the chaperone function using HDX-MS.

Hsp33의 Redox 규제 보호자 활동을 정의 하 고 수소 중수소 교환 질량 분석을 사용 하 여 Hsp33에 구조적 변화를 매핑

Living organisms regularly need to cope with fluctuating environments during their life cycle, including changes in temperature, pH, the accumulation of ...

연구

생화학

Extraction and Visualization of Protein Aggregates after Treatment of Escherichia coli with a Proteotoxic Stressor

The exposure of living organisms to environmental and cellular stresses often causes disruptions in protein homeostasis and can result in protein aggregation. The accumulation of protein aggregates in bacterial cells can lead to significant alterations in the cellular phenotypic behavior, including a reduction in growth rates, stress resistance, and virulence. Several experimental procedures exist for the examination of these stressor-mediated phenotypes. This paper describes an optimized assay for the extraction and visualization of aggregated and soluble proteins from different Escherichia coli strains after treatment with a silver-ruthenium-containing antimicrobial. This compound is known to generate reactive oxygen species and causes widespread protein aggregation. 
The method combines a centrifugation-based separation of protein aggregates and soluble proteins from treated and untreated cells with subsequent separation and visualization by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Coomassie staining. This approach is simple, fast, and allows a qualitative comparison of protein aggregate formation in different E. coli strains. The methodology has a wide range of applications, including the possibility to investigate the impact of other proteotoxic antimicrobials on in vivo protein aggregation in a wide range of bacteria. Moreover, the protocol can be used to identify genes that contribute to increased resistance to proteotoxic substances. Gel bands can be used for the subsequent identification of proteins that are particularly prone to aggregation.

Extraction and Visualization of Protein Aggregates after Treatment of Escherichia coli with a Proteotoxic Stressor

This protocol describes the extraction and visualization of aggregated and soluble proteins from Escherichia coli after treatment with a proteotoxic antimicrobial. Following this procedure allows a qualitative comparison of protein aggregate formation in vivo in different bacterial strains and/or between treatments.

프로테오독성 스트레스로 대장균 치료 후 단백질 골재의 추출 및 시각화

The exposure of living organisms to environmental and cellular stresses often causes disruptions in protein homeostasis and can result in protein ...

Microarray Analysis for Saccharomyces cerevisiae

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen peroxide (H2O2), an oxidizing agent. In the experiment, yeast is grown for 48 hours in 1/2X YPD broth containing 3X glucose. The culture is split into a control and treated group. The experiment culture is treated with 0.5 mM H2O2 in Hanks Buffered Saline (HBSS) for 1 hour. The control culture is treated with HBSS only. Total RNA is extracted from both cultures and is converted to a biotin-labeled cRNA product through a multistep process. The final synthesis product is taken back to the UVM Microarray Core Facility and hybridized to the Affymetrix yeast GeneChips. The resulting gene expression data are uploaded into bioinformatics data analysis software.

Microarray Analysis for Saccharomyces cerevisiae

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen peroxide (H2O2), an oxidizing agent.

Microarray 분석을위한 Saccharomyces cerevisiae</em

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen ...

생물학

Growth Assays to Assess Polyglutamine Toxicity in Yeast

Protein misfolding is associated with many human diseases, particularly neurodegenerative diseases, such as Alzheimer&#x2019;s disease, Parkinson's disease, and Huntington's disease 1. Huntington's disease (HD) is caused by the abnormal expansion of a polyglutamine (polyQ) region within the protein huntingtin. The polyQ-expanded huntingtin protein attains an aberrant conformation (i.e. it misfolds) and causes cellular toxicity 2. At least eight further neurodegenerative diseases are caused by polyQ-expansions, including the Spinocerebellar Ataxias and Kennedy&#x2019;s disease 3.
The model organism yeast has facilitated significant insights into the cellular and molecular basis of polyQ-toxicity, including the impact of intra- and inter-molecular factors of polyQ-toxicity, and the identification of cellular pathways that are impaired in cells expressing polyQ-expansion proteins 3-8. Importantly, many aspects of polyQ-toxicity that were found in yeast were reproduced in other experimental systems and to some extent in samples from HD patients, thus demonstrating the significance of the yeast model for the discovery of basic mechanisms underpinning polyQ-toxicity. 
A direct and relatively simple way to determine polyQ-toxicity in yeast is to measure growth defects of yeast cells expressing polyQ-expansion proteins. This manuscript describes three complementary experimental approaches to determine polyQ-toxicity in yeast by measuring the growth of yeast cells expressing polyQ-expansion proteins. The first two experimental approaches monitor yeast growth on plates, the third approach monitors the growth of liquid yeast cultures using the BioscreenC instrument. 
Furthermore, this manuscript describes experimental difficulties that can occur when handling yeast polyQ models and outlines strategies that will help to avoid or minimize these difficulties. The protocols described here can be used to identify and to characterize genetic pathways and small molecules that modulate polyQ-toxicity. Moreover, the described assays may serve as templates for accurate analyses of the toxicity caused by other disease-associated misfolded proteins in yeast models.

This manuscript describes three complementary protocols for assessing the toxicity of polyglutamine (polyQ)-expansion proteins in the yeast Saccharomyces cerevisiae. These protocols can easily be modified to monitor the toxicity of other misfolded proteins in yeast.

성장 Assays은 효모에서 Polyglutamine 독성을 평가하기 위해

Protein misfolding is associated with many human diseases, particularly neurodegenerative diseases, such as Alzheimer&#x2019;s disease, Parkinson's ...

4D Imaging of Protein Aggregation in Live Cells

One of the key tasks of any living cell is maintaining the proper folding of newly synthesized proteins in the face of ever-changing environmental conditions and an intracellular environment that is tightly packed, sticky, and hazardous to protein stability1. The ability to dynamically balance protein production, folding and degradation demands highly-specialized quality control machinery, whose absolute necessity is observed best when it malfunctions. Diseases such as ALS, Alzheimer's, Parkinson's, and certain forms of Cystic Fibrosis have a direct link to protein folding quality control components2, and therefore future therapeutic development requires a basic understanding of underlying processes. Our experimental challenge is to understand how cells integrate damage signals and mount responses that are tailored to diverse circumstances.
The primary reason why protein misfolding represents an existential threat to the cell is the propensity of incorrectly folded proteins to aggregate, thus causing a global perturbation of the crowded and delicate intracellular folding environment1. The folding health, or "proteostasis," of the cellular proteome is maintained, even under the duress of aging, stress and oxidative damage, by the coordinated action of different mechanistic units in an elaborate quality control system3,4. A specialized machinery of molecular chaperones can bind non-native polypeptides and promote their folding into the native state1, target them for degradation by the ubiquitin-proteasome system5, or direct them to protective aggregation inclusions6-9.
In eukaryotes, the cytosolic aggregation quality control load is partitioned between two compartments8-10: the juxtanuclear quality control compartment (JUNQ) and the insoluble protein deposit (IPOD) (Figure 1 - model). Proteins that are ubiquitinated by the protein folding quality control machinery are delivered to the JUNQ, where they are processed for degradation by the proteasome. Misfolded proteins that are not ubiquitinated are diverted to the IPOD, where they are actively aggregated in a protective compartment.
Up until this point, the methodological paradigm of live-cell fluorescence microscopy has largely been to label proteins and track their locations in the cell at specific time-points and usually in two dimensions. As new technologies have begun to grant experimenters unprecedented access to the submicron scale in living cells, the dynamic architecture of the cytosol has come into view as a challenging new frontier for experimental characterization. We present a method for rapidly monitoring the 3D spatial distributions of multiple fluorescently labeled proteins in the yeast cytosol over time. 3D timelapse (4D imaging) is not merely a technical challenge; rather, it also facilitates a dramatic shift in the conceptual framework used to analyze cellular structure.
We utilize a cytosolic folding sensor protein in live yeast to visualize distinct fates for misfolded proteins in cellular aggregation quality control, using rapid 4D fluorescent imaging. The temperature sensitive mutant of the Ubc9 protein10-12 (Ubc9ts) is extremely effective both as a sensor of cellular proteostasis, and a physiological model for tracking aggregation quality control. As with most ts proteins, Ubc9ts is fully folded and functional at permissive temperatures due to active cellular chaperones. Above 30 &deg;C, or when the cell faces misfolding stress, Ubc9ts misfolds and follows the fate of a native globular protein that has been misfolded due to mutation, heat denaturation, or oxidative damage. By fusing it to GFP or other fluorophores, it can be tracked in 3D as it forms Stress Foci, or is directed to JUNQ or IPOD.

Cellular viability depends on timely and efficient management of protein misfolding. Here we describe a method for visualizing the different potential fates of a misfolded protein: refolding, degradation, or sequestration in inclusions. We demonstrate the use of a folding sensor, Ubc9ts, for monitoring proteostasis and aggregation quality control in live cells using 4D microscopy.

라이브 셀의 단백질 응집체의 4D 영상

One of the key tasks of any living cell is maintaining the proper folding of newly synthesized proteins in the face of ever-changing environmental ...

Coupled Assays for Monitoring Protein Refolding in Saccharomyces cerevisiae

Proteostasis, defined as the combined processes of protein folding/biogenesis, refolding/repair, and degradation, is a delicate cellular balance that must be maintained to avoid deleterious consequences 1. External or internal factors that disrupt this balance can lead to protein aggregation, toxicity and cell death. In humans this is a major contributing factor to the symptoms associated with neurodegenerative disorders such as Huntington's, Parkinson's, and Alzheimer's diseases 10. It is therefore essential that the proteins involved in maintenance of proteostasis be identified in order to develop treatments for these debilitating diseases. This article describes techniques for monitoring in vivo protein folding at near-real time resolution using the model protein firefly luciferase fused to green fluorescent protein (FFL-GFP). FFL-GFP is a unique model chimeric protein as the FFL moiety is extremely sensitive to stress-induced misfolding and aggregation, which inactivates the enzyme 12. Luciferase activity is monitored using an enzymatic assay, and the GFP moiety provides a method of visualizing soluble or aggregated FFL using automated microscopy. These coupled methods incorporate two parallel and technically independent approaches to analyze both refolding and functional reactivation of an enzyme after stress. Activity recovery can be directly correlated with kinetics of disaggregation and re-solubilization to better understand how protein quality control factors such as protein chaperones collaborate to perform these functions. In addition, gene deletions or mutations can be used to test contributions of specific proteins or protein subunits to this process. In this article we examine the contributions of the protein disaggregase Hsp104 13, known to partner with the Hsp40/70/nucleotide exchange factor (NEF) refolding system 5, to protein refolding to validate this approach.

Coupled Assays for Monitoring Protein Refolding in Saccharomyces cerevisiae

This article describes the use of a firefly luciferase-GFP fusion protein to investigate in vivo protein folding in Saccharomyces cerevisiae. Using this reagent, refolding of a model heat-denatured protein can be monitored simultaneously by fluorescence microscopy and an enzymatic assay to probe the roles of proteostasis network components in protein quality control.

의 모니터링 단백질 접힘에 대한 결합 분석 실험<em&gt; 사카 cerevisiae의</em

Proteostasis, defined as the combined processes of protein folding/biogenesis, refolding/repair, and degradation, is a delicate cellular balance that must ...

Isolating Potentiated Hsp104 Variants Using Yeast Proteinopathy Models

Many protein-misfolding disorders can be modeled in the budding yeast Saccharomyces cerevisiae. Proteins such as TDP-43 and FUS, implicated in amyotrophic lateral sclerosis, and &#945;-synuclein, implicated in Parkinson&#8217;s disease, are toxic and form cytoplasmic aggregates in yeast. These features recapitulate protein pathologies observed in patients with these disorders. Thus, yeast are an ideal platform for isolating toxicity suppressors from libraries of protein variants. We are interested in applying protein disaggregases to eliminate misfolded toxic protein conformers. Specifically, we are engineering Hsp104, a hexameric AAA+ protein from yeast that is uniquely capable of solubilizing both disordered aggregates and amyloid and returning the proteins to their native conformations. While Hsp104 is highly conserved in eukaryotes and eubacteria, it has no known metazoan homologue. Hsp104 has only limited ability to eliminate disordered aggregates and amyloid fibers implicated in human disease. Thus, we aim to engineer Hsp104 variants to reverse the protein misfolding implicated in neurodegenerative disorders. We have developed methods to screen large libraries of Hsp104 variants for suppression of proteotoxicity in yeast. As yeast are prone to spontaneous nonspecific suppression of toxicity, a two-step screening process has been developed to eliminate false positives. Using these methods, we have identified a series of potentiated Hsp104 variants that potently suppress the toxicity and aggregation of TDP-43, FUS, and &#945;-synuclein. Here, we describe this optimized protocol, which could be adapted to screen libraries constructed using any protein backbone for suppression of toxicity of any protein that is toxic in yeast.

Yeast proteinopathy models are valuable tools to assess the toxicity and aggregation of proteins implicated in disease. Here, we present methods for screening Hsp104 variant libraries for toxicity suppressors. This protocol could be adapted to screen any protein library for toxicity suppressors of any protein that is toxic in yeast.

효력을 더 Hsp104 변종 사용 효모 Proteinopathy 모델을 분리

Many protein-misfolding disorders can be modeled in the budding yeast Saccharomyces cerevisiae. Proteins such as TDP-43 and FUS, implicated in amyotrophic ...

Cycloheximide Chase Analysis of Protein Degradation in Saccharomyces cerevisiae

Regulation of protein abundance is crucial to virtually every cellular process. Protein abundance reflects the integration of the rates of protein synthesis and protein degradation. Many assays reporting on protein abundance (e.g., single-time point western blotting, flow cytometry, fluorescence microscopy, or growth-based reporter assays) do not allow discrimination of the relative effects of translation and proteolysis on protein levels. This article describes the use of cycloheximide chase followed by western blotting to specifically analyze protein degradation in the model unicellular eukaryote, Saccharomyces cerevisiae (budding yeast). In this procedure, yeast cells are incubated in the presence of the translational inhibitor cycloheximide. Aliquots of cells are collected immediately after and at specific time points following addition of cycloheximide. Cells are lysed, and the lysates are separated by polyacrylamide gel electrophoresis for western blot analysis of protein abundance at each time point. The cycloheximide chase procedure permits visualization of the degradation kinetics of the steady state population of a variety of cellular proteins. The procedure may be used to investigate the genetic requirements for and environmental influences on protein degradation.

Cycloheximide Chase Analysis of Protein Degradation in Saccharomyces cerevisiae

Protein abundance reflects the rates of both protein synthesis and protein degradation. This article describes the use of cycloheximide chase followed by western blotting to analyze protein degradation in the model unicellular eukaryote, Saccharomyces cerevisiae (budding yeast).

단백질 분해에서의 사이클로 헥시 미드 체이스 분석<em&gt; 사카로 마이 세스 세레 비지에</em

Regulation of protein abundance is crucial to virtually every cellular process. Protein abundance reflects the integration of the rates of protein ...

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans

In the last decades, the prevalence of neurodegenerative disorders, such as Alzheimer's disease (AD) and Parkinson's disease (PD), has grown. These age-associated disorders are characterized by the appearance of protein aggregates with fibrillary structure in the brains of these patients. Exactly why normally soluble proteins undergo an aggregation process remains poorly understood. The discovery that protein aggregation is not limited to disease processes and instead part of the normal aging process enables the study of the molecular and cellular mechanisms that regulate protein aggregation, without using ectopically expressed human disease-associated proteins. Here we describe methodologies to examine inherent protein aggregation in Caenorhabditis elegans through complementary approaches. First, we examine how to grow large numbers of age-synchronized C. elegans to obtain aged animals and we present the biochemical procedures to isolate highly-insoluble-large aggregates. In combination with a targeted genetic knockdown, it is possible to dissect the role of a gene of interest in promoting or preventing age-dependent protein aggregation by using either a comprehensive analysis with quantitative mass spectrometry or a candidate-based analysis with antibodies. These findings are then confirmed by in vivo analysis with transgenic animals expressing fluorescent-tagged aggregation-prone proteins. These methods should help clarify why certain proteins are prone to aggregate with age and ultimately how to keep these proteins fully functional.

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans

The goal of the method presented here is to explore protein aggregation during normal aging in the model organism C. elegans. The protocol represents a powerful tool to study the highly insoluble large aggregates that form with age and to determine how changes in proteostasis impact protein aggregation.

꼬마 선 충 나이 연구 변화 내재 단백질 집계에 방법

In the last decades, the prevalence of neurodegenerative disorders, such as Alzheimer's disease (AD) and Parkinson's disease (PD), has grown. These ...

Quantification of Insoluble Protein Aggregation in Caenorhabditis elegans during Aging with a Novel Data-Independent Acquisition Workflow

We and others have shown that the aging process results in a proteome-wide accumulation of insoluble proteins. Knocking down genes encoding the insoluble proteins over 40% of the time results in an extension of the lifespan in C. elegans, suggesting that many of these proteins are key determinants of the aging process. Isolation and quantitative identification of these insoluble proteins are crucial to understand key biological processes that occur during aging. Here, we present a modified and improved protocol that details how to extract and isolate the SDS-insoluble proteins (insolublome) from C. elegans more efficiently to streamline mass spectrometric workflows via a novel label-free quantitative proteomics analysis. This improved protocol utilizes a highly efficient sonicator for worm lysis that greatly increases efficiency for protein extraction and allows us to use significantly less starting material (approximately 3,000 worms) than in previous protocols (typically using at least 40,000 worms). Subsequent quantitative proteomic analysis of the insolublome was performed using data-dependent acquisition (DDA) for protein discovery and identification and data-independent acquisition (DIA) for comprehensive and more accurate protein quantification. Bioinformatic analysis of quantified proteins provides potential candidates that can be easily followed up with other molecular methods in C. elegans. With this workflow, we routinely identify more than 1000 proteins and quantify more than 500 proteins. This new protocol enables efficient compound screening with C. elegans. Here, we validated and applied this improved protocol to wild-type C. elegans N2-Bristol strain and confirmed that aged day-10 N2 worms showed greater accumulation of the insolublome than day-2 young worms.

Quantification of Insoluble Protein Aggregation in Caenorhabditis elegans during Aging with a Novel Data-Independent Acquisition Workflow

This novel workflow efficiently extracts and isolates SDS-insoluble proteins (insolublome) from Caenorhabditis elegans with minimal starting material for quantitative differential proteomic analysis. The protocol uses a comprehensive data-independent acquisition mass spectrometry analysis to quantify the insolublome and bioinformatic analysis to gain biological insights into aging mechanisms and pathologies.

We and others have shown that the aging process results in a proteome-wide accumulation of insoluble proteins. Knocking down genes encoding the insoluble ...

효 모 세포 산화 스트레스에 단백질 집단의 영향 평가

요약

더 많은 비디오 탐색

이 비디오의 챕터

Hsp33의 Redox 규제 보호자 활동을 정의 하 고 수소 중수소 교환 질량 분석을 사용 하 여 Hsp33에 구조적 변화를 매핑

프로테오독성 스트레스로 대장균 치료 후 단백질 골재의 추출 및 시각화

Microarray 분석을위한 Saccharomyces cerevisiae

성장 Assays은 효모에서 Polyglutamine 독성을 평가하기 위해

라이브 셀의 단백질 응집체의 4D 영상

의 모니터링 단백질 접힘에 대한 결합 분석 실험

효력을 더 Hsp104 변종 사용 효모 Proteinopathy 모델을 분리

단백질 분해에서의 사이클로 헥시 미드 체이스 분석

꼬마 선 충 나이 연구 변화 내재 단백질 집계에 방법

Quantification of Insoluble Protein Aggregation in Caenorhabditis elegans during Aging with a Novel Data-Independent Acquisition Workflow