필자는 MilliporeSigma, Philip J. Morrissey 및 Sherree L. Friend의 동료들에게 수년 간 도움과지도를 해주신 것에 대해 감사드립니다. 이 책을 편집하는 데 도움을 준 IDEAS 소프트웨어의 BDC3 기능 , Ryan P. Jessup, 촬영 당일 도움을 준 Raymond Kong 및 특별 감사의 도움을 주신 Vidya Venkatachalam 및 Bryan R. Davidson에게도 감사드립니다. 메이크업 아티스트 Cynthia Xamonthiene.

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저는이 연구에서 사용 된 Amnis 브랜드 ImageStream의 제작자 인 MilliporeSigma에 고용되었습니다.

이 분석을 수행 할 때 고려해야 할 몇 가지 사항이 있습니다. 적절한 컨트롤 샘플을 갖는 것이 중요합니다. 이 실험을 위해 두 개의 다른 컨트롤이 사용되었습니다 : Control + Control + Chloroquine. Control 샘플을 사용하여 영역의 임계 값을 설정했습니다. 그것은 리소좀 분해를 멈추지 않으면 서 autophagy의 기초 수준을 나타내며 Starved 샘플의 컨트롤입니다. 그러나, Control 샘플은 Starved + Chloroquine 샘플의 결과와 비교할 수있는 적절한 컨트롤이 아닙니다. 왜냐하면 클로로퀸 자체가 컨트롤 샘플에 영향을 미치기 때문입니다. 그러므로 Control + Chloroquine 샘플이 필요했습니다. autophagy에 대한 분석을 수행하기 전에 하나 이상의 셀이 있거나 이미지가있는 경우 결과에 영향을 줄 수 있으므로 포커스가있는 단일 셀 ( 즉, 60보다 큰 그래디언트 RMS)에서만 분석 / 게이트를 분석하는 것이 중요합니다. 초점없는. 자궁이 중요하다.es와 lysosome은 적절한 spot count와 BDC3 분석에 초점을 맞추고있다. Apoptotic 세포는 autophagy 분석 전에 제거해야합니다, 그들은 결과를 왜곡 할 수 있으므로 포함되어서는 안됩니다. 세 가지 마커 ( 즉, LC3, p62 및 LAMP1) 모두에 대해 적절한 염색이 있어야합니다. 예를 들어, 3 개의 마커 모두는 세포 내 (intracellular)이며 점선 신호가 있어야합니다. 신호가 점을 찍지 않았거나 세포 표면에 있다면 염색이 적절하지 않아 실험 / 염색을 다시해야합니다. 또한 BDC3가 정확하려면 3 개의 형광 마커 모두에 밝은 셀을 게이트하는 것이 필수적입니다. 비특이적 결합, 이미징 인공물 및 / 또는 소음에 대한 BDC3 측정을 방지하려면 양성 반응에 대한 게이팅이 필요합니다. BDC3은 실제 신호가 아닌 인공물을 증폭시킬 수 있기 때문에 이것은 중요합니다. BDC3은 밝은 양성 반응에서만 수행 할 수 있으므로 많은 세포가 최종 분석에 포함되지 않을 수 있습니다. 이것은 특별하다.LC3, p62 및 / 또는 LAMP1의 축적이없는 대조군 세포에 대해서는 사실이다. 따라서,이 분석법의 한계는 BDC3가 세 가지 마커 모두에 대해 양성인 세포를 검사한다는 것인데, 이는 모든 자동 운동 실험에 적합하지 않을 수 있습니다. 이전에 15 , 16 , 17 , 20 , 21 , 22 , 23 , 24 , 25 , 26으로 보고 된 BDS와 마찬가지로 BDC3만으로는 공동 위치를 결정하는 autophagy organelles의 수를 고려하지 않았기 때문에 autophagosomes의 수에있는 가변성의. 따라서, Rajan et al. 고용되었다. bivariate plot을 보면, if세포는 LC3, p62 및 LAMP1에 대해 양성이어야합니다. 0 점이있는 셀이 왜 그렇게 많습니까? 이는 LC3 신호가 동일 위치에 충분히 밝을 수 있기 때문에 피크 마스크 (피크 (M11, Ch11-LC3-AF647, 밝기, 4))로 설정된 임계 값을 충족시키지 못하기 때문입니다 자리. 여기에 제시된 프로토콜은 LC3 puncta를 계산하기 위해 MIFC를 사용하였고, autophagic 플럭스를 측정하기 위해 세 개의 autophagy 마커의 co-localization을 사용했습니다. 기초 조건 (Control sample) 하에서,자가 형광체의 수가 적었고, &quot;High Spot&quot;으로 세포가 거의 발견되지 않았다. autophagosome / lysosome 융합을 억제하는 chloroquine의 첨가로 LC3 spot의 수가 증가했다. 리소좀이 autophagosome과 autophagosome에있는 p62를 파괴 할 수 없기 때문에 LC3, p62 및 LAMP1 autolysosome 축적의 공존이 증가합니다. 이 효력은 영양이되는 starvat이온, autophagy를 유도합니다. 그러나 chloroquine을 첨가하지 않으면 autophagosom의 수는 현저히 증가하지 않았고, autophagos turnover의 속도가 증가했기 때문인 것으로 보인다. 세포가 chloroquine의 존재 하에서 굶어 죽었을 때, autophagosomes의 co-localization과 수의 증가가 있었는데, 기아가 autophagic 플럭스를 증가 시킨다는 결론을지지한다. EBSS는 강력한 autophagy 유도제로 알려져 있습니다. 따라서 증가가 클 것으로 예상됩니다. 약물 유도와 같은 다른 방법을 사용하여 autophagy를 유도하는 경우, 대조군과 치료 된 시료의 차이는 미묘합니다. 이 특정 프로토콜은 인간 세포주에서 autophagy를 측정하도록 고안되었지만 특정 종에 대한 항체로 전환하여 다른 종에 적용 할 수 있습니다. 또한, 분석 방법은 공동 지역화를 필요로하는 모든 세포 내 응용에 사용될 수있다3 개의 프로브 / 마커로 구성됩니다.

이후 autophagy라고 불리는 Macroautophagy는 손상되었거나 기능 불능 인 성분, 수명이 긴 단백질 및 세포 소기관이 리소좀을 통해 분해되어 재활용되는 이화 과정입니다 1 . Autophagy는 autophagosome의 형성을 포함하는 동적 인 다단계 프로세스입니다. autophagosome과 lysosome의 융합, autolysosome 형성; 및 autolysosome 2 의 내용의 저하. 포유류 시스템에서 autophagy를 확인하는 데 사용되는 중요한 생물학적 마커는 autophagosomal membrane을 구성하는 미세 소관 관련 단백질 1A / 1B-L 鎖 사슬 3 (LC3)입니다. autophagy 동안, cytosolic LC3-1은 포스파티딜 에탄올 아민에 접합되어 LC3-II를 형성한다; LC3-II는 autophagosomal 막 3에 통합됩니다. autophagic 플럭스에 널리 사용되는 또 다른 마커는 autophagy 수용체 sequestosome 1 (SQSTM1, p62)입니다.autophagic 막에 autophagic화물을 nks 4 , 5 . 전통적으로 자식 작용을 측정하는 데 사용 된 방법은 서양 오 점 및 형광 현미경 (7)이다. 그러나 이들 방법 중 어느 것도이 두 가지 기법과 관련된 문제가 있기 때문에 &quot;황금 표준&quot; 2 , 6 으로 간주되지 않습니다. 웨스턴 블 롯은 균질 샘플을 사용하기 때문에 평균값을 제공하므로 관찰자는 개별 세포에서 일어나는 현상을 볼 수 없습니다. 반면에 형광 현미경 검사는 단일 셀 수준에서 관찰자 정보를 제공하지만 처리량 기능이 부족하여 객관적이고 통계적으로 엄격한 평가를 얻지 못합니다. 최근 몇 년 동안 multispectral imaging flow cytometry (MIFC, Table of Materials 참조)에 의한 LC3와 p62의 측정이 popu정량 전력, 높은 처리량 기능, 다중화 가능성 및 모든 셀을 이미지화 할 수있는 능력으로 인해 희소성이 희박합니다. (재료의 도표 참조) 컴패니언 분석 소프트웨어와 함께 MIFC를 이용하여 자식 작용을 측정하기 위해 가장 널리 사용되는 방법 중 하나는, LC3의 puncta에 또는 autophagosomes 8, 9, 10, 11, 12, 13, 14의 스폿 카운트 통해서 , 15 , 16 , 17 . 그러나, autophagosomes의 증가는 autophagy의 증가가 반드시 과정 2 의 봉쇄를 나타낼 수 있음을 의미하지는 않습니다. LC3 - II 회전율은 세포의 존재와 존재를 분석하여 autophagic 유동을 측정하는 데 유용한 매개 변수입니다.클로로퀸과 같은 리소좀 분해 억제제의 부재. 클로로퀸하여 18 발생할 수 리소좀 분해 전에 autophagic 플럭스 체포하여 자식 작용의 정도의 척도로서 autophagosome 형성의 정량을 허용, 리소좀에 autophagosome의 융합을 억제한다. 또한, p62는 주로 autophagy에 의해 분해되며, autophagosome의 lysosomal 분해와 그 내용물이 차단되면 p62의 축적이 예상됩니다 17 , 19 . Autophagy는 다단계 프로세스이며 LC3 또는 p62만으로는 세포에서 일어나는 일을 완벽하게 파악할 수 없습니다. 최근의 논문은 autolysosome 2 , 17 , 20 , 21 의 동시 형성을 조사 할 필요성을 강조했다. MIFC17, 20, 21, 22, 23, 24, 25, 26 - 15 리소좀에 autophagosome의 공동 촬상 지역화하여 autolysosome의 형성을 측정 할 수 의적. 또한, MIFC를 사용하여 p62와 LC3의 co-localization 또한 autophagic 플럭스 5 측정하기 위해 탐험되었습니다. 참조 된 분석 소프트웨어에서 동일 지역화를 측정하는 &quot;특징&quot;은 &quot;밝기 정보 유사성 R3&quot;(BDS)라고하며 두 이미지의 작고 밝은 이미지 세부 정보를 비교하도록 특별히 설계되었습니다. BDS는 로그 변환 된 Pearson의 반지름이 3 픽셀 이하인 지역화 된 밝은 점의 상관 계수입니다. 즉, BDS는 o의 정도를 계산합니다.두 개의 다른 형광 채널에서 픽셀을 verlapping. 밝은 지점은 상호 연관되어 있습니다 ( 즉, 동일한 공간 위치) 또는 비 상관 ( 즉, 다른 공간 위치). 따라서 상관 계수는 0 (상관 없음)과 1 (완전 상관) 사이에서 달라집니다. 계수를 로그 변환하여 범위를 0과 무한대 사이에서 26 , 27 로 증가시킵니다. BDS만으로는 충분하지 않을 수 있습니다. Rajan et al. BDS 만 사용하면 위양성 또는 위음성 결과가 발생할 수 있음을 발견했습니다 21 . BDS는 autophagy의 두 마커의 co-localization 평가하지만 autophagosomes의 수를 고려하지 않습니다. autophagosomes의 수를 설명하기 위해, Rajan et al. LC3 puncta 21 의 spot-counting을 포함합니다. Rajan et al. BDS에 비해 LC3 스폿 카운트의 2 변수 스 캐터 플롯을 사용하여 제안되었습니다. 이 두 변수를 사용하여, 두 집단먼저 확인 된 것은 LC3 스폿이 높은 세포와 LC3 스팟이 낮은 세포가있는 것입니다. 고 -LC3 자리 집단은 두 개의 집단으로 분류되었다 : 낮은 공 - 위치 화 ( 즉, 자가 - 포자충의 축적)를 갖는 세포 및 높은 공 - 위치 화 ( 즉, 오토 리소좀의 축적)를 갖는 세포. 이 2 변이 플롯은 극소수의자가 포식 세포와 autophagosomes 및 / 또는 autolysosome 21이 축적 된 세포를 구분할 수있게합니다. 지금까지 LC3, p62 및 LAMP1 (리소좀 마커)의 동시 공동 위치 화는 MIFC 동반자 분석 소프트웨어의 단일 &quot;피처 유형&quot;을 사용하여 가능하지 않았습니다 ( 재료 표 참조). 그러나 최근에 버전 6.1에서 소개 된 새로운 기능은 Bright Detail Colocalization 3 (BDC3)입니다. BDC3은 3 가지 이미지 각각의 밝은 디테일 이미지를 비교합니다 (이 경우 LC3, p62 및 LAMP1)를 측정하고 세 가지 프로브 ( 즉, LC3, p62 및 LAMP1)의 동일 지역화를 정량화합니다. BDC3 기능은 Pearson의 상관 계수를 수정하여 세 개의 이미지로 확장합니다. 세 이미지의 밝은 점이 상관되었거나 상관 관계가 없기 때문에 상관 계수는 0 (비 상관)과 1 (완벽한 상관) 사이에서 다릅니다. 계수는 0에서 무한대 사이의 동적 범위를 증가 시키도록 로그 변환됩니다. BDC3 기능을 사용하여 BDS 기능을 전환하면 Rajan et al. 동시에 하나의 시스템에서 자동 학습을 측정하기 위해 가장 많이 사용되는 3 개의 마커를 통합 할 수 있습니다. autophagy의 이러한 3 개의 마커를 단일 분석으로 공동 위치시킬 수있는 능력은 autophagy의 유도와 조절에 대한 새로운 통찰력을 이끌어 낼 수 있습니다. 다음 프로토콜은 Jurkat 세포에서 autophagy를 유도하는 단계를 개략적으로 보여줍니다. LC3, p62 및 LAMP1 항체로 세포를 표지하십시오. 멀티 스피어에서 데이터를 얻다.외과 적 이미징 유동 세포 계측기; autophagic 플럭스를 평가하기 위해 데이터를 분석 할 수 있습니다.

<table border="0" cellpadding="0" cellspacing="0" width="1012">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">15 mL centrifuge tube</td>
			<td style="width:244px;">Falcon</td>
			<td style="width:161px;">352096</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">50 mL centrifuge tube</td>
			<td>Falcon</td>
			<td>352070</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="121">
			<td height="121" style="height:121px;">AF647 labeled Donkey anti-Mouse - IgG&#160;</td>
			<td>Invitrogen</td>
			<td>A-31571</td>
			<td style="width:299px;">Donkey anti-Mouse IgG (H+L) Secondary Antibody, Alexa Fluor 647. Concntration 2mg/mL. https://www.thermofisher.com/antibody/product/Donkey-anti-Mouse-IgG-H-L-Secondary-Antibody-Polyclonal/A-31571</td>
		</tr>
		<tr height="62">
			<td height="62" style="height:62px;width:308px;">anti-human CD107a-PE (LAMP1)</td>
			<td>BioLegend</td>
			<td>328607</td>
			<td style="width:299px;">Clone H4A3. Concentration 400 &#181;g/mL. http://www.biolegend.com/pe-anti-human-cd107a-lamp-1-antibody-4967.html</td>
		</tr>
		<tr height="81">
			<td height="81" style="height:81px;">anti-human CD45- AF488</td>
			<td>BioLegend</td>
			<td>304017</td>
			<td style="width:299px;">Clone HI30. http://www.biolegend.com/alexa-fluor-488-anti-human-cd45-antibody-2738.html</td>
		</tr>
		<tr height="61">
			<td height="61" style="height:61px;">anti-human CD45- PE&#160;</td>
			<td>BioLegend</td>
			<td>304008</td>
			<td style="width:299px;">Clone HI30.&#160; http://www.biolegend.com/pe-anti-human-cd45-antibody-708.html</td>
		</tr>
		<tr height="81">
			<td height="81" style="height:81px;">anti-human CD45-AF647&#160;</td>
			<td>BioLegend</td>
			<td>304018</td>
			<td style="width:299px;">Clone HI30.&#160; http://www.biolegend.com/alexa-fluor-647-anti-human-cd45-antibody-2739.html</td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:308px;">Anti-LC3 (Human) mAb clone 4E12</td>
			<td>MBL International Corporation</td>
			<td>M152-3</td>
			<td style="width:299px;">Clone 4E+12.&#160; Concentration 2 mg/mL.&#160; https://www.mblintl.com/products/m152-3</td>
		</tr>
		<tr height="81">
			<td height="81" style="height:81px;width:308px;">Anti-SQSTM1 / p62 antibody [EPR4844] - Autophagosome Marker (Alexa Fluor 488)</td>
			<td>abcam</td>
			<td>ab185015</td>
			<td style="width:299px;">Clone EPR4844.&#160; Concentration 0.5 mg/mL.&#160; http://www.abcam.com/sqstm1-p62-antibody-epr4844-autophagosome-marker-alexa-fluor-488-ab185015.html</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">Chloroquine diphosphate Salt</td>
			<td>Sigma-Aldrich</td>
			<td>C6628-25G</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="101">
			<td height="101" style="height:101px;width:308px;">Cleanser - Coulter Clenz&#160;</td>
			<td>Beckman Coulter</td>
			<td>8546931</td>
			<td style="width:299px;">Fill container with 200 mL of Cleanser.&#160; https://www.beckmancoulter.com/wsrportal/page/itemDetails?itemNumber=8546931#2/10//0/25/1/0/asc/2/8546931///0/1//0/</td>
		</tr>
		<tr height="61">
			<td height="61" style="height:61px;width:308px;">DAPI Stain 5mg/mL</td>
			<td>MilliporeSigma</td>
			<td>508741</td>
			<td style="width:299px;">http://www.emdmillipore.com/US/en/product/DAPI-Stain---CAS-28718-90-3---Calbiochem,EMD_BIO-508741</td>
		</tr>
		<tr height="121">
			<td height="121" style="height:121px;width:308px;">Debubbler - 70% Isopropanol</td>
			<td>MilliporeSigma</td>
			<td>1.3704</td>
			<td style="width:299px;">Fill container with 200 mL of Debubbler.&#160; http://www.emdmillipore.com/US/en/product/2-Propanol-70%25-%28V%2FV%29-0.1-%C2%B5m-filtred,MDA_CHEM-137040?ReferrerURL=https%3A%2F%2Fwww.google.com%2F</td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:308px;">Dulbecco&#39;s Phosphate Buffered Saline 10X</td>
			<td>MilliporeSigma</td>
			<td>BSS-2010-B</td>
			<td style="width:299px;">&#160;Ca++Mg++ Free&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">Dulbecco&#39;s Phosphate Buffered Saline 1X</td>
			<td>MilliporeSigma</td>
			<td>BSS-1006-B</td>
			<td style="width:299px;">PBS Ca++Mg++ Free&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">Earle&#39;s Balanced Salt Solution 1X</td>
			<td>Gibco</td>
			<td>14155</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">Fetal Bovine Serum</td>
			<td>HyClone</td>
			<td>SH30071.03</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="241">
			<td height="241" style="height:241px;width:308px;">Formaldehyde, 10%, methanol free, Ultra Pure</td>
			<td>Polysciences, Inc.</td>
			<td>04018</td>
			<td style="width:299px;">This is what is used for the 4% and 1% Formalin. CAUTION: Formalin/Formaldehyde toxic by inhalation and if swallowed.&#160; Irritating to the eyes, respiratory systems and skin.&#160; May cause sensitization by inhalation or skin contact. Risk of serious damage to eyes.&#160; Potential cancer hazard.&#160; http://www.polysciences.com/default/catalog-products/life-sciences/histology-microscopy/fixatives/formaldehydes/formaldehyde-10-methanol-free-pure/</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">Hanks&#39; Balanced Salt Solution 1X</td>
			<td>Gibco</td>
			<td>14175</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:308px;">Jurkat, Clone E6-1 (ATCC TIB-152)</td>
			<td>ATCC</td>
			<td>TIB-152</td>
			<td style="width:299px;">https://www.atcc.org/products/all/TIB-152.aspx</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">MEM Non-Essential Amino Acids 100X</td>
			<td>HyClone</td>
			<td>SH30238.01</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="201">
			<td height="201" style="height:201px;width:308px;">MIFC - ImageStreamX Mark II</td>
			<td>MilliporeSigma</td>
			<td>100220</td>
			<td style="width:299px;">A 2 camera ImageStreamX Mark II eqiped with the 405nm, 488nm, and 642nm lasers was used. http://www.emdmillipore.com/US/en/life-science-research/cell-analysis/amnis-imaging-flow-cytometers/imagestreamx-Mark-ii-imaging-flow-cytometer/VaSb.qB.QokAAAFLzRop.zHe,nav?cid=BI-XX-BDS-P-GOOG-FLOW-B325-0006</td>
		</tr>
		<tr height="61">
			<td height="61" style="height:61px;width:308px;">MIFC analysis software - IDEAS 6.2</td>
			<td>MilliporeSigma</td>
			<td>100220</td>
			<td style="width:299px;">The companion software to the MIFC (ImageStreamX MKII).&#160; IDEAS version 6.2</td>
		</tr>
		<tr height="61">
			<td height="61" style="height:61px;width:308px;">MIFC software - INSPIRE</td>
			<td>MilliporeSigma</td>
			<td>100220</td>
			<td style="width:299px;">This is the software that runs the MIFC (ImageStreamX MKII). INSPIRE version 200.1.388.0</td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:308px;">PE anti-human CD107a (LAMP-1) Antibody clone H4A3</td>
			<td>BioLegend</td>
			<td>328608</td>
			<td style="width:299px;">http://www.biolegend.com/pe-anti-human-cd107a-lamp-1-antibody-4967.html</td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:308px;">Penicllin/Streptomycin/Glutamine solution 100X</td>
			<td>HyClone</td>
			<td>SV30082.1</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="61">
			<td height="61" style="height:61px;width:308px;">Rinse - Ultrapure water or deionized water</td>
			<td>NA</td>
			<td>NA</td>
			<td style="width:299px;">You can use any ultrapure water or deionized water.&#160; Fill container with 900 mL of Rinse.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">RPMI-1640 Medium 1X</td>
			<td>HyClone</td>
			<td>SH30027.01</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="81">
			<td height="81" style="height:81px;width:308px;">Sheath - PBS</td>
			<td>MilliporeSigma</td>
			<td>BSS-1006-B</td>
			<td style="width:299px;">This is the same as Dulbecco&#39;s Phosphate Buffered Saline 1X&#160; Ca++MG++ free.&#160; Fill container with 900mL of Sheath.</td>
		</tr>
		<tr height="101">
			<td height="101" style="height:101px;width:308px;">Siliconized polypropylene microcentrifuge tubes</td>
			<td>Fisherbrand</td>
			<td>02-681-320</td>
			<td style="width:299px;">Fisherbran Siliconized Low-Retention Microcentrifuge Tubes 1.5 mL. https://www.fishersci.com/shop/products/fisherbrand-siliconized-low-retention-microcentrifuge-tubes-8/p-193936</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">Sodium Pyruvate solution (100mM)</td>
			<td>HyClone</td>
			<td>SH30239.01</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="81">
			<td height="81" style="height:81px;width:308px;">Sterilizer - 0.4-0.7% Hypochlorite</td>
			<td>VWR</td>
			<td>JT9416-1</td>
			<td style="width:299px;">This is assentually 10% Clorox bleach that can be made by deluting Clorox bleach with water.&#160; Fill container with 200 mL of Sterilzer.</td>
		</tr>
		<tr height="121">
			<td height="121" style="height:121px;width:308px;">System Calibration Reagent - SpeedBead</td>
			<td>MilliporeSigma</td>
			<td>400041</td>
			<td style="width:299px;">Each tube holds ~10 mL.&#160; https://www.emdmillipore.com/US/en/life-science-research/cell-analysis/amnis-imaging-flow-cytometers/support-training/XDqb.qB.wQMAAAFLBDUp.zHu,nav&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">T75 flask</td>
			<td>Falcon</td>
			<td>353136</td>
			<td style="width:299px;"></td>
		</tr>
		<tr height="101">
			<td height="101" style="height:101px;width:308px;">TRITON X-100, PROTEIN GRADE Detergent, 10% Solution, Sterile-Filtered</td>
			<td>MilliporeSigma</td>
			<td>648463-50ML</td>
			<td style="width:299px;">http://www.emdmillipore.com/US/en/product/TRITON-X-100,-PROTEIN-GRADE-Detergent,-10%25-Solution,-Sterile-Filtered---CAS-9002-93-1---Calbiochem,EMD_BIO-648463</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:308px;">Water, Cell Culture Grade&#160;</td>
			<td>HyClone</td>
			<td>SH30529.03</td>
			<td style="width:299px;"></td>
		</tr>
	</tbody>
</table>

assessing autophagic flux by measuring lc3, p62, and lamp1 co-localization using multispectral imaging flow cytometry

Autophagy는 성장 및 분화 과정에서 축적되는 정상 또는 기능 장애 세포 구성 요소가 리소좀을 통해 분해되어 재활용되는 이화 경로입니다. autophagy 동안, cytoplasmic LC3 단백질은 지방화되고 autophagosomal membranes에 보충된다. autophagosome은 lysosome과 융합하여 autolysosome을 형성하는데, autophagosome 소포와 그 내용물의 분해가 일어난다. LC3에 결합하는 유비퀴틴 관련 단백질 p62는 또한 autophagic 플럭스를 모니터하는 데 사용됩니다. autophagy를 수행하는 세포는 p62, LC3 및 리소좀 마커의 동일 지역화를 입증해야합니다. Immunofluorescence 현미경 검사는 세포 단위로 LC3 puncta, p62 및 / 또는 lysosomes를 시각적으로 확인하는 데 사용되었습니다. 그러나 객관적이고 통계적으로 엄격한 평가는 얻기가 어려울 수 있습니다. 이러한 문제를 극복하기 위해 multispectral imaging flow cytometry와 함께 밝은 de3 개의 autophagy 마커 (LC3, p62 및 lysosomal LAMP1)로부터 꼬리 이미지를 추출하고 객관적이고 정량적이며 통계적으로 견고한 방식으로 자동 계수를 측정하기 위해 LC3 스폿 카운팅과 함께 공동 위치를 정량화합니다.

이 분석 방법은 autophagic 플럭스를 분석하기 위해 여러 기능을 사용합니다. 최종 2 변량 플롯을 완전히 이해하려면 개별 분석 기능을 먼저 조사해야합니다. autophagosomes의 계산은 autophagy를 측정하는 논리적 인 방법입니다; 그러나 LC3 puncta의 크기 / 모양 / 밝기는 세포간에 크게 다를 수 있습니다. 변이로 인해 자동자가 염색체를 수동으로 계산하거나 분석 소프트웨어의 스폿 카운트 기능을 사용하기가 어려울 수 있습니다. 따라서, autophagosomes의 큰 변화 때문에 spot-count 기능은 완벽하지 않습니다. 그러나, 좋은 장소 카운트 기능은 대부분의 세포 (26)에 작동합니다. 도 3 은 상이한 스폿 마스크를 사용하여 Jurkat 셀에서 LC3 점을 스팟 마스킹하는 예를 도시한다. 이 데이터 세트에 대해 선택된 스폿 카운트 기능은 Spot Count_Peak (M11, Ch11-LC3-AF647, Bright, 4) _4입니다. 즉, 스폿 카운트 기능이spot-to-cell 배경 비율이 4 (Bright, 4) 인 채널 11 (Ch11-LC3-AF647)의 기본 채널 11 마스크 (M11) 내에서 식별 된 마스크. 그림 4 는 대조군, Control + Chloroquine, Starved 및 Starved + Chloroquine Jurkat 세포에 대한 평균 스팟 카운트에 대한 스폿 카운트 히스토그램과 대표 이미지를 보여줍니다 (anti-LC3-AF647로 표시). 대조군과 굶주린 평균 자리 수는 크게 다르지 않습니다. chloroquine을 첨가하면 Starved + Chloroquine에 비해 Control + Chloroquine의 평균값에 큰 차이가 있습니다. 조사 할 다음 기능은 BDC3입니다. BDC3은 세 개의 마커 / 프로브 (이 경우 LC3, p62 및 LAMP1)의 동일 위치 측정 값입니다. 그림 5A - 5D 는 Control, Control + Chloroquine, Starved 및 Starved + Chloroquine Jurkat 세포에 대한 BDC3 히스토그램을 보여줍니다. anti-p62-AF488, 항 -LAMP1-PE 및 항 -LC3-AF647을 포함한다. Control + Chloroquine은 Starved + Chloroquine 평균을 의미합니다. 그러나, 그림 5E - 5H 의 평균 BDC3 점수에서 세포의 이미지를 보면, 히스토그램이 믿을 수있는 것보다 더 큰 차이가 있습니다. 이것은 BDC3가 동일한 BDC3 점수에 대해자가 염색체의 수에 큰 변동성을 초래하는 동시에 공동 위치하는자가 작용 세포 소기관의 수를 고려하지 않기 때문입니다. 대부분의 경우, 기초 수준 에서조차, p62, LAMP1 및 LC3은 어느 정도까지는 세포의 유사한 영역에 공동 위치하거나 상주해야하기 때문에 세 가지 프로브 사이에 중첩이 존재합니다. 대조적으로, 그림 6 과 같이 Starved + Chloroquine 샘플에 대해 anti-p62-AF488, anti-LC3-AF647 및 DAPI 핵 염료가 공존하지 않아야하는 세 가지 프로브의 예 &lt;/ p&gt; 스폿 카운트 기능과 BDC3 기능이 결합되면 다양한 샘플 / 조건을 구별하는 기능을 향상시키는 하위 모집단의 존재가 분명합니다. 그림 7 은 Control, Control + Chloroquine, Starved 및 Starved + Chloroquine의 네 가지 샘플에 대한 LC3 대 BDC3 p62 / LAMP1 / LC3의 스팟 카운트의 이변 변수 플롯을 보여줍니다. Control 샘플은 Low Spots, High Spots / Low BDC3 및 High Spots / High BDC3의 세 가지 집단에 대한 게이팅 전략을 설정하는 데 사용되었습니다. 대조군 샘플은 세포의 98 % 이상이 1 개 이하의 반점을 갖는 것으로 나타났다. High Spots / Low BDC3과 High Spots / High BDC3 사이의 경계는 대조 샘플의 91 % 이상이 1 미만의 BDC3 스코어를 가졌기 때문에 BDC3 스코어가 1로 설정되었습니다. bivariate 플롯에 대한 결과 요약 표 1 에 나타냈다 . age = &quot;1&quot;&gt; <img alt="그림 1" class="xfigimg" src="/files/ftp_upload/55637/55637fig1.jpg" /> 그림 1 : MIFC 악기 설정. 이 실험에 사용 된 MIFC 기기 설정의 스크린 샷으로 프로토콜의 8 단계에 설명되어 있습니다. <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55637/55637fig1large.jpg" target="_blank">이 그림의 더 큰 버전을 보려면 여기를 클릭하십시오.</a> <img alt="그림 2" class="xfigimg" src="/files/ftp_upload/55637/55637fig2.jpg" /> 그림 2 : 분석 소프트웨어 게이팅 전략. 프로토콜 9 단계에서 설명한 분석 소프트웨어 게이팅 구성표의 스크린 샷입니다. <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55637/55637fig2large.jpg" target="_blank">이 그림의 더 큰 버전을 보려면 여기를 클릭하십시오.</a> fig3.jpg &quot;/&gt; 그림 3 : LC3 스폿 마스킹. 스폿 카운트 기능을 만드는 데 사용되는 Jurkat 셀 이미지 및 마스크. BrightField (BF), LC3-AF647, 피크 (M11, Ch11-LC3-AF647, 밝기, 2), 피크 (M11, Ch11-LC3-AF647, 밝기, 4), 피크 (M11, Ch11-LC3-AF647 Bright, 5), Spot (M11, Ch11-LC3-AF647, Bright, 5,3,1) 및 Spot (M11, Ch11-LC3-AF647, Bright, 6,2,1) 표시된 모든 셀에서 가장 잘 작동하는 마스크는 Peak (M11, Ch11-LC3-AF647, Bright, 4)입니다. <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55637/55637fig3large.jpg" target="_blank">이 그림의 더 큰 버전을 보려면 여기를 클릭하십시오.</a> <img alt="그림 4" class="xfigimg" src="/files/ftp_upload/55637/55637fig4.jpg" /> 그림 4 : LC3 스폿 카운트 히스토그램. 컨트롤 ( A , 연한 파란색), 스팟 카운트 기능 Spot Count_Peak (M11, Ch11-LC3-AF647, 밝기, 4) _4 및 LC3-AF647 스폿 카운트 히스토그램을 사용하여 Control + Chloroquine ( B , 파란색), Starved ( C , 분홍색) 및 Starved + Chloroquine ( D , 빨간색). Control, Control + Chloroquine, Starved 및 Starved + Chloroquine의 평균 스팟 카운트는 각각 0.07, 1.13, 0.10 및 2.77입니다. (spot) 수에 대한 대표적인 세포의 LC3-AF647 및 DAPI 이미지의 복합체 인 BF, LC3-AF647 (적색), DAPI 핵 염료 (청색) 및 대조군 ( E , 0 스팟), 대조 + 클로로퀸 F , 1 지점), Starved ( G , 0 지점), Starved + Chloroquine ( H 지점, 3 지점). <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55637/55637fig4large.jpg" target="_blank">이 그림의 더 큰 버전을 보려면 여기를 클릭하십시오.</a> <img alt="그림 5" class="xfigimg" src="/files/ftp_upload/55637/55637fig5.jpg" /> 그림 5 : p62 / LAMP1 / LC3의 BDC3 히스토그램. BDC3 p62 / LAMP1 / LC3 히스토그램 fo( A , 연한 파란색), Control + Chloroquine ( B , 파란색), Starved ( C , 분홍색), Starved + Chloroquine ( D , 빨간색 Control, Control + Chloroquine, Starved 및 Starved + Chloroquine의 평균 BDC3 점수는 각각 0.57, 0.82, 0.74 및 0.98입니다. BF; p62-AF488 (녹색); LAMP1-PE (황색); LC3-AF647 (적색); Control ( E ), Control + Chloroquine ( F ), Starved ( G ), 및 Starved + Chloroquine에 대한 대표적인 세포의 p62-AF488, LAMP1-PE 및 LC3- H ). <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55637/55637fig5large.jpg" target="_blank">이 그림의 더 큰 버전을 보려면 여기를 클릭하십시오.</a> <img alt="그림 6" class="xfigimg" src="/files/ftp_upload/55637/55637fig6.jpg" /> 그림 6 : p62 / L의 BDC3 히스토그램굶주린 + 클로로퀸 시료의 경우 C3 / DAPI. ( A ) Starved + Chloroquine 샘플에 대한 BDC3 p62 / LC3 / DAPI 히스토그램이 표시됩니다. 평균 BDC3 점수는 0.07입니다. ( B ) BF; p62-AF488 (녹색); LC3-AF647 (적색); DAPI (파란색); Starved + Chloroquine 샘플의 경우 평균 BDC3에 대한 대표 세포의 p62-AF488, LC3-AF647 및 DAPI 이미지의 합성이 표시됩니다. <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55637/55637fig6large.jpg" target="_blank">이 그림의 더 큰 버전을 보려면 여기를 클릭하십시오.</a> <img alt="그림 7" class="xfigimg" src="/files/ftp_upload/55637/55637fig7.jpg" /> 그림 7 : LC3 스팟 카운트 대 BDC3 p62 / LAMP1 / LC3의 2 변이 플롯. ( A ) Control, Control + Chloroquine, Starved 및 Starved + Chloroquine Jurkat 세포에 대한 LC3 스팟 카운트 대 BDC3 p62 / LAMP1 / LC3의 2 변이 플롯. ( B ) BF; p62-AF488 (녹색); LAMP1-PE (황색); LC3-AF647 (적색); Starved + Chloroquine 샘플의 경우 3 개 영역 ( 즉, 낮은 스폿, 하이 스팟 / 로우 BDC3 및 하이 스팟 / 하이 BDC3)의 p62-AF488, LAMP1-PE 및 LC3-AF647 이미지가 합성되어 표시됩니다. <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55637/55637fig7large.jpg" target="_blank">이 그림의 더 큰 버전을 보려면 여기를 클릭하십시오.</a> <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td></td><td> 세포 수 </td><td> 밝은 세부 Colocalization 3 평균 </td><td> 스팟 카운트 LC3 평균 </td><td> 낮은 곳 (%) </td><td> 높음 높음 / 낮음 BDC3 </td><td> 높은 반점 / 높음 BDC3 </td></tr><tr><td> 제어 </td><td> 439 </td><td> 0.57 </td><td> 0.07 </td><td> 98.2 </td><td> 1.8 </td><td> 0.0 </td></tr><tr><td> 대조 + 클로로퀸 </td><td> 1432 년 </td><td> 0.82 </td><td> 1.13 </td><td> 68.9 </td&gt; <td> 19.5 </td><td> 11.7 </td></tr><tr><td> 굶주린 </td><td> 1204 </td><td> 0.74 </td><td> 0.10 </td><td> 98.4 </td><td> 0.6 </td><td> 1.0 </td></tr><tr><td> 굶주린 + Chloroquine </td><td> 1811 년 </td><td> 0.98 </td><td> 2.77 </td><td> 32.1 </td><td> 36.9 </td><td> 31.0 </td></tr></tbody></table> 표 1 : Jurkat LC3 스팟 카운트 대 BDC3 p62 / LAMP1 / LC3 2 변량 플롯의 요약

Watch this Scientific Journal Video about Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry at JoVE.com

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry

여기에 LC3 spot counting과 함께 3 개의 autophagy marker의 밝은 디테일 이미지를 비교하고 co-localization을 정량화하는 분석적인 특징을 가진 multispectral imaging flow cytometry가 객관적이고 정량적이며 통계적으로 강력한 방식으로 autophagy를 측정하는 데 사용되었습니다.

Multispectral Imaging Flow Cytometry를 사용하여 LC3, p62 및 LAMP1 Co-Localization 측정을 통한 Autophagic Flux 평가

Autophagy is a catabolic pathway in which normal or dysfunctional cellular components that accumulate during growth and differentiation are degraded via ...

assessing-autophagic-flux-measuring-lc3-p62-lamp1-co-localization

Nanyang Technological University

Research

JoVE Journal

Biology

31.0K 조회수.  MilliporeSigma.  여기에 LC3 spot counting과 함께 3 개의 autophagy marker의 밝은 디테일 이미지를 비교하고 co-localization을 정량화하는 분석적인 특징을 가진 multispectral imaging flow cytometry가 객관적이고 정량적이며 통계적으로 강력한 방식으로 autophagy를 측정하는 데 사용되었습니다. 

비디오: Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry

IP-FCM:  Immunoprecipitation Detected by Flow Cytometry

Immunoprecipitation detected by flow cytometry (IP-FCM) is an efficient method for detecting and quantifying protein-protein interactions. The basic principle extends that of sandwich ELISA, wherein the captured primary analyte can be detected together with other molecules physically associated within multiprotein complexes. The procedure involves covalent coupling of polystyrene latex microbeads with immunoprecipitating monoclonal antibodies (mAb) specific for a protein of interest, incubating these beads with cell lysates, probing captured protein complexes with fluorochrome-conjugated probes, and analyzing bead-associated fluorescence by flow cytometry. IP-FCM is extremely sensitive, allows analysis of proteins in their native (non-denatured) state, and is amenable to either semi-quantitative or quantitative analysis. As additional advantages, IP-FCM requires no genetic engineering or specialized equipment, other than a flow cytometer, and it can be readily adapted for high-throughput applications.

The IP-FCM method is presented, which allows a sensitive, robust, biochemical assessment of native protein-protein interactions, without requiring genetic engineering or large sample sizes.

IP - FCM : 유동세포계측법에 의해 감지 Immunoprecipitation

Immunoprecipitation detected by flow cytometry (IP-FCM) is an efficient method for detecting and quantifying protein-protein interactions. The basic ...

연구

생물학

Flow Cytometry Purification of Mouse Meiotic Cells

The heterogeneous nature of cell types in the testis and the absence of meiotic cell culture models have been significant hurdles to the study of the unique differentiation programs that are manifest during meiosis. Two principal methods have been developed to purify, to varying degrees, various meiotic fractions from both adult and immature animals: elutriation or Staput (sedimentation) using BSA and/or percoll gradients. Both of these methods rely on cell size and density to separate meiotic cells1-5. Overall, except for few cell populations6, these protocols fail to yield sufficient purity of the numerous meiotic cell populations that are necessary for detailed molecular analyses. Moreover, with such methods usually one type of meiotic cells can be purified at a given time, which adds an extra level of complexity regarding the reproducibility and homogeneity when comparing meiotic cell samples.
Here, we describe a refined method that allows one to easily visualize, identify, and purify meiotic cells, from germ cells to round spermatids, using FACS combined with Hoechst 33342 staining7,8. This method provides an overall snapshot of the entire meiotic process and allows one to highly purify viable cells from most stage of meiosis. These purified cells can then be analyzed in detail for molecular changes that accompany progression through meiosis, for example changes in gene expression9,10and the dynamics of nucleosome occupancy at hotspots of meiotic recombination11.

An efficient method to obtain highly purified viable meiotic fractions from mouse testis is described, which combines a refined cell dissociation protocol with fluorescent activated cell sorting (FACS). This method takes advantage of differences in the DNA content and nuclear density of discrete meiotic fractions.

마우스 Meiotic 셀 유동세포계측법의 정제

The heterogeneous nature of cell types in the testis and the absence of meiotic cell culture models have been significant hurdles to the study of the ...

Measuring Cell Cycle Progression Kinetics with Metabolic Labeling and Flow Cytometry

Precise control of the initiation and subsequent progression through the various phases of the cell cycle are of paramount importance in proliferating cells. Cell cycle division is an integral part of growth and reproduction and deregulation of key cell cycle components have been implicated in the precipitating events of carcinogenesis 1,2. Molecular agents in anti-cancer therapies frequently target biological pathways responsible for the regulation and coordination of cell cycle division 3. Although cell cycle kinetics tend to vary according to cell type, the distribution of cells amongst the four stages of the cell cycle is rather consistent within a particular cell line due to the consistent pattern of mitogen and growth factor expression. Genotoxic events and other cellular stressors can result in a temporary block of cell cycle progression, resulting in arrest or a temporary pause in a particular cell cycle phase to allow for instigation of the appropriate response mechanism. 
The ability to experimentally observe the behavior of a cell population with reference to their cell cycle progression stage is an important advance in cell biology. Common procedures such as mitotic shake off, differential centrifugation or flow cytometry-based sorting are used to isolate cells at specific stages of the cell cycle 4-6. These fractionated, cell cycle phase-enriched populations are then subjected to experimental treatments. Yield, purity and viability of the separated fractions can often be compromised using these physical separation methods. As well, the time lapse between separation of the cell populations and the start of experimental treatment, whereby the fractionated cells can progress from the selected cell cycle stage, can pose significant challenges in the successful implementation and interpretation of these experiments.
Other approaches to study cell cycle stages include the use of chemicals to synchronize cells. Treatment of cells with chemical inhibitors of key metabolic processes for each cell cycle stage are useful in blocking the progression of the cell cycle to the next stage. For example, the ribonucleotide reductase inhibitor hydroxyurea halts cells at the G1/S juncture by limiting the supply of deoxynucleotides, the building blocks of DNA. Other notable chemicals include treatment with aphidicolin, a polymerase alpha inhibitor for G1 arrest, treatment with colchicine and nocodazole, both of which interfere with mitotic spindle formation to halt cells in M phase and finally, treatment with the DNA chain terminator 5-fluorodeoxyridine to initiate S phase arrest 7-9. Treatment with these chemicals is an effective means of synchronizing an entire population of cells at a particular phase. With removal of the chemical, cells rejoin the cell cycle in unison. Treatment of the test agent following release from the cell cycle blocking chemical ensures that the drug response elicited is from a uniform, cell cycle stage-specific population. However, since many of the chemical synchronizers are known genotoxic compounds, teasing apart the participation of various response pathways (to the synchronizers vs. the test agents) is challenging. 
Here we describe a metabolic labeling method for following a subpopulation of actively cycling cells through their progression from the DNA replication phase, through to the division and separation of their daughter cells. Coupled with flow cytometry quantification, this protocol enables for measurement of kinetic progression of the cell cycle in the absence of either mechanically- or chemically- induced cellular stresses commonly associated with other cell cycle synchronization methodologies 10. In the following sections we will discuss the methodology, as well as some of its applications in biomedical research.

Tracking subtle changes in the progression and kinetics of cell cycle stages can be accomplished by use of a combination of metabolic labeling of nucleic acids with BrdU and total genomic DNA staining via Propidium Iodide. This method avoids the need of chemical synchronization of cycling cells, thereby preventing the introduction of non-specific DNA damage, which in turn affects cell cycle progression.

신진 대사 레이블 및 유동세포계측법와 세포주기 진행의 동력학 측정

Precise control of the initiation and subsequent progression through the various phases of the cell cycle are of paramount importance in proliferating ...

Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes

Fluorescent cell tracking dyes, in combination with flow and image cytometry, are powerful tools with which to study the interactions and fates of different cell types in vitro and in vivo.1-5 Although there are literally thousands of publications using such dyes, some of the most commonly encountered cell tracking applications include monitoring of:
<ol>
	<li>stem and progenitor cell quiescence, proliferation and/or differentiation6-8</li>
	<li>antigen-driven membrane transfer9 and/or precursor cell proliferation3,4,10-18 and</li>
	<li>immune regulatory and effector cell function1,18-21.</li>
</ol>
Commercially available cell tracking dyes vary widely in their chemistries and fluorescence properties but the great majority fall into one of two classes based on their mechanism of cell labeling. "Membrane dyes", typified by PKH26, are highly lipophilic dyes that partition stably but non-covalently into cell membranes1,2,11. "Protein dyes", typified by CFSE, are amino-reactive dyes that form stable covalent bonds with cell proteins4,16,18. Each class has its own advantages and limitations. The key to their successful use, particularly in multicolor studies where multiple dyes are used to track different cell types, is therefore to understand the critical issues enabling optimal use of each class2-4,16,18,24.
The protocols included here highlight three common causes of poor or variable results when using cell-tracking dyes. These are:
<ol>
	<li>Failure to achieve bright, uniform, reproducible labeling. This is a necessary starting point for any cell tracking study but requires attention to different variables when using membrane dyes than when using protein dyes or equilibrium binding reagents such as antibodies.</li>
	<li>Suboptimal fluorochrome combinations and/or failure to include critical compensation controls. Tracking dye fluorescence is typically 102 - 103 times brighter than antibody fluorescence. It is therefore essential to verify that the presence of tracking dye does not compromise the ability to detect other probes being used.</li>
	<li>Failure to obtain a good fit with peak modeling software. Such software allows quantitative comparison of proliferative responses across different populations or stimuli based on precursor frequency or other metrics. Obtaining a good fit, however, requires exclusion of dead/dying cells that can distort dye dilution profiles and matching of the assumptions underlying the model with characteristics of the observed dye dilution profile.</li>
</ol>
Examples given here illustrate how these variables can affect results when using membrane and/or protein dyes to monitor cell proliferation.

Successful use of cell tracking dyes to monitor immune cell function and proliferation involves several critical steps. We describe methods for: 1) obtaining bright, uniform, reproducible label-ing with membrane dyes; 2) selecting fluorochromes and data acquisition conditions; and 3) choosing a model to quantify cell proliferation based on dye dilution.

셀 추적 염료를 사용하여 전지 부문 모니터링에 최적화 된 착색 및 확산 모델링 방법

Fluorescent cell tracking dyes, in combination with flow and image cytometry, are powerful tools with which to study the interactions and fates of ...

Measuring Intracellular Ca2+ Changes in Human Sperm using Four Techniques: Conventional Fluorometry, Stopped Flow Fluorometry, Flow Cytometry and Single Cell Imaging

Spermatozoa are male reproductive cells especially designed to reach, recognize and fuse with the egg. To perform these tasks, sperm cells must be prepared to face a constantly changing environment and to overcome several physical barriers. Being in essence transcriptionally and translationally silent, these motile cells rely profoundly on diverse signaling mechanisms to orient themselves and swim in a directed fashion, and to contend with challenging environmental conditions during their journey to find the egg. In particular, Ca2+-mediated signaling is pivotal for several sperm functions: activation of motility, capacitation (a complex process that prepares sperm for the acrosome reaction) and the acrosome reaction (an exocytotic event that allows sperm-egg fusion). The use of fluorescent dyes to track intracellular fluctuations of this ion is of remarkable importance due to their ease of application, sensitivity, and versatility of detection. Using one single dye-loading protocol we utilize four different fluorometric techniques to monitor sperm Ca2+ dynamics. Each technique provides distinct information that enables spatial and/or temporal resolution, generating data both at single cell and cell population levels.

Measuring Intracellular Ca2+ Changes in Human Sperm using Four Techniques: Conventional Fluorometry, Stopped Flow Fluorometry, Flow Cytometry and Single Cell Imaging

Intracellular Ca2+ dynamics are very important in sperm physiology and Ca2+-sensitive fluorescent dyes constitute a versatile tool to study them. Population experiments (fluorometry and stopped flow fluorometry) and single cell experiments (flow cytometry and single cell imaging) are used to track spatio-temporal [Ca2+] changes in human sperm cells.

세포 내 칼슘 측정<sup&gt; 2 +</sup개의 기술하여 인간 정자에서&gt; 변경 : 기존 Fluorometry은 흐름 Fluorometry, 유동 세포 계측법 및 단일 세포 이미징을 중지

Spermatozoa  are male reproductive cells especially designed to reach, recognize and fuse  with the egg. To perform these tasks, sperm cells must be ...

Identification of a Murine Erythroblast Subpopulation  Enriched in Enucleating Events by Multi-spectral Imaging Flow Cytometry

Erythropoiesis in mammals concludes with the dramatic process of enucleation that results in reticulocyte formation. The mechanism of enucleation has not yet been fully elucidated. A common problem encountered when studying the localization of key proteins and structures within enucleating erythroblasts by microscopy is the difficulty to observe a sufficient number of cells undergoing enucleation.&#160;We have developed a novel analysis protocol using multiparameter high-speed cell imaging in flow (Multi-Spectral Imaging Flow Cytometry), a method that combines immunofluorescent microscopy with flow cytometry, in order to identify efficiently a significant number of enucleating events, that allows to obtain measurements and perform statistical analysis.
We first describe here two in vitro erythropoiesis culture methods used in order to synchronize murine erythroblasts and increase the probability of capturing enucleation at the time of evaluation.&#160;Then, we describe in detail the staining of erythroblasts after fixation and permeabilization in order to study the localization of intracellular proteins or lipid rafts during enucleation by multi-spectral imaging flow cytometry.&#160;Along with size and DNA/Ter119 staining which are used to identify the orthochromatic erythroblasts, we utilize the parameters &#8220;aspect ratio&#8221; of a cell in the bright-field channel that aids in the recognition of elongated cells and &#8220;delta centroid XY Ter119/Draq5&#8221; that allows the identification of cellular events in which the center of Ter119 staining (nascent reticulocyte) is far apart from the center of Draq5 staining (nucleus undergoing extrusion), thus indicating a cell about to enucleate.&#160;The subset of the orthochromatic erythroblast population with high delta centroid and low aspect ratio is highly enriched in enucleating cells.

The present protocol describes a novel method of identifying a population of enucleating orthochromatic erythroblasts by multi-spectral imaging flow cytometry, providing a visualization of the erythroblast enucleation process.

멀티 스펙트럼 이미징 유동 세포 계측법에 의한 탈핵 이벤트에 쥐의 적혈구 모세포 모집단 인리 치드의 확인

Erythropoiesis in mammals concludes with the dramatic process of enucleation that results in reticulocyte formation. The mechanism of enucleation has not ...

In Vivo 4-Dimensional Tracking of Hematopoietic Stem and Progenitor Cells in Adult Mouse Calvarial Bone Marrow

Through a delicate balance between quiescence and proliferation, self renewal and production of differentiated progeny, hematopoietic stem cells (HSCs) maintain the turnover of all mature blood cell lineages. The coordination of the complex signals leading to specific HSC fates relies upon the interaction between HSCs and the intricate bone marrow microenvironment, which is still poorly understood[1-2].
We describe how by combining a newly developed specimen holder for stable animal positioning with multi-step confocal and two-photon in vivo imaging techniques, it is possible to obtain high-resolution 3D stacks containing HSPCs and their surrounding niches and to monitor them over time through multi-point time-lapse imaging. High definition imaging allows detecting ex vivo labeled hematopoietic stem and progenitor cells (HSPCs) residing within the bone marrow. Moreover, multi-point time-lapse 3D imaging, obtained with faster acquisition settings, provides accurate information about HSPC movement and the reciprocal interactions between HSPCs and stroma cells.
Tracking of HSPCs in relation to GFP positive osteoblastic cells is shown as an exemplary application of this method. This technique can be utilized to track any appropriately labeled hematopoietic or stromal cell of interest within the mouse calvarium bone marrow space.

In Vivo 4-Dimensional Tracking of Hematopoietic Stem and Progenitor Cells in Adult Mouse Calvarial Bone Marrow

The nature of the interactions between hematopoietic stem and progenitor cells (HSPCs) and bone marrow niches is poorly understood. Custom hardware modifications and a multi-step acquisition protocol allow the use of two-photon and confocal microscopy to image ex vivo labeled HSPCs homed within bone marrow areas, tracking interactions and movement.

성인 마우스 두개골 골수에서 조혈 줄기 및 전구 세포의 생체 내 4 차원 추적에서

Through a delicate balance between quiescence and proliferation, self renewal and production of differentiated progeny, hematopoietic stem cells (HSCs) ...

Cytosolic Calcium Measurements in Renal Epithelial Cells by Flow Cytometry

A variety of cellular processes, both physiological and pathophysiological, require or are governed by calcium, including exocytosis, mitochondrial function, cell death, cell metabolism and cell migration to name but a few. Cytosolic calcium is normally maintained at low nanomolar concentrations; rather it is found in high micromolar to millimolar concentrations in the endoplasmic reticulum, mitochondrial matrix and the extracellular compartment. Upon stimulation, a transient increase in cytosolic calcium serves to signal downstream events. Detecting changes in cytosolic calcium is normally performed using a live cell imaging set up with calcium binding dyes that exhibit either an increase in fluorescence intensity or a shift in the emission wavelength upon calcium binding. However, a live cell imaging set up is not freely accessible to all researchers. Alternative detection methods have been optimized for immunological cells with flow cytometry and for non-immunological adherent cells with a fluorescence microplate reader. Here, we describe an optimized, simple method for detecting changes in epithelial cells with flow cytometry using a single wavelength calcium binding dye. Adherent renal proximal tubule epithelial cells, which are normally difficult to load with dyes, were loaded with a fluorescent cell permeable calcium binding dye in the presence of probenecid, brought into suspension and calcium signals were monitored before and after addition of thapsigargin, tunicamycin and ionomycin.

Calcium is involved in numerous physiological and pathophysiological signaling pathways. Live cell imaging requires specialized equipment and can be time consuming. A quick, simple method using a flow cytometer to determine relative changes in cytosolic calcium in adherent epithelial cells brought into suspension was optimized.

유동 세포 계측법에 의한 신장 상피 세포에서 세포 내 칼슘 측정

A variety of cellular processes, both physiological and pathophysiological, require or are governed by calcium, including exocytosis, mitochondrial ...

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Immunohistochemistry is a commonly used clinical and research lab detection technique for investigating protein expression and localization within tissues. Many semi-quantitative systems have been developed for scoring expression using immunohistochemistry, but inherent subjectivity limits reproducibility and accuracy of results. Furthermore, the investigation of spatially overlapping biomarkers such as nuclear transcription factors is difficult with current immunohistochemistry techniques. We have developed and optimized a system for simultaneous investigation of multiple proteins using high throughput methods of multiplexed immunohistochemistry and multispectral imaging. Multiplexed immunohistochemistry is performed by sequential application of primary antibodies with secondary antibodies conjugated to horseradish peroxidase or alkaline phosphatase. Different chromogens are used to detect each protein of interest. Stained slides are loaded into an automated slide scanner and a protocol is created for automated image acquisition. A spectral library is created by staining a set of slides with a single chromogen on each. A subset of representative stained images are imported into multispectral imaging software and an algorithm for distinguishing tissue type is created by defining tissue compartments on images. Subcellular compartments are segmented by using hematoxylin counterstain and adjusting the intrinsic algorithm. Thresholding is applied to determine positivity and protein co-localization. The final algorithm is then applied to the entire set of tissues. Resulting data allows the user to evaluate protein expression based on tissue type (ex. epithelia vs. stroma) and subcellular compartment (nucleus vs. cytoplasm vs. plasma membrane). Co-localization analysis allows for investigation of double-positive, double-negative, and single-positive cell types. Combining multispectral imaging with multiplexed immunohistochemistry and automated image acquisition is an objective, high-throughput method for investigation of biomarkers within tissues.

Immunohistochemistry is a powerful lab technique for evaluating protein localization and expression within tissues. Current semi-automated methods for quantitation introduce subjectivity and often create irreproducible results. Herein, we describe methods for multiplexed immunohistochemistry and objective quantitation of protein expression and co-localization using multispectral imaging.

멀티 플렉스 면역 조직 화학적 염색 및 멀티 스펙트럼 영상을 사용하여 단백질 발현 및 공동 현지화의 정량

Immunohistochemistry is a commonly used clinical and research lab detection technique for investigating protein expression and localization within ...

Measuring Endoreduplication by Flow Cytometry of Isolated Tuber Protoplasts

Endoreduplication, the replication of a cell's nuclear genome without subsequent cytokinesis, yields cells with increased DNA content and is associated with specialization, development and increase in cellular size. In plants, endoreduplication seems to facilitate the growth and expansion of certain tissues and organs. Among them is the tuber of potato (Solanum tuberosum), which undergoes considerable cellular expansion in fulfilling its function of carbohydrate storage. Thus, endoreduplication may play an important role in how tubers are able to accommodate this abundance of carbon. However, the cellular debris resulting from crude nuclear isolation methods of tubers, methods that can be used effectively with leaves, precludes the estimation of the tuber endoreduplication index (EI). This article presents a technique for assessing tuber endoreduplication through the isolation of protoplasts while demonstrating representative results obtained from different genotypes and compartmentalized tuber tissues. The major limitations of the protocol are the time and reagent costs required for sample preparation as well as relatively short lifespan of samples after lysis of protoplasts. While the protocol is sensitive to technical variation, it represents an improvement over traditional methods of nuclear isolation from these large specialized cells. Possibilities for improvements to the protocol such as recycling enzyme, the use of fixatives, and other alterations are proposed.

The protocol described herein is a method for measuring endoreduplication within tubers of potato (Solanum tuberosum). It includes plasmolysis and protoplast extraction steps to decrease the noise and debris in downstream flow cytometric analysis.

격리 된 괴 경 Protoplasts의 Cytometry에 의해 측정 Endoreduplication

Endoreduplication, the replication of a cell's nuclear genome without subsequent cytokinesis, yields cells with increased DNA content and is associated ...