Intracellulær Farvning og flowcytometri at identificere lymfocytundergrupper inden Murine Aorta, Nyre og lymfeknuder i en model af hypertension
Summary
Denne artikel giver detaljeret metode til at identificere og kvantificere funktionelle T lymfocyt delmængder stede i murine nyre, aorta og lymfeknuder ved intracellulær farvning og flowcytometri. Modellen af angiotensin II-induceret hypertension blev valgt til at forklare, trin-for-trin, de procedurer og grundlæggende principper for flowcytometri og intracellulær farvning.
Abstract
It is now well known that T lymphocytes play a critical role in the development of several cardiovascular diseases1,2,3,4,5. For example, studies from our group have shown that hypertension is associated with an excessive accumulation of T cells in the vessels and kidney during the development of experimental hypertension6. Once in these tissues, T cells produce several cytokines that affect both vascular and renal function leading to vasoconstriction and sodium and water retention1,2. To fully understand how T cells cause cardiovascular and renal diseases, it is important to be able to identify and quantify the specific T cell subsets present in these tissues. T cell subsets are defined by a combination of surface markers, the cytokines they secrete, and the transcription factors they express. The complexity of the T cell population makes flow cytometry and intracellular staining an invaluable technique to dissect the phenotypes of the lymphocytes present in tissues. Here, we provide a detailed protocol to identify the surface and intracellular markers (cytokines and transcription factors) in T cells isolated from murine kidney, aorta and aortic draining lymph nodes in a model of angiotensin II induced hypertension. The following steps are described in detail: isolation of the tissues, generation of the single cell suspensions, ex vivo stimulation, fixation, permeabilization and staining. In addition, several fundamental principles of flow cytometric analyses including choosing the proper controls and appropriate gating strategies are discussed.
Introduction
De seneste oplysninger viser, at den adaptive immunsystem, især T-lymfocytter, spiller en afgørende rolle i udviklingen af flere hjerte-kar-sygdomme 1,2,3,4,5. For eksempel i modellen af angiotensin II-induceret hypertension, en akkumulering af T-celler i karrene og nyrer fra mus er blevet beskrevet 6. Det vaskulære akkumulation er overvejende adventitia og perivaskulær fedt. I nyrerne T-celler akkumulerer i både medulla og renal cortex. Afhængigt af hvilken delmængde er involveret, disse T-celler giver anledning til forskellige cytokiner, der kan påvirke vaskulære og nyrefunktion og føre til udvikling af patologi (gennemgået af McMaster et al. 6).
CD4 + T-hjælper-lymfocytter kan opdeles i flere delmængder: T hjælper 1 (Th1), Th2, Th9, Th17, Th22, T regulerende (Treg) celler og T follikulær hjælper (TFH) celler baseret på deres funktioner og underskrift cytoKines 7. På samme måde kan CD8 + cytotoksiske T-celler klassificeres som Tc1, TC2, Tc17 eller TC9 8. Der er også dobbelt negative T-celler (dvs. celler, som ikke udtrykker CD4 eller CD8 T-cellemarkører). En undergruppe af disse celler besidder en alternativ gamma delta T-cellereceptor (i stedet for de klassiske alfa- og beta-receptorer) og er derfor benævnt gamma delta T-celler. Den multi-parameter analyse ved flowcytometri af overfladen markering, cytokin og transskriptionsfaktor udgør den bedste fremgangsmåde til at identificere disse celler. Selv om denne metode i udstrakt grad anvendes inden for immunologi, er det mindre godt beskrevet i faste organer og i fastsættelsen af cardiovaskulære sygdomme.
Historisk set blev identifikationen af lymfocytter i væv begrænset til immunhistokemi eller RT-PCR fremgangsmåder. Selvom immunhistokemi og immunofluorescens er stærke metoder til at bestemme vævsfordelingen af et antigen af intpåløbne, de er utilstrækkelige til fænotypisk identificere undergrupper involverede. Derudover, medens RT-PCR-analyse er nyttig til at detektere mRNA-ekspression af antigener, cytokiner eller transkriptionsfaktorer, den tillader ikke påvisningen af multiple proteiner samtidigt ved de enkelte celler.
Fremkomsten af flowcytometri, især ved kombination med intracellulær farvning til påvisning af cytokiner og transkriptionsfaktorer, giver undersøgere med en kraftfuld teknik, der tillader identifikation og kvantificering på enkelt celle niveau af immuncelleundergrupper i faste organer. Vi har optimeret en intracellulær farvning assay til at identificere ved flowcytometri de store T-celle-undergrupper til stede i murin nyre, aorta og aorta drænende lymfeknuder i en model for angiotensin II-induceret hypertension. Optimeringen af hvert trin: vævsfordøjelse, ex vivo-aktivering, permeabilisering, og overfladen og intracellulære farvningsresultater i et stærkt reproducerbart assay, der kan anvendes på andre kardiovaskulære og renale sygdomsmodeller.
Protocol
Representative Results
Discussion
The protocol described herein has been optimized to properly identify T cell subsets present within murine kidneys, aorta and lymph nodes. This protocol can be easily adapted to examine other immune cell subsets such as B lymphocytes and innate immune cells and can be modified to include other tissue types. The digestion step is critical and has to be modified and optimized for each tissue9. A prolonged digestion step or the use of an inappropriate enzyme can affect the stability of antigen expression. Similar…
Disclosures
The authors have nothing to disclose.
Acknowledgements
Dette arbejde blev støttet af en American Heart Association Fellowship Award (16POST29950007) til FL, en uddannelse bevilling fra National Institutes of Health (NIH T32 HL069765) til BLD, en American Heart Association Fellowship Award (14POST20420025) til MA Saleh, og en NIH K08 award (HL121671) til MSM. MSM er også understøttet af en forskningsbevilling fra Gilead Sciences, Inc.
Materials
| Collagenase D | ROCHE | 11088882001 | |
| Collagenase A | ROCHE | 10103586001 | |
| Collagenase B | ROCHE | 11088815001 | |
| Dnase | ROCHE | 10104159001 | |
| 1X Red blood cell lysis buffer | eBioscience | 00-4333-57 | |
| RPMI Medium 1614 1X | Gibco | 11835-030 | |
| DPBS without calcium and magnesium | Gibco | 14190-144 | |
| Percoll | GE Healthcare | 17-5445-02 | For density gradient centrifugation |
| GentleMACS ™ C tube | Miltenyi Biotec | 130-096-334 | |
| GentleMACS dissociator device | Miltenyi Biotec | 130-093-235 | Use the program SPLEEN_04 |
| Cell activation cocktail (with Brefeldin A) | Biolegend | 423303 | |
| anti-CD16/32 | eBioscience | 14-0161-81 | dilute 1:100 |
| LIVE/DEAD fixable violet dead cell stain kit | Life Technologies | L34955 | |
| Transcription factor buffer set | BD Pharmingen | 562725 | |
| OneComp eBeads | eBioscience | 01-1111-42 | |
| 123 count eBeads | eBioscience | 01-1234-42 | |
| CD45 AmCyan (clone 30-F11) | BioLegend | 103138 | |
| CD3 PerCP-Cy5.5 (clone 17A2) | BioLegend | 100218 | |
| IL-17A FITC (clone TC11-18H10.1) | BioLegend | 506910 | |
| IL-17F APC (clone 9D3.1C8) | BioLegend | 517004 | |
| CD4 APC-Cy7 (clone GK1.5) | BD Biosciences | 560181 | |
| CD8 APC (clone 53-67) | eBioscience | 17-0081-82 | |
| T-bet PE-Cy7 (clone 4B10) | BioLegend | 644823 | |
| IFNγ FITC (clone XMG1.2) | BD Biosciences | 557724 |
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