The identification of molecules associated with specific genomic regions of interest is required to understand the mechanisms of regulation of the functions of these regions. This protocol describes procedures to perform engineered DNA-binding molecule-mediated chromatin imunoprecipitation (enChIP) for identification of proteins and RNAs associated with a specific genomic region.
The identification of molecules associated with specific genomic regions of interest is required to understand the mechanisms of regulation of the functions of these regions. To enable the non-biased identification of molecules interacting with a specific genomic region of interest, we recently developed the engineered DNA-binding molecule-mediated chromatin immunoprecipitation (enChIP) technique. Here, we describe how to use enChIP to isolate specific genomic regions and identify the associated proteins and RNAs. First, a genomic region of interest is tagged with a transcription activator-like (TAL) protein or a clustered regularly interspaced short palindromic repeats (CRISPR) complex consisting of a catalytically inactive form of Cas9 and a guide RNA. Subsequently, the chromatin is crosslinked and fragmented by sonication. The tagged locus is then immunoprecipitated and the crosslinking is reversed. Finally, the proteins or RNAs that are associated with the isolated chromatin are subjected to mass spectrometric or RNA sequencing analyses, respectively. This approach allows the successful identification of proteins and RNAs associated with a genomic region of interest.
זיהוי של מולקולות הקשורות לאזורים הגנומי ספציפיים של העניין נדרש להבין את מנגנוני רגולציה של פונקציות הגנומי כגון שעתוק ורגולציה אפיגנטיים. למרות כמה טכניקות פותחו לאנליזה ביוכימית של אזורים הגנומי ספציפיים 1-7, הם לא בשימוש נרחב בשלב זה בגלל הבעיות שלהם הפנימיות כגון יישום מוגבל (למשל, רק ללוקוסים גבוה עותק מספר או לוקוסים עם חזרות) ו נדרשו זמן ומאמצים רבים מדי.
על מנת לבצע את הניתוח ביוכימי של אזורים הגנומי ספציפיים בקלות, פיתחנו שתי טכנולוגיות immunoprecipitation הכרומטין מוקד ספציפי (שבב), כלומר insertional השבב (iChIP) 8-13 ומהונדס שבב תיווך מולקולת ה- DNA מחייב (enChIP) 14-17 . בiChIP, מוקד של העניין מתויג על ידי רצפי הכרת החדרה של חלבון קושר DNA אקסוגני כגון לקסא המוקד מבודד לאחר מכן על ידי טיהור זיקה באמצעות החלבון קושר DNA מתויג. מתחמים חוזר palindromic קצר interspaced באופן קבוע בenChIP, מהונדס מולקולות ה- DNA מחייבת, כגון חלבוני אבץ-אצבע, חלבוני שעתוק כמו activator (טל), והתקבץ (CRISPR), משמשים לתייג מוקד של עניין (איור 1). בהמשך לכך, אזור גנומי מבודד על ידי טיהור זיקה של מולקולות ה- DNA מחייבת המתויגות.
אחד היתרונות של enChIP על iChIP הוא שההכנסה של רצפי הכרה של חלבון קושר DNA אקסוגני היא לא הכרחית. המיקוד של לוקוסים באמצעות מתחמי CRISPR בהיקף של צורת catalytically פעילה של Cas9 (dCas9) וRNA מדריך (gRNA) הוא הרבה יותר קל מאשר המיקוד של אזורים אלה על ידי iChIP או enChIP באמצעות חלבוני טל ואבץ-אצבע. כאן, אנו מתארים פרוטוקול צעד-אחר-צעד לenChIP בשילוב עם ספקטרומטריית מסה ורצף RNA (RNA-Seq) לזהות מוקד-associaחלבוני טד וRNAs, בהתאמה.
Here, we describe the purification of specific genomic regions using engineered DNA-binding molecules such as the CRISPR system and TAL proteins, and the identification of proteins and RNAs bound to these genomic regions. Binding of engineered DNA-binding molecules to the genome may affect chromatin structure, including nucleosome positioning, and may abrogate genomic functions, as described in CRISPR interference experiments21. To avoid these potential aberrant effects, we propose specific guidelines for choosing target genomic regions. First, to avoid potential inhibition of the recruitment of RNA polymerases and transcription factors, as well as disruption of nucleosome positioning around the transcription start site, the target regions for analyses of promoter regions should be several hundred base pairs upstream of (5′ to) the transcription start site. By contrast, when analyzing genomic regions with distinct boundaries, such as enhancers and silencers, genomic regions that are directly juxtaposed to these regions can be targeted because it is less likely that the binding of engineered DNA-binding molecules will affect their functions. Furthermore, it is best to avoid using target regions that are conserved among different species, because important DNA-binding molecules often bind to evolutionarily conserved regions and inhibition of their binding might disrupt the functions of the target genomic regions. In this regard, it is always necessary to check that the function of the target genomic region is maintained in the established cells used for enChIP analyses. Because multiple gRNAs can be tested easily and it is tedious and expensive to generate multiple versions of TAL or zinc-finger proteins recognizing different target genomic regions, enChIP using CRISPR is more advantageous than enChIP using other proteins.
It has been shown that dCas9 binds to off-target sites although affinity to those sites might be weaker than that to the target sites22-25. There are several ways to manage contamination of molecules bound to those off-target sites. First, the use of several, at least two, different gRNAs would be recommended. Those molecules commonly observed in enChIP using distinct gRNAs would be true positives. Second, comparison of different conditions for enChIP would be effective in cancelling contamination of non-specific molecules and molecules bound to off-target sites. Examples of those comparison sets would be (i) stimulation (-) and (+), or (ii) different cell types such as T cells vs. B cells. Finally, quantitative analysis of binding of candidate molecules should be performed to confirm their specific binding to the target sites. It is preferable to prepare cells expressing only dCas9 but not gRNA as a negative control.
Using enChIP analyses, we were able to successfully identify a number of known and novel molecules interacting with specific genomic regions (Tables 1-3)14-17. However, this technique failed to detect some other known proteins interacting with these regions. For example, STAT1 reportedly associates with the IRF-1 promoter upon IFNγ stimulation8, but our enChIP-SILAC analysis did not detect STAT1 as a protein induced to interact with this genomic region16. In addition, in the enChIP-MS analysis of telomeres, we did not detect shelterin proteins consisting of TRF-1 and TRF-215, which have been shown to interact with telomeres26. There are a few potential reasons for these discrepancies. First, the stoichiometry of binding of Stat1 to the IRF-1 promoter might be very low. It is reasonable that enChIP-MS, including enChIP-SILAC, detects proteins that are more abundantly associated with target genomic regions; hence, the analysis of more cells might be necessary to detect these proteins. Increases in the sensitivities of MS instruments would also contribute to the efficient detection of proteins with low stoichiometric binding. Second, some proteins, possibly including Stat1 and shelterins, might be difficult targets for MS analyses. Third, in our analysis of telomere-binding proteins15, the 3×FLAG-TAL proteins recognizing telomeres (3×FN-Tel-TAL) might have blocked the binding of shelterins to telomeres in a competitive fashion.
In contrast to the relative difficulty of detecting transcription factors binding to specific genomic regions using enChIP, we successfully identified epigenetic regulators such as histone modification enzymes using enChIP analyses. The success of this technique may be due to the fact that epigenetic regulators bind to a broad range of genomic regions; hence, more proteins per genomic region are available for MS. Because epigenetic regulators are increasingly recognized as important targets for drugs against intractable diseases such as cancer, enChIP would be a useful tool for the identification of epigenetic drug targets.
The authors have nothing to disclose.
עבודה זו נתמכה על ידי קרן מדע טאקדה (TF); זכוכית קרן אסאהי; קרן Uehara הזיכרון (HF); Kurata זיכרון Hitachi מדע וטכנולוגית קרן (TF וHF); גרנט ב- סיוע למדענים צעירים (B) (# 25,830,131), גרנט ב- סיוע למחקר מדעי (ג) (# 15K06895) (TF); וגרנט ב- סיוע, גרנט ב- סיוע למחקר מדעי (ב) (# 15H04329), גרנט ב- סיוע למחקר גישוש (למחקר מדעי על "מחזור תמלול 'תחומי חדשניים (# 25,118,512 & # 15H01354) # 26650059) ו'הגנום תמיכה '(# 221S0002) (HF) ממשרד החינוך, התרבות, הספורט, המדע והטכנולוגיה של יפן.
gBlock synthesis service | Life Technologies | Gene Synthesis by GeneArt | |
gBlock synthesis service | IDT (Integrated DNA Technologies) | gBlocks Gene Fragments | |
pSIR-neo | Addgene | 51128 | |
pSIR-GFP | Addgene | 51134 | |
pSIR-DsRed-Express2 | Addgene | 51135 | |
pSIR-hCD2 | Addgene | 51143 | |
TAL synthesis service | Life Technologies | GeneArt Precision TALs | |
3xFLAG-dCas9/pCMV-7.1 | Addgene | 47948 | |
3×FLAG-dCas9/pMXs-puro | Addgene | 51240 | |
3×FLAG-dCas9/pMXs-IG | Addgene | 51258 | |
3×FLAG-dCas9/pMXs-I2 | Addgene | 51259 | |
3×FLAG-dCas9/pMXs-neo | Addgene | 51260 | |
anti-FLAG M2 Ab | Sigma-Aldrich | F1804 | |
FITC-conjugated anti-FLAG M2 | Sigma-Aldrich | F4049 | |
DMEM medium for SILAC | Life Technologies | 89985 | Other medium can be purchased from Life Technologies |
Dialyzed FBS for SILAC | Life Technologies | 89986 | |
L-Lysine-2HCl for SILAC | Life Technologies | 89987 | for Light medium |
L-Arginine-HCl for SILAC | Life Technologies | 89989 | for Light medium |
L-Lysine-2HCl, 13C6 for SILAC | Life Technologies | 89988 | For Heavy medium |
L-Arginine-HCl, 13C6, 15N4 for SILAC | Life Technologies | 89990 | For Heavy medium |
Complete, mini, EDTA-free | Roche Diagnostics | 4693159 | |
Ultrasonic Disruptor UD-201 | Tomy Seiko | ||
ChIP DNA Clean & Concentrator | Zymo Research | D5205 | |
Dynabeads-Protein G | Life Technologies | DB10004 | |
RNasin Plus RNase Inhibitor | Promega | N2611 | |
Isogen II | Nippon Gene | 311-07361 | |
Direct-zol RNA Miniprep kit | Zymo Research | R2050 | |
LTQ Orbitrap Velos | Thermo Fisher Scientific | a component of a nanoLC-MS/MS system for MS analysis | |
nanoLC | Advance, Michrom Bioresources | a component of a nanoLC-MS/MS system for MS analysis | |
HTC-PAL autosampler | CTC Analytics | a component of a nanoLC-MS/MS system for MS analysis |