We thank all past and present members of the Nobile and Hernday laboratories for feedback on the manuscript.&#160;This work was supported by the National Institutes of Health (NIH) National Institute of General Medical Sciences (NIGMS) award number R35GM124594 and by the Kamangar family in the form of an endowed chair to C.J.N. This work was also supported by the NIH National Institute of Allergy and Infectious Diseases (NIAID) award number R15AI137975 to A.D.H. C.L.E. was supported by the NIH National Institute of Dental and Craniofacial Research (NIDCR) fellowship number F31DE028488. The content is the sole responsibility of the authors and does not represent the views of the funders. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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</ol>

Clarissa J. Nobile is a cofounder of BioSynesis, Inc., a company developing diagnostics and therapeutics for biofilm infections.

This protocol presents a comprehensive experimental and computational pipeline for genome-wide localization of regulatory TFs in C. albicans. It is designed to be highly accessible to anyone with standard microbiology and molecular biology training. By leveraging the high dynamic range and low sample input requirements of the CUT&amp;RUN assay and including optimizations for the localization of TF-DNA binding interactions in C. albicans biofilm and planktonic cultures, this protocol presents a powerful ...

Candida albicans is a clinically relevant, polymorphic human fungal pathogen that exists in a variety of different modes of growth, such as the planktonic (free-floating) mode of growth and as communities of tightly adhered cells protected by an extracellular matrix, known as the biofilm mode of growth1,2,3. Similar to other developmental and cellular processes, biofilm development is an important C. albicans virulence trait that is known to be controlled at the transcriptional level by regulatory transcription factors (TFs) that bind to DNA in a sequence-specific manner4. Recently, chromatin regulators and histone modifiers have also emerged as important regulators of C. albicans biofilm formation5 and morphogenesis6 by mediating DNA accessibility. To understand the complex biology of this important fungal pathogen, effective methods to determine the genome-wide localization of specific TFs during distinct developmental and cellular processes is valuable.
Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a widely used method to investigate protein-DNA interactions in C. albicans5,6 and has largely replaced the more classical chromatin immunoprecipitation followed by microarray (ChIP-chip)9 method. Both ChIP-seq and ChIP-chip methods, however, require a large number of input cells10, which can be a complicating factor when investigating TFs in the context of specific samples and modes of growth, such as biofilms collected from patients or animal models of infection. In addition, the chromatin immunoprecipitation (ChIP) assay often yields a significant amount of background signal throughout the genome, requiring a high level of enrichment for the target of interest to sufficiently separate signal from noise. While the ChIP-chip assay is largely outdated today, the sequencing depths necessary for ChIP-seq make this assay prohibitively expensive for many researchers, particularly those studying multiple TFs and/or chromatin-associated proteins.

Cleavage under targets and release using nuclease (CUT&#38;RUN) is an attractive alternative to ChIP-seq. It was developed by the Henikoff lab in 2017 to circumvent the limitations of ChIP-seq and chromatin endogenous cleavage followed by sequencing ChEC-seq11,12, another method to identify protein-DNA interactions on a genome-wide level, while providing high-resolution, genome-wide mapping of TFs and chromatin-associated proteins13. CUT&#38;RUN relies on the targeted digestion of chromatin within permeabilized nuclei using tethered micrococcal nucleases, followed by sequencing of the digested DNA fragments9,10. As DNA fragments are specifically generated at the loci that are bound by a protein of interest, rather than being generated throughout the genome via random fragmentation as in ChIP assays, the CUT&#38;RUN approach results in greatly reduced background signals and, thus, requires 1/10th&#160;of the sequencing depth compared to ChIP-seq11,13,14. These improvements ultimately lead to significant reductions in sequencing costs and reductions in the total number of input cells needed as starting material for each sample.
Here, a robust CUT&#38;RUN protocol is described that has been adapted and optimized for determining the genome-wide localization of TFs in C. albicans cells isolated from biofilms and planktonic cultures. A thorough data analysis pipeline is also presented, which enables the processing and analysis of the resulting sequence data and requires users to have minimal expertise in coding or bioinformatics. Briefly, this protocol describes epitope tagging of TF-coding genes, harvesting of biofilm and planktonic cells, isolation of intact permeabilized nuclei, incubation with primary antibodies against the specific protein or epitope-tagged protein of interest, tethering of the chimeric A/G-micrococcal nuclease (pAG-MNase) fusion proteins to the primary antibodies, genomic DNA recovery after chromatin digestion, and preparation of genomic DNA libraries for sequencing.
The experimental CUT&#38;RUN protocol is followed by a purpose-built data analysis pipeline, which takes raw DNA sequencing reads in FASTQ format and implements all required processing steps to provide a complete list of significantly enriched loci bound by the TF of interest (targeted by the primary antibody). Note that multiple steps of the described library preparation protocol have been specifically adapted and optimized for CUT&#38;RUN analysis of TFs (as opposed to nucleosomes). While the data presented in this manuscript were generated using TF-specific adaptations of a commercial CUT&#38;RUN kit, these protocols have also been validated using individually sourced components (i.e., pAG-MNase enzyme and magnetic DNA purification beads) and in-house-prepared buffers, which can significantly reduce experimental cost. The comprehensive experimental and data analysis protocols are described in detail below in a step-by-step format. All reagents and critical equipment, as well as buffer and media recipes, are listed in the Table of Materials and Supplementary File 1, respectively.

<table><tbody><tr><td>0.22 &amp;mu;m filter</td><td>Millipore Sigma</td><td>SLGPM33RS</td><td></td></tr><tr><td>0.65 mL low-adhesion tubes</td><td>VWR</td><td>490003-190</td><td></td></tr><tr><td>1 M CaCl&lt;sub&gt;2&lt;/sub&gt;</td><td>Fisher Scientific</td><td>50-152-341</td><td></td></tr><tr><td>1 M PIPES</td><td>Fisher Scientific</td><td>AAJ61224AK</td><td></td></tr><tr><td>12-well untreated cell culture plates</td><td>Corning</td><td>351143</td><td></td></tr><tr><td>2-mercaptoethanol</td><td>Sigma-Aldrich</td><td>60-24-2</td><td></td></tr><tr><td>2% Digitonin</td><td>Fisher Scientific</td><td>CHR103MI</td><td></td></tr><tr><td>50 mL conical tubes</td><td>VWR</td><td>89039-658</td><td></td></tr><tr><td>5x phusion HF buffer</td><td>Fisher Scientific</td><td>F530S</td><td>Item part of the Phusion high fidelity DNA polymerase; referred to in text as &quot;DNA polymerase buffer&quot;</td></tr><tr><td>Agar</td><td>Criterion</td><td>C5001</td><td></td></tr><tr><td>Agencourt AMPure XP magnetic beads</td><td>Beckman Coulter</td><td>A63880</td><td></td></tr><tr><td>Agilent Bioanalyzer</td><td>Agilent</td><td>G2939BA</td><td>Referred to in the text as &quot;capillary electrophoresis instrument&quot;; user-dependepent</td></tr><tr><td>Amplitube PCR reaction strips with attached caps, Simport Scientific</td><td>VWR</td><td>89133-910</td><td></td></tr><tr><td>Bacto peptone</td><td>BD Biosciences</td><td>211677</td><td></td></tr><tr><td>Benchling primer design tool</td><td>Benchling</td><td></td><td>https://www.benchling.com/molecular-biology/; Referred to in the text as &quot;the primer design tool&quot;</td></tr><tr><td>Betaine</td><td>Fisher Scientific</td><td>AAJ77507AB</td><td></td></tr><tr><td>Calcofluor white stain</td><td>Sigma-Aldrich</td><td>18909-100ML-F</td><td></td></tr><tr><td>&lt;em&gt;Candida &lt;/em&gt;Genome Database</td><td></td><td></td><td>http://www.candidagenome.org/</td></tr><tr><td>Concanavalin A (ConA) conjugated paramagnetic beads</td><td>Polysciences</td><td>&amp;nbsp;86057-3</td><td></td></tr><tr><td>Conda software</td><td></td><td></td><td>https://docs.conda.io/en/latest/miniconda.html</td></tr><tr><td>curl tool</td><td></td><td></td><td>http://www.candidagenome.org/download/sequence/C_albicans_SC5314/Assembly21/current/C_albicans_SC5314_A21_current_&lt;br/&gt; chromosomes.fasta.gz</td></tr><tr><td>CUTANA ChIC/CUT&amp;amp;RUN kit</td><td>Epicypher</td><td>14-1048</td><td>Referred to in the text as &quot;the CUT&amp;amp;RUN kit&quot;</td></tr><tr><td>Deoxynucleotide (dNTP) solution mix (10 mM)</td><td>New England Biolabs</td><td>N0447S</td><td></td></tr><tr><td>Dextrose (D-glucose)</td><td>Fisher Scientific</td><td>D163</td><td></td></tr><tr><td>Difco D-mannitol</td><td>&amp;nbsp;BD Biosciences</td><td>217020</td><td></td></tr><tr><td>Disposable cuvettes</td><td>Fisher Scientific</td><td>14-955-127</td><td></td></tr><tr><td>Disposable transfer pipets</td><td>Fisher Scientific</td><td>13-711-20</td><td></td></tr><tr><td>DNA Gel Loading Dye (6x)</td><td>Fisher Scientific</td><td>R0611</td><td></td></tr><tr><td>DreamTaq green DNA polymerase</td><td>Fisher Scientific</td><td>EP0713</td><td>Referred to in the text as &quot;cPCR DNA polymerase&quot;</td></tr><tr><td>DreamTaq green DNA polymerase buffer</td><td>Fisher Scientific</td><td>EP0713</td><td>Item part of the DreamTaq green DNA polymerase; referred to in the text as &quot;cPCR DNA polymerase buffer&quot;</td></tr><tr><td>&lt;em&gt;E. coli &lt;/em&gt;spike-in DNA</td><td>Epicypher</td><td>18-1401</td><td></td></tr><tr><td>ELMI Microplate incubator</td><td>ELMI</td><td>TRMS-04</td><td>Referred to in the text as &quot;microplate incubator&quot;</td></tr><tr><td>End Prep Enzyme Mix</td><td></td><td></td><td>Item part of the NEBNext Ultra II DNA Library Prep kit</td></tr><tr><td>End Prep Reaction Buffer</td><td></td><td></td><td>Item part of the NEBNext Ultra II DNA Library Prep kit</td></tr><tr><td>Ethanol 200 proof</td><td>VWR</td><td>89125-170</td><td></td></tr><tr><td>FastDigest MssI</td><td>Fisher Scientific</td><td>FD1344</td><td>Referred to in the text as &quot;restriction enzyme&quot;</td></tr><tr><td>FastDigest MssI Buffer</td><td>Fisher Scientific</td><td>FD1344</td><td>Item part of the FastDigest MssI kit; referred to in the text as &quot;restriction enzyme buffer&quot;</td></tr><tr><td>Ficoll 400</td><td>Fisher BioReagents</td><td>BP525-25</td><td></td></tr><tr><td>Fluorescence microscope</td><td></td><td></td><td>User-dependent</td></tr><tr><td>Gel electrophoresis apparatus</td><td></td><td></td><td>User-dependent</td></tr><tr><td>GeneRuler low range DNA ladder</td><td>Fisher Scientific</td><td>FERSM1192</td><td></td></tr><tr><td>GitBash workflow</td><td></td><td></td><td>https://gitforwindows.org/</td></tr><tr><td>GitHub source code</td><td></td><td></td><td>https://github.com/akshayparopkari/cut_run_analysis</td></tr><tr><td>HEPES-KOH pH 7.5</td><td>Boston BioProducts</td><td>BBH-75-K</td><td></td></tr><tr><td>High-speed centrifuge</td><td></td><td></td><td>User-dependent</td></tr><tr><td>Isopropanol</td><td>Sigma-Aldrich</td><td>PX1830-4</td><td></td></tr><tr><td>Lens paper</td><td>VWR</td><td>52846-001</td><td></td></tr><tr><td>Ligation Enhancer</td><td></td><td></td><td>Item part of the NEBNext Ultra II DNA Library Prep kit</td></tr><tr><td>Lithium acetate dihydrate</td><td>MP Biomedicals</td><td>215525683</td><td></td></tr><tr><td>Living Colors Full-Length GFP polyclonal antibody</td><td>Takara</td><td>632592</td><td>User-dependent</td></tr><tr><td>MACS2</td><td></td><td></td><td>https://pypi.org/project/MACS2/</td></tr><tr><td>Magnetic separation rack, 0.2 mL tubes</td><td>Epicypher</td><td>10-0008</td><td></td></tr><tr><td>Magnetic separation rack, 1.5 mL tubes</td><td>Fisher Scientific</td><td>MR02</td><td></td></tr><tr><td>MgCl&lt;sub&gt;2&lt;/sub&gt;</td><td>Sigma-Aldrich</td><td>M8266</td><td></td></tr><tr><td>Microcentrifuge tubes 1.5 mL</td><td>Fisher Scientific</td><td>05-408-129</td><td></td></tr><tr><td>Microplate and cuvette spectrophotometer</td><td>BioTek</td><td>EPOCH2TC</td><td>Referred to in the text as &quot;spectrophotometer&quot;; user-dependent</td></tr><tr><td>MochiView</td><td></td><td></td><td>http://www.johnsonlab.ucsf.edu/mochiview-downloads</td></tr><tr><td>MOPS</td><td>Sigma-Aldrich</td><td>M3183</td><td></td></tr><tr><td>NaCl</td><td>VWR</td><td>470302-522</td><td></td></tr><tr><td>NaOH</td><td>Fisher Scientific</td><td>S318-500</td><td></td></tr><tr><td>NCBI GEO</td><td></td><td></td><td>https://www.ncbi.nlm.nih.gov/geo/</td></tr><tr><td>NEBNext Adaptor for Illumina</td><td></td><td></td><td>Item part of the NEBNext Multiplex Oligos for Illumina (Index Primers Set 1); referred to in the text as &quot;Adapter&quot;</td></tr><tr><td>NEBNext Index X Primer for Illumina</td><td></td><td></td><td>Item part of the NEBNext Multiplex Oligos for Illumina (Index Primers Set 1); referred to in the text as &quot;Reverse Uniquely Indexed Library Amplification Primer&quot;</td></tr><tr><td>NEBNext Multiplex Oligos for Illumina (Index Primers Set 1)</td><td>New England Biolabs</td><td>E7335S</td><td></td></tr><tr><td>NEBNext Ultra II DNA Library Prep kit</td><td>New England Biolabs</td><td>E7645S</td><td>Referred to in the text as &quot;library prep kit&quot;</td></tr><tr><td>NEBNext Universal PCR Primer for Illumina</td><td></td><td></td><td>Item part of the NEBNext Multiplex Oligos for Illumina (Index Primers Set 1); referred to in the text as &quot;Universal Forward Library Amplification Primer&quot;</td></tr><tr><td>Nourseothricin sulfate (NAT)</td><td>Goldbio</td><td>N-500-2</td><td></td></tr><tr><td>Novex TBE Gels, 10%, 15 well</td><td>Fisher Scientific</td><td>EC62755BOX</td><td></td></tr><tr><td>Nutating mixer</td><td>VWR</td><td>82007-202</td><td></td></tr><tr><td>Nutrient broth</td><td>Criterion</td><td>C6471</td><td></td></tr><tr><td>pADH110</td><td>Addgene</td><td>90982</td><td>Referred to in the text as &quot;plasmid repository ID# 90982&quot;</td></tr><tr><td>pADH119</td><td>Addgene</td><td>90985</td><td>Referred to in the text as &quot;plasmid repository ID# 90985&quot;</td></tr><tr><td>pADH137</td><td>Addgene</td><td>90986</td><td>Referred to in the text as &quot;plasmid repository ID# 90986&quot;</td></tr><tr><td>pADH139</td><td>Addgene</td><td>90987</td><td>Referred to in the text as &quot;plasmid repository ID# 90987&quot;</td></tr><tr><td>pADH140</td><td>Addgene</td><td>90988</td><td>Referred to in the text as &quot;plasmid repository ID# 90988&quot;</td></tr><tr><td>pAG-MNase</td><td>Epicypher</td><td>15-1016 or 15-1116</td><td>50 rxn or 250 rxn</td></tr><tr><td>pCE1</td><td>Addgene</td><td>174434</td><td>Referred to in the text as &quot;plasmid repository ID# 174434&quot;</td></tr><tr><td>Petri dishes with clear lid</td><td>Fisher Scientific</td><td>FB0875712</td><td></td></tr><tr><td>Phusion high fidelity DNA polymerase</td><td>Fisher Scientific</td><td>F530S</td><td>Referred to in the text as &quot;DNA polymerase&quot;</td></tr><tr><td>Polyethylene glycol (PEG) 3350</td><td>VWR</td><td>10791-816</td><td></td></tr><tr><td>Potassium phosphate monobasic</td><td>Fisher Scientific</td><td>P285-500</td><td></td></tr><tr><td>Qubit 1x dsDNA HS assay kit</td><td>Invitrogen</td><td>Q33230</td><td></td></tr><tr><td>Qubit fluorometer</td><td>Life Technologies</td><td>Q33216</td><td>Referred to in the text as &quot;fluorometer&quot;; user-dependent</td></tr><tr><td>Rabbit IgG negative control antibody</td><td>Epicypher</td><td>13-0042</td><td></td></tr><tr><td>RNase A</td><td>Sigma-Aldrich</td><td>10109169001</td><td></td></tr><tr><td>Roche Complete protease inhibitor (EDTA-free) tablets</td><td>Sigma-Aldrich</td><td>5056489001</td><td></td></tr><tr><td>RPMI-1640</td><td>Sigma-Aldrich</td><td>R6504</td><td></td></tr><tr><td>Shaking incubator</td><td>Eppendorf</td><td>M12820004</td><td>User-dependent</td></tr><tr><td>Sorbitol</td><td>Sigma-Aldrich</td><td>S1876-500G</td><td></td></tr><tr><td>Spin-X centrifuge tube filters</td><td>Fisher Scientific</td><td>07-200-385</td><td></td></tr><tr><td>Sterile inoculating loops</td><td>VWR</td><td>30002-094</td><td></td></tr><tr><td>SYBR Gold nucleic acid gel stain</td><td>Fisher Scientific</td><td>S11494</td><td></td></tr><tr><td>SYTO 13 nucleic acid stain</td><td>Fisher Scientific</td><td>S7575</td><td>Referred to in the text as &quot;nucleic acid gel stain&quot;</td></tr><tr><td>Thermocycler</td><td></td><td></td><td>User-dependent</td></tr><tr><td>ThermoMixer C</td><td>Eppendorf</td><td>5382000023</td><td></td></tr><tr><td>Tris (hydroxymethyl) aminomethane</td><td>Sigma-Aldrich</td><td>252859-100G</td><td></td></tr><tr><td>Ultra II Ligation Master Mix</td><td></td><td></td><td>Item part of the NEBNext Ultra II DNA Library Prep kit; referred to in the text as &quot;Ligation Master Mix&quot;</td></tr><tr><td>Ultra II Q5 Master Mix</td><td></td><td></td><td>Item part of the NEBNext Ultra II DNA Library Prep kit; referred to in the text as &quot;High Fidelity DNA Polymerase Master Mix &quot;</td></tr><tr><td>UltraPure salmon sperm DNA solution</td><td>Invitrogen</td><td>15632011</td><td></td></tr><tr><td>USER Enzyme</td><td></td><td></td><td>Item part of the NEBNext Ultra II DNA Library Prep kit; referred to in the text as &quot;Uracil Excision Enzyme&quot;</td></tr><tr><td>Vortex mixer</td><td>VWR</td><td>10153-834</td><td></td></tr><tr><td>wget tool</td><td></td><td></td><td>http://www.candidagenome.org/download/sequence/C_albicans_SC5314/Assembly21/current/C_albicans_SC5314_A21_current_&lt;br/&gt; chromosomes.fasta.gz</td></tr><tr><td>Yeast extract</td><td>Criterion</td><td>C7341</td><td></td></tr><tr><td>Zymolyase 100T (lyticase, yeast lytic enzyme)</td><td>Fisher Scientific</td><td>NC0439194</td><td></td></tr></tbody></table>

genome-wide profiling of transcription factor-dna binding interactions in candida albicans: a comprehensive cut&amp;run method and data analysis workflow

Regulatory transcription factors control many important biological processes, including cellular differentiation, responses to environmental perturbations and stresses, and host-pathogen interactions. Determining the genome-wide binding of regulatory transcription factors to DNA is essential to understanding the function of transcription factors in these often complex biological processes. Cleavage under targets and release using nuclease (CUT&amp;RUN) is a modern method for genome-wide mapping of in vivo protein-DNA binding interactions that is an attractive alternative to the traditional and widely used chromatin immunoprecipitation followed by sequencing (ChIP-seq) method. CUT&amp;RUN is amenable to a higher-throughput experimental setup and has a substantially higher dynamic range with lower per-sample sequencing costs than ChIP-seq. Here, a comprehensive CUT&amp;RUN protocol and accompanying data analysis workflow tailored for genome-wide analysis of transcription factor-DNA binding interactions in the human fungal pathogen Candida albicans are described. This detailed protocol includes all necessary experimental procedures, from epitope tagging of transcription factor-coding genes to library preparation for sequencing; additionally, it includes a customized computational workflow for CUT&amp;RUN data analysis.

This robust CUT&amp;RUN protocol was adapted and optimized for investigating the genome-wide localization of specific TFs in C. albicans biofilms and planktonic cultures (see Figure 2 for an overview of the experimental approach). A thorough data analysis pipeline is also included to facilitate analysis of the resulting CUT&amp;RUN sequencing data and requires users to have minimal expertise in coding or bioinformatics (see Figure 3 for an overview of t...

Watch this Scientific Journal Video about Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow at JoVE.

Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow

This protocol describes an experimental method and data analysis workflow for cleavage under targets and release using nuclease (CUT&amp;RUN) in the human fungal pathogen Candida albicans.

Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&amp;RUN Method and Data Analysis Workflow

Regulatory transcription factors control many important biological processes, including cellular differentiation, responses to environmental perturbations ...

genome-wide-profiling-transcription-factor-dna-binding-interactions

Research

JoVE Journal

Biology

4.1K Views.  University of California, Merced. Dit protocol beschrijft alle experimentele procedures, van epitoop tagging van transcriptiefactorcoderende genen via computationele data-analyse, tot het uitvoeren van genoombrede profilering van transcriptiefactor-DNA-bindingsinteracties in Candida albicans via CUT & RUN. Dit is een meer toegankelijke, snellere, gevoeligere, goedkopere techniek en biedt gegevens van hogere kwaliteit dan traditionele ChIP-chip- en ChIP-seq-benaderingen. Hoewel ons protocol is ontwikkeld voor Candida albicans ...

Video: Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow

Genome-wide Mapping of Protein-DNA Interactions with ChEC-seq in Saccharomyces cerevisiae

Genome-wide mapping of protein-DNA interactions is critical for understanding gene regulation, chromatin remodeling, and other chromatin-resident processes. Formaldehyde crosslinking followed by chromatin immunoprecipitation and high-throughput sequencing (X-ChIP-seq) has been used to gain many valuable insights into genome biology. However, X-ChIP-seq has notable limitations linked to crosslinking and sonication. Native ChIP avoids these drawbacks by omitting crosslinking, but often results in poor recovery of chromatin-bound proteins. In addition, all ChIP-based methods are subject to antibody quality considerations. Enzymatic methods for mapping protein-DNA interactions, which involve fusion of a protein of interest to a DNA-modifying enzyme, have also been used to map protein-DNA interactions. We recently combined one such method, chromatin endogenous cleavage (ChEC), with high-throughput sequencing as ChEC-seq. ChEC-seq relies on fusion of a chromatin-associated protein of interest to micrococcal nuclease (MNase) to generate targeted DNA cleavage in the presence of calcium in living cells. ChEC-seq is not based on immunoprecipitation and so circumvents potential concerns with crosslinking, sonication, chromatin solubilization, and antibody quality while providing high resolution mapping with minimal background signal. We envision that ChEC-seq will be a powerful counterpart to ChIP, providing an independent means by which to both validate ChIP-seq findings and discover new insights into genomic regulation.

Genome-wide Mapping of Protein-DNA Interactions with ChEC-seq in Saccharomyces cerevisiae

We describe chromatin endogenous cleavage coupled with high-throughput sequencing (ChEC-seq), a chromatin immunoprecipitation (ChIP)-orthogonal method for mapping protein binding sites genome-wide with micrococcal nuclease (MNase) fusion proteins.

Genome-wide mapping of protein-DNA interactions is critical for understanding gene regulation, chromatin remodeling, and other chromatin-resident ...

Genetics

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for example, during cellular differentiation, morphogenesis, and functional stimulation (such as activation of immune cells), or after exposure to drugs and other factors from the local environment. Depending on the stimulus and cell type, these changes occur rapidly and at any possible level of gene regulation. Displaying all molecular processes of a responding cell to a certain type of stimulus/drug is one of the hardest tasks in molecular biology. Here, we describe a protocol that enables the simultaneous analysis of multiple layers of gene regulation. We compare, in particular, transcription factor binding (Chromatin-immunoprecipitation-sequencing (ChIP-seq)), de novo transcription (4-thiouridine-sequencing (4sU-seq)), mRNA processing, and turnover as well as translation (ribosome profiling). By combining these methods, it is possible to display a detailed and genome-wide course of action.
Sequencing newly transcribed RNA is especially recommended when analyzing rapidly adapting or changing systems, since this depicts the transcriptional activity of all genes during the time of 4sU exposure (irrespective of whether they are up- or downregulated). The combinatorial use of total RNA-seq and ribosome profiling additionally allows the calculation of RNA turnover and translation rates. Bioinformatic analysis of high-throughput sequencing results allows for many means for analysis and interpretation of the data. The generated data also enables tracking co-transcriptional and alternative splicing, just to mention a few possible outcomes.
The combined approach described here can be applied for different model organisms or cell types, including primary cells. Furthermore, we provide detailed protocols for each method used, including quality controls, and discuss potential problems and pitfalls.

This protocol describes the combinatorial use of ChIP-seq, 4sU-seq, total RNA-seq, and ribosome profiling for cell lines and primary cells. It enables tracking changes in transcription-factor binding, de novo transcription, RNA processing, turnover and translation over time, and displaying the overall course of events in activated and/or rapidly changing cells.

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for ...

A Chromatin Immunoprecipitation Assay to Identify Novel NFAT2 Target Genes in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is characterized by the expansion of malignant B cell clones and represents the most common leukemia in western countries. The majority of CLL patients show an indolent course of the disease as well as an anergic phenotype of their leukemia cells, referring to a B cell receptor unresponsive to external stimulation. We have recently shown that the transcription factor NFAT2 is a crucial regulator of anergy in CLL. A major challenge in the analysis of the role of a transcription factor in different diseases is the identification of its specific target genes. This is of&#160;great significance for the elucidation of pathogenetic mechanisms and potential therapeutic interventions. Chromatin immunoprecipitation (ChIP) is a classic technique to demonstrate protein-DNA interactions and can, therefore, be used to identify direct target genes of transcription factors in mammalian cells. Here, ChIP was used to identify LCK as a direct target gene of NFAT2 in human CLL cells. DNA and associated proteins are crosslinked using formaldehyde and subsequently sheared by sonication into DNA fragments of approximately 200-500 base pairs (bp). Cross-linked DNA fragments associated with NFAT2 are then selectively immunoprecipitated from cell debris using an &#945;NFAT2 antibody. After purification, associated DNA fragments are detected via quantitative real-time PCR (qRT-PCR). DNA sequences with evident enrichment represent regions of the genome which are targeted by NFAT2 in vivo. Appropriate shearing of the DNA and the selection of the required antibody are particularly crucial for the successful application of this method. This protocol is ideal for the demonstration of direct interactions of NFAT2 with target genes. Its major limitation is the difficulty to employ ChIP in large-scale assays analyzing the target genes of multiple transcription factors in intact organisms.

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the western world. NFAT transcription factors are important regulators of development and activation in numerous cell types. Here, we present a protocol for the use of chromatin immunoprecipitation (ChIP) in human CLL cells to identify novel target genes of NFAT2.

Chronic lymphocytic leukemia (CLL) is characterized by the expansion of malignant B cell clones and represents the most common leukemia in western ...

Cancer Research

Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences

Identifying the sets of transcription factors (TFs) that regulate each human gene is a daunting task that requires integrating numerous experimental and computational approaches. One such method is the yeast one-hybrid (Y1H) assay, in which interactions between TFs and DNA regions are tested in the milieu of the yeast nucleus using reporter genes. Y1H assays involve two components: a &#8216;DNA-bait&#8217; (e.g., promoters, enhancers, silencers, etc.) and a &#8216;TF-prey,&#8217; which can be screened for reporter gene activation. Most published protocols for performing Y1H screens are based on transforming TF-prey libraries or arrays into DNA-bait yeast strains. Here, we describe a pipeline, called enhanced Y1H (eY1H) assays, where TF-DNA interactions are interrogated by mating DNA-bait strains with an arrayed collection of TF-prey strains using a high density array (HDA) robotic platform that allows screening in a 1,536 colony format. This allows for a dramatic increase in throughput (60 DNA-bait sequences against &#62;1,000 TFs takes two weeks per researcher) and reproducibility. We illustrate the different types of expected results by testing human promoter sequences against an array of 1,086 human TFs, as well as examples of issues that can arise during screens and how to troubleshoot them.

Here, we present an enhanced yeast one-hybrid screening protocol to identify the transcription factors (TFs) that can bind to a human DNA region of interest. This method uses a high-throughput screening pipeline that can interrogate the binding of &#62;1,000 TFs in a single experiment.

Identifying the sets of transcription factors (TFs) that regulate each human gene is a daunting task that requires integrating numerous experimental and ...

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy

Accurate quantification of transcription factor (TF)-DNA interactions is essential for understanding the regulation of gene expression. Since existing approaches suffer from significant limitations, we have developed a new method for determining TF-DNA binding affinities with high sensitivity on a large scale. The assay relies on the established fluorescence anisotropy (FA) principle but introduces important technical improvements. First, we measure a full FA competitive titration curve in a single well by incorporating TF and a fluorescently labeled reference DNA in a porous agarose gel matrix. Unlabeled DNA oligomer is loaded on the top as a competitor and, through diffusion, forms a spatio-temporal gradient. The resulting FA gradient is then read out using a customized epifluorescence microscope setup. This improved setup greatly increases the sensitivity of FA signal detection, allowing both weak and strong binding to be reliably quantified, even for molecules of similar molecular weights. In this fashion, we can measure one titration curve per well of a multi-well plate, and through a fitting procedure, we can extract both the absolute dissociation constant (KD) and active protein concentration. By testing all single-point mutation variants of a given consensus binding sequence, we can survey the entire binding specificity landscape of a TF, typically on a single plate. The resulting position weight matrices (PWMs) outperform those derived from other methods in predicting in vivo TF occupancy. Here, we present a detailed guide for implementing HiP-FA on a conventional automated fluorescent microscope and the data analysis pipeline.

Here we present a novel method for determining binding affinities at equilibrium and in solution with high sensitivity on a large scale. This improves the quantitative analysis of transcription factor-DNA binding. The method is based on automated fluorescence anisotropy measurements in a controlled delivery system.

Accurate quantification of transcription factor (TF)-DNA interactions is essential for understanding the regulation of gene expression. Since existing ...

Biochemistry

Beginner-Friendly Single-Language Pipeline for CUT&RUN Data Analysis

Introductory Analysis and Validation of CUT&#38;RUN Sequencing Data

The CUT&amp;RUN technique facilitates detection of protein-DNA interactions across the genome. Typical applications of CUT&amp;RUN include profiling changes in histone tail modifications or mapping transcription factor chromatin occupancy. Widespread adoption of CUT&amp;RUN is driven, in part, by technical advantages over conventional ChIP-seq that include lower cell input requirements, lower sequencing depth requirements, and increased sensitivity with reduced background signal due to a lack of cross-linking agents that otherwise mask antibody epitopes. Widespread adoption of CUT&amp;RUN has also been achieved through the generous sharing of reagents by the Henikoff lab and the development of commercial kits to accelerate adoption for beginners. As technical adoption of CUT&amp;RUN increases, CUT&amp;RUN sequencing analysis and validation become critical bottlenecks that must be surmounted to enable complete adoption by predominantly wet lab teams. CUT&amp;RUN analysis typically begins with quality control checks on raw sequencing reads to assess sequencing depth, read quality, and potential biases. Reads are then aligned to a reference genome sequence assembly, and several bioinformatics tools are subsequently employed to annotate genomic regions of protein enrichment, confirm data interpretability, and draw biological conclusions. Although multiple in silico analysis pipelines have been developed to support CUT&amp;RUN data analysis, their complex multi-module structure and usage of multiple programming languages render the platforms difficult for bioinformatics beginners who may lack familiarity with multiple programming languages but wish to understand the CUT&amp;RUN analysis procedure and customize their analysis pipelines. Here, we provide a single-language step-by-step CUT&amp;RUN analysis pipeline protocol designed for users with any level of bioinformatics experience. This protocol includes completing critical quality checks to validate that the sequencing data is suitable for biological interpretation. We expect that following the introductory protocol provided in this article combined with downstream peak annotation will allow users to draw biological insights from their own CUT&amp;RUN datasets.

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

This protocol guides bioinformatics beginners through an introductory CUT&amp;RUN analysis pipeline that enables users to complete an initial analysis and validation of CUT&amp;RUN sequencing data. Completing the analysis steps described here, combined with downstream peak annotation, will allow users to draw mechanistic insights into chromatin regulation.

The CUT&amp;RUN technique facilitates detection of protein-DNA interactions across the genome. Typical applications of CUT&amp;RUN include profiling ...

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform

For most mammalian pathogens, gene expression profiling studies have been limited by technical difficulties to accurately quantify pathogen gene transcripts from infected tissues. Pathogen RNA constitutes a tiny portion of the total RNA isolated from infected tissue samples. Both microarray and RNAseq technologies have difficulties in generating reliable reads for weakly expressed pathogen genes. Mutant pathogen strains with reduced in vivo proliferation pose an even bigger challenge. Here we describe an in vivo gene expression profiling protocol that is very fast, extremely sensitive and highly reproducible. We developed this protocol during our investigation of the fungal pathogen Candida albicans in a murine model of hematogenously disseminated candidiasis. Using this protocol, we have documented time courses of dynamically regulated C. albicans gene expression during kidney infection, and discovered unexpected features of gene expression responses to antifungal drug treatment in vivo.

We developed a protocol that is fast, sensitive and reproducible for pathogen gene expression profiling during an infection.

For most mammalian pathogens, gene expression profiling studies have been limited by technical difficulties to accurately quantify pathogen gene ...

Immunology and Infection

Satellite Cell Isolation from Mouse Limb Muscles and Flow Cytometry Analysis

An Efficient Protocol for CUT&amp;RUN Analysis of FACS-Isolated Mouse Satellite Cells

Genome-wide analyses with small cell populations are a major constraint for studies, particularly in the stem cell field. This work describes an efficient protocol for the fluorescence-activated cell sorting (FACS) isolation of satellite cells from the limb muscle, a tissue with a high content of structural proteins. Dissected limb muscles from adult mice were mechanically disrupted by mincing in medium supplemented with dispase and type I collagenase. Upon digestion,&#160;the homogenate was filtered through cell strainers, and cells were suspended in FACS buffer. Viability was determined with fixable viability stain, and immunostained satellite cells were isolated by FACS. Cells were lysed with Triton X-100 and released nuclei were bound to concanavalin A magnetic beads. Nucleus/bead complexes were incubated with antibodies against the transcription factor or histone modifications of interest. After washes, nucleus/bead complexes were incubated with protein A-micrococcal nuclease, and chromatin cleavage was initiated with CaCl2. After DNA extraction, libraries were generated and sequenced, and the profiles for genome-wide transcription factor binding and covalent histone modifications were obtained by bioinformatic analysis. The peaks obtained for the various histone marks showed that the binding events were specific for satellite cells. Moreover, known motif analysis unveiled that the transcription factor was bound to chromatin via its cognate response element. This protocol is therefore adapted to study gene regulation in adult mice limb muscle satellite cells.

Author Spotlight: Cistrome Analysis in Mouse Muscle Stem Cells 

Presented here is an efficient protocol for the fluorescence-activated cell sorting (FACS) isolation of mouse limb muscle satellite cells adapted to the study of transcription regulation in muscle fibers by cleavage under targets and release using nuclease (CUT&amp;RUN).

Genome-wide analyses with small cell populations are a major constraint for studies, particularly in the stem cell field. This work describes an efficient ...

Developmental Biology

Whole Genome Sequencing of Candida glabrata for Detection of Markers of Antifungal Drug Resistance

Candida glabrata can rapidly acquire mutations that result in drug resistance, especially to azoles and echinocandins. Identification of genetic mutations is essential, as resistance detected in vitro can often be correlated with clinical failure. We examined the feasibility of using whole genome sequencing (WGS) for genome-wide analysis of antifungal drug resistance in C. glabrata. The aim was torecognize enablers and barriers in the implementation WGS and measure its effectiveness. This paper outlines the key quality control checkpoints and essential components of WGS methodology to investigate genetic markers associated with reduced susceptibility to antifungal agents. It also estimates the accuracy of data analysis and turn-around-time of testing.
Phenotypic susceptibility of 12 clinical, and one ATCC strain of C. glabrata was determined through antifungal susceptibility testing. These included three isolate pairs, from three patients, that developed rise in drug minimum inhibitory concentrations. In two pairs, the second isolate of each pair developed resistance to echinocandins. The second isolate of the third pair developed resistance to 5-flucytosine. The remaining comprised of susceptible and azole resistant isolates. Single nucleotide polymorphisms (SNPs) in genes linked to echinocandin, azole and 5-flucytosine resistance were confirmed in resistant isolates through WGS using the next generation sequencing.&#160;Non-synonymous SNPs in antifungal resistance genes such as FKS1, FKS2, CgPDR1, CgCDR1 and FCY2 were identified. Overall, an average of 98% of the WGS reads of C. glabrata isolates mapped to the reference genome with about 75-fold read depth coverage. The turnaround time and cost were comparable to Sanger sequencing.
In conclusion, WGS of C. glabrata was feasible in revealing clinically significant gene mutations involved in resistance to different antifungal drug classes without the need for multiple PCR/DNA sequencing reactions. This represents a positive step towards establishing WGS capability in the clinical laboratory for simultaneous detection of antifungal resistance conferring substitutions.

Whole Genome Sequencing of Candida glabrata for Detection of Markers of Antifungal Drug Resistance

This study implemented whole genome sequencing for analysis of mutations in genes conferring antifungal drug resistance in Candida glabrata. C. glabrata isolates resistant to echinocandins, azoles and 5-flucytosine, were sequenced to illustrate the methodology. Susceptibility profiles of the isolates correlated with presence or absence of specific mutation patterns in genes.

Candida glabrata can rapidly acquire mutations that result in drug resistance, especially to azoles and echinocandins. Identification of genetic mutations ...

Medicine

Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing (ChIP-seq)

ChIP-sequencing (ChIP-seq) methods directly offer whole-genome coverage, where combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing can be utilized to identify the repertoire of mammalian DNA sequences bound by transcription factors in vivo. "Next-generation" genome sequencing technologies provide 1-2 orders of magnitude increase in the amount of sequence that can be cost-effectively generated over older technologies thus allowing for ChIP-seq methods to directly provide whole-genome coverage for effective profiling of mammalian protein-DNA interactions.
For successful ChIP-seq approaches, one must generate high quality ChIP DNA template to obtain the best sequencing outcomes. The description is based around experience with the protein product of the gene most strongly implicated in the pathogenesis of type 2 diabetes, namely the transcription factor transcription factor 7-like 2 (TCF7L2). This factor has also been implicated in various cancers.
Outlined is how to generate high quality ChIP DNA template derived from the colorectal carcinoma cell line, HCT116, in order to build a high-resolution map through sequencing to determine the genes bound by TCF7L2, giving further insight in to its key role in the pathogenesis of complex traits.

Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing ChIP-seq

The combination of chromatin immunoprecipitation and ultra-high-throughput sequencing (ChIP-seq) can identify and map protein-DNA interactions in a given tissue or cell line. Outlined is how to generate a high quality ChIP template for subsequent sequencing, using experience with the transcription factor TCF7L2 as an example.

ChIP-sequencing (ChIP-seq) methods directly  offer whole-genome coverage, where combining chromatin immunoprecipitation  (ChIP) and massively parallel ...

Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow

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