Multi-omics Techniques for Profiling Chromatin State Transitions in Low-input Primary Mouse Cholangiocytes

Summary

This manuscript presents a comprehensive protocol for low-input ChIP-seq to profile histone modifications and ATAC-seq to assess chromatin accessibility in small amounts of primary mouse cholangiocytes.

Abstract

Polycystic liver disease (PLD) is a hereditary disorder characterized by the formation of fluid-filled cysts derived from cholangiocytes, leading to progressive disease and a significant reduction in patients' quality of life. Current treatments for PLD are inadequate, emphasizing the need for novel therapeutic strategies. The role of epigenetic regulation in PLD progression, particularly chromatin accessibility and histone modifications, remains underexplored. Traditional epigenetic profiling techniques, such as ChIP-seq and DNase-seq, require large numbers of cells, which are difficult to obtain from primary cholangiocytes. To address this, we optimized low-input ChIP-seq and ATAC-seq protocols for low numbers of primary cholangiocytes. These approaches allow for the analysis of histone modifications and chromatin accessibility with minimal cell input. Low-input ChIP-seq utilizes micrococcal nuclease (MNase) for DNA fragmentation, while ATAC-seq employs Tn5 transposase to capture open chromatin regions. These multi-omics techniques provide valuable insights into chromatin state dynamics during cholangiocyte fate transitions in PLD and other biliary diseases. Importantly, the optimized protocols are confidently applicable to other low-input primary cells, enabling the exploration of epigenetic mechanisms across various cellular contexts. This work presents a systematic approach for studying chromatin state alterations, contributing to the development of epigenetic-based therapeutic strategies for PLD and related diseases.

Introduction

PLD is an inherited disorder characterized by the development of multiple fluid-filled cysts derived from cholangiocytes. As these cysts progressively expand, they severely impact patients' quality of life^1,2. Existing treatment strategies for PLD are inadequate, providing only limited benefits while frequently leading to high recurrence rates and complications^3,4. Therefore, there is a pressing need for safer and more effective therapeutic approaches to meet the unresolved clinical challenges in PLD treatment.

Under nor....

Protocol

1. Preparation of solutions and cholangiocytes for ATAC-seq

1. At least 1 day prior to the ATAC-seq experiment, prepare the ATAC Lysis Buffer using the reagents listed in Table 1.
   NOTE: ATAC Lysis Buffer can be stored at 4 °C in the dark for at least 1 month.
2. For freshly isolated primary cholangiocytes¹⁴, count the cells using a hemocytometer immediately after isolation and proceed with the ATAC-seq experiment.
   NOTE: The sooner the better to minimize the impact on cell viability. However, if kept on ice, proceeding within 2 h is generally not a problem.

Results

To generate the chromatin landscape of primary cholangiocytes, we optimized the low-input ChIP-seq and ATAC-seq protocols for low numbers (~100,000) of primary cholangiocytes. Agarose gel electrophoresis results for primary cholangiocytes indicated that for 1 × 10⁵ primary cholangiocytes, 0.02 U MNase at 37 °C for 5 min resulted in the production of mononucleosomes, which was identified as the optimal concentration (Figure 1).

Overview of ATAC-s.......

Discussion

To systematically and comprehensively map the chromatin state dynamics underlying the state transition of cystic cholangiocytes, we successfully optimized low-input ChIP-seq and ATAC-seq for a limited number of primary cholangiocytes. Although this study focused on primary cholangiocytes, we are confident that the protocol can also be applied to other high-viability primary cells with limited availability. Similarly, while this study only presents the ChIP-seq analysis results of H3K9ac and H3K9me3, the protocol is equal.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
0.5 M EDTA	Solarbio	E1170
1 M Tris-HCl (pH=7.5)	Solarbio	T1140
1 M Tris-HCl (pH=8.0)	Solarbio	T1150
3 M NaAc	Beyotime	ST342
8 M LiCl	Sigma	L7026
Agarose gel	Biosharp	BS081
ATAC DNA Library Prep Kit	Vazyme	TD501
CaCl2	Sangon Biotech	A501330	1 M stock
ChIP DNA Library Prep Kit	Vazyme	ND607
DNA Clean beads	Vazyme	N411
DNA Extraction Reagent	Solarbio	P1012
EGTA	Solarbio	E8050	100 mM (pH = 8) stock
Fluorometer	Invitrogen	Q33226
Glycogen	Thermo Scientific	R0561
Hemocytometer	QIUJING	XB.K.25.
Igepal CA-630	Sigma	I8896	10% stock
Magnetic separator	Promega	Z5342
MgCl2	Sangon Biotech	A100288	1.5 M stock
MNase	Sigma	N3755	0.01 U/µL stock
NaCl	Sangon Biotech	A610476	5 M stock
NP40	Solarbio	N8030
Nuclease-free water	Life Technologies	AM9937
PCR instrument	Applied Biosystems	4484073
PCR Purification Kit	QIAGEN	28106
Protease Inhibitor	Roche	04693132001
Protein G beads	Invitrogen	10004D
Proteinase K	TransGen	GE201-01
Rotator	Kylin-Bell	QB-528
SDS	Solarbio	S8010	10%  stock
Sodium deoxycholate	Sigma	S1827
Thermomixer comfort	Eppendorf	5355
Triton X-100	Solarbio	T8200
Tween-20	Solarbio	T8220
Software	Citation (PMID)/Company	Version	Website
Bowtie2	22388286	2.3.5.1	https://github.com/BenLangmead/bowtie2
Deeptools	27079975	3.4.3	https://deeptools.readthedocs.io/en/latest/
FastQC		0.12.1	https://www.bioinformatics.babraham.ac.uk/projects/fastqc/
IGV	21221095	2.12.3	https://igv.org/
MACS2	18798982	2.2.7.1	https://hbctraining.github.io/Intro-to-ChIPseq/lessons/05_peak_calling_macs.html
Miniconda	Anaconda	4.7.12.1	https://www.anaconda.com/
MultiQC	27312411	1.23	https://seqera.io/multiqc/
Picard		2.27.5	https://broadinstitute.github.io/picard/
samtools	33590861	1.6	https://www.htslib.org/
trim-galore		0.6.6	https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/