Abstract
Identifying genomic regions bound by individual proteins such as transcription factors is essential to understanding bacterial gene regulation; however, comprehensive understanding of the effect of protein occupancy on gene regulation would be prohibitively laborious and expensive to achieve using methods such as chromatin immunoprecipitation with sequencing (ChIP-seq) and ChIP with exonuclease treatment (ChIP-exo) for every protein and condition of interest. Here we describe a protocol for performing in vivo protein occupancy display–high resolution (IPOD-HR), a powerful method for genome-wide profiling of protein-bound DNA in prokaryotic systems. Although assay for transposase-accessible chromatin with sequencing (ATAC-seq) is the method of choice for assaying general protein occupancy in eukaryotic systems, bacterial nucleoid-associated proteins can affect ATAC-seq, rendering it unsuitable for use in bacteria. In contrast, IPOD-HR can be used to identify regions of bacterial genomes that are highly bound by proteins, regardless of the identity of the proteins bound, allowing the identification of condition- and genotype-dependent changes in protein occupancy associated with changes in gene regulation. The technique is coupled to RNA polymerase ChIP, followed by sequencing of the extracted samples and downstream analysis using open-source, automated software that we provide and actively maintain. Once cross-linked samples are obtained, the core DNA selection portion of the IPOD-HR protocol takes 3 calendar days to perform. The resulting DNA extracts are subjected to high-throughput sequencing, resulting in sequencing data that are analyzed, which typically requires a few additional days, depending on the number of samples and computing resources. The IPOD-HR experimental method requires familiarity with standard molecular biology techniques suitable for preparing Illumina sequencing inputs, and the computational post-processing pipeline requires basic knowledge of the Linux command line environment.
Key points
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IPOD-HR enables high-resolution, genome-wide profiling of protein–DNA interactions in bacteria under physiological conditions, overcoming limitations of ATAC-seq caused by bacterial nucleoid-associated proteins.
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The protocol provides detailed wet-lab and computational steps, including integration with RNA polymerase ChIP-seq and automated open-source software for downstream analysis, to assess condition- and genotype-dependent changes in protein occupancy.
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Code availability
Exhaustive and up-to-date documentation for the open-source software that we provide and actively maintain can be found at the github repository for the IPOD pipeline (https://github.com/freddolino-lab/ipod). To simplify the process of establishing a compatible environment, we provide a conda environment definition in the conda_environment.yml file available in the IPOD github repository. Information about Apptainer is available at https://apptainer.org/docs/user/main/quick_start.html. A permanent mirror of the version used for this paper is provided at https://zenodo.org/records/17336331.
References
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).
Badel, C., Samson, R. Y. & Bell, S. D. Chromosome organization affects genome evolution in Sulfolobus archaea. Nat. Microbiol. 7, 820–830 (2022).
Marinov, G. K. et al. The chromatin landscape of the euryarchaeon Haloferax volcanii. Genome Biol. 24, 253 (2023).
Whitfield, C. R., Wardle, S. J. & Haniford, D. B. The global bacterial regulator H-NS promotes transpososome formation and transposition in the Tn5 system. Nucleic Acids Res. 37, 309–321 (2009).
Kelly, T. K. et al. Genome-wide mapping of nucleosome positioning and DNA methylation within individual DNA molecules. Genome Res. 22, 2497–2506 (2012).
Tavazoie, S. & Church, G. M. Quantitative whole-genome analysis of DNA-protein interactions by in vivo methylase protection in E. coli. Nat. Biotechnol. 16, 566–571 (1998).
Vora, T., Hottes, A. K. & Tavazoie, S. Protein occupancy landscape of a bacterial genome. Mol. Cell 35, 247–253 (2009).
Freddolino, L., Amemiya, H. M., Goss, T. J. & Tavazoie, S. Dynamic landscape of protein occupancy across the Escherichia coli chromosome. PLoS Biol. 19, e3001306 (2021).
Amemiya, H. M., Schroeder, J. & Freddolino, L. Nucleoid-associated proteins shape chromatin structure and transcriptional regulation across the bacterial kingdom. Transcription 12, 182–218 (2021).
Ren, B. et al. Genome-wide location and function of DNA binding proteins. Science 290, 2306–2309 (2000).
Park, P. J. ChIP-seq: advantages and challenges of a maturing technology. Nat. Rev. Genet. 10, 669–680 (2009).
Serandour, A. A., Brown, G. D., Cohen, J. D. & Carroll, J. S. Development of an Illumina-based ChIP-exonuclease method provides insight into FoxA1-DNA binding properties. Genome Biol. 14, R147 (2013).
Giresi, P. G., Kim, J., McDaniell, R. M., Iyer, V. R. & Lieb, J. D. FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements) isolates active regulatory elements from human chromatin. Genome Res. 17, 877–885 (2007).
Amemiya, H. M. et al. Distinct heterochromatin‐like domains promote transcriptional memory and silence parasitic genetic elements in bacteria. EMBO J. 41, e108708 (2022).
Rakibova, Y., Dunham, D. T., Seed, K. D. & Freddolino, L. Nucleoid-associated proteins shape the global protein occupancy and transcriptional landscape of a clinical isolate of Vibrio cholerae. mSphere 9, e0001124 (2024).
Zeinert, R. D. et al. A legacy role for DNA binding of Lon protects against genotoxic stress. Preprint at bioRxiv https://doi.org/10.1101/317677 (2018).
Ekdahl, A. M. et al. Conserved heterochromatin-like structures with local regulators mediate the iron stress response in mycobacteria. Preprint at bioRxiv https://doi.org/10.1101/2025.08.23.671944 (2025).
Palomar, V. M. et al. Membrane association of active genes organizes the chloroplast nucleoid structure. Proc. Natl Acad. Sci. USA 121, e2309244121 (2024).
Mihailovic, M. K. et al. Uncovering transcriptional regulators and targets of sRNAs using an integrative data-mining approach: H-NS-regulated RseX as a case study. Front. Cell. Infect. Microbiol. 11, 696533 (2021).
Ekdahl, A. M. et al. Multiscale regulation of nutrient stress responses in Escherichia coli from chromatin structure to small regulatory RNAs. Nucleic Acids Res. 53, gkaf647 (2025).
Trouillon, J., Doubleday, P. F. & Sauer, U. Genomic footprinting uncovers global transcription factor responses to amino acids in Escherichia coli. Cell Syst. 14, 860–871.e4 (2023).
Boyle, A. P. et al. High-resolution mapping and characterization of open chromatin across the genome. Cell 132, 311–322 (2008).
Schones, D. E. et al. Dynamic regulation of nucleosome positioning in the human genome. Cell 132, 887–898 (2008).
Gross, D. S. & Garrard, W. T. Nuclease hypersensitive sites in chromatin. Annu. Rev. Biochem. 57, 159–197 (1988).
Rychel, K. et al. iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning. Nucleic Acids Res. 49, D112–D120 (2021).
Lempp, M. et al. Systematic identification of metabolites controlling gene expression in E. coli. Nat. Commun. 10, 4463 (2019).
Hommais, F. et al. Large-scale monitoring of pleiotropic regulation of gene expression by the prokaryotic nucleoid-associated protein, H-NS. Mol. Microbiol. 40, 20–36 (2001).
Orans, J., Kovach, A. R., Hoff, K. E., Horstmann, N. M. & Brennan, R. G. Crystal structure of an Escherichia coli Hfq Core (residues 2–69)–DNA complex reveals multifunctional nucleic acid binding sites. Nucleic Acids Res. 48, 3987–3997 (2020).
Solomon, M. J. & Varshavsky, A. Formaldehyde-mediated DNA-protein crosslinking: a probe for in vivo chromatin structures. Proc. Natl Acad. Sci. USA 82, 6470–6474 (1985).
Bergendahl, V., Thompson, N. E., Foley, K. M., Olson, B. M. & Burgess, R. R. A cross-reactive polyol-responsive monoclonal antibody useful for isolation of core RNA polymerase from many bacterial species. Protein Expr. Purif. 31, 155–160 (2003).
Lacazette, E. A laboratory practical illustrating the use of the ChIP-qPCR method in a robust model: estrogen receptor alpha immunoprecipitation using Mcf-7 culture cells. Biochem. Mol. Biol. Educ. 45, 152–160 (2017).
Patel, L. A., Cao, Y., Mendenhall, E. M., Benner, C. & Goren, A. The wild west of spike-in normalization. Nat. Biotechnol. 42, 1343–1349 (2024).
Carroll, T. S., Liang, Z., Salama, R., Stark, R. & de Santiago, I. Impact of artifact removal on ChIP quality metrics in ChIP-seq and ChIP-exo data. Front. Genet. 5, 75 (2014).
Babraham Institute. Fast QC. Babraham Bioinformatics https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2026).
Rashid, F.-Z. M. & Dame, R. T. 2024: A ‘nucleoid space’ odyssey featuring H-NS. Bioessays 46, e2400098 (2024).
Acknowledgements
Work in the L.F. lab was supported by US National Institutes of Health R35 GM128637, and work in the US lab was supported by the ETH Postdoctoral Fellowship program (to J.T.). The authors are grateful to other members of the Sauer and Freddolino labs for helpful writing and figure suggestions.
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All authors contributed jointly to the writing, editing, figure generation and review. Contributions on experimental procedures were mainly from R.L.H.; contributions on the computational pipeline and data analysis were from J.W.S.; and contributions on data interpretation and application were mainly from R.L.H. and J.T. U.S. and L.F. performed substantial editing and revision of the manuscript and are responsible for the contributions from their respective labs.
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Nature Protocols thanks Fabian Blombach; Rob Phillips, who co-reviewed with Tom Roeschinger, Kian Faizi and Rosalind Pan; and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Key references
Freddolino, L. et al. PLoS Biol. 19, e3001306 (2021): https://doi.org/10.1371/journal.pbio.3001306
Trouillon, J. et al. Cell Syst. 14, 860–871.e4 (2023): https://doi.org/10.1016/j.cels.2023.09.003
Amemiya, H. et al. EMBO J. 41, e108708 (2022): https://doi.org/10.15252/embj.2021108708
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Hurto, R.L., Schroeder, J.W., Trouillon, J. et al. Profiling large-scale protein occupancy on bacterial genomes using IPOD-HR. Nat Protoc (2026). https://doi.org/10.1038/s41596-026-01357-7
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DOI: https://doi.org/10.1038/s41596-026-01357-7
