DMS-Seq for In Vivo Genome-wide Mapping of Protein-DNA Interactions and Nucleosome Centers

Abstract

Protein-DNA interactions provide the basis for chromatin structure and gene regulation. Comprehensive identification of protein-occupied sites is thus vital to an in-depth understanding of genome function. Dimethyl sulfate (DMS) is a chemical probe that has long been used to detect footprints of DNA-bound proteins in vitro and in vivo. Here, we describe a genomic footprinting method, dimethyl sulfate sequencing (DMS-seq), which exploits the cell-permeable nature of DMS to obviate the need for nuclear isolation. This feature makes DMS-seq simple in practice and removes the potential risk of protein re-localization during nuclear isolation. DMS-seq successfully detects transcription factors bound to cis-regulatory elements and non-canonical chromatin particles in nucleosome-free regions. Furthermore, an unexpected preference of DMS confers on DMS-seq a unique potential to directly detect nucleosome centers without using genetic manipulation. We expect that DMS-seq will serve as a characteristic method for genome-wide interrogation of in vivo protein-DNA interactions.

Technique Development for Probing RNA Structure In Vivo and Genome-Wide

“…Figure 2 shows this chemistry and also denotes whether the reactions directly result in a stop during reverse transcription or whether additional reactions are needed to read out the base-pairing status of the nucleotide. Probes have been identified that react with the Watson-Crick, Hoogsteen, and sugar faces of the base, the ribose sugar, and the phosphate, as reviewed in Ehresmann et al (1987) with recent advances presented in , Spitale et al (2013), Umeyama and Ito (2017), Feng et al (2018), and Mitchell et al (2018). Dimethyl sulfate (DMS) reacts with A(N1) and C(N3) on the Watson-Crick face, as well as G(N7) and A(N3) in the major and minor grooves, respectively, where it has also been used to probe dsDNA (Lawley and Brookes 1963;Umeyama and Ito 2017).…”

“…Probes have been identified that react with the Watson-Crick, Hoogsteen, and sugar faces of the base, the ribose sugar, and the phosphate, as reviewed in Ehresmann et al (1987) with recent advances presented in , Spitale et al (2013), Umeyama and Ito (2017), Feng et al (2018), and Mitchell et al (2018). Dimethyl sulfate (DMS) reacts with A(N1) and C(N3) on the Watson-Crick face, as well as G(N7) and A(N3) in the major and minor grooves, respectively, where it has also been used to probe dsDNA (Lawley and Brookes 1963;Umeyama and Ito 2017). Kethoxal is used to probe the Watson-Crick face of G, whereas selective 2 ′ -hydroxyl (2 ′ -OH) acylation analyzed by primer extension (SHAPE) reacts with the 2 ′ -OH ) and light-activated structural examination of RNA (LASER) modifies the C8 position of purines (G>A) (Feng et al 2018).…”

“…Advances in protein protection have been reported in correlating SHAPE reactivities with RNA-protein 3D structures (Spitale et al 2015) and in using uncertainties in SHAPE reactivity between states (Smola et al 2015a). In addition, LASER probes the nonhydrogen bonding C8 position of purines and so is inherently sensitive to protein protection at this position (Feng et al 2018), as is reactivity at other non-Watson-Crick positions (Umeyama and Ito 2017). Ultimately, a combination of these approaches, along with description of RNA-binding motifs (Ray et al 2013) and selective deployment of cross-linking (Lu et al 2016) may help with the assignment of protections.…”

DMS‐seq for In Vivo Genome‐Wide Mapping of Protein‐DNA Interactions and Nucleosome Centers

“…This simple consideration led us to develop DMS-seq. DMSseq can detect in vivo binding sites for various trans-acting factors, notably without isolating nuclei (Umeyama & Ito, 2017).…”

Understanding metabolic adaptation by using bacterial laboratory evolution and trans-omics analysis

“…Then, using omics technologies, we can obtain genome-wide information about the adaptive phenotypic and genotypic changes resulting from the selective pressure. Advances in omics technologies (Bentley et al 2008;Nagalakshmi et al 2008;Bennett et al 2009;Bamba et al 2012;Matsumoto et al 2017;Umeyama and Ito 2017;Miura et al 2019) have made ALE a powerful approach for analyzing evolutionary biology as well as for breeding useful microorganisms (Conrad et al 2011;Jiang et al 2012;Tokuyama et al 2018), and understanding stress-tolerant mechanisms (Dragosits and Mattanovich 2013;Winkler and Kao 2014;Horinouchi et al 2017a), or analyzing antibiotic-resistant evolution (Lenski 1998;Lazar et al 2014;Gillings et al 2017;Levin-Reisman et al 2017;Zampieri et al 2017;Furusawa et al 2018). For example, ALE of microorganisms for higher temperature (Bennett et al 1990;Leroi et al 1994;Bennett and Lenski 2007;Kishimoto et al 2010;Ying et al 2015), various stressors (Atsumi et al 2010;Reyes et al 2013;Harden et al 2015;Matsusako et al 2017), and alternativesubstrates (Lee and Palsson 2010) was performed previously.…”