Molecular studies of genome regulation often rely on the ability to map where specific proteins interact with genomic DNA. Existing techniques for mapping protein-DNA interactions genomewide rely on DNA amplification methods followed by sequencing with short reads, which dissociates joint binding information at neighboring sites, removes endogenous DNA methylation information, and precludes the ability to reliably map interactions in repetitive regions of the genome. To address these limitations, we created a new protein-DNA mapping method, called Directed Methylation with Long-read sequencing (DiMeLo-seq), which methylates DNA near each target protein's DNA binding site in situ, then leverages the ability to distinguish methylated and unmethylated bases on long, native DNA molecules using long-read, single-molecule sequencing technologies. We demonstrate the optimization and utility of this method by mapping the interaction sites of a variety of different proteins and histone modifications across the human genome, achieving a single-molecule binding site resolution of less than 200 bp. Furthermore, we mapped the positions of the centromeric histone H3 variant CENP-A in repetitive regions that are unmappable with short reads, while simultaneously analyzing endogenous CpG methylation and joint binding events on single molecules. DiMeLo-seq is a versatile method that can provide multimodal and truly genome-wide information for investigating protein-DNA interactions..

3522 Background: Preliminary data suggests that ctDNA can serve as a marker of minimal residual disease following colorectal cancer (CRC) tumor resection. Applicability of current ctDNA testing is limited by the requirement of sequencing known individual tumor mutations. We explored the applicability of a multi-gene panel ctDNA detection technology in CRC. Methods: Plasma was prospectively collected from CRC patients (pts) undergoing hepatic resections with curative intent between 1/2013 to 9/2016. In a blinded manner 5ml of preoperative (preop) and immediate post-operative (postop) plasma were tested using a novel 30kb ctDNA digital sequencing panel (Guardant Health) covering SNVs in 21 genes and indels in 9 genes based on the landscape of genomic alterations in ctDNA from over 10,000 advanced cancer pts with a high theoretical sensitivity (96%) for CRC. Median unique molecule coverage for this study is 9000 for cfDNA inputs ranging from 10 – 150 ng (media input preop = 27 ng, median input postop = 49 ng) with 120,000X sequencing depth on an IIlumina HiSeq2500. Results: A total of 54 pts underwent liver metastectomies with curative intent with a median follow-up of 33 months. Preop blood was a median of 49 days from last systemic chemotherapy and 3 days prior to surgery; postop blood was a median of 17 days after resection. Tumor mutations from standard of care hotspot multigene panel testing (at MDACC) were identified in 46 of 54 pts (85%). Preop ctDNA mutation detection rate was 80% (43/54) and 44% (24/54) in postop setting, with postop median allele frequency of 0.16% (range 0.01% to 20%). In pts with a minimum of 1 year follow up, sensitivity of postop ctDNA for residual disease was 58% (95%CI; 41%-74%), and specificity was 100% (66%-100%). In 43 patients who underwent successful resection of all visible disease, postop detection of ctDNA significantly correlated with RFS (P = 0.002, HR 3.1; 95% CI 1.7-9.1) with 2-year RFS of 0% vs. 47%. Recurrence was detected in ctDNA a median of 5.1 months prior to radiographic recurrence. Conclusions: The detection of postop ctDNA using an NGS panel-based approach is feasible and is associated with a very high rate of disease recurrence.

Highlights d New microfluidic device images and sorts single cells then performs single-cell DamID d Improved m6 A-Tracer method images protein-DNA interactions with less background d mDamID identifies LADs that vary between single cells and across cell types d Imaging can be used to select cells with greater DamID sequencing signal to noise

Molecular studies of genome regulation often rely on the ability to map where specific proteins interact with genomic DNA. Existing techniques for mapping protein-DNA interactions genome-wide rely on DNA amplification methods followed by sequencing with short reads, which dissociates joint binding information at neighboring sites, removes endogenous DNA methylation information, and precludes the ability to reliably map interactions in repetitive regions of the genome. To address these limitations, we created a new protein-DNA mapping method, called Directed Methylation with Long-read sequencing (DiMeLo-seq), which methylates DNA near each target protein's DNA binding site in situ, then leverages the ability to distinguish methylated and unmethylated bases on long, native DNA molecules using long-read, single-molecule sequencing technologies. We demonstrate the optimization and utility of this method by mapping the interaction sites of a variety of different proteins and histone modifications across the human genome, achieving a single-molecule binding site resolution of less than 200 bp. Furthermore, we mapped the positions of the centromeric histone H3 variant CENP-A in repetitive regions that are unmappable with short reads, while simultaneously analyzing endogenous CpG methylation and joint binding events on single molecules. DiMeLo-seq is a versatile method that can provide multimodal and truly genome-wide information for investigating protein-DNA interactions.

While all-trans retinoic acid (ATRA) is an essential therapy in the treatment of acute promyelocytic leukemia (APL), an aggressive subtype of acute myeloid leukemia, nearly 20% of APL patients are resistant to ATRA. As no biomarkers for ATRA resistance yet exist, we investigated whether cell mechanics could be associated with this pathological phenotype. Using mechano-node-pore sensing, a single-cell mechanical phenotyping platform, and patient-derived APL cell lines, NB4 (ATRA-sensitive) and AP-1060 (ATRA-resistant), we discovered that ATRA-resistant APL cells are less mechanically pliable. By investigating how different subcellular components of APL cells contribute to whole-cell mechanical phenotype, we determined that nuclear mechanics strongly influence APL cell mechanical responses. By arresting APL cells in S-phase or M-phase in the cell cycle, we found cell pliability to be inversely related to DNA content. In addition to DNA content affecting cell pliability, we observed that chromatin condensation also affects nuclear mechanics: decondensing chromatin with trichostatin A is especially effective in softening ATRA-resistant APL cells. RNA-Seq allowed us to compare the transcriptomic differences between ATRA-resistant and ATRA-responsive APL cells and highlighted gene expression changes that could be associated with mechanical changes. Overall, we demonstrate the potential of physical biomarkers in identifying APL resistance.

Summary All-trans retinoic acid (ATRA) is an essential therapy in the treatment of acute promyelocytic leukemia (APL), but nearly 20% of patients with APL are resistant to ATRA. As there are no biomarkers for ATRA resistance that yet exist, we investigated whether cell mechanics could be associated with this pathological phenotype. Using mechano-node-pore sensing, a single-cell mechanical phenotyping platform, and patient-derived APL cell lines, we discovered that ATRA-resistant APL cells are less mechanically pliable. By investigating how different subcellular components of APL cells contribute to whole-cell mechanical phenotype, we determined that nuclear mechanics strongly influence an APL cell’s mechanical response. Moreover, decondensing chromatin with trichostatin A is especially effective in softening ATRA-resistant APL cells. RNA-seq allowed us to compare the transcriptomic differences between ATRA-resistant and ATRA-responsive APL cells and highlighted gene expression changes that could be associated with mechanical changes. Overall, we have demonstrated the potential of “physical” biomarkers in identifying APL resistance.

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1 2 Genome regulation depends on carefully programmed protein-DNA interactions that maintain or 3 alter gene expression states, often by influencing chromatin organization. Most studies of these 4 interactions to date have relied on bulk methods, which in many systems cannot capture the 5 dynamic single-cell nature of these interactions as they modulate cell states. One method allowing 6 for sensitive single-cell mapping of protein-DNA interactions is DNA adenine methyltransferase 7 identification (DamID), which records a protein's DNA-binding history by methylating adenine 8 bases in its vicinity, then selectively amplifies and sequences these methylated regions. These 9interaction sites can also be visualized using fluorescent proteins that bind to methyladenines. Here 10 we combine these imaging and sequencing technologies in an integrated microfluidic platform 11 (µDamID) that enables single-cell isolation, imaging, and sorting, followed by DamID. We apply 12 this system to generate paired single-cell imaging and sequencing data from a human cell line, in 13 which we map and validate interactions between DNA and nuclear lamina proteins, providing a 14 measure of 3D chromatin organization and broad gene regulation patterns. µDamID provides the 15 unique ability to compare paired imaging and sequencing data for each cell and between cells, 16 enabling the joint analysis of the nuclear localization, sequence identity, and variability of protein-17