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Heom, K. A.

Publications and source records attributed to Heom, K. A..

5 recordsLinked to original sources

Photolabile oligonucleotides combined with topologically imposed light gradients enable spatially resolved single-cell transcriptomics and epigenomics

The organization of cells within a tissue plays a critical role in tuning cellular function. Several methods have recently been developed to capture the transcriptome of cells while retaining spatial information. However, these genome-wide sequencing methods typically lack the spatial resolution of individual cells and are confined to quantifying positional information within predefined lattice locations, thereby failing to capture large sections of a tissue outside these regions. Further, these methods are generally limited to profiling fixed cells with reduced mRNA capture efficiency compared to standard scRNA-seq. In addition, existing methods lack modularity and cross-platform compatibility, thereby limiting most of these techniques from jointly profiling the epigenetic and transcriptomic state of individual cells. To overcome these limitations, we present scSTAMP-seq (single-cell Spatial Transcriptomic And Multiomic Profiling), an approach that employs cholesterol-tagged photolabile oligonucleotides that incorporate into cell membranes, enabling us to "stamp" the position of cells using spatially imposed light gradients prior to tissue dissociation and single-cell sequencing. Applied to live cells, scSTAMP-seq efficiently captures spatially resolved single-cell transcriptomes at high resolution for all cells within a field of view. Further, we demonstrate that light patterning enables dynamic spatial resolution, including the ability to map the position of individual cells. Finally, we show that scSTAMP-seq is modular and can be seamlessly integrated with various downstream single-cell sequencing technologies. We demonstrate this by performing scRNA-seq using plate- and droplet-based methods, and by performing joint epigenome and transcriptome sequencing from the same cell while preserving positional information. Collectively, these results demonstrate that scSTAMP-seq is a sensitive and high-throughput technology for mapping single-cell transcriptomes and epigenomes at the spatial resolution of individual cells.

genomics↗

Joint profiling of 5mC, 5hmC, and the transcriptome in single cells identifies factors responsible for genome-wide DNA methylation erasure in human primordial germ cell maturation

Reprogramming of DNA methylation plays a vital role in the establishment of cell identity during early mammalian development. To gain deeper mechanistic insights into this process requires capturing the entire dynamics of DNA methylation - both 5-methylcytosine (5mC) and its downstream oxidation product 5-hydroxymethylcytosine (5hmC) - in individual cells. Therefore, in this work, we report a new single-cell genome-wide strand-specific sequencing method, scMHT-seq, to jointly profile 5mC, 5hmC, and the transcriptome from individual cells. Using human embryonic stem cells (hESCs), we first show that scMHT-seq can accurately detect both 5mC and 5hmC from the same cell with minimal crosstalk in quantifying these two DNA modifications, and that the multi-modal measurements are in close agreement with individual measurements of 5mC and 5hmC in single cells. After establishing the method, we next applied scMHT-seq to gain insights into human primordial germ cell (hPGC) development. After specification, hPGCs undergo rapid global demethylation as they mature, and this reprogramming is critical for normal development of gametes. However, it has not been possible to fully overcome this key epigenetic barrier in culture, thereby limiting our ability to generate mature hPGC-like cells (hPGCLCs) and accomplish in vitro gametogenesis. To gain deeper understanding of the molecular factors involved in germ cell maturation, we applied scMHT-seq to an extended in vitro culture system for generating hPGCLCs and observed partial and heterogeneous erasure of the methylome across single cells that is mechanistically predominantly driven by passive demethylation due to reduced DNMT1-mediated maintenance methylation activity. Notably, we discover that hPGCLCs in extended culture can be transcriptionally classified into two distinct states, with one population enriched with more mature hPGCLCs exhibiting genome-wide loss of DNA methylation. Moreover, analysis of these two cell states identifies DND1 and SOX15 as two factors that are potentially key drivers of hPGCLC demethylation and maturation. Overall, we demonstrate that scMHT-seq is a robust and high-throughput technology that can provide insights into the mechanisms driving DNA methylation dynamics and their effect on cell states.

genomics↗

Sp1 mechanotransduction regulates breast cancer cell invasion in response to multiple tumor-mimicking extracellular matrix cues

Breast cancer progression is marked by extracellular matrix (ECM) remodeling, including increased stiffness, faster stress relaxation, and elevated collagen levels. In vitro experiments have revealed a role for each of these factors to individually promote malignant behavior, but their combined effects remain unclear. To address this, we developed alginate-collagen hydrogels with independently tunable stiffness, stress relaxation, and collagen density. We show that these combined tumor-mimicking ECM cues reinforced invasive morphologies and promoted spheroid invasion in breast cancer and mammary epithelial cells. High stiffness and low collagen density in slow-relaxing matrices led to the greatest cell migration speed and displacement. RNA-seq revealed Sp1 target gene enrichment in response to both individual and combined ECM cues, with a greater enrichment observed under multiple cues. Notably, high expression of Sp1 target genes upregulated by fast stress relaxation correlated with poor patient survival. Mechanistically, we found that phosphorylated-Sp1 (T453) was increasingly located in the nucleus in stiff and/or fast relaxing matrices, which was regulated by PI3K and ERK1/2 signaling, as well as actomyosin contractility. This study emphasizes how multiple ECM cues in complex microenvironments reinforce malignant traits and supports an emerging role for Sp1 as a mechanoresponsive transcription factor.

bioengineering↗

Targeted rRNA depletion enables efficient mRNA sequencing in diverse bacterial species and complex co-cultures

Bacterial mRNA sequencing is inefficient due to the abundance of ribosomal RNA that is challenging to deplete. While commercial kits target rRNA from common bacterial species, they are frequently inefficient when applied to divergent species, including those from environmental isolates. Similarly, other methods typically employ large probe sets that tile the entire length of rRNAs; however, such approaches are infeasible when applied to many species. Therefore, we present EMBR-seq+, which requires fewer than ten oligonucleotides per rRNA by combining rRNA blocking primers with RNase H-mediated depletion to achieve rRNA removal efficiencies of up to 99% in diverse bacterial species. Further, in more complex microbial co-cultures between F. succinogenes strain UWB7 and anerobic fungi, EMBR-seq+ depleted both bacterial and fungal rRNA, with a 4-fold improvement in bacterial rRNA depletion compared to a commercial kit, thereby demonstrating that the method can be applied to non-model microbial mixtures. Notably, for microbes with unknown rRNA sequences, EMBR-seq+ enables rapid iterations in probe design without requiring to start experiments from total RNA. Finally, efficient depletion of rRNA enabled systematic quantification of the reprogramming of the bacterial transcriptome when cultured in the presence of the anerobic fungi Anaeromyces robustus or Caecomyces churrovis. We observed that F. succinogenes strain UWB7 downregulated several lignocellulose-degrading carbohydrate-active enzymes in the presence of anerobic gut fungi, suggesting close interactions between two cellulolytic species that specialize in different aspects of biomass breakdown. Thus, EMBR-seq+ enables efficient, cost-effective and rapid quantification of the transcriptome to gain insights into non-model microbial systems.

genomics↗

Efficient and cost-effective bacterial mRNA sequencing from low input samples through ribosomal RNA depletion

RNA sequencing is a powerful approach to quantify the genome-wide distribution of mRNA molecules in a population to gain deeper understanding of cellular functions and phenotypes. However, unlike eukaryotic cells, mRNA sequencing of bacterial samples is more challenging due to the absence of a poly-A tail that typically enables efficient capture and enrichment of mRNA from the abundant rRNA molecules in a cell. Moreover, bacterial cells frequently contain 100-fold lower quantities of RNA compared to mammalian cells, which further complicates mRNA sequencing from non-cultivable and non-model bacterial species. To overcome these limitations, we report EMBR-seq (Enrichment of mRNA by Blocked rRNA), a method that efficiently depletes 5S, 16S and 23S rRNA using blocking primers to prevent their amplification, resulting in greater than 80% of the sequenced RNA molecules from an E. coli culture deriving from mRNA. We demonstrate that this increased efficiency provides a deeper view of the transcriptome without introducing technical amplification-induced biases. Moreover, compared to recent methods that employ a large array of oligonucleotides to deplete rRNA, EMBR-seq uses a single oligonucleotide per rRNA, thereby making this new technology significantly more cost-effective, especially when applied to varied bacterial species. Finally, compared to existing commercial kits for bacterial rRNA depletion, we show that EMBR-seq can be used to successfully quantify the transcriptome from more than 500-fold lower starting total RNA. Thus, EMBR-seq provides an efficient and cost-effective approach to quantify global gene expression profiles from low input bacterial samples.

genomics↗