A tale of two measurements: protein-DNA interactions and gene expression in single cells. Protein-DNA interactions and gene expression in single cells

Our bodies are composed of trillions of cells which are the building blocks that cooperate with each other. A neuron has a characteristic tree-like appearance and is specialized in transmitting electrical pulses to signal. Fat cells on the other hand, are round and their primary function is fat storage. These two cell types, as well as the rest of the 200 different cell types in the human body, contain the same genetic information, yet are functionally and morphologically different. How does the same DNA code result in different outcomes? It is all about exposure. Not all DNA code is available for the cell to read and act upon at all times. Some parts of the DNA can be tightly folded, while others are more lose and are therefore easier for the cell to read. When the cell “reads” the genetic code, it copies this region, creating so-called messenger RNA (or mRNA) transcripts which are used as blueprints to produce proteins. A neuron needs different proteins than an adipocyte, which means that the accessible DNA parts and the resulting mRNA transcripts are different between the two cell types. Therefore, by measuring the mRNA transcripts of a cell, a PhD student can understand what cell type she is looking at. The DNA is stored in a spherical compartment at the center of the cell called the nucleus. Near the center of the nucleus, the DNA is more flexible and open, while at its periphery, the DNA is more densely packed. Whether the DNA is open or packed is important for cell function and morphology. Firstly, because the regions that are located at the periphery and the ones residing at the nuclear interior can differ between cell types. Secondly, because the DNA code that is needed by the cell is often located in the center of the nucleus where it is “read”. In contrast, code that is not useful for the cell’s tasks is “stored” at the periphery of the nucleus, and mostly goes unused. This thesis focuses on relating DNA folding and mRNA production. In general, DNA at the periphery of the nucleus is not read by the cell and produces almost no mRNA. However, until now, this was not confirmed because of the lack of molecular tools. To link the DNA folding with the mRNA production, one has to measure both things in the same cell. We developed the method scDam&T-seq that measures both DNA folding and mRNA in the same cell. We confirmed that most DNA regions are not read by the cell when they are at the periphery of the nucleus. We also found that some regions are more prone to be “shut off” at the nuclear periphery than other regions. We also applied scDam&T-seq to the brain of developing mice. We found that the cells which produce the neurons in the brain show differences in DNA folding even though their mRNA seems similar. In conclusion, this thesis presents mainly technical solutions to the field of DNA architecture

A tale of two measurements: protein-DNA interactions and gene expression in single cells. Protein-DNA interactions and gene expression in single cells

Our bodies are composed of trillions of cells which are the building blocks that cooperate with each other. A neuron has a characteristic tree-like appearance and is specialized in transmitting electrical pulses to signal. Fat cells on the other hand, are round and their primary function is fat storage. These two cell types, as well as the rest of the 200 different cell types in the human body, contain the same genetic information, yet are functionally and morphologically different. How does the same DNA code result in different outcomes? It is all about exposure. Not all DNA code is available for the cell to read and act upon at all times. Some parts of the DNA can be tightly folded, while others are more lose and are therefore easier for the cell to read. When the cell “reads” the genetic code, it copies this region, creating so-called messenger RNA (or mRNA) transcripts which are used as blueprints to produce proteins. A neuron needs different proteins than an adipocyte, which means that the accessible DNA parts and the resulting mRNA transcripts are different between the two cell types. Therefore, by measuring the mRNA transcripts of a cell, a PhD student can understand what cell type she is looking at. The DNA is stored in a spherical compartment at the center of the cell called the nucleus. Near the center of the nucleus, the DNA is more flexible and open, while at its periphery, the DNA is more densely packed. Whether the DNA is open or packed is important for cell function and morphology. Firstly, because the regions that are located at the periphery and the ones residing at the nuclear interior can differ between cell types. Secondly, because the DNA code that is needed by the cell is often located in the center of the nucleus where it is “read”. In contrast, code that is not useful for the cell’s tasks is “stored” at the periphery of the nucleus, and mostly goes unused. This thesis focuses on relating DNA folding and mRNA production. In general, DNA at the periphery of the nucleus is not read by the cell and produces almost no mRNA. However, until now, this was not confirmed because of the lack of molecular tools. To link the DNA folding with the mRNA production, one has to measure both things in the same cell. We developed the method scDam&T-seq that measures both DNA folding and mRNA in the same cell. We confirmed that most DNA regions are not read by the cell when they are at the periphery of the nucleus. We also found that some regions are more prone to be “shut off” at the nuclear periphery than other regions. We also applied scDam&T-seq to the brain of developing mice. We found that the cells which produce the neurons in the brain show differences in DNA folding even though their mRNA seems similar. In conclusion, this thesis presents mainly technical solutions to the field of DNA architecture

Simultaneous quantification of protein-DNA contacts and transcriptomes in single cells.

Protein-DNA interactions are critical to the regulation of gene expression, but it remains challenging to define how cell-to-cell heterogeneity in protein-DNA binding influences gene expression variability. Here we report a method for the simultaneous quantification of protein-DNA contacts by combining single-cell DNA adenine methyltransferase identification (DamID) with messenger RNA sequencing of the same cell (scDam&T-seq). We apply scDam&T-seq to reveal how genome-lamina contacts or chromatin accessibility correlate with gene expression in individual cells. Furthermore, we provide single-cell genome-wide interaction data on a polycomb-group protein, RING1B, and the associated transcriptome. Our results show that scDam&T-seq is sensitive enough to distinguish mouse embryonic stem cells cultured under different conditions and their different chromatin landscapes. Our method will enable the analysis of protein-mediated mechanisms that regulate cell-type-specific transcriptional programs in heterogeneous tissues

Simultaneous quantification of protein-DNA interactions and transcriptomes in single cells with scDam&T-seq.

Protein-DNA interactions are essential for establishing cell type-specific chromatin architecture and gene expression. We recently developed scDam&T-seq, a multi-omics method that can simultaneously quantify protein-DNA interactions and the transcriptome in single cells. The method effectively combines two existing methods: DNA adenine methyltransferase identification (DamID) and CEL-Seq2. DamID works through the tethering of a protein of interest (POI) to the Escherichia coli DNA adenine methyltransferase (Dam). Upon expression of this fusion protein, DNA in proximity to the POI is methylated by Dam and can be selectively digested and amplified. CEL-Seq2, in contrast, makes use of poly-dT primers to reverse transcribe mRNA, followed by linear amplification through in vitro transcription. scDam&T-seq is the first technique capable of providing a combined readout of protein-DNA contact and transcription from single-cell samples. Once suitable cell lines have been established, the protocol can be completed in 5 d, with a throughput of hundreds to thousands of cells. The processing of raw sequencing data takes an additional 1-2 d. Our method can be used to understand the transcriptional changes a cell undergoes upon the DNA binding of a POI. It can be performed in any laboratory with access to FACS, robotic and high-throughput-sequencing facilities