Chromatin Proteomics to Study Epigenetics - Challenges and Opportunities

Regulation of gene expression is essential for the functioning of all eukaryotic organisms. Understanding gene expression regulation requires determining which proteins interact with regulatory elements in chromatin. MS-based analysis of chromatin has emerged as a powerful tool to identify proteins associated with gene regulation, as it allows studying protein function and protein complex formation in their in vivo chromatin-bound context. Total chromatin isolated from cells can be directly analyzed using MS or further fractionated into transcriptionally active and inactive chromatin prior to MS-based analysis. Newly formed chromatin that is assembled during DNA replication can also be specifically isolated and analyzed. Furthermore, capturing specific chromatin domains facilitates the identification of previously unknown transcription factors interacting with these domains. Finally, in recent years, advances have been made toward identifying proteins that interact with a single genomic locus of interest. In this review, we highlight the power of chromatin proteomics approaches and how these provide complementary alternatives compared with conventional affinity purification methods. Furthermore, we discuss the biochemical challenges that should be addressed to consolidate and expand the role of chromatin proteomics as a key technology in the context of gene expression regulation and epigenetics research in health and disease.

Computational study of transcription factor binding sites

Romain Fernand Pietro Groux

Any living organism contains a whole set of instructions encoded as genes on the DNA. This set of instructions contains all the necessary information that the organism will ever need, from its development to a mature individual to environment specific responses. Since all these instructions are not needed at the same time, the gene expression needs to be regulated. Eukaryotic genomes are stored inside nuclei as chromatin. The chromatin is the association of DNA with dedicated storage proteins - the histones - and the necessary machinery to regulate and express genes (RNA polymerases or RNAPs). In the nuclei, histones are assembled into octamers around which are wrapped ~148bp of DNA. This structure is known as the nucleosome. The repetition of nucleosomes along the genome allows to drastically compact the genome, eventually allowing to fit it inside the nucleus. However, this comes at the cost of rendering the DNA sequence inaccessible to DNA readers, such as the RNAPs and transcription factors (TFs). TFs are a class of proteins that have the remarkable property of recognizing and binding specific DNA sequences. More striking, each TF can recognize a multitude of different - but similar - DNA sequences providing TFs with a wide sequence specificity range. Eventually, this allows the cell to recruit TFs at dedicated locations in the genome called regulatory elements (REs). The action of TFs at REs is crucial to gene expression. Indeed, TFs are involved in many processes such as the opening of the chromatin structure or the recruitment of RNAPs. However if TFs can influence the chromatin structure, the opposite is also true as histones impede TF binding on DNA. Thus the regulation of genes relies on a subtle and complex crosstalk between the chromatin and TFs. To better understand how TFs and chromatin interact together to regulate gene expression, I lead several projects prospecting TF binding specificity and the chromatin structure at REs in human. First, I used ENCODE next generation sequencing (NGS) data to explore how TF binding influences the nearby nucleosome organization and the propensity of some TFs to bind together. The results suggest that regular nucleosome arrays are found near all TFs. They also point out two special cases. When CTCF binds with the cohesin complex, it seems to drive the nucleosome organization, which is a unique feature among all TFs investigated. Additionally I present evidence supporting that EBF1 is a pioneer factor - a special class of TFs able to bind nucleosome. Secondly, I developed several clustering algorithms and software to partition genomic regions according to NGS data and/or on their DNA sequences. These methods allow to discover important trends, for instance different nucleosome architectures . I illustrated the usefulness of these methods for the study of chromatin accessibility data and the identification of REs. Thirdly, I participated to the assessment of SMiLE-seq, a new microfluidic device that generates TF specificity data. The creation of TF specificity models and their comparison with other publicly available models demonstrated the value of SMiLE-seq to study TF specificity. Finally, I participated in the development of a software that predicts TF binding sites. A careful benchmarking suggested that this software is - at the time of writing - the best available software in terms of speed while showing other performances similar to its competitors.

EPFL2020

Dissecting Gene Regulatory Networks Using Targeted Quantitative Proteomics

Jovan Simicevic

Gene regulatory networks control gene expression levels, and therefore play an essential role in mammalian development and function. Regulation of gene expression is the result of a complex interplay between DNA regulatory elements and their binding partners, known as transcription factors (TFs). Due to their vital role in development, intercellular signalling, cell cycle and disease development, elucidating the mechanisms by which TFs regulate gene expression is of crucial importance in the vast majority of biological processes. In particular, understanding how each TF contributes to the expression output of its respective target gene in space and time will help to elucidate how gene regulatory networks (GRNs) behave under different physiological or pathological conditions. Although extensive work has been accomplished in characterizing the key TFs involved in many biological processes, almost no quantitative information is currently available in the literature. To get a deep insight into the complex mechanisms underlying the regulation of gene expression, we need to acquire quantitative information, since TF abundance within the cell can be linked to their transcriptional capabilities. Such information would be of utmost importance to build accurate in silico quantitative DNA binding models that could predict and explain the particular properties of gene regulatory mechanisms. The quantification of TFs is a difficult task due their natural low abundance in cells, and their reliable detection is therefore very much dependent on the overall sensitivity of current technologies. In recent years, a new MS-based technology termed selected reaction monitoring (SRM) has gained popularity due to the targeted nature of its approach that allows the detection and quantification of proteins in complex samples with an exceptional sensitivity and specificity. I will show in this thesis, this approach is particularly well suited for targeting low abundant proteins such as TFs, which are otherwise difficult to identify with conventional shotgun proteomics experiments. Consequently, the main focus of my thesis research project entailed the development of an SRM-based platform aimed at quantifying TFs in absolute amounts based on in vitro protein expression during the terminal stage of adipogenesis, using the pre-adipocyte 3T3-L1 cell line. Interestingly, our initial efforts led to the creation of an atlas of TF-specific peptide data, which could be readily used for the design of quantitative assays. In the first phase, abundance measurements in terms of copies per cell were derived at precise differentiation time-points for two major adipogenic players, PPARγ and RXRα. In the second phase, we expanded the number of adipogenic TFs that can be monitored in one assay, allowing for the quantification of up to 10 TFs in one single, integrated SRM run. Such upscale increases the practical usefulness of the methodology while reducing the associated costs, and ultimately allows for non-negligible time-savings. The availability of absolute protein copy number data permitted us ultimately to examine the relationship between the number of genome-wide DNA binding events and TF molecules. We derived a quantitative DNA binding model that allowed the prediction of the number of PPARγ ChIP-seq binding events given its nuclear abundance, chromatin state, and DNA binding energetics. As such, we were able to explain the paradoxical observation of a significant increase in PPARγ binding sites despite a saturation in the number of PPARγ molecules. We thus demonstrate how TF abundance data can be modeled in conjunction with large-scale DNA occupancy and chromatin state data to further our understanding of gene regulatory mechanisms mediating cellular differentiation. We are now starting to build on our pioneering work to quantify in absolute terms key players of the entire, core adipogenic GRN, as such aiming to provide a quantitative explanation of the regulatory mechanisms at play during the terminal phase of adipocyte differentiation. Moreover, to increase the explicative power of our methodology and to alleviate the throughput limitation that comes with obtaining absolute protein measurements, we decided to perform copy-number estimates for a larger set of adipogenic TFs utilizing a modified version of our original approach. At the cost of a modest loss of accuracy, we are now aiming to develop a sensitive and robust methodology that will allow the quantification of entire GRNs at low cost and in a time-effective manner. This is consistent with the overall goal in life sciences or clinical research to improve our ability to accurately and reproducibly quantify entire pathways or biological networks to improve our systems understanding of biological processes.

EPFL2012

Phase specific transcriptional regulation of circadian clock and metabolism in mouse liver

Jonathan Aryeh Sobel

The molecular clock has been conserved from cyanobacteria to mammals and is believed to align behavioral and biochemical processes with the diurnal cycle. This cellular mechanism has been an advantage to increase the fitness of organisms through the ability to anticipate food availability or predator presence. Accumulating evidence has revealed that the circadian clock is intimately interconnected with the metabolic cycle. But, the nature of these interconnections is yet not clear at the transcriptional level, and the contribution of cis-regulatory modules has not been elucidated. Accessible chromatin regions of the genome are implicated in diverse processes, such as gene regulation through enhancers and promoters, insulation of genomic domains or alternative splicing. They allow cell-type specific programs that are controlled by tissue-specific transcription factors and chromatin modifiers, although tissue-specific regulation of the circadian clock remains unclear. Therefore, we compared genome-wide BMAL1 binding and chromatin accessibility in the liver and in NIH3T3 fibroblasts. Moreover, for the first time, our study explores the dynamics of accessible regions, histone 3 lysine 27 acetylation (H3K27ac) and RNA polymerase II (Pol II) every 4 hours over one day in mouse liver. In this study, we show that a substantial fraction of these accessible sites are oscillating during a diurnal cycle with a circadian period. We observed that these accessible regions are enriched in the proximity of actively transcribed genes, and that they are dynamically affected by the binding of transcription factors such as BMAL1. We investigated wild-type (WT) and Bmal1-/- genotypes, in night restricted feeding regimen and in Light-Dark (LD) cycle, to study the circadian clock regulatory network underlying diurnal transcription. Therefore, we applied a penalized generalized linear model to infer the activity of transcription factor binding motifs in oscillating accessible sites using Pol II loadings at the transcription start sites of nearby genes. We were able to recapitulate the known regulatory elements of the circadian clock, notably E-box, D-Box, and ROR-responsive elements (RRE) in the WT genotype. On the other hand, we found that Forkhead box (FOX), glucocorticoids responsive elements (GRE), and C-AMP Response Element (CRE) were the main contributors of the regulation of oscillating genes in Bmal1-/-. Finally, using a mixture model to detect footprints with a base pair resolution, we studied the dynamics of the accessibility overlapping E-box. Our last analysis suggested that BMAL1/CLOCK is binding on double E-boxes with a spacer of 6 or 7 bp in a hetero-tetramer configuration. A 3D structure model further supported this binding mode. In Summary, we used DNase I-seq and ChIP-seq of Pol II and H3K27ac to study the circadian chromatin landscape in a 4h time-resolved experimental design. We uncovered the underlying circadian transcriptional regulatory network and, we dissected the chromatin accessibility around BMAL1 binding sites at a base pair resolution, which led to an unappreciated mode of binding of BMAL1/CLOCK in a hetero-tetramer conformation on double E-boxes. Lastly, we found tissue-specific factors that might contribute to tissue-specific binding of BMAL1/CLOCK.

EPFL2016