Dissecting Gene Regulatory Networks Using Targeted Quantitative Proteomics

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

DNA-centered approaches to characterize regulatory protein–DNA interaction complexes

Gene regulation is mediated by site-specific DNA-binding proteins or transcription factors (TFs), which form protein complexes at regulatory loci either to activate or repress the expression of a target gene. The study of the dynamic properties of these regulatory DNA-binding complexes has so far been dominated by protein-centered methodologies, aiming to characterize the DNA-binding behavior of one specific protein at a time. With the emerging evidence for a role of DNA in allosterically influencing DNA-binding protein complex formation, there is renewed interest in DNA-centered approaches to capture protein complexes on defined regulatory loci and to correlate changes in their composition with alterations in target gene expression. In this review, we present the current state-of-the-art in such DNA-centered approaches and evaluate recent technological improvements in the purification as well as in the identification of regulatory DNA-binding protein complexes within or outside their biological context. Finally, we suggest possible areas of improvement and assess the putative impact of DNA-centered methodologies on the gene regulation field for the forthcoming years

Transcription factor proteomics - Tools, applications, and challenges

Transcription factors (TFs) are a family of DNA-binding proteins whose gene regulatory capabilities are of vital importance in defining the molecular state of a cell. Despite their biological significance, our understanding of TF behavior and function is still limited. This is because we have so far mostly relied on gene expression data to approximate TF protein levels given that the latter information has been notoriously difficult to obtain due to the relatively low expression levels of many TFs. However, significant advances in mass spectrometry technologies combined with the development of sensitive methodologies aimed at detecting TFs are now allowing a transition from a predominantly qualitative to a quantitative protein landscape. Such a paradigm shift is expected to unravel dynamic aspects of TF function, potentially linking TF copy number fluctuations in cells with specific regulatory functions. This in turn may provide novel insights into the regulatory mechanisms underlying a wide range of fundamental and disease-related biological processes. In this review, we will present the latest advances in mass spectrometry-based TF proteomics and describe novel strategies tailored around the quantification of this important family of DNA-binding proteins

A yeast one-hybrid and microfluidics-based pipeline to map mammalian gene regulatory networks

The comprehensive mapping of gene promoters and enhancers has significantly improved our understanding of how the mammalian regulatory genome is organized. An important challenge is to elucidate how these regulatory elements contribute to gene expression by identifying their trans-regulatory inputs. Here, we present the generation of a mouse-specific transcription factor (TF) open-reading frame clone library and its implementation in yeast one-hybrid assays to enable large-scale protein–DNA interaction detection with mouse regulatory elements. Once specific interactions are identified, we then use a microfluidics-based method to validate and precisely map them within the respective DNA sequences. Using well-described regulatory elements as well as orphan enhancers, we show that this cross-platform pipeline characterizes known and uncovers many novel TF–DNA interactions. In addition, we provide evidence that several of these novel interactions are relevant in vivo and aid in elucidating the regulatory architecture of enhancers

A mammalian transcription factor-specific peptide repository for targeted proteomics

Site-specific transcription factors (TFs) play an essential role in mammalian development and function as they are vital for the majority of cellular processes. Despite their biological importance, TF proteomic data is scarce in the literature, likely due to difficulties in detecting peptides as the abundance of TFs in cells tends to be low. In recent years, significant improvements in MS-based technologies in terms of sensitivity and specificity have increased the interest in developing quantitative methodologies specifically targeting relatively lowly abundant proteins such as TFs in mammalian models. Such efforts would be greatly aided by the availability of TF peptide-specific information as such data would not only enable improvements in speed and accuracy of protein identifications, but also ameliorate cross-comparisons of quantitative proteomics data and allow for a more efficient development of targeted proteomics assays. However, to date, no comprehensive TF proteotypic peptide database has been developed. To address this evident lack of TF peptide data in public repositories, we are generating a comprehensive, experimentally derived TF proteotypic peptide spectral library dataset based on in vitro protein expression. Our library currently contains peptide information for 89 TFs and this number is set to increase in the near future. All MS data have been deposited in the ProteomeXchange with identifier PXD001212 (http://proteomecentral.proteomexchange.org/dataset/PXD001212)

Imaging mass spectrometry using peptide isoelectric focusing

Imaging Mass Spectrometry (IMS) has emerged as a powerful technique in the field of proteomics. The use of Immobilized pH Gradient-IsoElectric Focusing (IPG-IEF) is also a new trend, as the first dimension of separation, in shotgun proteomics. We report a combination of these two outstanding technologies. This approach is based on the separation of shotgun-produced peptides by IPG-IEF. The peptides are then transferred by capillarity to a capture membrane, which is then scanned by the mass spectrometer to generate MS images. This high-throughput methodology allows a preview of the sample to be obtained in a single day. We report the application of this new pipeline for differential comparison of the membrane proteome of two different strains of Staphylococcus aureus bacteria in a proof-of-principle experiment

Acclimation strategies of the green alga Chlorella vulgaris to different light regimes revealed by physiological and comparative proteomic analyses

Acclimation to different light regimes is at the basis of survival for photosynthetic organisms, regardless of their evolutionary origin. Previous research efforts largely focused on acclimation events occurring at the level of the photosynthetic apparatus and often highlighted species-specific mechanisms. Here, we investigated the consequences of acclimation to different irradiances in Chlorella vulgaris, a green alga that is one of the most promising species for industrial application, focusing on both photosynthetic and mitochondrial activities. Moreover, proteomic analysis of cells acclimated to high light (HL) or low light (LL) allowed identification of the main targets of acclimation in terms of differentially expressed proteins. The results obtained demonstrate photosynthetic adaptation to HL versus LL that was only partially consistent with previous findings in Chlamydomonas reinhardtii, a model organism for green algae, but in many cases similar to vascular plant acclimation events. Increased mitochondrial respiration measured in HL-acclimated cells mainly relied on alternative oxidative pathway dissipating the excessive reducing power produced due to enhanced carbon flow. Finally, proteins involved in cell metabolism, intracellular transport, gene expression, and signaling-including a heliorhodopsin homolog-were identified as strongly differentially expressed in HL versus LL, suggesting their key roles in acclimation to different light regimes.Acclimation to different irradiances was investigated in the fast-growing green alga Chlorella vulgaris, focusing on photosynthetic and mitochondrial activities and identifying differentially expressed proteins including transcription factors and signaling components

Absolute quantification of transcription factors during cellular differentiation using multiplexed targeted proteomics

The cellular abundance of transcription factors (TFs) is an important determinant of their regulatory activities. Deriving TF copy numbers is therefore crucial to understanding how these proteins control gene expression. We describe a sensitive selected reaction monitoring–based mass spectrometry assay that allowed us to determine the copy numbers of up to ten proteins simultaneously. We applied this approach to profile the absolute levels of key TFs, including PPARɣ and RXRα, during terminal differentiation of mouse 3T3-L1 pre-adipocytes. Our analyses revealed that individual TF abundance differs dramatically (from ~250 to >300,000 copies per nucleus) and that their dynamic range during differentiation can vary up to fivefold. We also formulated a DNnA binding model for PPARɣ based on TF copy number, binding energetics and local chromatin state. This model explains the increase in PPARɣ binding sites during the final differentiation stage that occurs despite a concurrent saturation in PPARɣ copy number