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  • Periodic Report Summary 1 - EXPRESSION DYNAMICS (Orchestrating the Transcriptome and Proteome in Time and Space: Quantitative Modeling of Protein Production, Degradation and Localization in Mammalian Systems)


Project reference: 330665
Funded under: FP7-PEOPLE

Periodic Report Summary 1 - EXPRESSION DYNAMICS (Orchestrating the Transcriptome and Proteome in Time and Space: Quantitative Modeling of Protein Production, Degradation and Localization in Mammalian Systems)

During my outgoing phase in the Regev lab, my primary and most immediate goal was to systematically study the dynamics of gene expression control of mammalian cells, using the model system of bone marrow-derived dendritic cells (DCs) responding to lipopolysaccharide (LPS). First, I wanted to evaluate the contribution of protein production and degradation to changes in overall protein levels following LPS stimulation. Second, I planned integrate the generated data with data about the dynamics of the RNA life cycle to build an unprecedented quantitative genome-scale model of the temporal dynamics of gene expression, from transcription to protein degradation. Third, I wanted combine ribosomal footprinting with proteomics to study the translational potential of short non canonical ORFs (sncORFs) encoded on putative lincRNAs. Finally, I wanted to use refined measurements to monitor candidate key components that may affect the immune response of DCs and will use systematic perturbation followed by signature scale monitoring to validate and refine their roles. All of these goals have been met and the most important publications are attached. Here is a summary of the scientific work addressing the originally stated objectives:

I developed an integrated experimental and computational strategy to quantitatively assess how protein levels are maintained in the context of a dynamic response and applied it to the model response of DCs stimulated with LPS. I combined measurements of protein production and degradation and mRNA dynamics to build a quantitative genomic model of the differential regulation of gene expression in LPS-stimulated DCs. Changes in mRNA abundance played a dominant role in determining most dynamic fold changes in protein levels. Conversely, the preexisting proteome of proteins performing basic cellular functions was remodeled primarily through changes in protein production or degradation, accounting for over half of the absolute change in protein molecules in the cell. My results supported a model where the induction of novel cellular functions is primarily driven through transcriptional changes, whereas regulation of protein production or degradation updates the levels of preexisting functions as required for an activated state (Jovanovic et al., Science, 2015). Overall, the novel approach I developed for building quantitative genome-scale models of the temporal dynamics of protein expression is broadly applicable to other dynamic systems.
Although this genome-scale model provides significant insight about the temporal dynamics of gene expression and identifies genes and groups of genes regulated by similar modes of actions, it does not itself yet provide information about which genes regulate these expression changes. In an ideal case we would obtain such a list of candidate regulators in an unbiased and orthogonal approach. In typical model organisms, such as yeast, worm, or fly, genetic screening provides such an approach. However, in primary mammalian cells this is rather challenging and although shRNAs, haploid cell lines and recently CRISPR has been used for genome wide screens, these screens were mainly based on strong selection such as lethality or growth, and not yet applied to primary, short lived cells like DCs. Moreover, in many dynamic responses such strong selection does not exist and key regulators affect only a certain aspect of the studied response. Therefore, a genome wide screen in mammalian cells that could identify regulators that affect for example the expression of a marker of the studied response would be an extreme advantage.
I therefore adapted new CRISPR technology to develop a marker based genome-wide CRISPR screen in mouse primary bone marrow DCs using Cas-9 expressing transgenic mice. I stimulated DCs infected with a genome wide library of lentiviruses, containing 6 guide RNAs per mouse gene (total of ~ 126,000 guides), with LPS, and monitored their responses by intra-cellular staining for the anti-inflammatory cytokine TNF-α, an early response marker of LPS stimulation. Cells that failed to respond to LPS (i.e., caused by a mutation in a positive regulator) or that responded strongly (i.e., caused by a mutation in a negative regulator) were isolated by Fluorescence Activated Cell Sorting (FACS) and guides expressed in these cells were detected by deep sequencing. We found many of the known regulators of Tlr4 signaling, as well as dozens of previously unknown candidates that we validated. By measuring protein markers and mRNA profiles in DCs that are deficient in known or candidate regulators, we classified the genes into functional modules with distinct effects on the canonical responses to LPS. My findings uncover new facets of innate immune circuits in primary cells and provide a genetic approach for dissection of mammalian cell circuits (Parnas*, Jovanovic*, Eisenhaure*, et al., Cell, 2015, *contributed equally). This marker based genome wide screen in primary mammalian cells will allow me to apply unbiased genetic screening in nearly every available system of interest as long as I can sort for the expression of a marker of interest.
Finally, to study the translational potential of short non canonical ORFs (sncORFs) encoded on putative lincRNAs, we, in collaboration with Jonathan Weissman’s group, integrated proteomics and ribosome profiling data to predict with high confidence protein coding genes, which led to a co-author publication. We developed an experimental and analytical framework, for systematic identification and quantification of translation. We identified thousands of novel ORFs, including micropeptides and variants of known proteins, that bear the hallmarks of canonical translation and exhibit translation levels and dynamics comparable to that of annotated ORFs (Fields*, Rodriguez*, Jovanovic, et al., Molecular Cell, 2015, *contributed equally).

The essential skills, methods and knowledge gained during my outgoing phase (see above) provides now the “blueprint” to systematically study gene expression in hippocampal neurons upon synaptic stimulation during my returning phase in the Schuman lab. In addition I will look at gene expression control in somata and dendrites separately, thus considering both spatial and temporal regulation of translation in mammalian cells.

This systems biology project complies perfectly with specific research objectives emphasized by the European Commission (EC). Systems biology has become one major focus to enhance the research excellence of the ERA. The project is clearly in line with cutting edge projects in systems biology, as it quantifies, models and understands the complexity of the dynamic changes induced in two disease related mammalian cell system upon perturbation. The work so far pushed the limits of the most advanced ‘omics technologies in order to generate large scale, high quality data sets that provided the basis for sophisticated modeling approaches in order to describe quantitatively the contributions of the fundamental processes of gene expression to the final protein levels. Results provided by the project are: (1) a global quantitative model of gene expression dynamics of LPS stimulated DCs; (2) the identification and validation of new key regulators and therefore therapeutic targets of the immune response of DCs, cells critical for diseases such as cancer and autoimmunity; (3) proving the feasibility of such an extensive systems approach in a complex system and therefore providing the blueprint for further systems approaches (4) applying this blueprint to globally model temporal and spatial gene expression dynamics of stimulated neurons; (5) identifying new potential key regulators of memory formation and associated neurological diseases.
The economic usefulness of the already established methods is also exemplified by the patent application that is based on the established marker based genome wide CRISPER/Cas9 screen.

Patent Application:


Berken, Antje (Scientific Coordinator)
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Life Sciences
Record Number: 182174 / Last updated on: 2016-05-24
Information source: SESAM